Latest Articles from JUCS - Journal of Universal Computer Science Latest 100 Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Thu, 28 Mar 2024 17:58:38 +0200 Pensoft FeedCreator https://lib.jucs.org/i/logo.jpg Latest Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Design and Evaluation using Technology Acceptance Model of an Architecture Conceptualization Framework System based on the ISO/IEC/IEEE 42020 https://lib.jucs.org/article/104938/ JUCS - Journal of Universal Computer Science 29(12): 1510-1534

DOI: 10.3897/jucs.104938

Authors: Valdicélio Santos, Michel S. Soares

Abstract: Among the difficulties in developing software-intensive systems are the necessity of managing and controlling data that must be held for decades, as well as describing the needs and concerns of a variety of stakeholders. Therefore, one cannot neglect a good Software Engineering practice which is to develop software-intensive systems based on solid software architecture. However, the processes related to the software architecture of software-intensive systems are often considered only from a low level of abstraction. A recent architectural Standard, the ISO/IEC/IEEE 42020, defines 6 clauses for the architecture process, among them the Architecture Conceptual-ization process is the subject of this study. Considering that the ISO/IEC/IEEE 42020 has only recently been published, given the importance of establishing a well-defined software architecture, and considering the difficulties of understanding an architectural Standard, this work proposes a framework, and then the design and further evaluation of a web-based application to support soft-ware architects in using the activities and tasks of the Architecture Conceptualization clause based on the framework described. The ArchConcept was designed to address the high-level abstraction of the Standard ISO/IEC/IEEE 42020 and can be useful for software architects who want to follow ISO/IEC/IEEE 42020’s recommendation and achieve high-quality results in their work of software architecture conceptualization. A qualitative evaluation employing a questionnaire was carried out to obtain information about the perceptions of professionals regarding the ArchConcept, according to the Technology Acceptance Model (TAM). As ArchConcept is focused on activities of Archi-tecture Conceptualization, which is one of the early stages of a software project, the results found could be evidence of the short time dedicated to the initial phases of projects and their consequences.regarding the ArchConcept, according to the Technology Acceptance Model (TAM). As ArchConcept is focused on the early stages of the project (Architecture Conceptualization), the results found in this work could be evidence of the short time dedicated to the initial phase of projects and their consequences.

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Research Article Thu, 28 Dec 2023 08:00:06 +0200
OntoFoCE and ObE Forensics. Email-traceability supporting tools for digital forensics https://lib.jucs.org/article/97822/ JUCS - Journal of Universal Computer Science 29(12): 1482-1509

DOI: 10.3897/jucs.97822

Authors: Herminia Beatriz Parra de Gallo, Marcela Vegetti

Abstract: This paper shows the research conducted to respond to a continuous requirement of justice regarding the application of scientifically supported forensic tools. Considering ontological engineering as the appropriate framework to respond to this requirement, the article presents OntoFoCE (Spanish abbreviation for Ontology for Electronic Mail Forensics), a specific ontology for the forensic analysis of emails. The purpose of this ontology is to help the computer expert in the validation of an email presented as judicial evidence. OntoFoCE is the fundamental component of the ObE Forensics (Ontology-based Email Forensics) tool. Although there are numerous forensic tools to analyze emails, the originality of the one proposed here lies in the implementation of semantic technologies to represent the traceability of the email transmission process. From that point on, it is possible to provide answers to the items of digital evidence subject to the expert examination. These answers make it possible to support these evidence items in the forensic analysis of an email and to guarantee the gathering of scientifically and technically accepted results that are valid for justice. Thus, the research question that is tried to be answered is: Is it possible to apply ontological engineering as a scientific support to design and develop a forensic tool that allows automatic answers to the evidence items subject to the expert examination in the forensic analysis of emails?

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Research Article Thu, 28 Dec 2023 08:00:05 +0200
Towards a Traceable Data Model Accommodating Bounded Uncertainty for DST Based Computation of BRCA1/2 Mutation Probability With Age https://lib.jucs.org/article/112797/ JUCS - Journal of Universal Computer Science 29(11): 1361-1384

DOI: 10.3897/jucs.112797

Authors: Lorenz Gillner, Ekaterina Auer

Abstract: In this paper, we describe the requirements for traceable open-source data retrieval in the context of computation of BRCA1/2 mutation probabilities (mutations in two tumor-suppressor genes responsible for hereditary BReast or/and ovarian CAncer). We show how such data can be used to develop a Dempster-Shafer model for computing the probability of BRCA1/2 mutations enhanced by taking into account the actual age of a patient or a family member in an appropriate way even if it is not known exactly. The model is compared with PENN II and BOADICEA (based on undisclosed data), two established platforms for this purpose accessible online, as well as with our own previous models. A proof-of-concept implementation shows that set-based techniques are able to provide better information about mutation probabilities, simultaneously highlighting the necessity for ground truth data of high quality.

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Research Article Tue, 28 Nov 2023 18:00:07 +0200
Combining SysML and Timed Coloured Petri Nets for Designing Smart City Applications https://lib.jucs.org/article/97170/ JUCS - Journal of Universal Computer Science 29(10): 1217-1249

DOI: 10.3897/jucs.97170

Authors: Layse Santos Souza, Michel S. Soares

Abstract: A smart city is an urban centre that integrates a variety of solutions to improve infrastructure performance and achieve sustainable urban development. Urban roads are a crucial infrastructure highly demanded by citizens and organisations interested in their deployment, performance, and safety. Urban traffic signal control is an important and challenging real-world problem that aims to monitor and improve traffic congestion. The deployment of traffic signals for vehicles or pedestrians at an intersection is a complex activity that changes constantly, so it is necessary to establish rules to control the flow of vehicles and pedestrians. Thus, this article describes the joint use of the SmartCitySysML, a profile proposed by the authors, with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams specifying the internal behaviour, and then verify the developed model to prove behavioural properties of an urban traffic signal control system.

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Research Article Sat, 28 Oct 2023 18:00:07 +0300
Aggregating Users’ Online Opinions Attributes and News Influence for Cryptocurrencies Reputation Generation https://lib.jucs.org/article/85610/ JUCS - Journal of Universal Computer Science 29(6): 546-568

DOI: 10.3897/jucs.85610

Authors: Achraf Boumhidi, Abdessamad Benlahbib, El Habib Nfaoui

Abstract: Reputation generation systems are decision-making tools used in different domains including e-commerce, tourism, social media events, etc. Such systems generate a numerical reputation score by analyzing and mining massive amounts of various types of user data, including textual opinions, social interactions, shared images, etc. Over the past few years, users have been sharing millions of tweets related to cryptocurrencies. Yet, no system in the literature was designed to handle the unique features of this domain with the goal of automatically generating reputation and supporting investors’ and users’ decision-making. Therefore, we propose the first financially oriented reputation system that generates a single numerical value from user-generated content on Twitter toward cryptocurrencies. The system processes the textual opinions by applying a sentiment polarity extractor based on the fine-tuned auto-regressive language model named XLNet. Also, the system proposes a technique to enhance sentiment identification by detecting sarcastic opinions through examining the contrast of sentiment between the textual content, images, and emojis. Furthermore, other features are considered, such as the popularity of the opinions based on the social network interactions (likes and shares), the intensity of the entity’s demand within the opinions, and news influence on the entity. A survey experiment has been conducted by gathering numerical scores from 827 Twitter users interested in cryptocurrencies. Each selected user assigns 3 numerical assessment scores toward three cryptocurrencies. The average of those scores is considered ground truth. The experiment results show the efficacy of our model in generating a reliable numerical reputation value compared with the ground truth, which proves that the proposed system may be applied in practice as a trusted decision-making tool.

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Research Article Wed, 28 Jun 2023 12:00:03 +0300
Big Data Provenance Using Blockchain for Qualitative Analytics via Machine Learning https://lib.jucs.org/article/93533/ JUCS - Journal of Universal Computer Science 29(5): 446-469

DOI: 10.3897/jucs.93533

Authors: Kashif Mehboob Khan, Warda Haider, Najeed Ahmed Khan, Darakhshan Saleem

Abstract: The amount of data is increasing rapidly as more and more devices are being linked to the Internet. Big data has a variety of uses and benefits, but it also has numerous challenges associated with it that are required to be resolved to raise the caliber of available services, including data integrity and security, analytics, acumen, and organization of Big data. While actively seeking the best way to manage, systemize, integrate, and affix Big data, we concluded that blockchain methodology contributes significantly. Its presented approaches for decentralized data management, digital property reconciliation, and internet of things data interchange have a massive impact on how Big data will advance. Unauthorized access to the data is very challenging due to the ciphered and decentralized data preservation in the blockchain network. This paper proposes insights related to specific Big data applications that can be analyzed by machine learning algorithms, driven by data provenance, and coupled with blockchain technology to increase data trustworthiness by giving interference-resistant information associated with the lineage and chronology of data records. The scenario of record tampering and big data provenance has been illustrated here using a diabetes prediction. The study carries out an empirical analysis on hundreds of patient records to perform the evaluation and to observe the impact of tampered records on big data analysis i.e diabetes model prediction. Through our experimentation, we may infer that under our blockchain-based system the unchangeable and tamper-proof metadata connected to the source and evolution of records produced verifiability to acquired data and thus high accuracy to our diabetes prediction model.

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Research Article Sun, 28 May 2023 18:00:04 +0300
Leveraging Structural and Semantic Measures for JSON Document Clustering https://lib.jucs.org/article/86563/ JUCS - Journal of Universal Computer Science 29(3): 222-241

DOI: 10.3897/jucs.86563

Authors: Uma Priya D, P. Santhi Thilagam

Abstract: In recent years, the increased use of smart devices and digital business opportunities has generated massive heterogeneous JSON data daily, making efficient data storage and management more difficult. Existing research uses different similarity metrics and clusters the documents to support the above tasks effectively. However, extant approaches have focused on either structural or semantic similarity of schemas. As JSON documents are application-specific, differently annotated JSON schemas are not only structurally heterogeneous but also differ by the context of the JSON attributes. Therefore, there is a need to consider the structural, semantic, and contextual properties of JSON schemas to perform meaningful clustering of JSON documents. This work proposes an approach to cluster heterogeneous JSON documents using the similarity fusion method. The similarity fusion matrix is constructed using structural, semantic, and contextual measures of JSON schemas. The experimental results demonstrate that the proposed approach outperforms the existing approaches significantly.

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Research Article Tue, 28 Mar 2023 10:30:03 +0300
Restaurant Recommendations Based on Multi-Criteria Recommendation Algorithm https://lib.jucs.org/article/78240/ JUCS - Journal of Universal Computer Science 29(2): 179-200

DOI: 10.3897/jucs.78240

Authors: Qusai Y. Shambour, Mosleh M. Abualhaj, Ahmad Adel Abu-Shareha

Abstract: Recent years have witnessed a rapid explosion of online information sources about restaurants, and the selection of an appropriate restaurant has become a tedious and time-consuming task. A number of online platforms allow users to share their experiences by rating restaurants based on more than one criterion, such as food, service, and value. For online users who do not have enough information about suitable restaurants, ratings can be decisive factors when choosing a restaurant. Thus, personalized systems such as recommender systems are needed to infer the preferences of each user and then satisfy those preferences. Specifically, multi-criteria recommender systems can utilize the multi-criteria ratings of users to learn their preferences and suggest the most suitable restaurants for them to explore. Accordingly, this paper proposes an effective multi-criteria recommender algorithm for personalized restaurant recommendations. The proposed Hybrid User-Item based Multi-Criteria Collaborative Filtering algorithm exploits users’ and items’ implicit similarities to eliminate the sparseness of rating information. The experimental results based on three real-word datasets demonstrated the validity of the proposed algorithm concerning prediction accuracy, ranking performance, and prediction coverage, specifically, when dealing with extremely sparse datasets, in relation to other baseline CF-based recommendation algorithms.

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Research Article Tue, 28 Feb 2023 10:00:05 +0200
Towards an Open Ontology for Renewable Resource Management in Smart Self-Sustainable Human Settlements https://lib.jucs.org/article/77793/ JUCS - Journal of Universal Computer Science 28(6): 620-647

DOI: 10.3897/jucs.77793

Authors: Igor Tomicic, Markus Schatten, Vadym Shkarupylo

Abstract: This paper proposes an open ontology for self-sustainable human settlements in an effort to set the common language for modelling self-sustainable systems and address the issues regarding heterogeneity of physical devices, protocols, software components, data and message formats and other relevant factors, which proved to be unavoidable in implementations of smart systems in the domain of self-sustainability, smart homes, Internet of things, smart energy management systems, demand side systems, and related areas of research and engineering. Although the existing body of research is showing significant results in related, specialized research areas, currently there is no common formal language available which would bring the diversity of such research efforts under a single umbrella and thus enhance and integrate such efforts, which is often pointed out by the researchers in related fields. This paper discuses self- sustainable systems and associated areas, argues the need for the ontology development, presents its scope, development methodology, domain’s architecture and metamodel, and finally the proposed ontology itself, implemented in an open OWL format.

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Research Article Tue, 28 Jun 2022 10:00:00 +0300
The Use of Recommender Systems in Formal Learning. A Systematic Literature Mapping https://lib.jucs.org/article/69711/ JUCS - Journal of Universal Computer Science 28(4): 414-442

DOI: 10.3897/jucs.69711

Authors: Nahia Ugarte, Mikel Larrañaga, Ana Arruarte

Abstract: Recommender Systems provide users with content or products they are interested in. The main purpose of Recommender Systems is to find, among the vast amount of information that is available or advertised on the Internet, content that meets the user’s needs i.e., a product or content that satisfies his or her wishes. These systems are being used more and more in many of the services of our daily lives. In this paper, a systematic mapping review that explores the use of Rec- ommender Systems in formal learning stages is presented. The paper analyzes what kinds of items the Recommender Systems suggest, who the users that receive the recommendations are, what kinds of information the Recommender Systems use to carry out the recommendation process, the algorithms and techniques the Recommender Systems employ and, finally, how the Recommender Systems have been evaluated. The results obtained in the review will make it possible to iden- tify not only the current situation in this field but also some of the challenges that are still to be faced.

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Research Article Thu, 28 Apr 2022 10:00:00 +0300
Solving the problem of scheduling the production process based on heuristic algorithms https://lib.jucs.org/article/80750/ JUCS - Journal of Universal Computer Science 28(3): 292-310

DOI: 10.3897/jucs.80750

Authors: Dagmara Łapczyńska, Konrad Łapczyński, Anna Burduk, Jose Machado

Abstract: The paper deals with a production scheduling process, which is a problematic and it requires considering a lot of various factors while making the decision. Due to the specificity of the production system analysed in the practical example, the production scheduling problem was classified as a Job-shop Scheduling Problem (JSP). The production scheduling process, especially in the case of JSP, involves the analysis of a variety of data simultaneously and is well known as NP-hard problem. The research was performed in partnership with a company from the automotive industry. The production scheduling process is a task that is usually performed by process engineers. Thus, it can often be affected by mistakes of human nature e.g. habits, differences in experience and knowledge of engineers (their know-how), etc. The usage of heuristic algorithms was proposed as the solution. The chosen methods are genetic and greedy algorithms, as both of them are suitable to resolve a problem that requires analysing a lot of data. The paper presents both approaches: practical and theoretical aspects of the usefulness and effectiveness of genetic and greedy algorithms in a production scheduling process.

