Dilek Düştegör

Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand (Nahid Sultana, S. M.Zakir Hossain, Salmahamad Almuhaini and Dilek Düştegör), In Energies 2022, Vol. 15, Page 3425, Multidisciplinary Digital Publishing Institute, volume 15, 2022.
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
BibTeX

@article{Sultana2022, 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.}, author = {Nahid Sultana and S. M.Zakir Hossain and Salmahamad Almuhaini and Dilek Düştegör}, doi = {10.3390/EN15093425}, issn = {1996-1073}, issue = {9}, journal = {Energies 2022, Vol. 15, Page 3425}, keywords = {Bayesian optimization algorithm,NARX,SARIMAX,electricity demand,short,term forecast}, month = {5}, pages = {3425}, publisher = {Multidisciplinary Digital Publishing Institute}, title = {Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand}, volume = {15}, url = {https://www.mdpi.com/1996-1073/15/9/3425/htm https://www.mdpi.com/1996-1073/15/9/3425}, year = {2022}, }
url doi
Employability prediction: a survey of current approaches, research challenges and applications (Nesrine Mezhoudi, Rawan Alghamdi, Rim Aljunaid, Gomathi Krichna and Dilek Düştegör), In Journal of Ambient Intelligence and Humanized Computing, 2021.
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.
BibTeX

@article{Mezhoudi2021, 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.}, author = {Nesrine Mezhoudi and Rawan Alghamdi and Rim Aljunaid and Gomathi Krichna and Dilek Düştegör}, doi = {10.1007/s12652-021-03276-9}, issn = {18685145}, journal = {Journal of Ambient Intelligence and Humanized Computing}, title = {Employability prediction: a survey of current approaches, research challenges and applications}, year = {2021}, }
doi
Iot based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications (Farmanullah Jan, Nasro Min-Allah and Dilek Düştegör), volume 13, 2021.
Abstract
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.
BibTeX

@generic{Jan2021, abstract = {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.}, author = {Farmanullah Jan and Nasro Min-Allah and Dilek Düştegör}, doi = {10.3390/w13131729}, issn = {20734441}, issue = {13}, journal = {Water (Switzerland)}, title = {Iot based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications}, volume = {13}, year = {2021}, }
doi
Prediction of academic performance at undergraduate graduation: Course grades or grade point average? (Ahmet Emin Tatar and Dilek Düştegör), In Applied Sciences (Switzerland), volume 10, 2020.
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.
BibTeX

@article{Tatar2020, 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.}, author = {Ahmet Emin Tatar and Dilek Düştegör}, doi = {10.3390/app10144967}, issn = {20763417}, issue = {14}, journal = {Applied Sciences (Switzerland)}, title = {Prediction of academic performance at undergraduate graduation: Course grades or grade point average?}, volume = {10}, year = {2020}, }
doi
Predicting academic success in higher education: literature review and best practices (E. Alyahyan and D. Düştegör), In International Journal of Educational Technology in Higher Education, volume 17, 2020.
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
BibTeX

@article{Alyahyan2020, 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.}, author = {E. Alyahyan and D. Düştegör}, doi = {10.1186/s41239-020-0177-7}, issn = {23659440}, issue = {1}, journal = {International Journal of Educational Technology in Higher Education}, keywords = {Data mining,Guidelines,Higher education,Prediction,Review,Student success}, title = {Predicting academic success in higher education: literature review and best practices}, volume = {17}, year = {2020}, }
doi
Analytical tool for the modelling and simulation of curriculum: Towards automated design, assessment, and improvement (D. Düştegör), In International Journal of Engineering Education, volume 35, 2019.
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
BibTeX

@article{Dustegor2019, 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.}, author = {D. Düştegör}, issn = {0949149X}, issue = {2}, journal = {International Journal of Engineering Education}, keywords = {Accreditation,Automated tool,Curriculum design,Curriculum development,Engineering education,Quality assurance}, title = {Analytical tool for the modelling and simulation of curriculum: Towards automated design, assessment, and improvement}, volume = {35}, year = {2019}, }
Fostering higher cognitive skills through design thinking in digital hardware course: A case study (D. Düştegör, M. Farooqui and M.A. Alam Khan), In ICIC Express Letters, volume 13, 2019.
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
BibTeX

@article{Dustegor2019b, 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.}, author = {D. Düştegör and M. Farooqui and M.A. Alam Khan}, doi = {10.24507/icicel.13.10.891}, issn = {1881803X}, issue = {10}, journal = {ICIC Express Letters}, keywords = {Analysis,Continuous quality improvement,Design,Design Thinking,Digital Logic,Higherorder cognitive skills,Student learning outcomes}, title = {Fostering higher cognitive skills through design thinking in digital hardware course: A case study}, volume = {13}, year = {2019}, }
doi
Learning behind glass walls: learning style and partition-room, is there a correlation? (D. Düştegör, M.A. Elhussein, A. Alghamdi and N. Nagy), In International Journal of Innovation Science, 2018.
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
BibTeX

