DOI: 10.3897/jucs.137699

Authors: Wolfram Luther, Ashot Harutyunyan

Abstract: This article presents an extensive literature review on the importance of fairness in society, science, the world of work and leisure, with a focus on healthcare. Depending on the application area, fairness criteria and metrics play a major role in evaluation, classification, and allocation. Different approaches to a general definition of algorithmic fairness for individuals or groups are considered, and their measures from the perspective of the concerned sciences and requirements for the decision-making processes are also formulated. There are many reasons for the lack of fairness: inadequate data quality or low model performance, differences in understanding, competing standards, inappropriate measures in selection, classification and decision-making, lack of accuracy or performance of algorithms paired with insufficient communication, interaction or collaboration of stakeholders. The requirements are illustrated using the example of medical risk prediction tools, e.g., the individual and familial risk for the occurrence of pathogenic variants in BRCA1 (BReast CAncer 1) or BRCA2 genes with impact on early breast cancer (BC) and ovarian cancer (OC) disease, and the 5-year risk that an individual with ocular hypertension will develop Primary Open Angle Glaucoma (POAG), the leading global cause of irreversible blindness.

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DOI: 10.3897/jucs.152114

Authors: Vahide Nida Kılıç, Esra Saraç Eşsiz

Abstract: In previous studies, the focus has predominantly been on anomaly detection, with minimal attention given to anomaly prevention. However, anomaly prevention holds greater significance than anomaly detection. Preventing anomalous behavior before it occurs and identifying potential anomalies in advance to enable timely intervention is both challenging and crucial. In this study, a Suspicious Nodes Anomaly Prevention framework for anomaly prevention has been developed. First, a novel K-medoid based Salp Swarm Anomaly Detection method is proposed within the framework. This method reveals unclustered data by applying clustering and determines the boundaries of clusters using a nature-inspired algorithm that optimizes the threshold. Since threshold determination is an optimization problem, it aligns well with nature-inspired algorithms. Additionally, the Enron email dataset was selected as it is a real-world dataset with accessible content information. Initially, content and node features were extracted from the Enron email dataset. The proposed anomaly detection method was then applied separately to each of these features. Nodes identified as anomalous by one feature but normal by others were of particular interest. These nodes were labeled as “suspicious nodes,” and their connections were analyzed to detect potentially harmful email content. This framework fills a significant gap in the anomaly detection literature by contributing an unprecedented approach to anomaly prevention, offering early intervention capabilities in various sectors by identifying risks in advance. In this study, the proposed framework demonstrates high efficacy in detecting anomalies, achieving a True Positive Rate of 94% in node-based anomaly detection and 78% in content-based anomaly detection, indicating a robust capability for early intervention and risk identification.

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DOI: 10.3897/jucs.130590

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

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

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DOI: 10.3897/jucs.119828

Authors: Seyedeh Aridis Ahadi, Kian Jazayeri, Sahand Tebyani

Abstract: The identification of individuals who indicate suicidal behaviors on social media platforms has become more significant in recent years. The utilization of textual data may help in the development of systems aimed at predicting individuals' mental health. This article proposes an integrated framework for the identification of suicidal thoughts in social media through the implementation of a layered classifier model consisting of a convolutional neural network (CNN) and a long short-term memory (LSTM) model. Various combinations of embedding techniques, activation functions, and solver algorithms are applied to the network. The mixture of these techniques forms 82 distinct methodologies employed, followed by comparing the results obtained. A collection of approximately 60,0000 user posts from 2018 to 2020 was compiled from Reddit for the study. It has resulted in the combination of TF-IDF (word embedding), RReLU (activation function), and Adam (solver algorithm) reaching the highest overall performance. The model achieved impressive accuracy, F1 Score, and AUC of 86%, with precision and recall score of 91% and 82% respectively. It was fitted in just 8.69 seconds, demonstrating its time efficiency as well. This approach has great potential for creating a platform in real life to not only reduce the social impacts of suicidality and mental illness, but also increase social access to mental health resources for all individuals.

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DOI: 10.3897/jucs.110356

Authors: Houda Tadjer, Zohra Mehenaoui, Yacine Lafifi, Amira Chemmakh

Abstract: Various factors can enhance students' learning outcomes in e-learning environments. Time management is a crucial aspect of effective learning, as it enables students to prioritize their tasks and achieve their goals within the given time frame. To improve time management ability students can benefit from feedback, which is a powerful tool to increase self-awareness and encourage positive temporal behavior. Feedback can take different forms such as regular evaluations, progress reports, and reminders of deadlines. By providing students with constructive feedback, they can become more aware of their strengths and weaknesses and adjust their time management strategies. This study proposes a technique based on students' temporal traces and the production of automatic feedback in an online learning environment. The experiment was conducted with 40 students enrolled in an online course on a developed system to validate the proposed approach. The results demonstrate that using feedback is an effective strategy to encourage students to better manage their time in online learning environments.

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DOI: 10.3897/jucs.104093

Authors: Bashar Alshouha, Jesus Serrano-Guerrero, David Elizondo, Francisco P. Romero, Jose A. Olivas

Abstract: The capability of offering patient-centered healthcare services involves knowing the consumer needs. Many of these needs can be conveyed through opinions about services that can be found on social networks. The consumers/patients can express their complains, satisfaction, frustration, etc. in terms of feelings and emotions toward those services; for that reason, it is pivotal to accurately detect them. There are many recent techniques to detect sentiments or emotions, but one of the most promising is transfer learning. This allows adapting a model originally trained for a task to a different one by fine-tuning. Following this idea, the primary objective of this research is to study whether several pre-trained language models can be adapted to a task such as patient emotion detection in an efficient manner. For this purpose, seven clinical and biomedical pre-trained models and four domain-general models have been adapted to detect multiple emotions. These models have been tuned using a dataset consisting of real patient opinions which convey several emotions per opinion. The experiments carried out state the domain-specific pre-trained models outperform the domain-general ones. Particularly, Clinical-Longformer obtained the best scores, 98.18% and 95.82% in terms of accuracy and F1-score, respectively. Analyzing the patient feedback available on social networks may provide valuable knowledge about consumer sentiments and emotions, especially for healthcare managers. This information can be very interesting for purposes such as assessing the quality of healthcare services or designing patient-centered services.

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DOI: 10.3897/jucs.101550

Authors: Anita Herrera, Ángel Arroyo, Alfredo Jiménez, Álvaro Herrero

Abstract: The analysis of Artificial Intelligence techniques and models used in the tourism sector provides insightful information for the management and innovation of this industry. In this paper, we conduct a comprehensive review of the different techniques and models, in regards to Artificial Intelligence when applied to the tourism industry. Specifically, we present a categorization of Artificial Intelligence applications used in different areas of tourism. The results allow to recognize valid studies and useful tools for the activation and growth of the tourism sector, an industry that represents a significant increase in the Gross Domestic Product of various economies and supports the development of life conditions for their inhabitants. Artificial Intelligence applications generate more personalized travel experiences, improve the efficiency of tourism services and strengthen the tourism competitiveness of the destination.

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DOI: 10.3897/jucs.94067

Authors: Luis P. Prieto, Gerti Pishtari, Yannis Dimitriadis, María Jesús Rodríguez-Triana, Tobias Ley, Paula Odriozola-González

Abstract: Recent advances in machine learning and natural language processing have the potential to transform human activity in many domains. The field of learning analytics has applied these techniques successfully to many areas of education but has not been able to permeate others, such as doctoral education. Indeed, doctoral education remains an under-researched area with widespread problems (high dropout rates, low mental well-being) and lacks technological support beyond very specialized tasks. The inherent uniqueness of the doctoral journey may help explain the lack of generalized solutions (technological or otherwise) to these challenges. We propose a novel approach to apply the aforementioned advances in computation to support doctoral education. Single-case learning analytics defines a process in which doctoral students, researchers, and computational elements collaborate to extract insights about a single (doctoral) learner's experience and learning process. The feasibility and added value of this approach are demonstrated using an authentic dataset collected by nine doctoral students over a period of at least two months. The insights from this exploratory proof-of-concept serve to spark a research agenda for future technological support of doctoral education, which is aligned with recent calls for more human-centred approaches to designing and implementing learning analytics technologies.

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DOI: 10.3897/jucs.94514

Authors: Fernando Terroso-Saenz, Andres Muñoz

Abstract: Predicting human mobility is a key element in the development of intelligent transport systems. Current digital technologies enable capturing a wealth of data on mobility flows between geographic areas, which are then used to train machine learning models to predict these flows. However, most works have only considered a single data source for building these models or different sources but covering the same spatial area. In this paper we propose to augment a macro open-data mobility study based on cellular phones with data from a road traffic sensor located within a specific motorway of one of the mobility areas in the study. The results show that models trained with the fusion of both types of data, especially long short-term memory (LSTM) and Gated Recurrent Unit (GRU) neural networks, provide a more reliable prediction than models based only on the open data source. These results show that it is possible to predict the traffic entering a particular city in the next 30 minutes with an absolute error less than 10%. Thus, this work is a further step towards improving the prediction of human mobility in interurban areas by fusing open data with data from IoT systems.

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DOI: 10.3897/jucs.89412

Authors: Oscar I Caldas, Mauricio Mauledoux, Oscar F Aviles, Carlos Rodriguez Guerrero

Abstract: Dynamically Difficulty Adjustment (DDA) has been widely used to preserve engagement in serious and entertaining games, reach better learning, and enhance user performance. A variety of studies suggests that in DDA, task performance (score) rises until hitting a plateau associated with the skill level. However, the sense of engagement is individual and context-dependent, and the effect of DDA on other engagement indicators for immersive virtual environments is still unclear. This study measured objective indicators of engagement while study subjects played an immersive virtual game with DDA to find evidence of dynamic response, similar to game performance. Participants were demanded to perform repetitive upper-limb motions while recording the following indicators: Response Latency as perceptive engagement (elapsed time after sensory stimulus), Exercise Intensity as motion engagement (hand velocity), and psychophysiological responses as emotional engagement (Heart Rate, Skin Conductance, and Respiratory Rate). In addition, 30 features were extracted from the signals to evaluate their variations between time windows. Results indicate that response latency, vertical hand velocity, and heart rate showed significant changes over time during DDA and grew until hitting a plateau, i.e., at the subject's maximum performance. Moreover, some of the features extracted from the signals showed significant differences between time windows, and having strong correlation with the mean of score: max Latency, min velocity on the Y-axis, and mean heart rate, which suggest a promising application for evaluating changes in engagement between different experimental conditions in VR.

