| Journal Papers |
– S. Alavian Ghavanini, E. Homayounvala, A. Rezaeian, “Mood-Tracking Application as Persuasive Technology for Reduction of Occupational Stress”, accepted for publication in International Journal of Mobile Learning and Organization, 2017
Abstract
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– M. Eslami, M. Firoozabadi, E. Homayounvala, “User Preferences for Adaptive User Interfaces in Health Information Systems” , Journal of Universal Access in the Information Society, August 2017.
Abstract
An adaptive user interface requires identification of user requirements. Interface designers and engineers must understand end-user interaction with the system to improve user interface design. A combination of interviews and observations is applied for user requirement analysis in health information systems (HIS). Then, user preferences are categorized in this paper as either data entry, language and vocabulary, information presentation, or help, warning and feedback. The user preferences in these categories were evaluated using the focus group method. Focus group sessions with different types of HIS users comprising medical staff (with and without computer skills) and system administrators identified each user group’s preference for the initial adaptation of the HIS user interface. User needs and requirements must be identified to adapt the interface to users during data entry into the system. System designers must understand user interactions with the system to identify their needs and preferences. Without this, interface design cannot be adapted to users and users will not be comfortable using the system and eventually abandon its use.
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– Sh. Akbarinasaji, E. Homayounvala, “A Novel Context-Aware Augmented Reality-Assisted Framework for Maintenance Systems” , Journal of Ambient Intelligence and Smart Environments, Vol.9, pp.315-327, 2017.
Abstract
Augmented Reality (AR) bridges the gap between the real and the virtual world by bringing virtual information to a real environment as seamlessly as possible. The need for better perception of knowledge-intensive complex maintenance tasks and access to large amounts of documents and data makes the use of AR technology promising in a maintenance domain. Context-awareness enhances the usability of such AR applications, i.e. the output and behavior of the system will be adapted according to different contexts, such as the user location, preferences, devices, etc. to afford a higher level of personalization. The adaptation needs to be efficient in terms of performance and speed. This paper presents an optimized framework which combines context-awareness and AR for training and assisting technicians in maintaining equipment in an industrial context to improve field workers effectiveness. Ontology is used to model a maintenance context, and Semantic Web Rule Language (SWRL) provides logical reasoning. This optimized framework utilizes a behavior network to select a collection of suitable actions based on the current step of an ongoing task, and applies context-based inferred information from the ontology to each member of this collection. Evaluation results comparing the performance of the proposed framework with conventional ontology alone in a maintenance domain confirmed that the proposed framework in this research provides the same results as the ontology in terms of content, but it runs much faster in terms of run-time and performance. The proposed context-aware framework is quite valuable especially in terms of response time and performance for maintenance systems with a large number of maintenance activities.
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| – M. Khalilzadeh, A. Taleb pour, E. Homayounvala, “Identification and Classification of Organizational level competencies for BI success” , Journal of Intelligence Studies in Business, Vol.6, 2016.
Abstract
Business intelligence is a technology-oriented solution that businesses need to survive in today’s competitive and constantly changing market. To gain the benefits of BI systems, it is important to evaluate, assess, and improve factors that have an influence on BI success. Organizational competencies can provide answers to the question of how companies could gain more benefits from BI systems. While investment in BI systems is increasingly growing, measures to evaluate effective organizational competencies leading to BI success are gaining more importance. Therefore, this research identified a number of effective organizational competencies that contribute to BI success. Using the developed questionnaire for determining the effect of organizational level success on BI success, the research data was gathered for the study. A chi-square test confirmed the effectiveness of all nineteen identified competencies. Then, an exploratory factor analysis (EFA) was carried out on the data in order to identify the underlying dimensions. In addition, competencies were grouped into six categories, namely data management, information system/information technology (IS/IT) development, financial resources, relationship management, IS strategy and human capital policies. As a result, these competencies can be used as a measure to evaluate an organization’s status in holding some of the effective factors for BI success.
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– S. Bani hashemi, E. Homayounvala, A. Taleb pour, A. Abdolreza, “Identifying and Prioritizing Evaluation Criteria for User-Centric Digital Identity Management Systems” , International journal of advanced computer science and applications, Vol.7, pp.45-54, 2016.