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Research Article Mon, 28 Mar 2022 10:00:00 +0300
A Novel Real-Time Edge-Cloud Big Data Management and Analytics Framework for Smart Cities https://lib.jucs.org/article/71645/ JUCS - Journal of Universal Computer Science 28(1): 3-26

DOI: 10.3897/jucs.71645

Authors: Roberto Cavicchioli, Riccardo Martoglia, Micaela Verucchi

Abstract: Exposing city information to dynamic, distributed, powerful, scalable, and user-friendly big data systems is expected to enable the implementation of a wide range of new opportunities; however, the size, heterogeneity and geographical dispersion of data often makes it difficult to combine, analyze and consume them in a single system. In the context of the H2020 CLASS project, we describe an innovative framework aiming to facilitate the design of advanced big-data analytics workflows. The proposal covers the whole compute continuum, from edge to cloud, and relies on a well-organized distributed infrastructure exploiting: a) edge solutions with advanced computer vision technologies enabling the real-time generation of “rich” data from a vast array of sensor types; b) cloud data management techniques offering efficient storage, real-time querying and updating of the high-frequency incoming data at different granularity levels. We specifically focus on obstacle detection and tracking for edge processing, and consider a traffic density monitoring application, with hierarchical data aggregation features for cloud processing; the discussed techniques will constitute the groundwork enabling many further services. The tests are performed on the real use-case of the Modena Automotive Smart Area (MASA).

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Research Article Fri, 28 Jan 2022 10:30:00 +0200
Data-driven Storytelling to Support Decision Making in Crisis Settings: A Case Study https://lib.jucs.org/article/66714/ JUCS - Journal of Universal Computer Science 27(10): 1046-1068

DOI: 10.3897/jucs.66714

Authors: Andrea Lezcano Airaldi, Jorge Andres Diaz-Pace, Emanuel Irrazábal

Abstract: Data-driven storytelling helps to communicate facts, easing comprehension and decision making, particularly in crisis settings such as the current COVID-19 pandemic. Several studies have reported on general practices and guidelines to follow in order to create effective narrative visualizations. However, research regarding the benefits of implementing those practices and guidelines in software development is limited. In this article, we present a case study that explores the benefits of including data visualization best practices in the development of a software system for the current health crisis. We performed a quantitative and qualitative analysis of sixteen graphs required by the system to monitor patients' isolation and circulation permits in quarantine due to the COVID-19 pandemic. The results showed that the use of storytelling techniques in data visualization contributed to an improved decision-making process in terms of increasing information comprehension and memorability by the system stakeholders.

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Research Article Thu, 28 Oct 2021 10:30:00 +0300
Non-verbal Aspects of Collaboration in Virtual Worlds: a CSCW Taxonomy-development Proposal Integrating the Presence Dimension https://lib.jucs.org/article/74166/ JUCS - Journal of Universal Computer Science 27(9): 913-954

DOI: 10.3897/jucs.74166

Authors: Armando Cruz, Hugo Paredes, Leonel Morgado, Paulo Martins

Abstract: Virtual worlds, particularly those able to provide a three-dimensional physical space, have features that make them suitable to support collaborative activities. These features distinguish virtual worlds from other collaboration tools, but current taxonomies of the field of Computer-Supported Cooperative Work do not account for several distinctive features of virtual worlds, namely those related with non-verbal communication. We intended to find out how the use of an avatar, gestures, spatial sounds, etc., influence collaboration in order to be able to include non-verbal communication in taxonomies of the field Computer-Supported Cooperative Work. Several cases of collaboration in virtual worlds are analysed, to find the impact of these non-verbal characteristics of virtual worlds. We proposed adding the concept of Presence to taxonomies of Computer-Supported Cooperative Work and contribute with guidance for future taxonomy development that includes it as a new dimension. This new dimension of Presence is subdivided into "avatar" and "physical space" subdimensions. In turn, these are divided into "physical appearance", "gestures, sounds and animations" and "focus, nimbus and aura"; "environment" and "objects / artefacts". This new taxonomy-development proposal may contribute to inform better design of virtual worlds in support of cooperative work.

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Research Article Tue, 28 Sep 2021 10:00:00 +0300
Enhancing GDPR compliance through data sensitivity and data hiding tools https://lib.jucs.org/article/70369/ JUCS - Journal of Universal Computer Science 27(7): 650-666

DOI: 10.3897/jucs.70369

Authors: Xabier Larrucea, Micha Moffie, Dan Mor

Abstract: Since the emergence of GDPR, several industries and sectors are setting informatics solutions for fulfilling these rules. The Health sector is considered a critical sector within the Industry 4.0 because it manages sensitive data, and National Health Services are responsible for managing patients’ data. European NHS are converging to a connected system allowing the exchange of sensitive information cross different countries. This paper defines and implements a set of tools for extending the reference architectural model industry 4.0 for the healthcare sector, which are used for enhancing GDPR compliance. These tools are dealing with data sensitivity and data hiding tools A case study illustrates the use of these tools and how they are integrated with the reference architectural model.

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Research Article Wed, 28 Jul 2021 10:00:00 +0300
Integration Model between Heterogeneous Data Services in a Cloud https://lib.jucs.org/article/67046/ JUCS - Journal of Universal Computer Science 27(4): 387-412

DOI: 10.3897/jucs.67046

Authors: Marcelo Aires Vieira, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, Babacar Mane

Abstract: With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.

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Research Article Wed, 28 Apr 2021 19:30:00 +0300
Weather Station IoT Educational Model Using Cloud Services https://lib.jucs.org/article/24151/ JUCS - Journal of Universal Computer Science 26(11): 1495-1512

DOI: 10.3897/jucs.2020.079

Authors: Ján Molnár, Simona Kirešová, Tibor Vince, Dobroslav Kováč, Patrik Jacko, Matej Bereš, Peter Hrabovský

Abstract: IoT technology is gaining more and more popularity in practice, as it collects, processes, evaluates and stores important measured data. The IoT is used every day in the work, in the home or smart houses or in public areas. It realizes the connectivity between real world and digital world which means, that it converts physical quantities of the real world in the form of analog signals into digital numbers stored in clauds. It is essential that students gain practical experience in the design and implementation of the IoT systems during their studies. The article first describes IoT issues and communication protocols used in IoT generally are closer described. Then the design and implementation of an educational model of IoT system - Weather station with the ThingSpeak cloud support is described. The created IoT model interconnects microcontroller programming, sensors and measuring, cloud API interfaces, MATLAB scripts which are useful to analyses the stored data, Windows and Android application developing.

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Research Article Sat, 28 Nov 2020 00:00:00 +0200
Social Choice-based Explanations: An Approach to Enhancing Fairness and Consensus Aspects https://lib.jucs.org/article/24006/ JUCS - Journal of Universal Computer Science 26(3): 402-431

DOI: 10.3897/jucs.2020.021

Authors: Thi Ngoc Trang Tran, Muesluem Atas, Man Le, Ralph Samer, Martin Stettinger

Abstract: Explanations are integrated into recommender systems to give users an insight into the recommendation generation process. Compared to single-user recommender systems, explanations in group recommender systems have further goals. Examples thereof are fairness, which helps to take into account as much as possible group members' preferences and consensus, which persuades group members to agree on a decision. In this paper, we proposed different types of explanations and found the most effective ones in terms of increasing the fairness perception, consensus perception and satisfaction of group members with regard to group recommendations. We conducted a user study to evaluate the proposed explanations. The results show that explanations which consider the preferences of all or the majority of group members achieve the best results in terms of the mentioned dimensions. Besides, we discovered positive correlations among these aspects. In the context of repeated decisions, group members' satisfaction from previous decisions are helpful to improve the fairness perception of users concerning group recommendations and speed up the group decision-making process. Furthermore, we found out that gender diversity does influence the perception of users regarding the mentioned dimensions of the explanations. Although the proposed explanations were analyzed in group decision scenarios for non-configurable (no-attribute) items, there exist potential possibilities to apply them to explanations for configurable items.

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Research Article Sat, 28 Mar 2020 00:00:00 +0200
Analysing Bias in Political News https://lib.jucs.org/article/23996/ JUCS - Journal of Universal Computer Science 26(2): 173-199

DOI: 10.3897/jucs.2020.011

Authors: Gabriel De Arruda, Norton Roman, Ana Monteiro

Abstract: Although of paramount importance to all societies, the fact that media can be biased is a troubling thought to many people. The problem, however, is by no means easy to solve, given its high subjectivity, thereby leading to a number of different approaches by researchers. In this work, we addressed media bias according to a tripartite model whereby news can suffer from a combination of selective coverage of issues (Selection Bias), disproportionate attention given to specific subjects (Coverage Bias), and the favouring of one side in a dispute (Statement Bias). To do so, we approached the problem within an outlier detection framework, defining bias as a noticeable deviation from some mainstream behaviour. Results show that, in following this methodology, one can not only identify bias in specific outlets, but also determine how that bias comes about, how strong it is, and the way it interacts with other dimensions, thereby rendering a more complete picture of the phenomenon under inspection.

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Research Article Fri, 28 Feb 2020 00:00:00 +0200
Improving Multi-Label Classification for Learning Objects Categorization by Taking into Consideration United States of Americage Information https://lib.jucs.org/article/22692/ JUCS - Journal of Universal Computer Science 25(13): 1687-1716

DOI: 10.3217/jucs-025-13-1687

Authors: Pedro Espejo, Eva Gibaja, Victor Menéndez, Alfredo Zapata, Cristobal Romero

Abstract: Learning objects are digital resources that can be deployed by means of a web system for supporting teaching. A key advantage is reuse, and this is possible thanks to learning objects repositories that allow learning object search, management and categorization. In this work, we propose a novel approach towards automatically learning object categorization taking into consideration learning object United States of Americage information. We use a multi-label learning approach since each learning object might be associated with multiple categories. We have developed a methodology with three main stages allowing us to firstly select the most suitable set of text features from learning objects metadata, secondly selecting how much historical learning object United States of Americage information can enhance classification performance, and finally selecting the best multi-label classification algorithms with our data. We have carried out an experimental work using 519 learning objects gathered from the AGORA repository for 8 years. We have compared 13 multi-label classification algorithms over 16 evaluation measures. The results obtained show that United States of Americage information about the learning object can improve the classification.

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Research Article Sat, 28 Dec 2019 00:00:00 +0200
Cyber Threat Intelligence for Improving Cybersecurity and Risk Management in Critical Infrastructure https://lib.jucs.org/article/22673/ JUCS - Journal of Universal Computer Science 25(11): 1478-1502

DOI: 10.3217/jucs-025-11-1478

Authors: Halima Kure, Shareeful Islam

Abstract: Cyber-attack is one of the significant threats affecting to any organisation specifically to the Critical Infrastructure (CI) organisation. These attacks are nowadays more sophisticated, multi-vectored and less predictable, which make the Cyber Security Risk Management (CSRM) task more challenging. Critical Infrastructure needs a new line of security defence to control these threats and minimise risks. Cyber Threat Intelligence (CTI) provides evidence-based information about the threats aiming to prevent threats. There are existing works and industry practice that emphasise the necessity of CTI and provides methods for threat intelligence and sharing. However, despite these significant efforts, there is a lack of focus on how CTI information can support the CSRM activities so that the organisation can undertake appropriate controls to mitigate the risk proactively. This paper aims to fill this gap by integrating CTI for improving cybersecurity risks management practice specifically focusing on the critical infrastructure. In particular, the proposed approach contributes beyond state of the art practice by incorporating CTI information for the risk management activities. This helps the organisation to provide adequate and appropriate controls from strategic, tactical and operational perspectives. We have integrated concepts relating to CTI and CSRM so that threat actor's profile, attack detailed can support calculating the risk. We consider smart grid system as a Critical Infrastructure to demonstrate the applicability of the work. The result shows that cyber risks in critical infrastructures can be minimised if CTI information is gathered and used as part of CSRM activities. CTI not only supports understanding of threat for accurate risk estimation but also evaluates the effectiveness of existing controls and recommend necessity controls to improve overall cybersecurity. Also, the result shows that our approach provides early warning about issues that need immediate attention.

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Research Article Thu, 28 Nov 2019 00:00:00 +0200
Digital Investigation of IoT Devices in the Criminal Scene https://lib.jucs.org/article/22652/ JUCS - Journal of Universal Computer Science 25(9): 1199-1218

DOI: 10.3217/jucs-025-09-1199

Authors: François Bouchaud, Gilles Grimaud, Thomas Vantroys, Pierrick Buret

Abstract: The Internet of Things (IoT) is everywhere around us. Smart communicating objects are offering the digitalization of lives. They create new opportunities within criminal investigations. In recent years, the scientific community sought to develop a common digital framework and methodology adapted to IoT-based infrastructure. However, the difficulty in exploiting the IoT lies in the heterogeneous nature of the devices, the lack of standards and the complex architecture. Although digital forensics are considered and adopted in IoT investigations, this work only focuses on the collection. The identification phase is quite unexplored. It addresses the challenges of locating hidden devices and finding the best evidence to be collected. The matter of facts is the traditional method of digital forensics does not fully fit the IoT environment. Furthermore, the investigator can no longer consider a connected object as a single device, but as an interconnected whole one, anchored in a cross-disciplinary environment. This paper presents the methodology for identifying and classifying connected objects in search of the best evidence to be collected. It offers techniques for detecting and locating the appropriate equipment. Based on frequency mapping and interactions, it transfers the concept of "fingerprinting" into the field of crime scene. It focuses on the technical and data criteria to successfully select the relevant IoT devices. It gives a general classiffication as well as the limits of such an approach. It shows the collection of digital evidence by focusing on pertinent information from the Internet of Things.

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Research Article Sat, 28 Sep 2019 00:00:00 +0300
A Model for Resource Management in Smart Cities Based on Crowdsourcing and Gamification https://lib.jucs.org/article/22643/ JUCS - Journal of Universal Computer Science 25(8): 1018-1038

DOI: 10.3217/jucs-025-08-1018

Authors: Rodrigo Barbosa Sounited States Of America Orrego, Jorge Luis Victória Barbosa

Abstract: Resources of a city are urban assets such as hospitals and pharmacies (health facilities) or accessible ramps and adapted toilets (accessibility resources). This paper addresses the problem of resource management for smart cities combining crowdsourcing with gamification, and proposes a model called CORE-MM. This model allows the use of crowdsourcing techniques so that the management of cities resources is done by the citizens, without having to rely on an organization or public administration. To encourage participation in this resource management, this model also uses techniques of gamification. CORE-MM proposes the use of crowdsourcing integrated with gamification to manage the resources of a smart city, with two interdependent objectives: to motivate the use of the system by the users, and to encourage their participation in the sharing and management of information. The scientific contribution of this work is that CORE-MM treats the resource management considering a generic resources approach for smart cities. A prototype of CORE-MM was offered to volunteers and a questionnaire was developed to collect data and to evaluate the model, its performance and relevance. Results with volunteers indicated good perceived ease of use and good perceived utility. From the affirmations of the questionnaire that the 10 volunteers that tested the CORE-MM prototype had to answer, 91.67% agreed on the ease of use of the system and 8.33% manifested indifference in their responses. Regarding the utility of the system, 99.17% agreed and only 0.83% were indifferent. These results point to positive perspectives regarding the use of the application in possible situations and real locations.

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Research Article Wed, 28 Aug 2019 00:00:00 +0300
Planning of Urban Public Transportation Networks in a Smart City https://lib.jucs.org/article/22640/ JUCS - Journal of Universal Computer Science 25(8): 946-966

DOI: 10.3217/jucs-025-08-0946

Authors: Jonathan Frez, Nelson Baloian, José Pino, Gustavo Zurita, Franco Basso

Abstract: Planning efficient public transport is a key issue in modern cities. When planning a route for a bus or a line for a tram or subway, it is necessary to consider people's demand for this service. In this work we present a method to use existing crowdsourced data (like Waze and OpenStreetMap) and cloud services (like Google Maps) to support a transportation network decision making process. The method is based on the Dempster-Shafer Theory to model transportation demand. It uses data from Waze to provide a congestion probability and data from OpenStreetMap to provide information about location of facilities such as shops, in order to predict where people may need to start or end their trips using public transportation vehicles. The paper also presents an example using this method with real data. The example shows an analysis of the current availability of public transportation stops in order to discover its weak points.

