Distributed Systems

Journals


  1. Network Testing Utilizing ProgrammableNetworking Hardware. (, , , and ), In IEEE Communications Magazine, IEEE, .

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  2. Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand (, , and ), In Energies 2022, Vol. 15, Page 3425, Multidisciplinary Digital Publishing Institute, volume 15, .

    Abstract

    This article focuses on developing both statistical and machine learning approaches for forecasting hourly electricity demand in Ontario. The novelties of this study include (i) identifying essential factors that have a significant effect on electricity consumption, (ii) the execution of a Bayesian optimization algorithm (BOA) to optimize the model hyperparameters, (iii) hybridizing the BOA with the seasonal autoregressive integrated moving average with exogenous inputs (SARIMAX) and nonlinear autoregressive networks with exogenous input (NARX) for modeling separately short-term electricity demand for the first time, (iv) comparing the model’s performance using several performance indicators and computing efficiency, and (v) validation of the model performance using unseen data. Six features (viz., snow depth, cloud cover, precipitation, temperature, irradiance toa, and irradiance surface) were found to be significant. The Mean Absolute Percentage Error (MAPE) of five consecutive weekdays for all seasons in the hybrid BOA-NARX is obtained at about 3%, while a remarkable variation is observed in the hybrid BOA-SARIMAX. BOA-NARX provides an overall steady Relative Error (RE) in all seasons (1 6.56%), while BOA-SARIMAX provides unstable results (Fall: 0.73 2.98%; Summer: 8.41 14.44%). The coefficient of determination (R2) values for both models are >0.96. Overall results indicate that both models perform well; however, the hybrid BOA-NARX reveals a stable ability to handle the day-ahead electricity load forecasts.


    Keywords: Bayesian optimization algorithm, NARX, SARIMAX, electricity demand, short, term forecast


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  3. TCEP: Transitions in Operator Placement to Adapt to Dynamic Network Environments. (, , , , and ), In In Journal of Computer and Systems Sciences (JCSS), Special Issue on Algorithmic Theory of Dynamic Networks and its Applications., Elsevier, volume 122, .

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  4. Employability prediction: a survey of current approaches, research challenges and applications (, , , and ), In Journal of Ambient Intelligence and Humanized Computing, .

    Abstract

    Student employability is crucial for educational institutions as it is often used as a metric for their success. The job market landscape, however, more than ever dynamic, is evolving due to the globalization, automation, and recent advances in Artificial Intelligence. Identifying the significant factors affecting employability, as well as the requirements of the new job market can tremendously help all stakeholders. Knowing their weaknesses and strengths, students might better plan their career. Instructors can focus on more appropriate skill sets to meet the requirements of rapidly evolving labor markets. Program managers can anticipate and improve their curriculum to build new competencies, both for educating, training and reskilling current and future workers. All these combined efforts certainly can contribute to increasing employability. Data driven and machine learning techniques have been extensively used in various fields of educational data mining. More and more studies are investigating data mining techniques for the prediction of employability. Yet, these studies show a lot of variation, for instance, with respect to the data used, the methods adopted, or even the research questions posed. In this paper, we aim to depict a clear picture of the art, clarifying for each standard step of data mining process, the differences, and similarities of these studies, along with further suggestions. Thus, this survey provides a comprehensive roadmap, enabling the application of data mining for employability.


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  5. OpenBNG: Central office network functions on programmable data plane hardware (, , , , , , , , , and ), In International Journal of Network Management, Wiley, volume 31, .

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  6. SVNN: an efficient PacBio-specific pipeline for structural variations calling using neural networks (, and ), In BMC bioinformatics, BioMed Central, volume 22, .

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  7. Adaptive On-the-fly Changes in Distributed Processing Pipelines (, , and ), In Frontiers in Big Data, Frontiers, .

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  8. A multi-robot allocation model for multi-object based on Global Optimal Evaluation of Revenue (, , , and ), In International Journal of Advanced Robotic Systems, volume 9, .