@article{Dustegor2018, 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.}, author = {D. Düştegör and M.A. Elhussein and A. Alghamdi and N. Nagy}, doi = {10.1108/IJIS-09-2017-0100}, issn = {17572231}, journal = {International Journal of Innovation Science}, keywords = {Cultural specific education,Educational technology,Female education,Learning environment,Partition room,Saudi education,Technology efficacy}, title = {Learning behind glass walls: learning style and partition-room, is there a correlation?}, year = {2018}, }
doi
A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications (D. Düştegör, N. Sultana, N. Felemban and D. Al Qahtani), In Utilities Policy, volume 50, 2018.
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
BibTeX

@article{Dustegor2018b, 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.}, author = {D. Düştegör and N. Sultana and N. Felemban and D. Al Qahtani}, doi = {10.1016/j.jup.2017.09.009}, issn = {09571787}, journal = {Utilities Policy}, keywords = {Kingdom of Saudi Arabia,Renewable energy,Residential area,Smart grid,Smart metering,Social acceptance,Solar energy}, title = {A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications}, volume = {50}, year = {2018}, }
doi
The impact of digital technology on female students' learning experience in partition-rooms: Conditioned by social context (Mariam A. Elhussein, Dilek Düştegör, Naya Nagy and Amani K.Hamdan Alghamdi), In IEEE Transactions on Education, volume 61, 2018.
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.
BibTeX

@article{Elhussein2018, 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.}, author = {Mariam A. Elhussein and Dilek Düştegör and Naya Nagy and Amani K.Hamdan Alghamdi}, doi = {10.1109/TE.2018.2840501}, issn = {00189359}, issue = {4}, journal = {IEEE Transactions on Education}, title = {The impact of digital technology on female students' learning experience in partition-rooms: Conditioned by social context}, volume = {61}, year = {2018}, }
doi
A remotely piloted aerial system for a faster processing of traffic collisions towards reducing the resulting road congestion (Hager Sameh, Kulthoom Aiman and Dilek Düştegör), In , 2018.
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.
BibTeX

@inproceedings{Sameh2018, 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.}, author = {Hager Sameh and Kulthoom Aiman and Dilek Düştegör}, doi = {10.1109/IEEEGCC.2017.8447915}, journal = {2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017}, title = {A remotely piloted aerial system for a faster processing of traffic collisions towards reducing the resulting road congestion}, year = {2018}, }
doi
iTrack: A residential energy monitoring system tailored to meet local needs (Khadijah Alsafwan, Fatimah Alshaer, Lolah Hakami, Khawlah Aseeri, Masoumah Aljishi and Dilek Düştegör), In , 2017.
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

@inproceedings{Alsafwan2017, 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.}, author = {Khadijah Alsafwan and Fatimah Alshaer and Lolah Hakami and Khawlah Aseeri and Masoumah Aljishi and Dilek Düştegör}, doi = {10.1109/econf.2015.7858256}, title = {iTrack: A residential energy monitoring system tailored to meet local needs}, year = {2017}, }
doi
Tracing back the chain: Cognitive pre-requisite analysis for CIS capstone project (M. Elhussein and D. Düştegör), In , volume Part F1346, 2017.
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
BibTeX

@inproceedings{Elhussein2017, 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.}, author = {M. Elhussein and D. Düştegör}, doi = {10.1145/3175536.3175537}, isbn = {9781450354356}, journal = {ACM International Conference Proceeding Series}, keywords = {Bloom's taxonomy,CIS capstone,Course design,Course evaluation}, title = {Tracing back the chain: Cognitive pre-requisite analysis for CIS capstone project}, volume = {Part F1346}, year = {2017}, }
doi
Design and implementation of a residential energy monitoring system prototype tailored to meet local needs (Khadijah AlSafwan, Fatimah AlShaer, Lolah Hakami, Khawlah Aseeri, Masoumah AlJishi and Dilek Düştegör), In International Journal of Computing and Digital Systems, volume 5, 2016.
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

@article{AlSafwan2016, 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.}, author = {Khadijah AlSafwan and Fatimah AlShaer and Lolah Hakami and Khawlah Aseeri and Masoumah AlJishi and Dilek Düştegör}, doi = {10.12785/IJCDS/050405}, issn = {2210142X}, issue = {4}, journal = {International Journal of Computing and Digital Systems}, title = {Design and implementation of a residential energy monitoring system prototype tailored to meet local needs}, volume = {5}, year = {2016}, }
doi
Public acceptance of renewable energy and Smart-Grid in Saudi Arabia (D. Düştegör, N. Sultana, N. Felemban and D. Al-Qahtani), In , 2015.
Abstract
© 2015 IEEE. This study aims to measure the public's knowledge about renewable energy sources, their willingness to use solar energy as a main source in their households, and to understand their main motivation in undergoing (or not) such an energy shift; hence, potential influencing factors that will help win public support can be determined. A survey is tailored in order to capture relevant public belief, perception, and planned behavior, then a descriptive analysis of the data is performed to examine the associations between the willingness to use solar panels in households and the other explanatory variables. Initial results show that government policies and subsidies are main factors affecting the desire to adopt green energy. These results will help overcome obstacles that might be faced prior or during a transition to the Smart-Grid, especially in residential area.