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DOI: 10.3897/jucs.86891

Authors: Aurora Polo-Rodríguez, Pietro Dionisio, Francesco Agnoloni, Ana Perandrés Gómez, Cristiano Paggetti, Lucía González López, Alfonso Cruz Lendínez, Macarena Espinilla-Estévez, Javier Medina-Quero

Abstract: Active ageing is a multidimensional process for achieving the potential quality of life and meaning in the life cycle. In the context of the Andalusian region in Spain, where the majority of the population is over 60 years old and lives in rural areas, it has become a key challenge. That is why the European projects within the Framework Programme for Research and Innovation, such as Pharaon - Pilots for Active and Healthy Ageing, promote technologies adapted by and for our elders. In the case of the Andalusian pilot, part of this project, we have selected a social network adapted to them, enabling them to communicate with the community at home and share their experiences. In addition, to improve their physical fitness, a device to count active minutes and steps is included, which provides users and caregivers with a visible and objective metric of daily health status. The technology has been evaluated following a well-defined methodology, which is described in this work to promote the deployment of technology in large-scale pilots. A specific architecture (Information System for Active Ageing in Andalusia - ISA3) and the components evaluated within a common ecosystem (Pharaon Project) are presented.

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DOI: 10.3897/jucs.81518

Authors: Zohra Mehenaoui, Yacine Lafifi, Layachi Zemmouri

Abstract: Learning styles cover various attributes related to the attitude and the learning behavior of individuals. Research and educational theories confirm that considering learning styles in distance learning environments can improve academic performance and learner satisfaction. The traditional approach to identify learning styles is based on asking students to fill out a questionnaire. This approach is considerably less accurate due to the learners’ lack of awareness of their own preferences. Furthermore, learners’ learning styles are defined only once. In this study, we propose an automatic approach to identify learners’ learning styles based on patterns of learning behavior with respect to Felder and Silverman Learning Style Model (FSLSM), in an online learning environment. Patterns of behavior were analysed based on a data-driven approach. This approach exploits different Machine Learning (ML) techniques to detect the learning styles of learners. To validate our proposals, experiments were carried out in a higher education institution with 73 students enrolled in online courses on the ADLS (Automatic Detection of Learning Styles) system that we implemented. A 9 runs cross-validation was used to evaluate the selected ML techniques. Detection accuracy, recall, precision, and F measure were observed. The findings show the possibility of detecting learning styles automatically based on learning behavior with high performances. Different levels of accuracy were found for the different dimensions of FSLSM. However, Support Vector Machines (SVM) have exhibited great ability in predicting learning styles for all dimensions of FSLSM with an accuracy average of 88%.

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DOI: 10.3897/jucs.72590

Authors: Jesus Serrano-Guerrero, Bashar Alshouha, Francisco P. Romero, Jose A. Olivas

Abstract: Online opinions/reviews contain a lot of sentiments and emotions that can be very useful, especially, for Internet suppliers which can know whether their services/products are meeting their customers’ expectations or not. To detect these sentiments and emotions, most applications resort to lexicon-based approaches. The major issue here is that most well-known emotion lexicons have been developed for English language; nevertheless, in other languages such as Arabic, there are fewer available tools, and many times, the quality of them is poor.The goal of this study is to compare the performance of two different types of algorithms, shallow machine learning-based and deep learning-based, when dealing with emotion detection in Arabic language. To improve the performance of the algorithms, two lexicons, which were originally developed in other languages and translated into Arabic language, have been used to add emotional features to different information models used to represent opinions. All approaches have been tested using the dataset SemEval 2018 Task 1: Affect in Tweets and the dataset LAMA+DINA. The semantic approaches outperform the classical algorithms, that is, the information provided by the lexicons clearly improves the results of the algorithms. Particularly, the BiLSTM algorithm outperforms the rest of the algorithms using word2vec. On the contrary to other languages, the best results were obtained using the NRC lexicon.

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DOI: 10.3897/jucs.69377

Authors: Sedef Demirci, Seref Sagiroglu

Abstract: Social media platforms have become popular news sources thanks to their immense popularity and high speed of information dissemination. Using these platforms is essential for news organizations and journalists to track and discover news in digital journalism age. However, the abundance of meaningless data and the lack of organization on these platforms make it difficult to reach valuable news for journalists. In this paper, we create the first public dataset containing large number of real-world Turkish news tweets belonging to different news categories, to the best of our knowledge. We propose an artificial intelligence-based two-step approach to assist journalists for accessing the news shared by various sources on social media under the relevant categories like politics (elections, riots, etc.), health (pandemic, covid-19, etc.), etc. via a single platform by reducing the possibility of overlooking needed information. In the first step, we propose a machine learning based novel model for collecting and categorizing news posts on social media. We implement several traditional machine learning and deep learning based algorithms and evaluate their classification performance in terms of accuracy, precision, recall, and F1 score. In the second step, we develop a software tool, named TwitterBulletin, which automatically retrieves Turkish news tweets and groups them under news categories in real time by using the CNN classifier which achieves the best performance in the first step. The results show that the overall accuracy rate of TwitterBulletin is reasonably high and satisfactory despite the challenge of classifying short tweets.

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DOI: 10.3897/jucs.80688

Authors: Daniel Gomez González, Luis Llana Díaz, Cristóbal Pareja

Abstract: The Brandes algorithm has the lowest computational complexity for computing the betweenness centrality measures of all nodes or edges in a given graph. Its numerous applications make it one of the most used algorithms in social network analysis. In this work, we provide a parallel version of the algorithm implemented in Spark. The experimental results show that the parallel algorithm scales as the number of cores increases. Finally, we provide a version of the well-known community detection Girvan-Newman algorithm, based on the Spark version of Brandes algorithm.

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DOI: 10.3897/jucs.77237

Authors: Atsuko Matsumoto, Takeshi Kamita, Yukari Tawaratsumida, Ayako Nakamura, Harumi Fukuchimoto, Yuko Mitamura, Hiroko Suzuki, Tsunetsugu Munakata, Tomoo Inoue

Abstract: In recent years, various organizations, such as companies and governments, have been required to take measures for the mental health of their employees, and the importance of self-care for mental health by employees themselves has been increasing, as well as being supported by administrators, such as doctors and workplace managers. As a means of self-care of mental health that can be implemented by busy professionals during their workdays and daily lives, the Digital-SAT method has been developed to implement the stress-care process of the SAT method, a psychological counseling technique for resolving psychological stress problems, in a self-guided manner using digital media. To realize the Digital-SAT method, two issues need to be addressed: first, to obtain the same emotional stress reduction effect as the SAT method and, second, to ensure the continuous implementation of the Digital-SAT method. Previous studies have shown that applications (apps) using virtual reality are effective in solving the former issue, and an app using a chatbot can be effective in solving the latter. In this research, an intervention study was conducted to verify the effectiveness of combined use of the two apps to encourage continuous use, resulting in increased emotional stress reduction, with the aim of making it feasible in actual work environments. An intervention of four weeks of app use was conducted with 70 nurses working in two hospitals where measures for mental health due to emotional labour and overwork were required. The emotional stress reduction effects of the intervention were evaluated using psychological scales and blood pressure levels, and it was confirmed that combined use of apps was more effective than using them separately to practice the Digital-SAT method in an actual work environment.

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DOI: 10.3897/jucs.66389

Authors: Uyara Ferreira Silva, Deller James Ferreira

Abstract: This paper presents a systematic literature review of the literature on productive dialogues and emotional aspects in Computer-Supported Collaborative Learning (CSCL) and also presents emotional aspects used in debates with conflicting points of view in other contexts. Initially, more than 400 articles were catalogued, belonging mainly to the databases of Springer and Science Direct, not limited by years, because of very important works referenced until today. The findings reveal that in CSCL there is a neglect in relation to the emotional dimension, the results also show that there are negative emotional aspects that impair the motivation in the participation of students in collaborative activities. Empathy is seen as an alternative to conflict resolution in different contexts, in addition to collaborative learning, but it is rarely addressed in CSCL.

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DOI: 10.3897/jucs.2020.045

Authors: Simon Vrhovec, Damjan Fujs, Luka Jelovčan, Anže Mihelič

Abstract: There is a growing number of scientific papers reporting on case studies and action research published each year. Consequently, evaluating the quality of pilling up research reports is becoming increasingly challenging. Several approaches for evaluation of quality of the scientific outputs exist however they appear to be fairly time-consuming and/or adapted for other research designs. In this paper, we propose a reasonably light-weight structure-based approach for evaluating case study and action research reports (SAE-CSAR) based on eight key parts of a real-world research report: research question, case description, data collection, data analysis, ethical considerations, results, discussion and limitations. To evaluate the feasibility of the proposed approach, we conducted a systematic literature survey of papers reporting on real-world cybersecurity research. A total of N = 102 research papers were evaluated. Results suggest that SAE-CSAR is useful and relatively efficient, and may offer a thought-provoking insight into the studied field. Although there is a positive trend for the inclusion of data collection, data analysis and research questions in papers, there is still room for improvement suggesting that the field of real-world cybersecurity research did not mature yet. The presence of a discussion in a paper appears to affect most its citation count. However, it seems that it is not uniformly accepted what a discussion should include. This paper explores this and other issues related to paper structure and provides guidance on how to improve the quality of research reports.

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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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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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DOI: 10.3897/jucs.2020.002

Authors: Henrique Vianna, Jorge Luis Victória Barbosa

Abstract: Caused by habits such as poor diets, lack of physical activity practice or smoking, non-communicable diseases were elected by the World Health Organization as one of the greatest challenges of the twenty-first century, despite a lot of information produced in social media focused on preventing this type of disease. This paper presents the Pompilos Model, which aims at improving computer-aided social support by suggesting beneficial health resources and revealing what inuences other people's health, so to foster better health behaviors in social relations. In order to evaluate the model's feasibility, we performed a random experiment during one month and half with two groups to assess the influence of messages related to the prevention of chronic diseases. Those messages presented information on a healthier diet, the practice of physical activities, and ways to lose weight, from monitored Twitter profiles on the habits of health assistant web application's users. So it would be possible to manage food intake, the practice of physical activities, and weight control. Messages related to the prevention of chronic diseases, such as a healthier diet, the practice of physical activities, and weight loss from monitored Twitter profiles were directed to an intervention group as a way to re-engage users in their care activities. With this information, we found a correlation between message reading and the access to the application history feature among intervention users.

