Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932896
Konstantina Maidatsi, E. Christopoulou, Konstantinos Oikonomou
In this literature review we aim to study the integration of sustainability and environmental education into the STEM education. The study’s key ideas center on STEM education with a focus on environmental and sustainability issues (EE). This literature review starts with a summary of the knowledge base of the factors that influence the quality of STEM Education and of the ways that recent studies designed STEM projects to address development issues in teaching. Moreover, we present the factors that affect education for sustainability, with focus on Environmental Education, and recent published studies that explore and assess the ESD and STEM education. Empirical studies that focuses in the design and enhancement of teaching and learning in order to connect knowledge achievement competences and important pedagogical approaches in STEM domains through ESD are also examined. Furthermore, this study explores and identifies major trends of IoT technology integration, its relevant applications and various examples that have already been suggested and how to equip students and teachers with knowledge skills essential for their future.
{"title":"Using STEM Learning Concepts with IoT Technology on the Road of Education for Sustainability: A Short Literature Review","authors":"Konstantina Maidatsi, E. Christopoulou, Konstantinos Oikonomou","doi":"10.1109/SEEDA-CECNSM57760.2022.9932896","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932896","url":null,"abstract":"In this literature review we aim to study the integration of sustainability and environmental education into the STEM education. The study’s key ideas center on STEM education with a focus on environmental and sustainability issues (EE). This literature review starts with a summary of the knowledge base of the factors that influence the quality of STEM Education and of the ways that recent studies designed STEM projects to address development issues in teaching. Moreover, we present the factors that affect education for sustainability, with focus on Environmental Education, and recent published studies that explore and assess the ESD and STEM education. Empirical studies that focuses in the design and enhancement of teaching and learning in order to connect knowledge achievement competences and important pedagogical approaches in STEM domains through ESD are also examined. Furthermore, this study explores and identifies major trends of IoT technology integration, its relevant applications and various examples that have already been suggested and how to equip students and teachers with knowledge skills essential for their future.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84157754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932946
Angelos Dimitsas, V. Nastos, Christos Valouxis, Christos G Gogos
The scheduling community has long been interested in educational timetabling. Particularly in academia, since timetabling dictates the day to day operation of Universities, great effort has been exercised to produce high quality schedules. Typically, timetabling problems are NP-Hard and several approaches have been tried in order to generate schedules that satisfy all stakeholders. A number of timetabling competitions have been organized through the last two decades focusing on problems stemming from educational operations. In this paper we use data from two such competitions, ITC2002 and ITC2007 about the post enrollment course timetabling problem. We propose a mathematical model that captures the problem in its entirety and we use it in order to construct feasible solutions initially, and then explore the prospect of optimization. We employ a pre-process stage that attempts to reduce the size of the model and then use an open source solver, that produces solutions in reasonable time for most of the cases. We also propose a simple decomposition of the problem in a day by day basis that can improve the initial feasible solutions.
{"title":"A mathematical formulation for constructing feasible solutions for the Post Enrollment Course Timetabling Problem","authors":"Angelos Dimitsas, V. Nastos, Christos Valouxis, Christos G Gogos","doi":"10.1109/SEEDA-CECNSM57760.2022.9932946","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932946","url":null,"abstract":"The scheduling community has long been interested in educational timetabling. Particularly in academia, since timetabling dictates the day to day operation of Universities, great effort has been exercised to produce high quality schedules. Typically, timetabling problems are NP-Hard and several approaches have been tried in order to generate schedules that satisfy all stakeholders. A number of timetabling competitions have been organized through the last two decades focusing on problems stemming from educational operations. In this paper we use data from two such competitions, ITC2002 and ITC2007 about the post enrollment course timetabling problem. We propose a mathematical model that captures the problem in its entirety and we use it in order to construct feasible solutions initially, and then explore the prospect of optimization. We employ a pre-process stage that attempts to reduce the size of the model and then use an open source solver, that produces solutions in reasonable time for most of the cases. We also propose a simple decomposition of the problem in a day by day basis that can improve the initial feasible solutions.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87056722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932975
Athanasios T. Patenidis, Eirini E. Mitsopoulou, K. Votis, D. Tzovaras
Gait analysis is a methodical study of how people move that can be applied to a range of settings, including sports, rehabilitation and clinical diagnosis. This paper describes a system for tracking the kinetic rehabilitation of hemiplegic patients with a combined use of gait analysis system and wearable devices. The concept is focused on training and extracting individualized knowledge from an intelligent information system during the patient’s stay in the rehabilitation facility. This knowledge can be utilized so that the patient may self-manage their rehabilitation regimen and monitor the improvement of their condition in their own place. Medical experts will then be able to monitor patients’ progress through a cloud-based platform.