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Research Article Wed, 28 Aug 2019 00:00:00 +0300
Mobile Applications for People with Parkinson's Disease: A Systematic Search in App Stores and Content Review https://lib.jucs.org/article/22627/ JUCS - Journal of Universal Computer Science 25(7): 740-763

DOI: 10.3217/jucs-025-07-0740

Authors: Sonia Estévez, M. Cambronero, Yolanda García-Ruiz, Luis Llana Díaz

Abstract: Parkinson's disease (PD) is the most common age-related neurodegenerative motor disease. People with Parkinson's have different motor symptoms related to movement, the most common of which are tremor, muscle rigidity and slowness of movement. In addition, there are other problems that are unrelated to motor symptoms, such as sleep behavior disorders, personality changes, pain and depression. Numerous apps designed for people with this disease have been developed in recent years. Due to the diversity of symptoms, there are very many different apps. Our goal is to carry out a systematic review of available apps related to PD for the operating systems iOS and Android and to assess their features. In addition, we are interested in the United States of Americability of the apps. A search for the representative terms "Parkinson" and "Parkinson's Disease", together with the descriptors of the symptoms, was conducted in the Google Play and Apple App stores. Next, we screened the PD-related apps. Finally, we assessed the apps with respect to symptoms, users, purpose and features. In addition, a United States of Americability evaluation was carried out.

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Research Article Sun, 28 Jul 2019 00:00:00 +0300
An Effective Risk Factor Detection and Disease Prediction (RFD-DP) Model Applied to Hypertension https://lib.jucs.org/article/23527/ JUCS - Journal of Universal Computer Science 24(9): 1192-1216

DOI: 10.3217/jucs-024-09-1192

Authors: Dingkun Li, Yaning Li, Zhou Ye, Musa Ibrahim, Keun Ryu, Seon Jeong

Abstract: Never before in history is the data growing at such a high volume, variety and velocity. It not only provides multi-sources of information for people to discover useful, important and valuable nuggets of information, but also increases the difficulty in finding such nuggets in almost all fields. Particularly, the field of healthcare is known for its dominical or ontological complexity and variety of clinical data or medical data regarding its variable data standards and data quality and so as the high data dimensionality. In order to effectively use the data at the hand to improve healthcare outcomes and processes, this paper illustrates a model called Risk Factor Detection and Disease Prediction (RFD-DP) model. The model incorporates statistics, data mining and MapReduce techniques on high dimensional clinical data to detect risk factors and generate predicator for a specified disease, hypertension disease. The experimental results indicate that the proposed model outperforms traditional feature selection and classification methods in terms of accuracy, F-score, and AUC. Consequently, the proposed model is promising to be applied to healthcare system.

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Research Article Fri, 28 Sep 2018 00:00:00 +0300
An Experimental System for MQTT/CoAP-based IoT Applications in IPv6 over Bluetooth Low Energy https://lib.jucs.org/article/23524/ JUCS - Journal of Universal Computer Science 24(9): 1170-1191

DOI: 10.3217/jucs-024-09-1170

Authors: Chi-Yi Lin, Kai-Hung Liao, Chia-Hsuan Chang

Abstract: With the rapid development of Internet of Things (IoT), it is an inevitable trend that all things will get connected to the Internet to form various intelligent services such as Industry 4.0, smart home, smart medical care, etc. To make such intelligent IoT services practicable, it is vital to have a low-power link-layer technology that can accommodate a diversity of upper-layer networking protocols. Currently, there are many popular low-power wireless networking technologies for IoT such as ZigBee and Bluetooth Low Energy (BLE). Because of the ubiquity of BLE-enabled smartphones nowadays, BLE has gained much attention in the IoT industry recently. In this research, we aim at implementing an IPv6 over BLE experimental system using Raspberry Pi 3 and nRF51-DK development boards, and then run the Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) protocol and the Constrained Application Protocol (CoAP) over the protocol stack of IPv6/BLE. Specifically, in our experimental system every BLE node is IPv6-addressable and accessible through the MQTT/CoAP protocols from anywhere over the Internet. Moreover, to ease user accesses from ordinary web browsers, we build two gateways as the web servers for end users, which receive real-time sensor data via CoAP or MQTT-SN protocols and then push the data to end users' browsers. The gateways are also designed to routinely request sensor data and then forward the data to cloud database platforms, which serve as the data sources for historical sensor data. Preliminary results showed that our system is capable of achieving the designed goals and is user-friendly. Compared with the non-IP based BLE sensor networks, our implementation can be integrated into a variety of existing and widely used IP-based applications easily.

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Research Article Fri, 28 Sep 2018 00:00:00 +0300
Air4People: a Smart Air Quality Monitoring and Context-Aware Notification System https://lib.jucs.org/article/23378/ JUCS - Journal of Universal Computer Science 24(7): 846-863

DOI: 10.3217/jucs-024-07-0846

Authors: Alfonso Garcia-De-Prado, Guadalupe Ortiz, Juan Boubeta-Puig, David Corral-Plaza

Abstract: Over the last years, air pollution and air quality have received increasing attention in the scope of Internet of Things and smart cities, since they can seriously affect citizens' health. However, current systems for air quality monitoring and notification lack essential key requirements in order to be effective as far as users' access to the information is concerned and, particularly, the provision of context-aware notifications. This paper presents Air4People, an air quality monitoring and context-aware notification system, which submits personalized alerts to citizens based on several types of context, whenever air quality-related health risks are detected for their particular context.

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Research Article Sat, 28 Jul 2018 00:00:00 +0300
Research on Computational Intelligence in Medical Resource Allocation Based on Mass Customization https://lib.jucs.org/article/23302/ JUCS - Journal of Universal Computer Science 24(6): 753-774

DOI: 10.3217/jucs-024-06-0753

Authors: Yang Xu, Shuwen Liu, Binglu Wang

Abstract: In this era characterized by rapid improvements in the quality of living, people are eager to seek better medical services. However, the medical resource shortage threatens people's daily lives and has become an important factor causing dissatisfaction. Furthermore, as a sub-branch of artificial intelligence, computational intelligence is widely used to solve real-world problems like resource allocation. This paper proposes a medical resource allocation model based on mass customization, considering parameters such as doctors' professional level, patient preferences, and the medical station distribution. This model aims at optimizing and balancing the uneven distribution of medical resources by taking into account the patient requirements and medical costs. Moreover, a genetic algorithm is applied to improve the computational efficiency of the proposed method. The results show that the medical resource allocation model based on mass customization can lead to a higher profit. Suggestions are also discussed for sustainable development in medical service based on mass customization.

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Research Article Thu, 28 Jun 2018 00:00:00 +0300
Relating Mobile Device Use and Adherence to Information Security Policy with Data Breach Consequences in Hospitals https://lib.jucs.org/article/23224/ JUCS - Journal of Universal Computer Science 24(5): 634-645

DOI: 10.3217/jucs-024-05-0634

Authors: Simon Vrhovec, Blaž Markelj

Abstract: Critical infrastructure is a high value target in the real world and cyberspace. A failure to protect the critical infrastructure in the cyberspace could lead to serious financial and material losses and violate the effective functioning of a country. In this paper, we will focus on healthcare as an important part of the critical infrastructure. An important part of the healthcare infrastructure are hospitals. Hospital personnel is increasingly using mobile devices in their everyday work to improve patient care. Hospitals may however fail to adequately address the use of mobile devices and adapt their information security policies in time. Hospital personnel may use both their personal and work mobile devices for everyday work. Sometimes they do it without adhering to an adequate hospital information security policy. The objective of this paper is to study the relation between the use of mobile devices, adhering to hospital information security policy and perceived consequences of data breaches. An exploratory survey (N = 95) has been conducted in a Slovenian hospital. Respondents were asked about the use of their personal and work mobile devices for accessing medical data, adhering to the hospital information security policy, and the perceived consequences of data breaches for themselves, the hospital and the patients. The results show that perceived personal consequences are negatively correlated with personal and work mobile device use for work. Also, adhering to information security policy is positively correlated with perceived data breach consequences for both the patients and the hospital.

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Research Article Mon, 28 May 2018 00:00:00 +0300
Large Scale Mobility-based Behavioral Biometrics on the Example of the Trajectory-based Model for Anomaly Detection https://lib.jucs.org/article/23147/ JUCS - Journal of Universal Computer Science 24(4): 417-443

DOI: 10.3217/jucs-024-04-0417

Authors: Piotr Kałużny, Agata Filipowska

Abstract: The paper describes an implementation of a behavioral authentication system, working on sparse geographical data generated by mobile devices in the form of CDR logs. While providing a review of state of the art w.r.t. sensors and measures that can be used when creating a system detecting anomalies in the user behavior, it also describes domain specific authorization methods focusing on the user mobility. The trajectory based stay-extraction model is utilized to build user mobility patterns, upon which the anomaly detection model measures the repeatability of human behavior in dimensions of: geography, time and sequentiality. The goal is to measure the extent to which the geographical aspect of the human mobility can be used in behavioral biometrics' systems i.e. in which scenarios geography may enable to describe (and differentiate between) user patterns - based on anomaly detection in cases resembling real life scenarios (phone theft or sharing between users). The research methods developed may be implemented on mobile devices to benefit from multiple sensors data in the authentication processes. The model is evaluated on a large telecom dataset, with the use of similarity classes, what allows measuring the accuracy of the model in real-life scenarios and provides benchmarking guidelines for the future work on the topic.

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Research Article Sat, 28 Apr 2018 00:00:00 +0300
Air-Pollution Prediction in Smart Cities through Machine Learning Methods: A Case of Study in Murcia, Spain https://lib.jucs.org/article/23068/ JUCS - Journal of Universal Computer Science 24(3): 261-276

DOI: 10.3217/jucs-024-03-0261

Authors: Raquel Martínez-España, Andrés Bueno-Crespo, Isabel Timón, Jesús Soto, Andrés Muñoz, José Cecilia

Abstract: Air-pollution is one of the main threats for developed societies. According to the World Health Organization (WHO), pollution is the main cause of deaths among children aged under five. Smart cities are called to play a decisive role to improve such pollution by first collecting, in real-time, different parameters such as SO2, NOx, O3, NH3, CO, PM10, just to mention a few, and then performing the subsequent data analysis and prediction. However, some machine learning techniques may be more well-suited than others to predict pollution-like variables. In this paper several machine learning methods are analyzed to predict the ozone level (O3) in the Region of Murcia (Spain). O3 is one of the main hazards to health when it reaches certain levels. Indeed, having accurate air-quality prediction models is a previous step to take mitigation activities that may benefit people with respiratory disease like Asthma, Bronchitis or Pneumonia in intelligent cities. Moreover, here it is identified the most-significant variables to monitor the air-quality in cities. Our results indicate an adjustment for the proposed O3 prediction models from 90% and a root mean square error less than 11 μ/m3 for the cities of the Region of Murcia involved in the study.

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Research Article Wed, 28 Mar 2018 00:00:00 +0300
A Study on Context-Relationship with Context-Attributes for a Smart Service Generation in Smart City https://lib.jucs.org/article/23067/ JUCS - Journal of Universal Computer Science 24(3): 249-260

DOI: 10.3217/jucs-024-03-0249

Authors: Hoon Ko, Seogchan Hwang, Libor Mesicek, Jongsun Choi, Junho Choi, Pankoo Kim

Abstract: This paper is to study how to provide smart services by analyzing each service history based on Cloud computing in smart cities. Normally, users use each smart device to receive their services while they stay in a place. In case they move and visit to other place, the system prepares the service based on their services history. At that time, although the users had visited and had services in past, this visiting may ask other services. Then the existing system usually generates new service, and next it provides the service to the user. However, this method is inefficient, because the system has to accept the number of process whenever all users request the service. In this paper, it suggests the smart service model that it keeps users' services history, which had used them while the user stays to a place. The system catches the user's visiting with the user's contexts in the smart device. The model considers their plan/purpose based on old services, and it decides if they modifies them by editing extra services. It calls the system optimization and the suggesting method shows better efficiency after experimenting.

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Research Article Wed, 28 Mar 2018 00:00:00 +0300
Developing a BYOD Scale to Measure the Readiness Level: Validity and Reliability Analyses https://lib.jucs.org/article/23769/ JUCS - Journal of Universal Computer Science 23(12): 1113-1131

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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Research Article Thu, 28 Dec 2017 00:00:00 +0200
Digitalization Canvas - Towards Identifying Digitalization Use Cases and Projects https://lib.jucs.org/article/23691/ JUCS - Journal of Universal Computer Science 23(11): 1070-1097

DOI: 10.3217/jucs-023-11-1070

Authors: Andreas Heberle, Welf Löwe, Anders Gustafsson, Örjan Vorrei

Abstract: Nowadays, many companies are running digitalization initiatives or are planning to do so. There exist various models to evaluate the digitalization potential of a company and to define the maturity level of a company in exploiting digitalization technologies summarized under buzzwords such as Big Data, Artificial Intelligence (AI), Deep Learning, and the Industrial Internet of Things (IIoT). While platforms, protocols, patterns, technical implementations, and standards are in place to adopt these technologies, small- to medium-sized enterprises (SME) still struggle with digitalization. This is because it is hard to identify the most beneficial projects with manageable cost, limited resources and restricted know-how. In the present paper, we describe a real-life project where digitalization use cases have been identified, evaluated, and prioritized with respect to benefits and costs. This effort led to a portfolio of projects, some with quick and easy wins and some others with mid- to long-term benefits. From our experiences, we extracted a general approach that could be useful for other SMEs to identify concrete digitalization activities and to define projects implementing their digital transformation. The results are summarized in a Digitalization Canvas.

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Research Article Tue, 28 Nov 2017 00:00:00 +0200
Big Data in Cross-Disciplinary Research https://lib.jucs.org/article/23681/ JUCS - Journal of Universal Computer Science 23(11): 1035-1037

DOI: 10.3217/jucs-023-11-1035

Authors: Giangiacomo Bravo, Mikko Laitinen, Magnus Levin, Welf Löwe, Göran Petersson

Abstract: The ubiquity of sensor, computing, communication, and storage technologies provides us with access to previously unknown amounts of data - Big Data. Big Data has revolutionized research communities and their scientific methodologies. It has, for instance, innovated the approaches to knowledge and theory building, validation, and exploitation taken in the engineering sciences. The humanities and social sciences even face a paradigm shift away from data-scarce, static, coarse-grained and simple studies towards data-rich, dynamic, high resolution, and complex observations and simulations. The present focused topic presents investigations from different research fields in which the focus is either on utilizing Big Data or charting the benefits of using such evidence in basic research.

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Research Article Tue, 28 Nov 2017 00:00:00 +0200
OnionSIP: Preserving Privacy in SIP with Onion Routing https://lib.jucs.org/article/23601/ JUCS - Journal of Universal Computer Science 23(10): 969-991

DOI: 10.3217/jucs-023-10-0969

Authors: Alexandros Fakis, Georgios Karopoulos, Georgios Kambourakis

Abstract: While more and more users turn to IP-based communication technologies, privacy and anonymity remain largely open issues. One of the most prominent VoIP protocols for multimedia session management is SIP which, despite its popularity, suffers from security and privacy aws. As SIP messages are sent in plain text, user data are exposed to intermediate proxies and eavesdroppers. As a result, information about users participating in a call can leak from header data, which cannot be omitted since they are needed for the correct routing of SIP messages to their final destination. Even more, traffic analysis attacks can be mounted with data stemming from lower layers. To redress this kind of problems, privacy can be achieved either by the construction of a lower level tunnel (via the use of SSL or IPsec protocols) or by employing a customtailored solution. However, SSL and IPsec are known for leading to undesirable, non affordable delays, and thus the need for a SIP-oriented solution is preferable. In the context of this article, we evaluate three alternative solutions to encounter the above issues. More specifically, we use two well-known anonymity networks, Tor and I2P, for secluding both caller's and callee's actions by securing SIP messages content. As a third solution, we present our proposal for preserving privacy in SIP signaling, by using an onion-routing approach, where selected sensitive fields of SIP messages are encrypted using either asymmetric or symmetric encryption. We compare these three alternatives in terms of performance, mentioning the pros and cons that come up with each proposal. Our work also presents the reasons why other existing anonymity networks fail to be considered as appropriate for preserving anonymity in SIP.