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DOI: 10.3217/jucs-025-12-1625

Authors: Carlos De Carvalho, Pedro Cano, José Roa, Anna Wanka, Franz Kolland

Abstract: Being able to effectively use online tools has become a fundamental competence in our Society. Therefore, it is important to tackle the age digital divide as there is a rapidly growing number of elderly people. Like everyone else, older adults (senior citizens or the silver generation) must be equipped with the necessary skills to be able to be connected and integrated in the online world to prevent their social isolation and to foster their inclusion. As a contribution to that effort, a European-wide digital literacy development initiative for senior citizens was setup and this article presents the analysis of the achieved results which shows a very positive perception of the seniors on the developed digital abilities.

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DOI: 10.3217/jucs-025-12-1531

Authors: Mahnane Lamia, Mohamed Hafidi, André Tricot, Ouissem Benmesbah

Abstract: While some studies indicate that flipped classrooms offer many positive educational outcomes, other studies draw attention to limitations associated with flipped classroom (students' limited preparation prior to class, students' need for guidance at home, students' inability to get immediate feedback while they study at home, and little research has focused on students' learning outcomes, such as: satisfaction and motivation). This paper attempts to address several of these limitations through exploratory studies conducted in an Algerian University. The approach proposed in this paper called Flipped classroom based on Context-Aware mobile learning system (FC-CAMLS) aims to provide learners with an adapted course content format based on their feedback and context. The latter has a significant influence on multimedia content in adaptive mobile learning. The system was implemented in an English Language course. It was expected that the FC-CAMLS increased the management of students' heterogeneity. A quantitative analysis by means of structural equation modeling was performed to analyze the caUnited States of Americal relationships between knowledge, skills, motivation and students' satisfaction. The results show that the system has positive effects on students' knowledge, skills, and motivation. Finally, our research provides useful results that the use of the context dimensions and learner's feedback in adaptive mobile learning is more beneficial for learners especially in the flipped classroom.

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DOI: 10.3217/jucs-024-09-1217

Authors: Difeng Yu, Hai-Ning Liang, Feiyu Lu, Vijayakumar Nanjappan, Konstantinos Papangelis, Wei Wang

Abstract: Target selection is one of the most common and important tasks in interactive systems. Within virtual reality environments, target selection can pose extra challenges to users because targets can be located far away, clustered together, and occluded from view. Although selection techniques have been explored, it is often unclear which techniques perform better across different environmental target density levels and which have higher levels of usability especially for recently released commercial head-mounted display (HMD) virtual reality systems and input devices. In this paper, we first review previous studies on target selection in HMD VR environments. We then compare the performances of three main techniques or metaphors (RayCasting, Virtual Hand, and Hand-Extension) using recently marketed VR headsets and input devices under different density conditions and selection areas. After, we select the best two techniques (RayCasting and Virtual Hand) for the second experiment to explore their relative performance and usability by adding different feedback to these two techniques. In the third experiment, we implemented three techniques with pointing facilitators and compared them against the best techniques from the second experiment, RayCasting with visual feedback, to assess their performance, error rates, learning effects, and usability. The three studies altogether suggest the best target selection features, based on techniques, feedback, and pointing facilitators for target density conditions in HMD VR environments.

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DOI: 10.3217/jucs-024-07-0975

Authors: Yves Wautelet, Manuel Kolp, Loris Penserini

Abstract: The increased symbiotic relationships between society and Information and Communication Technology (ICT) pave the ways for a substantial alignment and rethinking of current software development methodologies. This paper presents the use and validation of a software analysis and project management (PM) framework for iterative software development within the Tropos method. This methodology is servicedriven, its requirements models are founded on social-based modeling elements. The PM framework includes risk and quality management; it has been applied on multiple case studies and this paper presents a full experience report. The proposed methodology is aimed to provide a reference for practitioners willing to develop iteratively using Tropos.

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DOI: 10.3217/jucs-024-07-0935

Authors: Alaa Qaffas, Alexandra Cristea, Mohamed Mead

Abstract: Adaptive online advertising is a rapidly expanding marketing tool that delivers personalised messages and adverts to Internet users. At a time when the Internet is burgeoning, many websites use an adaptation process to tailor their advertisements, however, often in an ad-hoc manner. Thus, a new model that guarantees a systematic integration of adaptive features on existing business websites has become an urgent requirement to satisfy customers. This paper aims to solve this issue, by presenting an innovative model for e-advertising adaptation: the Layered Adaptive Advertising Integration (LAAI). LAAI is building upon previous models and frameworks from different domains, by selecting and adding novel features appropriate for e-advertising. Based on this model, a new adaptation system -AEADS - is developed, to test and evaluate the LAAI model. This research also reports on the perception on the methods towards obtaining generalisation, portability and efficiency, as proposed by the LAAI model, by evaluating how a range of businesses are enabled to adapt their advertisements based on user profiles and behaviours.

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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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DOI: 10.3217/jucs-024-03-0322

Authors: O-Joun Lee, Yunhu Kim, Hoang Nguyen, Jai Jung

Abstract: The goal of this paper is to discover latent social events from social media for sensitively understanding social opinions that appeared within a city. The latent social event indicates a regional and inconspicuous social event which is mostly buried under macroscopic trends or issues. To detect the latent social event, we propose three methods: i) discovering areas-ofinterest (AOIs), ii) allocating social texts to the AOIs, and iii) detecting social events in each AOI. The AOIs can be composed by grouping social texts which are topically and spatially homogeneous. To make the AOIs dynamic and incremental, we use windows for allocating a social text to an adequate AOI. Lastly, the latent social events are detected from the AOI on the basis of keywords and temporal distribution of the social texts. Although, in this study, we limited the proposed method into analyzing social media, it could be extended to detecting events among agents/things/sensors.

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DOI: 10.3217/jucs-024-02-0085

Authors: Jan Schneider, Dirk Börner, Peter Van Rosmalen, Marcus Specht

Abstract: Educational practitioners have stressed the relevance of providing learners with a set of 21th century skills that will allow them to face current life challenges. Among others this includes communication and social skills such as public speaking, argumentation, negotiation, etc. Besides the acquisition of knowledge and techniques, these skills have the special characteristic that their performance is usually conducted under emotionally charged and stressful situations. Recent advances in technology have allowed the creation of digital applications to support learners with the development of techniques for this type of skills. However, supporting learners on the preparation of a mindset that allows them to perform well under emotionally charged circumstances is an area that technology enhanced learning has practically overlooked. To examine this gap, we developed the Booth, an application designed to get learners into a powerful and resourceful emotional state. In this article we present a two-step user study. Results of the first evaluation show that the use of the Booth induced a positive emotional state on users. Results from the second step suggest that using the Booth helps learners to emotionally prepare for public speaking.

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DOI: 10.3217/jucs-023-12-1113

Authors: Murat Topaloglu, Dilek Kırar

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

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DOI: 10.3217/jucs-023-11-1057

Authors: Giangiacomo Bravo, Mike Farjam

Abstract: Computational social sciences (CSS) refer to computer-enabled investigations of human behaviour and social interaction. They include three main components - (i) computational modelling and social simulation, (ii) the analysis of digital traces of online interactions, (iii) virtual labs and online experiments - and allow researchers to perform studies that were even hard to imagine a few decades ago. Moreover, CSS favour a more systematic test of theories and increase the possibility of study replication, two factors holding the potential to help social sciences reach a higher scientific status. Despite the huge potential of CSS, we follow previous works in identifying several impediments to a larger adoption of computational methods in social sciences. Most of them are linked with the humanistic attitude and a lack of technical skills of many social scientist. Significant changes in the basic training of social scientist and in the relation patterns with other disciplines and departments are needed before the potential of CSS can be fully exploited.

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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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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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DOI: 10.3217/jucs-023-05-0432

Authors: Darius Ašeriškis, Robertas Damaševičius

Abstract: We study how virtual incentive mechanisms (such as leaderboards) help motivate players to extend the game playing time. We have designed a multiplayer strategy game, called OilTrader, which is set in a game-theoretic framework of a Minority Game, to verify the effect of motivation reinforcement on the sustainability of game playing process. We have conducted an experiment with 114 players and evaluated their psychological types using the HEXAD player type model. Players were divided into a main experimental group (who used the user interface enhanced with motivation-increasing factors) and a control group (who used a simpler game interface). Results indicate that game players, who have used the motivation-enhancing interface, have had stronger motivation to play the game longer. Using statistical analysis, we have discovered that Free Spirits, Disruptors and Players (according to the HEXAD questionnaire player types) are more motivated by a progress leaderboard rather than an achievement leaderboard.

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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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DOI: 10.3217/jucs-023-03-0304

Authors: Sonia Ortiz-Ángeles, Yenny Villuendas-Rey, Itzamá López-Yáñez, Oscar Camacho-Nieto, Cornelio Yáñez-Márquez

Abstract: The contemporary world has witnessed technological advances, such as Online Social Networks (OSN), whose influence in almost every action of the human being is remarkable. Among the human activities most significantly impacted by OSNs are: entertainment, human relationships, education, and political activities, including those related to electoral campaigns and electoral preferences prediction. The research contribution of the current paper regards the usefulness of OSNs users generated data to predict the political context. More specifically, 25 Computational Intelligence (CI) algorithms are used to predict voting intentions on the United States primary presidential elections for 2016, taking as input the data sets generated by 1200 users of the YouGov OSN, as well as the answers they gave to an online study run by the American National Election Studies (ANES). The application of the 25 supervised classification algorithms is done over the Waikato Environment for Knowledge Analysis (WEKA), using a stratified 5-fold cross validation scheme. Also, the experimental results obtained were validated in order to identify significant differences in performance by mean of a non-parametric statistical test (the Friedman test), and a post-hoc test (the Holm test). The hypothesis testing analysis of the experimental results indicates that predicting voting intentions in favour of a democrat or republican candidate is simpler than predicting the particular candidate, given that the prediction performances for a democrat or republican candidate (best performances of 80% and 78%, respectively) are better than those given when predicting a specific candidate (70% for democrat candidates and 56% for republican candidates).

