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

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Effective Ways to Pass Exams in Programming Disciplines and Optimize the Process of Analyzing Results. Case Study: Suleyman Demirel University 通过编程学科考试的有效途径和优化分析结果的过程。案例研究:苏莱曼德米雷尔大学
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663777
Ualikhan Sadyk, Zhasdauren Duisebekov, Nauryzbay Sapargali, Altynbek Amirzhanov
{"title":"Effective Ways to Pass Exams in Programming Disciplines and Optimize the Process of Analyzing Results. Case Study: Suleyman Demirel University","authors":"Ualikhan Sadyk, Zhasdauren Duisebekov, Nauryzbay Sapargali, Altynbek Amirzhanov","doi":"10.1109/icecco53203.2021.9663777","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663777","url":null,"abstract":"The article identifies effective ways to pass exams in programming disciplines and how to optimize the process of analyzing results. Also we discussed a list of the problems that we may faced during the exam and their solutions(proposed method). The main part of our project was divided into 4 stages: Analysis of exam results using Google Sheets, Writing a special script(program) that automatically loads images, Detection of plagiarism manifestations using the principles of computer vision, Facial recognition using machine learning algorithms.","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":"125475052","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
Intrusion Detection System for Wireless Networks 无线网络入侵检测系统
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663787
Baimukashev Rashid, Kamalkhan Artykbayev, Kazybek Adam, Begenov Mels
{"title":"Intrusion Detection System for Wireless Networks","authors":"Baimukashev Rashid, Kamalkhan Artykbayev, Kazybek Adam, Begenov Mels","doi":"10.1109/icecco53203.2021.9663787","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663787","url":null,"abstract":"The network security plays a vital role in the performance of the wireless networks, and as a part of network security features the intrusion detection system may enhance the performance of the network. In our project we designed such intrusion detection system using deep learning approaches such as CNN, RNN and LSTM as well as with traditional machine learning algorithms such as SVM, Random Forest and XGBoost. In our project we achieved a near to state-of-the-art performance on detecting network attacks on the NSL-KDD dataset.","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":"134296379","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: 4
Development of a preliminary version of a model for machine learning in predicting yield on the example of wheat in the conditions of East Kazakhstan 开发机器学习模型的初步版本，以东哈萨克斯坦条件下的小麦为例预测产量
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663758
Nail Alikuly Beisekenov, M. Sadenova, N. Kulenova, Mamysheva Asel Mukhtarkanovna
{"title":"Development of a preliminary version of a model for machine learning in predicting yield on the example of wheat in the conditions of East Kazakhstan","authors":"Nail Alikuly Beisekenov, M. Sadenova, N. Kulenova, Mamysheva Asel Mukhtarkanovna","doi":"10.1109/icecco53203.2021.9663758","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663758","url":null,"abstract":"An approach to forecasting crop yields using Earth remote sensing data is described. The values of the normalized difference vegetation index (NDVI) were used as the main predictive regression model. The article provides an assessment of the possibility of early forecasting before the NDVI index reaches its maximum values using a Gaussian as an approximating function used by weekly NDVI composites. For arable lands of the Glubokovsky district of the East Kazakhstan region, the error in determining the maximum NDVI, depending on the calendar week of forecasting, was calculated. The constructed model for a preliminary estimate of the yield of spring wheat in a specific field in 2022.","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":"122853024","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
Modeling and Cluster Analysis of Antagonistic Systems 拮抗系统的建模与聚类分析
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663751
D. O. Toybazarov, S. Atanov, Z. R. Burnayev, Gani Baiseitov, Dauren Kassenov
{"title":"Modeling and Cluster Analysis of Antagonistic Systems","authors":"D. O. Toybazarov, S. Atanov, Z. R. Burnayev, Gani Baiseitov, Dauren Kassenov","doi":"10.1109/icecco53203.2021.9663751","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663751","url":null,"abstract":"This paper presents a consideration about a significant exacerbation of geopolitical contradictions associated with a new redistribution of influence zones. As a result of these processes, a significant increase in instability is observed in many regions, which actualizes the problem of the states security and their citizens. The main antagonistic contradictions are both the source and the driving force of the society historical development. The aim of this study is an attempt to simulate the processes taking place in society using data analysis on the Internet. To analyze these current processes in the world, we use cluster methods for modeling stochastic systems, and a computer parser will be used to collect data. A special aspect of the work is the creation of system attributes based on antagonism.","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":"123929428","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