Keywords: Kingdom of Saudi Arabia, Renewable Energy, Residential Area, Social Acceptance, Solar Energy, Willingness to Pay
BibTeX

@inproceedings{Dustegor2015, abstract = {© 2015 IEEE. This study aims to measure the public's knowledge about renewable energy sources, their willingness to use solar energy as a main source in their households, and to understand their main motivation in undergoing (or not) such an energy shift; hence, potential influencing factors that will help win public support can be determined. A survey is tailored in order to capture relevant public belief, perception, and planned behavior, then a descriptive analysis of the data is performed to examine the associations between the willingness to use solar panels in households and the other explanatory variables. Initial results show that government policies and subsidies are main factors affecting the desire to adopt green energy. These results will help overcome obstacles that might be faced prior or during a transition to the Smart-Grid, especially in residential area.}, author = {D. Düştegör and N. Sultana and N. Felemban and D. Al-Qahtani}, doi = {10.1109/IEEEGCC.2015.7060018}, isbn = {9781479984220}, journal = {2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015}, keywords = {Kingdom of Saudi Arabia,Renewable Energy,Residential Area,Social Acceptance,Solar Energy,Willingness to Pay}, title = {Public acceptance of renewable energy and Smart-Grid in Saudi Arabia}, year = {2015}, }
doi
Wireless sensor network based monitoring system for photovoltaic panels in extreme GCC climate conditions: A literature review of current approaches (D. Düştegör and N.M. Felemban), In , 2013.
Abstract
Photovoltaic system performance highly depends on environmental conditions. Hence system requirements to optimize energy yield are unique, and in most cases no relevant data are available to make implementation decisions. This is why monitoring of such systems is very essential for initial system evaluation, and continuous output optimization. This paper is the result of a thorough literature survey about existing performance monitoring system for photovoltaic panels, aiming to propose a system tailored for photovoltaic panels under the very particular environmental conditions experienced in the GCC region, as these countries are in an area with tremendous potential for development of solar energy projects. A wireless sensor network based monitoring system is proposed, that measures data relevant for desert climate like dust, temperature and humidity. A small-scale prototype is described, along with initial experimental results. © 2013 IEEE.

Keywords: PV panels, Renewable energy, monitoring system, wireless sensor network
BibTeX

@inproceedings{Dustegor2013, abstract = {Photovoltaic system performance highly depends on environmental conditions. Hence system requirements to optimize energy yield are unique, and in most cases no relevant data are available to make implementation decisions. This is why monitoring of such systems is very essential for initial system evaluation, and continuous output optimization. This paper is the result of a thorough literature survey about existing performance monitoring system for photovoltaic panels, aiming to propose a system tailored for photovoltaic panels under the very particular environmental conditions experienced in the GCC region, as these countries are in an area with tremendous potential for development of solar energy projects. A wireless sensor network based monitoring system is proposed, that measures data relevant for desert climate like dust, temperature and humidity. A small-scale prototype is described, along with initial experimental results. © 2013 IEEE.}, author = {D. Düştegör and N.M. Felemban}, doi = {10.1109/IEEEGCC.2013.6705798}, isbn = {9781479907243}, journal = {2013 7th IEEE GCC Conference and Exhibition, GCC 2013}, keywords = {PV panels,Renewable energy,monitoring system,wireless sensor network}, title = {Wireless sensor network based monitoring system for photovoltaic panels in extreme GCC climate conditions: A literature review of current approaches}, year = {2013}, }
doi
An agent-based wide area protection scheme for self-healing grids (D. Düştegör), In , 2011.
Abstract
This paper presents a wide area protection multi-agent system with high degree of tolerance to faults. Agents in this protection system detect and locate faults by comparing current measurements across the protected component following principles of conventional differential protection; yet they perform sensor data integrity evaluation through a trip confirmation mechanism, by cooperating and collaborating with neighbor agents. This mechanism prevent from possible false trips caused by measurement failure or a failure of communication channel, resulting in explicit sensor failure detection and location. A missing sensor restoration mechanism is initiated to mitigate the effects of sensor failure, applying a self-healing strategy. The principles of cooperation and collaboration are presented, and the structure and hierarchy of protection agents are designed. © 2011 IEEE.