{"title":"ISOMETRIC: An Intelligent System of Outpatient Monitoring Evaluation Towards Rehabilitation In Cloud","authors":"Athanasios T. Patenidis, Eirini E. Mitsopoulou, K. Votis, D. Tzovaras","doi":"10.1109/SEEDA-CECNSM57760.2022.9932975","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932975","url":null,"abstract":"Gait analysis is a methodical study of how people move that can be applied to a range of settings, including sports, rehabilitation and clinical diagnosis. This paper describes a system for tracking the kinetic rehabilitation of hemiplegic patients with a combined use of gait analysis system and wearable devices. The concept is focused on training and extracting individualized knowledge from an intelligent information system during the patient’s stay in the rehabilitation facility. This knowledge can be utilized so that the patient may self-manage their rehabilitation regimen and monitor the improvement of their condition in their own place. Medical experts will then be able to monitor patients’ progress through a cloud-based platform.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79108185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932947
Vasileios Karaiskos, N. Zinas, Theodosios Gkamas, I. Karolos, C. Pikridas, N. Vrettos, V. Tsioukas, Sotirios Kontogiannis
This paper presents a novel framework for Industrial maintenance. The proposition covers the three major parts of a holistic Industry 4.0 process: Digital twins representation, ubiquity, and intelligent decision support. The authors have implemented a test-bed maintenance system for the maintenance needs of the oil refinery industry. Finally, they present their implementation system capabilities of their proof of concept following their proposed framework.
{"title":"Proposed Industry 4.0 Maintenance framework for critical and demanding infrastructures and processes","authors":"Vasileios Karaiskos, N. Zinas, Theodosios Gkamas, I. Karolos, C. Pikridas, N. Vrettos, V. Tsioukas, Sotirios Kontogiannis","doi":"10.1109/SEEDA-CECNSM57760.2022.9932947","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932947","url":null,"abstract":"This paper presents a novel framework for Industrial maintenance. The proposition covers the three major parts of a holistic Industry 4.0 process: Digital twins representation, ubiquity, and intelligent decision support. The authors have implemented a test-bed maintenance system for the maintenance needs of the oil refinery industry. Finally, they present their implementation system capabilities of their proof of concept following their proposed framework.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77266486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932934
D. Amanatidis, Kyriakos Kydoniefs, Michael F. Dossis
The present work aims to lay the foundations for the development of a modern web database application for storage, retrieval, manipulation and visualisation of biological data. The application also offers a data compression service. Although the set of operational requirements will initially be small, the goal is to implement the application following a modern software development methodology, to design with a modern architecture and to rely on a modern stack of technologies, so that our application is easily maintainable and scalable in the future. The latest design patterns will be used in the construction of the application, such as microservices, the model-view-controller technique and three-tier architecture. In the above context, a prototype of the application will be developed, initially in a local development environment, but with the prospect that it will be transferred in the future to a hosting environment so that it is accessible to all.