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DOI: 10.3217/jucs-023-03-0236

Authors: Klara Grčić, Marina Babac, Vedran Podobnik

Abstract: Social networks are nowadays an influential tool in the hands of the centres of political power because of their possibilities for direct and two-way communication with citizens in real time, dissemination of information, or a self-promotion and marketing. The use of social networks in the political context has become extremely important in the analysis and prediction of elections and generally in monitoring activities of politicians and public opinion. In this paper, we provide a content analysis of Facebook activities of leading European Union (EU) politicians to generate their extended individual profiles. Based on these profiles, a comparative analysis between the European Commissioners (i.e., EU ministers) and Croatian ministers is provided showing certain unexpected differences in their online behaviour. Summarizing these results, a model for prediction of online political behaviour is proposed.

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DOI: 10.3217/jucs-022-10-1418

Authors: Yasuhito Noguchi, Tomoo Inoue

Abstract: Asynchronous exchange of video messaging is a way to achieve time-shifted communication for the people who have difficulties to enjoy daily family communication in real time, because of time-zone differences or life-rhythm differences. However face-to-face communication and video messaging communication is significantly different. Since mealtime is the most common opportunity for daily family communication, it has been proposed to synchronize the video message with the viewer by changing its playback speed in dining situations to improve video messaging communication. This paper studies the influence of the synchronization method by means of Wizard of Oz (WoZ), and by means of the implemented prototype system. In the synchronization method, the dining progress of the video person is matched with that of the viewer by real-time meal weight detection. The lab study found that the synchronization via WoZ increased speech frequency, decreased the duration of switching pauses, and led to a higher ratio of eating actions immediately after verbal responses of the user. This indicated that a more active commitment of the user was observed. The prototype system with finer control of the video than WoZ also achieved comparable result in terms of questionnaire scores, indicating the feasibility of a videoconferencing system with such a function.

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DOI: 10.3217/jucs-022-10-1298

Authors: Virginia Yannibelli, Marcelo Armentano, Franco Berdun, Anala Amandi

Abstract: Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.

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DOI: 10.3217/jucs-022-05-0671

Authors: Yolanda Baca-Gomez, Alicia Martinez, Paolo Rosso, Hugo Estrada, Delia Irazu Hernandez Farias

Abstract: The increasing use of social networks and online sites where people can express their opinions has created a growing interest in Opinion Mining. One of the main tasks of Opinion Mining is to determine whether an opinion is positive or negative. Therefore, the role of the feelings expressed on the web has become crucial, mainly due to the concern of businesses and government to automatically identify the semantic orientation of the views of customers or citizens. This is also a concern, in the area of health to identify psychological disorders. This research focuses on the development of a web application called SWePT (Web Service for Polarity detection in Spanish Texts), which implements the Sequential Minimal Optimization (SMO) algorithm, extracting its features from an affective lexicon in Mexican Spanish. For this purpose, a corpus and an affective lexicon in Mexican Spanish were created. The experiments using three (positive, neutral, negative) and five categories (very positive, positive, neutral, negative, and very negative) allow us to demonstrate the effectiveness of the presented method. SWePT has also been implemented in the Emotion-bracelet interface, which shows the opinion of a user graphically.

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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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DOI: 10.3217/jucs-022-03-0438

Authors: I-Hsien Ting

Abstract: Opinion mining has been a crucial research topic among recent studies, particularly concerning data from social media. However, a widely discussed communication concern called "the spiral of silence effect" has not been examined in opinion mining studies. In this paper, we propose an approach for detecting the spiral of silence effect in social media. We believe that the accuracy of opinion mining can be improved by considering the effect of the spiral of silence. The details and steps of the detection approach are discussed. We also collected data from two popular social networking websites, namely Facebook and Twitter, for performance measurement. Analysis findings show that the average accuracy of the proposed approach was higher than 0.85, indicating that the approach is highly effective.

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DOI: 10.3217/jucs-022-03-0375

Authors: Georgios Lappas, Amalia Triantafillidou, Prodromos Yannas, Anastasia Kavada, Alexandros Kleftodimos, Olga Vasileiadou

Abstract: The purpose of this study is to examine the use of social media such as Facebook, Twitter, and YouTube by candidates running for the 2014 Greek Municipal Elections by addressing the following questions: (1) which factors affect social media adoption by municipal candidates?, and (2) whether social media usage along with the popularity of candidates' social media pages influence candidates' vote share. Results indicate that social media are not very popular campaigning tools among municipal candidates in Greece. This implies that Greek candidates still rely on traditional ways to lure their voters. Furthermore, findings reveal that candidates running in large municipalities are more likely to utilize social media (i.e., Facebook, Twitter, and YouTube) as means of political marketing. In addition, challengers seem to prefer Facebook and Twitter as campaign tools while males tend to focus on YouTube to attract voters. Despite the low adoption rate, results suggest that candidates who made use of social media won more votes compared to candidates who were not social media users. Moreover, it was found that a candidate's Facebook page and YouTube channel popularity are good indicators of the candidate's vote share.

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DOI: 10.3217/jucs-022-03-0302

Authors: Masoud Sagharichian, Morteza Langouri, Hassan Naderi

Abstract: The variety of applications requiring graph analysis is growing rapidly. Diameter is one of the most important metrics of a graph. The diameter is important in both designing algorithms for graphs and understanding the nature and evolution of graphs. So, detecting diameter of large graphs is very important. We propose an algorithm to calculate the diameter of such graphs. The main goal of this algorithm is to reduce the number of breadth-first searches required to determine the diameter of the graph by finding a better upper bound for the eccentricity of vertices. Based on experimental results, our proposed algorithm can quickly detect the exact diameter of the large-scale real world graphs with a few number of breadth-first searches.

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DOI: 10.3217/jucs-022-02-0247

Authors: Dragos Datcu, Stephan Lukosch, Heide Lukosch

Abstract: While augmented reality research has grown into a mature field over the last years, the aspects of situational awareness and presence of augmented reality (AR) are still quite open research topics. This paper introduces a collaborative game to explore the different perception of situational awareness and presence in a physical and an AR environment. The game is employed as an approximation of collaboratively solving complex problems. The goal of the game is to jointly build a tower with either physical blocks in a physical environment or virtual blocks in an augmented reality environment. A first study with 18 users shows the feasibility of the game and questionnaire design for studying the different perception of situational awareness and presence in a physical and an AR environment. The study further identifies necessary future research with regard to the perception of presence and awareness in AR.

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DOI: 10.3217/jucs-022-01-0114

Authors: Jesus Garcia Laborda, Teresa Magal-Royo, Margarita Bakieva

Abstract: This research addresses the change in how the Spanish University Entrance Examination can be delivered in the future. There is a wide acknowledgement that computer tests are very demanding for the delivering institutions which makes computer language testing difficult to implement. However, the use of tablet PCs can facilitate the delivery at even lower cost than the regular computer based language testing. 183 students in their last year of high school took a computer based language test which included reading, writing, listening and speaking. The research aspects were 1) whether they feel at ease with the tablet PC exam; 2) if they felt that visual aspects were accessible and 3) whether the interface organization was clear. The paper first has a brief description of the OPENPAU® platform, after it addresses the field study based on questionnaires and observations with students during the test delivery, finally the results indicate that this means of language test delivery could be adequate not only for the Spanish University Entrance Examination but for most standardized tests.

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DOI: 10.3217/jucs-021-05-0638

Authors: Derick Leony, Pedro Muñoz-Merino, José Ruipérez-Valiente, Abelardo Pardo, Carlos Delgado-Kloos

Abstract: Massive Open Online Courses (MOOCs) have grown up to the point of becoming a new learning scenario for the support of large amounts of students. Among current research efforts related to MOOCs, some are studying the application of well-known characteristics and technologies. An example of these characteristics is adaptation, in order to personalize the MOOC experience to the learner’s skills, objectives and profile. Several educational adaptive systems have emphasized the advantages of including affective information in the learner profile. Our hypothesis, based on theoretical models for the appraisal of emotions, is that we can infer the learner’s emotions by analysing their actions with tools in the MOOC platform. We propose four models, each to detect an emotion known to correlate with learning gains and they have been implemented in the Khan Academy Platform. This article presents the four models proposed, the pedagogical theories supporting them, their implementation and the result of a first user study.

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DOI: 10.3217/jucs-020-15-2005

Authors: Jinghuai She, Xi Zhang, Weiguang Wang, Patricia Ordóñez de Pablos

Abstract: Social media and mobile internet are both hottest topics in internet technologies which bring great challenges and wonderful opportunities for a large number of researchers in recent years. In some research fields, i.e., telemedicine or e-healthcare, Chinese researchers quickly took advantage of the spread of social media and mobile internet. In this study, we conducted a citation analysis with CiteSpace II by comparing the performance between researchers from China and advanced countries (e.g., USA) in Telemedicine field from 2005-2013. Although there remain huge gaps between China and developed countries, we found that social networks and mobile internet helped Chinese researchers to narrow the gap quickly in recent years. We also found that in the sub fields such as "SNS-facilitated telemedicine" or "m-healthcare", Chinese researchers even achieved similar performance as compared with world class researchers. These findings implicate that SNS or mobile internet may help researchers in developing countries to bridge the digital divide and enhance "late-mover advantage".

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DOI: 10.3217/jucs-020-10-1418

Authors: Eugenijus Kurilovas, Anita Juskeviciene, Svetlana Kubilinskiene, Silvija Serikoviene

Abstract: The aim of the paper is to investigate and propose Semantic Web approaches to improving the adaptation quality of Virtual Learning Environments (VLEs). These approaches are the method for semantic search for Web 2.0 tools in VLEs, and the method for curriculum mapping and semantic search for Learning Objects (LOs) in VLEs. In the paper, a special attention is paid to improving the adaptation capabilities of VLE, e.g. its suitability for different learning styles such as VARK. Web 2.0 tools ontology based on VARK model learning activities gives the possibility to develop adaptive learning environment with better access to specific learning content managing tools (i.e. Web 2.0 tools). The learner will only need to enter the name of learning activity into the search system field and the machine offers the appropriate tools to perform this activity. The engine facilitates the search process by optimizing workloads, thereby improving learner's satisfaction and improving the efficiency and effectiveness of the learning process. Presented curriculum mapping approach makes interoperability and LOs semantic search possible by making use of two smaller controlled vocabularies instead of a very large one on competencies which would be more volatile. One could exchange information on competencies in a multi-lingual and multi-cultural environment by: (1) breaking down competencies, and (2) relating these competency components to multilingual controlled vocabularies. The research results have shown that, in order to improve the adaptation quality of VLEs, it is very important to improve semantic search for both LOs and Web 2.0 tools in VLEs.

