计算机工程与设计最新文献_第6页

SEEDA-CECNSM 2022 Cover Page SEEDA-CECNSM 2022封面页

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/seeda-cecnsm57760.2022.9932954

引用次数: 0

Using STEM Learning Concepts with IoT Technology on the Road of Education for Sustainability: A Short Literature Review 将STEM学习概念与物联网技术应用于可持续教育之路:简短的文献综述

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932896

Konstantina Maidatsi, E. Christopoulou, Konstantinos Oikonomou

{"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":"9 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":"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}

引用次数: 0

A mathematical formulation for constructing feasible solutions for the Post Enrollment Course Timetabling Problem 建立入学后课程排课问题可行解的数学公式

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932946

Angelos Dimitsas, V. Nastos, Christos Valouxis, Christos G Gogos

{"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":"75 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":"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}

引用次数: 0

ISOMETRIC: An Intelligent System of Outpatient Monitoring Evaluation Towards Rehabilitation In Cloud ISOMETRIC:云环境下门诊康复监测评估智能系统

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932975

Athanasios T. Patenidis, Eirini E. Mitsopoulou, K. Votis, D. Tzovaras

引用次数: 0

Proposed Industry 4.0 Maintenance framework for critical and demanding infrastructures and processes 为关键和苛刻的基础设施和流程提出工业4.0维护框架

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932947

Vasileios Karaiskos, N. Zinas, Theodosios Gkamas, I. Karolos, C. Pikridas, N. Vrettos, V. Tsioukas, Sotirios Kontogiannis

引用次数: 0

A gene visualising database 基因可视化数据库

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932934

D. Amanatidis, Kyriakos Kydoniefs, Michael F. Dossis

引用次数: 0

A TinyML-based Alcohol Impairment Detection System For Vehicle Accident Prevention 基于tinyml的汽车事故预防酒精损伤检测系统

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932962

Anargyros Gkogkidis, Vasileios Tsoukas, A. Kakarountas

{"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":"24 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":"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}

引用次数: 1

Visible Light Positioning: A Machine Learning Approach 可见光定位:一种机器学习方法

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932981

Vasileios P. Rekkas, S. Sotiroudis, D. Plets, W. Joseph, S. Goudos

{"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}

引用次数: 2

Augmented Reality and Internet of Things Trends in Education 增强现实和物联网在教育中的发展趋势

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932914

Panagiotis Gkotsiopoulos, Eleni Seralidou, C. Douligeris

{"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":"23 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":"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}

引用次数: 0

Breast Cancer Classification of Histopathological Images using Deep Convolutional Neural Networks 基于深度卷积神经网络的乳腺癌组织病理图像分类

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932898

Athanasios Kanavos, Efstratios Kolovos, Orestis Papadimitriou, M. Maragoudakis

引用次数: 2