Distributed Systems

Publications

    2022


    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. On the Incremental Reconfiguration of Time-sensitive Networks at Runtime (, , , , and ), In Proceedings of the IFIP Networking Conference., IFIP, .

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    4. Enhancing Flexibility for Dynamic Time-Sensitive Network Configurations (, , , , and ), In Proceedings of the 3rd KuVS Fachgespräch on Network Softwarization, Universität Tübingen, .

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    5. Travel light: state shedding for efficient operator migration (, , and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (DEBS'22), ACM press, .

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    6. FA2: Fast, Accurate Autoscaling for Serving Deep Learning Inference with SLA Guarantees (, , , and ), In Proceedings of the 28th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2022), IEEE, .

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    7. PANDA: performance prediction for parallel and dynamic stream processing (, , and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems, ACM press, .

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    8. Window-based Parallel Operator Execution with In-Network Computing: Proceedings (, and ), In Proceedings of the 16th ACM International Conference on Distributed and Event-based Systems (DEBS '22), ACM New York, NY, USA, .

      Abstract

      Data parallel processing is a key concept to increase the scalability and elasticity in event streaming systems. Often data parallelism is accomplished in a splitter-merger architecture where the splitter divides incoming streams into partitions and forwards them to parallel operator instances. The splitter performance is a limiting factor to the system throughput and the parallelization degree.This work studies how to leverage novel methods of in-network computing to accelerate the splitter functionality by implementing it as an in-network function. While dedicated hardware for in-network computing has a high potential to enhance the splitter performance, in-network programming models like the P4 language are also highly limited in their expressiveness to support corresponding parallelization models. We propose P4SS which supports overlapping and non-overlapping count-based windows for multiple independent data streams and parallelizes them to a dynamically configurable number of operator instances. We validate in the context of a prototypical implementation our splitting strategy and its scalability in terms of switch resource consumption.


      Keywords: Data Parallelism, In-network Computing, Load Balancing, Complex Event Processing (CEP), P4 Language, Data Plane Programming


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    9. On the Use of the Conformance and Compliance Keywords During Verification of Business Processes (, and ), In BPM 2022 Forum, Springer International Publishing, .

      Abstract

      A wealth of techniques have been developed over the past decades to help organizations understand their processes, verify correctness against requirements and diagnose potential problems. In general, these techniques for verification allow us to check whether a business process conforms or complies with some specification, and each of them is specifically designed to solve a particular business problem at each stage of the BPM lifecycle. However, the terms conformance and compliance are often used as synonyms and their distinct differences in verification goals is blurring. As a result, the terminology used to describe the techniques or the corresponding verification activity does not always match with the precise meaning of the terms as they are defined in the area of verification. Consequently, the confusion of these terms may hamper the application of the different techniques and the correct positioning of research. In this position paper, we aim to provide comprehensive definitions and a unified terminology throughout the BPM lifecycle and the artifacts they apply to. Moreover, we explore the consequences when these terms are used incorrectly. In doing so, we aim to improve transfer from research to practical applications and increase adoption of relevant approaches and new advances in the field by clarifying the relation between available techniques and the intended verification goals.


      Keywords: Conformance, Compliance, Verification, Review


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    2021


    1. Multi-Energy Management of Buildings in Smart Grids (), University of Groningen, .

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    2. Automated Service Composition Using AI Planning and Beyond (), Chapter in (M. Aiello, A. Bouguettaya, D. A. Tamburri, W. J. van den Heuvel, eds.), Springer International Publishing, .

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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. Digital Twins: an enabler for digital transformation ( and ), Chapter in The Digital Transformation handbook, .

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    10. Accelerating the Performance of Data Analytics using Network-centric Processing (), In The 15th ACM International Conference on Distributed and Event-based Systems (DEBS '21), June 28-July 2, 2021, Virtual Event, Italy, ACM New York, NY, USA, .

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    11. Leveraging Flexibility of Time-Sensitive Networks for dynamic Reconfigurability (, , , , and ), In Proceedings of IFIP Networking 2021, IFIP, .