Abstract
Identity Management systems are used for securing digital identity of users in reliable, automated and compatible way. Service providers employ identity management systems which are cost effective and scalable but cause poor usability for users. Identity management systems are user-centric applications which should be designed by considering users’ perspective. User centricity is a remarkable concept in identity management systems as it provides more powerful user control and privacy. This approach has been evolved from amending past paradigms. Thus, evaluation of digital identity management systems based on users’ point of view, is really important. The main objective of this paper is to identify the appropriateness of the criteria used in evaluation of user-centric digital identity management systems. These criteria are gathered from the literature and then categorized into four groups for the first time in this work to examine the importance of each parameter. In this approach, several interviews were performed as a qualitative research method and two questionnaires have been filled out by forty six users who were involved with identity management systems. Since the answers are perception based data the most important criteria in each category are assessed by using fuzzy method. This research found that the most important criteria are related to security category. The results of this research can provide valuable information for managers and decision makers of hosting companies as well as system designers to adapt and develop appropriate user-centric digital identity management systems.
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– E. Homayounvala, “A Bayesian Approach to Service Selection for Secondary Users in Cognitive Radio Networks” , International journal of advanced computer science and applications, Vol.6, pp.201-204, 2015.
Abstract
In cognitive radio networks where secondary users (SUs) use the time-frequency gaps of primary users’ (PUs) licensed spectrum opportunistically, the experienced throughput of SUs depend not only on the traffic load of the PUs but also on the PUs’ service type. Each service has its own pattern of channel usage, and if the SUs know the dominant pattern of primary channel usage, then they can make a better decision on choosing which service is better to be used at a specific time to get the best advantage of the primary channel, in terms of higher achievable throughput. However, it is difficult to inform directly SUs of PUs’ dominant used services in each area, for practical reasons. This paper proposes a learning mechanism embedded in SUs to sense the primary channel for a specific length of time. This algorithm recommends the SUs upon sensing a free primary channel, to choose the best service in order to get the best performance, in terms of maximum achieved throughput and the minimum experienced delay. The proposed learning mechanism is based on a Bayesian approach that can predict the performance of a requested service for a given SU. Simulation results show that this service selection method outperforms the blind opportunistic SU service selection, significantly.
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– E. Homayounvala, N. Pourmehr, “Evaluation of Augmented Reality Technology Acceptance by Iranian Tourists” , International journal of Information Technology & Business Management, pp.25-30, 2015.
Abstract
Tourism industry has a significant impact on the economy of many countries. Providing enjoyable tourism experience is an important issue in this industry. Information technologies can boost on-trip tourists’ experience. Augmented Reality (AR) technology is among technologies with great potential in this industry. But technologies can only enhace users’ experience if they are accepted and adopted by the users. There are limited studies that analyze the social acceptance of augmented tourism experience.This paper examines the acceptance of AR technology based on the experiences of tourists in Tehran, Iran. We find how perceived usefulness and the perceived ease of use have impct on the intention to use AR technology. The results of this study can provide valuable information for developers and designers of augmented tourism experience.
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– E. Homayounvala, “Early Requirement Engineering Based on Data Mining and Social Modelling” , Journal of Information and communication Technologies, Vol.3, pp.1-5, 2013.
Abstract
Users’ needs and interests are major issues in information system design. In order to design systems that truly meet users’ needs or add new features to already developed systems to better satisfy users’ needs, early requirement engineering can play a significant role. Early requirement engineering refers to issues that should come before the traditional requirements analysis activities. This paper proposes utilization of data mining techniques as a tool to acquire better understanding of users’ needs and interests in early requirement engineering. We believe that information systems with large datasets hold a wealth of information hidden in their databases. Therefore, data mining techniques can be applied to uncover users’ needs and interests for better domain understanding and also in order to design new features for system development. In this paper, a new methodology for requirement elicitation based on data mining techniques is proposed. The proposed methodology has an evaluation phase in which identified requirements, can be analyzed based on Strategic Dependency and Strategic Rationale models in i* framework which is based on social modeling. Consistency of customer and other stakeholders’ requirements can be studied in this methodology by strategic reasoning and the label propagation algorithm.
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– E. Homayounvala, A. J., “Promoting Research Collaboration Based on Data Mining in Library Information Systems” , International journal of Information Technology & Business Management, Vol.8, pp.73-82, 2012.
Abstract
Research collaboration connects distributed knowledge and competencies into new ideas and research institutes and has been the subject of many research projects. We argue that academic libraries, including libraries of universities and research institutes, hold a wealth of information regarding patrons’ research interests hidden in their data bases. Mining these databases can provide better understanding of researchers’ needs and interests. This paper has two main contributions. Firstly, it proposes a new methodology based on data mining techniques in library information systems to uncover patrons’ research interests in order to facilitate research collaboration including interdisciplinary research. The proposed methodology, studies data mining techniques in a library information system as a case study and makes advantage of clustering algorithms to cluster researchers based on their library usage which is interpreted as their research interests. The second contribution of this paper is that, it presented a knowledge map as a visual representation of usage trends of an academic library to portray virtual interest groups based on item use information. The result of this study can support managers and decision makers for strategic decision making regarding future research directions and collaborations. The outcome of the case study confirms our hypotheses by revealing clusters of library users with similar research interests validated by their academic backgrounds.