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DOI: 10.3217/jucs-019-18-2639

Authors: Ramiro Gonçalves, José Martins, Jorge Pereira, Vitor Santos, Manuel Pérez Cota

Abstract: Web accessibility is becoming a current topic in social and scientific discussions. With the advances in technology, a need for access to all Web resources is becoming more and more recurrent due to the several advantages that the Web brings to those with some sort of disability, allowing them accessing and integrating in society. With this document we aim to present indicators regarding the lower accessibility levels of the Portuguese teaching institutions websites. A set of background and theoretical considerations is made alongside the article, as well as the results of an accessibility evaluation made to the Portuguese secondary schools websites using a specialized software tool and according to WCAG 2.0. The present document also contains a proposal for a model that aims on improving Web accessibility Levels in Portugal by fostering the creation of relations and group activities between the actors that, in our opinion, are those with the most relevance in the Web content accessibility issue.

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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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DOI: 10.3217/jucs-019-14-2150

Authors: Sylvana Kroop

Abstract: Instead of using traditional learning environments which contain tools and content of a single provider that are often owned by one specific educational organization, the presented idea of Widget- and Cloud-based Personal Learning Environments (PLEs) exploits a variety of existing and developing open educational sources including popular Web2.0 resources such as YouTube, Flickr or Wikipedia. The main contribution of this paper is the analysis of teachers’ and students’ attitudes and reasons for acceptance of widget- and cloud-computing based PLE technology. A quantitative and qualitative comparison of three widget-based PLE scenarios reveals the benefits as well as barriers of the new PLE technology regarding a) learning outcome and b) (cognitive, technical, time-wise) ease of the personal learning process. Findings show that a systematic cloud computing approach - software as a service (SaaS) where users do not need to install and run tools locally - is preferred. It saves time and meets the needs to keep the personal environment flexible and up to date. But while users have to manage a broad range of tools and content their most essential request is to be efficiently supported by the system in regard to their individual learning needs, e.g. in the decision making process of selecting and evaluating relevant tools.

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DOI: 10.3217/jucs-019-09-1199

Authors: Jaime Guixeres, Javier Saiz, Mariano Alcañiz, Ausias Cebolla, Patricia Escobar, Rosa Baños, Cristina Botella, Juan Lison, Julio Alvarez, Laura Cantero, Empar Lurbe

Abstract: Virtual Reality (VR) could be an interesting tool to combat obesity and sedentariness in children. During the last years a multidisciplinary research team comprised of engineers, psychologists, physiotherapists and paediatricians have been testing these technologies. Throughout the tests, physiological (cardiovascular and metabolic response with biomedical sensors (smart fabrics TIAS) and psychological responses have been collected. The results presented in this paper reflect two main aspects: 1) the feasibility of the monitoring techniques employed and 2) the validity of virtual reality and exergaming technologies as promoters of physical activity and their potential as tools in clinical intervention programs. In the first study (n=90) children, a commercial platform was tested as support tool to aerobic exercise in a treadmill. Results showed a more physiological effort by obese group and limitations to measure effort perception with Borg scale especially in obese group. In second study (n=126) a new VR platform was developed (VREP) and tested as support of aerobic activities, a difference of first study, all the boys completed both conditions (same Aerobic exercise with/without support VR). 59.5% felt that they had to exert more effort in the traditional condition. Regarding to acceptability in both studies the vast majority of the participants liked the idea of combining physical activity with the VR platform as a form of treatment to increase physical activity. The capacity of VR technology to create controllable, multisensory, interactive 3D stimulus environments within which children's performance can be motivated, recorded, and measured, has been tested in these studies, offering clinical assessment and intervention options which are not possible using traditional methods.

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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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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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DOI: 10.3217/jucs-018-08-1048

Authors: Victor Ströele, Geraldo Zimbrão, Jano Souza

Abstract: Social networks are dynamic social structures consisting of individuals or organizations, usually represented by nodes tied by one or more relationship type. Analyzing these structures enables us to detect several inter and intra connections between people in and outside their organizations. In this context, we construct a multi-relational scientific social network where researchers may have four different types of relationships with each other. We adopt some criteria such as relationship age in order to assign a weight to relationships and to enable the modeling of a scientific social network as close as possible to reality. Using clustering techniques with maximum flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific community.

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DOI: 10.3217/jucs-018-04-0577

Authors: Anna Zygmunt, Piotr Bródka, Przemysław Kazienko, Jarosław Koźlak

Abstract: Identifying key persons active in social groups in the blogosphere is performed by means of social network analysis. Two main independent approaches are considered in the paper: (i) discovery of the most important individuals in persistent social communities and (ii) regular centrality measures applied either to social groups or the entire network. A new method for separating of groups stable over time, fulfilling given conditions of activity level of their members is proposed. Furthermore, a new concept for extracting user roles and key persons in such groups is also presented. This new approach was compared to the typical clustering method and the structural node position measure applied to rank users. The experimental studies have been carried out on real two-year blogosphere data.

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DOI: 10.3217/jucs-018-04-0507

Authors: Onur Can Sert, Kayhan Dursun, Tansel Özyer, Jamal Jida, Reda Alhajj

Abstract: Multi objective clustering is one focused area of multi objective optimization. Multi objective optimization attracted many researchers in several areas over a decade. Utilizing multi objective clustering mainly considers multiple objectives simultaneously and results with several natural clustering solutions. Obtained result set suggests different point of views for solving the clustering problem. This paper assumes all potential solutions belong to different experts and in overall; ensemble of solutions finally has been utilized for finding the final natural clustering. We have tested on categorical datasets and compared them against single objective clustering result in terms of purity and distance measure of k-modes clustering. Our clustering results have been assessed to find the most natural clustering. Our results get hold of existing classes decided by human experts.

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DOI: 10.3217/jucs-018-04-0487

Authors: John Lee, Gerard Cabunducan, Francis George C. Cabarle, Raphael Castillo, Jasmine Malinao

Abstract: Past work analysing elections in online domains has largely ignored the underlying social networks present in such environments. Here, the Wikipedia Request for Adminship (RfA) process is studied within the context of a social network and several factors influencing different stages of the voting process are pinpointed. Machine-learning problems were formulated to test the identified factors. The different facets explored are: election participation, decision making in elections, and election outcome. Our results show that voters tend to participate in elections that their contacts have participated in. Furthermore, there is evidence showing that an individual's decision-making is influenced by his contacts' actions. The properties of voters within the social graph were also studied; results reveal that candidates who gain the support of an influential coalition tend to succeed in elections. Additionally, detailed analyses on different classes of voters and candidates were made. Finally, the structural properties corresponding to networks of election participants were analysed and these networks were found to exhibit higher degrees of community structure versus graphs of participants selected at random.

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DOI: 10.3217/jucs-018-01-0086

Authors: Benjamim Fonseca, Leonel Morgado, Hugo Paredes, Paulo Martins, Ramiro Gonçalves, Pedro Neves, Ricardo Nunes, Jorge Lima, João Varajão, Ângela Pereira, Robert Sanders, Vera Barracho, Urban Lapajne, Matej Rus, Martin Rahe, Andre Mostert, Thorsten Klein, Viktorija Bojovic, Saša Bošnjak, Zita Bošnjak, João Carvalho, Isabel Duarte, Andreana Casaramona, Alberto Soraci

Abstract: Entrepreneurship is widely recognized as one of the basic skills to be acquired through a life-long learning. The European Union, under the guidance of the Oslo Agenda, promotes several initiatives to develop entrepreneurship culture in Europe. Education can make a significant contribution to entrepreneurship, encouraging the development of entrepreneurial attitudes and skills in young people. Serious Games are presently recognised as having an important role and potential in education and social networks emerged in the last years as the platform preferred by many, especially young people, to socialize, play games and even learn. This paper presents the PLAYER project, in which a game was developed and implemented as a Facebook application, to enable learning entrepreneurial skills progressively, by guiding users to develop a business idea in the form of a business plan.

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DOI: 10.3217/jucs-017-14-1951

Authors: Victor Ströele, Ricardo Silva, Moises De Souza, Carlos Eduardo R. De Mello, Jano Souza, Geraldo Zimbrão, Jonice Oliveira

Abstract: Social networks are social structures consisting of individuals or organizations, usually represented by nodes tied by one or more types of relationships. Although these structures are often complex, analyzing them enables us to detect several inter and intra connections amongst people in and outside their organizations. In this context, we present an approach using data mining techniques in order to identify intra and inter organizational linkages amongst groups of people with similar profiles. Using clustering techniques, we identify groups of people in a way that allows us to evaluate how researchers collaborate in the Brazilian scientific scenario of Computing Science. Besides this, we are able to understand how research flows amongst the best universities and research centres in Brazil. Understanding the Scientific Brazilian scenario can help the development of research in other scenario or even in other Social Network Types.

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DOI: 10.3217/jucs-017-10-1492

Authors: Felix Mödritscher, Zinayida Petrushyna, Effie Law

Abstract: Personal learning environments (PLEs) comprise a new kind of learning technology which aims at putting learners into centre stage, i.e. by empowering them to design and use environments for their learning needs and purposes. Setting a PLE approach into practice, however, is not trivial at all, as the prospective end-users have varying attitudes and experiences in using ICT in general and PLE software in particular. Here, practice sharing could be an enabler for increasing the usefulness and usability of PLE solutions. In this paper we examine the relevant issues of capturing and sharing "good practices" of PLE-based, collaborative activities. By good practices we refer to learning experiences provided by learners for a networked community. Moreover, we introduce the concept of a pattern repository as a back-end service for PLEs which should, in the sense of community approaches like Last.fm, support PLE users in selecting and using learning tools for their activities. Finally, we present a prototype and argue for the advantages of such a practice sharing infrastructure with respect to community literature, experiences, and an evaluation study.

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DOI: 10.3217/jucs-017-10-1430

Authors: Alice Comi, Martin Eppler

Abstract: As suggested by several scholars, inter-organizational collaboration is an important vehicle for innovation, but working across organizational boundaries entails great complexity. In this paper, we argue that visual facilitation may act as a catalyst of inter-organizational teamwork, leading to increased knowledge sharing quality (H1), team performance (H2) and satisfaction (H3). On the other hand, we suggest that the aesthetic beauty of visual representations may exert a manipulatory effect, inducing inter-organizational actors to overestimate the collaboration value potential (H4). We adopt an experimental design (N=145 participants) in order to assess the advantages and disadvantages of visual facilitation in inter-organizational teamwork. In particular, we compare inter-organizational teams working with i) software-based visualization, ii) poster-based visualization, and iii) text-based facilitation (control condition). By comparing results across the two treatment conditions (software and poster), we disentangle the effects of visual facilitation and computer interactivity, therefore making a unique contribution to research on information visualization. The experiment findings show that software-supported teams outperform the control groups in terms of performance (H2), and exhibit greater satisfaction with the inter-organizational meetings (H3). We extend our experimental study by conducting focus groups with 17 experiment participants to gain an in-depth understanding of the users' experience with the different support systems. After discussing relevant implications for both researchers and practitioners, we point out the limitations of our study and suggest directions for future research.

