Proceedings of the 6th International Conference on Engineering & MIS 2020最新文献_第10页

Auto-abstracting of texts in the Kazakh language 哈萨克语文本的自动抽象

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410832

D. Rakhimova, A. Turganbayeva

{"title":"Auto-abstracting of texts in the Kazakh language","authors":"D. Rakhimova, A. Turganbayeva","doi":"10.1145/3410352.3410832","DOIUrl":"https://doi.org/10.1145/3410352.3410832","url":null,"abstract":"In this article, the authors propose an approach for abstracting text resources and documents in the Kazakh language. Using software solutions to normalize texts in the Kazakh language, the text data developed by the scientific team of the authors of this work was prepared for further processing. Reviewing is based on keywords and phrases. To extract keywords and phrases, an algorithm is used TF-IDF algorithm to extract keywords and phrases from texts in the Kazakh language. To solve the problem, an approach based on machine learning was applied. To determine the similarity of the sentence, the cosine similarities of the data of the sentence are calculated, and thus the semantic content of the text is determined. When outputting text annotations, the volume of text is taken into account, that is, the amount of annotation depends on the volume of the document. Abstracting of texts in the Kazakh language is an urgent task of classification, clustering of text and information retrieval. The paper presents the results of experimental calculations for various approaches. The results of the study show that the presented approach is the best solution for extracting annotations from texts in the Kazakh language.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134118732","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

E-learning as a factor of quality assurance of professional training of future teachers of Russian language and literature 电子学习是未来俄语语言文学教师专业培训质量保证的一个因素

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410839

B. Zholdasbekova, K. Galay, S. Mizanbekov, Zh. A. Bayanbayeva, J. B. Dzhalamova

引用次数: 1

Design Optimaztion of An Electromagnetic Gearing System for Wind Power Application 风电电磁传动系统的设计优化

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410796

E. Diryak, O. Imrayed, S. Zeid

引用次数: 0

Design and Performance Evaluation of Rectangular Microstrip Antenna for 5G Communication systems at 48.6 GHz 48.6 GHz 5G通信系统矩形微带天线设计与性能评价

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410801

N. Shebani, Abdalnaser F. Kaeib, A. Zerek

引用次数: 0

Assessment of Qualitative Characteristics of Project Risks 项目风险的定性特征评价

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410810

G. Omarov, Y. Shildibekov, A. Omarova, A. E. Tashtamysheva

{"title":"Assessment of Qualitative Characteristics of Project Risks","authors":"G. Omarov, Y. Shildibekov, A. Omarova, A. E. Tashtamysheva","doi":"10.1145/3410352.3410810","DOIUrl":"https://doi.org/10.1145/3410352.3410810","url":null,"abstract":"The article considers qualitative characteristics of risks based on the practice of financing projects in a Kazakh bank. Identified and proposed significant risk factors that require careful analysis during the project appraisal. Classification and risk ranking are combined into three main groups: (1) Macroeconomics and the Industry, (2) Competitive Position and (3) Management Evaluation. The first group includes the risks of the industry with an assessment of the current and prospective state, exposure to technological risks, capital intensity. The second group determines the level and optimization of the cost of the company, a comparison with the indicators of competitors; strength of market positions of products. Evaluation of the company's sales level, its stability; diversification of products, buyers and suppliers are conducted expert way. The third group reveals the level of management of the company on the basis of factors: experience in this industry, education, reputation; the success of doing business and projects; an assessment of the interaction system between say shareholders and the company's management. Qualitative characteristics together with quantitative serve as a tool for decision-making in the analysis and evaluation of investment projects of business.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132246948","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

Performance Analysis of Blockchain-Based Systems for Industry Applications 基于区块链的工业应用系统性能分析