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| – E. Homayounvala, A. Aghvami, “User Preference Modelling for Access Selection in Multiple Radio Access Environments” , IEICE Transactions on Communications, pp.4186-4193, 2005.
Abstract
Access selection in future multiple radio access environments is considered in this paper from a new perspective, that of the consumer. A model is proposed for the automatic acquisition of user preferences to assist in access selection decision making. The proposed approach uses a two-level Bayesian C-Metanetwork that models individual user preferences in terms of affordable cost, acceptable level of quality of service and reputation of the access networks. User preferences under different contexts, such as leisure and business, are also considered. The model also adapts to the change of user preferences over time. A simulator has been developed to evaluate the proposed model and the simulation results are promising in terms of the proportion of correct preference predictions after a small number of training samples
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| Conference Papers |
| – A. Bodaghi, E. Homayounvala, “Personalization of Interactive Recommender Systems for Expert Users”, 4th International Conference on Web research, Tehran, Iran, April 2018.
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| – E. Homayounvala, S. Alavian Ghavanini, “Investigating the Relationship between Parental Supervision of their Children’s Internet Settings and Children Reactions”, 4th International Conference on Web research, Tehran, Iran, April 2018.
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| – Sh. Shokoufefard, M.A. Mazaheri, E. Homayounvala, “Development of a Novel Serious Game for the Assessment of Maternal Sensitivity and e-coaching Mothers of 1 to 5 years old Children” , In e-Coaching for Health and Wellbeing (eCHW2017), At Amsterdam, Netherland, 2017.
Abstract
A large part of the stability of child’s internal working model of attachment depends on his/her relationship with caregiver. Mother’s responses to child’s needs can be different in various situations and developmental stages. The main point of all the available sensitivity measurement is exact observation of target behaviors in natural circumstances like home by a completely educated observer, which causes many limitations. According to the importance of identifying the different situational requirements in mother-child relationship and providing urgent interventions, development of a serious game give us the possibility of simulating mother-child interacting situation as in real life and by considering various contexts and circumstances. This game will be installed on smartphones and tablets and mother as a user, plays the game and interacts with a child in different situations. System’s feedback in form of child reactions in the game provides e-coaching for mother regarding how to pick up sensitive approach toward the child.
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| – E. Homayounvala,S. Alaviyan Ghavanini “Tracking My Mood for e-Coaching, Comparing User Acceptance of Self-Report Mood-Tracking and Automatic Mood Detection from Facial Expression” , In e-Coaching for Health and Wellbeing (eCHW2017), At Amsterdam, Netherland, 2017.
Abstract
Mood-tracking mobile applications are among novel m-health approaches that can be utilized to create mood-journals for e-coaching. Mood-journals can increase users’ self-awareness and consequently emotional self-management and also is a valuable tool for communicating moods to coach. Interaction design or human-computer interface of such mobile health apps plays an important role in acceptance of such applications. In this paper we compare self-reporting and mood detection from facial expression as an automatic mood tracking method. Our research question is finding which one of these two input methods is considered more acceptable by users. To answer this question, two mobile mood-tracking applications are selected and then their user acceptances are compared. The applications are introduced to participants before completing technology acceptance questionnaire. The results show that self-reporting app is considered more useful.
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| – A. J., E. Homayounvala, “Organizational Knowledge Explorer: Architecture, Designing and Prototyping: IRANDOC Case Study” , In International Conference on Innovation Management and Technology Research (ICIMTR), 2012.
Abstract
Knowledge management refers to identifying and leveraging the collective knowledge in an organization to help the organization compete more effectively in market. However, many managers do not have a comprehensive view of their organizational knowledge. It is also very rare that an organization utilizes an information system that prepares reports about its knowledge assets. In this research, we try to identify the knowledge assets focusing on research institutes. We define logical relationships between the main entities and discover organizational datasets that show the status of the knowledge assets. Then we design and build an organizational knowledge explorer prototype, named KnowEx, for our research institute, IRANDOC. We demonstrate that KnowEx software helps managers to gain an abstract overview of their organizations by exploring and observing IRANDOC organizational knowledge map. We also show that the designed software, KnowEx, works as a supportive tool to permit decision makers traveling around the organization knowledge space in order to decide about knowledge entities. This software provides a huge relational map of organizational knowledge assets that one can explore it locally.
