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":"15 1","pages":"1-5"},"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-CECNSM57760.2022.9932900
T. Karvounidis, Anastasios Ladias, C. Douligeris
The assessment of data in Scratch using the SOLO taxonomy is part of a broader framework for setting standards for the assessment of STEM educational projects in the Panhellenic Educational Robotics Competition of WRO-Hellas. The relevant factors of the data that are developed and studied are the forms, the types, the ways of use, the carriers, the visibility, the organization, the processing and the naming. In this work we examine the data carriers which are the “objects” with the code, the costumes and the sounds as well as the backgrounds of the stage. The data carriers are assessed through a categorization using the SOLO taxonomy. This categorization can be used by the educator as a tool with measurable criteria either to evaluate the learning outcomes that the influence of the data carriers has in the students’ code or to develop personal teaching paths, thus creating mental scaffolds that may help students to acquire new knowledge.
{"title":"Assessment of data carriers with the SOLO taxonomy in Scratch","authors":"T. Karvounidis, Anastasios Ladias, C. Douligeris","doi":"10.1109/SEEDA-CECNSM57760.2022.9932900","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932900","url":null,"abstract":"The assessment of data in Scratch using the SOLO taxonomy is part of a broader framework for setting standards for the assessment of STEM educational projects in the Panhellenic Educational Robotics Competition of WRO-Hellas. The relevant factors of the data that are developed and studied are the forms, the types, the ways of use, the carriers, the visibility, the organization, the processing and the naming. In this work we examine the data carriers which are the “objects” with the code, the costumes and the sounds as well as the backgrounds of the stage. The data carriers are assessed through a categorization using the SOLO taxonomy. This categorization can be used by the educator as a tool with measurable criteria either to evaluate the learning outcomes that the influence of the data carriers has in the students’ code or to develop personal teaching paths, thus creating mental scaffolds that may help students to acquire new knowledge.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"16 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77054478","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-CECNSM57760.2022.9932910
Evangelos Hytis, Vasileios Nastos, Christos G Gogos, Angelos Dimitsas
Firms are obliged by law to publish accurate financial statements. Nevertheless, cases exist where publicly issued documents hide the actual bad financial statuses of companies and this is revealed years later. Since companies publish financial figures periodically, it is interesting to examine whether monitoring those values or ratios based on them can help in early detection of fraud. In this work, a dataset was constructed including 943 firm-years of Greek companies enlisted at the Athens Stock Exchange, for the period 2005-2018. Experiments using combinations of financial ratios and various machine learning algorithms were undertaken in an effort to construct a system able to automatically detect false and misleading financial statements, that were issued legitimately by firms. Several instantiations of a machine learning workflow were tested using various classifier algorithms including AdaBoost, Random Forests, and others. Experiments showed that companies that issue false financial statements can be spotted automatically for most of the cases, years before the problem is manifested. So, the potential of early detection of seemingly healthy, but in fact, distressed companies do exist. An automated tool can be constructed that should be useful for financial analysts, investors and the capital markets authorities.