Keywords: Distributed Energy Resources, Distributed-Intelligence, Fault Detection, Location and Isolation, Multi-Agent System, Self-Healing, Wide-Area Protection
BibTeX

@inproceedings{Dustegor2011d, abstract = {This paper presents a wide area protection multi-agent system with high degree of tolerance to faults. Agents in this protection system detect and locate faults by comparing current measurements across the protected component following principles of conventional differential protection; yet they perform sensor data integrity evaluation through a trip confirmation mechanism, by cooperating and collaborating with neighbor agents. This mechanism prevent from possible false trips caused by measurement failure or a failure of communication channel, resulting in explicit sensor failure detection and location. A missing sensor restoration mechanism is initiated to mitigate the effects of sensor failure, applying a self-healing strategy. The principles of cooperation and collaboration are presented, and the structure and hierarchy of protection agents are designed. © 2011 IEEE.}, author = {D. Düştegör}, doi = {10.1109/ISGT-MidEast.2011.6220803}, isbn = {9781467309875}, journal = {2011 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East, ISGT Middle East 2011}, keywords = {Distributed Energy Resources,Distributed-Intelligence,Fault Detection,Location and Isolation,Multi-Agent System,Self-Healing,Wide-Area Protection}, title = {An agent-based wide area protection scheme for self-healing grids}, year = {2011}, }
doi
A distributed fault protection method for power grid with high penetration of renewable energy sources (D. Düştegör, T. El Mezyani and S.K. Srivastava), In , 2011.
Abstract
This study addresses the fault protection issues that will be caused by the increased penetration of Renewable Energy Sources (RES). A new Distributed Wide Area Differential Protection (DWADP) scheme is proposed to overcome these problems, and hence to improve reliability of power systems. Tools of intelligence are integrated at the relay level, capable of generating optimal responses, based on communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. The proposed DWADP scheme contains a conventional differential protection scheme cascaded with a trip confirmation mechanism (TCM), which performs sensor data integrity evaluation, and a missing sensor restoration mechanism (MSRM). Hence, false trip can be avoided, while locating sensor failures, thus making it possible to take preventive action. © 2011 IEEE.

Keywords: Fault Location, Fault Tolerance, Power System Protection, Renewable Energy Sources
BibTeX

@inproceedings{Dustegor2011b, abstract = {This study addresses the fault protection issues that will be caused by the increased penetration of Renewable Energy Sources (RES). A new Distributed Wide Area Differential Protection (DWADP) scheme is proposed to overcome these problems, and hence to improve reliability of power systems. Tools of intelligence are integrated at the relay level, capable of generating optimal responses, based on communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. The proposed DWADP scheme contains a conventional differential protection scheme cascaded with a trip confirmation mechanism (TCM), which performs sensor data integrity evaluation, and a missing sensor restoration mechanism (MSRM). Hence, false trip can be avoided, while locating sensor failures, thus making it possible to take preventive action. © 2011 IEEE.}, author = {D. Düştegör and T. El Mezyani and S.K. Srivastava}, doi = {10.1109/SmartGridComm.2011.6102386}, isbn = {9781457717024}, journal = {2011 IEEE International Conference on Smart Grid Communications, SmartGridComm 2011}, keywords = {Fault Location,Fault Tolerance,Power System Protection,Renewable Energy Sources}, title = {A distributed fault protection method for power grid with high penetration of renewable energy sources}, year = {2011}, }
doi
A sensor failure resilience metric for ship-board power system (D. Düştegör, T.E. Mezyani and P.G. McLaren), In , 2011.
Abstract
This study defines a metric of resilience to sensor faults for ship-board power system. Hence, one is able to compare different power system topology with respect to their robustness to sensor faults, which provides valuable information in the design phase. For a given power system topology, we first present a distributed wide area differential protection (DWAPS) scheme, that is able to cope with the difficulties caused by short cables used to connect the various busbars on board. The proposed scheme is an elaboration of previous studies yet integrates tools of intelligence at the relay level based on a communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. We then demonstrate how to explicitly reconstruct lost data after sensor failure. Finally, we define the minimum number of sensor that makes this restoration possible as sensor failure resilience metric. © 2011 IEEE.
BibTeX