    Abstract

    The problem of global optimal evaluation for multi-robot allocation has gained attention constantly, especially in a multi-objective environment, but most algorithms based on swarm intelligence are difficult to give a convergent result. For solving the problem, we established a Global Optimal Evaluation of Revenue method of multi-robot for multi-tasks based on the real textile combing production workshop, consumption, and different task characteristics of mobile robots. The Global Optimal Evaluation of Revenue method could traversal calculates the profit of each robot corresponding to different tasks with global traversal over a finite set, then an optimization result can be converged to the global optimal value avoiding the problem that individual optimization easy to fall into local optimal results. In the numerical simulation, for fixed set of multi-object and multi-task, we used different numbers of robots allocation operation. We then compared with other methods: Hungarian, the auction method, and the method based on game theory. The results showed that Global Optimal Evaluation of Revenue reduced the number of robots used by at least 17%, and the delay time could be reduced by at least 16.23%.


    Keywords: global optimal, multi-robot, path planning, response time, task allocation


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  9. Prediction of academic performance at undergraduate graduation: Course grades or grade point average? ( and ), In Applied Sciences (Switzerland), volume 10, .

    Abstract

    Predicting the academic standing of a student at the graduation time can be very useful, for example, in helping institutions select among candidates, or in helping potentially weak students in overcoming educational challenges. Most studies use individual course grades to represent college performance, with a recent trend towards using grade point average (GPA) per semester. It is unknown however which of these representations can yield the best predictive power, due to the lack of a comparative study. To answer this question, a case study is conducted that generates two sets of classification models, using respectively individual course grades and GPAs. Comprehensive sets of experiments are conducted, spanning different student data, using several well-known machine learning algorithms, and trying various prediction window sizes. Results show that using course grades yields better accuracy if the prediction is done before the third term, whereas using GPAs achieves better accuracy otherwise. Most importantly, variance analysis on the experiment results reveals interesting insights easily generalizable: individual course grades with short prediction window induces noise, and using GPAs with long prediction window causes over-simplification. The demonstrated analytical approach can be applied to any dataset to determine when to use which college performance representation for enhanced prediction.


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  10. The Internet of Everything: Smart things and their impact on business models (, , , , and ), In Journal of Business Research, .

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  11. Predicting academic success in higher education: literature review and best practices ( and ), In International Journal of Educational Technology in Higher Education, volume 17, .

    Abstract

    © 2020, The Author(s). Student success plays a vital role in educational institutions, as it is often used as a metric for the institution’s performance. Early detection of students at risk, along with preventive measures, can drastically improve their success. Lately, machine learning techniques have been extensively used for prediction purpose. While there is a plethora of success stories in the literature, these techniques are mainly accessible to “computer science”, or more precisely, “artificial intelligence” literate educators. Indeed, the effective and efficient application of data mining methods entail many decisions, ranging from how to define student’s success, through which student attributes to focus on, up to which machine learning method is more appropriate to the given problem. This study aims to provide a step-by-step set of guidelines for educators willing to apply data mining techniques to predict student success. For this, the literature has been reviewed, and the state-of-the-art has been compiled into a systematic process, where possible decisions and parameters are comprehensively covered and explained along with arguments. This study will provide to educators an easier access to data mining techniques, enabling all the potential of their application to the field of education.


    Keywords: Data mining, Guidelines, Higher education, Prediction, Review, Student success


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  12. Efficient conditional compliance checking of business process models (, and ), In Computers in Industry, volume 115, .

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  13. Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation (, , and ), In arXiv preprint arXiv:2003.02820, .

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  14. OpenBNG: Central office network functions on programmable data plane hardware (, , , , , , , , , and ), In International Journal of Network Management, Wiley, .

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  15. Grußwort der Gastherausgeber zum Thema Fog Computing (, , and ), In Informatik Spektrum, Springer Science and Business Media LLC, volume 42, .

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  16. Unsupervised approach towards analysing the public transport bunching swings formation phenomenon (, , , and ), In Public Transport, .

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  17. Analytical tool for the modelling and simulation of curriculum: Towards automated design, assessment, and improvement (), In International Journal of Engineering Education, volume 35, .