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| – A. Jalalimanesh, E. Homayounvala, “Organizational Knowledge Mapping based on Library Information System” , In IADIS International Conference Collaborative Technologies, 2011.
Abstract
One of the most popular techniques for identifying knowledge in organizations is knowledge mapping. It can help decision makers to better understand the knowledge flow within the organizations. Mapping organizations knowledge, especially in research institutes, has attracted much attention from senior managements in recent years. Libraries, among the most important parts of research institutes, have a significant role in scientific advances. Due to this important role, many knowledge operations take place in collaboration with libraries. All of library transactions including users borrowing and returning logs and also books metadata are recorded in library information systems. Users’ transaction logs are rich resources to extract information about knowledge operations in an organization.
In this paper we propose a new methodology for drawing knowledge map, based on library information system logs. Our proposed methodology contains five steps including data collection and making data warehouse, data preprocessing and refinement, applying knowledge mapping algorithm for extracting input data for mapping, drawing knowledge map and finally analyzing the results. According to this methodology, we have drawn the IRANDOC knowledge map emphasizing interdisciplinary domains based on library information system users’ logs. IRANDOC knowledge map shows most studied subjects and also interrelation between them which are invaluable source of knowledge for IRANDOC decision makers in order to initiate research projects.
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| – E. Homayounvala, I. Groves, A. Aghvami, “On Migration Policies for Personal Assistant Agents Embedded in Future Intelligent Mobile Terminals” , In 6th IEE International Conference on 3G and Beyond,, 2005.
Abstract
Personalization is gaining more and more attention as the unique selling point of mobile devices. Future mobile terminals should be intelligent enough to match users’ unique needs and preferences and provide personalized assistance for mobile users. Personal assistant agents are an enabling technology for the realization of personalization for mobile users. Personal assistant agents observe user behavior and make mobile services more valuable for users by making them easier to use and more adaptive. This paper has two main contributions. First, it studies the evaluation of personal assistant agents from when they were introduced until their current applications in mobile telecommunications. Secondly, it highlights the personal agent migration problem and presents a solution to this problem. A migration policy based on user classification is proposed to enhance the performance of mobile services.
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| – E. Homayounvala, A. Aghvami, “Performance Evaluation of Personal Agent Migration Policies in an Ambient Use Case Scenario” , In European Symposium on Ambient Intelligence, 2004.
Abstract
This paper investigates the impact of agent migration on the performance of personal agents in an ambient use case scenario. Four migration policies are proposed and a performance model, based on two quantitative performance metrics, network load and response time for processing the user request, is applied to compare the performance of the proposed migration policies. Scenario mapping to performance model and analytical results are also discussed in this paper. An agent emulator is designed and implemented in the Java programming language based on the Jatlite agent framework. The emulator is used to produce the experimental results of this study. It has been shown that, in this scenario, the policy in which a user agent follows the mobile user in the wired side of wireless network lowers the response time when the agent size is smaller than the reply size. However, when the reply size is smaller than the agent size, a simple stay-at-home policy outperforms the other three policies.
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| – E. Homayounvala, S. Ghorashi, A. Aghvami, “A Bayesian Approach to Modelling User Preferences for Reconfiguration” , In E2R Workshop on Reconfigurable Mobile Systems and Networks Beyond 3G, 2004.
Abstract
A dynamic radio network simulator is implemented for studying WCDMA based hierarchical cell structures. The simulator allows estimation of capacity and quality of service related issues in a two-layer network (microcells and macrocells). The input to the simulator is base station and mobile station information and its output is presented as the blocking and dropping probabilities, handoff rate and capacity of the assumed network. Both uplink and downlink are considered. As an example, the impact of between-layer handover on the capacity is investigated. The whole simulator is based entirely on visual C++ software.
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| – S. Ghorashi, E. Homayounvala, F. Said, A. Aghvami, “Dynamic simulator for studying WCDMA based hierarchical cell structures” , In Pimrc 2000: The 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2001.
Abstract
A dynamic radio network simulator is implemented for studying WCDMA based hierarchical cell structures. The simulator allows estimation of capacity and quality of service related issues in a two-layer network (microcells and macrocells). The input to the simulator is base station and mobile station information and its output is presented as the blocking and dropping probabilities, handoff rate and capacity of the assumed network. Both uplink and downlink are considered. As an example, the impact of between-layer handover on the capacity is investigated. The whole simulator is based entirely on visual C++ software.
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