DOI: 10.3897/jucs.208033

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the seventh regular issue of 2026. In this issue, 6 papers by 19 authors from 7 countries - Austria, Brazil, Egypt, Germany, India, USA, Vietnam - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.As always, I would like to thank all the authors for their sound research and the editorial board members and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the consistently high number of user accesses and PDF downloads. These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal.In the seventh regular issue, I am very pleased to present the following 6 accepted articles: Sang Suh and Numery Zaber from the USA address in their manuscript the limitations of traditional keyword-based resume screening by proposing an AI-powered framework that leverages contextual sentence embeddings, machine learning, and explainable AI to better capture the semantic relationship between resumes and job descriptions. Experimental results demonstrate that the proposed approach achieves high classification performance while providing transparent and interpretable recommendations for more effective recruitment decisions.Christian Schlager and Atif Mashkoor from Austria discuss in their research the challenges of time-consuming and costly separate assessments for ASPICE and ASPICE for Cybersecurity in the automotive industry by proposing a unified integrated assessment approach that systematically maps related processes and work products across the two models and schedules them closely together for parallel evaluation. In a real-world case study with two projects, this method achieved a measurable reduction in total assessment time (approximately 1.5 days from the typical 8.5 days) while preserving rigor, quality, and compliance, offering organizations greater efficiency with minimal additional overhead.In their collaborative research between Vietnam and Germany, Dung Hai Dinh, Quan Nguyen Minh Tran, Quang Huan Dong, and Nicole Ondrusch conduct research on predictive modeling in project management, developing and validating machine learning models to forecast issue closures in the open-source TensorFlow project using data collected from GitHub. The findings suggest that the Lasso regression model, enhanced with advanced feature engineering, achieves the best predictive performance, while time-aware validation indicates the need for further refinement of temporal evaluation.Vinicius Eduardo Ferreira, João Pedro Vidotti Cesaro, Gabriela Rosa, Edson Oliveira Jr, Gislaine Camila Lapasini Leal, and Renato Balancieri from Brazil investigate in their research the 2024 CrowdStrike Falcon blackout through an integrative multivocal literature review that combines academic and gray literature to analyze its impacts, technical root causes, and lessons learned for software engineering and cybersecurity. The study reveals that inadequate validation processes, weaknesses in update mechanisms, and organizational shortcomings amplified the incident's severity and provides evidence-based recommendations to strengthen software quality assurance, update governance, and the resilience of critical digital infrastructures.Fatmaelzahra Hamdi, Ramadan Moawad, and Amr Mansour Mohsen from Egypt conduct a systematic literature review of Automated Program Repair (APR) with Large Language Models (LLMs) to examine the recent advancements, research trends, evaluation practices, and challenges of this promising area. This review provides a comprehensive review of existing LLM-based APR approaches, points out key research gaps and evaluation challenges, and builds a foundation for future research toward more reliable and effective automated program repair.Sangeetha E and Deny J from India report on the challenges of secure, energy-efficient routing in 6G edge networks by proposing the Energy Optimized Network Route Cluster Bandwidth (EONRCB) framework, which uses Priority Cycle Tags and a Service Level Route Count Rollback Node Aggregator (SLR-CRNA) for recursive, priority-based scheduling. The results show that EONRCB outperforms existing routing techniques, achieving higher throughput, packet delivery ratio, and network lifetime, along with a 20% reduction in energy consumption.Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.203799

Authors: Christian Gütl

Abstract: Dear Readers, I am very happy to announce the sixth regular issue of 2026. In this issue, 6 articles by 16 authors from 6 countries (Algeria, Austria, Brazil, Finland, Spain, Türkiye) cover a variety of topical research aspects in computer science. Allow me to express my appreciation to all the authors for their sound research work and to thank the editorial board and guest reviewers for their extremely valuable reviews and suggestions for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the KOALA initiative, helps to maintain the quality of our journal.In the ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal.In the sixth regular issue, I am very pleased to introduce the following six accepted articles:Gema Gutierrez, Moisés Rodríguez, Javier Garzás, and Mario Piattini from Spain address the problem that organizations require high-quality, trustworthy data for digital transformation and AI but often lack structured methods aligned with business goals. Their article proposes OKR4DQ, integrating ISO/IEC 25012-based assessment with OKRs to drive targeted improvements. A real-world case study demonstrates measurable gains in key data quality dimensions using OKR4DQ, showing its effectiveness in improving data reliability while aligning quality initiatives with business performance objectives.Gerhard Jurasek from Austria discusses the results of a longitudinal research on benefits realization for the implementation of ERP-systems based on a mixed methods approach. Additionally, a concept of benefits controlling is proposed to support benefits realization over the lifetime of an ERP-system in order to exploit benefits ideally without a time lag and to a high extent.Jefferson Martins, Rodrigo Andrade, and Luis F. Alves Pereira from Brazil evaluate in their study whether LLM-generated implementations of ten classical algorithms, such as Heap Sort and Binary Search, in Java, Python, and C are correct and resource-efficient. Five open models and six code assistant applications are assessed against human-written code from Rosetta Code and The Algorithms repositories, using Intel's RAPL to measure energy consumption, memory usage, and execution time. The findings show that LLMs generate correct implementations in over 97% of cases and tend to outperform human-written code in energy efficiency, though no single model is consistently superior across all metrics, with human-written code still proving more memory-efficient in Python and faster in Java.Davut Çulha from Turkey investigates in this article the internal conceptual organization of LLMs by introducing a prompt engineering-based method that identifies maximally divergent conceptual regions within latent conceptual spaces using a geometric conceptual spaces framework. The experimental evaluation across various LLMs revealed substantial differences in conceptual diversity, suggesting that the proposed metric can provide complementary insights into the factual knowledge organization of LLMs.Youssouf Abda, Zohra Mehenaoui, and Yacine Lafifi from Algeria propose in their research an enhanced FSLSM-based approach for analyzing and personalizing online learning content through the comparison of learners’ behavioral profiles and instructional content characteristics using a fuzzy logic model. The experimental results demonstrated that the proposed adaptive approach significantly improved learners’ cognitive progression and enhanced the alignment between pedagogical content and individual learning preferences.In a collaborative work between researchers from Brazil and Finland, Edna Dias Canedo, Gabriel Matheus da Rocha de Oliveira, Fabiana Freitas Mendes, and Heloise Acco Tives Bedin investigate in their research the growing challenge of selecting appropriate test generation tools in increasingly complex software development environments by combining a Multivocal Literature Review with a survey of 87 software practitioners to identify, compare, and classify testing tools used in academia and industry. The study contributes a practical reference guide for software practitioners and reveals a significant gap between academic research and industrial adoption, highlighting that practitioners prioritize factors such as integration, traceability, visibility, and maintainability when choosing testing tools. Enjoy Reading! Best regards, Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.151158

Authors: Vívian Santos Marques Severino, Lílian Santos Marques Severino, Edna Dias Canedo, Gilmar dos Santos Marques

Abstract: The article examines predictions made at the end of the 20th century about contemporary society, assessing which have been confirmed or refuted at the start of the 21st century, and explores the impact of the first phase of Artificial Intelligence (AI). Considering contributions from renowned authors such as Bauman, Castells, Kahneman, Nicolelis, and Acemoglu, the study investigates forecasts related to liquid modernity, network society, information era, economic power concentration, and technological advances. The research aims to understand how these predictions influence current society and its policies through a comparative analysis of documents and literature drawing parallels between past forecasts and current developments. Among the findings, Bauman's prediction about volatility and freedom in liquid modernity is confirmed, noticeable in work flexibility and dissatisfaction with consumption. Castells accurately predicted organizational decentralization and global collaboration, despite persistent digital inequality. Rifkin forewarned of job reductions due to automation continuing to face challenges in the current market. Schwab emphasized the Internet of Things (IoT) impact, increasing economic inequality. Chomsky predicted the intensification of corporate power and media manipulation; Nicolelis highlighted the therapeutic applicability of brain-machine interfaces, though limited by ethical issues. Harari emphasized the transformative impact of AI and biotechnology, still holding authoritarian nuances. Acemoglu and Robinson emphasized the importance of inclusive institutions in preventing stagnation. The research highlights the need for ethical governance and regulation of technological innovations, emphasizing the urgency of evolving policies to ensure social equity in the era of technological advancement.

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DOI: 10.3897/jucs.199478

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the fifth regular issue of 2026. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the KOALA consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research.We are interested in receiving high-quality proposals for special issues on new topics and emerging trends; in particular strong international collaborations on current topics are highly welcome.In this regular issue, I am very pleased to introduce 4 papers by 17 authors from 3 countries: Brazil, China, Türkiye.Ozan Can Acar and Hürevren Kılıç from Türkiye investigate in their research whether competition among goal-driven agents can enhance the quality of pseudo-random number generation and proposes an agent-driven gamification framework built on a two-dimensional linear cellular automata environment. NIST test results and statistical analyses demonstrate that incorporating rational agents with conflicting objectives improves statistical randomness, with most configurations achieving near-optimal benchmark scores and outperforming environment-only setups.Vívian Santos Marques Severino, Lílian Santos Marques Severino, Edna Dias Canedo, and Gilmar dos Santos Marques from Brazil analyze in their research predictions made at the end of the 20th century regarding social, economic, and technological transformations of the 21st century—particularly in the early stages of artificial intelligence—through a qualitative, exploratory, and comparative approach based on bibliographical and documentary research. It verifies which theses from thinkers like Bauman, Castells, Rifkin, Schwab, Chomsky, Nicolelis, Harari, Kahneman, and Acemoglu were confirmed or refuted globally and in Brazil during the first quarter of the 21st century, offering insights for innovative policies, strategies, and future studies on trends like automation, inequality, and AI governance.Guohui Liu, Huan Zhang, Jianghong Li, Yanling Zhao, and Xin Liu from China propose in their article an enhanced Wavelet-TimesNet model that integrates adaptive wavelet transform and multi-scale residual networks. By dynamically adjusting the parameters of wavelet basis functions, constructing multi-scale residual networks, and introducing an adaptive wavelet attention mechanism, the model can effectively suppress noise interference and accurately capture both local detailed features and global variation trends of photovoltaic power sequences. Last but not least, Kevin Lima, Alex Roehrs, Cristiano André da Costa, Rodrigo da Rosa Righi, Jorge Luis Victória Barbosa, and Kleinner Silva Farias de Oliveira from Brazil focus their research on noninvasive digestive health monitoring by proposing the Mathematical Formula for Systematic Digestive Sounds (MFSDS), an approach that converts abdominal audio signals into mathematical formulas for automated analysis using IoT, signal processing, and artificial intelligence. The study shows that MFSDS can identify recurring patterns in digestive sounds, achieving similarity rates between 50% and 67% across different experimental settings, and highlights the potential of mathematical modeling as a novel direction for real-time gastrointestinal monitoring and preventive healthcare.Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.196586

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye - cover a great variety of topical aspects of computer science.In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the increasing number of accesses and PDF downloads.In the fourth regular issue, I am very pleased to introduce the following 6 accepted articles:Wicus J. van der Linden, Trienko L. Grobler, and Lynette van Zijl from South Africa investigate in their article how class imbalance and adverse imaging conditions affect optical Braille recognition (OBR), by comparing the current standard multiclass character‑based models with multilabel, dot‑based classification models, supported by a novel resampling strategy that exploits Braille symmetry. Empirical results confirm that the proposed framework achieves more robust and generalized performance under diverse conditions, positioning it as a new standard modelling framework for multilingual OBR systems.Yelda Fırat, Yılmaz Kılıçaslan, Hüseyin Ali Sarıkaya, and Murat Kaan Yılmaz from Türkiye focus in their research on the need for scalable and objective early screening of Autism Spectrum Disorder (ASD) by applying a hybrid deep learning approach - integrating Convolutional Neural Networks, Bidirectional Long Short-Term Memory, and attention mechanisms - to detect motor biomarkers from children's natural home video recordings. The findings demonstrate that the model achieves over 97% accuracy on controlled datasets and over 83% on real-world public videos, offering a robust, clinically applicable screening tool that overcomes the limitations of artificial laboratory environments.Sava Stanisic, Borislav Djordjevic, Branislav Belotic, Olga Ristic, Ivan Tot, Kristina Zivanovic, and Dimitrije Kolasinac from Republic of Serbia discuss in their article the challenge of minimizing end-to-end latency in dynamic, heterogeneous Kubernetes clusters by proposing a reinforcement learning-based orchestration framework that employs a deep Q-network (DQN) agent to make scheduling and migration decisions. The proposed approach achieves up to 25–32% reduction in average latency compared to default Kubernetes schedulers, demonstrating superior load balancing and effective adaptation to workload variability through learned placement policies.In a collaborative effort between researchers from México and Colombia, Mirna Muñoz, Gabriel Garcia-Mireles, Jezreel Mejia, Yadira Quiñonez, Gloria Gasca-Hurtado, and Adriana Peña investigate in their research how Software Engineering (SE) provides methodological support throughout the Machine Learning (ML) development lifecycle. This study conducts a Systematic Mapping Study that examines current SE methodologies for ML-based systems and identifies gaps across lifecycle phases. The results indicate a significant focus on testing operations, with insufficient software engineering support for other phases, underscoring the need for more comprehensive frameworks, procedures, and standards to improve the stability, maintainability, and quality of machine learning-based software.Rabia Tintin and Sait Can Yucebas from Türkiye report on the study addressing the limitations of existing sentiment analysis approaches for the Turkish language by proposing Duygu-Turk, a context-aware and linguistically enriched deep learning framework based on Plutchik’s Wheel of Emotions and non-monotonic logic. The results demonstrate that the proposed model significantly outperforms state-of-the-art transformer-based models by achieving high accuracy in both polarity and fine-grained multi-class emotion classification, highlighting its effectiveness for morphologically rich and low-resource languages.And last but not least, Dimitrios Psilias, Athanasios Milidonis, and Ioannis Voyiatzis from Greece propose in their article an FPGA-based architecture for the combined secure transmission of UAVs' telemetry and high-definition video data using a single AES-128 module. Experimental results show that using this approach, a high throughput of 25.6 Gbps is achieved, without having significant overheads in execution delay and power consumption.Enjoy Reading! Best wishes,Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.139707

Authors: Chaimae Moumouh, José A. García-Berná, Begoña Moros, Juan M. Carrillo de Gea, Mohamed Yassin Chkouri, José L. Fernández-Alemán

Abstract: The impact of technology on improving health and well-being of individuals is remarkable. EHealth boosts the transition from paper-based health records to Electronic Health Records (EHRs). The use of EHRs can lead to improve quality of care, costs and time. In eHealth systems the health data is stored in digital form, and can be exchanged or accessed securely by authorised users. It is worth noting that medical data is considered very confidential information. However, the privacy and security of medical data remains a critical issue. Any leak or breach in security can lead to serious privacy damages for patients. Despite the safeguards, training courses and the consciousness on keeping data safe, the human error continues to be a problem. The main purpose of this paper is to present a bibliometric overview on the academic research related to privacy and security in EHRs. For this purpose, the papers of this study were searched in the Scopus. A period of 24 years was considered for selecting the papers. The information gathered in the database identified a total of 3,077 publications. Some key findings revealed that in the year 2015 the highest number of publications was produced. The Harvard Medical School was the most prolific institution with 2.44% papers from the total number of publications. A total of 97.21% of the documents were written in English. Finally, the results provided in this manuscript allowed us to make a picture on the current relevance in academic literature on privacy and security in EHRs.

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DOI: 10.3897/jucs.192427

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the third regular issue of 2026. I would like to thank all the authors for their sound research and the editorial board for the extremely valuable reviews and suggestions for improvement. These contributions together with the support of the community and the generous support of the KOALA initiative enable us to run our journal and maintain its quality.I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to present 6 accepted papers by 27 authors from 6 countries: Brazil, India, Kingdom of Saudi Arabia, Morocco, Spain and Sri Lanka.In a collaborative effort between researchers from Morocco and Spain, Chaimae Moumouh, José A. García-Berná, Begoña Moros, Juan M. Carrillo de Gea, Mohamed Y. Chkouri, and José L. Fernández-Alemán address in their paper the critical challenges of privacy and security in Electronic Health Records (EHRs) by presenting a comprehensive bibliometric analysis of academic research in this field based on 3,077 publications indexed in Scopus over a 24-year period. The findings identify major publication trends, leading institutions, dominant languages, and the year with the highest research output, highlighting the growing academic relevance of EHR privacy and security and providing a structured overview of the field’s development.Jorge Arthur Schneider Aranda, Ricardo dos Santos Costa, Vitor Werner de Vargas, Paulo Ricardo da Silva Pereira, Jorge Luis Victória Barbosa, Marcelo Pinto Vianna, and Eleandro Luis Marques da Silva from Brazil research in their work the challenge of efficiently classifying electrical metrics in power distribution networks by proposing OntoFreya, an ontology-based model that applies semantic reasoning to interpret voltage, current, and contextual data. The results demonstrate that OntoFreya enables precise and scalable automatic classification, reducing specialist analysis effort while supporting context-aware inference across large datasets.Ayodhya Liyanage and Anuradha Mahasinghe from Sri Lanka investigate in their paper the lack of well‑posed state transition diagrams for basic quantum gates in the standard Quantum Turing Machine model by constructing rigorous diagrams for a universal quantum gate set. The results demonstrate that these diagrams satisfy the postulates of quantum mechanics, thereby providing a universal, fault‑tolerant basis for simulating quantum computations within the QTM framework.Moulay Youssef Ichahane, Noureddine Assad, and Hassan Ouahmane from Morocco present in their work a multimodal diagnostic framework that combines case-based reasoning with deep learning to address the complexity and heterogeneity of rheumatoid arthritis diagnosis, integrating electronic health record data with deep learning–based analysis of chest X-ray images. Experimental evaluations show that the proposed approach significantly improves diagnostic accuracy and robustness compared to conventional CNN- and KNN-based methods, highlighting the framework’s relevance for advanced computer-aided medical diagnosis.Abdelhady Naguib and Abdulaziz Shehab from Saudi Arabia tackle in their article the problem of robust and energy-efficient localization in obstacle-rich wireless sensor networks by introducing a deterministic mobile anchor trajectory model, that integrates square spiral coverage with lightweight obstacle avoidance. A range of simulations demonstrate that the proposed approach achieves superior localization accuracy, higher node coverage, and reduced trajectory length compared to state-of-the-art path planning schemes.In a collaborative research between Saudi Arabia and India, Abdulhadi Altherwi, Md. Mottahir Alam, Mastoor M. Abushaega, Abdulmajeed Azyabi, Ahmed Hamzi, Shabbir Hassan and Asif Irshad Khan research the challenge of accurate and computationally efficient forecasting in Hybrid Renewable Energy Systems by proposing a hybrid Grey Wolf Optimization–Deep Belief Network (GWO-DBN) framework that integrates metaheuristic feature selection with deep learning. Validation on two real-world datasets demonstrates reduced prediction error and computational time, achieving high forecasting accuracy and improved energy efficiency for smart grid applications.Enjoy Reading!Warm regards,Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.189356

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the second regular issue of 2026. I would like to thank all the authors for their sound research and the editorial board and guest reviewers for the extremely valuable reviews and suggestions for improvement. These contributions together with the support of the community enable us to run our journal and maintain its quality. I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to present 6 accepted papers by 20 authors from 6 countries: Brazil, Germany, India, North Macedonia, Saudi Arabia, Türkiye. Gustavo Lazarotto Schroeder, Wesllei Felipe Heckler, Rosemary Francisco, and Jorge Luis Victória Barbosa from Brazil address in their manuscript the growing problem of problematic smartphone use (PSU) by proposing OntoKratos, an ontology-based approach that models contextual, demographic, and mental health information to identify PSU and recommend personalized interventions through semantic reasoning. The research contributes a formal and reusable ontology with SWRL-based inference mechanisms, demonstrating through simulated data that OntoKratos effectively classifies PSU states, infers risk factors, and generates evidence-based intervention suggestions. In a collaborative research between colleagues from North Macedonia and Germany, Aleksandar Velinov, Aleksandra Mileva, Simon Volpert, Sebastian Zillien, and Steffen Wendzel look into the steganographic analysis of different network protocols which becomes a necessary part of their security evaluation, to prevent their abuse as carriers of hidden messages. In this manuscript, twenty novel covert channels are identified in QUIC, with an accent on their transmission rate, undetectability, and robustness, suggested countermeasures, and one implemented covert channel as a proof-of-concept.Hanan Hafiz and Maher Alharby from Saudi Arabia introduce in their work a study that aims to develop efficient machine learning models for detecting DDoS attacks in cloud environments by addressing challenges related to multi-tenant traffic patterns and virtualized infrastructure constraints. The main contributions of this study include binary and multiclass DDoS classification with feature selection, evaluation of model performance and computational efficiency, and mitigation of data imbalance using oversampling techniques.Kausthav Pratim Kalita, Debojit Boro, and Dhruba Kumar Bhattacharyya from India investigate in their research the issue that big data platforms face limitations in centralized access control despite their distributed architecture and propose integrating blockchain technology using smart contracts to enable secure and controlled access to cluster resources. Through Ethereum-based simulations, the study demonstrates that appropriate indexing and hashing mechanisms can effectively enforce access control while maintaining acceptable execution cost and execution time.Gamze Cabadag, Ali Degirmenci, and Omer Karal from Türkiye research in their work FFT-based radar frequency estimation errors arising from non-integer FFT bin alignment and evaluate twelve interpolation techniques under Gaussian and Laplace noise over varying SNRs and bandwidths. Monte Carlo analyses combined with FLOPs-based complexity evaluation show that the improved Quinn method achieves the highest estimation accuracy for both noise types, while simpler methods offer lower computational cost with reduced performance.Last but not least, Mashael M. Alsulami, Kholoud Althobaiti and Haneen Algethami from Saudi Arabia address in their paper the limitation of traditional job recommendation systems by introducing JobMatcher, a multi-layered framework that combines content-based filtering-KNN, and large language model–based evaluation to better capture career context and progression. The findings show that utilizing ChatGPT as a refinement layer improves alignment with expert judgments, resulting in more relevant and realistic job recommendations.Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.185149