    Abstract

    © 2019 TEMPUS Publications. Continuous quality improvement cycle is essential in educational systems allowing institutions to meet the evolving needs of the market. As such, it is required by all accreditation agencies. Curriculum revision is a critical step of this cycle. This study proposes a modelling paradigm to automate the design, analysis and improvement of curriculum. Based on proven theoretical principles, this novel graph-based approach captures both pre-requisite and cognitive dependencies among courses, enabling an optimal learning environment for students. The presented tool allows an easy and fast analysis of the impact of potential course revisions on all other courses, hence enabling a better continuous quality improvement process, thus providing benefits to many stakeholders in the education system, namely managers, instructors, students and employers. The proposed modelling paradigm is explained and illustrated on a capstone project course offered in the College of Computer Science and IT.


    Keywords: Accreditation, Automated tool, Curriculum design, Curriculum development, Engineering education, Quality assurance


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  18. Fostering higher cognitive skills through design thinking in digital hardware course: A case study (, and ), In ICIC Express Letters, volume 13, .

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    © 2019 ICIC International. All rights reserved. Computer Science students are reportedly facing many issues in acquiring higher cognitive skills (e.g., analysis, and design). Digital hardware is one of the first courses in a typical Computer Science curriculum where students need to master these skills while analyzing and designing sequential circuits. This study investigates the pedagogical effectiveness of the Design Thinking methodology in improving students' higherorder cognitive skills in the digital hardware course. Design Thinking was embedded in the digital hardware course through a real-world design challenge where teams of students iteratively collaborated. The design problem was purposely set to necessitate knowledge and skills yet to be covered hence fostering in students' curiosity and eagerness to learn new topics, thus engaging students as active learners and meaning creators. The study demonstrates a significant gain in test scores. It also describes how to easily embed the Design Thinking process in the digital hardware curriculum.


    Keywords: Analysis, Continuous quality improvement, Design, Design Thinking, Digital Logic, Higherorder cognitive skills, Student learning outcomes


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  19. The u-can-act Platform: A Tool to Study Intra-individual Processes of Early School Leaving and Its Prevention Using Multiple Informants (, , , , and ), In Frontiers in Psychology, volume 10, .

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  20. Energy management for user's thermal and power needs: A survey ( and ), In Energy Reports, volume 5, .

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  21. IMOS: improved meta-aligner and Minimap2 on spark (, and ), In BMC bioinformatics, Springer, volume 20, .

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  22. Variability in business processes: Automatically obtaining a generic specification (, , and ), In Information Systems, volume 80, .

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  23. Multi-User Low Intrusive Occupancy Detection (, , and ), In Sensors, MDPI, volume 18, .

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  24. Topological Considerations on Decentralised Energy Exchange in the Smart Grid ( and ), In Procedia Computer Science, volume 130, .

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  25. Zero-queue ethernet congestion control protocol based on available bandwidth estimation (, and ), In Journal of network and computer applications, Elsevier, volume 105, .

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  26. Learning behind glass walls: learning style and partition-room, is there a correlation? (, , and ), In International Journal of Innovation Science, .

    Abstract

    © 2018, Emerald Publishing Limited. Purpose: This study aims to investigate how a very particular learning environment, namely, partition rooms, affect students’ teaching experience and further explore if students’ learning styles is a pertinent determinant. Partition rooms are very common in Saudi Arabia when lectures are held by male instructors for female students. The male instructor delivers his lesson behind a glass wall, creating an environment of limited visual and auditory interaction. Various digital tools are present, meant to overcome the gap caused by the lack of direct student–teacher contact. Design/methodology/approach: The researchers collected data from a sample of 109 female students who are studying at Level 4 Computer Science Department, College of Computer Sciences and Information Technology, at a public university in Saudi Arabia. All of them experienced a minimum of two courses undertaken in a partition room. The survey consists of two parts with a total of 53 questions. The first 20 questions were adopted from the perceptual learning style preference questionnaire (PLSP). Findings: Research findings reveal that students are affected differently by the various dimensions of the partition room depending on their learning style. Originality/value: There are fewer results in the literature that study learners of our particular group, namely, Saudi females. The study focuses on students studying IT and related fields. This study is almost unique, as most studies of the kind are related to the experience of females learning English as a foreign language. Therefore, the authors’ research gives much-needed insight into the conditions and perceptions of female students studying toward their degree in a technical field.


    Keywords: Cultural specific education, Educational technology, Female education, Learning environment, Partition room, Saudi education, Technology efficacy


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  27. A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications (, , and ), In Utilities Policy, volume 50, .

