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2021 16th International Conference on Electronics Computer and Computation (ICECCO)最新文献

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Predicting Student Performance and Motivation in Online Education - A Survey of Current Research Trends 预测在线教育中的学生表现和动机——当前研究趋势的调查
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663780
Yerbol Baigarayev, Zhumat Abdimaulenov, Aizada Nurlanova, Birzhan Moldagaliyev
{"title":"Predicting Student Performance and Motivation in Online Education - A Survey of Current Research Trends","authors":"Yerbol Baigarayev, Zhumat Abdimaulenov, Aizada Nurlanova, Birzhan Moldagaliyev","doi":"10.1109/icecco53203.2021.9663780","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663780","url":null,"abstract":"In recent years Online Education has emerged as a complementary medium of education for students from all over the world. Though online education has seen a rise in popularity, there are still problems to be solved, such as high dropout rates. This articles reviews studies that address the problems of predicting student performance, motivation and related concepts in the context of online education. The article provides some reviews of works on student motivation, as it plays a major role in high dropout rates. Apart of reviewing the prominent works in this field, the current paper proposed new directions of research that could shed more light into the problems in this research field.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132498943","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
Question answering model construction by using transfer learning 基于迁移学习的问答模型构建
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663846
Aimoldir Aldabergen, B. Kynabay, A. Zhamanov
{"title":"Question answering model construction by using transfer learning","authors":"Aimoldir Aldabergen, B. Kynabay, A. Zhamanov","doi":"10.1109/icecco53203.2021.9663846","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663846","url":null,"abstract":"Every day there is a need for querying different kinds of data for a number of purposes and tasks. Therefore it became very important to have a tool like a Question Answering System (QAS) for information retrieving from any form of data in a quick manner. In this work a QAS which combines major fields of modern research topics: Deep Learning (DL), Natural Language Processing (NLP) and Information Technology (IT) is developed. Primary goal of this system is to provide users with an appropriate answer, based on the information that it has. Also an implementation of transfer learning on pre-trained bidirctionl nodr for question answering tasks is researched. Developed model is focused on question answering and was trained on a special Stanford dataset for QAS. The work explains the model’s structure, workflow and implementation in a detailed manner.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114063475","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
Computational model of stationary flow with integral nonlocal boundary conditions 积分非局部边界条件下稳态流动的计算模型
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663789
Altyngazy Karimov, Alexei Kavokin, Saule Kattabekova
{"title":"Computational model of stationary flow with integral nonlocal boundary conditions","authors":"Altyngazy Karimov, Alexei Kavokin, Saule Kattabekova","doi":"10.1109/icecco53203.2021.9663789","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663789","url":null,"abstract":"A finite-difference numerical method for solving the model represented by the Poisson equation with integral non-local boundary conditions is considered. The model describes the steady flow of fluid near the well under the condition of a known total flow both on the well contour and on the permeable part of the domain boundary. The model describes one of the possible situations in well-logged oil production. The problems of existence and uniqueness of the solution to this problem are discussed. Peaceman–Rachford type method used to construct a difference scheme.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133508163","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
Deep Neural Network Classification Models for COVID-19 Detection in X-ray Images x射线图像中COVID-19检测的深度神经网络分类模型
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663823
Yerkin Abdukarimov, Assanali Abu, M. Altynbekov, A. Shomanov, Seong-Jun Lee, Minho Lee
{"title":"Deep Neural Network Classification Models for COVID-19 Detection in X-ray Images","authors":"Yerkin Abdukarimov, Assanali Abu, M. Altynbekov, A. Shomanov, Seong-Jun Lee, Minho Lee","doi":"10.1109/icecco53203.2021.9663823","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663823","url":null,"abstract":"At the beginning of 2020 new COVID-19 infection became a global pandemic, and society needed an efficient method to detect infected people. To handle the spread of infection testing systems were developed. But due to the fact that they take a lot of time and are not available to everyone, alternative methods of early screening have become an urgent need. In our paper, we propose to use convolutional neural networks (CNN) to detect coronavirus infection on X-ray images. We have collected 9 of the most popular datasets containing x-ray images of patients infected with COVID-19 or pneumonia and classified on most common CNN models: ResNet50, VGG- 16, Alexnet, Inception-v3, and InceptionResNet-v2. Based on results we obtained it was possible to generate a heat map that indicates areas containing features that distinguish infected patients most effectively. Also, 2D T-SNE images were created to provide a lower dimensional overview of the data distribution among 2 classes representing infected scans vs normal scans. In our experiments, the InceptionResNet-v2 model showed best test result and the average prediction value reached 95.1%, which is a very promising accuracy for classifying healthy and infected patients.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240154","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: 5
ICECCO 2021 Reviewers
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663752
{"title":"ICECCO 2021 Reviewers","authors":"","doi":"10.1109/icecco53203.2021.9663752","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663752","url":null,"abstract":"","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132312402","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
Speech data collection system for Kazakh language 哈萨克语语音数据采集系统
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663771
Darkhan Kuanyshbay, O. Baimuratov, Y. Amirgaliyev, Arailym Kuanyshbayeva