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    12. Leveraging PIFO Queues for Scheduling in Time-Sensitive Networks (, , , , , and ), In In the Proceedings of the IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2021)., IEEE, .

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    13. P4-CoDel: Experiences on Programmable Data Plane Hardware (, , , , and ), In Proceedings of the IEEE International Conference on Communications (ICC 2021): Next-Generation Networking and Internet Symposium, IEEE, .

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    14. Towards QoE-Driven Optimization of Multi-Dimensional Content Streaming (, , , , , , and ), In Proceedings of the Conference on Networked Systems 2021 (NetSys 2021), European Association of Software Science and Technology, .

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    15. "log data compliance" (, , and ), .

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      This disclosure relates to a computer analysing log data. The computer receives log data comprising traces having log events from respective process executions. The computer creates a stream of log events, wherein the stream is sorted by the event time. The computer iterates over the stream of log events, and for each log event, executes update functions that define updates of a set of variables based on the log events. The set of variables comprises at least one cross-trace variable to calculate an updated value of the set of variables. The update functions define updates of the cross-trace variable in response to the log events of the traces. The computer further executes evaluation functions on the set of variables to determine compliance in relation to the log data based on the updated value. The evaluation functions represent compliance rules based on the set of variables including the cross-trace variable.


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    16. Iot based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications (, and ), volume 13, .

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      Safe water is becoming a scarce resource, due to the combined effects of increased population, pollution, and climate changes. Water quality monitoring is thus paramount, especially for domestic water. Traditionally used laboratory-based testing approaches are manual, costly, time consuming, and lack real-time feedback. Recently developed systems utilizing wireless sensor network (WSN) technology have reported weaknesses in energy management, data security, and communication coverage. Due to the recent advances in Internet-of-Things (IoT) that can be applied in the development of more efficient, secure, and cheaper systems with real-time capabilities, we present here a survey aimed at summarizing the current state of the art regarding IoT based smart water quality monitoring systems (IoT-WQMS) especially dedicated for domestic applications. In brief, this study probes into common water-quality monitoring (WQM) parameters, their safe-limits for drinking water, related smart sensors, critical review, and ratification of contemporary IoT-WQMS via a proposed empirical metric, analysis, and discussion and, finally, design recommendations for an efficient system. No doubt, this study will benefit the developing field of smart homes, offices, and cities.


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    2020


    1. Office Occupancy Detection based on Power Meters and BLE Beaconing (), University of Groningen, .

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    2. Optimization of energy distribution in smart grids (), University of Groningen, .

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

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

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

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

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

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    11. Theorie: processen van voortijdig schoolverlaten en begeleiding om dat te voorkomen (, , , and ), Chapter in Voortijdig schoolverlaten voorkomen Perspectieven van wetenschap, praktijk en beleid (M. A. E. van der Gaag, N. R. Snell, G. G. Bron, E. S. Kunnen, eds.), Uitgeverij Acco, .

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    12. Procesonderzoek: processen van uitvallen, blijven en begeleiding (, , , , , and ), Chapter in Voortijdig schoolverlaten voorkomen Perspectieven van wetenschap, praktijk en beleid (M. A. E. van der Gaag, N. R. Snell, G. G. Bron, E. S. Kunnen, eds.), Uitgeverij Acco, .

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    13. Towards Service-Oriented and Intelligent Microgrids (, and ), In Proceedings of the 3rd International Conference on Applications of Intelligent Systems, Association for Computing Machinery, .

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    14. Predictive Multi-Objective Scheduling with Dynamic Prices and Marginal CO2-Emission Intensities ( and ), In ACM e-Energy 2020, .

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    15. Sustainability Choices when Cooking Pasta (, and ), In ACM e-Energy 2020, .

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    16. Operator as a Service: Stateful Serverless Complex Event Processing (, , , and ), In Proceedings of the 2020 IEEE International Conference on Big Data, IEEE, .

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    17. The Community Structure of Constraint Satisfaction Problems and Its Correlation with Search Time ( and ), In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), volume , .