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Research Article Sat, 28 Oct 2017 00:00:00 +0300
Contextualization and Recommendation of Annotations to Enhance Information Exchange in Assembly Assistance https://lib.jucs.org/article/23517/ JUCS - Journal of Universal Computer Science 23(9): 932-951

DOI: 10.3217/jucs-023-09-0932

Authors: Rebekka Alm

Abstract: Increasingly exible production processes require intelligent assistance systems containing information and knowledge to maintain high quality and efficiency. To ensure a reliable supply of information, it is of great importance to find easy and fast ways to record and store "new" information, as well as to provide a sensible mechanism to supply the information when needed. In this paper an approach is presented that uses annotations in combination with a formalized knowledge base that represents the work domain. This pre-condition enables a context-based annotation recommendation. A framework is proposed to integrate different factors to measure the relevance of an annotation according to a given situation. The approach is illustrated using the example of an assembly assistance system. To evaluate the users' attitude regarding annotations as instruction support and to test the system's capabilities when handling a great number of annotations some studies were performed and analyzed.

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Research Article Thu, 28 Sep 2017 00:00:00 +0300
Comparative Evaluation of Algorithms for Sentiment Analysis over Social Networking Services https://lib.jucs.org/article/23437/ JUCS - Journal of Universal Computer Science 23(8): 755-768

DOI: 10.3217/jucs-023-08-0755

Authors: Akrivi Krouska, Christos Troussas, Maria Virvou

Abstract: Twitter is a highly popular social networking service and a web-based communication platform with million users exchanging daily public messages, namely tweets, expressing their opinion and feelings towards various issues. Twitter represents one of the largest and most dynamic datasets for data mining and sentiment analysis. Therefore, Twitter Sentiment Analysis constitutes a prominent and an active research area with significant applications in industry and academia. The purpose of this paper is to provide a guideline for the decision of optimal algorithms for sentiment analysis services. In this context, five well-known learning-based classifiers (Naive Bayes, Support Vector Machine, k-Nearest Neighbor, Logistic Regression and C4.5) and a lexicon-based approach (SentiStrength) have been evaluated based on confusion matrices, using three different datasets (OMD, HCR and STS-Gold) and two test models (percentage split and cross validation). The results demonstrate the superiority of Naive Bayes and Support Vector Machine regardless of datasets and test methods.

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Research Article Mon, 28 Aug 2017 00:00:00 +0300
An Anesthesia Alert System based on Dynamic Profiles Inferred through the Medical History of Patients https://lib.jucs.org/article/23435/ JUCS - Journal of Universal Computer Science 23(8): 705-724

DOI: 10.3217/jucs-023-08-0705

Authors: Jorge Luis Victória Barbosa, Bruno Sempe, Bruno Mota, Leandro Dini

Abstract: Anesthesia Information Management Systems (AIMSs) have existed for many decades. However, how to turn patient records into strategic information to improve the anesthesia process is still a research challenge. We did not find systems that use data from previous procedures for issuing alerts. This data can prevent errors during procedures and aid on medical staff evaluation. We propose SaneWatch, an alert system guided by the medical history of patients. SaneWatch uses configurable rules to continuously review the patient's history and automatically generate an anesthesia profile. This dynamic profile allows the emission of strategic alerts during the anesthesia procedures. We have implemented and integrated the system in an AIMS that has been used the past four years by more than 40 anesthesiologists in several hospitals in the city of Porto Alegre in southern Brazil. We applied the integrated system in a practical experiment. Twenty doctors tried it and filled out a questionnaire based on the Technology Acceptance Model (TAM). An overall strong agreement of 96% was obtained in perceived usefulness acceptance assessment. In addition, 86% of users indicated that the system was easy to use. The results were encouraging and demonstrate the potential for implementing SaneWatch in anesthesia procedures. However, 12% of doctors disagreed with regard to ease of use, showing that the system needs improvements in interface related aspects.

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Research Article Mon, 28 Aug 2017 00:00:00 +0300
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy-aware Scheduling in Heterogeneous Computing Systems https://lib.jucs.org/article/23369/ JUCS - Journal of Universal Computer Science 23(7): 636-651

DOI: 10.3217/jucs-023-07-0636

Authors: Gaoshan Deng, Quanxi Feng, Pan Zheng, Tao Song

Abstract: Heterogeneous computing systems (HCSs) use many heterogeneous processors or cores to perform particular tasks. To address the requirement of green IT, several power management techniques have been developed to reduce the energy consumption of these systems. Dynamic voltage scaling, which dynamically changes the supply voltage of processors during the execution of an application, is widely used. However, reducing supply voltage decreases computation speed. Therefore, system makespan and energy consumption need to be considered at the same time. We propose a multi-objective scheduling algorithm based on decomposition for scheduling of the system workflow. Through experiments, we examine the performances of several algorithms, including the proposed one, in different benchmarks and real-world applications. Results show that our algorithm demonstrates better performance than other state-of-art evolutionary algorithms under various conditions involving the use of different crossover and mutation operators.

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Research Article Fri, 28 Jul 2017 00:00:00 +0300
Framework for Affective News Analysis of Arabic News: 2014 Gaza Attacks Case Study https://lib.jucs.org/article/23063/ JUCS - Journal of Universal Computer Science 23(3): 327-351

DOI: 10.3217/jucs-023-03-0327

Authors: Mahmoud Al-Ayyoub, Huda Al-Sarhan, Majd Ud, Mohammad Al-Smadi, Yaser Jararweh

Abstract: This paper aims at fostering the domain of Arabic affective news analysis through providing: (a) a benchmark annotated Arabic dataset of news for affective news analysis, (b) an aspect-based sentiment analysis (ABSA) approach for evaluating the sentimental affect of Arabic news posts on the reader, and (c) a baseline approach with a common evaluation framework to compare future research results with the baseline ones.

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Research Article Tue, 28 Mar 2017 00:00:00 +0300
Terrorism in the 2015 Election Period in Turkey: Content Analysis of Political Leaders' Social Media Activity https://lib.jucs.org/article/23059/ JUCS - Journal of Universal Computer Science 23(3): 256-279

DOI: 10.3217/jucs-023-03-0256

Authors: Ahmet Güneyli, Metin Ersoy, Şevki Kıralp

Abstract: In this research, a case study was conducted, analyzing the Twitter messages posted between July and November 2015 by six political leaders in Turkey. The Twitter messages posted by President Erdoğan, AKP's leader Davutoğlu, CHP's leader Kiliçdaroğlu, MHP's leader Bahçeli and HDP's co-chairs Demirtaş and Yüsekdağ were all examined. The analysis focused primarily on the messages that were related to terrorism. The research utilized a descriptive and qualitative approach as well as thematic content analysis. To consolidate the thematic content analysis, numerical data (total word amount and arithmetic mean), charts and tables were used. During the relevant period, terrorism and political instability dominated Turkish politics, and, on 1 November 2015, early elections were held. This research concluded that the six leaders differed in their approaches towards terrorism, which constituted a key issue for the political leaders in Turkey by dominating the political discourse during the electoral campaign.

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Research Article Tue, 28 Mar 2017 00:00:00 +0300
Boosting Point-of-Interest Recommendation with Multigranular Time Representations https://lib.jucs.org/article/23430/ JUCS - Journal of Universal Computer Science 22(8): 1148-1174

DOI: 10.3217/jucs-022-08-1148

Authors: Gonzalo Rojas, Diego Seco, Francisco Serrano

Abstract: Technologies of recommender systems are being increasingly adopted by Location Based Social Networks (LBSNs) with the purpose of recommending Pointsof-Interest (POIs) to their users, and different contextual characteristics have been incorporated to enhance this process. Among these characteristics, the time at which users express their preferences (typically, by checking-in to different POIs) and ask for recommendations, is frequently referred as a first-order feature in this process. However, even when its influence on improving the accuracy of recommendations has been empirically demonstrated, time is still mainly considered through a monogranular representation (one-hour or one-day blocks). In this article, we introduce a POI recommendation approach based on a multigranular characterization of time, composed of hour, day-of-the-week, and month. Based on this concept, we propose two representations of user check-ins: one that directly extends a monogranular proposal of time for POI recommendations, and other based on a statistical representation of check-in distributions in time. For both representations, corresponding algorithms to compute user similarity and preference prediction are introduced. The experimental evaluation shows promising results in terms of accuracy and scalability.

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Research Article Mon, 1 Aug 2016 00:00:00 +0300
CMSN: An Efficient and Effective Agent Lookup for Mobile Agent Middleware https://lib.jucs.org/article/23427/ JUCS - Journal of Universal Computer Science 22(8): 1072-1096

DOI: 10.3217/jucs-022-08-1072

Authors: Hiroaki Fukuda, Paul Leger, Keita Namiki

Abstract: A Wireless Sensor Network (WSN) is typically deployed in a location in which no electrical source is provided, meaning that sufficient battery life is crucial. Applications for WSNs require implementations of complex operations such as network administration. To simplify the development of these applications, several mobile agent middleware solutions have been proposed. Applications for these middleware frameworks are executed by communication among agents; therefore, a common operation is to look up agents. Because existing proposals do not have much technical support for an efficient approach to look up agents, every lookup consumes a significant amount of battery power and time. In addition, current approaches can fail in their lookup operations if the target agent moves during a lookup operation. This paper proposes Chord for Mobile agent on Sensor Network (CMSN), an efficient and effective lookup for mobile agent middleware. CMSN is inspired by Chord for Sensor Networks (CSN), which introduces hierarchical ring structures and a distributed hash table algorithm to improve lookup performance. Unfortunately, CSN cannot be applied to mobile agent middleware solutions because CSN always requires a base station and assumes no agent migration between nodes. Unlikely CSN, CMSN is designed for an environment where agents can freely move between nodes without dependency on a special node such as a base station. In addition, CMSN leverages a feature where the location of a node is stationary in order to improve lookup performance with simplified algorithms. We evaluate and compare CMSN in terms of performance, effective lookups, and battery consumption.

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Research Article Mon, 1 Aug 2016 00:00:00 +0300
IntelliGOV - A Semantic Approach for Compliance Validation of Service-Oriented Architectures https://lib.jucs.org/article/23426/ JUCS - Journal of Universal Computer Science 22(8): 1048-1071

DOI: 10.3217/jucs-022-08-1048

Authors: Haroldo Maria Teixeira Filho, Leonardo Azevedo, Sean Wolfgand Matsui Siqueira

Abstract: Organizations are adopting Service-Oriented Architecture (SOA) to increase operation's efficiency and flexibility. To accomplish these goals, it is necessary to ensure that the architecture and its evolution are compliant with business goals, best practices, legal and regulatory requirements. However, the diversity of domains and stakeholders involved in SOA solutions demands complex and expensive work to validate the architecture compliance. Hence, it can result in high costs and low quality assessment if the organization does not use an effective approach in this scenario. In addition, it would be important to consider standards and open solutions in order to promote interoperability and reuse of available tools, making it easier to spread throughout the organizations. We propose intelliGov, an architecture that aims to solve these problems by using ontologies, semantic rules and queries in order to simplify the compliance validation process. The architecture employs open standards - OWL, SWRL and SQWRL - in its implementation. A case study, executed in a global energy company that is currently adopting SOA, demonstrates gains in quality and costs of the compliance assessment process using the proposed architecture.

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Research Article Mon, 1 Aug 2016 00:00:00 +0300
PLA Based Strategy for Solving RCPSP by a Team of Agents https://lib.jucs.org/article/23279/ JUCS - Journal of Universal Computer Science 22(6): 856-873

DOI: 10.3217/jucs-022-06-0856

Authors: Piotr Jędrzejowicz, Ewa Ratajczak-Ropel

Abstract: In this paper the dynamic interaction strategy based on the Population Learning Algorithm (PLA) for the A-Team solving the Resource-Constrained Project Scheduling Problem (RCPSP) is proposed and experimentally validated. The RCPSP belongs to the NP-hard problem class. To solve this problem a team of asynchronous agents (A-Team) has been implemented using multiagent system. An A-Team is the set of objects including multiple agents and the common memory which through interactions produce solutions of optimization problems. These interactions are usually managed by some static strategy. In this paper the dynamic learning strategy based on PLA is suggested. The proposed strategy supervises interactions between optimization agents and the common memory. To validate the proposed approach computational experiment has been carried out.

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Research Article Wed, 1 Jun 2016 00:00:00 +0300
TwiSNER: Semi-supervised Method for Named Entity Recognition from Text Streams on Twitter https://lib.jucs.org/article/23274/ JUCS - Journal of Universal Computer Science 22(6): 782-801

DOI: 10.3217/jucs-022-06-0782

Authors: Van Tran, Dosam Hwang, Jason Jung

Abstract: The data on Social Network Services (SNSs) has recently become an interesting source for researchers conducting different Natural Language Processing (NLP) experiments, such as sentiment analysis, information extraction, Named Entity Recognition (NER), and so on. The characteristics of SNS data are usually described as short, noisy, with insufficient supplemental information. They often contain grammatical errors, misspellings, and unreliable capitalization. Thus, standard NLP tools (e.g., NER systems) have difficulty obtaining good results when they are applied on these data, even if they perform well on well-formatted texts. Most of the traditional NER methods are based on supervised learning techniques that often require a large amount of standard training data to train a classifier. In this paper, we propose a method called TwiSNER to classify named entities in Twitter data (called tweets) by using a semi-supervised learning approach combined with the conditional random field model, hand-made rules, and the co-occurrence coefficient of the featured words surrounding entities. In the experiments, TwiSNER is applied on a dataset collected from Twitter, which includes 11,425 tweets for training with 4,716 labeled tweets and 1,450 tweets for testing. TwiSNER produces promising results, where the best F-measure is better than the baselines.

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Research Article Wed, 1 Jun 2016 00:00:00 +0300
A Proposal for Recommendation of Feature Selection Algorithm based on Data Set Characteristics https://lib.jucs.org/article/23272/ JUCS - Journal of Universal Computer Science 22(6): 760-781

DOI: 10.3217/jucs-022-06-0760

Authors: Saptarsi Goswami, Amlan Chakrabarti, Basabi Chakraborty

Abstract: Feature selection is an important prerequisite of any pattern recognition, machine learning or data mining problem. A lot of algorithms for feature subset selection have been developed so far for reduction of dimensionality of the data set in order to achieve high recognition accuracy with low computational cost. However, some methods or algorithms work well for some of the data sets and perform poorly on others. For any particular data set, it is difficult to find out the most suitable algorithm without some random trial and error process. It seems that the characteristics of the data set might have some effect on the algorithm for feature selection. In this work, the data set characteristics is studied for recommendation of appropriate feature selection algorithm to be used for a particular data set. A new proposal in terms of intra attribute relationship and a measure MVS (multivariate score) has been introduced to quantify and group different data sets on the basis of the data set correlation structure into several categories. The measure is used to group 63 publicly available bench mark data set according to their characteristics. The performance of different feature selection algorithms on different groups of data are then studied by simulation experiments to verify the relationship o f data set characteristics and the feature selection algorithm. The effect of some other data set characteristics has also been studied. Finally a framework of recommendation regarding the choice of proper feature selection algorithm has been indicated.