@inproceedings{Dustegor2011c, abstract = {This study defines a metric of resilience to sensor faults for ship-board power system. Hence, one is able to compare different power system topology with respect to their robustness to sensor faults, which provides valuable information in the design phase. For a given power system topology, we first present a distributed wide area differential protection (DWAPS) scheme, that is able to cope with the difficulties caused by short cables used to connect the various busbars on board. The proposed scheme is an elaboration of previous studies yet integrates tools of intelligence at the relay level based on a communication with direct neighbors only, instead of a system wide communication, thus minimizing both the required bandwidth and the degree of connectivity between different relays. We then demonstrate how to explicitly reconstruct lost data after sensor failure. Finally, we define the minimum number of sensor that makes this restoration possible as sensor failure resilience metric. © 2011 IEEE.}, author = {D. Düştegör and T.E. Mezyani and P.G. McLaren}, doi = {10.1109/ESTS.2011.5770874}, isbn = {9781424492725}, journal = {2011 IEEE Electric Ship Technologies Symposium, ESTS 2011}, title = {A sensor failure resilience metric for ship-board power system}, year = {2011}, }
doi
Sensor optimization and placement for enhanced power system monitoring using entropy (T. El-Mezyani, S.K. Srivastava, D.A. Cartes and D. Düştegör), In , 2011.
Abstract
In this paper we propose a new methodology for sensor optimization and placement in a power system. The objectives of this study are to identify basic concepts on sensor optimization and placements to enhance the reliability and for efficient sensor data collection, processing, and transmission. Two approaches based on automatic control and information theory have been proposed. Condition of observability and fault detectability and isolability is developed to determine the optimal number of sensors and to determine the set of candidate sensors necessary for state estimation and fault detection and isolation. An entropy-based heuristic is proposed for the selection of the best sensors candidate that increases the information gain, thereby decreasing the drawback of system complexity and information uncertainty. © 2011 IEEE.
BibTeX

@inproceedings{Dustegor2011, abstract = {In this paper we propose a new methodology for sensor optimization and placement in a power system. The objectives of this study are to identify basic concepts on sensor optimization and placements to enhance the reliability and for efficient sensor data collection, processing, and transmission. Two approaches based on automatic control and information theory have been proposed. Condition of observability and fault detectability and isolability is developed to determine the optimal number of sensors and to determine the set of candidate sensors necessary for state estimation and fault detection and isolation. An entropy-based heuristic is proposed for the selection of the best sensors candidate that increases the information gain, thereby decreasing the drawback of system complexity and information uncertainty. © 2011 IEEE.}, author = {T. El-Mezyani and S.K. Srivastava and D.A. Cartes and D. Düştegör}, doi = {10.1109/ESTS.2011.5770864}, isbn = {9781424492725}, journal = {2011 IEEE Electric Ship Technologies Symposium, ESTS 2011}, title = {Sensor optimization and placement for enhanced power system monitoring using entropy}, year = {2011}, }
doi
Automated graph-based methodology for fault detection and location in power systems (D. Düştegör, S.V. Poroseva, M.Y. Hussaini and S. Woodruff), In IEEE Transactions on Power Delivery, volume 25, 2010.
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
BibTeX

@article{Dustegor2010b, 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.}, author = {D. Düştegör and S.V. Poroseva and M.Y. Hussaini and S. Woodruff}, doi = {10.1109/TPWRD.2009.2037005}, issn = {08858977}, issue = {2}, journal = {IEEE Transactions on Power Delivery}, keywords = {Fault diagnosis,Power system protection,Structural analysis,Wide-area protection}, title = {Automated graph-based methodology for fault detection and location in power systems}, volume = {25}, year = {2010}, }
doi
Parity space approach for enhanced fault detection and intelligent sensor network design in power systems (T. El-Mezyani, D. Düştegör, S.K. Srivastava and D.A. Cartes), In , 2010.
Abstract
In this study, the model-based fault detection and isolation (FDI) approach of parity-space is adapted to the diagnosis of sensor faults in power systems. Hardware redundancy is conventionally utilized to overcome this problem. However, this is an expensive solution. Instead, we propose to detect and locate faults by the systematic use of the system's analytical redundancy, with a global view of the system. This redundancy can be used to detect and isolate sensor failure as well. We also give necessary and sufficient conditions for a sensor network to be able detect faults, sensor failures included. Hence, the sensor configuration problem boils down to an optimization problem that can be intelligently guided by our method. The principle of parity-space approach is described in detail and illustrated on a simple power system model. The method is then validated through simulation. ©2010 IEEE.

Keywords: Fault diagnosis, Power system protection, Sensor, Wide-Area protection
BibTeX

@inproceedings{Dustegor2010, abstract = {In this study, the model-based fault detection and isolation (FDI) approach of parity-space is adapted to the diagnosis of sensor faults in power systems. Hardware redundancy is conventionally utilized to overcome this problem. However, this is an expensive solution. Instead, we propose to detect and locate faults by the systematic use of the system's analytical redundancy, with a global view of the system. This redundancy can be used to detect and isolate sensor failure as well. We also give necessary and sufficient conditions for a sensor network to be able detect faults, sensor failures included. Hence, the sensor configuration problem boils down to an optimization problem that can be intelligently guided by our method. The principle of parity-space approach is described in detail and illustrated on a simple power system model. The method is then validated through simulation. ©2010 IEEE.}, author = {T. El-Mezyani and D. Düştegör and S.K. Srivastava and D.A. Cartes}, doi = {10.1109/PES.2010.5590102}, isbn = {9781424483570}, journal = {IEEE PES General Meeting, PES 2010}, keywords = {Fault diagnosis,Power system protection,Sensor,Wide-Area protection}, title = {Parity space approach for enhanced fault detection and intelligent sensor network design in power systems}, year = {2010}, }
doi
Fault diagnosis of a water for injection system using enhanced structural isolation (M. Laursen, M. Blanke and D. Düştegör), In International Journal of Applied Mathematics and Computer Science, volume 18, 2008.
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
BibTeX