Authors: Christian Gütl

Abstract: Dear Readers,First of all, I would like to wish you all the best for the New Year! It is with great pleasure that I welcome you to our first regular issue in 2026.Looking back on the past year, we have further increased our visibility and taken steps to fully comply with the Diamond Open Content Standard and align our journal with the KOALA requirements. Thanks to the combined efforts of the Pensoft team and the J.UCS publishing team, we are listed and indexed in more than 40 indexing services worldwide, including DOAJ, Web of Science, and Scopus. The increased visibility and presence on social media have also led to a further increase in page views and article downloads.With around 340,000 unique views, reader interest in J.UCS publications increased by almost 200% compared to the previous year. We can also look back on an increasing number of submitted articles and special issue proposals. This interest is reflected in a notable impact factor with a Scopus Cite Score of 2.5 and a Web of Science Journal Impact Factor of 0.9, both metrics have improved slightly since last year. We proudly look back on a total of 14 issues – 12 regular and 2 special issues – with 70 articles by 247 authors from 34 countries on novel aspects of various topics in computer science. The acceptance rate has fallen to below 6 per cent.These great achievements were only possible thanks to the commitment and interest of the community, the valuable support of the Editorial Board and the financial supporters of J.UCS through the KOALA Computer Science Cluster from TIB - Leibniz Information Centre for Science and Technology University Library, Germany.In 2025, we welcomed 10 new members to the Editorial Board, bringing our total number of Editorial Board members to 222. We would also like to gratefully acknowledge the support of 78 guest reviewers over the past year.In particular, I would like to thank Dr. Ulrike Krießmann from the Library of the Graz University of Technology, the TIB - Leibniz Information Centre for Science and Technology University Library in Germany, and the Institute of Human-Centred Computing (HCC) from TU Graz for their financial support.I would also like to thank the J.UCS team, Johanna Zeisberg for taking care of the publication process, David Kerschbaumer for his social media support, and Sebastian Gürtl and Alexander Nussbaumer for their technical support, as well as Pensoft Publishers Ltd. for hosting our journal.I look forward to continuing to work with our editors, editorial team and technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can improve and develop J.UCS in the future. We also greatly appreciate the generous support of the J.UCS community, especially in promoting the journal and citing relevant articles in their research papers.In this regular issue, I am very pleased to present 6 accepted articles by 34 authors from 8 different countries, namely Austria, China, France, Germany, India, Thailand, Türkiye, United Kingdom.In a collaborative research effort from several research institutions from Austria, Thailand and Germany, Stefan Lengauer, Lin Shao, Hossein Miri, Michael Bedek, Cordula Kupfer, Maria Zangl, Bettina Kubicek, Barbara Dienstbier, Klaus Jeitler, Cornelia Krenn, Thomas Semlitsch, Carolin Zipp, Dietrich Albert, Andrea Siebenhofer, and Tobias Schreck present an advanced and innovative visual health information system - A+CHIS - based on adaptive document visualizations. Depending on the users’ information needs and preferences, the system displays its content at different levels of detail, aggregation, and visual granularity, addressing individual needs and preferences.Jinghan Liu, Hui Zhao, Chenyang Lin, Dan Wang, and Shufan Li from China address in their research the issue that existing smart contract vulnerability detection methods overly rely on expert rules and struggle to adapt to complex application scenarios. The article proposes a vulnerability detection model called ESA based on the enhanced sequential algorithm. Experimental results demonstrate that ESA significantly outperforms cutting-edge methods, achieving detection accuracies of 89.09% for reentrancy vulnerabilities and 88.49% for timestamp dependency vulnerabilities.Kadir Ileri, M. Şamil Balcı, and Adem Dalcalı from Türkiye focus in their research on predicting the harvested power of toroidal electromagnetic energy harvesters using machine learning models optimized with the Artificial Bee Colony algorithm. The findings show that the ABC-optimized XGBoost model provides highly accurate and robust predictions, outperforming the other evaluated approaches.Banani Ghose and Zeenat Rehena from India propose in their research work a Genetic Algorithm-based lossless data compression technique to reduce the size of the time-series data while conserving energy of the sensor-based system. The proposed lossless data compression technique can not only compress the air quality time series data with a high compression ratio, but it is also energy efficient, both contributing finally towards greater efficiency and longer lifetime of the sensor network.Hamdullah Karamollaoğlu, İbrahim Yücedağ, İbrahim Alper Doğru, Sinan Toklu and İsmail Atacak from Türkiye cover in their study the critical security challenge of DDoS attacks in resource-constrained IoT environments by proposing a novel hybrid deep learning model (CBM-IDS) that integrates Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and a Multi-Head Attention Mechanism for robust intrusion detection. The proposed model, evaluated on the CICDDoS2019 benchmark dataset and enhanced through advanced feature reduction and data balancing techniques, achieved a detection accuracy of 99.93%, demonstrating its significant potential for real-world IoT security applications.In a collaborative research effort between France and Türkiye, İbrahim Çakırlar, Sevcan Emek, Şebnem Bora, and Oğuz Dikenelli introduce RatKit, an advanced framework and methodology for verification, validation and testing of agent-based simulation models, which is based on the Boids model. The findings demonstrate that a test-driven approach can enhance model reliability and ensure that individual agent behaviors coalesce into realistic emergent phenomena.Enjoy Reading!Best wishes, Christian Gütl, Managing Editor-in-Chief Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.183050

Authors: Christian Gütl

Abstract: Dear Readers, At the end of this year, it gives me great pleasure to announce another regular issue of J.UCS. In this issue, various topical aspects of computer science are covered in 6 articles by 14 authors from 7 countries – Armenia, Chile, Germany, Poland, South Africa, United Kingdom, and Vietnam.I would like to thank all the authors for their sound research and the editorial board and guest reviewers for the highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal. I am looking forward to continuing my work as Editor-in-Chief with the J.UCS community also in 2026. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals to our journal. Finally, we are preparing to offer a J.UCS portal on ResearchGate as well as the Altmetric and Web of Science reviewer recognition service with beginning of the next year. In the last regular issue in 2025, I am very pleased to introduce 6 accepted articles covering various aspects of computer science. Nguyen Thi Hoang Phuong, Phan Minh Nhat, and Nguyen Van Hieu from Vietnam introduce in their study NirMACNet, a multi-scale convolutional neural network incorporating a residual mechanism to address the limitations of existing methods in predicting compositional attributes from raw near-infrared spectra across diverse materials. Experimental evaluations on milk and soil datasets demonstrate that NirMACNet significantly enhances feature extraction, eliminates the need for complex preprocessing, and outperforms state-of-the-art techniques in prediction accuracy. Nadia van Niekerk, Brink van der Merwe, and Louwrens Labuschagne from South Africa introduce in their work a mining software repositories approach to unravel insights from the expansive landscape of zero-knowledge proofs development. Through a metrics-driven analysis, the authors unveil patterns in tool popularity, development trends, and historical perspectives, offering a comprehensive understanding of the ZKP tooling ecosystem. In a collaboration between researchers from Germany and Armenia, Wolfram Luther and Ashot Harutyunyan present in their article an extensive literature review on the importance of fairness and absence of bias in society, science, the world of work and leisure, with a focus on healthcare and risk prediction tools. Based on this findings, relevant approaches to a general definition of algorithmic fairness for individuals and groups are presented, assessed from the perspective of the concerned sciences, and requirements for the decision-making processes are formulated. Alexandru Pintea from UK researches in his article how sensor data can be used by robust AI models to accurately estimate the number of people present in a room while considering real-time monitoring as a primary use case. The study explores sensor positioning and model hyperparameters for numerous models in order to optimize the robustness and performance of inhabitance monitoring systems. Przemyslaw Jatkiewicz from Poland proposes in his work to integrate artificial intelligence techniques - specifically machine learning, neural networks, and user behaviour analysis - to enhance corporate data protection through real-time anomaly detection and adaptive authentication. The research demonstrates that AI-based access control systems significantly improve security by enabling dynamic threat detection and prediction, and provides practical recommendations for implementing machine learning-based anomaly detection systems in combination with traditional authentication methods, while ensuring data protection through techniques such as anonymisation, encryption, and federated learning. Claudio Gutiérrez-Soto, Marco A. Palomino, Patricio Galdames, and Cristian Duran-Faundez from Chile address in their study the challenge of identifying determinants of academic success in higher education by integrating descriptive student profiling with Bayesian predictive modelling. Using enriched datasets from the University of Bio-Bio, the approach achieves over 97% accuracy, advancing learning analytics through reliable forecasting.Season greetings to all of you, relaxing holidays and ‘Enjoy Reading’! Best regards, Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.159191

Authors: Muhammad Saqlain, José M. Merigó, Keivan Amirbagheri, Hermann Maurer

Abstract: This study presents a comprehensive bibliometric analysis of the Journal of Universal Computer Science (JUCS) covering the period 1994-2024, based on data retrieved from the Scopus database in April 2025. The analysis has been conducted following the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol and using mathematical and statistical methods, VOS viewer, and bibliometrix. The article investigates the journal’s publication trends, citation structures, collaboration networks, and thematic evolution over three decades. A comparative review with the study published in 2021 by Baloain and collaborators, shows improved journal metrics, enhanced global recognition, and alignment with emerging research trends. The co-citation and bibliographic coupling analyses highlight JUCS’s strong intellectual connectivity across key domains of computer science, particularly in interdisciplinary areas. Thematic mapping and keyword analysis show a clear transition from classical computing themes to modern topics like artificial intelligence, deep learning, big data, and blockchain, demonstrating the journal’s responsiveness to evolving scientific priorities. The study concludes with general findings, practical implications, and future research directions, emphasizing JUCS’s role as a durable, adaptive, and impactful platform for scholarly output in the global computer science research community.

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DOI: 10.3897/jucs.178548

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the 13th J.UCS issue of 2025. I would like to thank all the authors for their sound research and the editorial board and guest reviewers for the extremely valuable reviews and suggestions for improvement. These contributions together with the support of the community and the generous support of the KOALA initiative enable us to run our journal and maintain its quality.I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to present 6 accepted articles by 18 authors from 9 countries: Australia, Austria, Brazil, Chile, China, Iran, Malaysia, Spain, and Turkiye.In a collaborative effort between researchers from Australia and Austria, Muhammad Saqlain, José M. Merigó, Keivan Amirbagheri, and Hermann Maurer provide a comprehensive bibliometric analysis of the Journal of Universal Computer Science (JUCS) from 1994 to 2024, employing the SPAR-4-SLR protocol with VOSviewer and Bibliometrix to examine publication patterns, collaboration networks, and thematic evolution. The findings reveal JUCS’s strengthened global impact, intellectual connectivity, and transition toward modern computer science domains such as artificial intelligence, deep learning, and big data, underscoring its sustained relevance and adaptability over three decades.Claudio Alvarez, Andres Carvallo, and Gustavo Zurita from Chile address in their research the growing orchestration load teachers face in real-time case-based learning discussions by introducing a low-footprint natural language processing approach that can run on standard hardware without requiring large-scale models. Expert evaluation shows that small pre-trained models, particularly BETO and the Universal Sentence Encoder, effectively identify relevant student responses while maintaining low computational cost and minimizing bias, enabling scalable and equitable AI support for educators in the Global South.In a collaborative research effort between Malaysia and China, Yongbin Li, Xinyue Yang, Linhu Hui, Enlin Fu, and Stephanie Chua focus on Lung Nodule Detection. To reduce false positives on CT scans, the authors propose AMCF-CNN, a 3D attention-guided multi-scale cross-fusion network that effectively integrates local features and global contextual information through SimAM-Res and the Global Modeling Module. Evaluated on the LUNA16 dataset, AMCF-CNN achieves a CPM of 0.936 and a balanced accuracy of 0.983, outperforming most existing methods. José de Oliveira Guimarães from Brazil focuses his research on aspects of metaprogramming in Cyan. Most compile-time metaprogramming languages allow unrestricted modifications to the in-memory representation of the base program by providing largely unconstrained access to the compiler’s internal data structures. The Cyan metaprogramming system, in contrast, uses a sandboxed model that prevents errors caused by such unrestricted access while retaining most of the expressive power of other systems.Vahide Nida Kılıç and Esra Saraç Eşsiz from Turkiye propose in their research a novel anomaly prevention framework that combines clustering-based nature-inspired algorithms with both node and content features to identify suspicious instances in communication networks. The approach advances the field by shifting from traditional anomaly detection to proactive prevention through the early classification of suspicious nodes, threshold-based risk assessment, and link analysis to flag potential anomalies before escalation.Atefeh Parvin, Farahnaz Mohanna, and Masoumeh Rezaei from Iran discuss in their research a genetic-based square jigsaw puzzle solver. To address the challenge of distinguishing identically colored pieces from different objects in jigsaw puzzle solving, they propose a genetic algorithm-based solver that integrates a novel color and texture compatibility criterion using Sum of Squared Distances and Gabor filter features. This approach improves accuracy by 11.9% and 3.65% in direct and neighbor comparison criteria across 66 puzzles, offering a data-efficient solution for type 1, 2, and 3 square jigsaw puzzles.Enjoy Reading!Cordially, Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.175734

Authors: Christian Gütl

Abstract: Dear Readers,It is a great pleasure to announce the twelfth J.UCS issue of 2025. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for the extremely valuable reviews and suggestions for improvement. These contributions together with the support of the community and the generous support of the KOALA initiative enable us to run our journal and maintain its quality. I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to present 5 accepted papers by 18 authors from 5 countries: Algeria, Brazil, China, Spain, and Türkiye. Irene Ruiz-Pozo, Juan Morales-García, Claudia Ximena Aguirre-Mejía, and Antonio Serrano from Spain explore in their study the application of generative AI tools such as ChatGPT and Gemini - in creating Instagram marketing content for eSports, comparing them with human-generated campaigns. Findings reveal that AI-generated content achieves comparable or higher engagement metrics, while hybrid strategies combining AI and human creativity maximize reach, authenticity, and audience growth. Aluizio Haendchen Filho, Jonathan Nau, Hércules Antonio do Prado, and Edilson Ferneda from Brazil tackle in their research the scarcity of methodologies for argument mining in Brazilian Portuguese by analyzing student essays from the National High School Exam, and introducing a feature-engineering approach based on discourse markers. This method enhances automated essay scoring while providing a transparent and computationally efficient alternative to black-box transformer models. Findings show that a streamlined set of five argument-mining features significantly improves scoring accuracy for the competency of developing intervention proposals grounded in scientific concepts. Samet Aymaz from Türkiye discusses in the article a histogram-based feature selection method with a custom LSTM model to improve early detection of coronary artery disease. The proposed approach achieves convincing classification results on benchmark datasets, offering a fast, accurate, and scalable diagnostic solution. Zhichao Chen, Zixi Han, Bingqing Shen, Yuxin Zeng, Min Wang, Hongming Cai, and Minqi Wang from China address in their study the issue of complex Integrated Process Planning and Scheduling (IPPS) modeling that existing methods have difficulties in satisfying new modeling requirements for adequately representing the complex scenarios and settings in real-life production. This study proposed an enhanced modeling and computing framework for solving complex IPPS problems, and empirically demonstrated its effectiveness and efficiency in solving complex IPPS problems with the key demanding features. Fouzi Lezzar and Seif Eddine Mili from Algeria address in their research the lack of real-time guidance in home-based physical rehabilitation by proposing a Temporal Conditional Generative Adversarial Network (TCGAN) that generates patient-specific skeletal motion sequences for exercise execution. The system demonstrates high accuracy and realism, achieving strong alignment between generated and real movements, and significantly improves the precision of rehabilitation exercises compared to existing methods.Enjoy Reading!Cordially,Christian Gütl, Editor-in-Chief

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DOI: 10.3897/jucs.171956

Authors: Christian Gütl

Abstract: Dear Readers,Welcome to another J.UCS regular issue covering 5 articles on topical research areas in computer science. As part of our continuous improvement process, we have decided to provide more information about the accepted papers in the editorials starting with this issue.I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the KOALA initiative, contribute to the quality of our journal.In an ongoing effort to further strengthen our journal, I am continuously looking for new editorial board members: If you are a tenured associate professor or higher with a good publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.It gives me great pleasure to announce the eleventh J.UCS issue of 2025. In this issue, 5 papers by 14 authors from 5 countries - India, Malaysia, Sweden, Taiwan, Türkiye - cover various topical aspects of computer science.Timothy Louis Scott, Wei Wei Goh, and Navid Ali Khan from Malaysia introduce their research on aspect-based sentiment analysis for product reviews. To address the problem of information overload on e-commerce platforms, a hybrid machine learning classification algorithm that employs aspect-based sentiment analysis and soft voting, was developed to detect the polarity and key aspects mentioned in Amazon product reviews. Based on the experiments conducted, SVHA attained higher accuracies and macro F1-scores compared to four other algorithms, showing its suitability in conducting aspect-based sentiment analysis.Emine Cengiz and Murat Gök from Türkiye propose in their study an enhanced approach for detecting money laundering in blockchain networks by representing transaction graphs as chaotic time series, extracting Lyapunov Exponents through phase space reconstruction, and classifying them with Graph Convolutional Networks. The main contribution is a feature expansion and chaotic analysis framework that improves blockchain transaction representation and enables more effective detection of illicit activities.In a collaborative effort, researchers from India and Sweden, Ashish Ranjan Mishra, Rakesh Kumar, and Rajkumar Saini introduce a deep learning technique for multimodal biometric authentication. More specifically, the article proposes DeepV-Net, a multimodal biometric authentication system that fuses EEG signals with handwritten signatures using V-net integrated with squeeze-excitation and attention modules. The model outperforms unimodal and state-of-the-art methods, demonstrating high accuracy, robustness, and significant contributions from its fusion and attention mechanisms.Ming-Lung Hsu, Yu-Wei Liu, and Sheng Tun Li from Taiwan address in their study the limitations of existing monotonic classification models in one-class classification by proposing a monotonicity-constrained support vector domain description – the MC-SVDD model, which integrates monotonicity constraints into the SVDD framework using quadratic programming and visualization techniques. Experimental results show that MC-SVDD outperforms conventional SVDD in prediction performance, contributing to the advancement of domain-driven data mining.Jafseer KT, Shailesh S, and Sreekumar A from India address in their research a feature evolution aware classification framework for streaming data using dynamic autoencoder and ensembled learning. The proposed research focuses on handling dynamically evolving features by introducing an enhanced solution that leverages a Dynamic Autoencoder DAE and ensemble learning. The ensemble technique used in the proposed classification framework demonstrates promising performances in diverse datasets, achieving accuracies of 86%, 94%, and 95% in the Weather, Electricity and Forest Cover Type datasets.Enjoy Reading!Kind regards,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.168512

Authors: Christian Gütl

Abstract: Dear Readers,I am very pleased to announce today the tenth J.UCS issue of 2025. In this issue, various topical aspects of computer science are covered in 5 articles by 13 authors from 5 countries (Brazil, Croatia, Germany, India, Spain). As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions sustain the quality of our journal. I would also like to express my sincere thanks to the KOALA Initiative and its team for their financial support, without which the J.UCS team would not be able to publish our journal.In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal.In this regular issue, I am very pleased to introduce the following 5 accepted articles: Rodrigo Costa Camargos and Ismar Frango Silveira from Brazil explore in their research the application of Explainable Artificial Intelligence (XAI) techniques to mitigate cognitive biases in predicting student dropout comparing Explainable Boosting Machine (EBM), Logistic Regression and XGBoost models.Sorav Kumar Singh, Alak Roy and Rajneesh Raushan from India focus their research on underwater wireless sensor networks and propose a Residual Energy-Aware Fuzzy-Based Clustering Algorithm (REAFCA), which presents an enhanced framework to improve network performance and addresses issues with energy usage.Juan Morales-García, Fernando Terroso-Sáenz, Andrés Bueno-Crespo, and José M. Cecilia from Spain discuss in their research the analysis of synthetic timeseries as an enabler to improve region-based human mobility forecasting by applying Generative adversarial network (GANs) to generate synthetic time-series mobility data.Igor Tomičić, Petra Grd, and Andrija Bernik from Croatia present in their research a comprehensive analysis of the integration of artificial intelligence into threat intelligence (TI) systems focusing on its potential to enhance cybersecurity operations by an extensive literature review including machine learning, deep learning, and natural language processing for automating threat detection, classification, and analysis.And last but not least, Daniel Spiekermann from Germany investigates in his research the real-world behaviour of network traffic within virtualized environments to identify the key factors that impact packet dynamics, including VM operations, multi-tenancy, user customization, and hardware adjustments.Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.130590

Authors: Eugen Valentin Butilă, Mihai Burlacu, Răzvan Gabriel Boboc, Robertas Damaševičius

Abstract: As a relatively new technology that has gone through several iterations in the last decade, virtual reality (VR) applications have been used in a plethora of activities pertaining to various sciences, including anthropology. In this paper, we expound a bibliometric analysis of the reviews and research articles regarding the use of VR applications in anthropology between 2010 and 2023. The analysed publications were obtained from the Scopus database, and Microsoft Excel and VOSViewer were used to analyse the data. Utilizing bibliometric methods, the analysis encompasses a thorough examination of scholarly publications, identifying and scrutinizing prominent journals, prolific authors, affiliated institutions, and key research themes within the realm of VR applications in anthropology. The objective is to provide a systematic and insightful overview of the evolution, current state, and emerging trends in the integration of VR within the anthropo-logical discourse, shedding light on the interdisciplinary nature and impact of this innovative technology on anthropological research and practice.