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Research Article Wed, 1 Jun 2016 00:00:00 +0300
An Aspect-Based Sentiment Analysis Approach to Evaluating Arabic News Affect on Readers https://lib.jucs.org/article/23206/ JUCS - Journal of Universal Computer Science 22(5): 630-649

DOI: 10.3217/jucs-022-05-0630

Authors: Mohammad Al-Smadi, Mahmoud Al-Ayyoub, Huda Al-Sarhan, Yaser Jararweh

Abstract: Great challenges arise due to the rapid growth of online data. The widespread use of online social networks (OSN) have enabled the generation of massive amounts of raw data where users post their own material. One interesting example of user generated data is their political views and opinions. The ability to crawl OSN and automatically analyze their political content is of undeniable importance. However, this requires automated methods for posts’ tone analysis, sentiment analysis, and emotional affect. The purpose of this paper is to evaluate Arabic news posts affect on readers using a novel approach of aspect-based sentiment analysis (ABSA). There are many tasks typically associated with ABSA such as the extraction and polarity identification of aspect terms and categories. The focus of this work is on the tasks related to aspect terms. A typical approach to address these tasks goes through several stages of text pre-processing, features extraction and classification. This paper follows this approach and makes use of widely used features and classifiers. The features considered include Part of Speech (POS) tagging, Named Entity Recognition (NER), and N-Grams. As for the considered classifiers, they are: Conditional Random Fields (CRF), Decision Tree (J48), Naive Bayes and K-Nearest Neighbor (IBk). A set of experiments are conducted to compare the considered classifiers against each other and against a baseline classifier that is very common for ABSA. The results show that the extracted features allow all of the four considered classifiers to significantly outperform the baseline classifier. They also show that J48 performs the best for the task of aspect terms extraction whereas CRF and Naive Bayes are slightly better in aspect terms polarity identification.

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Research Article Sun, 1 May 2016 00:00:00 +0300
Opinion Retrieval for Twitter Using Extrinsic Information https://lib.jucs.org/article/23205/ JUCS - Journal of Universal Computer Science 22(5): 608-629

DOI: 10.3217/jucs-022-05-0608

Authors: Yoon-Sung Kim, Young-In Song, Hae-Chang Rim

Abstract: Opinion retrieval in social networks is a very useful field for industry because it can provide a facility for monitoring opinions about a product, person or issue in real time. An opinion retrieval system generally retrieves topically relevant and subjective documents based on topical relevance and a degree of subjectivity. Previous studies on opinion retrieval only considered the intrinsic features of original tweet documents and thus suffer from the data sparseness problem. In this paper, we propose a method of utilizing the extrinsic information of the original tweet and solving the data sparseness problem. We have found useful extrinsic features of related tweets, which can properly measure the degree of subjectivity of the original tweet. When we performed an opinion retrieval experiment including proposed extrinsic features within a learning-to-rank framework, the proposed model significantly outperformed both the baseline system and the state-of-the-art opinion retrieval system in terms of Mean Average Precision (MAP) and Precision@K (P@K) metrics.

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Research Article Sun, 1 May 2016 00:00:00 +0300
A Novel Similar Temporal System Call Pattern Mining for Efficient Intrusion Detection https://lib.jucs.org/article/23120/ JUCS - Journal of Universal Computer Science 22(4): 475-493

DOI: 10.3217/jucs-022-04-0475

Authors: Vangipuram Radhakrishna, Puligadda Kumar, Vinjamuri Janaki

Abstract: Software security pattern mining is the recent research interest among researchers working in the areas of security and data mining. When an application runs, several process and system calls associated are invoked in background. In this paper, the major objective is to identify the intrusion using temporal pattern mining. The idea is to find normal temporal system call patterns and use these patterns to identify abnormal temporal system call patterns. For finding normal system call patterns, we use the concept of temporal association patterns. The reference sequence is used to obtain temporal association system call patterns satisfying specified dissimilarity threshold. To find similar (normal) temporal system call patterns, we apply our novel method which performs only a single database scan, reducing unnecessary extra overhead incurred when multiple scans are performed thus achieving space and time efficiency. The importance of the approach coins from the fact that this is first single database scan approach in the literature. To find if a given process is normal or abnormal, it is just sufficient to verify if there exists a temporal system call pattern which is not similar to the reference system call support sequence for specified threshold. This eliminates the need for finding decision rules by constructing decision table. The approach is efficient as it eliminates the need for finding decision rules (2n is usually very large for even small value of n) and thus aims at efficient dimensionality reduction as we consider only similar temporal system call sequence for deciding on intrusion.

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Research Article Fri, 1 Apr 2016 00:00:00 +0300
Fuzzy Modeling of User Behaviors and Virtual Goods Purchases in Social Networking Platforms https://lib.jucs.org/article/23055/ JUCS - Journal of Universal Computer Science 22(3): 416-437

DOI: 10.3217/jucs-022-03-0416

Authors: Jarosław Jankowski, Kostas Kolomvatsos, Przemysław Kazienko, Jarosław Wątróbski

Abstract: An important aspect of managing social platforms, online games and virtual worlds is the analysis of user characteristics related to subscriptions and virtual goods purchases. The results of such a process could be adopted in decision support applications that build on top of users' behavior provide efficient strategies for the virtual world's management. One of the research questions in this area is related to the factors affecting purchases and their relation to the activity within social networks as well as the ability to use past data to make reasoning about future behaviors. Complex online systems are hard to analyze when adopting legacy methodologies due to the huge amount of data generated by users' activity and changes in their behavior over time. In this paper, we discuss an analysis of the characteristics of users performing purchases for virtual products. We adopt a Neuro-Fuzzy system which has the ability to process data under uncertainty towards better decisions related to parameterization of the virtual retail system. The proposed Fuzzy Logic (FL) inference model focuses on the analysis of purchases based on the types of past transactions and social activity as inputs. The proposed system results values for specific parameters affecting/depicting users’ behavior like own purchases, gifting and virtual products usage as output. Our results could be adopted for decision support of online platform operators and show the relations between less and more experienced users in terms of frequency and value of purchases, engagement with the use of virtual goods and gifting behaviors. Models based on the social activity with distinguished inbound and outbound social connections show increased interest in virtual goods among users with a higher number of inbound connections as a possible tool for building social position.

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Research Article Tue, 1 Mar 2016 00:00:00 +0200
Mining Social Networks for Calculation of SmartSocial Influence https://lib.jucs.org/article/23054/ JUCS - Journal of Universal Computer Science 22(3): 394-415

DOI: 10.3217/jucs-022-03-0394

Authors: Vanja Smailovic, Vedran Podobnik

Abstract: In today's networked society where everybody and everything becomes inter-connected, it is very important to be able to identify key actors and key relationships in such a complex multi-layered eco-system. This paper focuses on the specific research challenge of identifying the most influential actors in a social network built through combining relationships among same actors in two different domains - communication domain (proxied through real-world mobile phone communication data) and social networking service domain (proxied through real-world Facebook data). A practical aspect of the paper is evaluated through the SmartSocial Platform, which uses methodology and implements algorithms that enable: i) joining multiple relations among actors across different social networks into the single unified social network; as well as ii) mining created unified social network for identification of most influential actors. Evaluation of the proposed approach is based on the social experiment with 465 users. Experiment results underline two important paper contributions: i) posting frequency sensitivity analysis shows a significant effect of posting frequency on social influence scores; and ii) interdependency analysis shows a synergic effect of combining data from communication and social networking service domains when it comes to calculating influence scores.

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Research Article Tue, 1 Mar 2016 00:00:00 +0200
Going beyond your Personal Learning Network, Using Recommendations and Trust through a Multimedia Question-Answering Service for Decision-support: a Case Study in the Healthcare https://lib.jucs.org/article/23051/ JUCS - Journal of Universal Computer Science 22(3): 340-359

DOI: 10.3217/jucs-022-03-0340

Authors: Patricia Santos, Sebastian Dennerlein, Dieter Theiler, John Cook, Tamsin Treasure-Jones, Debbie Holley, Micky Kerr, Graham Attwell, Dominik Kowald, Elisabeth Lex

Abstract: Social learning networks enable the sharing, transfer and enhancement of knowledge in the workplace that builds the ground to exchange informal learning practices. In this work, three healthcare networks are studied in order to understand how to enable the building, maintaining and activation of new contacts at work and the exchange of knowledge between them. By paying close attention to the needs of the practitioners, we aimed to understand how personal and social learning could be supported by technological services exploiting social networks and the respective traces reflected in the semantics. This paper presents a case study reporting on the results of two co-design sessions and elicits requirements showing the importance of scaffolding strategies in personal and shared learning networks. Besides, the significance of these strategies to aggregate trust among peers when sharing resources and decision-support when exchanging questions and answers. The outcome is a set of design criteria to be used for further technical development for a social semantic question and answer tool. We conclude with the lessons learned and future work.

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Research Article Tue, 1 Mar 2016 00:00:00 +0200
Evaluating the Relative Performance of Collaborative Filtering Recommender Systems https://lib.jucs.org/article/23834/ JUCS - Journal of Universal Computer Science 21(13): 1849-1868

DOI: 10.3217/jucs-021-13-1849

Authors: Humberto Jesús Corona Pampín, Houssem Jerbi, Michael P. O Mahony

Abstract: Past work on the evaluation of recommender systems indicates that collaborative filtering algorithms are accurate and suitable for the top-N recommendation task. Further, the importance of performance beyond accuracy has been recognised in the literature. Here, we present an evaluation framework based on a set of accuracy and beyond accuracy metrics, including a novel metric that captures the uniqueness of a recommendation list. We perform an in-depth evaluation of three well-known collaborative filtering algorithms using three datasets. The results show that the user-based and item-based collaborative filtering algorithms have a high inverse correlation between popularity and diversity and recommend a common set of items at large neighbourhood sizes. The study also finds that the matrix factorisation approach leads to more accurate and diverse recommendations, while being less biased toward popularity.

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Research Article Mon, 28 Dec 2015 00:00:00 +0200
Extending Mobile Cloud Platforms Using Opportunistic Networks: Survey, Classification and Open Issues https://lib.jucs.org/article/23755/ JUCS - Journal of Universal Computer Science 21(12): 1594-1634

DOI: 10.3217/jucs-021-12-1594

Authors: Shantanu Pal

Abstract: With the tremendous growth of mobile devices, e.g, smartphones, tablets and PDAs in recent years, people are looking for more advanced platforms in order to use their computational applications (e.g., processing and storage) in a faster and more convenient way. In addition, mobile devices are capable of using cloud-based applications and the use of such technology is growing in popularity. However, one major concern is how to efficiently access these cloud-based applications when using a resource-constraint mobile device. Because it requires a continuous Internet connection which is difficult to obtain in challenged environments that lack an infrastructure for communication (e.g., in sparse or rural areas) or areas with infrastructure (e.g., urban or high density areas) with restricted/full of interference access networks and even areas with high costs of Internet roaming. In these situations the use of opportunistic networks may be extended to avail cloud-based applications to the user. In this paper we explore the emergence of extending mobile cloud platforms using opportunistic networks. The motivation of this paper is twofold. First, we classify the available mobile cloud architectures according to their intent, the way they deliver services, and survey the state of the art research and issues related to their performance (e.g., battery power, storage capacity, bandwidth utilisation), environments (e.g., heterogeneity of networks, user's collaborations), robustness (e.g., scalability and availability of resources) and efficiency (e.g., context aware mobile services, access costs, energy consumption). Second, we devise a new `mobile-opportunistic collaborative cloud' (MoCC) architecture which enhances mobile cloud platforms using opportunistic networks. Next, we outline the open issues and future research directions that need to be improved upon for delivering a more scalable, location-aware and context based service to the users.

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Research Article Tue, 1 Dec 2015 00:00:00 +0200
Exploring the Impacts of Social Networking on Brand Image and Purchase Intention in Cyberspace https://lib.jucs.org/article/23651/ JUCS - Journal of Universal Computer Science 21(11): 1425-1438

DOI: 10.3217/jucs-021-11-1425

Authors: Hsing-Wen Wang, Yen-Chun Wu, Tse-Ping Dong

Abstract: Social networking websites have become increasingly popular, and have also become the main media not only to connect lives socially, but also to affect brand image and consumers' purchase intention. The purpose of this paper is to incorporate the Facebook fan page and e-journal provide over the Internet (cloud e-journal) with the uses and gratification theory to test the impact on brand image and purchase intention through the use of cloud learning. We used cloud learning material from the Ivy League in Taiwan in our case study. This paper also applied structural equation modeling to analyze the data collected from members of the Ivy League Facebook fan page and the Cloud users’ e-journal. The results of this study demonstrated that for the members of the Ivy League Facebook fan page, purchase intention was positively and significantly influenced, regardless of any use intention factors, based on the uses and gratification theory. In addition, using the Facebook fan page and Cloud e-journal would also positively and significantly affect the brand image for Internet users. Moreover, with the Ivy League fan page and the Cloud e-journal's improved brand image, there is an increase in intention to buy the journals and relevant services. This paper also demonstrated that six features of the Cloud e-journal did have a moderating effect on the purchase intention. Our results provide suggestions to those who attempt to build cloud learning solutions for customers, and are also helpful to those who wish to apply the Facebook fan page to customer relationship marketing platforms.

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Research Article Sun, 1 Nov 2015 00:00:00 +0200
Modelling and Linking Accessibility Data in the Public Bus Network https://lib.jucs.org/article/23258/ JUCS - Journal of Universal Computer Science 21(6): 777-795

DOI: 10.3217/jucs-021-06-0777

Authors: Paloma Cáceres, Almudena Sierra-Alonso, Carlos Cuesta, Belén Vela, José Cavero

Abstract: Many organizations and public administrations are currently working to open their data for the general use, in the context of the Linked Open Data (LOD) initiative. This emphasizes the need to publish available data in a structured format, so that they can be accessed and externally processed in order to maximize their utility for citizens. This also poses a general challenge in the area of information technologies, as it requires being able to integrate data from heterogeneous distributed sources, provided in a compatible format. We consider the specific domain of public transport networks, where the information has obviously a public interest. The processing of these data can be used for a wide variety of applications: route planning systems are a classic example. However, most of the existing approaches in this domain fail to provide specific means to deal with accessibility data, i.e. the information which is relevant for people with special mobility needs, especially when it is obtained from different transit networks. In this context, the LD approach is particularly useful, due to the complexity of those relationships and their inherently graph-oriented nature. In this work we describe the process we use to define this information and to make it available in the context of the CoMobility project. First, we define a conceptual model, supported by the main reference data models in the transport domain: Transmodel and IFOPT, and emphasizing the role of accessibility. We transform it into an ontology, in order to combine data from diverse sources; and then such concrete data are captured using the schema defined by this ontology. In this context, we use actual data from the public bus network in the City of Madrid. Afterwards we are able to define and build new mobility services, e.g. to automatically decide if a certain bus route is accessible or not, considering any potential transfers in this route. Finally, we are able to publish the obtained information, albeit partially, preserving the LOD spirit.

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Research Article Mon, 1 Jun 2015 00:00:00 +0300
Public Services Provided with ICT in the Smart City Environment: The Case of Spanish Cities https://lib.jucs.org/article/22961/ JUCS - Journal of Universal Computer Science 21(2): 248-267

DOI: 10.3217/jucs-021-02-0248

Authors: Daniel Perez-Gonzalez, Raimundo Díaz-Díaz

Abstract: Social, technological and economic changes, citizen demand of services modernization, new ICT developments related to the Internet of Things and an economic situation that urges more efficient public administrations, have allowed the adoption of ICT by municipalities in order to provide public services. All the foregoing constitutes a boost of the smart city concept, which is considered in the scientific literature mainly from a technical point of view, overlooking deeper analysis on the specific services being provided by means of smart technologies. The current research identifies services provided using smart technologies at 26 Spanish smart cities and the degree of smart development of those cities based on which services provide. The results highlight that the services most widely implemented are those that allow direct reductions in local administration expenditure. On the other hand, the remaining services enjoy greater perspectives of future development. Additionally, three groups of smart city development have been identified, which allows benchmarking analysis and enhances the exchange of information between the cities.

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Research Article Sun, 1 Feb 2015 00:00:00 +0200
An Adaptive Intent Resolving Scheme for Service Discovery and Integration https://lib.jucs.org/article/23819/ JUCS - Journal of Universal Computer Science 20(13): 1791-1812

DOI: 10.3217/jucs-020-13-1791

Authors: Cheng Zheng, Weiming Shen, Hamada Ghenniwa

Abstract: Service discovery and integration is an important research area with efforts invested to explore the potential advantages of collaborative computing in general and service-oriented computing in particular. However, current technologies still limit their application within the reach of enterprise systems or privately available services. Intents is an emerging and innovative technique aimed to discover and integrate publically available services. In Intents, intent message resolving is a critical step which is deemed to decide the quality of the whole system. However, existing schemes applied in intent resolving adopt the exact-matching strategy which may rule out services desired by the user. This paper brings in information retrieval techniques and applies them to intent resolving. We take an empirical approach through extensive experiments and analyses on a real dataset to obtain guiding principles. Based on the resulting principles, an adaptive intent resolving scheme is designed. Afterwards, we integrate the scheme into the Intents user agent developed in a previous project.