{"title":"Automated identification of fraudulent financial statements by analyzing data traces","authors":"Evangelos Hytis, Vasileios Nastos, Christos G Gogos, Angelos Dimitsas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932910","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932910","url":null,"abstract":"Firms are obliged by law to publish accurate financial statements. Nevertheless, cases exist where publicly issued documents hide the actual bad financial statuses of companies and this is revealed years later. Since companies publish financial figures periodically, it is interesting to examine whether monitoring those values or ratios based on them can help in early detection of fraud. In this work, a dataset was constructed including 943 firm-years of Greek companies enlisted at the Athens Stock Exchange, for the period 2005-2018. Experiments using combinations of financial ratios and various machine learning algorithms were undertaken in an effort to construct a system able to automatically detect false and misleading financial statements, that were issued legitimately by firms. Several instantiations of a machine learning workflow were tested using various classifier algorithms including AdaBoost, Random Forests, and others. Experiments showed that companies that issue false financial statements can be spotted automatically for most of the cases, years before the problem is manifested. So, the potential of early detection of seemingly healthy, but in fact, distressed companies do exist. An automated tool can be constructed that should be useful for financial analysts, investors and the capital markets authorities.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"89 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77252855","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":"71 1","pages":"1-6"},"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}
Pub Date : 2022-09-23DOI: 10.1109/SEEDA-CECNSM57760.2022.9933011
Vasiliki Fiska, Sofia Evangelou, N. Giannakeas, A. Tzallas, P. Angelidis, M. Tsipouras
Diabetes Mellitus (DM) is a metabolic disorder affecting millions of patients worldwide. Continuous glucose monitoring (CGM) is integral to managing diabetes, and when used in conjunction with closed-loop automated medication administration systems, it can considerably lower the risks of hyperglycemia in DM patients. However, such treatment frequently necessitates the use of invasive blood glucose monitoring techniques and drug infusion. Because of its unique characteristics, sweat is considered one of the most important bio-fluids utilized in non-invasive CGM applications. In order to provide patients with effective and painless DM monitoring and treatment, the architecture of a sweat-based non-invasive closed-loop system for diabetes monitoring and treatment is extensively presented.
{"title":"A non-invasive closed-loop diagnostic and therapeutic wearable device for diabetic hyperglycemia prevention: System Architecture","authors":"Vasiliki Fiska, Sofia Evangelou, N. Giannakeas, A. Tzallas, P. Angelidis, M. Tsipouras","doi":"10.1109/SEEDA-CECNSM57760.2022.9933011","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9933011","url":null,"abstract":"Diabetes Mellitus (DM) is a metabolic disorder affecting millions of patients worldwide. Continuous glucose monitoring (CGM) is integral to managing diabetes, and when used in conjunction with closed-loop automated medication administration systems, it can considerably lower the risks of hyperglycemia in DM patients. However, such treatment frequently necessitates the use of invasive blood glucose monitoring techniques and drug infusion. Because of its unique characteristics, sweat is considered one of the most important bio-fluids utilized in non-invasive CGM applications. In order to provide patients with effective and painless DM monitoring and treatment, the architecture of a sweat-based non-invasive closed-loop system for diabetes monitoring and treatment is extensively presented.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"100 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76993485","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-CECNSM57760.2022.9932944
A. Anagnostakis, N. Giannakeas, A. Tzallas, M. Tsipouras, E. Glavas
Consensus achievement is a scalable process, which relies on the mutual “Proof of something” among the consenting parties. Not every application has the same consensus needs: a classification of escalating complexity proofing cases is presented in [1], where it is proved that high complexity consensus policies can be effectively delivered on a pure P2P manner even over finite, even trivial capacity systems. The Proof of Existence (PoE) is utilized there as a minimal universal proofing case, the increased complexity of which is too high to be handled by a single atom, yet it can be delivered effectively on a collective basis. Irrespective of the undoubtable universality and soundness of PoE, it constitutes but the first and least-demanding proofing class identified. Universal consensus achievement on ownership transfer and monetary transactions requires elevated complexity proofing policies, capable of safeguarding the uniqueness of the transferred tokens as well as the finality of the transactional blockchain. In this work we present a pure P2P consensus schema for ownership transfer over finite populations. It relies on the IoT micro-Blockchain architecture which delivers a robust verifiable atomic consistency framework and facilitates the delivery of Proof of Originality-PoO and Proof of Consistency-PoC based consensus. We assert that PoO and PoC are necessary and capable to deliver robust consensus on ownership transfer transactions, and we study their traits over finite populations.