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DOI: 10.3897/jucs.165499

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the seventh regular issue of 2025. In this issue, 4 papers by 12 authors from 6 countries – Colombia, India, Lithuania, Romania, Spain, Turkiye – cover various topical and novel aspects of computer science. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the increasing number of accesses and PDF downloads. These contributions, together with the generous financial support of the KOALA initiative, sustain the quality of our journal. n a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. In the seventh regular issue, I am very pleased to introduce the following 5 accepted articles: In a collaboration between researchers from Colombia and Spain, Juan-Sebastián González-Sanabria, Cristian Pinto, Jhon Zuñiga, Hugo Ordoñez, and Xiomara Blanco focus on a XGBoost Classifier-Based Model to predict the nature of gender-based violence based on specific socio-demographic and situational features.Muthukumaran N and Vignesh A from India present enhancements of chatbot responses by addressing challenges such as context retention over extended interactions, syntactic ambiguities and bias propagation from training data. They propose an advanced transformer model, the Improved T5 (IT5), to solve these issues.In a collaboration between researchers from Romania and Lithuania, Eugen Valentin Butilă, Mihai Burlacu, Răzvan Gabriel Boboc, and Robertas Damaševičius discuss the findings of a bibliometric analysis of reviews and research articles on the use of VR applications in anthropology between 2010 and 2023.Last but not least, Davut Çulha from Turkiye addresses scalability aspects through a binary tree blockchain of decomposed transactions, which can reduce the computational overhead required to calculate account balances and make the system more efficient.Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.162422

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the sixth regular issue of 2025. In this issue, 4 papers by 11 authors from 3 countries - Brazil, Italy, Republic of Korea - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.As always, I would like to thank all the authors for their sound research and the editorial board members and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the consistently high number of user accesses and PDF downloads. These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal.In the sixth regular issue, I am very pleased to present the following 4 accepted articles: Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, and Sylvio Barbon from Italy focus their research on synthetic data generation as an alternative to traditional data anonymization based on variational autoencoders to generate high-quality synthetic tabular datasets.Roger Vieira and Kleinner Farias from Brazil introduce in their research CognIDE, a tool-supported methodology that aims to seamlessly integrate psychophysiological data linked to cognitive indicators into VS Code by offering actionable contextual cues alongside dynamic source code.Pedro Henrique Dias Valle and Elisa Yumi Nakagawa from Brazil discuss in their research a catalog of the main interoperability architectural solutions for addressing the four levels of interoperability - namely technical, syntactic, semantic, and organizational – for solving interoperability issues in software systems by analyzing 65 studies from the scientific literature.Ji Woong Yoo, Kyoung Jun Lee and Arum Park from the Republic of Korea explore the potential of deep learning techniques - Long Short-Term Memory (LSTM) algorithm and Word2Vec model – for cleansing malicious comments from users, and enhancing the ethical nature of AI systems.Enjoy Reading!Christian Gütl, ManagingEditor-in-Chief

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DOI: 10.3897/jucs.158922

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the fifth regular issue of 2025. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the KOALA consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research.Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce 5 papers by 13 authors from 5 countries: Brazil, China, India, Tunisia, Vietnam. Icaro Prado Fernandes and Luiz Eduardo Galvão Martins from Brazil propose in their article a method to prioritize test cases based on human knowledge using a combination of factors evaluated in an assessment answered by 29 software industry professionals and 5 academics. Ryma Abassi from Tunisia builds on the principles of ethics, human rights and legal frameworks in his research to address the challenges and dilemmas faced by policymakers when it comes to ensuring cybersecurity without compromising privacy and civil liberties and proposes a set of ethical guidelines and best practices for designing and implementing cybersecurity policies. M. Priadarsini and J. Akilandeswari from India propose a unique framework in their research that leverages the big five personality traits alongside long short-term memory (LSTM) networks under a multitask learning paradigm to improve the performance of aspect-based sentiment analysis. Thuy Phuong Khuat, Trang Van and Hoang Thien Van from Vietnam discuss in their research an approach to plant leaf recognition by integrating the vision transformer (ViT) model with the OSSGabor filter, referred to as the OGViT method, and analyze the performance on four public datasets (Swedish Leaf, Flavia, Folio, and UCI Leaf) that outperforms state-of-the-art approaches. Yang Zhang, Ziwen Wei, Zhihua Liu, Xiaolong Wu and Junchao Qian from China introduce in their study a cost-effective and highly accurate method for recognizing patient postures during radiotherapy based on stacked grayscale 3-channel images. Enjoy Reading!Best regards,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.156450

Authors: Christian Gütl

Abstract: Dear Readers,I am very happy to announce the fourth regular issue of 2025. In this issue, 4 articles by 14 authors from 4 countries (Brazil, Egypt, India, Indonesia) cover a variety of topical research aspects in computer science. Allow me to express my appreciation to all the authors for their sound research work and to thank the editorial board and guest reviewers for their extremely valuable reviews and suggestions for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the KOALA initiative, helps to maintain the quality of our journal.In the ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal.In the fourth regular issue, I am very pleased to introduce the following four accepted articles: In their paper, Carlos Goetz, Rodrigo Simon Bavaresco, Wesllei Felipe Heckler, Gustavo Lazarotto Schroeder, Rafael Kunst, and Jorge Luis Victória Barbosa from Brazil propose an ontology to identify stressors, considering personal and environmental data, which makes it possible to generate knowledge about work stressors in order to mitigate the problem utilizing a methodology consisting of seven stages and two evaluation phases. In their research, Manpreet Singh and Jitender Kumar Chhabra from India deal with fault prediction of multimedia software which integrates various multimedia heterogeneous components by a GA-based technique to combine multiple features using conjunction (AND) and disjunction (OR) operators while finding threshold values. Sarah Khater, Magda B. Fayek, and Mayada Hadhoud from Egypt present their research on human activity recognition (HAR) and discuss a GA-based approach to automatically generate ConvLSTM architectures for human activity recognition. And last but not least, Hendrik Hendrik, Silmi Fauziati, and Adhistya Erna Permanasari from Indonesia introduce an enhancing knowledge graph construction with automated source evaluation utilizing large language models.Enjoy Reading!Best regards,hristian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.153315

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the third regular issue of 2025. I would like to thank all the authors for their sound research and the editorial board and guest reviewers for the extremely valuable reviews and suggestions for improvement. These contributions together with the support of the community enable us to run our journal and maintain its quality.I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to present 5 accepted papers by 19 authors from 6 countries: Algeria, Argentina, Bangladesh, India, United Kingdom, and Vietnam.In the first paper Neha Kumari and Rajeev Kumar from India address improvements of compiler error messages in the context of wildcard-type argument inference in Java programs by additions to the current wildcard-based type inference algorithm to get detailed and valuable error messages. Liliana Favre from Argentina discusses research on a unified formal framework for metamodeling in the context of MDE, which is based on the Nereus metamodeling language and includes transformers for translating MOF metamodels to Nereus metamodels and Nereus metamodels to MOF metamodels. In their joint work between researchers from Vietnam and the UK, Phan Minh Nhat, Ngo Le Huy Hien, Dinh Minh Toan, Le Viet Hung, Phan Binh, Phung Thi Anh, Nguyen Thi Hoang Phuong, and Nguyen Van Hieu introduce their research on detecting concentrations by Near Infrared Reflectance Spectroscopy (NIR) in cattle and poultry fertilizers by a synthesized machine learning model named EBAR (Error Based Accumulation Regression) combined with a backward elimination technique designed to identify crucial wavelength ranges for monitoring component concentrations. In another collaborative research between Algeria and India, Maroua Benleulmi, Ibtissem Gasmi, Nabiha Azizi, and Nilanjan Dey present an overview of deep learning-based recommender systems, explore their application to enhance performance, and discuss their limitations. Last but not least, Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, and M. Jamshed Alam Patwary from Bangladesh highlight their research on a multimodal fusion algorithm for non-intrusive anxiety detection based on TI-Fusion, a multimodal fusion technique that integrates text and image data for a unified reliable outcome and overcomes the limitations of other existing methods. Enjoy Reading!Best regards, Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.150728

Authors: Christian Gütl

Abstract: Dear Readers,Today we have sad news to share with you. We are deeply saddened by the passing of Arto Salomaa, one of the visionary founding members of our journal. Arto Salomaa, former professor of mathematics at the University of Turku, Finland, was a highly respected pioneer in the field of mathematical theory of computer science with a focus on formal languages and automata theory. Salomaa passed away peacefully on January 26 at the age of 90, surrounded by his family. Our thoughts are with his family, friends and all those who had the privilege of knowing him. His legacy will forever be a part of our journal.It gives me great pleasure to announce the second regular issue of 2025. In this issue, 4 papers by 13 authors from 5 countries - Brazil, Germany, India, Pakistan and Turkiye - cover a great variety of topical aspects of computer science.In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the increasing number of accesses and PDF downloads.In the second regular issue, I am very pleased to introduce the following 4 accepted articles: Mehmet Ali Altuncu, Kaplan Kaplan, and Melih Kuncan from Turkiye discuss their comparative study of transfer learning models - Resnet-50, Resnet-101, VGG19, and InceptionResnetV2 - on skin cancer confirmation methods based on dermoscopic dataset images. Kiran K A and Jaison Jacob from India present their research on Energy-aware application mapping on 3D mesh-based network-on-chip using heuristic mapping algorithms where performance metrics such as communication cost, communication energy consumption, and CPU runtime were applied. In their study, Aneela Nargis, Muhammad Mobeen Movania, and Shama Siddiqui from Pakistan discuss an autoencoder-integrated WideResNet with dynamic optimization, which was designed specifically for the analysis of head and neck cancer gene expression data. In a joint research paper by researchers from Brazil and Germany, Ana Paula Allian, Frank Schnicke, Pablo Oliveira Antonino, Thomas Kuhn and Elisa Yumi Nakagawa look at the adoption of blockchain to trustworthy interoperability in Industry 4.0 systems and aim to highlight the challenges and close the gap between theoretical promises and practical applications.Enjoy Reading!Best wishes,Christian Gütl, Managing Editor-in-Chief

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DOI: 10.3897/jucs.146652

Authors: Christian Gütl

Abstract: Dear Readers, I would like to wish you all the best for the new year! It is with great pleasure that I welcome you to our first regular issue in 2025 with a pleasant new achievement. The journal has successfully exceeded 30 years and is still available to authors and readers without interruption. I would like to gratefully acknowledge the visionary ideas of Prof. Hermann Maurer, who founded the journal and successfully managed it for many years, preparing the ground for it to become one of the longest-running open content journals in computer science. Starting with this issue in the new year, we are very pleased to be part of the KOALA Computer Science Cluster from TIB - Leibniz Information Centre for Science and Technology University Library, Germany. We have also changed our license to CC BY, and future special issues will also be free of charge because of the KOALA funding. Looking back on the past year, we have further increased our visibility and taken steps to fully comply with the Diamond Open Content Standard and align our journal with the KOALA requirements. Thanks to the combined efforts of the Pensoft team and the J.UCS publishing team, we are listed and indexed in more than 40 indexing services worldwide, including DOAJ, Web of Science, and Scopus. The increased visibility and social media presence have also led to a further increase in page views and article downloads. With around 120,000 unique views, reader interest in J.UCS publications increased by 20% compared to the previous year. We can also look back on an increasing number of submitted articles and special issue proposals. This interest is reflected in a notable impact factor with a Scopus Cite Score of 2.2 and a Web of Science Journal Impact Factor of 0.7. We proudly look back on a total of 13 issues - 12 regular and 1 special issue - with 78 articles by 256 authors from 45 countries on novel aspects of various computer science topics. The acceptance rate has fallen to below 15 per cent. These great achievements were only possible thanks to the commitment and interest of the community and the valuable support of the Editorial Board and financial supporters of J.UCS. In 2024, we welcomed 19 new members to the Editorial Board, bringing our total number of Editorial Board members to 211. We would also like to gratefully acknowledge the support of 33 guest reviewers over the past year. In particular, I would like to thank Dr. Ulrike Krießmann from the Library of the Graz University of Technology, the TIB - Leibniz Information Centre for Science and Technology University Library in Germany, and the Institute of Interactive Systems and Data Science from TU Graz for their financial support. I would also like to thank the J.UCS team, Johanna Zeisberg for taking care of the publication process, David Kerschbaumer for his social media support, and Sebastian Gürtl and Alexander Nussbaumer for their technical support, as well as Pensoft Publishers Ltd. for hosting our journal. I look forward to continuing to work with our editors, editorial team and technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can improve and develop J.UCS in the future. We also greatly appreciate the generous support of the J.UCS community, especially in promoting the journal and citing relevant articles in their research papers. In this regular issue, I am very pleased to present 5 accepted articles by 16 authors from 7 different countries, namely Algeria, China, India, Ireland, Spain, Tunisia, and Turkiye. Emre Önal and Abdullah Bülbül from Turkiye cover in their research a computational game unit balancing approach based on game theory to make each game unit equally preferable against a uniform play strategy. Ruchika Malhotra and Madhukar Cherukuri from India look in their research into Software Defect Categorization (SDC) models and apply convolutional neural networks in their empirical study. Song Yu, Bugao Jiang, Danni Zhang, and Zhifang Liao from China address in their research a cross-community question relevance prediction model, CCQRP, to predict the relevance of Stack Overflow questions and GitHub issues and recommend relevant GitHub issues. In a collaboration between researchers from Algeria and Tunesia, Soraya Setti Ahmed, Yahya Slimani and Riadh Frefita report their research on a fault tolerance model for the Hadoop Distributed System. In a collaboration between researchers form Spain and Ireland, Francisco Dominguez-Mateos, Vincent O’Brien, James Garland, Ryan Furlong, and Daniel Palacios-Alonso present their research on zero-shot learning for sub-discrimination in pre-trained models to differentiate several attributes such as gender, age, and skin tone, without any additional training.Enjoy Reading!Best wishes,Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.116830

Authors: Alessander Osorio, Paulo Roberto Ferreira Jr., Gerson Geraldo H. Cavalheiro

Abstract: Researchers have access to a vast repository of scientific papers reporting research results through the Internet. In this context, fostering collective knowledge growth, researchers may encounter situations where the content of a paper is not effectively utilized due to flaws in the presentation of conducted research. Various fields of knowledge have developed research protocols to assist in the production of scientific reports. In the field of Computer Science, proposals for such protocols are still in development. This paper describes a case study conducted with undergraduate and graduate students in Computer Science, involving guided reading of scientific papers, and recording students’ perceptions regarding adherence to a set of guidelines for the presentation of scientific results. The case study focused on papers presenting research results with a quantitative focus, such as performance evaluations. The exercise took place over two academic semesters, where reading instructions were provided, and impressions about the observed content were collected every two or three weeks. The analysis results indicated that, despite being well-written, the papers had gaps in relation to the reading guidelines. The study’s conclusions suggest that authors underestimate the importance of providing a comprehensive account of their experi-ence, highlighting the need for protocols to report scientific results in the field of Computer Science.

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DOI: 10.3897/jucs.144927

Authors: Christian Gütl

Abstract: Dear Readers,At the end of this year, it gives me great pleasure to announce the twelfth regular issue of 2024. In this issue, various topical aspects of computer science are covered in 5 articles by 14 authors from 5 countries. I would like to thank all the authors for their sound research and the editorial board for the highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, maintain the quality of our journal. I am looking forward to continuing my work as Managing Editor-in-Chief with the J.UCS community also in 2025. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals to our journal. Finally, we are preparing to join the KOALA Cluster for Computer Science and Mathematics, making some minor organizational adjustments. We are switching to the CC BY license, and all metadata is accessible under the CC0 license. We are very grateful for the financial support for the next three years. In this regular issue, I am very pleased to introduce the following 5 accepted articles: Marija Kuštelega, Renata Mekovec, and Ahmed Shareef from Croatia have conducted a systematic literature review to find out how the current research on the digital twin implementations has been positioned in front of practical challenges focused on privacy and security issues. Mehtap Ülker and A. Bedri Özer from Turkiye address in their research a fine-tuning BART-based model which generates a scientific summary by selecting important words from the text of the input document. Alessander Osorio, Paulo Roberto Ferreira Jr., and Gerson Geraldo H. Cavalheiro from Brazil introduce a case study conducted with undergraduate and graduate students in Computer Science, involving guided reading of scientific papers, and recording students’ perceptions of adherence to a set of guidelines for the presentation of scientific results. Ruan Visser, Trieko Grobler, and Marcel Dunaiski from South Africa address the gap in natural language processing for Southern African languages, and present an in-depth analysis of language model development under resource-constrained conditions. Last but not least, Seyedeh Aridis Ahadi, Kian Jazayeri, and Sahand Tebyani from Cyprus propose in their research an integrated framework for the identification of suicidal thoughts in social media through the implementation of a layered classifier model consisting of a convolutional neural network (CNN) and a long short-term memory (LSTM) model.Season greetings to all of you, relaxing holidays and ‘Enjoy Reading’! Best regards,Christian Gütl,Managing Editor-in-Chief Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.114513

Authors: Geová Junio da Silva Tavares, Nelson Souto Rosa

Abstract: Adaptive systems possess the remarkable capability to assess and modify their behavior in real-time, particularly when the software deviates from its programmed course or when opportunities for enhanced functionality or performance arise. This adaptability proves invaluable in highly dynamic environments, where rapid changes occur, and human oversight alone falls short in effectively managing applications. However, in certain system types, achieving optimal performance through adaptation may necessitate human input, be it as a sensor providing unique information beyond the system’s reach, an actuator driving adaptation, or a fallback mechanism in contingency scenarios. In this context, the concept of ’human-in-the-loop’ harnesses the innate capabilities of humans to execute tasks and make decisions with greater efficiency and precision, thereby ensuring the security and reliability of these systems. Our primary objective in this study is to present a comprehensive analysis of the key research and contributions in this field. Additionally, we aim to pinpoint potential research avenues and unresolved challenges within the realm of Human-in-the-loop.