    Abstract

    © 2017 Elsevier Ltd Saudi Arabia aspires to transition toward a smarter electricity grid with increased reliance on renewable energy, where customers will use or produce green energy and where smart meters will enable customers to tailor their behavior and decrease their carbon footprint. The success of the transition is dependent on householder acceptance. This research studies the public's disposition toward a smarter grid. The Eastern Province of Saudi Arabia is taken as a case study through a field questionnaire to assess public knowledge about energy sources and environmental impacts on the environments, people's disposition toward a smarter electric grid, and the main motivations for undergoing this transition. A logit model is used to investigate determinants. Stated willingness is taken as a variable representing an individual's disposition. We found that the public is willing to use green energy, accept smart meters, or become co-producers. However, their fear of unknown technologies and perceptions about their high cost are major obstacles to their adoption. Enhancive knowledge, especially about ecological sensitivity, and governmental incentives will help to win public acceptance. Also, government subsidies that lower prices should be cut and dynamic pricing should be implemented to motivate electricity saving behavior.


    Keywords: Kingdom of Saudi Arabia, Renewable energy, Residential area, Smart grid, Smart metering, Social acceptance, Solar energy


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  28. Exploring the emotional dynamics of subclinically depressed individuals with and without anhedonia: An experience sampling study (, , , , and ), In Journal of Affective Disorders, volume 228, .

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  29. Topological Considerations on the Use of Batteries to Enhance the Reliability of HV-Grids (, , and ), In Journal of Energy Storage, volume 18, .

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  30. A task-based greedy scheduling algorithm for minimizing energy of mapreduce jobs ( and ), In Journal of grid computing, Springer, volume 16, .

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  31. The impact of digital technology on female students' learning experience in partition-rooms: Conditioned by social context (, , and ), In IEEE Transactions on Education, volume 61, .

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    Contribution: As expected, a partition-room environment negatively affects students' learning. An unexpected result of this study is that female students occasionally choose not to use the technology available in partition-rooms, to avoid undesirable facial exposure. Background: The main purpose of partition-rooms is to prevent male instructors from seeing female students' faces. In learning environments where instructors and students are physically separated, technology is expected to play an integral role in bridging the gap. In one side of partition-rooms, female students use their own mobile devices, such as laptops, tablets and mobile phones, for course activities and communication; in the other side, the instructor has various digital teaching equipment provided by the institution. Research Question: What effect does a partition-room's physical environment have on female students' academic performance, satisfaction, technology efficacy, and perceived learning? What effect does a partition-room's social environment have on female students' academic performance, satisfaction, technology efficacy, and perceived learning? Methodology: Both quantitative and qualitative approaches were followed. Quantitative results were obtained from a student questionnaire. Qualitative data was gathered in a focus group session. Findings: The communication benefits offered by technology are impaired by both the physical context and the cultural-social context. The latter emerged during focus group discussions where students said that their faces might by revealed in the light emitted by their devices. Thus, local culture and social context limit the benefits of using digital technology in the classroom.


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  32. Shedding Light on the Dark Corners of the Internet: A Survey of Tor Research (, and ), In Journal of Network and Computer Applications, Elsevier, volume 114, .

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  33. One for All, All for One: A Heterogeneous Data Plane for Flexible P4 Processing (, , , and ), In arXiv e-prints, .

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  34. Personalized Physical Activity Coaching: A Machine Learning Approach (, , , and ), In Sensors, volume 18, .

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  35. Adaptive Provisioning of Heterogeneous Cloud Resources for Big Data Processing (, , , and ), In Big Data and Cognitive Computing, volume 2, .

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  36. A Formal Model for Compliance Verification of Service Compositions (, and ), In IEEE Transactions on Services Computing, volume 11, .

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  37. Indoor self-localization via bluetooth low energy beacons (, , and ), In IDRBT JOURNAL OF IJBT, volume 1, .

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  38. Metrics for Sustainable Data Centers ( and ), In IEEE Transactions on Sustainable Computing, .

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  39. MuGKeG: Secure Multi-channel Group Key Generation Algorithm for Wireless Networks (, , and ), In Wireless Personal Communications, Springer, volume 96, .

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  40. A Stochastic Model for Transit Latency in OpenFlow SDNs (, , , and ), In Computer Networks, Elsevier, volume 113, .