{"title":"A peer, “wallet-only” consensus schema for ownership transfer over finite populations","authors":"A. Anagnostakis, N. Giannakeas, A. Tzallas, M. Tsipouras, E. Glavas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932944","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932944","url":null,"abstract":"Consensus achievement is a scalable process, which relies on the mutual “Proof of something” among the consenting parties. Not every application has the same consensus needs: a classification of escalating complexity proofing cases is presented in [1], where it is proved that high complexity consensus policies can be effectively delivered on a pure P2P manner even over finite, even trivial capacity systems. The Proof of Existence (PoE) is utilized there as a minimal universal proofing case, the increased complexity of which is too high to be handled by a single atom, yet it can be delivered effectively on a collective basis. Irrespective of the undoubtable universality and soundness of PoE, it constitutes but the first and least-demanding proofing class identified. Universal consensus achievement on ownership transfer and monetary transactions requires elevated complexity proofing policies, capable of safeguarding the uniqueness of the transferred tokens as well as the finality of the transactional blockchain. In this work we present a pure P2P consensus schema for ownership transfer over finite populations. It relies on the IoT micro-Blockchain architecture which delivers a robust verifiable atomic consistency framework and facilitates the delivery of Proof of Originality-PoO and Proof of Consistency-PoC based consensus. We assert that PoO and PoC are necessary and capable to deliver robust consensus on ownership transfer transactions, and we study their traits over finite populations.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"15 1","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80963004","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-CECNSM57760.2022.9932937
Georgios Prapas, Kosmas Glavas, A. Tzallas, Katerina D. Tzimourta, N. Giannakeas, M. Tsipouras
Brain-computer interface (BCI) is a rapidly growing field with various applications in many domains such as medical, gaming and lifestyle. This paper presents a 3D non-invasive BCI game. Muse 2 headband is used for acquiring electroencephalogram (EEG) data and OpenViBE platform for processing the raw signals and classification. The game is developed in Unity game Engine. Several subjects are included in the study and EEG signals are recorded for three different mental states i.e. left and right Motor Imagery and eye blink, before playing the game for ten times, aiming to collect coins. Average classification result is 94.86% and average coins collected from the users is 30.8 out of 50 coins. Furthermore, longer periods of playing the game leads to increased control over the game.
{"title":"Motor Imagery Approach for BCI Game Development","authors":"Georgios Prapas, Kosmas Glavas, A. Tzallas, Katerina D. Tzimourta, N. Giannakeas, M. Tsipouras","doi":"10.1109/SEEDA-CECNSM57760.2022.9932937","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932937","url":null,"abstract":"Brain-computer interface (BCI) is a rapidly growing field with various applications in many domains such as medical, gaming and lifestyle. This paper presents a 3D non-invasive BCI game. Muse 2 headband is used for acquiring electroencephalogram (EEG) data and OpenViBE platform for processing the raw signals and classification. The game is developed in Unity game Engine. Several subjects are included in the study and EEG signals are recorded for three different mental states i.e. left and right Motor Imagery and eye blink, before playing the game for ten times, aiming to collect coins. Average classification result is 94.86% and average coins collected from the users is 30.8 out of 50 coins. Furthermore, longer periods of playing the game leads to increased control over the game.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"83 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80385742","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-CECNSM57760.2022.9933003
Antonios Pekias, George S. Maraslidis, M. Tsipouras, F. Koumboulis, G. Fragulis
Unmanned air vehicles belong to the field of aeronautics and automation. The rapid development of technology in the engineering and automation field, helped to take UAVs to the highest level. These kind of technologies were imported into the military and aviation industry, performing multiple high/low risk activities. In combination with automation technology and mechanical vision where cameras, imaging sensors, thermal, etc. were introduced, a very modern highly technological form has been created. Therefore, the user has the ability to control remotely, a plurality of functions via a controller, a mobile phone, or even a ground station cockpit in military facilities. In this study, we will be reviewing the three main characteristics of an unmanned aerial vehicle; their power source technology the deep learning neural network systems used for their computer vision, and some of the most used applications. We conclude with suggestions and future directions to overcome the challenges of optimizing operational capabilities.