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Research Article Fri, 28 Nov 2014 00:00:00 +0200
Context Classification Framework for Handset-based End User Studies https://lib.jucs.org/article/23868/ JUCS - Journal of Universal Computer Science 20(14): 1964-1986

DOI: 10.3217/jucs-020-14-1964

Authors: Tapio Soikkeli, Juuso Karikoski, Heikki Hämmäinen

Abstract: Utilizing rich end user context information is viewed as one of the necessary approaches in developing more personalized mobile services and user experiences. The practical impact of end user context research and new opportunities in the field provided by emerging data collection methods such as handset-based measurements (i.e., collecting usage data directly from the end users' devices) have inspired new highly interesting large scale empirical context studies, but also brought quite diverse usage of the term context itself. Proper discussion and usage of context requires an unambiguous statement of how the term is understood in the particular case. On one hand the term should be positioned with the existing and commonly understood general definitions, but on the other hand it should also be acknowledged that especially an empirical research paper, or a context-aware service, can grasp only some specific aspects or elements of context. This paper proposes a context classification framework that aims to clarify the use of the term context in handset-based related end user studies. The framework is partly based on the experimental experience accumulated in our own handset panel studies. While helping researchers to plan context data acquisition and communicate and position the end user context elements used, the framework helps other stakeholders, such as application developers and service providers, to identify and utilize research and data most relevant for their particular needs. The paper also demonstrates the expressivity of the framework by examples.

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Research Article Sat, 1 Nov 2014 00:00:00 +0200
A Secure Multi-Layer e-Document Method for Improving e-Government Processes https://lib.jucs.org/article/23647/ JUCS - Journal of Universal Computer Science 20(11): 1583-1604

DOI: 10.3217/jucs-020-11-1583

Authors: Gia Vo, Richard Lai

Abstract: In recent years, there has been a tremendous growth in e-Government services due to advances in Information Communication Technology and the number of citizens engaging in e-Government transactions. In government administration, it is very time consuming to process different types of documents and there are many data input problems. There is also a need to satisfy citizens’ requests to retrieve government information and to link these requests to build an online document without asking the citizen to input the data more than once. To provide an e-Government service which is easy to access, fast and secure, the e-Document plays an important role in the management and interoperability of e-Government Systems. To meet these challenges, this paper presents a Secure Multilayer e-Application (SMeA) method for improving e-Government processes. This method involves five steps: namely (i) identifying an e-Template; (ii) building a SMeA; (iii) mapping the data; (iv) processing the e-Application; and (v) approving the e-Application. The first step involves requirements analysis and the last four involve data analysis for building a SMeA. To demonstrate its usefulness, we applied SMeA to a case study of an application for a licence to set up a new business in Vietnam.

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Research Article Tue, 28 Oct 2014 00:00:00 +0200
Middleware-Oriented Government Interoperability Frameworks: A Comparison https://lib.jucs.org/article/23645/ JUCS - Journal of Universal Computer Science 20(11): 1543-1563

DOI: 10.3217/jucs-020-11-1543

Authors: Giansalvatore Mecca, Michele Santomauro, Donatello Santoro, Enzo Veltri

Abstract: We discuss deployment solutions for e-Government Interoperability Frameworks (GIFs). We concentrate on middleware-oriented GIFs, i.e., those in which middleware modules act as intermediaries among information systems that need to exchange data and services. A prominent example is the Italian SPCoop interoperability framework. We review the SPCoop architecture, and two popular open-source implementations of its core modules, called OpenSPCoop and freESBee. We argue that the comparison of these two solutions is relevant since they obey to radically different philosophies, both in terms of the relationship to the underlying J2EE container, and of their internal module organization. Then, we discuss one of the main problems in large-scale deployment of SPCoop-like GIFs, namely the need to quickly deploy a large number of middleware instances over a relatively small number of servers. We report a number of experiments to discuss how the different design choices impact performance. To the best of our knowledge, this is the first large-scale test of the framework, from which a number of important lessons can be learned.

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Research Article Tue, 28 Oct 2014 00:00:00 +0200
An Adaptive and Social-Aware Recommendation Algorithm for Administration Services https://lib.jucs.org/article/23643/ JUCS - Journal of Universal Computer Science 20(11): 1523-1542

DOI: 10.3217/jucs-020-11-1523

Authors: Luis M. Álvarez Sabucedo, Roberto Barreiros, Juan M. Santos Gago, Manuel J. Fernández Iglesias

Abstract: This paper addresses the recommendation of online services provided by public administrations taking into account both the specific characteristics of these services and the perception of other citizens. The solution discussed is based on an enhanced hybrid model that relies on content-based and collaborative strategies aimed to exploit the information shared by other users to validate the quality of the recommendations provided. As a relevant feature, the proposed schema takes advantage of an automatic compensation of the mentioned strategies. To make the most of theses two approaches, the use of semantics is introduced to describe knowledge and to make smart recommendation decisions. To facilitate the task of other researchers and practitioners, details about the actual development and validation of the proposed model are also included in the paper, making it possible its replication in other environmentsEurope is involved in a process of transition to digital terrestrial television that is aimed to replace all analog broadcasting infrastructures into digital ones by year 2012. Besides the substitution of all broadcasting networks scattered around Europe, this process includes the replacement of all household elements related to the reception of terrestrial television emissions, namely television appliances and antenna settings. As in any major change in the every-day life of citizens, public administrations must keep citizen informed and provide convenient support, specially when dealing with the a communication medium designated to be the carriers of services and information. This paper tackles how this situation has been faced in Galicia, a European region with special needs in this area, as shown in the paper. Through a successful use case based on Geographical Information Services and Web2.0 technologies, we illustrate some features not present in related initiatives in other areas.

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Research Article Tue, 28 Oct 2014 00:00:00 +0200
ICTs, Mobile Learning and Social Media to Enhance Learning for Attention Difficulties https://lib.jucs.org/article/23573/ JUCS - Journal of Universal Computer Science 20(10): 1499-1510

DOI: 10.3217/jucs-020-10-1499

Authors: Athanasios Drigas, Rodi-Eleni Ioannidou, Georgia Kokkalia, Miltiadis Lytras

Abstract: Recent development in the role of Information and Communication Technologies (ICTs) at the field of special education is thought significant. ICT nowadays is recognized as a tool that can foster the knowledge and the experiences in the areas of needs it serves as it is considered significant for teaching and learning process. In the last decade, a number of studies have demonstrated the benefits of various forms of ICTs tools for children with attention difficulties and hyperactivity disorders (ADHD). These tools can be employed to facilitate and train young learners, as well as can help them to increase their quality of life and functional independence. In this paper we present a brief review of the most representative research papers for computer-based applications for diagnosis and intervention purposes included the mobile learning and social media for technology enhanced learning for people with Attention Deficit Hyperactivity Disorder.

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Research Article Wed, 1 Oct 2014 00:00:00 +0300
Some Aspects of the Reliability of Information on the Web https://lib.jucs.org/article/23488/ JUCS - Journal of Universal Computer Science 20(9): 1284-1303

DOI: 10.3217/jucs-020-09-1284

Authors: Narayanan Kulathuramaiyer, Hermann Maurer, Rizwan Mehmood

Abstract: When we look up information in the WWW we hope to find information that is correct, fitting in quantity for our purposes and written at a level that we can understand. Unfortunately, very often one of the above criteria will not be met. A young person looking for information on some aspect of physics may well be frustrated when finding a complex formula whose understanding requires higher mathematics. In other cases, information may be much too voluminous or too short. This seems to indicate that what we need is presentation of material at various levels of detail and complexity. But most important of all, and this is what we are going to discuss in this paper is: how do we know that what we read is actually true? We will analyse this problem in the introductory section. We will show that it is impossible to expect "too much". We will argue that some improvements can be made, particularly if the domain is restricted. We will then examine certain types of geographical information. Detailed research shows that some quantitative measurements like the area of a country or the highest mountains of a country, even if different sources disagree, can be verified by explaining why the discrepancies occur and by trusting numbers if they are identical in very different databases.

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Research Article Mon, 1 Sep 2014 00:00:00 +0300
Capturing and Relating Multilingual Clinical Cases https://lib.jucs.org/article/23482/ JUCS - Journal of Universal Computer Science 20(9): 1154-1173

DOI: 10.3217/jucs-020-09-1154

Authors: Renato Bulcão-Neto, José Antonio Camacho Guerrero, Paulo Schor, Alessandra Lopes, Marcio Dutra, Alessandra Macedo

Abstract: Recent studies reveal that the Internet use has grown tremendously in the past few years, most rapidly in non-English-speaking regions. However, this scenario creates a demand for innovative information retrieval services to better support a world wide community. This paper presents the MedLink linking service, which automatically identifies semantic relationships among multilingual clinical cases and makes them available to users as hyperlinks. As a proof of concept, we also present an experiment relating multilingual clinical cases in Ophthalmology, where the relationships created by MedLink were qualitatively analyzed by a Faculty with strong Ophthalmology background. Analysis results are described in terms of the completeness and the fidelity of the relationships created, which can be most useful in a globalized world for several purposes including research, teaching, and presurgical decision making.

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Research Article Mon, 1 Sep 2014 00:00:00 +0300
Internet of Things Aware WS-BPEL Business Processes Context Variables and Expected Exceptions https://lib.jucs.org/article/23413/ JUCS - Journal of Universal Computer Science 20(8): 1109-1129

DOI: 10.3217/jucs-020-08-1109

Authors: Dulce Domingos, Francisco Martins, Carlos Cândido, Ricardo Martinho

Abstract: Business processes can use Internet of Things (IoT) information to monitor context data in real-time and to respond to changes in their values in a timely fashion. For this matter, business process definition and execution languages should foresee an easy way for process modelers to define which values to monitor, and which automatic behaviors to adopt when these values change. In this paper, we propose the use of context variables to monitor sensor values, as well as a when-then language construct to detect and handle changes in these values within business processes. We define a Web Services Business Process Execution Language (WS-BPEL) extension to convey these constructs, and implement then using a "BPEL language transformation" approach. With these contributions, process modelers can define IoT-aware business processes avoiding the increase of process complexity and keeping their focus on modeling the processes' main logic. In addition, the language transformation approach assures the portability of processes using our constructs amongst WS-BPEL execution engines.

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Research Article Fri, 1 Aug 2014 00:00:00 +0300
Decision Support System to Diagnosis and Classification of Epilepsy in Children https://lib.jucs.org/article/23254/ JUCS - Journal of Universal Computer Science 20(6): 907-923

DOI: 10.3217/jucs-020-06-0907

Authors: Rui Rijo, Catarina Silva, Luis Pereira, Dulce Gonçalves, Margarida Agostinho

Abstract: Clinical decision support systems play an important role in organizations. They have a tight relation with the information systems. Our goal is to develop a system to support the diagnosis and the classification of epilepsy in children. Around 50 million people in the world have epilepsy. Epilepsy diagnosis can be an extremely complex process, demanding considerable time and effort from physicians and healthcare infrastructures. Exams such as electroencephalograms and magnetic resonances are often used to create a more accurate diagnosis in a short amount of time. After the diagnosis process, physicians classify epilepsy according to the International Classification of Diseases, ninth revision (ICD-9). Physicians need to classify each specific type of epilepsy based on different data, e.g., types of seizures, events and exams' results. The classification process is time consuming and, in some cases, demands for complementary exams. This work presents a text mining approach to support medical decisions relating to epilepsy diagnosis and ICD-9-based classification in children. We put forward a text mining approach using electronically processed medical records, and apply the K-Nearest Neighbor technique as a white-box multiclass classifier approach to classify each instance, mapping it to the corresponding ICD-9-based standard code. Results on real medical records suggest that the proposed framework shows good performance and clear interpretations, albeit the reduced volume of available training data. To overcome this hurdle, in this work we also propose and explore ways of expanding the dataset.

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Research Article Sun, 1 Jun 2014 00:00:00 +0300
The Role of Absorptive Capacity in the Usage of a Complex Information System: The Case of the Enterprise Information System https://lib.jucs.org/article/23249/ JUCS - Journal of Universal Computer Science 20(6): 826-841

DOI: 10.3217/jucs-020-06-0826

Authors: Maral Mayeh, Thurasamy Ramayah, Simona Popa

Abstract: The purpose of this study is to model the relationship between absorptive capacity and intention to use in the Enterprise Resource Planning (ERP) environment in Iran. This research is a correlation study where a field survey was employed for data collection. The unit of analysis is Iranian individuals who are ERP user in organizations using ERP systems. The questionnaires were sent to the selected organizations. Using a structural equation modeling analysis we tested the hypothesized relationship using AMOS version 16.0. The results indicate that all three absorptive capacity measures to be good predictors of intention to use. Absorptive capacity for applying was the strongest predictor followed by absorptive capacity for understanding and absorptive capacity for assimilating. When implementing complex information systems, managers must also look at the absorptive capacity of the users in order to successful implementation of the system and to ensure continued usage. Previous researchers have not looked at the role of absorptive capacity in system usage at the same rate as those related to technology acceptance research which only focuses on the ease of use and usefulness. Thus this research adds on to the existing literature where future researchers may want to expand on the factors that may influence absorptive capacity for further policy implications.

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Research Article Sun, 1 Jun 2014 00:00:00 +0300
A Framework for Cost-Aware Process Management: Cost Reporting and Cost Prediction https://lib.jucs.org/article/23031/ JUCS - Journal of Universal Computer Science 20(3): 406-430

DOI: 10.3217/jucs-020-03-0406

Authors: Moe Wynn, Wei Low, Arthur H. M. Ter Hofstede, Wiebe Nauta

Abstract: Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

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Research Article Sat, 1 Mar 2014 00:00:00 +0200
Automatic Authentication to Cloud-Based Services https://lib.jucs.org/article/23030/ JUCS - Journal of Universal Computer Science 20(3): 385-405

DOI: 10.3217/jucs-020-03-0385

Authors: Mircea Vleju

Abstract: We describe the concept of automatic authentication for cloud-based services via the use of a client-centric solution for small and medium enterprises (SMEs). In previous work we have introduced the Identity Management Machine (IdMM) whichis designed to handle the interaction between a client's identity directory and various cloud identity management systems. We now further refine this machine by describingits interaction with various cloud authentication systems. The IdMM is designed to aid SMEs in their adoption or migration to cloud-based services. The system allowsSMEs to store its confidential data on-premise, enhancing the client's control over the data. We further enhance the privacy related aspects of a client-to-cloud interaction viathe introduction of obfuscated and partially obfuscated identities which allow SMEs to also choose the type of data being sent to a cloud service. Since the IdMM is a singlesign-on system capable of automatic authentication the risk of phishing or other social engineering attacks is reduced as an individual user may not be aware of his or hercredentials for a given cloud service.

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Research Article Sat, 1 Mar 2014 00:00:00 +0200
Combining Psycho-linguistic, Content-based and Chat-based Features to Detect Predation in Chatrooms https://lib.jucs.org/article/22953/ JUCS - Journal of Universal Computer Science 20(2): 213-239

DOI: 10.3217/jucs-020-02-0213

Authors: Javier Parapar, David Losada, Álvaro Barreiro

Abstract: The Digital Age has brought great benefits for the human race but also some draw-backs. Nowadays, people from opposite corners of the World can communicate online via instant messaging services. Unfortunately, this has introduced new kinds of crime. Sexual predators haveadapted their predatory strategies to these platforms and, usually, the target victims are kids. The authorities cannot manually track all threats because massive amounts of online conversationstake place in a daily basis. Automatic methods for alerting about these crimes need to be designed. This is the main motivation of this paper, where we present a Machine Learning approachto identify suspicious subjects in chat-rooms. We propose novel types of features for representing the chatters and we evaluate different classifiers against the largest benchmark available.This empirical validation shows that our approach is promising for the identification of predatory behaviour. Furthermore, we carefully analyse the characteristics of the learnt classifiers. Thispreliminary analysis is a first step towards profiling the behaviour of the sexual predators when chatting on the Internet.