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DOI: 10.3217/jucs-017-09-1314

Authors: Ángel Hernández-García, Santiago Iglesías-Pradas, Julián Chaparro-Peláez, Félix Pascual-Miguel

Abstract: Acceptance of online shopping adoption by individuals has been a concerning issue for researchers in the past decade. However, most research has focused in evaluating the attitudes and intention to use electronic commerce from the shoppers' perspective, neglecting to analyze the behavior and attitudes of those who have not adopted e-commerce yet: the non-shoppers. The objective of this study is to explore and evaluate the behavior and attitudes of the non-shoppers' segment towards the acceptance of business-to-consumer electronic commerce (B2C-EC). The theoretical foundations of the study are provided by the Technology Acceptance Model (TAM) and the Innovations Diffusion Theory (IDT), with the addition of a specific factor related to the nature of B2C-EC: product offering of the e-commerce channel. This framework leads to an attitudinal/behavioral model which seeks to identify the factors perceived by non-shoppers as the most important for the adoption of B2C-EC. The model has been validated with data from 995 Spanish non-shoppers using the partial least squares (PLS) technique. Findings from the analysis results show that perceived usefulness, perceived compatibility and product offering affect positively the attitude of non-shoppers towards the adoption of B2C-EC and their intention to use it. Among these factors, perceived compatibility stands out as the most relevant factor to foster the adoption of B2C-EC among non-shoppers. Other implications for theory and practice are discussed in the final section.

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DOI: 10.3217/jucs-017-09-1261

Authors: Wilfred Wells, Waldemar Karwowski, Serge Sala-Diakanda, Kent Williams, Tareq Ahram, James Pharmer

Abstract: At present time most system engineers do not have access to cognitive work analysis knowledge or training in terms that they could understand and apply in the system design process. This may lead to specifying systems requirements that do not account for cognitive strengths and limitations of the prospective users. This paper proposes integration of cognitive work demands in the systems engineering process through development of a Cognitive Work Analysis (CWA) framework and a Tutorial using Systems Modeling Language (SysML). The CWA framework provides a structured approach for defining, managing, organizing, and modeling cognitive work requirements in systems engineering process.

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DOI: 10.3217/jucs-016-14-1853

Authors: Dong Kim, JingTao Yao

Abstract: One of the main problems of web-based learning is staying motivated at a sufficientlevel. Learning games offering challenges and entertainment may stimulate student motivation for learning and mitigate this problem. Web-based learning support systems combined with learninggames may efficiently promote learning by encouraging student participation in learning. This study introduces a treasure hunt model, which represents the idea of inquiry-based learning usingset theory. We demonstrate this via a prototype of a web-based learning support system called OTHI, which employs an online treasure hunt game as the learning game. We integrate the soundlearning strategies of inquiry-based learning with the Web and online game technologies in this system. We expect that our learning support system will motivate students, and furnish an inter-active student-centered learning environment.

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DOI: 10.3217/jucs-016-13-1801

Authors: Chulmo Koo, Yulia Wati

Abstract: Mobile banking has been considered to be one of the most value-added and important mobile services currently available. Considering the fact that the penetration of this technology is undefined well, particularly in developing country, this study clarified the role of trust as a mediating variable in mobile banking environment. An empirical study was undertaken in Indonesia and the data of 100 respondents were collected. The empirical results provided strong evidence for the explanatory power of our research model. Firstly, we found that the trust mediated the effects of information quality to perceived usefulness and end-user satisfaction. Second, the both relationships of system quality and perceived usefulness and system quality and end-user satisfaction were partially mediated by trust. Third, trust also showed a direct effect on both end-user satisfaction and perceived usefulness. Lastly, the result provided support of the positive relationship between perceived usefulness and end-user satisfaction. Implication for both practice and further research were also discussed.

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DOI: 10.3217/jucs-016-06-0983

Authors: Maytham Safar, Nosayba El-Sayed, Khaled Mahdi, David Taniar

Abstract: Recent work on social networks has tackled the measurement and optimization of these networks’ robustness and resilience to both failures and attacks. Different metrics have been used to quantitatively measure the robustness of a social network. In this work, we design and apply a Genetic Algorithm that maximizes the cyclic entropy of a social network model, hence optimizing its robustness to failures. Our social network model is a scale-free network created using Barabási and Albert's generative model, since it has been demonstrated recently that many large complex networks display a scale-free structure. We compare the cycles distribution of the optimally robust network generated by our algorithm to that belonging to a fully connected network. Moreover, we optimize the robustness of a scale-free network based on the links-degree entropy, and compare the outcomes to that which is based on cycles-entropy. We show that both cyclic and degree entropy optimization are equivalent and provide the same final optimal distribution. Hence, cyclic entropy optimization is justified in the search for the optimal network distribution.

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DOI: 10.3217/jucs-015-14-2786

Authors: Emilio Castellano, Luis Martínez-López

Abstract: Collaborative Filtering has been widely used in Recommender Systems helping customers of e-shops to find out items matching their requirements in huge or complex search spaces. There exist many commercial applications that show the utility of these systems, especially in e-commerce whose features and good performance obtained has driven us to consider their application in a specific domain as Academic Orientation, in order to support students’ decisions through their academic journey. We propose the use of the ideas behind the Collaborative Recommender Systems to develop a Web-based Decision Support System (Web-DSS) for Academic Orientation that analyze the students’ skills, attitudes, preferences, etc., and then compute relevant information to support their decisions concerning their academic future. Furthermore, we shall study the performance of such techniques in Academic Orientation by using a dataset gathered from various Secondary and High Schools in Spain. OrieB, a web-DSS for academic orientation is then presented.

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DOI: 10.3217/jucs-015-09-1746

Authors: Sven Tackenberg, Bernhard Kausch, Sönke Duckwitz, Christopher Schlick, Selvinaz Karahancer

Abstract: The complexity of process engineering projects in the chemical industry — resulting from the large number of activities to be accounted for as well as the required actors and resources — and the number of projects running simultaneously within an enterprise are rapidly increasing. In order to stay competitive, the factors relevant to the success of project planning and execution, e.g. the project budget or duration, must be accurately predicted and controlled. For this reason, a novel simulation approach for development projects is introduced and validated. A formal description of a development project and of an activity-oriented simulation model is given. This "meta model" is able to describe the influencing factors of a development project as well as their interrelations during the course of a project. On the basis of the meta model, an activity-oriented simulation model is developed in cooperation with enterprises from the chemical industry. The simulation model enables the automatic creation and prospective benchmarking of complex, detailed project plans. The dynamics of such a development project are represented as a stochastic Petri net, including Java functions. Organizational factors of a development project such as task scheduling, the limited availability of actors and tools or uncertainty regarding the effort required to solve a task can be systematically studied through simulation experiments. The results of these experiments assist project managers in understanding the influence of the quantity and characteristics of actors and resources on project performance. In the validation study, a chemical process design project in a large enterprise is considered and the external validity of the stochastic project model is analyzed.

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DOI: 10.3217/jucs-014-18-2912

Authors: Josep Lladós, Dimosthenis Karatzas, Joan Mas, Gemma Sánchez

Abstract: Mass digitization of document collections with further processing and semantic annotation is an increasing activity among libraries and archives at large for preservation, browsing and navigation, and search purposes. In this paper we propose a software architecture for the process of converting high volumes of document collections to semantically annotated digital libraries. The proposed architecture recognizes two sources of knowledge in the conversion pipeline, namely document images and humans. The Image Analysis module and the Correction and Validation module cover the initial conversion stages. In the former information is automatically extracted from document images. The latter involves human intervention at a technical level to define workflows and to validate the image processing results. The second stage, represented by the Knowledge Capture modules requires information specific to the particular knowledge domain and generally calls for expert practitioners. These two principal conversion stages are coupled with a Knowledge Management module which provides the means to organise the extracted and acquired knowledge. In terms of data propagation, the architecture follows a bottom-up process, starting with document image units, called terms, and progressively building meaningful concepts and their relationships. In the second part of the paper we describe a real scenario with historical document archives implemented according to the proposed architecture.

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DOI: 10.3217/jucs-014-16-2650

Authors: Judy Van Biljon, Paula Kotzé

Abstract: In human-computer interaction and computing, mobile phone usage is mostly addressed from a feature-driven perspective, i.e. which features do a certain user group use, and/or a usability perspective, i.e. how do they interact with these features. Although the feature driven and usability focus carry value, it is not the full picture. There is also an alternative or wider perspective: mobile phone use is influenced by demographic, social, cultural, and contextual factors that complicate the understanding of mobile phone usage. Drawing on concepts and models from sociology, computer-supported cooperative work, human-computer interaction and marketing, we researched the influence of culture on mobile phone adoption using interviews and two surveys. The contribution of this research is a model that includes culture as one of the factors that influence mobile phone adoption and usage. The proposed model represents the influence of mediating factors and determining factors on actual mobile phone use. The proposed model has been evaluated from both a qualitative and quantitative perspective.

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DOI: 10.3217/jucs-014-09-1391

Authors: Huyen Dao, Adam Bazinet, Robin Berthier, Ben Shneiderman

Abstract: NASDAQ Market Velocity and Market Forces are two relatively new data products that attempt to capture market sentiment, something that was previously only observable if one was on a trading floor. Given the transient and temporal properties of the data, we were challenged to create a visualization that would highlight the ever-changing qualities of Velocity and Forces. To that end, we developed FireStox, a web application that provides unified representation and filtering solutions to help market researchers observe the behavior of these metrics for one or many companies throughout the course of a trading day.