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DOI: 10.3897/jucs.142059

Authors: Christian Gütl

Abstract: Dear Readers,First of all, I am very happy to announce that the funding round of the KOALA initiative initiated by the TIB was successful and that our journal will be part of the computer science and mathematics cluster for the next three years. The entire J.UCS team is very grateful for the great efforts of the KOALA team and for the support of the J.UCS community. This enables us to continue our work to maintain J.UCS as a diamond open access journal and to further improve the service and scientific quality.Also, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, contribute to the quality of our journal.It gives me great pleasure to announce the eleventh regular issue of 2024. In this issue, 6 papers by 21 authors from 5 countries - Brazil, India, Algeria, Italy, Sweden - cover various topical aspects of computer science. In an ongoing effort to further strengthen our journal, I am continuously looking for new editorial board members: If you are a tenured associate professor or higher with a good publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.Geová Junio da Silva Tavares and Nelson Souto Rosa from Brazil present the results of a survey on humans in the loop for self-adaptive systems. Aluizio Haendchen Filho, Adson Marques da Silva Esteves, Hércules Antonio do Prado, Edilson Ferneda and André Luis Alice Raabe from Brazil discuss their study on adaptive content recommendations to improve logic and programming teaching and learning by using learning paths to group students and provide personalized recommendations based on peers' progress. Rupesh Kumar Verma, A. J. Khan, Sunil Kashyap and Manoj Kumar Chande from India conduct their study on the certificateless aggregate signature scheme in terms of their computational performance and security, which can be widely used in areas such as IoT or healthcare systems. Besma Hezili and Hichem Talbi from Algeria address the collaborative auto-diversified optimization scheme (CADOS) for solving continuous and combinatorial optimization problems by exploring the synergy of various optimization algorithms and enhance their effectiveness and efficiency, particularly for higher-dimensional problems. Maroua Chemlal, Amina Zedadra, Ouarda Zedadra, Antonio Guerrieri and Med Nadjib Kouahla from Algeria outline their approach and findings on a multi-criteria food and restaurant recommendation system. And last but not least, Ashish Ranjan Mishra, Rakesh Kumar and Rajkumar Saini from India present their study on the improvement of the effectiveness of person authentication by using deep learning techniques on electroencephalogram (EEG) signals by applying a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model to extract features and classify raw EEG data.Enjoy Reading!Kind regards,Christian Gütl, Managing EditorGraz University of Technology, Graz

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DOI: 10.3897/jucs.139725

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the tenth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research.Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to introduce six accepted papers involving 17 authors from six different countries (Argentina, Brazil, Ecuador, Hong Kong, India, Saudi Arabia).Álex dos Santos Moura, Fábio Gomes Rocha, and Michel S. Soares from Brazil propose in their research a recommendation tool based on information retrieval to assist developers in choosing the suitable microservices pattern to solve a given problem. In a collaborative research effort between Ecuador and Argentina, Gonzalo P. Espinel-Mena, José L. Carrillo-Medina, Eddie E. Galarza, and Mario Matias Urbieta discuss a systematic mapping of configuration management activities in software product line. Edward Kai Fung Dang, Robert Wing Pong Luk, and Qing Li from Hong Kong contribute to the forum for negative results with their study on word bigrams for pseudo-relevance feedback in information retrieval. Prateek Thakral and Yugal Kumar from India present in their work an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. Samit Bhanja, Banani Ghose, and Abhishek Das from India highlight their findings on multi-step-ahead time series forecasting using a deep learning and fuzzy time series-based error correction method. And last but not least, Abdullilah A. Alotaibi and Salman A. AlQahtani from Saudi Arabia present in their research an intelligent distributed channel selection framework with hybrid mode selection for interference mitigation in D2D based 5G networks. Enjoy Reading!Best regards, Christian Gütl, Managing EditorGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.109788

Authors: Lojenaa Navanesan, Nhien-An Le-Khac, Yossi Oren, Kasun De Zoysa, Asanka P. Sayakkara

Abstract: The possession of smart devices has ingrained itself into daily life. Therefore, smart devices, such as IoT and smartphones, are crucial sources of evidence in instances where criminal activity occurs. Due to the challenges in traditional digital forensic techniques involving smart devices, it has been recently proposed in the literature to leverage electromagnetic side-channel analysis (EM-SCA) for the purpose. This paper identifies and discusses an important barrier that exists in the application of EM-SCA for digital forensics that hinders its successful use, namely, the issue of cross-device portability of machine learning (ML) models that are used for EM-SCA. Firstly, the paper empirically evaluates the possibility of using trained ML models to extract forensic insights from EM radiation data of IoT devices. During this empirical study, the inability to reuse a trained ML model across different devices is identified. Secondly, the paper surveys the literature in search of related work that has studied the use of EM-SCA to gather information from smart devices. The purpose of the survey is to identify whether any existing work has been able to introduce potential approaches to enable cross-device portability of ML models in EM-SCA. The findings of this survey point to the fact that the identified problem still exists and requires further studies opening the door to future research.

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DOI: 10.3897/jucs.137611

Authors: Christian Gütl

Abstract: Dear Readers, Following the publication of the J.UCS special issue ‘Fighting Cybersecurity Risks from a Multidisciplinary Perspective” by our esteemed guest editors Steffen Wendzel, Aleksandra Mileva, Virginia N. L. Franqueira and Martin Gilje in mid-September, I am very pleased to announce today the ninth J.UCS regular issue of 2024. In this issue, various topical aspects of computer science are covered by 26 authors from 8 countries (Algeria, Brazil, India, Indonesia, Ireland, Israel, Serbia, Sri Lanka) in 6 articles. As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as part of the KOALA initiative. Please think about the possibility of such financial participation by your institution in the computer science and mathematics cluster of the KOALA initiative together with a lot of other active members, we would be very grateful for any kind of support. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal. In this regular issue, I am very pleased to introduce the following 6 accepted articles: Panji Bintoro, Zulkifli Zulkifli, Yaya Heryadi, Fitriana Fitriana, Nopi Anggista Putri, and Dwi Yana Ayu Andini introduce their research on the automatic detection of systemic diseases to recognize Mpox virus using GPLNet based on skin lesions. In their research, Farhad Lotfi, Branka Rodić, Aleksandra Labus, and Zorica Bogdanović from Serbia are looking at predicting university students' anxiety by using supervised learning algorithms with providing pertinent feedback. Michele dos Santos Soares, Cássio Andrade Furukawa, Maria Istela Cagnin, and Débora Maria Barroso Paiva from Brazil discuss their research findings on identifying the accessibility barriers faced by the community of blind students and highlighting the main factors that hinder this community from accessing learning objects. Houda Tadjer, Zohra Mehenaoui, Yacine Lafif, Amira Chemmakh, and Asanka P. Sayakkara from Algeria discuss their research on time management for effective learning based on students' temporal traces and the production of automatic feedback in an online learning environment. In a collaborative research effort between Sri Lanka, Ireland and Israel, Lojenaa Navanesan, Nhien-An Le-Khac, Yossi Oren, and Asanka P. Sayakkara cover in their research cross-device portability of machine learning models in electromagnetic side-channel analysis for forensics. Last but not least, Ujjwala Thakur, Ankit Vidyarthi, and Amarjeet Prajapati from India cover the latest research on video activity recognition by introducing a robust framework that leverages the power of a stacked Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU) architecture, harmonized within a fusion-based deep model. Enjoy Reading! Best regards, Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.132132

Authors: Dagmar Gesmann-Nuissl, Ines Maria Tacke, Stefanie Meyer

Abstract: As part of the modern Internet, Internet of Things (IoT) devices are particularly indispensable. The reason these devices fit so seamlessly into our everyday lives is that they constantly generate, process and evaluate data (using the Internet) and can react smoothly to circumstances – such as the refrigerator that automatically reorders missing food or a maintenance monitory system in smart homes that assigns digital maintenance orders to the responsible tradesmen. These data flows and underlying information are the subject of a wide variety of legal projects: Europe aims to become a pioneer of the data economy by providing access to available data accessible for further value and business models. Subject matter includes both personal data and non-personal data, such as IoT machine data. To achieve these politicaleconomic goals, but also to ensure the interests of users and especially manufacturers in confidentiality and fair competition, we introduce the person of the neutral data intermediary: the data innovator.

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DOI: 10.3897/jucs.134740

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the eighth regular issue of 2024. In this issue, 6 papers by 20 authors from 9 countries – Algeria, Brazil, China, Germany, Iraq, Ireland, Pakistan, Turkey, United Kingdom – cover various topical and novel aspects of computer science. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the increasing number of accesses and PDF downloads. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. In the eighth regular issue, I am very pleased to introduce the following 6 accepted articles: In a joint research work between Iraq, Algeria and the UK, Rewayda Razaq Abo-Alsabeh, Meryem Cheraitia and Abdellah Salhi discuss their results on a plant propagation algorithm for the bin packing problem. Ildevana Poltronieri, Avelino Francisco Zorzo, Maicon Bernardino and Edson Oliveira Jr from Brazil introduce Usa-DSL, a usability evaluation process for domain-specific languages (DSLs) that aims to assist DSL designers in evaluating their languages in terms of ease and quality of use without requiring deep knowledge of usability evaluation. Carina Heßeling, Sebastian Litzinger and Jörg Keller from Germany report on their research on the archive-based covert channel in sensor streaming data. This is an approach in which the covert sender and receiver first build an archive of values that occur in the stream in a certain time interval, and then encode bits of the secret message via sensor stream values belonging to the class of seen values or not. In another collaborative effort between researchers from Pakistan and Ireland, Anwar Ahmed Khan, Shama Siddiqui and Indrakshi Dey present a novel risk prediction approach, namely Association Rule Mining for Risk Prediction (ARMR), which integrates an IoMT framework with the emerging machine learning technique known as Association Rule Mining (ARM). Furkan Berk Seyrek and Halil Yiğit from Turkey discuss their study, which focuses on the classification of lung images from computed tomography (CT) scans into cancerous and non-cancerous categories by employing prevalent deep learning models, transfer learning, and rigorous evaluation metrics. And last but not least, Yu Zhong, Bo Shen, Tao Wang, Jinglin Zhang and Yun Liu from China address the interaction and fusion of rich textual information for document-level relation extraction that simultaneously considers multiple types of nodes.Enjoy Reading!Best regards, Christian Gütl, Managing EditorGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.131928

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the seventh regular issue of 2024. In this issue, 5 papers by 12 authors from 6 countries - Brazil, Ecuador, Germany, Iraq, Spain, Turkey - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the consistently high number of user accesses and PDF downloads. These contributions, together with the generous support of the consortium members, maintain the quality of our journal. In the seventh regular issue, I am very pleased to present the following 5 accepted articles: Vinicius Bischoff and Kleinner Farias from Brazil report their study on a controlled experiment with 22 participants (15 students, 7 professionals) in which the correctness and the effort required for the integration of feature models were investigated. Abdulkadir Buldu, Kaplan Kaplan and Melih Kuncan from Turkey present their research on an assistive system based on EEG data and Continuous Wavelet Transform (CWT), which aims to reduce the life-threatening risk for epilepsy patients. In a collaboration between researchers from Ecuador and Spain, Darwin Alulema, Maximiliano Paredes-Velasco and Ricardo de Arriba Lasso report in their manuscript on the LESCA system, which performs adaptive content feedback through scaffolding and supports the development of high-level competencies. In another joint research between colleagues from Iraq and Germany, Anwar Mira and Olaf Hellwich present their approach to improve recognition capabilities by optimizing deep learning features for hand gesture image recognition. Specifically, they propose to enhance features of well-trained DNNs using an improved radial basis function (RBF) neural network, targeting recognition within individual gesture categories. And last but not least, Rasim Çekik and Mahmut Kaya from Turkey propose in their research a new performance metric to evaluate filter feature selection methods in text classification. Enjoy Reading! Best regards, Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.129593

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the sixth regular issue of 2024. In this issue, 6 papers cover various topical aspects of computer science by 19 authors from 7 countries: Brazil, Chile, France, India, Saudi Arabia, Tunisia, and Turkey. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all authors for their sound research and the editorial board and our guest reviewers for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, help to maintain the quality of our journal. In this regular issue, I am very pleased to introduce the following 6 accepted articles: George Marsicano, Edna Dias Canedo, Glauco V. Pedrosa, Cristiane S. Ramos, and Rejane M. da C. Figueiredo from Brazil look in their study into digital transformation of public services in a startup-based environment by 23 focus groups and 175 participants in total. Mauricio Solar and Pablo Aguirre from Chile discuss their research on 3D chest CT processes applying a ResNet-50 model to which a new dimension of information has been added, namely a simple autoencoder. In a collaborative work between researchers from Tunisia and France, Rakia Saidi, Fethi Jarray, and Didier Schwab propose in their article a cross-encoder neural network (Cross-BERT-GRU) to deal with the semantic similarity of Arabic sentences that benefits from both the strong contextual understanding of BERT and the sequential modeling capabilities of GRU. Also in a collaborative research between institutions from Tunisia and Saudi Arabia, Nozha Jlidi, Sameh Kouni, Olfa Jemai, and Tahani Bouchrika present their research on MediaPipe with GNN for human activity recognition. G.V.Vidya Lakshmi and S. Gopikrishnan from India look into missing values research for the IoT domain and in particular present IMD-MP technique that improves imputation accuracy for big data analysis in IoT applications based on spatial-temporal correlations. Last but not least, F. Didem Alay, Nagehan İlhan, and M. Tahir Güllüoğlu address in their article a comparative study of data mining methods for solar radiation and temperature forecasting models. Enjoy Reading Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.109227

Authors: Binnu Paul, Dwijen Rudrapal, Kunal Chakma, Anupam Jamatia

Abstract: Multimodal machine translation (MMT) is a challenging task in the linguistically diverse Indian landscape. Machine translation refers to the task of automatically converting content from one language to another without human involvement. Within the realm of natural language processing, a significant challenge arises from the inherent ambiguity present in human language. Translation ambiguity is a cross-lingual phenomenon that can manifest itself for various reasons, including lexical ambiguity, the occasional need to impute missing words, the presence of gen-der ambiguity, and word-sense ambiguities. These factors can lead to a decrease in translation accuracy. The integration of multiple modalities, such as images, videos, and audio, in addition to text, plays a pivotal role in improving the robustness and precision of translation systems. Over the past five years, extensive research has been dedicated to incorporating secondary modalities alongside text to improve language translation and comprehension. In this comprehensive study, our objective was to identify and explore promising MMT approaches, available corpora, eval-uation metrics, research challenges, and the future direction of research specifically for Indian languages. We evaluated 81 papers, including MMT models, MMT dataset in Indian languages, survey on MMT approach, and the effects of multiple modalities in machine translation. The performance of the different proposed approaches has also been briefly analyzed on the basis of the claimed results and comparative evaluations. Finally, the challenges associated with the MMT task for India and some possible directions for future research in this domain are highlighted.

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DOI: 10.3897/jucs.127994

Authors: Christian Gütl

Abstract: Dear Readers, I am very happy to announce the fifth regular issue of 2024. In this issue, 7 articles by 21 authors from 8 countries (Austria, Brazil, France, India, Iran, Morocco, Pakistan, and Turkey) cover a variety of topical research aspects in computer science. Allow me to express my appreciation to all authors for their sound research and to the editorial board and guest reviewers for the highly valuable reviews and comments for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the consortium members, sustains the quality of our journal. In the ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal. In the fifth regular issue, I am very pleased to introduce the following seven accepted articles: Florian Skopik, Arndt Bonitz, Daniel Slamanig, Markus Kirschner, and Wolfgang Hacker from Austria focus on cybersecurity issues and aim to deliver a concept for a device that can be used in multiple security domains, isolating mission-specific data from each other without the risk of data spillover, and based on this, outline a high-level concept for a resilient single device concept that is able to withstand common intrusion attempts. Yunus Emre Avcı and Adem Tuncer from Turkey propose their model for detecting lane changes by applying a wavelet transform to high-resolution data from unmanned aerial vehicles based on empirical lane changing data from pNEUMA. Alaor Cervati Neto and Alexandre L. M. Levada from Brazil cover in their article improvements to the Locality Preserving Projections (LPP) algorithm by incorporating a recently proposed graph inference method called Probabilistic Nearest Neighbors (PNN), an extension of the Clustering with Adaptive Neighbors (CAN) approach. In a collaboration between researchers from Morocco and France, Ayoub Charef, Zahi Jarir, and Mohamed Quafafou discuss their approach, which utilizes computer vision algorithms to detect and quantify traffic violations by motorcyclists, such as non-compliance with helmet regulations, illegal lane changing, driving in the wrong direction, weaving between vehicles and running red lights. Razieh Dehghani and Raman Ramsin from Iran propose an evaluation framework for Situational Method Engineering processes and guidelines for improvements as well as for knowledge management support. Saima Farhan, Rubiya Shoukat and Aqsa Aslam from Pakistan address the detection of sarcastic remarks from a multi-domain dataset by using a Bi-LSTM model that works with pre-trained GloVe word embeddings. Binnu Paul, Dwijen Rudrapal, and Kunal Chakma from India cover a comprehensive survey on multimodal machine translation approaches for Indian languages. Enjoy Reading! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.111677

Authors: André Fernandes, João Cruz, Miguel Mira da Silva, Rúben Pereira

Abstract: Organizations are under increasing pressure to comply with various rules, standards, and policies in today’s regulatory environment. Compliance controls are put in place to avoid legal or regulatory violations, which could lead to severe penalties, loss of reputation, and financial damages. However, these controls may have similar scopes and objectives, resulting in duplicated work and unnecessary costs for the organizations. To address this issue, researchers carry out the mapping and integration of these standards to avoid duplication, streamline compliance efforts, and identify best practices. Our work aims to improve the State-of-the-Art by exploring the main benefits and problems resulting from these processes, as well as identifying methods or artifacts that can be reused in the future. We focus on the fields of Risk, Security, and Business Continuity, as these are critical areas where compliance is crucial for organizations. Through our research, we have found that current methods of generating mapping artifacts are not only cumbersome to execute but also ineffective, as they output a single artifact without the reasoning behind it.

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DOI: 10.3897/jucs.125268

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the fourth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. I am also very proud to announce that our journal has been included in the Free Journal Network as one of the listed high-quality journals in this field. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce six papers by 22 authors from nine countries: Brazil, Czech Republic, Germany, Iran, Jordan, Portugal, Thailand, Turkey, and the USA. In a collaboration between researchers from the Czech Republic and Germany, Sivaramasamy Elayaraja, Sunil Yeruva Vlastimil Stejskal, and Satish Nandipati look into multi-class microscopic image analysis of protozoan parasites using convolutional neural network and perform a study on 4740 microscopic images. André Diegues Fernandes, João Cruz, Miguel Mira da Silva, and Rúben Pereira from Portugal cover a systematic literature review for mapping and integrating security and risk standards. In a collaborative research between Jordan and the USA, Sahar Idwan, Junaid Zubairi, Syed Ali Haider, and Wael Etaiwi introduce their reactive traffic congestion control method based on a hierarchical graph approach. Shahrzad Riahi, Ramtin Khosravi, and Fatemeh Ghassemi from Iran conduct a study on knowledge-related policy analysis in an inference-enabled actor model. Josival Silva, Nelson Rosa, and Fernando Aires from Brazil research and present UP-Home, a self-adaptive solution that manages the security of smart homes by industry standards, and identifies and mitigates smart home security vulnerabilities. Last but not least, Sait Can Yucebas, Sukran Yalpir, Levent Genc, and Melike Dogan from Turkey discuss their research on price prediction and determination of the factors influencing real estate prices using X-Means clustering and CART decision trees. Enjoy Reading! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.107082

Authors: Jan Bergstra, John V. Tucker

Abstract: Previously, in [Bergstra and Tucker 2023], we provided a systematic description of elementary arithmetic concerning addition, multiplication, subtraction and division as it is practiced. Called the naive fracterm calculus, it captured a consensus on what ideas and options were widely accepted, rejected or varied according to taste. We contrasted this state of the practical art with a plurality of its formal algebraic and logical axiomatisations, some of which were motivated by computer arithmetic. We identified a significant gap between the wide embrace of the naive fracterm calculus and the narrow precisely defined formalisations. In this paper, we introduce a new intermediate and informal axiomatisation of elementary arithmetic to bridge that gap; it is called the synthetic fracterm calculus. Compared with naive fracterm calculus, the synthetic fracterm calculus is more systematic, resolves several ambiguities and prepares for reasoning underpinned by logic; indeed, it admits direct formalisations, which the naive fracterm calculus does not. The methods of these papers may have wider application, wherever formalisations are needed to analyse and standardise practices.

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DOI: 10.3897/jucs.123217

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the third regular issue of 2024. In this issue, 6 papers by 20 authors from 6 countries - China, Ecuador, Spain, The Netherlands, Turkey, United Kingdom - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest on our articles indicated by an increasing access number and PDF downloads. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. In the third regular issue, I am very pleased to introduce the following 6 accepted articles: In a collaboration between researchers from The Netherlands and the United Kingdom, Jan Bergstra and John V. Tucker discuss their research on synthetic fracterm calculus, more specifically they introduce a new intermediate and informal axiomatisation of elementary arithmetic. Yasir Yakup Demircan and Serhat Ozekes from Turkey highlight their research on least significant bit steganography technique based on image segmentation. In a collaborative research effort between Spain and Ecuador, Alberto Jimenez-Macias, Pedro Muñoz-Merino, Margarita Ortiz-Rojas, Mario Muñoz-Organero, and Carlos Delgado-Kloos present their study on a systematic literature review on content modeling using machine learning algorithms in smart learning environments considering content indicators based on student interaction. Melih Kuncan, Kaplan Kaplan, Yılmaz Kaya, Mehmet Recep Minaz, and H. Metin Ertunç from Turkey focus on computer numerical control (CNC) systems, more specifically on classification of CNC vibration speeds by Heralick features. Lifang Ren, Jing Li, and Wenjian Wang from China address in their research support vector regression (SVR) and the location-aware method for mobile QoS prediction to overcome the difficulty caused by the sparsity of data and to predict the unknown QoS more accurately. Last but not least, Emre Sadıkoğlu, İrfan Kösesoy, and Murat Gök from Turkey look into the vulnerability of artificial systems to cyber-attacks by applying a gradient descent-based method to generate fake data. Enjoy Reading! Cordially, Christian Gütl, Managing Editor-in-Chief Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.98708

Authors: Anne Perera, Amitha Caldera

Abstract: Sentiment Analysis is the task of identifying and extracting the opinion expressed in a text to determine the writer's perception of an entity. Due to globalization, people often mix two or more languages and use phonetic typing and lexical borrowing in web communication. This concept is known as code-mixing. Although extracting the opinion of text written in monolingual languages is simple and straightforward, Sentiment Analysis of code-mixed text is challenging. Classifiers fail within the context of the code-mixed text as text may consist of creative writing, spelling variations, grammatical errors, and different word orders. Hence, SA of code-mixed text is an interesting, challenging, and popular research area. This paper presents the state-of-the-art in Sentiment Analysis of code-mixed text by discussing each concept in detail. The paper also discusses the focused areas, techniques used, limitations, and performances of the studies related to code-mixing.