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Research Article Sat, 1 Feb 2014 00:00:00 +0200
A Virtual Reality Test for the Identification of Memory Strengths of Dyslexic Students in Higher Education https://lib.jucs.org/article/23966/ JUCS - Journal of Universal Computer Science 19(18): 2698-2721

DOI: 10.3217/jucs-019-18-2698

Authors: Katerina Kalyvioti, Tassos Mikropoulos

Abstract: Research suggests that Virtual Reality has a key role in the development of new diagnostic tools in neuropsychology and shows great rehabilitative potentials for individuals with specific neurological, intellectual and cognitive disabilities. In the case of dyslexia, a neurodevelopmental reading disorder, the use of Virtual Reality technologies has only been recently documented in a handful of studies. The main focus of these studies has been the identification of visuospatial strengths, the exploration of nonverbal problem solving treatment and the increase of awareness in educators and parents with children with dyslexia. Even fewer are the studies of Virtual Reality and the lifelong memory difficulties of adult individuals with dyslexia. With a more clinical, rather than technological, perspective the goal of this paper was to design specialized tasks in virtual environments to be part of a screening process/assessment of characteristic memory difficulties for undergraduate students diagnosed with dyslexia. Results showed that there were no statistically significant differences in the performance of students with dyslexia and students without dyslexia, a finding which highlights the development and successful use of compensatory memory strategies by the participants with dyslexia. Taking into consideration the real life representations, the multisensory approach, the increased sense of presence, the well-designed tasks and the recorded positive attitude of all participants, the study concludes that the use of Virtual Reality in neurological and neurodevelopmental memory disorders will be innovative and suggests that hands on Virtual Reality applications, become an indispensable part of these deficits' cognitive assessment and rehabilitation.

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Research Article Sun, 1 Dec 2013 00:00:00 +0200
Self-Aware Trader: A New Approach to Safer Trading https://lib.jucs.org/article/23892/ JUCS - Journal of Universal Computer Science 19(15): 2292-2319

DOI: 10.3217/jucs-019-15-2292

Authors: Javier Fernández, Juan Augusto, Giuseppe Trombino, Ralf Seepold, Natividad Madrid

Abstract: Traders are required to work in the financial market with highly complex information and to perform efficiently under high levels of psychological pressure. Multiple disciplines, from programs with artificial intelligence to complex mathematical functions, are used to help traders in their effort to maximize profits. However, an essential problem not yet considered in this rapidly evolving environment is that traders are not supported to adequately manage how stress influences their decisions. This paper takes into consideration the negative influences of stress on individuals and proposes a system designed to support traders by providing them with information that can reduce the likelihood of poor decision-making. The system has been designed considering both technical and physiological aspects to make information available in a suitable way. Biometric sensors are used to collect data associated with stress, a software platform then analyses this information and displays it to the trader. The resulting system is capable of making individual traders, as well as teams of traders, self-aware of their levels of stress. The system has been tested in real environments and the results provide evidence that self-aware traders benefit from the system by reducing risky decision-making.

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Research Article Sun, 1 Sep 2013 00:00:00 +0300
Ontology Combined Structural and Operational Semantics for Resource-Oriented Service Composition https://lib.jucs.org/article/23812/ JUCS - Journal of Universal Computer Science 19(13): 1963-1985

DOI: 10.3217/jucs-019-13-1963

Authors: Cheng Xie, Hongming Cai, Lihong Jiang

Abstract: Resource-oriented Services recently become an enabling technology to integrate and configure information from different heterogeneous systems so as to meet ever-changing environment which not only need the concepts for entities but also require the semantics for operations. By the aim of combining structural and operational semantics agilely, a Semantic Resource Service Model (SRSM) is proposed. Firstly, SRSM describes Entity-Oriented and Transition-Oriented Resource by semantic meta-model which contains data structures and operation semantics. Secondly, by describing structural semantics for Entity-Oriented Resource, heterogonous inputs/outputs of a service can be automatically matched. Thirdly, by describing operational semantics for Transition-Oriented Resource, the service composition sequence can be inferred after ontology reasoning. Then, both Entity-Oriented and Transition-Oriented Resources are encapsulated into composited RESTful service. At last, a case study and several comparisons are applied in a prototype system. The result shows that the proposed approach provides a flexible way for resource-oriented service composition.

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Research Article Mon, 1 Jul 2013 00:00:00 +0300
Business Process Management Applications based on Semantic Process Models: the ProcessGene Suite Case-Study https://lib.jucs.org/article/23808/ JUCS - Journal of Universal Computer Science 19(13): 1892-1913

DOI: 10.3217/jucs-019-13-1892

Authors: Avi Wasser, Maya Lincoln

Abstract: In recent years, Business Process Management (BPM) applications have become central enablers for the generation, customization and utilization of business processes within and between organizations. One of the central techniques for extending the span of BPM applications is Natural Language Processing (NLP). This work aggregates and reviews previous works on NLP standardization for BPM. Based on these works, we present a set of BPM applications, aiming at extending the utilization of the knowledge embedded in business process repositories. To verify the industrial deployment, we then present an extended case study that examines the feasibility of the suggested applications in real life scenarios using the ProcessGene BPM suite.

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Research Article Mon, 1 Jul 2013 00:00:00 +0300
Promoting International Interoperability of Research Information Systems: VIVO and CERIF https://lib.jucs.org/article/23735/ JUCS - Journal of Universal Computer Science 19(12): 1854-1867

DOI: 10.3217/jucs-019-12-1854

Authors: Leonardo Lezcano, Brigitte Jörg, Brian Lowe, Jon Corson-Rikert

Abstract: Institutional repositories (IR) and Current Research Information Systems (CRIS) store and manage information on the context in which research activity takes place. Several models, standards and ontologies have been proposed to date as solutions to provide coherent semantic descriptions of research information. These present a large degree of overlap but also present very different approaches to modelling. This paper introduces a contrast of two of the more widespread models, the VIVO ontology and the CERIF standards, and provides guidance for mapping them in a way that enables clients to integrate data coming from heterogeneous sources. The majority of mapping challenges have risen from the representation of VIVO sub-hierarchies in CERIF as well as from the representation of CERIF attributes in VIVO. In addition, the paper illustrates features for linking data across the Web, for querying of geographically distributed data stores and for aggregating data described using different data models in a common store. These features are supported by semantic web technologies including RDF, OWL and SWRL.

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Research Article Fri, 28 Jun 2013 00:00:00 +0300
Applying Professional Solutions within the Educational Environments by Means of Cloud Computing: Coaching for Teachers https://lib.jucs.org/article/23725/ JUCS - Journal of Universal Computer Science 19(12): 1703-1717

DOI: 10.3217/jucs-019-12-1703

Authors: Habib Fardoun, Abdulfattah Mashat, Sebastián López

Abstract: In a world where the most used sentences is: "I haven't got the time..." Information Technologies (IT) plays an important role in supporting our daily work, including in everyday educational settings. Such technologies can aid a complete educational system to function successfully so to help the whole school educational life. For this to prove, we present the "Coaching for Teacher" system, a personal technological conversational coach; it aims to provide solutions to overcome difficulties that teachers face during their teaching and learning process. In real time, a teacher can appeal and seek advice rapidly by comfortably talking to an agent. In this paper, we present the steps we followed to design and develop this agent-based application, and a case study conducted in an educational centre for proof that the concept works in an authentic educational environment.

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Research Article Fri, 28 Jun 2013 00:00:00 +0300
Socio-semantic Integration of Educational Resources - the Case of the mEducator Project https://lib.jucs.org/article/23629/ JUCS - Journal of Universal Computer Science 19(11): 1543-1569

DOI: 10.3217/jucs-019-11-1543

Authors: Stefan Dietze, Eleni Kaldoudi, Nikolas Dovrolis, Daniela Giordano, Concetto Spampinato, Maurice Hendrix, Aristidis Protopsaltis, Davide Taibi, Hong Yu

Abstract: Research in technology-enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, such as IEEE LOM or ADL SCORM, and interface mechanisms, such as OAI-PMH, SQI and REST-ful services in general. More recently, semantic technologies were taken into account to improve interoperability. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de facto standard for sharing data on the Web and is fundamentally based on established W3C standards. This paper presents results of the European Commission-funded project mEducator, which exploits Linked Data principles for (1) semantic integration and (2) social interconnecting of educational data, resources and actors. We describe a general approach to exploit the wealth of already existing educational data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide a rich and well-interlinked graph for the educational domain. Additionally, the paper presents an evaluation of our work with respect to a set of socio-semantic dimensions. Experimental results demonstrate improved interoperability and retrievability of the resulting resource descriptions as part of an interlinked resource graph.

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Research Article Sat, 1 Jun 2013 00:00:00 +0300
Interactive Design System for Schools using Cloud Computing https://lib.jucs.org/article/23321/ JUCS - Journal of Universal Computer Science 19(7): 950-964

DOI: 10.3217/jucs-019-07-0950

Authors: Habib Fardoun, Bassam Zafar, Abdulrahman Altalhi, Antonio Paules

Abstract: The design of an educational system involves a good understanding of the whole school environment in order to find the correct approach to develop a comprehensive educational system that will meet real educational needs in their operation. This article describes a design model for an educational system based on the teaching methods applied in the Spanish classrooms, which takes into account new advances in technology, while preserving the current teaching methods in the classroom to ensure a quality teaching and learning process. This development has been achieved by combining technological components such as Cloud Computing, Web Services and Distributed User Interfaces. The proposed system is based on a systematic approach where different phases are implemented, containing workflows and stages.

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Research Article Mon, 1 Apr 2013 00:00:00 +0300
PETs at CSCL Service: Underutilised Potentials for Privacy Enhancing Distance Education https://lib.jucs.org/article/23319/ JUCS - Journal of Universal Computer Science 19(7): 912-931

DOI: 10.3217/jucs-019-07-0912

Authors: Mohamed Bourimi, Dogan Kesdogan, Marcel Heupel, Dhiah el Diehn I Abou-Tair, Niki Lambropoulos

Abstract: Computer Supported Collaborative Learning (CSCL) support is currently widely accepted to provide reliable and valid formal and informal educational practices as proven to benefit students in onsite as well as distant educational settings. However, some results from case studies indicate that privacy problems could negatively affect CSCL implementation in educational settings. Privacy Enhancing Technologies research (PETs) and the development of multilaterally secure systems are still limited research topics within CSCL due to diverse reasons. Based on deep related literature analysis and previous research results conducted by the authors in building CSCL systems, three main categories were identified for such reasons that have an impact in PETs and multilateral security research: lack of awareness of such PETs’ existence; lack of knowledge on ways to efficiently integrate them in CSCL systems and settings; and reluctance to consider their multilaterally secure implementation by CSCL participations due to conflict of interests (e.g. explicit students monitoring requirements, high integration costs, etc.). In this paper, these categories are addressed and the PETs potential is discussed for overcoming the associated emerging drawbacks focused on the distance education CSCL settings in particular. The result of our research is an integrated framework considering multilateral security requirements. Furthermore, proof of concept is provided; enhanced privacy in such settings is applied by demonstrating the fulfilment of selected improvements areas (i.e. mainly network, application anonymity, and process support for resolving potential multilateral security conflicts) in an existing collaborative distance education system.

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Research Article Mon, 1 Apr 2013 00:00:00 +0300
Tweeters on Campus: Twitter a Learning Tool in Classroom? https://lib.jucs.org/article/23177/ JUCS - Journal of Universal Computer Science 19(5): 672-691

DOI: 10.3217/jucs-019-05-0672

Authors: Amandeep Dhir, Khalid Buragga, Abeer Boreqqah

Abstract: Twitter is a well-known Web 2.0 microblogging social networking site that is quite popular for organizing events and sharing updates. It provides just in time communication, social connectivity and immediate feedback through Web, smartphones, tablet PCs, etc. The use of Twitter has also attracted educators and researchers due to its growing popularity among students, teachers, and academic communities as a whole. This study provides a critical review of Twitter use in educational settings. By practicing a systematic research methodology in the selection and review of literature, different pedagogical and instructional benefits and drawbacks of Twitter use in education were discussed. Based on these discussions, it was discovered that Twitter has positive impact on informal learning, class dynamics, motivation, as well as the academic and psychological development of young students. However, the potential long-term impact of Twitter on academic performance of students and its long-term effect on learning is still worth investigating. 

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Research Article Fri, 1 Mar 2013 00:00:00 +0200
Analysis of Mobile Service Usage Behaviour with Bayesian Belief Networks https://lib.jucs.org/article/23010/ JUCS - Journal of Universal Computer Science 19(3): 325-352

DOI: 10.3217/jucs-019-03-0325

Authors: Pekka Kekolahti, Juuso Karikoski

Abstract: The purpose of this paper is to identify probabilistic relationships of mobile service usage behaviour, and especially to understand the probabilistic relationship between overall service usage diversity and average daily service usage intensity. These are topical themes due to the high number of services available in application stores which may or may not lead to high usage diversity of mobile services. Four analytical methods are used in the study, all are based on Bayesian Networks; 1) Visual analysis of Bayesian Networks to find initially interesting patterns, variables and their relationships, 2) user segmentation analysis, 3) node force analysis and 4) a combination of expert-based service clustering and machine learning for usage diversity vs. intensity analysis. All the analyses were conducted with handset-based data collected from university students and staff. The analysis indicates that services exist, which mediate usage of other services. In other words, usage of these services increases the probability of using also other services. A service called Installer is an example of this kind of a service. In addition, probabilistic relationships can be found within certain service cluster pairs in their usage diversity and intensity values. Based on these relationships, similar mediation type of behaviour can be found for service clusters as for individual services. This is most visible in the relation between System/Utilities and Business/Productivity service clusters. They do not have a direct relationship but usage diversity is a mediator between them. Furthermore, segmentation analysis shows that the user segment called "experimentalists" uses more mediator services than other user segments. Furthermore, "experimentalists" use a much broader set of services daily, than the other segments. This study demonstrates that a Bayesian Network is a straightforward way to express model characteristics on high level. Moreover, Node Force, Direct and Total effect are useful metrics to measure the mediation effects. The clustering implemented as a hybrid of machine learning and expert-based clustering process is also a useful way to calculate relationships between clusters of more than a hundred individual services.

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Research Article Fri, 1 Feb 2013 00:00:00 +0200
Model-Driven Framework for Design and Production of Low-Budget Stereoscopic TV Content https://lib.jucs.org/article/22863/ JUCS - Journal of Universal Computer Science 19(1): 78-109

DOI: 10.3217/jucs-019-01-0078

Authors: Aleksandar Spasić, Dragan Jankovic

Abstract: Three-dimensional television (3D TV) is expected by many to be the next step in the advancement of television. Due to significant financial exhaustion during the process of transition from analogue to digital production, low-budget broadcasters are not in the position to invest in a new 3D system. This paper proposes one model-driven framework approach to 3D TV production system applicable to and suitable for low-budget broadcasters. The target of the project is to define one of the possible scenarios for applying stereoscopic 3D technologies to low-budget TV production. 3D TV content production chain is described in the first step of the project. 3D TV production workflow is proposed in the second step. This step has two parts: the analyses of the production stages and their integral processes, and the definition of a problem space model which is suitable for low-budget 3D TV production. The preproduction, production and postproduction phases of a low-budget 3D TV production are described during the analyses of 3D TV content production workflow. The UML is used as a modelling tool. The behavioural description of a program production is modelled by the Use Case diagram. A state machine diagram is used to describe the dynamic behavioral representation and the life cycle of a 3D content. The flow and dependencies in 3D workflow are modelled by using the activity diagrams. The structural static representation (domain model) is presented by a class diagram.