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410836

M. Khan, O. Bayat, Ugur Coruh

{"title":"Performance Analysis of Blockchain-Based Systems for Industry Applications","authors":"M. Khan, O. Bayat, Ugur Coruh","doi":"10.1145/3410352.3410836","DOIUrl":"https://doi.org/10.1145/3410352.3410836","url":null,"abstract":"Blockchain is the most prominent phenomenon of the technological world and provides a foundation for future ecosystems to build trust less nodes in a distributed system. However, the security and privacy provided by the blockchain-based systems in industrial and business applications are not yet matured. Therefore, the security and privacy of the domains are under future researches. This paper presents and highlights the security and privacy feature in Blockchain-based systems, specifically in supply chain management, trade digitization, and smart factories. We referenced some real-life use cases of Blockchain in the supply chain, letter of credits, trade digitization, and in Smart factories. We focus on recent challenges while adding security in these systems with the blockchain and suggests some solutions to these challenges. The existing framework and merging a private block with a robust privacy guideline, following confidentiality, integrity, and availability (CIA). The traditional blockchain smart factory includes sensing layer, management hub layer, storage, firmware, and application layer, therefore, incorporating the Hyperledger Fabric with our new secure communication and storage architecture will enhance security and privacy in blockchain-based smart factories.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130623081","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

Control and Prediction of Communications Network Congestion by Using Artificial Intelligent techniques 基于人工智能技术的通信网络拥塞控制与预测

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410750

Someya Younes Saleh, I. Ighneiwa, Wafa Alsadik Hammad

{"title":"Control and Prediction of Communications Network Congestion by Using Artificial Intelligent techniques","authors":"Someya Younes Saleh, I. Ighneiwa, Wafa Alsadik Hammad","doi":"10.1145/3410352.3410750","DOIUrl":"https://doi.org/10.1145/3410352.3410750","url":null,"abstract":"There exists great demand supporting ever-increasing new Internet applications such as voice over IP and video on demand.This causes network congestion, which occurs when the load on the network is greater than the capacity of the network, despite of the implementation of various conventional control algorithms, congestion remains a critical concern in network systems. Hence it is necessary to find some non-conventional intelligent techniques to control and predict congestion. In this work, intelligent Control Techniques (ICT), specifically Fuzzy Logic Control (FLC) is utilized to control congestion and keep the load lower than the network capacity. We propose using learning techniques (WEKA )the concept from another intelligent control technique which is the Artificial Neural Networks to predict network congestion problems before they start impacting the performance of services. We trained the network so it would not stick with the conventional \"either or\" logic, but also consider the cases close to both, then we tested the network using data known to us but not to the network. Finally, we evaluated the system by hitting the network with completely strange to it and to us data and see if it would accomplish the job it was trained for. also we used OPNET Modeler, for network simulation and final results validation.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124187572","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

Geoinformational education and project approach at KSU named after Sh. Ualikhanov 以乌利哈诺夫命名的KSU地理信息教育和项目方法

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410840

Damekova Saule, Nurmuhanbetova Nurgul, Belgibayeva Anargul

引用次数: 0

A Smart Resource-efficient Surveillance System 智能资源高效监控系统

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-09-14 DOI: 10.1145/3410352.3410805

Amine A. Kechroud, Salem A. Alseah, Mohamed S. Musbah

引用次数: 0

Neural Networks Identification and Control of Mobile Robot Using Adaptive Neuro Fuzzy Inference System 基于自适应神经模糊推理系统的移动机器人神经网络辨识与控制

Proceedings of the 6th International Conference on Engineering & MIS 2020 Pub Date : 2020-08-23 DOI: 10.1145/3410352.3410734

A. Abougarair

{"title":"Neural Networks Identification and Control of Mobile Robot Using Adaptive Neuro Fuzzy Inference System","authors":"A. Abougarair","doi":"10.1145/3410352.3410734","DOIUrl":"https://doi.org/10.1145/3410352.3410734","url":null,"abstract":"This paper developed and investigates the performance of intelligent algorithms in order to stabilize the robot when it is tracking to the reference signal. One type of robot is a Two Wheeled Balancing Mobile Robot (TWBMR) that requires control for both balancing and maneuvering. Combination artificial intelligence, Neural Networks (NNs) and Fuzzy Logic Control (FLC) have been recognized as the main tools to improve the performance of coupling nonlinear robot system without using any mathematical model. The input-output data of TWBMR generated from closed loop control system is used to develop a neural network model. In this study, neural networks model can be trained offline and then transferred into a process where an adaptive online learning is carried out using Adaptive Network Based Fuzzy Inference System ANFIS to improve the system performance. The simulation results verify that the considered identification and control strategies can achieve favorable control performance. The ANFIS control design approach does not require an accurate model of the plant. In addition, high-level knowledge of the system is not needed to build a set of rules for a fuzzy controller.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126618756","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: 15