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DOI: 10.3897/jucs.121223

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the second regular issue of 2024. I would like to thank all the authors for their sound research and the editorial board for the extremely valuable reviews and suggestions for improvement. These contributions together with the generous support of the consortium members enable us to run our journal and maintain its quality. I would still like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends. And finally, we are still looking for some financial support for 2024 to cover all our expenses. We would be very grateful if your library or institution can support us. We would then be happy to add it to our consortium list. In this regular issue, I am very pleased to present 6 accepted papers by 19 authors from 9 countries: Canada, China, Croatia, India, Kazakhstan, México, Sri Lanka, Ukraine, and Vietnam. Petra Grd, Igor Tomičić, and Ena Barčić from Croatia address in their article a multi-step methodology for face shape classification that is based on the potential of transfer learning and a pretrained EfficientNetV2S neural network. Lizbeth Alejandra Hernández-González, Ulises Juárez-Martínez, Jezreel Mejía, and Alberto Aguilar-Laserre from México focus their research on applying the naturalistic programming paradigm within a software development process using a naturalistic software development method. In a joint research, Shanshan Jia from China, Gaukhar A. Kamalova from the Republic of Kazakhstan, and Dmytro Mykhalevskiy from Ukraine report on a mobile handover technique aligning with the neighbour discovery paradigm in 6LoWPAN. Ajay Kumar from India is investigating a mechanism to assess machine learning approaches for software effort estimation (SEE) modeling in the context of accuracy measures, specifically exploring machine learning techniques for SEE modeling as a multi-criteria decision making (MCDM) problem. Anne Perera and Amitha Caldera from Sri Lanka conduct a comprehensive review on sentiment analysis in the context of mix of languages, phonetic typing and lexical borrowing in web communication. And last but not least, in a collaboration between researchers from Vietnam and Canada, Tien Quang Dam, Nghia Thinh Nguyen, Trung Viet Le, Tran Duc Le, Sylvestre Uwizeyemungu, and Thang Le-Dinh look into malware detection methods, specifically leveraging machine learning to encode critical information from portable executable (PE) headers into visual representations of ransomware samples. Enjoy Reading! Cordially, Christian Gütl, Managing Editor-in-Chief Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.119196

Authors: Christian Gütl

Abstract: Dear Readers, I would like to wish you all the best for the new year! It is with great pleasure that I welcome you to our first regular issue in 2024, which is already the 30th year that J.UCS has been available to authors and readers without any interruptions. I would like to gratefully acknowledge the visionary ideas of Prof. Hermann Maurer, who founded the journal and ran it successfully for many years, preparing the ground for it to become one of the longest-running open content journals in computer science. Looking back on the past year, we have further increased our visibility and taken steps to fully comply with the Diamond Open Content Standard and prepare to join the KOALA initiative. Thanks to the combined efforts of the Pensoft team and the J.UCS publishing team, we are listed and indexed in more than 40 indexing services worldwide, including DOAJ, Web of Science, and Scopus. The increased visibility and social media presence have also led to a further increase in page views and article downloads. With around 100,000 unique views, interest has doubled compared to the previous year. We can also look back on an increasing number of submitted articles and special issue proposals. We are also very pleased to report that the journal's Impact Factor has stabilised at a high level with a Web of Science Impact Factor of 1.0 and a Scopus Science Score of 2.7. We proudly look back on a total of 12 issues - 11 regular and 1 special issue - with 63 articles by 231 authors from 40 countries on new aspects of various computer science topics. The acceptance rate has fallen to below 15 per cent. These great achievements were only possible thanks to the commitment and interest of the community and the valuable support of the Editorial Board and the J.UCS Consortium members. In 2023, we welcomed 10 new members to the Editorial Board, bringing our total number of Editorial Board members to 196. We would also like to gratefully acknowledge the support of 67 guest reviewers over the past year. In particular, I would like to thank Dr. Ulrike Krießmann from the Library of the Graz University of Technology, Prof. Klaus Tochtermann from the ZBW, Prof. Christian Eckhardt from California Polytechnic State University, Prof. Krzysztof Pietroszek from the American University in Washington DC, and Prof. Muhammad Tanvir Afzal from Shifa Tameer-e-Millat University in Islamabad in Pakistan for their generous support in offering an open content journal without charging the authors for their articles. Unfortunately, some partners are withdrawing their support for 2024 due to financial restrictions, but we are very happy to welcome the Leibniz Information Centre for Science and Technology and are very grateful for their support. I would also like to thank the J.UCS team, Johanna Zeisberg for taking care of the publication process, Aleksandar Bobic and David Kerschbaumer for their social media support, and Alexander Nussbaumer for his technical support, as well as Pensoft Publishers Ltd. for hosting our journal. I look forward to continuing to work with our editors, editorial team and technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can improve and develop J.UCS in the future. We also greatly appreciate the generous support of the J.UCS community, especially in promoting the journal and citing relevant articles in their research papers. In this regular issue, I am very pleased to present 6 accepted articles by 21 authors from 6 different countries, namely Brazil, Cuba, France, Malaysia, Spain, and the United Kingdom. In a collaborative effort between researchers from Spain and the UK, Bashar Alshouha, Jesus Serrano-Guerrero, David Elizondo, Francisco P. Romero and Jose A. Olivas look into consumer attitudes towards healthcare services by applying a transfer learning approach to detect emotions from consumer feedback. In the second article, Ana Díaz Muñoz, Moisés Rodríguez Monje, and Mario Gerardo Piattini Velthuis from Spain address the design of an environment to measure quality metrics for hybrid, classic-quantum software, propose a set of new measurements for hybrid maintainability, and develop a first prototype as a SonarQube plugin that is capable of measuring these metrics. In a research collaboration between the UK, Malaysia and France, Ngo Le Huy Hien, Ah-Lian Kor, Mei Choo Ang, Eric Rondeau, and Jean-Philippe Georges cover findings on image filtering techniques for object recognition in autonomous vehicles based on the evaluation of 5 different deep learning models, YOLOv5s, EfficientNet-B7, Xception, MobilenetV3, and InceptionV4, and Hessian, Laplacian, and Hessian-based Ridge Detection filtering techniques. Francisco Iniesto and Covadonga Rodrigo from Spain look into the evaluation of MOOC accessibility as students’ experience by applying web content accessibility guidelines and an automatic tool, and investigate students’ perceptions and comparison of the two approaches. Yilena Pérez-Almaguer, Edianny Carballo-Cruz, Yailé Caballero-Mota, and Raciel Year from Cuba explore content-based group recommendations for suggesting restaurants in Havana City enhanced by extended restaurant features, virtual group profiles, and the selection of the most appropriate aggregation approach for composing group recommendations. Last but not least, Raimundo Osvaldo Vieira and Helyane Bronoski Borges from Brazil cover a systematic mapping study on dimensionality reduction for hierarchical multi-label classification. Enjoy Reading! Cordially, Christian Gütl, Managing Editor-in-ChiefGraz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.117559

Authors: Christian Gütl

Abstract: Dear Readers, At the end of this year, it gives me great pleasure to announce the eleventh regular issue of 2023. In this issue, various topical aspects of computer science are covered in 6 articles by 18 authors from 7 countries (Argentina, Brazil, China, France, Germany, Spain, and Turkey). I would like to thank all the authors for their sound research and the editorial board for the highly valuable review effort and comments for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. I am looking forward to continuing my work as Managing Editor-in-Chief with the J.UCS community. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal. Finally, we are looking for further financial support from potential consortium members to cover the costs of publishing the journal next year. In this regular issue, I am very pleased to introduce the following 6 accepted articles: F. Kebire Bardak, M. Nuri Seyman, and Feyzullah Temurtaş from Turkey present in their research a hybrid algorithm for emotion classification based on electroencephalogram signals, which is composed of a radial basis function neural network and a probabilistic neural network. In a collaborative research effort between Spain and France, Anita Herrera, Ángel Arroyo, Alfredo Jiménez and Álvaro Herrero conduct a comprehensive review of the different techniques and models with regard to Artificial Intelligence when applied to the tourism industry. In a collaboration between researchers from Brazil and Germany, Ana Cristina Alves de Oliveira, Marco Aurélio Spohn, Christof Fetzer, Le Quoc Do, and André Martin aim to address the cost problem of DaaS by developing a model that optimizes the cost of querying distributed data sources over virtual machines spread across multisite data centers. Herminia Beatriz Parra and Marcela Vegetti from Argentina present in their article OntoFoCE, Ontology for Electronic Mail Forensics, which is a specific ontology for the forensic analysis of emails to help the computer expert in validating an email presented as judicial evidence. Valdicélio Santos and Michel S. Soares from Brazil propose a framework, and then the design and further evaluation of a web-based application to support software architects in using the activities and tasks of the architecture conceptualization clause based on the ISO/IEC/IEEE 42020 framework. Last but not least, Yunwu Xu and Yan Li from China contribute to the improvement of an existing wireless sensor network coverage optimization method which is based on the pigeon-inspired optimization algorithm. Season greetings to all of you, relaxing holidays and ‘Enjoy Reading’! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.94929

Authors: Anderson Melo de Morais, Fernando Antonio Aires Lins, Nelson Souto Rosa

Abstract: While IoT systems are increasingly present in different areas of society, ensuring their data’s privacy, security, and inviolability becomes paramount. In this direction, Blockchain has been used to protect the security and immutability of data generated by IoT devices and sensors. At the heart of Blockchain solutions, consensus algorithms are crucial in ensuring the security of creating and writing data in new blocks. Choosing which consensus algorithms to utilise is critical because of a fundamental tradeoff between their security strength and response time. However, recent surveys of consensus mechanisms for IoT-based Blockchain focused on individually using and analysing these algorithms. Investigating the integration between these algorithms to address IoT-specific requirements better is a promising approach. In this context, this paper presents a literature review that explains and discusses consensus algorithms in IoT environments and their combinations. The review analyses eight dimensions that help understand existing proposals: ease of integration, scalability, latency, throughput, power consumption, configuration issues, integrated algorithms, and adversary tolerance. The final analysis also suggests and discusses open challenges in integrating multiple consensus algorithms considering the particularities of IoT systems.

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DOI: 10.3897/jucs.114450

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the tenth regular issue of 2023. In this issue, various topical aspects of computer science are covered by 18 authors from 8 countries in 6 articles. As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal. As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as consortium members, who will then benefit from the research community, international visibility, and the opportunity to manage special issues and focused topics within the journal. Please think about the possibility of such financial participation by your institution, we would be very grateful for any kind of support. In this regular issue, I am very pleased to introduce the following 6 accepted articles: In a collaboration between researchers from Palestine and Jordan, Rasha R. Atallah, Ahmad Sami Al-Shamayleh, and Mohammed A. Awadallah look into the impact of plastic surgery on face recognition models and propose a model based on an artificial neural network with model-agnostic meta-learning (ANN-MAML) for plastic surgery face recognition which results in an accuracy of 90% in all evaluation experiments. In another research collaboration between colleagues from Tunisia and the Kingdom of Saudi Arabia, Samar Bouazizi, Emna Benmohamed, and Hela Ltifi propose in their article an advanced approach to recognize human emotions by using electroencephalogram (EEG) signals and focus their analysis on two specific classes of emotion recognition: H/L Arousal and H/L Valence. Anderson Melo de Morais, Fernando Antonio Aires Lins, and Nelson Souto Rosa from Brazil report on their survey on integration of consensus mechanisms into IoT-based blockchains, analyzing eight dimensions that help understand existing proposals: ease of integration, scalability, latency, throughput, power consumption, configuration issues, integrated algorithms, and adversary tolerance. In the next article Aymane Ezzaim, Aziz Dahbi, Abdelfatteh Haidine, and Abdelhak Aqqal from Morocco carry out a systematic mapping of the literature on AI-based adaptive learning environments and approaches. They examine 93 articles published between 2000 and 2022 and discuss the findings, including the types of AI algorithms used, the objectives targeted by these systems as well as the factors related to adaptation. Sergio-Daniel Sanchez-Solar, Gustavo Rodriguez-Gomez, and Jose Martinez-Carranza from México present their research on the control of a spherical robot rolling over irregular surfaces, which is achieved by controlling two motors for longitudinal and lateral motion in this non-holonomic system, and showed improvements by tuning the controller’s gains using stochastic signals for the longitudinal controller. Last but not least, Layse Santos Souza and Michel S. Soares from Brazil propose in their article the joint use of the SmartCitySysML with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams that specify internal behavior, and then verify the developed model to prove behavioral properties of an urban traffic signal control system. Enjoy Reading! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.111691

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the ninth regular issue of 2023. I would like to thank all the authors for their sound research and our editorial board and guest reviewers for the extremely valuable reviews and suggestions for improvement. These contributions, together with the generous support of the consortium members, enable us to run our journal successfully and maintain its quality. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as consortium members, who will then benefit from the research community, international visibility, and the opportunity to manage special issues and focused topics within the journal. Please think about the possibility of such financial participation by your institution, we would be very grateful for any kind of support. In this regular issue, I am very pleased to introduce five accepted papers involving 22 authors from 10 different countries: Austria, Brazil, Estonia, France, Lebanon, Malaysia, Spain, The Netherlands, United Kingdom, and Vietnam. In a collaborative research effort, Jan Bergstra from The Netherlands and John V. Tucker from the United Kingdom introduce the Naive Fracterm Calculus, which is a new perspective on elementary arithmetic and can be described as naive when compared to a variety of algebraic and logical, axiomatic formalisations of elementary arithmetic. Ricardo Caceffo, Jacques Wainer, Guilherme Gama, Islene Garcia, and Rodolfo Azevedo from Brazil conducted a study based on perceptual learning modules, more specifically a variation of perceptual learning based on multiple-choice questionnaires to be used in an introductory programming course, and report on related issues. In a collaborative research work between colleagues from Malaysia, Lebanon and France, Mohammad Kchouri, Norharyati Harum, Hussein Hazimeh, and Ali Obeid suggest a new technique to detect falls by combining Fuzzy Logic and Support Vector Machine, achieving an overall accuracy of about 99.87% in detecting the fall function. In an international research collaboration between Estonia, Austria, Spain, Luis P. Prieto, Gerti Pishtari, Yannis Dimitriadis, María Jesús Rodríguez-Triana, Tobias Ley, and Paula Odriozola-González propose and explore single-case learning analytics, which defines a process in which doctoral students, researchers, and computational elements collaborate to extract insights into a single learner’s experience and learning process. Last but not least, also in a joint research work by researchers from Vietnam and the United Kingdom, Nguyen Van Hieu, Ngo Le Huy Hien, Luu Van Huy, Nguyen Huy Tuong, and Pham Thi Kim Thoa present their approach PlantKViT for forest plants classification, which is based on a combination model of Vision Transformer and KNN and achieves a 93% accuracy. Enjoy Reading! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

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DOI: 10.3897/jucs.109658

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the eighth regular issue of 2023. In this issue, five papers by 24 authors from nine countries cover various topical aspects of computer science. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvements. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as consortium members, who will then benefit from the research community, international visibility, and the opportunity to manage special issues and focused topics within the journal. Please think about the possibility of such financial participation of your institution, we would be very grateful for any kind of support. In this regular issue, I am very pleased to introduce the following 5 accepted articles: In a collaborative research effort between Jordan and Qatar, Ahmad Abusukhon, Ala Al-Fuqaha and Belal Hawashin present their technique for detecting underground water pipeline leakage based on an Internet of Things approach. In another collaboration between researchers from Croatia and Bosnia and Herzegovina, Ani Grubišić, Slavomir Stankov, Branko Žitko, Ines Šarić-Grgić, Angelina Gašpar, Emil Brajković, and Daniel Vasić describe and evaluate the performance of a semiautomatic authoring tool for knowledge extraction in the AC&NL Tutor and discuss strengths and weaknesses. Also in a collaboration between researchers from the United States and United Arab Emirates, Longhao Li, Taieb Znati, and Rami Melhem propose an energy-aware fault-tolerance model for silent error detection and mitigation in heterogeneous extreme-scale computing environments, referred to diffReplication, which is associated with one replica that executes at the same rate as the main process, and one diffReplica that is executed at a fraction of the execution rate of the main process. In a collaboration between researchers form China and Japan, Xiaojuan Liao, Hui Zhang, Miyuki Koshimura, Rong Huang, and Fagen Li propose in their paper an optimized strategy for solving restricted preemptive scheduling on parallel machines applying Partial Maximum Satisfiability (PMS), an optimized version of a Boolean Satisfiability (SAT) solver. Finally, in a collaboration between researchers from South Korea and the USA, Jaeyoung Yang, Sooin Kim, Sangwoo Lee, Won-gyum Kim, Donghoon Kim, and Doosung Hwang aim in their paper to establish a binary classification method for distinguishing copyrighted and noncopyrighted images by introducing a deep hashing model for an image authentication system, which uses deep learning-based perceptual hashing. Enjoy Reading! Cordially,Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.109504

Authors: Christian Gütl

Abstract: Dear Readers, Welcome to the seventh issue in 2023. I am very pleased to announce the journal’s continued high Scopus CiteScore of 2.7 and Web of Science Impact Factor of 1.0 for 2022, indicating another scientifically successful year. On behalf of the J.UCS team, I would like to thank all the authors for their sound research contributions, the reviewers for their very helpful suggestions for improvements, and the consortium members for their financial support. Your commitment and dedicated work have contributed significantly to the long-lasting success of our journal. As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as consortium members, who will then benefit from the research community, international visibility, and the opportunity to manage special issues and focused topics within the journal. Please think about the possibility of such financial participation of your institution, we would be very grateful for any kind of support. In this regular issue, I am very pleased to introduce six accepted papers from seven different countries and 20 involved authors. Ana P. Allian, Leandro F. Silva, Edson OliveiraJr and Elisa Y. Nakagawa from Brazil present VMTools-RA, a reference architecture that encompasses the knowledge and practice for developing and evolving variability tools. In a collaboration between researchers from the UK and Estonia, Vimal Dwivedi, Mubashar Iqbal, Alex Norta and Raimundas Matulevičius are focusing their research on the evaluation of a legally binding smart-contract language for blockchain applications. Monika, Seema Verma, and Pardeep Kumar from India discuss an intelligent vision-based decision-making system for the exploration of past aviation accidents and incidents, which is based on a visual query-based model capable of analyzing the major factors including flight phases, human factors, weather conditions, and faulty components in particular aircraft models. Luis Eduardo Ordoñez Palacios, Víctor Bucheli Guerrero and Hugo Ordoñez from Colombia present their research on integrating satellite imagery and meteorological data to estimate solar radiation applying and evaluating five machine learning models. In a collaboration between researchers from Palestine and Egypt, Muath Sabha, Thaer Thaher, and Marwa M. Emam apply cooperative swarm intelligence algorithms to adaptive multilevel thresholding segmentation of COVID-19 CT scan images. Geovana Ramos Sousa Silva, Genaína Nunes Rodrigues and Edna Dias Canedo from Brazil introduce their work on a modeling strategy to design and verify chatbot conversational flows via the Uppaal model checking tool. Enjoy Reading!Cordially,Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.87550

Authors: Soukaina Benabdelouahab, José A. García-Berná, Chaimae Moumouh, Juan M. Carrillo-de-Gea, Jaber El Bouhdidi, Yacine El Younoussi, José L. Fernández-Alemán

Abstract: Due to the substantial development of information and communications technology, the use of E-learning in higher education has become essential to boost teaching methods and enhance students' learning skills and competencies. E-learning in Software Engineering turns out to be increasingly interesting for scholars. In fact, researchers have worked to enhance modern Software Engineering education techniques to meet the required educational objectives. The aim of this article is to analyse the scientific production on E-learning Software Engineering education by conducting a bibliometric analysis of 10,603 publications, dating from 1954 to 2020 and available in the Scopus database. The results reveal some scientific production information, such as the temporal evolution of the publications, the most prolific authors, institutions and countries, as well as the languages used. Besides, the paper evaluates additional bibliometric parameters, including the authors' production, journal productivity, and scientific cooperation, among other bibliometric parameters. The subject of the current study has not been treated by any previous bibliometric studies. Our research is deeper and more specific; it covers a long period of 66 years and a large number of publications, thanks to the chosen search string containing the different spellings of the used terms. In addition, the literature is analysed using several tools such as Microsoft Excel, VOSviewer, and Python. The research findings can be used to identify the current state of E-learning Software Engineering Education, as well as to identify various research trends and the general direction of E-learning research.