{"title":"A gene visualising database","authors":"D. Amanatidis, Kyriakos Kydoniefs, Michael F. Dossis","doi":"10.1109/SEEDA-CECNSM57760.2022.9932934","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932934","url":null,"abstract":"The present work aims to lay the foundations for the development of a modern web database application for storage, retrieval, manipulation and visualisation of biological data. The application also offers a data compression service. Although the set of operational requirements will initially be small, the goal is to implement the application following a modern software development methodology, to design with a modern architecture and to rely on a modern stack of technologies, so that our application is easily maintainable and scalable in the future. The latest design patterns will be used in the construction of the application, such as microservices, the model-view-controller technique and three-tier architecture. In the above context, a prototype of the application will be developed, initially in a local development environment, but with the prospect that it will be transferred in the future to a hosting environment so that it is accessible to all.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76602334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932962
Anargyros Gkogkidis, Vasileios Tsoukas, A. Kakarountas
Driving under the influence of alcohol is one of the most severe and critical problems in every country throughout the world. Driving is a difficult endeavor that demands a high degree of concentration and great visual processing. A system based on the Internet of Things can be utilized to measure drivers’ alcohol level and restrict their operation of motor vehicles. This technology is affordable but has a number of disadvantages, including the requirement for an internet connection, the transfer of data to other organizations, bandwidth and latency constraints, and security concerns. TinyML is an emerging technology that can overcome the aforementioned challenges by performing machine learning models locally and delivering real-time intelligence. In this work, the possibility of developing a TinyML-based system that can detect alcohol and alert the driver was investigated. The experimental findings demonstrate a high degree of accuracy, indicating that the technology under consideration may be utilized to develop compact, intelligent, and inexpensive devices capable of detecting alcohol and alerting the driver in real-time.
{"title":"A TinyML-based Alcohol Impairment Detection System For Vehicle Accident Prevention","authors":"Anargyros Gkogkidis, Vasileios Tsoukas, A. Kakarountas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932962","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932962","url":null,"abstract":"Driving under the influence of alcohol is one of the most severe and critical problems in every country throughout the world. Driving is a difficult endeavor that demands a high degree of concentration and great visual processing. A system based on the Internet of Things can be utilized to measure drivers’ alcohol level and restrict their operation of motor vehicles. This technology is affordable but has a number of disadvantages, including the requirement for an internet connection, the transfer of data to other organizations, bandwidth and latency constraints, and security concerns. TinyML is an emerging technology that can overcome the aforementioned challenges by performing machine learning models locally and delivering real-time intelligence. In this work, the possibility of developing a TinyML-based system that can detect alcohol and alert the driver was investigated. The experimental findings demonstrate a high degree of accuracy, indicating that the technology under consideration may be utilized to develop compact, intelligent, and inexpensive devices capable of detecting alcohol and alerting the driver in real-time.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73837814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932981
Vasileios P. Rekkas, S. Sotiroudis, D. Plets, W. Joseph, S. Goudos
Visible light positioning (VLP) systems have experienced substantial revolutionary progress over the past year because they can offer great positioning accuracy without needing any additional infrastructure, as conventional radio-frequency (RF)-based systems. Received signal strength (RSS)-based VLP systems are a promising approach to many indoor positioning estimation problems, but still suffer from difficulty in providing high accuracy and reliability. A potential solution to these challenges is to combine VLP systems, and machine learning (ML) approaches to enhance the position prediction accuracy in two-dimensional (2-D) spaces, or more complex problems. In this paper, we propose a ML approach to accurately predict the 2-D indoor position of a mobile receiver (eg. an automated guided vehicles-AGV), based on the measured RSS values of 4 photodiodes (PDs) forming a star architecture. We examine and evaluate the performance of different ML learners applied to the above-described problem. The proposed ML and Neural Network (NN) methods exhibit great accuracy results in predicting the 2-D coordinates of a PD-based receiver.