@article{Laursen2008, 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.}, author = {M. Laursen and M. Blanke and D. Düştegör}, doi = {10.2478/v10006-008-0052-5}, issn = {1641876X}, issue = {4}, journal = {International Journal of Applied Mathematics and Computer Science}, keywords = {Fault diagnosis,Fault isolation,Matching,Structural analysis}, title = {Fault diagnosis of a water for injection system using enhanced structural isolation}, volume = {18}, year = {2008}, }
doi
Structural analysis for assessment of monitoring possibilities: Application to simple power system topologies (D. Düştegör, S.V. Poroseva, M.Y. Hussaini and S.L. Woodruff), In , 2008.
Abstract
Any power system, either an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the possibility of detecting faults and isolating them from each other, i.e., on the monitoring potential of the system. The area of power system engineering that is concerned with the fault detection and isolation is called protection. As power systems becoming more and more complex, current standards for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach used in power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that open up to isolate a fault (short circuit). Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so they open up in a desired sequence. Wide-area (global) protection is a new research direction. Wide-area protection schemes provide protection at more unified, global level than local protection schemes, and often operate as a backup level of protection. However, these schemes are usually developed manually, that is, the arrangement of protective actions within areas are made by hand, following heuristic considerations. More systematic and automated approaches are required for successful wide-area protection of larger systems. The objective of the current study is to adapt the model-based fault detection and isolation approach based on structural analysis to power systems in order to evaluate the monitoring potential of a given power system topology (architecture) in a systematic and automated manner. A new methodology is applied to evaluate the monitoring potential of a few simple topologies. © 2008 IEEE.

Keywords: Fault detection and isolation, Power systems, Protection algorithms, Structural analysis
BibTeX

@inproceedings{Dustegor20108b, abstract = {Any power system, either an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the possibility of detecting faults and isolating them from each other, i.e., on the monitoring potential of the system. The area of power system engineering that is concerned with the fault detection and isolation is called protection. As power systems becoming more and more complex, current standards for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach used in power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that open up to isolate a fault (short circuit). Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so they open up in a desired sequence. Wide-area (global) protection is a new research direction. Wide-area protection schemes provide protection at more unified, global level than local protection schemes, and often operate as a backup level of protection. However, these schemes are usually developed manually, that is, the arrangement of protective actions within areas are made by hand, following heuristic considerations. More systematic and automated approaches are required for successful wide-area protection of larger systems. The objective of the current study is to adapt the model-based fault detection and isolation approach based on structural analysis to power systems in order to evaluate the monitoring potential of a given power system topology (architecture) in a systematic and automated manner. A new methodology is applied to evaluate the monitoring potential of a few simple topologies. © 2008 IEEE.}, author = {D. Düştegör and S.V. Poroseva and M.Y. Hussaini and S.L. Woodruff}, doi = {10.1109/PES.2008.4596702}, isbn = {9781424419067}, journal = {IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES}, keywords = {Fault detection and isolation,Power systems,Protection algorithms,Structural analysis}, title = {Structural analysis for assessment of monitoring possibilities: Application to simple power system topologies}, year = {2008}, }
doi
A new methodology for automated assessment of fault detection and isolation possibilities in large power systems (D. Düştegör, S.V. Poroseva, M.Y. Hussaini and S.L. Woodruff), In , 2008.
Abstract
Any power system, whether an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the monitoring possibilities of the system. The area of power system engineering that is concerned with fault detection and isolation is called protection. As power systems become more complex, current methods for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach for power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that can open in order to isolate a fault. Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so that they open in a desired sequence. Wide-area protection is a new research direction that provides protection at a more unified level, and often operates as a backup level of protection. However, these schemes are usually developed manually following heuristic considerations. This study proposes a new methodology based on the structural analysis of control theory, and provides the possibility of a systematic and automated approach to global power-system protection. © 2008 SIMULATION COUNCILS, INC.