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DOI: 10.3897/jucs.108250

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the sixth regular issue of 2023. In this issue, 5 papers cover various topical aspects of computer science by 16 authors from 4 countries. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all authors for their sound research and the editorial board and our guest reviewers for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. In this regular issue, I am very pleased to introduce the following 5 accepted articles: In a collaborative research effort between Morocco and Spain, Soukaina Benabdelouahab, José A. García-Berná, Chaimae Moumouh, Juan M. Carrillo-de-Gea, Jaber El Bouhdidi, Yacine El Younoussi, and José L. Fernández-Alemán report on their bibliometric study on e-learning software engineering education by conducting an analysis of 10,603 publications, dating from 1954 to 2020. Achraf Boumhidi, Abdessamad Benlahbib and El Habib Nfaoui from Morocco propose in their research a financially-oriented reputation system that generates a single numerical value from user-generated content on Twitter toward cryptocurrencies by applying a sentiment polarity extractor based on the fine-tuned auto-regressive language model named XLNet. Samuel Caetano da Silva and Ivandré Paraboni from Brazil focus on politically-oriented information inference from text by a series of experiments to compare a number of strategies for political bias and ideology inference from text data using sequence-based BERT models, syntax- and semantics-driven features. Burak Gülmez from Türkiye discusses a model developed for disease detection from images of cotton leaves applying a deep convolutional neural network model and the grey wolf optimization algorithm. This model outperforms the ResNet50, VGG19, and InceptionV3 models frequently used in the literature. Last but not least, José L. López Ruiz, Ángeles Verdejo Espinosa and Macarena Espinilla Estévez from Spain discuss a new methodology for the optimization of Bluetooth anchors for location-relevant systems in an enclosed space using a machine learning-based inference model based on different configurations of the BLE anchors located in the enclosed environment. Enjoy Reading! Cordially, Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.106251

Authors: Christian Gütl

Abstract: Dear Readers, I am very happy to announce the fifth regular issue of 2023. In this issue, 5 articles by 22 authors from 5 countries cover a variety of topical research aspects in computer science. Allow me to express my appreciation to all authors for their sound research and to the editorial board for the highly valuable reviews and comments for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the consortium members, sustains the quality of our journal. In the ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal. In the fifth regular issue, I am very pleased to introduce the following five accepted articles: César Domínguez Pérez, Jónathan Heras, Eloy Mata, Vico Pascual, Lucas Fernández-Cedrón, Marcos Martínez-Lanchares, Jon Pellejero-Espinosa, Antonio Rubio-Loscertales, and Carlos Tarragona-Perez from Spain report on their deep learning approach for semi-supervised semantic segmentation to identify irrelevant objects in a waste recycling plant. In a research collaboration between Australia and Iraq, Mitchell Jensen, Khamael Al-Dulaimi, Khairiyah Saeed Abduljabbar and Jasmine Banks are focusing on their work on autoimmune disease detection in humans, more specifically on automating the classification procedure of HEp-2 stained cells from microscopic images and improving the accuracy of computer-aided diagnosis. Kashif Mehboob Khan, Warda Haider, Najeed Ahmed Khan, and Darakhshan Saleem from Pakistan address their research on big data provenance using blockchain for qualitative analytics through machine learning. Abubakhari Sserwadda, Alper Ozcan, and Yusuf Yaslan from Türkiye present their research on a novel end-to-end unified topological similarity and centrality driven hybrid deep learning model for temporal link prediction. And last but not least, Tahseen A. Wotaifi, and Ban N. Dhannoon from Iraq aim in their research to use deep learning, pre-trained models, and machine learning based on Convolution Neural Networks to predict Arabic and English fake news based on three public and available datasets: the Fake-or-Real dataset, the AraNews dataset, and the Sentimental LIAR dataset.Enjoy Reading!Cordially, Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.105420

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the fourth regular issue of 2023. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce five accepted papers involving 14 authors from four different countries.Seyedeh Mahsa Mirhoseini-Moghaddam, Mohammad Reza Yamaghani and Adel Bakhshipour from Iran look into fraud detection for Olive oil by applying smell and sight sensors resulting in an accurate, fast and non-destructive detection of adulteration in extra virgin olive oil. Fahimeh Ramazankhani, Mahdi Yazdian-Dehkordi and Mehdi Rezaeian report their research on kinship verification by analysing facial features based on various texture and color features and metric learning methods. Stefan Strydom, Andrei Michael Dreyer and Brink van der Merwe from South Africa contribute in their research to the International Classification of Disease (ICD) coding based on a transformer model applied to hospital discharge summaries. Fernando Terroso-Saenz and Andres Muñoz from Spain present their research on human mobility prediction using a long short-term memory and Gated Recurrent Unit neural network based on geo-data from cellular phones combined with data from road traffic sensors. Shefali Varshney, Rajinder Sandhu and P. K. Gupta from India report their research on cost-effective scheduling in fog computing based on the modified PROMETHEE technique. Enjoy Reading! Cordially, Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.103612

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the third regular issue of 2023. In this issue, 4 papers by 11 authors from 5 countries cover various topical aspects of computer science. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. In the third regular issue, I am very pleased to introduce the following 4 accepted articles: Gerardo Matturro from Uruguay reports on his research findings on undergraduate software engineering over a seven-year period, specifically on students' motivation to participate in research projects, skills acquired, and their perceptions of benefits. Uma Priya D and P. Santhi Thilagam from India propose an approach to cluster heterogeneous JSON documents using the similarity fusion method based on structural, semantic and contextual measures of JSON schemas. Zeinab Rahimi and Mehrnoush Shamsfard from Iran present a hybrid contradiction detection approach that can detect seven categories of contradictions in Persian texts: Antonymy, negation, numerical, factive, structural, lexical and world knowledge, which is based on a novel data mining method and a transformer-based deep neural method for contradiction detection. In their joint research between Estonia, Spain and India, Shashi Kant Shankar, Adolfo Ruiz-Calleja, Luis P. Prieto, María Jesús Rodríguez-Triana, Pankaj Chejara, and Sandesh Tripathi discuss a modular and modifiable infrastructure for data preparation, organization, and fusion to partially support the development of context-aware multimodal learning analytics solutions. Enjoy Reading!Cordially,

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DOI: 10.3897/jucs.102031

Authors: Christian Gütl

Abstract: Dear Readers, It gives me great pleasure to announce the second regular issue of 2023. I would like to thank all the authors for their sound research and the editorial board for the extremely valuable reviews and suggestions for improvement. These contributions together with the generous support of the consortium members enable us to run our journal and maintain its quality. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce 4 accepted papers involving 16 authors from 6 different countries. In a collaboration between researchers from South Africa and the USA, Trienko Grobler, Manfred Habeck, Lynette van Zijl and Jaco Geldenhuys address improved algorithms for combinatorial generation of bordered box repetition-free words based on tree-based search space and graph-based search space. In another joint research between Algeria and France, Mehdi Rouissat, Mohammed Belkheir, Hicham Sid Ahmed Belkhira, Sofiane Boukli Hacen, Pascal Lorenz and Merahi Bouziani describe a new technique to mitigate the version number attack for IoT networks, reducing control overhead by 83% and energy consumption by 74%. Amira Samir, Huda Amin Maghawry and Nagwa Badr from Egypt aim in their research to increase the effectiveness of the graphical user interface testing process of mobile applications by proposing an enhanced combinatorial-based metaheuristic approach that has been compared with monkey, frequency, random and greedy approaches. Qusai Y. Shambour, Mosleh M. Abualhaj and Ahmad Adel Abu-Shareha from Jordan propose an effective multi-criteria recommender algorithm for personalized restaurant recommendations by exploiting users’ and items’ implicit similarities to eliminate the sparseness of rating information. Enjoy Reading! Cordially,

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DOI: 10.3897/jucs.100486

Authors: Christian Gütl

Abstract: Dear Readers,I would like to wish you all the best for the new year! It is with great pleasure that I welcome you to our first regular issue in 2023, which contains 4 highly relevant and novel articles on various topics in computer science.Looking back at the past year, we successfully increased our visibility and improved the J.UCS platform by featuring the most frequently accessed articles each month on Pensoft Publishers Ltd.’s ARPHA Publishing Platform. Thanks to the combined efforts of the Pensoft team and the J.UCS publishing team, we are listed and indexed in more than 40 indexing services worldwide, including DOAJ, Web of Science, and Scopus. The increased visibility and social media presence has also led to a further increase in page views and article downloads, with around 45000 unique views, as well as an increasing number of submitted articles and special issue proposals. We are also very pleased to report that the journal's Impact Factor has continued to improve with a Web of Science Impact Factor of 1.056 and a Scopus Science Score of2.7. We are proud to look back on a total of 12 issues with 56 articles by 172 authors from 33 countries on new aspects of various topics in computer science; more precisely, the articles were published in two special issues and ten regular issues.These great achievements were only possible because of the commitment and interest of the community, the valuable support of the Editorial Board, and the support of the members of the J.UCS Consortium. In 2022, we welcomed 12 new Editorial Board members, reaching a total of 189 Editorial Board members. We also gratefully acknowledge the support of 56 guest reviewers during the past year. In particular, I would like to thank Dr. Ulrike Krießmann from the Library of the Graz University of Technology, Prof. Klaus Tochtermann from the ZBW, Prof. Christian Eckhardt from California Polytechnic State University, and Prof. Krzysztof Pietroszek from the American University in Washington DC for their generous support in offering an open content journal without charging the authors for their articles. I would also like to thank the J.UCS team, Johanna Zeisberg for taking care of the publication process, Aleksandar Bobic for his social media support, and Alexander Nussbaumer for his technical support, as well as Pensoft Publishers Ltd. for hosting our journal.I look forward to continuing to work with our editors, editorial team and technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can make J.UCS even better and evolve in the future. We also greatly appreciate the generous support of the J.UCS community, especially in promoting the journal and citing relevant articles in their research papers.In this regular issue, I am very pleased to present 4 accepted articles from 16 authors from 6 different countries.Purvaja Balaji, Helena Merker and Amar Gupta from MIT in the USA introduce in their article an automated, three-step pipeline to solve the challenge of text classification, specifically to automate the labeling of each sentence in an input document consisting of section titles and section text. In a research collaboration between Colombia and Belguim, Oscar I. Caldas, Mauricio Mauledoux, Oscar F. Aviles and Carlos Rodriguez-Guerrero conducted a study to measure objective indicators of engagement while study subjects played an immersive virtual game with DDA to find evidence of dynamic response similar to game performance. Robert Ehrensperger, Clemens Sauerwein und Ruth Breu from University of Innsbruck in Austria present in their article a maturity model for comparing and assessing Digital Business Ecosystems (DBE), which was developed based on the Design Science methodology, the review of 22 scientific publications and the interviews of 28 senior experts. In their joint research between Chile, Japan and Colombia, Matias Salinas, Paul Leger, Hiroaki Fukuda, Nicolas Cardozo, Vannessa Duarte and Ismael Figueroa outline their integrated programming environment Incre-IDLE, specifically designed for first-year students, and an evaluation revealed that it is easier to use for the target group compared to professional IDEs.Enjoy Reading

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DOI: 10.3897/jucs.98885

Authors: Christian Gütl

Abstract: Dear Readers,At the end of this year, it gives me great pleasure to announce the tenth regular issue of 2022. In this issue, various topical aspects of computer science are covered in 4 articles by 10 authors from 4 countries in 4 articles. I would like to thank all the authors for their sound research papers and the editorial board for the highly valuable review effort and comments for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. I am looking forward to continuing my work as Managing Editor-in-Chief with the J.UCS community.In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal.In this regular issue, I am very pleased to introduce the following 4 accepted articles: Nibras Othman Abdulwahid, Sana Fakhfakh and Ikram Amous from Tunisia present their research and proposal for simulating and predicting students’ academic performance based on two models, the seven-subject, one-grade, one-output (SOO) and the seven-subject, twelve-year, seven-output (STS) model. Jorge R. Quiñones and Antonio J. Fernández-Leiva from Spain introduce their approach to automated video gaming parameter tuning based on an extension of XVGDL, a language for specifying video games. Jarashanth Selvarajah and Ruwan Nawarathna from Sri Lanka build an automated drug monitoring and surveillance system for social media based on embedding-level attention, convolutional neural networks (CNN), and bidirectional gated recurrent units (BiGRU). Marko Zekan, Igor Tomičić and Markus Schatten from Croatia discuss their research of an improved Network Intrusion Detection System (NIDS) applying a novel semi-supervised EC-GAN method for network flow classification.Season greetings to all of you, relaxing holidays and ‘Enjoy Reading’!

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DOI: 10.3897/jucs.97859

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the ninth regular issue of 2022. I would like to thank all the authors for their sound research and the editorial board for their extremely valuable reviews and suggestions for improvement. These contributions, together with the generous support of the consortium members and the recognition from the research community, enable us to run our journal and maintain its quality.Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to introduce four accepted papers from 18 authors from six different countries.In a research collaboration between Ecuador, Spain and Argentina, Alexandra Corral, Luis E. Sanchez and Leandro Antonelli focus on improving the software development process to overcome the lack of communication regarding an understanding of the discourse domain and to integrate and process excessive information from different sources using intelligent systems and semantic reasoning. Fatemeh Farnaghi-Zadeh, Mohsen Rahmani and Maryam Amiri from Iran propose an improved approach to feature selection based on targEt PointS To computE neIghborhood relatioNs (EPSTEIN). Zohra Mehenaoui, Yacine Lafifi and Layachi Zemmouri from Algeria present an automatic approach to identifying learning styles based on patterns of learning behavior with respect to the Felder and Silverman Learning Style Model (FSLSM) and report about their study of 73 students enrolled in online courses. Last but not least, in a collaboration between Spain and Italy, Aurora Polo-Rodríguez, Pietro Dionisio, Francesco Agnoloni, Ana Perandrés Gómez, Cristiano Paggetti, Lucía González López, Alfonso Cruz Lendínez, Macarena Espinilla- Estévez and Javier Medina-Quero present their research on ubiquitous and wearable solutions to address active ageing and report about a pilot project implemented for the Andalusian community.

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DOI: 10.3897/jucs.96515

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the eighth regular issue of 2022. In this issue, various topical aspects of computer science are covered by 18 authors from 5 countries in 5 articles. As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal.In this regular issue, I am very pleased to introduce the following 5 accepted articles: Raoua Abdelkhalek, Imen Boukhris, and Zied Elouedi from Tunisia present their research on more trustworthy predictions based on the uncertain framework of belief function theory to support the representation, quantification and management of imperfect evidence. In a research collaboration between Jordan and the USA, Abd Al-Rahman Al-Nounou, Osama Al-Khaleel, Fadi Obeidat, and Mohammad Al-Khaleel present a methodology for designing binary multipliers, in which different sizes of customized partial products generation cells are designed and used as smaller building blocks. Venilton FalvoJr, Anderson da Silva Marcolino, Nemesio Freitas Duarte Filho, Edson OliveiraJr, and Ellen Francine Barbosa present the design, development and experimental evaluation of a software product line for mobile learning applications. Ghazala Hcini, Imen Jdey, and Hela Ltifi from Tunesia introduce their research on a new and robust deep learning model for automatically classifying malaria cells as infected or uninfected, built on a convolutional neural network. And last but not least, Sercan Yalçın, Musa Eşit, and Mehmet İshak Yüce from Turkiye discuss their approach to estimating climatological parameters based on artificial intelligence techniques with particle swarm optimization and deep neural networks.

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DOI: 10.3897/jucs.93582

Authors: Christian Gütl

Abstract: It gives me great pleasure to announce the eighth regular issue of 2022. In this issue, 4 papers cover various topical aspects of computer science by 12 authors from 5 countries. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.As always, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.In the second regular issue, I am very pleased to introduce the following 4 accepted articles: Sanam Fida, Nayyer Masood and Nirmal Tariq from Pakistan, and Faiza Qayyum from the Republic of Korea address in their joint research a novel hybrid ensemble clustering technique for student performance prediction. In a research collaboration between India and Greece, Banani Ghose, Zeenat Rehena and Leonidas Anthopoulos discuss a Deep Learning-based technique for predicting air quality using influencing pollutants of neighboring locations in a smart city environment. Marloes Vredenborg, Daan Sutmuller, Mariëlle den Hengst-Bruggeling, and Judith Masthoff from the Netherlands introduce an exploratory study on a system to reduce information overload and tunnel vision in homicide investigations. And last but not least, Wim Westera from the Netherlands presents three computational scoring models that take into account the number of attempts that a player makes to be successful.Enjoy Reading!

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DOI: 10.3897/jucs.90508

Authors: Christian Gütl

Abstract: Dear ReadersWelcome to the seventh issue in 2022. I am very pleased to announce the journal’s improved Scopus CiteScore of 2.7 and the Web of Science impact factor of 1.056 for 2021, indicating another scientifically successful year. On behalf of the J.UCS team, I would like to thank all the authors for their sound research contributions, the reviewers for their very helpful suggestions, and the consortium members for their financial support. Your commitment and dedicated work have contributed significantly to the long-lasting success of our journal.In this regular issue, I am very pleased to introduce four accepted papers from four different countries and 11 involved authors.Daisy Ferreira Brito, Monalessa P. Barcellos and Gleison Santos from Brazil address in their research a pattern language to support software measurement planning for statistical process control. More specifically, they use the Goal-Question-Metric format and organize it in a Measurement Planning Pattern Language. Ajay Kumar from India presents a hybridized neuro-fuzzy approach for software reliability prediction and validates the proposed approach by applying the neuro-fuzzy method to a software failure dataset. Jesus Serrano-Guerrero, Bashar Alshouha, Francisco P. Romero and Jose A. Olivas from Spain conduct a comparative study of affective knowledge-enhanced emotion detection in Arabic language. Jing Qiu, Feng Dong and Guanglu Sun from China propose and discuss a disassembly method based on a code extension selection network by combining traditional linear sweep and recursive traversal methods.

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DOI: 10.3897/jucs.87156

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the sixth regular issue of 2022. First of all, I would like to welcome all the new members of our editorial board and also express my sincere gratitude to all the members who have recently retired. It is only thanks to the expertise of our editorial board and volunteer guest reviewers, as well as the generous support of the J.UCS consortium and the novel contributions of our authors, that we are able to maintain this high standard and even improve the impact factor over the years.In this issue, various topical aspects of computer science are covered by 12 authors from 5 countries in 4 articles. Stefano Masneri, Ana Domínguez, Mikel Zorrilla, Mikel Larrañaga and Ana Arruarte from Italy present a systematic review of the literature on the use of augmented reality applications in primary and secondary schools, with a specific focus on collaborative, multi-user, and interactive applications. In their article, Julio Cesar Vale Neves, Luiz Enrique Zarate and Mark Alan Junho Song from Brazil describe an approach to add a new data structure, binary decision diagrams (BDD), to the TRIAS algorithm and retrieve triadic concepts for high dimensional contexts. In a collaborative research between Croatia and Ukraine, Igor Tomicic, Markus Schatten, and Vadym Shkarupylo propose an open ontology for self-sustainable human settlements in an effort to find a common language for modeling self-sustainable systems and address issues of heterogeneity of physical devices, protocols, software components, data and message formats, and other relevant factors for the implementation of smart systems. Last but not least, Derya Yiltas-Kaplan from Turkey presents her research on traffic optimization with software-defined network controllers.

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DOI: 10.3897/jucs.86654

Authors: Christian Gütl

Abstract: Dear Readers,I am very happy to announce the fifth regular issue of 2022. In this issue, a variety of topical research aspects of computer science are covered in four articles by 14 authors from 7 countries. Allow me to express my appreciation to all authors for their sound research and to the editorial board for the highly valuable reviews and comments for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the consortium members, sustains the quality of our journal.In the ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal.In the fifth regular issue, I am very pleased to introduce the following 4 accepted articles: María Castañeda, Mercedes G. Merayo, Juan Boubeta-Puig, and Iván Calvo from Spain introduce MODELFY, a novel model-driven solution for designing a decision-making process based on fuzzy automata that allows users to abstract from technical complexities. Natasa Koceska and Saso Koceski from North Macedonia present in their work the design and validation of a low-cost mobile robot system that can assist elderly people and professional caregivers in everyday activities. In a collaborative research between Palestine, the USA, Saudi Arabia and Libya, Thaer Thaher, Mohammed Awad, Mohammed Aldasht, Alaa Sheta, Hamza Turabieh and Hamouda Chantar have developed an enhanced evolutionary-based approach to feature selection using the Grey Wolf Optimizer for classification of high-dimensional biological data. Nikola Zornić and Aleksandar Marković from Serbia present a methodological framework for building a hybrid agent-based model that integrates machine learning algorithms aimed at overcoming some of the elaborated problems related to the use of a utility function.