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Research Article Tue, 1 Jan 2013 00:00:00 +0200
Ontology-based Approach to Competence Profile Management https://lib.jucs.org/article/23984/ JUCS - Journal of Universal Computer Science 18(20): 2893-2919

DOI: 10.3217/jucs-018-20-2893

Authors: Vladimir Tarasov

Abstract: Competence management has received much attention during recent years because it contributes to achieving organizational goals and solving problems such as improvement of information flow or competence supply. Many approaches were proposed to modelling competence and using competence models but there is still a lack of research into structures and utilisation of competence profiles in a competence management system. This article addresses this problem by proposing a formal approach to competence profile management. Four project cases are first analysed to elicit requirements of competence profile management, including competence profile operations. After that, an abstract model of competence profile management is formally defined based on the requirements. Finally, an ontology-based implementation of the abstract model is presented including a software architecture of a competence profile management system. The main contribution of this work is formalization of operations on competence profiles and ontology-based implementation of these operations. The proposed implementation architecture can facilitate construction of a competence profile management system.

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Research Article Sat, 1 Dec 2012 00:00:00 +0200
Metamodeling the Structure and Interaction Behavior of Cooperative Component-based User Interfaces https://lib.jucs.org/article/23972/ JUCS - Journal of Universal Computer Science 18(19): 2669-2685

DOI: 10.3217/jucs-018-19-2669

Authors: Luis Iribarne, Nicolas Padilla, Javier Criado, Cristina Vicente-Chicote

Abstract: In Web-based Cooperative Information Systems (WCIS), user groups with different roles cooperate through specialized interfaces. Cooperative interaction and user interface structures are usually rather complicated, and modeling has an important part in them. Model-Driven Engineering (MDE) is a software engineering discipline which assists engineers in abstracting system implementations by means of models and metamodels. This article describes an interactive, structural metamodel for user interfaces based on component architectures as a way to abstract, model, simplify and facilitate implementation. The paper also presents a case study based on an Environmental Management Information Systems (EMIS), where three actors (a politician, a GIS expert, and a technician) cooperate in assessing natural disasters.

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Research Article Thu, 1 Nov 2012 00:00:00 +0200
A Conceptual Ontology-based Resource Meta-Model towards Business-driven Information System Implementation https://lib.jucs.org/article/23943/ JUCS - Journal of Universal Computer Science 18(17): 2493-2513

DOI: 10.3217/jucs-018-17-2493

Authors: Hongming Cai, Boyi Xu, Fenglin Bu

Abstract: Enterprises need a flexible and configurable IT architecture to meet complex business requirements agilely. For the purpose of bridging business modelling in build-time and application configuration in runtime seamlessly, a Conceptual Ontology-based Resource meta-Model (CORM) is proposed. Firstly, a resource meta-model is built as a referred model to describe business elements and relationships. Then, by means of ontology, these business elements are transformed into IT service-oriented components such as SOAP services, RESTful services and BPEL files. Referring to Model-View-Controller pattern, these service components are then configured in a runtime supported environment. Next, a state space defined by a resource array is built as the control mechanism to realize a completed IT system. Finally, a CORM-based supported Platform is built to support business modelling, service transformation and system configuration. The research indicates a new approach to develop and implement enterprise information systems in a more flexible and configurable way.

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Research Article Sat, 1 Sep 2012 00:00:00 +0300
A Conceptual Model for IT Service Systems https://lib.jucs.org/article/23941/ JUCS - Journal of Universal Computer Science 18(17): 2452-2473

DOI: 10.3217/jucs-018-17-2452

Authors: Ajantha Dahanayake, Bernhard Thalheim

Abstract: Although services are developed, used, applied and intensively discussed in nowadays IT practice, the concept of an IT service has not yet been introduced. Services are IT artifacts that can be used by many users in different context at different points of time in different locations and serve a certain purpose. They provide the data and functionality at the best point of time, in the agreed format and quality for the right user with the right location and context. We generalize some of the introduced notions such as the REA framework (resource-event-agent) and introduce a framework for conceptual modeling of IT service systems that is based on the classical rhetorical frame introduced by Hermagoras of Temnos (Quis, quid, quando, ubi, cur, quem ad modum, quibus adminiculis (W7: Who, what, when, where, why, in what way, by what means)). Services are primarily characterized by W4: wherefore (end), whereof (source), wherewith (supporting means), and worthiness ((surplus) value). Additionally, the purpose can be characterized by answering the why, whereto, when, and for which reason W4 questions. The secondary characterization W14H is given by characterizing user or stakeholder (by whom, to whom, whichever), the application domain (wherein, where, for what, wherefrom, whence, what), the solution they are providing (how, why, whereto, when, for which reason), and the additional context (whereat, whereabout, whither, when).

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Research Article Sat, 1 Sep 2012 00:00:00 +0300
Architecture for Collaborative Learning Activities in Hybrid Learning Environments https://lib.jucs.org/article/23876/ JUCS - Journal of Universal Computer Science 18(15): 2187-2202

DOI: 10.3217/jucs-018-15-2187

Authors: María Ibáñez, David Maroto, José Jesús García Rueda, Derick Leony, Carlos Delgado-Kloos

Abstract: 3D virtual worlds are recognized as collaborative learning environments. However, the underlying technology is not sufficiently mature and the virtual worlds look cartoonish, unlinked to reality. Thus, it is important to enrich them with elements from the real world to enhance student engagement in learning activities. Our approach is to build learning environments where participants can either be in the real world or in its mirror world while sharing the same hybrid space in a collaborative learning experience. This paper focuses on the system architecture and a usability study of a proof-of-concept for these hybrid learning environments. The architecture allows the integration of the real world and its 3D virtual mirror; the exchange and geolocalization of multimodal information, and also the orchestration of learning activities. The results of the usability evaluation show positive engagement effects on participants in the mirror world and, to a lesser extent, on those in the real world.

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Research Article Wed, 1 Aug 2012 00:00:00 +0300
Human and Intellectual Capital Management in the Cloud: Software Vendor Perspective https://lib.jucs.org/article/23622/ JUCS - Journal of Universal Computer Science 18(11): 1544-1557

DOI: 10.3217/jucs-018-11-1544

Authors: Ricardo Colomo-Palacios, Eduardo Fernandes, Marc Sabbagh, Antonio Seco

Abstract: Cloud systems have shifted traditional on-premise software products towards new and service oriented solutions. In order to adapt to this new trend, traditional software vendors are facing a necessary evolution towards service oriented software products. This software evolution is quite complex and full of problems. This paper presents lessons learned and the issues that emerged in a project aimed to adapt Meta 4' PeopleNet solution to adopt a cloud computing approach. This project, designed as a two-step approach, presents a set of issues that are analyzed in this paper, namely: Software evolution, Software processes and Technology and Personnel issues. The resultant conclusions, that highlight the importance of people in this software evolution, are useful for companies facing a product evolution process towards cloud oriented environments.

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Research Article Fri, 1 Jun 2012 00:00:00 +0300
Utilization-level and Serviceability of a Social Name-card Portal for QoS in a Cloud Social Networking Service https://lib.jucs.org/article/23621/ JUCS - Journal of Universal Computer Science 18(11): 1523-1543

DOI: 10.3217/jucs-018-11-1523

Authors: Yung Kim

Abstract: Various mobile-web services have expanded with the evolution of mobile Internet technologies and with the increasing variety of smart phones in the proliferating cloud computing environment. Web services for the integration of cloud applications/services can be evaluated at the utilization-level as well as the serviceability of the service on the server side in the management for cloud computing. In web activity, a web server can be a unified hub for web interactions as well as for the real-time estimation model of service-based parameters, i.e. utilization-level/serviceability for service monitoring. With the real-time estimation/analysis of the parameters in a web server for service-based contents delivery, the utilization-level and serviceability of a social-web name-card portal are presented. Empirical results are presented on the basis of the implementation of the real-time estimation scheme in a social-web name-card portal server for a cloud SNS.

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Research Article Fri, 1 Jun 2012 00:00:00 +0300
Design Choices Underlying the Software as a Service (SaaS) Business Model from the User Perspective: Exploring the Fourth Wave of Outsourcing https://lib.jucs.org/article/23620/ JUCS - Journal of Universal Computer Science 18(11): 1501-1522

DOI: 10.3217/jucs-018-11-1501

Authors: Anton Joha, Marijn Janssen

Abstract: Software as a Service (SaaS) can be viewed as the fourth wave of outsourcing. SaaS is a relatively new type of service delivery model in which a service provider delivers its services over the web to many users on a pay per use or period basis. In the scarce literature available, the SaaS business model is almost always analyzed from the perspective of the service provider perspective, and rarely from the user organization. Using the unified business model conceptual framework, two case studies are investigated to understand the design choices underlying the SaaS business model from the user organization perspective. The analyses on the business model dimensions provided insight into the differences between the case studies and helped to identify eight discriminating design choices that are important when designing SaaS business models. These include the (1) SaaS service characteristics, (2) SaaS value source, (3) SaaS user target group, (4) data architecture configuration and tenancy model, (5) SaaS governance and demand/supply management core competencies, (6) cloud deployment model, (7) SaaS integration and provider strategy and the (8) SaaS pricing structure. An appeal is made for more research into the impact of cloud business models.

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Research Article Fri, 1 Jun 2012 00:00:00 +0300
The Wookie Widget Server: a Case Study of Piecemeal Integration of Tools and Services https://lib.jucs.org/article/23616/ JUCS - Journal of Universal Computer Science 18(11): 1432-1453

DOI: 10.3217/jucs-018-11-1432

Authors: David Griffiths, Mark Johnson, Kris Popat, Paul Sharples, Scott Wilson

Abstract: Apache Wookie (incubating) has generated considerable interest within the context of Technology Enhanced Learning where it was developed, as well as in mobile applications. The origins of the system in providing services for IMS Learning Design are described, together with an introduction to the system's design and functionality. However, the areas where it has had success are distinct from the application area for which it was designed and developed. The implications of this for understanding user needs is analysed by using ideas drawn from sociology. The complexity of the relationship between the context of use and user needs, and the feedback loops between them is discussed, and the role of technological interventions as an element in a discourse is considered. It is proposed that this understanding of users needs, together with the experience of the development and use of Wookie, argues in favour of an interoperability strategy which focuses on relatively small sets of functional requirements, and avoidance where possible of specifications developed for particular application domains: an approach which may be characterised as piecemeal rather than Utopian.

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Research Article Fri, 1 Jun 2012 00:00:00 +0300
A Simple Model Based on Web Services to Exchange Context Information between Web Browsers and Web Applications https://lib.jucs.org/article/23615/ JUCS - Journal of Universal Computer Science 18(11): 1410-1431

DOI: 10.3217/jucs-018-11-1410

Authors: Jordán Espada, Oscar Martínez, B. Cristina Pelayo G-Bustelo, Juan Manuel Cueva Lovelle, Patricia Ordóñez de Pablos

Abstract: Nowadays mobile devices are equipped with sensors and hardware elements capable of capturing many types of information from the real world, location, orientation, light level, temperature, etc. This information is known in some areas as context information. For years many mobile native applications use context information to support specific tasks. Most of the applications developed with traditional technologies don’t have mechanisms to use most types of context information. This paper presents a lightweight approach to use context information in conventional web applications. The proposal defines a set of highly customizable XML tags, and included web applications that can express specific requests for context information. A web browser designed following the proposed specification is responsible for processing the XML tags and send the context information to the web application using web services. In this paper we present the proposed architecture, then develop and evaluate a GPS navigator application based on this proposal.

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Research Article Fri, 1 Jun 2012 00:00:00 +0300
Product Presentation Strategy for Online Customers https://lib.jucs.org/article/23548/ JUCS - Journal of Universal Computer Science 18(10): 1323-1342

DOI: 10.3217/jucs-018-10-1323

Authors: Marija Jovic, Dusan Milutinovic, Anton Kos, Saso Tomazic

Abstract: This paper deals with customers' behavior in an online environment. The major hypothesis of this paper is that different online product presentation strategies have a different impact on the customer's choice and that this impact can be measured. The research was conducted using an experimental method based on 6 product groups of 8 products per group. The products were presented with different combinations of several audio and visual elements: text, picture, video, animation, speech, special sound, and background music. The impact of each combination on the customer's choice was tested on a customer sample of 46 examinees. The most important conclusion is that besides text and a picture of the product, it is highly recommendable to include a video of the product in the product's online presentation. Regarding the number of multimedia elements, it is better to include more than less elements in a product presentation on the Internet, in contrast to some findings in connection with e-Learning.

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Research Article Mon, 28 May 2012 00:00:00 +0300
The Method of Logistic Optimization in E-commerce https://lib.jucs.org/article/23544/ JUCS - Journal of Universal Computer Science 18(10): 1238-1258

DOI: 10.3217/jucs-018-10-1238

Authors: Robert Bucki, Petr Suchánek

Abstract: Rapidly changing business environment requires new approaches and methods for supporting management systems in all types of companies. Modern companies doing business use e-commerce systems by default. One of the key areas of e-commerce systems is logistics and the supply chain. The optimal way to ensure the success of logistics and supply chains is to use the methods of modeling and simulation based on appropriate models and especially its mathematical representation. In this paper, authors highlight the customer-oriented model of the e-commerce system and deal with logistic optimization and simulations. As an example, a sample logistic structure which requires the adequate control approach is presented. This is realized by means of heuristic algorithms which are responsible for meeting the set criterion. Moreover, the criteria to either maximize the production output or minimize the lost flow capacity of the logistic system or minimize the tool replacement criterion are introduced. Equations of state are given in order to represent the flow of material through the logistic system.

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Research Article Mon, 28 May 2012 00:00:00 +0300
Localized Processing and Analysis of Accelerometer Data in Detecting Traffic Events and Driver Behaviour https://lib.jucs.org/article/23455/ JUCS - Journal of Universal Computer Science 18(9): 1152-1176

DOI: 10.3217/jucs-018-09-1152

Authors: Bratislav Predic, Dragan Stojanovic

Abstract: Recent advancements in sensor technologies resulted in the development of sensors with small dimensions and with power consumption that is low enough to be embedded in various mobile devices and which is widely integrated in vehicles. Such sensors can be extensively used to detect real-time traffic events and situations of user/vehicle in context-aware mobile applications. This paper explores the usage of a large number of anonymous mobile devices already involved in the road navigation function as mobile sources of traffic information. Apart from collecting location and speed data, which is extensively used today to calculate average trip time per road segment, we are exploring possibility of using an acceleration sensor integrated with a mobile device in order to efficiently and timely detect critical traffic events and redistribute this information to other drivers through proactive traffic information system. Such a system would be capable of warning drivers of 'near-accident' situations enhancing their situational awareness and general safety.

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Research Article Tue, 1 May 2012 00:00:00 +0300
Discovering Consumer Insight from Twitter via Sentiment Analysis https://lib.jucs.org/article/23387/ JUCS - Journal of Universal Computer Science 18(8): 973-992

DOI: 10.3217/jucs-018-08-0973

Authors: Wilas Chamlertwat, Pattarasinee Bhattarakosol, Tippakorn Rungkasiri, Choochart Haruechaiyasak

Abstract: Traditional approaches for studying consumer behavior, such as marketing survey and focus group, require a large amount of time and resources. Moreover, some products, such as smartphones, have a short product life cycle. As an alternative solution, we propose a system, the Micro-blog Sentiment Analysis System (MSAS), based on sentiment analysis to automatically analyze customer opinions from the Twitter micro-blog service. The MSAS consists of five main functions to (1) collect Twitter posts, (2) filter for opinionated posts, (3) detect polarity in each post, (4) categorize product features and (5) summarize and visualize the overall results. We used the product domain of smartphone as our case study. The experiments on 100,000 collected posts related to smartphones showed that the system could help indicating the customers' sentiments towards the product features, such as Application, Screen, and Camera. Further evaluation by experts in smartphone industry confirmed that the system yielded some valid results.

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Research Article Sat, 28 Apr 2012 00:00:00 +0300