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DOI: 10.3217/jucs-014-05-0766

Authors: Sergios Soursos, Costas Courcoubetis, Richard Weber

Abstract: Nowadays, in the markets of broadband access services, traditional contracts are of "static" type. Customers buy the right to use a specific amount of resources for a specific period of time. On the other hand, modern services and applications render the demand for bandwidth highly variable and bursty. New types of contracts emerge ("dynamic contracts") which allow customers to dynamically adjust their bandwidth demand. In such an environment, we study the case of a price competition situation between two providers of static and dynamic contracts. We investigate the resulting reaction curves, search for the existence of an equilibrium point and examine if and how the market is segmented between the two providers. Our first model considers simple, constant provision costs. We then extend the model to include costs that depend on the multiplexing capabilities that the contracts offer to the providers, taking into consideration the size of the market. We base our analysis on the theory of effective bandwidths and investigate the new conditions that allow the provider of dynamic contracts to enter the market.

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DOI: 10.3217/jucs-014-05-0717

Authors: Zbigniew Hulicki

Abstract: Development of e-services in the CE (Central European) countries d epends on a number of factors which can result in overcoming or extending digital divide between the "new" and "old" EU member states. These factors comprise both drives of and barriers to development of broadband access and growth of e-services. This paper provides insight into the environment for the CE mass-market broadband adoption, and examines each of the factors that condition this adoption: novel approaches to increase ICT penetration; clear policy and legal regulations; segmented service offerings for specific user needs in such markets ; and innovative pricing schemes and service packages.

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DOI: 10.3217/jucs-012-09-1358

Authors: Robert Sinka

Abstract: This study represents a survey approach in order to analyse the information society in a regional setting. The first part deals with a current problematic issue: the human resources of the information society, which is a neglected research area of the information society. The second part of the paper will point out the main characteristics of the human adaptation of the information society. My aim is to accentuate the importance of the 'human-interface gap’. These days the accessibility is strongly connected to the education and to the fact that several jobs do not require competence in digital or information literacy. Focusing on the human aspect has become a central issue of the higher education, and one of its prominent tasks, besides others, is to prepare the next generation for the challenges of the information society.

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DOI: 10.3217/jucs-012-03-0357

Authors: Ignacio Nieto, Juan Botía, Antonio Gómez-Skarmeta

Abstract: This paper describes OCP (Open Context Platform), a middleware which provides support for management of contextual information and merging of information from different sources. The host system is thus endowed with proactive capacities which, in turn, provide a certain environmental intelligence [8]. The approach consists of a modelling of contextual information which is based on Semantic Web derived technologies and a description of the structured merging in the form of decision rules. The latter serve to classify situations of interest and subsequently to trigger off the relevant actions at each moment. Elsewhere, the underlying architecture in OCP is designed so that it can function both by centralizing all the contextual information from a central server and by distributing it among consumers and producers of this type of information.

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DOI: 10.3217/jucs-012-01-0059

Authors: Anthony Glascock, David Kutzik

Abstract: The lack of appropriate and accurate information on the ability of a frail individual to accomplish specific task oriented activities can place the individual at risk or result in the allocation of costly and unnecessary care. Although there have been previous attempts to use computer technology to obtain this information, they have proved to be costly and complex and therefore not widely used. However, a behavioral monitoring technology, based on smart-home and telemedicine applications, has been developed that obtains more accurate and timely information on the ability of frail individuals to accomplish specific tasks in their own residences than any other existing method. During a twelve month pilot study, this system has been used by care providers to assess the status of their clients, respond to immediate needs and alter overall care plans, thus resulting in better care and greater peace of mind for the individual.

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DOI: 10.3217/jucs-011-11-1780

Authors: Jason Jung

Abstract: In contrast with centralized recommender systems, social recommendation algorithm is applied to the item rating data on social networks. Meaningful recommendation can be uncovered by the topology of social network as well as the similarity between users. More importantly, this information becomes propagated into the users in the estimated same groups. As the goal of this paper, we propose a novel method for visual explanation of the recommender system on social network. For experiments, we simulate the recommendation flow by using the MovieLens dataset on a social network constructed with FOAF.

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DOI: 10.3217/jucs-011-09-1543

Authors: Ana Molina, Miguel Redondo, Manuel Ortega Cantero

Abstract: Some tasks supported by educative and collaborative tools can be more realistic and accessible if they are tackled using mobile devices. This approach allows students to benefit from the mobility features of this kind of devices, which are expected to revolutionize teaching in the next decade. In this paper we present an application called DomoSim-Mob to carry out practical activities of domotical design using PDAs. We introduce the task of collaborative planning of design which is supported by DomoSim-Mob and describe its materialization starting from the user tasks supported by the previous desktop computer version.

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DOI: 10.3217/jucs-011-03-0394

Authors: Eric Ras, Gabriela Avram, Patrick Waterson, Stephan Weibelzahl

Abstract: There are various Knowledge Management Systems available currently and designed to support knowledge sharing and learning. An example of these are Experience-based Information Systems in the domain of Software Engineering, i.e., Information Systems designed to support experience management. Lately, these have become more and more sophisticated from a technical point of view. However, there are several shortcomings that appear to limit the input, the content of these systems and their usage. The problems identified in this paper relate to knowledge acquisition, learning issues, as well as to the users' motivation and trust. We introduce an approach meant to enhance the content of the experience base and improve learning from experiences within information spaces, namely weblogs that are maintained during daily work and serve as input for both an experience base and for an information element base. In order to enhance learning, a pedagogical information agent is envisaged for retrieving suitable experiences to be further enriched with additional information elements and produce micro-didactical learning arrangements. In addition we consider the relevance of motivation and trust issues. An empirical study demonstrates that using weblogs for such an approach is feasible.

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DOI: 10.3217/jucs-011-03-0378

Authors: Stefan Münzer, Bo Xiao

Abstract: E-learning at the workplace might be accomplished by synchronous cooperative learning sessions of small groups using net-based communication. This form of learning is suitable both for course-based e-learning as well as for knowledge transfer within the company. The small groups learn self-regulated, i.e. without the guidance of an instructor. However, the learning tasks are pre-defined and a specific learning process is precisely described. In the present study, the goal of the cooperative learning sessions is to deepen pre-existing declarative knowledge. During cooperative learning, group members are required to actively use, acquire, enrich and exchange their knowledge. In a field study carried out in a large software company, a software tool was used which supported the specific process by phase-specific delivering of instructions and learning materials as well as by means of process control (including turn-taking, role assignment, and coordination of task flow). The results of the empirical evaluation demonstrate a high amount of topic-oriented contributions and the realization of the expected learning activities. However, feedback data indicated a low acceptance of the software tool because of its restrictive process control. It is discussed that there might have been a non-optimal interaction between the factors technology and target group in the study.

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DOI: 10.3217/jucs-010-12-1693

Authors: Gianpiero Cabodi, Sergio Nocco, Stefano Quer

Abstract: Binary Decision Diagrams (BDDs) have been widely used in synthesis and verification. Boolean Satisfiability (SAT) Solvers, on the other hand, have been gaining ground only recently, with the introduction of efficient implementation procedures. Specifically, while BDDs have been mainly adopted to formally verify the correctness of hardware devices, SAT-based Bounded Model Checking (BMC) has been widely used for debugging. In this paper, we combine BDD and SAT-based methods to increase the efficiency of BMC. We first exploit affordable BDD-based symbolic approximate reachability analysis to gather information on the state space. Then, we use the collected overestimated reachable state sets to restrict the search space of a SAT-based BMC. This is possible by feeding the SAT solver with a description that is the combination of the original BMC problem with the extra information coming from BDD-based symbolic analysis. We develop specific strategies to appropriately mix BDD and SAT efforts, and to efficiently convert BDD-based symbolic state set representations into SAT-oriented ones.Experimental results prove the validity of our strategy to reduce the amount of variable assignments and variable conflicts generated by SAT solvers, with a subsequent significant performance gain. We gather results with four among the most used SAT solvers, namely Chaff, Limmat, BerkMin, and Siege. We could reduce the number of conflicts up to more than 100x, and the verification time up to 30x.

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DOI: 10.3217/jucs-010-06-0691

Authors: Tobias Mueller-Prothmann, Ina Finke

Abstract: In many organisations, conservation of specialised expertise is picked out as a central theme only after experienced members have already left. The paper presents the SELaKT method, a method for Sustainable Expert Localisation and Knowledge T ransfer based on social network analysis (SNA). It has been developed during a project co-operation between the Department of Information Science at the Institute for Media and Communication Studies, Free University Berlin, and the Fraunhofer Institute for Production Systems and Design Technology IPK, Berlin. The SELaKT method uses recent insights into network analysis and pragmatically adapts SNA to suit organisational practice. Thus it provides a strategic tool to localise experts, to identify knowledge communities and to analyse the structure of knowledge flows within and between organisations. The SELaKT method shows its advances and increasing relevance for practical use by integration of specific organisational conditions and requirements into the process of analysis.

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DOI: 10.3217/jucs-010-01-0090

Authors: Edith Denman-Maier

Abstract: This paper is based on on-going research carried out in the framework of an EU project aimed at enhancing knowledge management (KM) in enterprises. It deals with the impact of intercultural factors on the accessibility and presentation of eLearning content. It reports on preliminary findings and discusses the issues which have emerged so far in the contextual study and requirements analysis conducted in preparation for designing Web-based training modules. Once the empirical research is completed and the data analyzed, guidelines will be proposed for developing Web-based training modules for culturally heterogeneous user groups sharing the same professional background. Special consideration will be given to interactive and community features.

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DOI: 10.3217/jucs-009-12-1487

Authors: Anna Fuglseth, Kjell Groenhaug

Abstract: Few studies attempt to measure organisational learning. Measurement is critical to evaluate relationships between initiatives to support learning and organisational performance. This paper proposes a theory-based tool kit for measurement of organisational learning. By tool kit we mean a collection of methods that each captures elements of the phenomenon organisational learning . The paper clarifies the term and discusses requirements of theories and methods to be included in the tool kit. Some examples of theories with methods are given. Emphasis is placed on Kelly s Personal Construct Theory with the accompanying Role Construct Repertory Test to illustrate methodological requirements.