Breast cancer histopathology image classification using CNN 基于CNN的乳腺癌组织病理学图像分类
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663757
Mukhamejan Karatayev, Saltanat Khalyk, Shomanov Adai, Min-Ho Lee, M. Demirci
{"title":"Breast cancer histopathology image classification using CNN","authors":"Mukhamejan Karatayev, Saltanat Khalyk, Shomanov Adai, Min-Ho Lee, M. Demirci","doi":"10.1109/icecco53203.2021.9663757","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663757","url":null,"abstract":"The breast cancer is one of the wide spread diseases around the world. Cancer develops in a milk duct and then spreads to the surrounding breast tissues. This initial stage of progression is called invasive ductal carcinomas (IDC). Almost 80% of all breast cancers are invasive ductal carcinomas. If IDC is detected at early stages, the patient can be treated and will have a high survival rate, whereas undetected cancer may spread into other parts of the body, as well as surrounding breast tissues. In this work, the dataset that contains breast cancer histopathology images was used. The objective of this work is to implement a convolutional neural network (CNN) model for accurate IDC classification, by balancing the dataset and tuning hyperparameters. The proposed model achieves an accuracy of 92% for the classification of histopathological images, and outperforms the baseline CancerNet model with accuracy of 86%. Furthermore, our experimental results demonstrate the superiority of our approach over the pre-trained networks, such as VGG16, DenseNet and ResNet18.","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":"114246451","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
Part-of-speech tagging of Kazakh text via LSTM network with a bidirectional modifier 基于双向修饰语的LSTM网络哈萨克语文本词性标注
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663794
Azamat Serek, A. Issabek, Adil Akhmetov, Alisher Sattarbek
{"title":"Part-of-speech tagging of Kazakh text via LSTM network with a bidirectional modifier","authors":"Azamat Serek, A. Issabek, Adil Akhmetov, Alisher Sattarbek","doi":"10.1109/icecco53203.2021.9663794","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663794","url":null,"abstract":"In this paper, part-of-speech tagging on Kazakh text has been implemented using an LSTM neural network with a bidirectional modifier. A quite simple and fast tagger has been built, tested and evaluated on the self-collected dataset of Kazakh sentences with an accuracy of 94 %. There was addressed basically the problem of tagging having a small number of training samples (around 100 Kazakh sentences). It has been shown that quite good accuracy can be achieved in this situation.","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":"114620278","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
Development of Attendance Monitoring System using IoT Technologies 利用物联网技术开发考勤监控系统
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663827
Zhumaniyaz Mamatnabiyev
{"title":"Development of Attendance Monitoring System using IoT Technologies","authors":"Zhumaniyaz Mamatnabiyev","doi":"10.1109/icecco53203.2021.9663827","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663827","url":null,"abstract":"Recently, applications of Internet of Things (IoT) technologies have been established in many organizations offering low-costed, low-powered, automatic systems. In addition, IoT systems are secure, less time-consuming, and controlled remotely. Implementing IoT technologies in managing the educational process makes huge changes by creating digital classrooms and automation systems. However, taking students’ absence reports is still a critical element or issue in the education sector that is more paperwork, which is time-consuming, requires much workforce and efforts, and imposes inefficiency. Various automatic identification technologies have been developed using Radio Frequency Identification (RFID). Many research works and projects are produced to take maximum benefits of using this technology. The current work proposes an automatic attendance monitoring system (AMS) using IoT technologies including RFID and hardware platforms. The objectives of the proposed system are to check attendance of students automatically without human interface, inform students about gaps in attendance, and monitor instructors whether they come to lessons on time. Based on the results, the proposed AMS is time-effective, economically available, and has not any power consumption. The system is analyzed and criticized with respect to other authors’ works. Future work is discussed and identified.","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":"131320362","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