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DOI: 10.3897/jucs.85545

Authors: Christian Gütl

Abstract: Dear Readers,It gives me great pleasure to announce the third regular issue of 2022. I would like to thank all the authors for their sound research and the editorial board for the extremely valuable reviews and suggestions for improvement. These contributions, together with the generous support of the consortium members, enable us to run our journal and maintain its quality.Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends.In this regular issue, I am very pleased to introduce four accepted papers involving nine authors from four different countries.Sedef Demirci and Seref Sagiroglu from Turkey introduce TwitterBulletin which is a real-time automated news categorization tool for Twitter based on a novel machine learning approach built on a public dataset with a large number of real-world Turkish news tweets. Also in the social media domain, Vitor Garcia dos Santos and Ivandré Paraboni from Brazil apply pre-trained language models to the classification of personalities from texts, focusing specifically on the Myers-Briggs personality model. Mohd Khaled Y. Shambour and Esam A. Khan from the Kingdom of Saudi Arabia discuss in their paper a hyper-heuristic approach to optimize the distribution process of pilgrims over Mina tent camps by selecting one among four predefined low-level heuristics to generate a new one, and discuss solution quality and convergence rate. Nahia Ugarte, Mikel Larrañaga and Ana Arruarte from Spain conduct a systematic mapping review that explores the use of recommender systems in formal learning stages.Enjoy Reading!

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DOI: 10.3897/jucs.82291

Authors: Christian Gütl

Abstract: Dear Readers,It is my great pleasure to announce the second regular issue of 2022. In this issue, various topical aspects of computer science are covered by 17 authors from 6 countries in 5 articles. I would like to thank all the authors for their sound research and the editorial board for the highly valuable review effort and comments for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issues for our journal.In the second regular issue, I am very pleased to introduce the following 5 accepted articles: In a collaborative research between Italy and Ireland, Luca Calderoni, Dario Maio, and Paolo Palmieri compare two probabilistic data structures for association queries derived from the well-known Bloom filter, and extend and optimize the functionality of the shifting Bloom filter, which is applicable to any non-trivial number of subsets. Zeinab Ghasemi-Naraghi, Ahmad Nickabadi and Reza Safabakhsh from Iran focus their research on multi-task learning, more specifically, they introduce a novel multi-task loss function to capture homoscedastic uncertainty in multi regression tasks models without increasing the complexity of the network. Daniel Gómez, Luis Llana and Cristóbal Pareja from Spain present and experimentally review a parallel version of the Brandes algorithm implemented in Spark to compute the betweenness centrality measures. Vít Novotný, Michal Štefánik, Eniafe Festus Ayetiran, Petr Sojka and Radim Řehůřek from the Czech Republic propose and evaluate a constrained positional model that adapts the sparse attention mechanism from neural machine translation to improve the speed of the positional model. Mahmut Ünver, Atilla Ergüzen and Erdal Erdal from Turkey focus their research on an approach based on distributed file systems for managing large amounts of data generated by distance education.

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DOI: 10.3897/jucs.71693

Authors: Rodolfo Medeiros, Sílvio Fernandes, Paulo G. G Queiroz

Abstract: The Internet of Things (IoT) emerged to describe a network of connected things on a large scale to offer services to a large number of applications in different environments and domains. Middleware is software that seeks to facilitate the management and communication of all these things, providing the necessary functionalities to manage things, to discover, to compose services, and perform communication. For this reason, several proposals for middleware solutions for IoT have been developed. In this article, we conducted a systematic review of the literature to bring together middleware solutions for IoT, identifying the requirements and communication protocols used. In addition, we present some gaps and directions for future research in the development of IoT middleware.

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DOI: 10.3897/jucs.80812

Authors: Christian Gütl

Abstract: It is with great pleasure that I welcome you to our first regular issue in 2022, which contains 5 very relevant and new articles on various topics in computer science.Looking back over the past year, we had a successful relaunch of the J.UCS platform hosted by Pensoft Publishers Ltd. on their ARPHA Publishing Platform. Thanks to the combined efforts of the Pensoft team and the J.UCS publishing team, we are listed and indexed in more than 40 indexing services worldwide, including DOAJ, Web of Science, and Scopus. Increased visibility and social media presence have also continued to increase page views and article downloads, as well as the number of articles submitted and special issue proposals. We are also very proud to report that the journal's Impact Factor continued to improve. The Web of Science Impact Factor increased to 1.139 and the Scopus Science Score to 2.0. We are proud to present a total of 12 issues with 64 articles on new aspects of various topics in computer science; more precisely, 40 articles were published in 6 special issues and 24 articles in 6 regular issues. These great achievements were only possible through the commitment and interest of the community, the valuable support of the Editorial Board, and the support of the members of the J.UCS Consortium. In particular, I would like to thank Dr. Ulrike Krießmann from the Library of the Graz University of Technology, Prof. Klaus Tochtermann from the ZBW, Prof. Christian Eckhardt from California Polytechnic State University, and Prof. Krzysztof Pietroszek from the American University in Washington DC for their generous support in offering an open-content journal without charging authors for their articles. I would also like to thank the J.UCS team, Johanna Zeisberg for taking care of the publication process, Aleksandar Bobic for his social media support, and Alexander Nussbaumer for his technical support, as well as Pensoft Publishers Ltd. for hosting our journal.I look forward to continuing to work with our editors, editorial team and technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can make J.UCS even better and develop it further in the future.In this regular issue, I am very pleased to introduce 5 accepted articles from 5 different countries.Roberto Cavicchioli, Riccardo Martoglia and Micaela Verucchi from Italy report on an innovative framework aiming to facilitate the design of advanced Big Data analytics workflows for smart cities. Sébastien Martinez, Christophe Gransart, Olivier Stienne, Virginie Deniau, and Philippe Bon from France focus in their article on aspects of dynamic software updating, specifically they present SoREn - Security REconfigurable Engine – in the context of moving vehicles. In their article, Rodolfo Medeiros, Sílvio Fernandes, and Paulo G. G. Queiroz from Brazil perform a systematic review of the literature to bring together middleware solutions for the Internet of Things, identify the requirements and communication protocols used, and finally point out some gaps and directions for future research in IoT middleware development. Canan Tastimur and Erhan Akin form Turkey focus on the challenging problem of classifying highly similar objects by exploring the Siamese Convolution Neural Network, a similarity measurement-based network, and applying it to classify different types of screws, nuts, and bolts. In a research collaboration between Argentina and Brazil, Florencia Vega, Guillermo Rodríguez, Fabio Rocha and Rodrigo Pereira dos Santos present and discuss Scrum Watch, a tool for monitoring the performance of Scrum-based work teams.

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DOI: 10.3897/jucs.77029

Authors: Ani Vanyan, Hrant Khachatrian

Abstract: Semi-supervised learning is a branch of machine learning focused on improving the performance of models when the labeled data is scarce, but there is access to large number of unlabeled examples. Over the past five years there has been a remarkable progress in designing algorithms which are able to get reasonable image classification accuracy having access to the labels for only 0.1% of the samples. In this survey, we describe most of the recently proposed deep semi-supervised learning algorithms for image classification and identify the main trends of research in the field. Next, we compare several components of the algorithms, discuss the challenges of reproducing the results in this area, and highlight recently proposed applications of the methods originally developed for semi-supervised learning.

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DOI: 10.3897/jucs.66979

Authors: José Monteiro, Maria Bernando, Mafalda Ferreira, Tânia Rocha

Abstract: In democratic countries, government websites became an important channel for interaction with the public administration in the last few years. Nevertheless, several issues have an impact on the way users access to content and information. Lack of accessibility and usability or, in the broad sense, lack of concern with user needs, can still be found in many government websites. To address the problem, a previous literature review on e-government information delivery attributes was performed. Based on this review, a large set of attributes related to quality was obtained to evaluate these dimensions in the context of e-government. The purpose of this study is to better understand which of these attributes are the most valued, in the users’ perspective, for evaluating content delivered by government websites. A qualitative approach was adopted, using Focus Group interviews as a strategy to obtain data and Thematic Analysis to analyze such data. The main results highlighted the attributes related to content delivery, interaction, and emotional aspects. User Experience, accessibility, and usability were prioritized by Focus Group participants.

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DOI: 10.3897/jucs.76797

Authors: Christian Gütl

Abstract: It gives me great pleasure to announce the sixth regular issue of 2021. All this is only possible thanks to the great support of the J.UCS community. Therefore, I would like to thank all the authors for their sound research and the editorial board for the highly valuable reviews and suggestions for improvement. These contributions together with the generous support of the consortium members sustain the quality of our journal.We are always interested in receiving high quality proposals for special issues on new topics and emerging trends. Please consider yourself and encourage your colleagues to submit high quality articles to our journal. I am also still looking to expand our editorial board: If you are a tenured associate professor or higher and have a good publication record, please feel free to apply to join our editorial board.In this regular issue, I am very pleased to introduce six accepted papers contributed by 17 authors from six different countries.Rochdi Boudjehem and Yacine Lafifi from Algeria outline their research on how to identify and assist struggling learners by monitoring and analyzing their behavior within the e-learning environment. Abdelouafi Ikidid, Abdelaziz El Fazziki and Mohammed Sadgal from Morocco introduce a fuzzy logic-based multi-agent system for traffic light control at a signalized intersection by acting on the length and sequence of traffic light phases to favor priority flows and make traffic flow more smoothly at an isolated intersection and for the entire network with multiple intersections. Andrea Lezcano Airaldi, Jorge Andrés Diaz-Pace and Emanuel Irrazábal from Argentina conducted a case study to evaluate the benefits of incorporating data-driven storytelling into the development of a software system to support decision-making in crisis settings. José Monteiro, Maria Bernardo, Mafalda Ferreira, and Tânia Rocha from Portugal discuss their study of quality aspects of e-government information with the goal of better understanding which of these attributes are most valued from the users’ perspective when evaluating content provided by government websites. Ricardo Pérez- Castillo and Mario Piattini from Spain outline their study on how the evolution of the development effort influences the code quality, which was analyzed on 13 open source projects. Hamda Slimi, Ibrahim Bounhas and Yahya Slimani from Tunisia discuss their approach, which aims to detect emerging and unseen rumors on Twitter by adapting a pre-trained language model, namely RoBERTa, to the task of rumor detection.

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DOI: 10.3897/jucs.75354

Authors: Christian Gütl

Abstract: Dear Readers,Welcome to the ninth issue in 2021. I am very pleased to mention that the access statistics show a steady growth and also the interest in our journal is increasing. This success is only possible because of the great support from all of you. Thus, on behalf of the J.UCS team, I would like to thank all authors for their sound research contributions, the reviewers for their very helpful suggestions, and the consortium members for their financial support. Your commitment and dedicated work have contributed significantly to the overall success of J.UCS.In this regular issue, I am very pleased to present three accepted papers from five different countries and 10 involved authors.Armando Cruz, Hugo Paredes, Leonel Morgado and Paulo Martins from Portugal investigate in their work non-verbal aspects of collaboration in virtual worlds in the context of the presence dimension. In a collaborative research between Chile and Japan, Paul Leger, Hiroaki Fukuda and Ismael Figueroa present a JavaScript package that allows developers to write event handlers that need nested callbacks in a synchronous style, avoiding the so-called ‘callback hell’. In another collaboration between Indonesia and the UK, Riri Fitri Sari, Asri Samsiar Ilmananda, and Daniela M. Romano discuss their research on a social trust-based blockchain-enabled social media news verification system.Enjoy Reading!

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DOI: 10.3897/jucs.70129

Authors: Christian Gütl

Abstract: Dear Readers,Welcome to the sixth issue in 2021. I am very pleased to announce the journals’ Scopus CiteScore of 2.0 for 2020, indicating another scientifically successful year. On behalf of the J.UCS team, I would like to thank all authors for their sound research contributions, the reviewers for their very helpful suggestions and the consortium members for their financial support. Your commitment and dedicated work have strongly contributed to the long-lasting success of our journal. In this regular issue, I am very pleased to introduce 5 accepted papers from 17 authors of 6 different countries. Edinelço Dalcumune, Luis Antonio Brasil Kowada, André da Cunha Ribeiro, Celina Miraglia Herrera de Figueiredo and Franklin de Lima Marquezino from Brazil present in their article a new algorithm for the synthesis of reversible circuits for arbitrary n-bit bijective functions using generalized Toffoli gates, which include positive and negative controls. Murat Firat, Derya Yiltaş-Kaplan and Ruya Samli introduce their work on a machine learning method – including Artificial Neural Network (ANN), Linear Regression (LR) and Gradient Boosting (GB) – for determining optimal seat capacity that can supply the highest load factor for the flight operation between any two countries. In a collaborative research between Switzerland, China and the Netherlands Fabian Honegger, Yuan Feng and Matthias Rauterberg have investigated effects of visual, auditory, vibration and draught stimuli on the sense of presence within a virtual environment. Julio Moreno, David G. Rosado, Luis E. Sánchez, Manuel A. Serrano and Eduardo Fernández-Medina from Spain discuss in their research a security reference architecture for cyber-physical systems. Adem Tuncer from Turkey introduces a new approach based on an Artificial Bee Colony Algorithm for solving the 15-puzzle problem. Enjoy Reading! Cordially,Christian Gütl, Managing Editor

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DOI: 10.3897/jucs.66455

Authors: Fairouz Fakhfakh, Slim Kallel, Saoussen Cheikhrouhou

Abstract: Cloud and Fog computing have been widely recognized as attractive solutions in both academic and industrial sectors. Despite their benefits, the adoption of Cloud and Fog computing still have considerable challenges to be handled due to the increase of client requirements. A crucial issue, in this context, is how to verify the correctness of Cloud and Fog systems. The use of formal methods is an efficient mean which provides a real help for the designer to evaluate the behaviour of a system and prevent errors before its implementation. In this paper, we present a systematic literature review (SLR) on the current state of the art in this field. We collect the existing studies on the use of formal methods for proving the correctness of Cloud and Fog systems. The proposed approaches are compared based on some technical properties such as the verification methods, the verification tools, the considered properties, and the application domains. In addition, future directions which need more investigations are presented. We believe that our paper will be useful for industry and academic researchers to understand the existing contributions that deal with the cor- rectness of Cloud and Fog systems. Moreover, it helps them to address several gaps in the literature.

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DOI: 10.3897/jucs.67831

Authors: Christian Gütl

Abstract: I am pleased to announce the fourth issue of 2021. As always, I would like to express my sincere appreciation for the great support that makes the continued publication of novel and high quality articles possible. Thus, I would like to thank all authors for their sound research contributions, the reviewers for their very helpful suggestions and the consortium members for their financial support.I would also like to report on further achievements regarding our new platform. We have successfully migrated all the information of the Board of Editors and we have also started to use the new review module. Due to the cooperation with Pensoft Inc., our new platform provider, we will also be able to offer review acknowledgment on the Publons portal in the future.In this regular issue, I am very pleased to introduce four accepted papers from three different countries and 14 involved authors.Martin Berglund, Brink van der Merwe, and Steyn van Litsenborgh from South Africa investigate in their article regular expressions which contain lookaheads in addition to the standard operators of union, concatenation, and Kleene star. Fairouz Fakhfakh, Slim Kallel and Saoussen Cheikhrouhou from Tunisia research and discuss in their work a crucial issue in modern distributed information systems, i.e. how to verify the correctness of Cloud and Fog systems based on formal verification. Marcia Henke, Eulanda Santos, Eduardo Souto, and Altair O. Santin from Brazil introduce their enhanced spam detection system which is based on analyzing the evolution of features. And finally, also from Brazil, Marcelo Aires Vieira, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, and Babacar Mane investigate the challenging problem of integrating heterogeneous DaaS and DBaaS sources and explore the Data Join (DJ) method for integrating heterogeneous data.

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DOI: 10.3897/jucs.67025

Authors: Christian Gütl

Abstract: It gives me a great pleasure to announce the second regular issue of 2021. I want to thank all authors for contributing their sound research and the editorial board for the highly valuable reviews and comments for improvements. These contributions together with the generous support of the consortium members sustain the quality of our journal.I would still like to expand our editorial board: If you are a tenured Associate Professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high quality proposals for special issues covering new topics and emerging trends. Please think of yourself and encourage your colleagues to submit high quality articles to our journal.In this regular issue, I am very pleased to introduce three accepted papers from three different countries.Alessia D’Andrea, Maria Chiara Caschera, Fernando Ferri, and Patrizia Grifoni from Italy introduce in their research MuBeFE, a Multimodal Behavioural Features Extraction Method based on Hidden Markov Models, which allows to extract information such as communicative intention, the social style and personality traits. Güldem Alev Özkök from Turkey aims in her research to model the process of data visualization (DV) and design to facilitate computational thinking (CT) of secondary- level students. Uyara Ferreira Silva and Deller James Ferreira from Brazil present a systematic literature review based on 400 articles of the literature on productive dialogues and emotional aspects in Computer-Supported Collaborative Learning (CSCL), and they also address emotional aspects used in debates with conflicting points of view in other contexts.

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DOI: 10.3897/jucs.64594

Authors: Nelson Baloian, José A. Pino, Gustavo Zurita, Valeria Lobos-Ossandón, Hermann Maurer

Abstract: The Journal of Universal Computer Science is a monthly peer-reviewed open-access scientific journal covering all aspects of computer science, launched in 1994, so becoming twenty-five years old in 2019. In order to celebrate its anniversary, this study presents a bibliometric overview of the leading publication and citation trends occurring in the journal. The aim of the work is to identify the most relevant authors, institutions, countries, and analyze their evolution through time. The article uses the Web of Science Core Collection citations and the ACM Computing Classification System in order to search for the bibliographic information. Our study also develops a graphical mapping of the bibliometric material by using the visualization of similarities (VOS) viewer. With this software, the work analyzes bibliographic coupling, citation and co-citation analysis, co-authorship, and co-occurrence of keywords. The results underline the significant growth of the journal through time and its international diversity having publications from countries all over the world and covering a wide range of categories which confirms the “universal” character of the journal.

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DOI: 10.3897/jucs.64585

Authors: Christian Gütl

Abstract: Dear Readers,It is a great pleasure for me to welcome you to our first regular issue in 2021 covering 3 very relevant and novel articles in various computer science topics.There are also many news and changes with the beginning of the new year that I am excited to report on and share. To start with, we are very happy to welcome two new consortium members and editors-in-chief: California Polytechnic State University San Luis Obispo represented by Prof. Christian Eckhardt from the Department of Computer Science & Software Engineering and the Institute for IDEAS at American University in Washington DC represented by Prof. Krzysztof Pietroszek. On the management side of J.UCS, Dana Kaiser has retired at the end of last year, and on behalf of the journal I want to gratefully thank Dana for her devoted and great work since the foundation of this journal. I also want to give Johanna Zeisberg a warm welcome who will take over the role as Publishing Manager and collaborate and support the whole J.UCS community. On the technical side, our journal has moved to another submission and publishing platform. Since the foundation of J.UCS more than 25 years ago, the journal has offered readers, authors and editors various novel features over the course of the years. In this perspective but also in terms of the visionary view of founding a freely accessibly online journal, I want to express our deep gratitude for the contributions of Prof. Hermann Maurer to the success of J.UCS for almost 20 years. Since beginning of 2021, J.UCS is hosted by Pensoft Publishers Ltd. on the ARPHA Publishing Platform. This allows us not only to offer state-of-the-art publishing features but also to make use of integrated long-time archiving systems and various indexing services. In this context I also want to thank Internet Studio Isser and Photographer Christian Trummer for the kind support in the development of the design update and the J.UCS images.In this first issue of the year, I also want to look back on the journal’s achievements in 2020. We are proud to report a total of 11 issues with 74 articles on novel aspects of various topics in computer science; to be more specific, 51 articles have been published in 7 special issues and 23 articles in 4 regular issues. Since last year, J.UCS publishes under the open access Creative Commons License CC BY-ND 4.0 and therefore provides even more value und openness to a broader community. In 2020, we counted more than 87 thousand unique visits and almost 65 thousand paper downloads. This success is only possible due to the great support of the involved institutions, reviewers and authors, and I want to gratefully thank them all for their valuable support and work. Over the years we have not only offered readers open access to our high-quality journal, but we also do not charge our authors publication fees. This adventurous approach together with a rigorous review process and a broad support by the community resulted in a valuable contribution in the field of computer science, which is reflected in the high number of unique visitors and article downloads. In this context I gratefully thank all consortium members for their financial support of J.UCS.I am looking forward to continuing the cooperation with our editors, the editorial team and the technical support to maintain the success of J.UCS. I would be very grateful for suggestions and feedback on how we can even improve and develop J.UCS in the future.In this regular issue, I am very pleased to introduce 3 accepted papers from 5 different countries.On the occasion of the 25th anniversary of the J.UCS journal, Nelson Baloian, José A. Pino, Gustavo Zurita, Valeria Lobos-Ossandón, and Hermann Maurer analyze and discuss a bibliometric overview of the first 25 years of the journal in their collaboration between Austria and Chile. In a collaborative research between China and Spain, Xin Liu, Xiaoying Song, Wei Gao, Li Zou, and Alvaro Labella Romero report on their decision making approach based on hesitant fuzzy linguistic-valued credibility reasoning. And finally, Christian Moreira Matos, Vitor Kehl Matter, Marcio Garcia Martins, Joao Elison Da Rosa Tavares, Alexandre Sturmer Wolf, Paulo Cesar Buttenbender, and Jorge Luis Victoria Barbosa from Brazil discuss a collaborative model to assist people with disabilities and the elderly people in smart assistive cities.Enjoy Reading!