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DOI: 10.3217/jucs-009-12-1469

Authors: Juan Cegarra-Navarro, Beatriz Rodrigo-Moya

Abstract: This paper will study the influence of three components of human capital focusing on operative personnel under a dynamic perspective. It considers learning flows and the knowledge stocks that the employees of the organization generate because of the relationships that they maintain with their clients. The influence of individual knowledge in these learning flows will be examined. These being components such as: learning capacities, automatic and conscious knowledge, on the flows of the relational learning process including transfer, transformation and harvesting phases of knowledge. In order to study the relative importance of the individual knowledge components in each phase of the relational process, the scale established by [Kohli and Jaworski 1990] will be used in this research. The paper is structured in four parts. In the first, a theoretical reference on individual knowledge on the relational learning process will be established. In the second part, some hypothesis and the necessary methodology will be proposed. In the third part the results will be shown and finally, in the conclusions some interesting aspects on the role of individual knowledge in the process described will be shown. Conclusions are based on a study of eighty-four organizations. This investigation establishes important conclusions on the role of individual knowledge in the generation of the customer capital. Concretely, the explicit knowledge of the employees is the most meaningful in the relational learning process, although it is also true that the tacit knowledge and individual learning capacities have a special importance in the harvesting phase of knowledge.

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DOI: 10.3217/jucs-009-12-1455

Authors: Luca Stefanutti, Dietrich Albert

Abstract: Simulated learning environments provide an efficient means for improving individual skills in specific problem solving and learning situations. One crucial aspect of an optimal system for simulated training environments is its capability to keep track of the improvements of the user along the whole training process. In this paper we present a set-theoretical formal framework that can be applied for the efficient assessment of the skills of an individual in a simulated learning environment. The basic concept underlying our approach is that of a functional skill mapping of the simulated learning environment through problem spaces.

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DOI: 10.3217/jucs-009-12-1428

Authors: Cord Hockemeyer, Owen Conlan, Vincent Wade, Dietrich Albert

Abstract: Several approaches for formalising prerequisite structures on skills or competencies based on the psychological theory of knowledge space have been suggested and applied for adaptive eLearning. In this paper, we will discuss how these structures may be applied in skill management in a broader sense. After introducing some formal structures for prerequisite relationships between competencies, we will briefly present an example of an adaptive eLearning system based on this approach (APeLS). Several other aspects of the system which promise to be useful for advanced skill management are discussed. In the final part of this paper, we will discuss such broader applications of the model with respect to personal as well as to organisational skill management.

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DOI: 10.3217/jucs-009-06-0571

Authors: Lilia Efimova, Janine Swaak

Abstract: Companies are starting to recognise synergies between knowledge management, training and e-learning programs, but a closer look reveals that these integration ideas are rarely implemented in practice. The goal of this paper is to provide a starting point for collaboration between corporate KM and HR/learning teams by mapping existing practices of linking KM, training and e-learning efforts. We provide an overview of experiences and future ideas of collaboration derived from several studies, group them in three themes and then illustrate each theme with a scenario. The first theme gives examples of using HR and training instruments to support knowledge management. The second theme represents cases of using KM methods (namely a community of practice) to support HR learning management efforts. The last theme describes how KM and HR/learning teams could work on joint initiatives. Then we discuss the added value of the scenarios and propose further practical steps and research directions.

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DOI: 10.3217/jucs-009-06-0481

Authors: Leena Ilmola, Anna Kotsalo-Mustonen

Abstract: In the fast moving businesses the ability to be flexible and adaptive to change is crucial. When monitoring their operating environments for weak signals and for other disruptive information companies face filters that hinder the entry of the information to the company. We are discussing three filters: mentality filter, surveillance filter and power filter. Each filter has a logic of its own that hinders effective knowledge flow. We introduce a software tool that helps to overcome these filters especially in a strategy formulation process.

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DOI: 10.3217/jucs-009-04-0369

Authors: Daniela Camhy, Robert Stubenrauch

Abstract: This bibliography offers citations for people who are interested in learning more about visual language, new types of communicating and archiving information with emphases on novel technologies and theoretical works in these multidisciplinary areas. This bibliography is considered in its broadest sense and covers references of research in humanities and social sciences as well as computer technology. Far from being exhaustive, it nevertheless covers essential resources in a selective way, so that the material can provide starting points for many different directions. What is not included here are references to visual programming languages.

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DOI: 10.3217/jucs-009-04-0349

Authors: Robert Stubenrauch, Daniela Camhy, Jennifer Lennon, Hermann Maurer

Abstract: Systems supporting new forms of communication and archiving of dynamic visual information have a range of potential applications, some of which are described in this paper on a conceptual basis. We present a visual language for dynamic (historic) maps, applications of pictorial lexicons, concepts for interactive support systems for assembly and repair, and a platform for abstract movies.

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DOI: 10.3217/jucs-009-04-0309

Authors: Hermann Maurer, Robert Stubenrauch, Daniela Camhy

Abstract: Research in neurosciences, cognitive psychology and media sciences indicates that "visual thinking" carries a potential of the human mind that is generally still neglected today but could heavily be fostered by novel types of communicating and archiving information. Computer technology (information systems, telecommunication and visual tools) in turn promises to provide a wide range of highly effective tools to support visual, dynamic communication. MIRACLE treads new paths to address a crucial issue: In what way and to what extent can and should current and future systems support new ways of communicating and archiving information using dynamic, visual information? This paper gives a survey of the numerous attempts that have been made so far to overcome language barriers by introducing artificial languages (both on a spoken/text and on a visual basis). It also analyzes the general status of technology (computer hardware and software) to support such efforts as well as a number of specific projects. From this overview we draw the conclusion that computer-based systems designed to support communicating and archiving dynamic visual information should focus on the following features: Support dynamic language elements on a structural level in addition to traditional animated icons, Incorporate gestural language elements (inspired by natural sign languages) anticipating future ways of human-computer interaction, Allow evolutionary development of the language in a group-dynamic and interactive process involving large international groups of participants. In a final section we give a brief outline of the cluster of specific projects carried out under the heading of MIRACLE.

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DOI: 10.3217/jucs-008-09-0834

Authors: Joachim Hasebrook

Abstract: Major companies, especially banks, invest in interactive distance learning replacing face-to-face training. Research has shown learning gains are mostly due to a shift in instruction. In this study, a WBT about currency management of a major German bank was examined. The communicational features of the WBT comprise a discussion forum, note taking, and automatic messaging of questions and answers between experts and students. The experimental design compared a face-to-face seminar with WBT learning. The results show that WBT participants learned as much as the seminar participants, but in about 70% of the seminar s study time. Young seminar participants performed better than older ones, while WBT learning did not produce an age effect. The results of the study demonstrate that the learners in the bank tend to choose traditional learning strategies, they do not cope optimally with co-operative and selective learning strategies, and they tend to appreciate audio-visual media. Experts did not voluntarily play an active role in the discussion processes. Communicational features, however, were used quite frequently. The users who were experienced in using a CBT and showed high self esteem gained most from WBT learning.

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DOI: 10.3217/jucs-008-05-0546

Authors: Elisabeth Milchrahm, Arnulf Hasler

Abstract: This paper reports on long-term research work of recycling networks in Germany and Austria from a knowledge-based perspective. Using data from expert interviews, we discuss the key determinants of inter-organizational knowledge transfer within networks. In particular, we highlight the factor of mutual trust as important determinant of knowledge transfer in company recycling networks. One important goal of our empirical research is the institutionalization of knowledge transfer through the implementation of a central recycling agency in order to build core capabilities and to create intellectual capital.

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DOI: 10.3217/jucs-007-10-0893

Authors: Yuliang Liu, Dean Ginther, Paul Zelhart

Abstract: Computer-mediated Communication (CMC) has been commonly compared to face-to-face (FtF) communication in recent CMC literature. Research comparisons suggested depersonalizing effects of CMC. However, this experimental study indicates that CMC is a potentially viable mode of social-emotion-oriented communication. In this study, the effects of frequency and duration of messaging on impression development in CMC were investigated. Undergraduate participants were randomly assigned to each of the four experimental groups. For a period of two weeks, participants monitored discussion lists that differed in relation to the frequency and duration of messaging in asynchronous CMC environments. ANOVA results indicated that duration and frequency had significant main effects on impression development in asynchronous CMC environments. No interaction effects were found. The results of this study not only theoretically support the social-emotion-oriented model in CMC, but also lay foundations for further research in many popular types of interactive CMC environments, including e-learning, e-commerce, and e-health.

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DOI: 10.3217/jucs-007-06-0498

Authors: Peter Johnston

Abstract: The rapid emergence of a global knowledge economy both shortens the timetable for progress on sustainable development and also offers a potential "win-win" alternative to the traditional trade-off between growth and environmental sustainability. The Lisbon Strategy and e-Europe initiative to accelerate development of the knowledge economy in Europe already addresses several aspects of social and economic sustainability. However, the trends in most resource-use and environmental impact indicators are still worsening, and much more needs to be done to realise the potential benefits of structural change in business and employment, notably in the service sector. The Stockholm and Göteborg EU Summits, and the subsequent Rio+10 conference give a timely and unique opportunity to establish European coherence and leadership in seeking sustainable development in the knowledge economy. However, we also need a new clarification of individual and business-level responsibilities for lifestyle and business organisation changes, and a much wider take-up of innovative "win-win" solutions for growth with reductions in resource use and impacts.

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DOI: 10.3217/jucs-007-06-0472

Authors: Joachim Hasebrook

Abstract: Humans are not able to cope with the exponential growth of information and the increasing speed of information and business processes fostered by information and communication technologies. Technical support not only for information storage and retrieval but also for information selection, process planning, and decision support is needed. Most of the ICT investments, however, do not foster innovation or productivity. Recent studies show that ICT-based training is the main instrument of knowledge management. On-line media and self-directed learning environments are among the most effective training solutions in terms of cost, time and logistics. In the last few years, the percentage of employees participating in training courses increased. At the same time, there has been a decline of training budgets. E-Learning is able to deliver more valuable training for less money only if it is part of an integrated knowledge and skills management system. Two case studies of knowledge and meta data management systems are discussed.

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DOI: 10.3217/jucs-006-03-0256

Authors: Patricia Carlson

Abstract: This introduction briefly summarizes the six articles that makeup this special issue on IT and process reengineering, and places them against a backdrop of the role of IT within the 21stcentury organization. Maintaining high-quality information technology (IT) is essential as organizations move toward a "system of systems" and a "team of team." Added to this milieu of managed change are emerging new requirements for leadership and challenging new roles for knowledge workers in the next decade. This article examines three goals for IT in organizations: increased productivity, mediated change, and empowered workforce. Four enablers are identified as the means through which IT can accomplish modernization: (1) using next-generation IT as cognitive tools, (2) understanding the dynamics of organizational culture in order to purposefully change culture, (3) nurturing human performance as a source of yet unrealized gains, (4) leading people as well as managing resources.

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