Electromyography Signal Classification Using Deep Learning 基于深度学习的肌电信号分类
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/ICECCO53203.2021.9663803
Mekia Shigute Gaso, S. Cankurt, A. Subasi
{"title":"Electromyography Signal Classification Using Deep Learning","authors":"Mekia Shigute Gaso, S. Cankurt, A. Subasi","doi":"10.1109/ICECCO53203.2021.9663803","DOIUrl":"https://doi.org/10.1109/ICECCO53203.2021.9663803","url":null,"abstract":"We have implemented a deep learning model with L2 regularization and trained it on Electromyography (EMG) data. The data comprises of EMG signals collected from control group, myopathy and ALS patients. Our proposed deep neural network consists of eight layers; five fully connected, two batch normalization and one dropout layers. The data is divided into training and testing sections by subsequently dividing the training data into sub-training and validation sections. Having implemented this model, an accuracy of 99 percent is achieved on the test data set. The model was able to distinguishes the normal cases (control group) from the others at a precision of 100 percent and classify the myopathy and ALS with high accuracy of 97.4 and 98.2 percents, respectively. Thus we believe that, this highly improved classification accuracies will be beneficial for their use in the clinical diagnosis of neuromuscular disorders.","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":"131903666","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
Analysis of supervisors and students in the context of diploma defense 浅析导师与学生的学历答辩
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663776
Azamat Serek, Aisaule Bazarkulova, Abylaikhan Chazhabayev, Adil Akhmetov
{"title":"Analysis of supervisors and students in the context of diploma defense","authors":"Azamat Serek, Aisaule Bazarkulova, Abylaikhan Chazhabayev, Adil Akhmetov","doi":"10.1109/icecco53203.2021.9663776","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663776","url":null,"abstract":"This work analyzed supervisors and students in the context of diploma defense. One of the most important aspects of education is the search for students and supervisors, as well as the establishment of projects, the introduction of research, and work delegation. Unfortunately, the issue comes when looking for students and supervisors in fields of interest to them. Based on an examination of common interests, study fields, and demands, it was determined to establish a project management system and search for students or research supervisors to solve this challenge. As a result, the current study discusses the development of a specialized platform and a user-friendly system for monitoring student progress in a supervisory setting. It also strives to develop.","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":"132685135","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
Data Analysis for The Student Health Digital Profile 学生健康数字档案的数据分析
2021 16th International Conference on Electronics Computer and Computation (ICECCO) Pub Date : 2021-11-25 DOI: 10.1109/icecco53203.2021.9663804
M. Mansurova, Malika Zubairova, N. Kadyrbek, G. Tyulepberdinova, T. Sarsembayeva
{"title":"Data Analysis for The Student Health Digital Profile","authors":"M. Mansurova, Malika Zubairova, N. Kadyrbek, G. Tyulepberdinova, T. Sarsembayeva","doi":"10.1109/icecco53203.2021.9663804","DOIUrl":"https://doi.org/10.1109/icecco53203.2021.9663804","url":null,"abstract":"The work aims to develop a methodology for data collection and mining algorithms for an information system for assessing students’ health. Within the framework of this scientific problem, several problems are solved related to analysis, search for patterns, visualization of results, and a combination of medical, social, and academic data using artificial intelligence methods. This study will be especially targeted at Kazakh educational institutions. An information system with visualization of the results of aggregation and analysis of data on health-related indicators can be used by various groups of internal and external stakeholders as a regularly updated information resource for the development of various social or medical support programs. The work studied and compared machine learning algorithms based on specially collected data on consultations of medical specialists. In addition, statistical analysis was carried out.","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":"129853736","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: 3
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