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  41. Planning meets activity recognition: Service coordination for intelligent buildings (, , , , and ), In Pervasive and Mobile Computing, Elsevier, volume 38, .

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  42. Sizing and Siting of Large-Scale Batteries in Transmission Grids to Optimize the Use of Renewables (, , , and ), In IEEE Journal on Emerging and Selected Topics in Circuits and Systems, volume 7, .

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  43. Automated Generation Algorithm for Synthetic Medium Voltage Radial Distribution Systems (, , and ), In IEEE Journal on Emerging and Selected Topics in Circuits and Systems, volume 7, .

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  44. Analytical Modeling of End-to-End Delay in OpenFlow Based Networks (, , , , and ), In IEEE Access, IEEE, volume 5, .

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  45. A Novel Strategy for Optimising Decentralised Energy Exchange for Prosumers ( and ), In Energies, MDPI, volume 9, .

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  46. Optimizing groups of colluding strong attackers in mobile urban communication networks with evolutionary algorithms (, , , and ), In Applied Soft Computing, Elsevier, volume 40, .

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  47. Domain-Independent Planning for Services in Uncertain and Dynamic Environments ( and ), In Artificial Intelligence, Elsevier, volume 236, .

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  48. Let's get Physiqual - an intuitive and generic method to combine ssensor technology with ecological momentary assessments (, , , , , and ), In Journal of Biomedical Informatics, volume 63, .

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  49. From the grid to the smart grid, topologically ( and ), In Physica A, Elsevier, volume 449, .

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  50. Automatic RDF-ization of big data semi-structured datasets (, , , and ), In Maskana, volume 7, .

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  51. Automated planning for ubiquitous computing ( and ), In ACM Comput. Surv., ACM, volume 49, .

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  52. Design and implementation of a residential energy monitoring system prototype tailored to meet local needs (, , , , and ), In International Journal of Computing and Digital Systems, volume 5, .

    Abstract

    The Kingdom of Saudi Arabia, like many other Gulf Council Countries, is lately experiencing a very rapid population and industrial growth, which results in an increasing demand for energy. To meet this growing demand, the GCC too is transitioning towards a smarter electricity grid with increased penetration of renewable sources. However, all agree that the success of such a shift in paradigm also depends on demand side management, most of energy demands coming for residential area. Providing residents with real-time feedback on their energy consumption is a promising way to promote energy saving behavior through an increased awareness. This paper outlines the design and development phases of a residential energy monitoring system that has been tailored to meet local needs, that is to say a non-intrusive system with a user friendly interface available both in English and Arabic endowed with an alert system providing real-time consumption information, as well as energy saving and awareness tips.


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  53. Temporal dynamics of health and well-being: A crowdsourcing approach to momentary assessments and automated generation of personalized feedback (, , , , , , and ), In Psychosomatic Medicine, .

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  54. Detecting similar areas of knowledge using semantic and data mining technologies (, , , , and ), In Electronic Notes in Theoretical Computer Science, Elsevier, volume 329, .

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  55. Automating vector autoregression on electronic patient diary data (, , , , and ), In IEEE Journal of Biomedical and Health Informatics, IEEE, volume 20, .

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  56. Integrating Transactions into BPEL Service Compositions: An Aspect-Based Approach (, , and ), In ACM Transactions on the Web, ACM, volume 9, .

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  57. Characterizing topological bottlenecks for data delivery in CTP using simulation-based stress testing with natural selection (, and ), In Ad Hoc Networks, Elsevier, volume 30, .

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  58. A complex network approach for identifying vulnerabilities of the medium and low voltage grid ( and ), In International Journal of Critical Infrastructures, Inderscience, volume 11, .

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  59. HTN planning: Overview, comparison, and beyond ( and ), In Artificial Intelligence, Elsevier, volume 222, .

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  60. HowNutsAreTheDutch (HoeGekIsNL): A crowdsourcing study of mental symptoms and strengths (, , , , , , , , , , , and ), In International Journal of Methods in Psychiatric Research, .

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  61. Improving QoS of IPTV and VoIP over IEEE 802.11n (, and ), In Computers & Electrical Engineering, Elsevier, volume 43, .

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  62. Integration and massive storage of hydro-meteorological data combining big data & semantic web technologies (, , and ), In Maskana, volume 6, .