{"title":"An overview of power supply technologies for Unmanned Aerial Vehicles (UAVs) and machine vision applications","authors":"Antonios Pekias, George S. Maraslidis, M. Tsipouras, F. Koumboulis, G. Fragulis","doi":"10.1109/SEEDA-CECNSM57760.2022.9933003","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9933003","url":null,"abstract":"Unmanned air vehicles belong to the field of aeronautics and automation. The rapid development of technology in the engineering and automation field, helped to take UAVs to the highest level. These kind of technologies were imported into the military and aviation industry, performing multiple high/low risk activities. In combination with automation technology and mechanical vision where cameras, imaging sensors, thermal, etc. were introduced, a very modern highly technological form has been created. Therefore, the user has the ability to control remotely, a plurality of functions via a controller, a mobile phone, or even a ground station cockpit in military facilities. In this study, we will be reviewing the three main characteristics of an unmanned aerial vehicle; their power source technology the deep learning neural network systems used for their computer vision, and some of the most used applications. We conclude with suggestions and future directions to overcome the challenges of optimizing operational capabilities.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"108 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80536065","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-CECNSM57760.2022.9932912
Christos G Gogos, Angelos Dimitsas, Christos Valouxis, P. Alefragis
In this work we present modeling and optimally solving a timetabling problem that was given as a compulsory assignment to students attending an Operations Research course. The project aimed at introducing Integer Programming in a problem that used enrollments of the students themselves to individual courses and aimed at minimizing, in a balanced manner, commute time needed for attending lessons. Students were given a problem that was familiar to them and nontrivial to be solved optimally. In the process, modern commercial and open source Integer Programming solvers were used. More importantly, modeling skills were acquired and the benefits of approaching hard problems using solvers employing exact algorithms was demonstrated.
{"title":"Modeling a balanced commute educational timetabling problem in the context of teaching Integer Programming","authors":"Christos G Gogos, Angelos Dimitsas, Christos Valouxis, P. Alefragis","doi":"10.1109/SEEDA-CECNSM57760.2022.9932912","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932912","url":null,"abstract":"In this work we present modeling and optimally solving a timetabling problem that was given as a compulsory assignment to students attending an Operations Research course. The project aimed at introducing Integer Programming in a problem that used enrollments of the students themselves to individual courses and aimed at minimizing, in a balanced manner, commute time needed for attending lessons. Students were given a problem that was familiar to them and nontrivial to be solved optimally. In the process, modern commercial and open source Integer Programming solvers were used. More importantly, modeling skills were acquired and the benefits of approaching hard problems using solvers employing exact algorithms was demonstrated.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"82 3 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81219584","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-CECNSM57760.2022.9932948
Konstantinos Sakkas, Alexandra Tsogka, N. Giannakeas, Katerina D. Tzimourta, A. Tzallas, E. Glavas
The development of Virtual Reality technologies has improved people's daily lives in many sections. Nowadays, it is applied in fields such as Health, Work, Telecommuting and in a large number of other sectors. Education from different perspectives is something that constantly concerns researchers and virtual reality developers, which is why we come across a series of virtual reality applications for situation simulation and student education. Mathematics and especially geometry which is interrelated with the concept of the implementation of applications in three-dimensional space, as well as VR applications, from the perspective of learning are often considered complicated as there are three-dimensional objects that are not easily perceived only through a book. In this paper we examine how through virtual reality geometric concepts can be better understood but at the same time to examine geometric shapes from different angles and perspectives.
{"title":"Applied Virtual Reality in 3D Geometry","authors":"Konstantinos Sakkas, Alexandra Tsogka, N. Giannakeas, Katerina D. Tzimourta, A. Tzallas, E. Glavas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932948","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932948","url":null,"abstract":"The development of Virtual Reality technologies has improved people's daily lives in many sections. Nowadays, it is applied in fields such as Health, Work, Telecommuting and in a large number of other sectors. Education from different perspectives is something that constantly concerns researchers and virtual reality developers, which is why we come across a series of virtual reality applications for situation simulation and student education. Mathematics and especially geometry which is interrelated with the concept of the implementation of applications in three-dimensional space, as well as VR applications, from the perspective of learning are often considered complicated as there are three-dimensional objects that are not easily perceived only through a book. In this paper we examine how through virtual reality geometric concepts can be better understood but at the same time to examine geometric shapes from different angles and perspectives.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"39 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76685696","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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