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DOI: 10.3897/jucs.2020.055

Authors: Dennis Beck, Leonel Morgado, Patrick Shea

Abstract: Advancing the field of research in Immersive Learning Environments requires avoiding the pitfalls of previous educational technologies. Studies must consider the actual use of these environments and the context where it occurs, not simply the technocentric perspectives on these environments. This paper provides an overview and analysis of surveys on this topic, in order to map the field and find out which information on actual uses of Immersive Learning Environments are reported, and hence which gaps need to be covered towards a robust, encompassing knowledge on their relationship with learning. Collected accounts of use were clustered via thematic analysis and contrasted with research areas in learning and technology, highlighting the gaps in the field and serving as a blueprint for research agendas on uses of immersive learning environments.

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DOI: 10.3897/jucs.2020.042

Authors: Damjan Fujs, Simon Vrhovec, Damjan Vavpotič

Abstract: Information systems are pervasive in organizations of all sizes. To use them securely, users must be properly trained. Because of the pervasiveness of information systems the number of scientific publications reporting on user training for secure use of information systems is increasing year by year. To overcome the issue of manually surveying such a vast body of knowledge and to keep up with research trends, we conducted bibliometric mapping of research on user training for secure use of information systems. A total of N = 1955 records published between 1991 and 2019 were retrieved from the Web of Science bibliographic database on 21 November 2019. Top contributing authors, organizations, countries and research field were identified with the Web of Science built-in results analysis tool. Additionally, keyword mapping was performed with VOSviewer software. The analysis of the network and overlay keyword maps revealed six clusters: healthcare, technology adoption, management, information security, technical solutions and physical security. The results of this study suggest attractive research directions to be pursued in the future, such as information security training in healthcare and individualized user training alternatives to one-size-fits-all user training approach.

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DOI: 10.3217/jucs-025-06-0611

Authors: Dominik Pieczyński, Marek Kraft, Michał Fularz

Abstract: In this paper, a method for improving the quality of person re-identification results is presented. The method is based on the assumption, that including segmentation information into re-identi_cation pipeline discards the automated detections that are of poor quality due to occlusions, misplaced regions of interest (ROI), multiple persons found within a single ROI, etc. using a simple segment number, bounding box fill rate and aspect ratio check. Assuming that a joint detector-segmented approach is used, the additional cost associated with the use of the proposed approach is very low.

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DOI: 10.3217/jucs-023-12-1113

Authors: Murat Topaloglu, Dilek Kırar

Abstract: The BYOD programme is a trend that aims to provide companies and workers with the next generation of security methods and flexible business models. These have been developed recently as a result of technological developments, especially in smart devices. Individuals from the "Y generation", who are also called the millennials, have a significant influence on shaping the present and future technology. Y generation employees want to use their own devices, including their own personal applications. Allowing employees to use their own devices does not mean that you will lose anything or have no control. For this reason, the BYOD policy, when implemented at a good level, significantly increases business performance and increases the productivity with the benefits provided by mobility. The BYOD tendency, which is difficult to avoid, increases the productivity of employees and the flexibility of the company in the eyes of the employees, by letting them use their own devices in the business environment. Moreover, it reflects positively on the employees' morale, with a subsequent increase in company loyalty. The aim of this study is to evaluate the validity and reliability analyses done during the development of the scale which aims to measure the effects of BYOD on workers and to assess its security components, benefits, applicability and sustainability. Our goal is to revise the previous research done and present objective values and findings obtained from the analyses. These values were based on the demographic information and the answers given by participants about to what extent BYOD is known and legal, its vulnerabilities in infrastructure and data security, the way it affects workers' perceptions individually and in general, and the benefits it provides. SPSS 20 program was used for descriptive statistics, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), item analyses and correlation coefficients.

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DOI: 10.3217/jucs-022-02-0161

Authors: J. Agudo, Mercedes Rico, Héctor Sánchez

Abstract: The increasing popularity of hypermedia games is reaching far beyond the boundaries of entertainment and edging its way into many educational domains. The growth in game technologies has created new teaching environments through proposals combining learning with fun and motivating expectations which make the use of digital games a relevant trend in versatile learning situations at all educational levels. Based on the implementation of the Shaiex project, funded by the government of Extremadura (Spain) and develop by the research group GexCALL, the aim of this paper is twofold. First, it analyses the steps and requirements for the design of adaptive games for the teaching of English as a foreign language at the preschool level. Exploring the general premises for task adaptation by personalizing content to children's needs and abilities, the implementation of the whole design is described in light of its applicability. Second, an assessment of the adaptive games designed is conducted, based on the assumption that selecting developmentally appropriate digital experiences to meet users' expectations and to maximize their learning potential should undergo careful evaluation.

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DOI: 10.3217/jucs-021-02-0268

Authors: Mehri Rajaei, Mostafa Haghjoo, Eynollah Miyaneh

Abstract: A well-known privacy-preserving network data publication problem focuses on how to publish social network data while protecting privacy and permitting useful analysis. Designing algorithms that safely transform network data is an active area of research. The process of applying these transformations is called anonymization operation. The authors recently proposed the (?,?,?,?)-SNP (Social Network Privacy) model and its an anonymization technique. The present paper introduces a novel anonymization algorithm for the (?,?,?,?)-SNP model. The desirability metric between two individuals of social network is defined to show the desirability of locating them in one group keeping in mind privacy and data utility considerations. Next, individuals are grouped using a greedy algorithm based on the values of this metric. This algorithm tries to generate small-sized groups by maximizing the sum of desirability values between members of each group. The proposed algorithm was tested using two real datasets and one synthetic dataset. Experimental results show satisfactory data utility for topological, spectrum and aggregate queries on anonymized data. The results of the proposed algorithm were compared in the topological properties with results of two recently proposed anonymization schemes: Subgraph-wise Perturbation (SP) and Neighborhood Randomization (NR). The results show that the proposed method is better than or similar to SP and NR for preservation of all structural and spectrum properties, except for the clustering coefficient.

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DOI: 10.3217/jucs-020-15-1995

Authors: Chien-Wen Shen, Shih-Hsuan Chu

Abstract: Given the increasingly important role social networking services play as sources of information during disasters, this study aims to investigate how the municipal governments and their emergency agencies employed RSS or Atom, webcast, Facebook, Twitter, YouTube, and photo-sharing platforms in the major U.S. cities. Our findings show that the emergency agencies of San Diego, Los Angeles, and San Jose are the top 3 performers on the Web 2.0 services. Regarding the social networking services provided by municipal emergency agencies, New York, Los Angeles, and Philadelphia rank among the top 3 cities. While San Diego city government and its emergency agencies provide the most number of Web 2.0 channels, New York City and its emergency agencies have the highest number of services in Facebook, Twitter, YouTube, and photo-sharing platforms (Flickr, Pinterest, and Instagram). Because big cities can support better collaboration and communication during crisis if they provide more services on social networking services, under-performing cities can enhance their services by learning from the top-performing cities such as San Diego or New York City.

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DOI: 10.3217/jucs-020-02-0135

Authors: Johan Fabry, Romain Robbes, Marcus Denker

Abstract: Integrated development environments (IDEs) have become the primary way to develop software. Besides just using the built-in features, it becomes more and more important to be able to extend the IDE with new features and extensions. Plugin architectures exist, but they show weaknesses related to unanticipated extensions and event handling. In this paper, we argue that a more general solution for extending IDEs is needed. We present and discuss a solution, motivated by a set of concrete examples: a domain specific aspect language for IDE events. In it, join points are events of interest that may trigger the advice in which the behavior of the IDE extension is called. We show how this allows for the development of IDE plugins and demonstrate the advantages over traditional publish/subscribe systems.

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DOI: 10.3217/jucs-018-20-2748

Authors: Lutz Prechelt

Abstract: In September 1997, J.UCS published an article titled "Why we Need an Explicit Forum for Negative Results" [Prechelt, 1997]. It argued that when a plausible approach for solving a computer science or software engineering problem had failed to work out, it was silly for the scientific system not to publish the attempt iff a useful insight had been gained along the way nevertheless. Due to the strong bias of essentially all Computer Science publication venues towards "successful" research results, it was thus required to call for such negative results explicitly in order to avoid that those results would either be misleadingly disguised as successes or disappear in some closet. The article declared that J.UCS had thus agreed to create the "Forum for Negative Results (FNR)" as a permanent special section of J.UCS.

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DOI: 10.3217/jucs-018-16-2334

Authors: Javier Melero, Davinia Hernández-Leo, Josep Blat

Abstract: Information and Communication Technology (ICT) engineering education is facing a decreasing interest by students. To deal with this issue, a need for shifting from traditional learning approaches to constructivist methods has been identified. Several pedagogical methodologies based on social and constructivist theories are being applied to engage students in ICT education. This paper presents a literature review of studies carried out from 2000 to 2010 that have applied constructivist learning methods with supportive tools to specific ICT areas. From the analysis of the literature review this paper identifies the most representative constructivist learning methods within the field of ICT education. In particular, we pay attention to the educational tooling used to support the learning process and the learning benefits of applying such methods. The analysis also reveals that different combinations of guidance approaches and tooling implementations are often adopted to scaffold the learning process. With the aim of understanding to what extent and how scaffolding is present in the studied learning scenarios, this document proposes a definition of different types of scaffolding techniques. Namely: social-guidance and system-guidance scaffolding, depending on whether an individual or a tool is the responsible for providing support to students; macro-scaffolding when pedagogical methods define activity flows, or micro-scaffolding when the support is provided to perform specific actions within activities; and tool-enveloped scaffolding, when a generic tool such a learning management system scaffolds the learning process by the integration of different supportive tools, and tool-embedded scaffolding when the scaffolding is applied within a specific-purpose tooling.

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DOI: 10.3217/jucs-018-09-1072

Authors: Hongyu Huang, Daqiang Zhang, Yanmin Zhu, Minglu Li, Min-You Wu

Abstract: The past few years have witnessed the growing interest in vehicular ad hoc networks(VANETs) and their potential applications for Internet of Things (IoT). Since the mobility model is crucial to simulation based researches of VANET, using a realistic mobility model can ensurethe consistency between simulation results and real deployments. Although there are many mobility models characterizing the movement of mobile nodes, none of them consider the behaviorof vehicles in a metropolitan scenario. In this paper, we present our study of extracting a mobility model for VANET from a large amount of real taxi GPS trace data. In order to capture charac-teristics of the urban vehicle network from microscopic to macroscopic aspects, we design three parameters and extract their values from the GPS trace data. Using this mobility model, we cangenerate the synthetic trace to simulate the movement of taxis in the urban area of a metropolis. The validation is carried through extensive comparisons between the synthetic trace and the realtrace. The results show that our mobility model has a good approximation with the real scenario.

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DOI: 10.3217/jucs-018-03-0377

Authors: Paolo Ferri, Andrea Pozzali

Abstract: The current debate on the potential for change that the development of social media can bring to education seems to be based more on general and theoretical considerations than on systematic data. In order to contribute to the development of a more informed perspective, in this paper we present empirical evidence gathered from a 2008 and 2009 survey on undergraduate students at the University of Milan-Bicocca, concerning students' attitudes toward traditional and new media. In particular, we focus here on data concerning the diffusion of some specific tools and services that are commonly meant to represent the most important features of the "collaborative web". The comparison of the results obtained in the two surveys allows us to make some reflections on the path of diffusion of social media among young university students and to critically review their actual significance in an educational perspective.

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DOI: 10.3217/jucs-017-12-1673

Authors: Michele Brocco, Florian Forster, Marc Frieß

Abstract: Open Innovation is a new paradigm that suggests including actors from inside as well as outside a company's boundaries in the innovation process. Open creativity refers to the creative phase in this process. In this article we investigate on open creativity support. We conducted interviews within companies in the German ICT sector to analyze the status quo of open creativity and the tools currently used to support it. In a second step we derive design guidelines and an architecture for IT systems supporting open creativity that lead to a holistic, 360ffi support for open creativity.

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DOI: 10.3217/jucs-017-10-1367

Authors: Rainer Erne

Abstract: Experts in specific professional domains form the fastest increasing workforce in OECD countries. Since this fact has been realised by management researchers, they have focussed on the question of how to measure and enhance the productivity of said workforce. According to the author's cross-industrial research undertaken in five different knowledge-intensive organisations, it is, however, not productivity in the traditional meaning of the term which is to be regarded as the crucial performance indicator in expert work. There rather exist multiple performance indicators, each of which is, moreover, differently graded as to its importance by different stakeholders. These findings, firstly, indicate the need for an alternative definition and way of measurement of productivity when the term is applied to knowledge work, and, secondly, they indicate the need for alternative management strategies in order to generate an increase in the productivity of knowledge workers. This paper describes and summarises the key performance indicators for expert work as well as the major 'managing forces' and their general strategies in assessing knowledge workers' performance across five different business segments. It further delineates consequences for the management of knowledge workers - consequences affecting various 'knowledge-intensive' industries.

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DOI: 10.3217/jucs-016-13-1761

Authors: Kichan Nam, Nam Lee

Abstract: This study provides a conceptual framework with respect to service innovation, especially from a service-dominant logic (S-D logic) perspective. Even though innovation has been discussed as one of the most critical elements in enhancing the competitiveness of service industry, it was not clear how service innovation should be different from diverse types of existing innovation. The S-D logic provides a novel and valuable theoretical perspective that unifies the conventional literature on innovation. According to this new logic, four types of service innovation are presented based on two dimensions: the degree of co-creation and the degree of networked collaboration. We argue that service innovation can arise by the activity of value co-creation between firm and customer on the first dimension. On the second dimension, the firm needs to enhance their own capabilities for service innovation by applying the resources of all actors including suppliers and customers. Our framework indicates that it is critical for productive service innovation to make customers participate in value creation process and to integrate the dispersed resources held by participants. Examples are discussed with respect to different types of services innovation.

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DOI: 10.3217/jucs-016-13-1720

Authors: Lei Li, Yan Wang, Ee-Peng Lim

Abstract: In Service-Oriented Computing (SOC) environments, service clients interact with service providers for consuming services. From the viewpoint of service clients, the trust level of a service or a service provider is a critical factor to consider in service selection, particularlywhen a client is looking for a service from a large set of services or service providers. However, a invoked service may be composed of other services. The complex invocations in composite services greatly increase the complexity of trust-oriented service selection. In this paper, we propose novel approaches for composite service representation, trust evaluation and trust-oriented com-posite service selection (with QoS constraints). Our experimental results illustrate that compared with the existing approaches our proposed trust-oriented (QoS constrained) composite serviceselection algorithms are realistic and enjoy better efficiency.

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DOI: 10.3217/jucs-016-09-1152

Authors: James Decraene, Thomas Hinze

Abstract: All processes of life are controlled by networks of interacting biochemical components. The purpose of modelling these networks is manifold. From a theoretical point of view it allows the exploration of network structures and dynamics, to find emergent properties or to explain the organisation and evolution of networks. From a practical point of view, in silico experiments can be performed that would be very expensive or impossible to achieve in the laboratory, such as hypothesis-testing with regards to knock-out experiments or overexpression, or checking the validity of a proposed molecular mechanism. The literature on modelling biochemical networks is growing rapidly and the motivations behind different modelling techniques are sometimes quite distant from each other. To clarify the current context, we review several of the most popular methods and outline the strengths and weaknesses of deterministic, stochastic, probabilistic, algebraic and agent-based approaches. We then present a comparison table which allows one to identify easily key attributes for each approach such as: the granularity of representation or formulation of temporal and spatial behaviour. We describe how through the use of heterogeneous and bridging tools, it is possible to unify and exploit desirable features found in differing modelling techniques. This paper provides a comprehensive survey of the multidisciplinary area of biochemical networks modelling. By increasing the awareness of multiple complementary modelling approaches, we aim at offering a more comprehensive understanding of biochemical networks.

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DOI: 10.3217/jucs-016-08-1056

Authors: Manuel J. Fernández Iglesias, Luis M. Álvarez Sabucedo

Abstract: Europe is currently transitioning to digital terrestrial television and isaimed to replace all analog infrastructures by 2012. Besides replacing all broadcasting networks in Europe, the transition requires updating household televisions andantennas. As with any major change, public administrations must keep citizens informed and provide support, especially when dealing with a communication mediumexpected to support a new portfolio of services and information. State-of-the-art technologies enable universal coverage in locations where television services are currentlyunavailable. This paper evaluates the transition to digital television in several European regions and analyzes novel approaches and solutions to achieving universal accessto digital television and citizen awarenes.

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DOI: 10.3217/jucs-015-05-0970

Authors: Pablo Najera, Francisc Moyano, Javier López

Abstract: Traditional paper documents are not likely to disappear in the near future as they are present everywhere in daily life, however, paper-based documentation lacks the link with the digital world for agile and automated processing. At the same time it is prone to cloning, alteration and counterfeiting attacks. E-passport defined by ICAO and implemented in 45 countries is the most relevant case of hybrid documentation (i.e. paper format with electronic capabilities) to date, but, as the advantages of hybrid documentation are recognized more and more will undoubtedly appear. In this paper, we present the concept and security requirements of general-use e-documents, analyze the most comprehensive security solution (i.e. ePassport security mechanisms) and its suitability for general-purpose e-documentation. Finally, we propose alternatives for the weakest and less suitable protocol from ePassports: the BAC (Basic Access Control). In particular, an appropriate key management infrastructure for access control to document memory is discussed in conjunction with a prototype implementation.

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DOI: 10.3217/jucs-014-16-2599

Authors: Toni Granollers, Cesar Collazos, María González

Abstract: Human-Computer Interaction (HCI) is a challenging discipline that is currently concerned with the design, implementation and evaluation of interactive systems for human use, as well as the study of major phenomena surrounding them. Indeed, interdisciplinary communities formed by scientists, university teachers and students, people coming from the industry and customers related to HCI are emerging in different parts of the world. In particular, this article overviews the HCI community in the Ibero-American context, which involves hundreds of millions of people working or studying in HCI, whose cultural background is primarily associated with the Spanish and Portuguese languages and cultures, regardless of ethnic and geographical differences. Our final goal is to improve the visibility of this particular HCI community, enhancing the self awareness of its members and their individual motivation and future exchanges.

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DOI: 10.3217/jucs-014-04-0526

Authors: Claudia Müller, Benedikt Meuthrath, Anne Baumgraß

Abstract: Increasingly wikis are used to support existing corporate knowledge exchange processes. They are an appropriate software solution to support knowledge processes. However, it is not yet proven whether wikis are an adequate knowledge management tool or not. This paper presents a new approach to analyze existing knowledge exchange processes in wikis based on network analysis. Because of their dynamic characteristics four perspectives on wiki networks are introduced to investigate the interrelationships between people, information, and events in a wiki information space. As an analysis method the Social Network Analysis (SNA) is applied to uncover existing structures and temporal changes. A scenario data set of an analysis conducted with a corporate wiki is presented. The outcomes of this analysis were utilized to improve the existing corporate knowledge processes.

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DOI: 10.3217/jucs-014-04-0508

Authors: Ronald Maier, Stefan Thalmann, Florian Bayer, Michael Krüger, Hendrik Nitz, Alexander Sandow

Abstract: Even though knowledge management has been around for more than a decade, so far concrete instruments that can be systematically deployed are still rare. This paper presents an optimization solution targeted at flexible management of office space considering knowledge management criteria in order to enhance knowledge work productivity. The paper presents the Flexible Office conceptual model and optimization solution. It discusses the theoretical foundation, assumptions and reasoning. A corresponding prototype was field-tested, successfully introduced, evaluated with the help of a series of interviews with users and improved according to their requirements. The paper also reflects on the organizational impact and lessons learned from field test and practical experience.

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DOI: 10.3217/jucs-013-06-0721

Authors: Leandro De Freitas, Marcel Caraciolo, Márcio Cornélio

Abstract: Programming laws are a means of stating properties of programming con-structs and resoning about programs. Also, they can be viewed as a program transformation tool, being useful to restructure object-oriented programs. Usually the appli-cation of a programming law is only allowed under the satisfaction of side-conditions. In this work, we present how the conditions associated to object-oriented program-ming laws are checked by using Prolog. This is a step towards a tool that allows user definable refactorings based on the application of programming laws.

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