Keywords: Fault detection and isolation, Power systems, Protection algorithms, Structural analysis
BibTeX

@inproceedings{Dustegor2008, abstract = {Any power system, whether an integrated power system in an all-electric ship or a utility power system, needs to be highly reliable. Reliability of a complex system strongly depends on the monitoring possibilities of the system. The area of power system engineering that is concerned with fault detection and isolation is called protection. As power systems become more complex, current methods for their protection should be adjusted accordingly to meet the challenges associated with increased system complexity. The standard approach for power system protection is local, that is, current and voltage sensors are placed at or near individual breakers that can open in order to isolate a fault. Coordination between breakers is achieved indirectly by setting the voltage or current trip points of the breakers differently so that they open in a desired sequence. Wide-area protection is a new research direction that provides protection at a more unified level, and often operates as a backup level of protection. However, these schemes are usually developed manually following heuristic considerations. This study proposes a new methodology based on the structural analysis of control theory, and provides the possibility of a systematic and automated approach to global power-system protection. © 2008 SIMULATION COUNCILS, INC.}, author = {D. Düştegör and S.V. Poroseva and M.Y. Hussaini and S.L. Woodruff}, isbn = {9781622763603}, journal = {Grand Challenges in Modeling and Simulation Symposium 2008, GCMS 2008, Part of the 2008 Summer Simulation Multiconference, SummerSim 2008}, keywords = {Fault detection and isolation,Power systems,Protection algorithms,Structural analysis}, title = {A new methodology for automated assessment of fault detection and isolation possibilities in large power systems}, year = {2008}, }
Adaptive structural analysis for FDI design in evolving systems (D. Düştegör, V. Cocquempot and M. Staroswiecki), volume 1, 2007.
Abstract
Although structural analysis for Fault Detection and Isolation (FDI) is a well formalized method, a significant effort has still to be made concerning implementation issues and algorithmic aspects to make the method better applicable for real life industrial problems. System's evolution is one of these points to be considered. The main contribution of this chapter is an adaptive/evolutive algorithm that avoids unnecessary duplication of work by efficiently making use of already generated results. The benefit of such an adaptive algorithm is twofold. First, it enables determining structural properties and performing structural analysis efficiently when system structure changes. Second, such an algorithm is an important tool for safe system design. The chapter recalls the main steps of structural analysis for FDI, analyzes the different kinds of structure modifications that can occur, treats the constraint removal case, proposes a solution to the constraint addition case, and finally, summarizes the whole analysis. © 2007 Copyright © 2007 Elsevier Ltd All rights reserved.
BibTeX

@book{Dustegor2007, abstract = {Although structural analysis for Fault Detection and Isolation (FDI) is a well formalized method, a significant effort has still to be made concerning implementation issues and algorithmic aspects to make the method better applicable for real life industrial problems. System's evolution is one of these points to be considered. The main contribution of this chapter is an adaptive/evolutive algorithm that avoids unnecessary duplication of work by efficiently making use of already generated results. The benefit of such an adaptive algorithm is twofold. First, it enables determining structural properties and performing structural analysis efficiently when system structure changes. Second, such an algorithm is an important tool for safe system design. The chapter recalls the main steps of structural analysis for FDI, analyzes the different kinds of structure modifications that can occur, treats the constraint removal case, proposes a solution to the constraint addition case, and finally, summarizes the whole analysis. © 2007 Copyright © 2007 Elsevier Ltd All rights reserved.}, author = {D. Düştegör and V. Cocquempot and M. Staroswiecki}, doi = {10.1016/B978-008044485-7/50071-3}, isbn = {9780080444857}, journal = {Fault Detection, Supervision and Safety of Technical Processes 2006}, title = {Adaptive structural analysis for FDI design in evolving systems}, volume = {1}, year = {2007}, }
doi
Structural analysis of fault isolability in the DAMADICS benchmark (D. Düştegör, E. Frisk, V. Cocquempot, M. Krysander and M. Staroswiecki), In Control Engineering Practice, volume 14, 2006.
Abstract
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
BibTeX

@article{Dustegor2006, abstract = {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.}, author = {D. Düştegör and E. Frisk and V. Cocquempot and M. Krysander and M. Staroswiecki}, doi = {10.1016/j.conengprac.2005.04.008}, issn = {09670661}, issue = {6 SPEC. ISS.}, journal = {Control Engineering Practice}, keywords = {Fault detection and isolation,Fault modelling,Structural analysis}, title = {Structural analysis of fault isolability in the DAMADICS benchmark}, volume = {14}, year = {2006}, }
doi
Adaptive structural analysis for FDI design in evolving systems (D. Düştegör, V. Cocquempot and M. Staroswiecki), In , volume 6, 2006.
Abstract
Although structural analysis for Fault Detection and Isolation (FDI) is a well formalized method, a significant effort has still to be made concerning implementation issues and algorithmic aspects in order to make the method better applicable for real-life industrial problems. System's evolution is one of these points to be considered. The main contribution of this paper is an adaptive/evolutive algorithm that avoids unnecessary duplication of work by efficiently making use of already generated results. Copyright © 2006 IFAC.