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    18. Microbursts in Software and Hardware-based Traffic Load Generation (, and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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    19. Flexible Content-based Publish/Subscribe over Programmable Data Planes (, , , and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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    20. P4STA: High Performance Packet Timestamping with Programmable Packet Processors (, , , and ), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, .

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    2019


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

      Abstract

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

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

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

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    7. Office Multi-Occupancy Detection using BLE Beacons and Power Meters (, and ), In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics, and Mobile Communication Conference, .

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    8. Temporal Analysis of 911 Emergency Calls Through Time Series Modeling (, , and ), In The International Conference on Advances in Emerging Trends and Technologies, .

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    9. Prediction of Imports of Household Appliances in Ecuador Using LSTM Networks (, , and ), In Conference on Information Technologies and Communication of Ecuador, .

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    10. Predictive CO2-Efficient Scheduling of Hybrid Electric and Thermal Loads ( and ), In 2019 IEEE International Conference on Energy Internet (ICEI), .

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    11. ECiDA: Evolutionary Changes in Data Analysis (, , , , , , , and ), In ICT.Open, Hilversum, The Netherlands, .

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    12. Development of a decision-aid for patients with depression considering treatment options: prediction of treatment response using a data-driven approach (, , , , , , , , , and ), In ISPOR Europe 2019, Copenhagen, Denmark, .

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    13. Time to get personal? The impact of researchers’ choices on the selection of treatment targets using the experience sampling methodology (, , , , , , , , , and ), PsyArXiv, .

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    2018


    1. The Web Was Done by Amateurs: A Reflection on One of the Largest Collective Systems Ever Engineered (), Springer, .

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    2. The non-existent average individual: Automated personalization in psychopathology research by leveraging the capabilities of data science (), University of Groningen, .

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

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

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    5. 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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    6. 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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    7. A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications (, , and ), In Utilities Policy, volume 50, .

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      © 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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    8. 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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    9. 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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    10. 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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    11. 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, .

      Abstract

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

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

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

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

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    17. Low-power Appliance Recognition using Recurrent Neural Networks (, , and ), In Applications of Intelligent Systems, .

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    18. A remotely piloted aerial system for a faster processing of traffic collisions towards reducing the resulting road congestion (, and ), In , .

      Abstract

      This paper presents the motivation, design, implementation, and testing of a remotely piloted aerial system, designed to facilitate police officers processing traffic collisions. A drone remotely controlled by the police officer can reach faster the accident scene and act as the police officer's eye, ear, and voice in the sky. A complete system prototype has been constructed and tested to validate the proposed system. The results show that the system performance is promising in terms of system functionality, safety, and cost.


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    19. Household CO2-efficient energy management ( and ), In Energy Informatics, Springer, .

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    20. Mining Sequential Patterns for Appliance Usage Prediction (, , , and ), In International Conference on Smart Cities and Green ICT Systems, .

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    21. Modeling 911 emergency events in Cuenca-Ecuador using geo-spatial data (, , and ), In International Conference on Technology Trends, .

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    22. LOD-GF: an integral linked open data generation framework (, , , , , and ), In Conference on Information Technologies and Communication of Ecuador, .

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    23. Robustness of reconfigurable complex systems by a multi-agent simulation: Application on power distribution systems (, , , and ), In 2018 Annual IEEE International Systems Conference (SysCon), .

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    2017


    1. two bestsellers (), Saccargia Holding BV Publisher, .

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

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

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

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

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

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    7. 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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    8. 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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    9. Semantic web and augmented reality for searching people, events and points of interest within of a university campus (, , and ), In 2017 XLIII Latin American Computer Conference (CLEI), .

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    10. Tv program recommender using user authentication on middleware ginga (, , , and ), In 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM), .

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    11. Runtime Modifications of Spark Data Processing Pipelines (, , , and ), In 2017 International Conference on Cloud and Autonomic Computing, ICCAC, .

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      url
    12. Automated compliance verification of business processes in Apromore (, and ), In Proceedings of the BPM Demo Track 2017, .

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    13. Methodological guidelines for publishing library data as linked data (, , , , and ), In 2017 International Conference on Information Systems and Computer Science (INCISCOS), .