{"title":"Visible Light Positioning: A Machine Learning Approach","authors":"Vasileios P. Rekkas, S. Sotiroudis, D. Plets, W. Joseph, S. Goudos","doi":"10.1109/SEEDA-CECNSM57760.2022.9932981","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932981","url":null,"abstract":"Visible light positioning (VLP) systems have experienced substantial revolutionary progress over the past year because they can offer great positioning accuracy without needing any additional infrastructure, as conventional radio-frequency (RF)-based systems. Received signal strength (RSS)-based VLP systems are a promising approach to many indoor positioning estimation problems, but still suffer from difficulty in providing high accuracy and reliability. A potential solution to these challenges is to combine VLP systems, and machine learning (ML) approaches to enhance the position prediction accuracy in two-dimensional (2-D) spaces, or more complex problems. In this paper, we propose a ML approach to accurately predict the 2-D indoor position of a mobile receiver (eg. an automated guided vehicles-AGV), based on the measured RSS values of 4 photodiodes (PDs) forming a star architecture. We examine and evaluate the performance of different ML learners applied to the above-described problem. The proposed ML and Neural Network (NN) methods exhibit great accuracy results in predicting the 2-D coordinates of a PD-based receiver.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79812338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932914
Panagiotis Gkotsiopoulos, Eleni Seralidou, C. Douligeris
Augmented Reality (AR) Technologies are gaining considerable attention due to their increased stability and reliability. Combined with the availability of smarter and cheaper devices, like smart-phones and tablets, AR technology greatly helps in enhancing the amount, relevance and ease of access of the available information. At the same pace, Internet of Things (IoT) technologies due to their pervasiveness, are paving the way towards a smarter interconnected world. Several industries, like entertainment, medicine and engineering, have developed and adapted IoT and AR technologies where the enrichment of the physical reality by the information and capabilities offered by AR proved useful for their business. The same approach should and could be the case in the education field. Nevertheless, the usage of IoT and AR technologies is still in its infancy, not following yet the path of many other industry fields. In this paper, after the presentation of contemporary AR and IoT technologies a proposal for utilizing these technologies to teach concepts that are required by the curriculum of the “Informatics Applications” course for the first class of senior high schools in Greece is presented.
{"title":"Augmented Reality and Internet of Things Trends in Education","authors":"Panagiotis Gkotsiopoulos, Eleni Seralidou, C. Douligeris","doi":"10.1109/SEEDA-CECNSM57760.2022.9932914","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932914","url":null,"abstract":"Augmented Reality (AR) Technologies are gaining considerable attention due to their increased stability and reliability. Combined with the availability of smarter and cheaper devices, like smart-phones and tablets, AR technology greatly helps in enhancing the amount, relevance and ease of access of the available information. At the same pace, Internet of Things (IoT) technologies due to their pervasiveness, are paving the way towards a smarter interconnected world. Several industries, like entertainment, medicine and engineering, have developed and adapted IoT and AR technologies where the enrichment of the physical reality by the information and capabilities offered by AR proved useful for their business. The same approach should and could be the case in the education field. Nevertheless, the usage of IoT and AR technologies is still in its infancy, not following yet the path of many other industry fields. In this paper, after the presentation of contemporary AR and IoT technologies a proposal for utilizing these technologies to teach concepts that are required by the curriculum of the “Informatics Applications” course for the first class of senior high schools in Greece is presented.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75292310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9932898
Athanasios Kanavos, Efstratios Kolovos, Orestis Papadimitriou, M. Maragoudakis
Histopathology refers to the diagnosis of tissue diseases and involves the thorough examination of tissues and cells under a microscope. Tissues are collected by biopsy and viewed under the microscope after being properly processed. Modern medical image processing techniques involve the collection of histopathological images taken under a microscope and their analysis using different algorithms and techniques. Deep Learning is widely used in the field of medical imaging as it does not require any specialized prior knowledge in the problem domain. The dataset used for our experiments comprises of histopathological scans derived from the PatchCamelyon dataset. Various Convolutional Neural Network architectures were implemented, where their hyperparameters were fine tuned and the classification results are presented. The deep learning neural networks are accessed for their worth in terms of accuracy, loss, AUC, precision, recall and time required.
{"title":"Breast Cancer Classification of Histopathological Images using Deep Convolutional Neural Networks","authors":"Athanasios Kanavos, Efstratios Kolovos, Orestis Papadimitriou, M. Maragoudakis","doi":"10.1109/SEEDA-CECNSM57760.2022.9932898","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932898","url":null,"abstract":"Histopathology refers to the diagnosis of tissue diseases and involves the thorough examination of tissues and cells under a microscope. Tissues are collected by biopsy and viewed under the microscope after being properly processed. Modern medical image processing techniques involve the collection of histopathological images taken under a microscope and their analysis using different algorithms and techniques. Deep Learning is widely used in the field of medical imaging as it does not require any specialized prior knowledge in the problem domain. The dataset used for our experiments comprises of histopathological scans derived from the PatchCamelyon dataset. Various Convolutional Neural Network architectures were implemented, where their hyperparameters were fine tuned and the classification results are presented. The deep learning neural networks are accessed for their worth in terms of accuracy, loss, AUC, precision, recall and time required.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85880433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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