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  63. The Impact of Topology on Energy Consumption for Collection Tree Protocols: An Experimental Assessment through Evolutionary Computation (, , and ), In Applied Soft Computing, volume 16, .

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  64. Smart Education Modes and E-Learning Market: The Needs of the Next Generation (), In Smart Learning Environments Journal, The State of the Art in Smart Learning Issue, Springer, .

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  65. Leefplezier: Personalized Well-being (, , and ), In IEEE Intelligent Informatics Bulletin, volume 15, .

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  66. Generating Realistic Dynamic Prices and Services for the Smart Grid ( and ), In IEEE Systems Journal, volume 9, .

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  67. Power Grid Complex Network Evolutions for the Smart Grid ( and ), In Physica A: Statistical Mechanics and its Applications, volume 396, .

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  68. E-Mental Health Self-Management for Psychotic Disorders: State of the Art and Future Perspectives (, , , and ), In Psychiatric Services, volume 65, .

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  69. Automated Runtime Repair of Business Processes (, , , and ), In Inf. Syst., volume 39, .

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  70. Dynamic Constraint Satisfaction with Space Reduction in Smart Environments ( and ), In International Journal on Artificial Intelligence Tools, volume 23, .

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  71. Generating personalized advice for schizophrenia patients (, , , and ), In Artificial Intelligence in Medicine, volume 58, .

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  72. Coordinating the Web of Services for a Smart Home ( and ), In ACM Transactions on the Web, volume 7, .

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  73. An Interplatform Service-Oriented Middleware for the Smart Home ( and ), In International Journal of Smart Home, volume 7, .

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  74. The Management of Elearning at University of KKU, ABHA ( and ), In International Journal of Emerging Technologies in Learning, volume 8, .

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  75. The Power Grid as a Complex Network: a Survey ( and ), In Physica A: Statistical Mechanics and its Applications, volume 392, .

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  76. E-health self-management in psychotic disorders: state of the art and future perspectives (, , , and ), In Psychiatric Services, volume 65, .

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  77. Aware homes (), In Awareness Magazine: Self-awareness in autonomic systems, .

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  78. Energy Intelligent Buildings based on User Activity: A Survey ( and ), In Energy and Buildings, volume 56, .

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  79. Ontology-based Office Activity Recognition with Applications for Energy Savings (, and ), In Journal of Ambient Intelligence and Humanized Computing, .

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  80. What IS can do for Environmental Sustainability (), In Communications of the Association for Information Systems, volume 30, .

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  81. Policy-Based Scheduling of Cloud Services ( and ), In Scalable Computing: Practice and Experience, volume 13, .

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  82. Service-Orientation and the Smart Grid: State and Trend (), In Service Oriented Computing and Applications, volume 6, .

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  83. Optimizing Energy Costs for Offices Connected to the Smart Grid ( and ), In IEEE Transactions on Smart Grid, volume 3, .

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  84. Logic for physical space ( and ), In Synthese, volume 18, .

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  85. Forward ( and ), In Journal of System Assurance Engineering and Management, volume 3, .

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  86. Reduced Context Consistency Diagrams for Resolving Inconsistent Data ( and ), In ICST Transactions on Ubiquitous Environments, volume 12, .

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  87. Usability Evaluation of a Web-Based Support System for People With a Schizophrenia Diagnosis (), In Journal of Medical Internet Research, volume 14, .

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  88. Modeling Dynamic Reconfigurations in Reo using High-Level Replacement Systems (, , and ), In Science of Computer Programming, volume 76, .

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  89. Transaction management in Service-Oriented Systems: requirements and a proposal (), In IEEE Transactions on Service Computing, volume 2, .

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  90. Towards Decentralized Trading: A Topological Investigation of the Medium and Low Voltage Grids ( and ), In IEEE Transactions on Smart Grid, volume 2, .

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  91. Deriving Business Processes with Service Level Agreements from Early Requirements (), In Journal of Systems and Software, volume 84, .

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  92. An Online Portal on Outcomes for Dutch Service Users (, and ), In Psychiatric Services, volume 62, .

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  93. Modelling and Managing the Variability of Web Service-based Systems (), In Journal of Systems and Software, volume 83, .