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    14. Cloud Ready Applications Composed via HTN Planning (, , and ), In IEEE International Conference on Service Oriented Computing and Applications, .

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    15. iTrack: A residential energy monitoring system tailored to meet local needs (, , , , and ), In , .

      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.


      BibTeX



      doi
    16. Tracing back the chain: Cognitive pre-requisite analysis for CIS capstone project ( and ), In , volume Part F1346, .

      Abstract

      © 2017 Association for Computing Machinery. When teaching the first part of the capstone project to the senior students at the College of Computer Sciences and Information Technology, some problems have been reported for the past few semesters. This paper aims to identify the cause of the problem by comparing necessary skills for the capstone project to skills acquired in prior courses, tracing back through the pre-requisite dependency chain. The comparison is set between the Course Learning Outcomes identified in the capstone project and the Course Objectives of courses offered in previous years. The analysis revealed two main discrepancies, namely: Several mismatches and missing links that explained the problems initially observed. It also led to identifying a weakness in one of the previous courses and triggered an adjustment in the course content.


      Keywords: Bloom's taxonomy, CIS capstone, Course design, Course evaluation


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      doi
    17. Post Summarization of Microblogs of Sporting Events (, , , and ), In Proceedings of the 26th International Conference on World Wide Web Companion, .

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    18. Challenges and trends about smart big geospatial data: A position paper (, and ), In 2017 IEEE International Conference on Big Data (Big Data), .

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    19. Comparison of Energy Consumption in Wi-Fi and Bluetooth Communication in a Smart Building (, , and ), In IEEE Annual Computing and Communication Workshop and Conference, .

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      url
    20. Prediction of Running Injuries from Training Load: a Machine Learning Approach (, , and ), In International Conference on eHealth, Telemedicine, and Social Medicine, .

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      url
    21. Power-Based Device Recognition for Occupancy Detection (, , and ), In Service-Oriented Computing - ICSOC 2017 Workshops, volume in press, .

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      doi

    2016


    1. A Smart Energy System for Sustainable Buildings: The Case of the Bernoulliborg (), Rijksuniversiteit Groningen, .

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      url
    2. Business Process Variability: A Study into Process Management and Verification (), Rijksuniversiteit Groningen, .

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      url
    3. 5th IFIP WG 2.14 European Conference Service-Oriented and Cloud Computing, (M. Aiello, E. B. Johnsen, S. Dustdar, I. Georgievski, eds.), Springer, volume 9846, .

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

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

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

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

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

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

      BibTeX



      url
    12. 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.


      BibTeX



      doi
    13. 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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    14. 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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    15. Sentiment Classification of Tweets using Hierarchical Classification (, , , and ), In International Conference on Communications, .

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    16. Pfpsim: A programmable forwarding plane simulator (, , , , , and ), In 2016 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS), .

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    17. Power Management of Personal Computers based on User Behaviour (, , and ), In International Conference on Smart Cities and Green ICT Systems, .

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    18. Benchmark Datasets for Fault Detection and Classification in Sensor Data (, , and ), In International Conference on Sensor Networks, .

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    19. Proactive ethernet congestion control based on link utilization estimation (, , , , and ), In 2016 international conference on computing, networking and communications (icnc), .

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    20. Influence Maximization in Social Networks with Genetic Algorithms ( and ), In European Conference on the Applications of Evolutionary and Bio-inspired Computation (Evo* EvoApplications), track EvoComplex: Evolutionary Algorithms and Complex Systems, .

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    21. Detecting National Political Unrest on Twitter (, , , and ), In International Conference on Communications, .

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    22. On the relationship between automation and occupants in smart buildings ( and ), In International Conference on ICT for Sustainability, .

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      url
    23. Memory-efficient string matching for intrusion detection systems using a high-precision pattern grouping algorithm (, , and ), In Proceedings of the 2016 symposium on architectures for networking and communications systems, .

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    24. A price-based approach for voltage regulation and power loss minimization for the electrical power distribution system (, and ), In 55th IEEE Conference on Decision and Control, .

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      url