Keywords: Adaptive algorithm, FDI, Structural analysis, System evolution
BibTeX

@inproceedings{Dustegor206b, abstract = {Although structural analysis for Fault Detection and Isolation (FDI) is a well formalized method, a significant effort has still to be made concerning implementation issues and algorithmic aspects in order to make the method better applicable for real-life industrial problems. System's evolution is one of these points to be considered. The main contribution of this paper is an adaptive/evolutive algorithm that avoids unnecessary duplication of work by efficiently making use of already generated results. Copyright © 2006 IFAC.}, author = {D. Düştegör and V. Cocquempot and M. Staroswiecki}, isbn = {9783902661142}, issn = {14746670}, issue = {PART 1}, journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)}, keywords = {Adaptive algorithm,FDI,Structural analysis,System evolution}, title = {Adaptive structural analysis for FDI design in evolving systems}, volume = {6}, year = {2006}, }
Structural isolability of faults and breakdowns: Application to a valve model (D. Düştegör, V. Cocquempot, M. Staroswiecki and E. Frisk), In Journal Europeen des Systemes Automatises, volume 38, 2004.
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
BibTeX

@article{Dustegor2004b, 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.}, author = {D. Düştegör and V. Cocquempot and M. Staroswiecki and E. Frisk}, issn = {12696935}, issue = {1-2}, journal = {Journal Europeen des Systemes Automatises}, keywords = {Diagnosis,Fault isolability,Modelling,Structural analysis}, title = {Structural isolability of faults and breakdowns: Application to a valve model}, volume = {38}, year = {2004}, }
Isolabilité structurelle des défaillances. Application à un modèle de vanne (Dilek Düştegör, Vincent Cocquempot, Marcel Starowiecki and Erik Frisk), In Journal Européen des Systèmes Automatisés, volume 38, 2004.
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.
BibTeX

@article{Dustegor2004, 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.}, author = {Dilek Düştegör and Vincent Cocquempot and Marcel Starowiecki and Erik Frisk}, doi = {10.3166/jesa.38.103-124}, issn = {12696935}, issue = {1-2}, journal = {Journal Européen des Systèmes Automatisés}, title = {Isolabilité structurelle des défaillances. Application à un modèle de vanne}, volume = {38}, year = {2004}, }
doi
Structural analysis for residual generation: Towards implementation (D. Düştegör, V. Cocquempot and M. Staroswiecki), In , volume 2, 2004.
Abstract
In that paper an innovative way of dealing with the generation of residuals for fault-detection and isolation based on structural information is presented. The developed technique considers implementation issues therefore it has a more realistic point of view compared to classical structural approaches. First practical issues that can be encountered such as computational complexity or implementation considerations are introduced. Then the way of incorporating them to the existing structural analysis framework is explained. Finally, we show how the Stable Marriage Problem can be successfully adapted in order to choose the most suited matching that leads to residual computational sequences. The algorithm has been implemented and tested using a real life benchmark model: the Damadics valve © 2004 IEEE.
BibTeX

@inproceedings{Dustegor204c, abstract = {In that paper an innovative way of dealing with the generation of residuals for fault-detection and isolation based on structural information is presented. The developed technique considers implementation issues therefore it has a more realistic point of view compared to classical structural approaches. First practical issues that can be encountered such as computational complexity or implementation considerations are introduced. Then the way of incorporating them to the existing structural analysis framework is explained. Finally, we show how the Stable Marriage Problem can be successfully adapted in order to choose the most suited matching that leads to residual computational sequences. The algorithm has been implemented and tested using a real life benchmark model: the Damadics valve © 2004 IEEE.}, author = {D. Düştegör and V. Cocquempot and M. Staroswiecki}, journal = {Proceedings of the IEEE International Conference on Control Applications}, title = {Structural analysis for residual generation: Towards implementation}, volume = {2}, year = {2004}, }
Improving fault isolability properties by structural analysis of faulty behavior models: Application to the damadics benchmark problem (Erik Frisk, Dilek Düştegör, Mattias Krysander and Vincent Cocquempot), In , volume 36, 2003.
Abstract
Structural analysis is a powerful tool for early determination of detectability/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 that need further modeling to get desired isolability properties of the diagnosis system.
BibTeX

@inproceedings{Frisk2003, abstract = {Structural analysis is a powerful tool for early determination of detectability/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 that need further modeling to get desired isolability properties of the diagnosis system.}, author = {Erik Frisk and Dilek Düştegör and Mattias Krysander and Vincent Cocquempot}, doi = {10.1016/S1474-6670(17)36641-7}, issn = {14746670}, issue = {5}, journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)}, title = {Improving fault isolability properties by structural analysis of faulty behavior models: Application to the damadics benchmark problem}, volume = {36}, year = {2003}, }
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