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  94. Channel-based Coordination via Constraint Satisfaction (, , and ), In Science of Computer Programming, .

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  95. Automated graph-based methodology for fault detection and location in power systems (, , and ), In IEEE Transactions on Power Delivery, volume 25, .

    Abstract

    This study investigates how the model-based fault detection and location approach of structural analysis can be adapted to meet the needs of power systems, where challenges associated with increased system complexity make conventional protection schemes impractical. With a global view of the protected system and the systematic and automated use of the system's analytical redundancy, faults are detected and located by more than one means. This redundancy can be used as a confirmation mechanism within a wide-area protection scheme to avoid unnecessary or false tripping due to protection component failure or disturbance. Furthermore, this redundancy turns the sensor configuration problem into an optimization problem with regard to fault detection and location. The effectiveness of different system topologies can then be compared on the basis of the optimal number of sensors they require. The principle of structural analysis is described in detail and illustrated on a simple power system model. Pertinence of the approach is demonstrated through simulation. © 2010 IEEE.


    Keywords: Fault diagnosis, Power system protection, Structural analysis, Wide-area protection


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  96. Are our homes ready for services? A domotic infrastructure based on the Web service stack ( and ), In Pervasive and Mobile Computing, volume 4, .

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  97. Fault diagnosis of a water for injection system using enhanced structural isolation (, and ), In International Journal of Applied Mathematics and Computer Science, volume 18, .

    Abstract

    A water for injection system supplies chilled sterile water as a solvent for pharmaceutical products. There are ultimate requirements for the quality of the sterile water, and the consequence of a fault in temperature or in flow control within the process may cause a loss of one or more batches of the production. Early diagnosis of faults is hence of considerable interest for this process. This study investigates the properties of multiple matchings with respect to isolability, and it suggests to explore the topologies of multiple use-modes for the process and to employ active techniques for fault isolation to enhance structural isolability of faults. The suggested methods are validated on a high-fidelity simulation of the process.


    Keywords: Fault diagnosis, Fault isolation, Matching, Structural analysis


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  98. Structural analysis of fault isolability in the DAMADICS benchmark (, , , and ), In Control Engineering Practice, volume 14, .

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    Structural analysis is a powerful tool for early determination of fault detectability/fault isolability possibilities. It is shown how different levels of knowledge about faults can be incorporated in a structural fault isolability analysis and how they result in different isolability properties. The results are evaluated on the DAMADICS valve benchmark model. It is also shown how to determine which faults in the benchmark need further modelling to get desired isolability properties of the diagnosis system. © 2005 Elsevier Ltd. All rights reserved.


    Keywords: Fault detection and isolation, Fault modelling, Structural analysis


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  99. Structural isolability of faults and breakdowns: Application to a valve model (, , and ), In Journal Europeen des Systemes Automatises, volume 38, .

    Abstract

    Structural analysis is a powerful tool for early determination of many underlying properties of a system. This tool is widely used for the diagnosis of complex systems for the early analysis of structural detectability and isolability of faults. The contribution of this paper is twofold: different points such as faults representation or how to handle differential variables are clarified. It is then shown how different levels of knowledge about faults can be incorporated in a structural fault isolability analysis and how they result in different isolability properties. The results are evaluated on a valve model that constitutes a benchmark for the European DAMADICS 1 Research and Training network. It is also shown how to determine which faults in a system need further modelling investigation to get desired isolability properties.


    Keywords: Diagnosis, Fault isolability, Modelling, Structural analysis


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  100. Isolabilité structurelle des défaillances. Application à un modèle de vanne (, , and ), In Journal Européen des Systèmes Automatisés, volume 38, .

    Abstract

    Structural analysis is a powerful tool for early determination of many underlying properties of a system. This tool is widely used for the diagnosis of complex systems for the early analysis of structural detectability and isolability of faults. The contribution of this paper is twofold: different points such as faults representation or how to handle differential variables are clarified. It is then shown how different levels of knowledge about faults can be incorporated in a structural fault isolability analysis and how they result in different isolability properties. The results are evaluated on a valve model that constitutes a benchmark for the European DAMADICS1 Research and Training network. It is also shown how to determine which faults in a system need further modelling investigation to get desired isolability properties.


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    doi
  101. , In .

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