{"title":"Speech data collection system for Kazakh language","authors":"Darkhan Kuanyshbay, O. Baimuratov, Y. Amirgaliyev, Arailym Kuanyshbayeva","doi":"10.1109/icecco53203.2021.9663771","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663771","url":null,"abstract":"Speech data in most of the languages that have a low resource doesn’t even exist. Therefore, producing speech corpora is very challenging and requires tremendous amount of time. Kazakh language due to its lack of popularity considered to be low-resource language. This paper provides an overview on many data collection techniques, marking some of the issues related to a particular method. The main aim of this paper is to present crowd sourcing web-based tool called “Kazakh recorder” which accessible on the website and designed to make the collection of Kazakh speech data more conveniently and quickly. Moreover, this section provides a statistics of people (age, gender, number of sentences) who made a contribution on collecting this speech data. Using this tool, we have collected over 50 hours of speech data 65 different native speakers, each having on average 500 sentences pronounced in Kazakh language.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130956935","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
Computer Vision Based Pre-processing of Microscopic Images 基于计算机视觉的显微图像预处理
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663812
Kurmangazy Kongratbayev, Cemil Turan, Bekzot Tursunmamatov
{"title":"Computer Vision Based Pre-processing of Microscopic Images","authors":"Kurmangazy Kongratbayev, Cemil Turan, Bekzot Tursunmamatov","doi":"10.1109/icecco53203.2021.9663812","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663812","url":null,"abstract":"Preparing the microscopic images for analyses is a crucial step for any kind of image processing task. In this paper, the methods for analyzing and processing of biomedical images are presented. The main task is to select the appropriate object images of interest for further measurement of their morphological parameters. In the article, several methods are presented such as contrast adjustment, intensity adjustment, histogram equalization, morphological operation and background subtraction that can be used in pre-processing of microscopic images.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122890131","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
Development an Intelligent Task Offloading System for Edge-Cloud Computing Paradigm 基于边缘云计算范式的智能任务卸载系统的开发
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663797
S. Atanov, Zhexen Y. Seitbattalov, Zhanar S. Moldabayeva
{"title":"Development an Intelligent Task Offloading System for Edge-Cloud Computing Paradigm","authors":"S. Atanov, Zhexen Y. Seitbattalov, Zhanar S. Moldabayeva","doi":"10.1109/icecco53203.2021.9663797","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663797","url":null,"abstract":"This paper presents a task offloading system based on fuzzy logic for Edge-Cloud servers. The designed model in the Toolbox of MATLAB focuses on collecting data, which user receives from computing network: task length, virtual machine utilization, delay sensitivity, network demand and energy consumption. The aims of the research are reducing network latency and optimizing the energy efficient of edge device. As a result designed model proposes an optimal resources and choice of computing network between cloud, fog and edge for solving task.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123402443","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: 5
Deploying Microwave Radios using Mitigation Techniques for Eluding Interference between NAN to MDMS Fragment of Smart Grid Communication Network 利用减缓技术部署微波无线电以躲避智能电网通信网络中NAN到MDMS碎片之间的干扰
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663744
Ahmed Qaddus, A. A. Minhas
{"title":"Deploying Microwave Radios using Mitigation Techniques for Eluding Interference between NAN to MDMS Fragment of Smart Grid Communication Network","authors":"Ahmed Qaddus, A. A. Minhas","doi":"10.1109/icecco53203.2021.9663744","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663744","url":null,"abstract":"In this era Science has seen a remarkable progression and rapid expansion in the field of Smart Grid infrastructure deployed in both Urban and Rural Communities. One of the key feature of Smart Grid infrastructure is Smart Grid Communication Network (SGCN). In SGCN the most cost effective and rapid deployment form of communication medium is Wireless connectivity. In this research, authors have recommended the use of unlicensed spectrum ISM band Microwave Radios in 2.4 GHz (2.402 to 2.472 GHz) and 5.8 GHz (4.910 to 5.970 GHz) as a substitute for licensed spectrum Microwave Radios between Neighborhood Area Network (NAN) to Meter Data Management System (MDMS) fragment of Smart Grid Communication Network (SGCN). In this investigation authors will discuss the shortcomings of using traditional wired connectivity in Smart Grid Communication Network (SGCN). Further authors will advise the use of Hybrid Mitigation techniques like Dynamic Frequency Selection (DFS) & Dual Polarization (DP) in Microwave radios to reduce interference to enhanced network technical operations capabilities of interconnectivity between Neighborhood Area Network (NAN) to Meter Data Management System (MDMS) fragment of Smart Grid Communication Network (SGCN).","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127519495","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
Morphological Classification of Galaxies Using SpinalNet 基于SpinalNet的星系形态分类
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/ICECCO53203.2021.9663784
Dim Shaiakhmetov, R. R. Mekuria, R. Isaev, Fatma Unsal
{"title":"Morphological Classification of Galaxies Using SpinalNet","authors":"Dim Shaiakhmetov, R. R. Mekuria, R. Isaev, Fatma Unsal","doi":"10.1109/ICECCO53203.2021.9663784","DOIUrl":"https://doi.org/10.1109/ICECCO53203.2021.9663784","url":null,"abstract":"Deep neural networks (DNNs) with a step-by-step introduction of inputs, which is constructed by imitating the somatosensory system in human body, known as SpinalNet have been implemented in this work on a Galaxy Zoo dataset. The input segmentation in SpinalNet has enabled the intermediate layers to take some of the inputs as well as output of preceding layers thereby reducing the amount of the collected weights in the intermediate layers. As a result of these, the authors of SpinalNet reported to have achieved in most of the DNNs they tested, not only a remarkable cut in the error but also in the large reduction of the computational costs. Having applied it to the Galaxy Zoo dataset, we are able to classify the different classes and/or sub-classes of the galaxies. Thus, we have obtained higher classification accuracies of 98.2, 95 and 82 percents between elliptical and spirals, between these two and irregulars, and between 10 sub-classes of galaxies, respectively.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126420525","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
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