2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)最新文献_第9页

KazRivDyn: Toolkit for Measuring the Dynamics of Kazakhstan Rivers with a Graphics Based on Google Earth Engine KazRivDyn:基于谷歌地球引擎的图形测量哈萨克斯坦河流动态的工具包

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465902

Assel Ospan, M. Mansurova, E. Kakimzhanov, Baurzhan Aldakulov

引用次数: 0

Digital Education Ecosystem (DEE): User-Centred Design of the Student Journey Configurator 数字教育生态系统(DEE):以用户为中心的学生旅程配置器设计

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465899

E. Mikhaylova, Areej Aldaghamin, Felix Ebberg, Olzhas Tokanov, Carsten Wolff, Christian Reimannn

{"title":"Digital Education Ecosystem (DEE): User-Centred Design of the Student Journey Configurator","authors":"E. Mikhaylova, Areej Aldaghamin, Felix Ebberg, Olzhas Tokanov, Carsten Wolff, Christian Reimannn","doi":"10.1109/SIST50301.2021.9465899","DOIUrl":"https://doi.org/10.1109/SIST50301.2021.9465899","url":null,"abstract":"Higher Education is changing towards personalized student journeys – meaning that students and teachers tailor educational programmes to the goals and preferences of individuals. This causes the need for decision support and information systems in order to facilitate the student journey. This paper describes the concept of the Student Journey Configurator (SJC) platform as a digital tool to facilitate a transparent educational process through the study programme for teachers, academic staff, and students. After elaborating on the general background of digital education ecosystems (DEE) and the concept of the student journey, the SJC application architecture and the authentication process based on eduGain are explained. The scientific contribution is the evaluation of the usability of the platform and the view-based concept of the configuration process. To do that, the user interface was tested with 7 students of one of the relevant international Master programmes. The students were given access to the five main views of the SJC and asked 14 questions to navigate through the process. The results showed that the view concept and the user interface design are valid. However, students had several problems with the understanding of particular icons, naming, and navigation elements. These findings should be considered during the following development process.","PeriodicalId":318915,"journal":{"name":"2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)","volume":"41 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113969026","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

Contact Centers Management Models: Analysis and Recommendations 联络中心管理模式:分析与建议

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465921

B. Aitchanov, O. Baimuratov, Muratbek Zhussupekov, Tleu Aitzhanov

引用次数: 0

Implementation Of An Intelligent Control System For Heat Distribution In Rooms 室内热分配智能控制系统的实现

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9491797

N. Tasmurzayev, B. Amangeldy, E. S. Nurakhov, A. Mukhanbet, Zh. Yeltay

{"title":"Implementation Of An Intelligent Control System For Heat Distribution In Rooms","authors":"N. Tasmurzayev, B. Amangeldy, E. S. Nurakhov, A. Mukhanbet, Zh. Yeltay","doi":"10.1109/SIST50301.2021.9491797","DOIUrl":"https://doi.org/10.1109/SIST50301.2021.9491797","url":null,"abstract":"This scientific article discusses the hardware and software implementation of an intelligent distributed system for predicting and controlling optimal heat distribution in a room. The system collects data from sensors and sends it to the server for further monitoring and training of the neural network. Prediction is based on a pre-trained neural network model. The principle of operation of modern air conditioners is based on maintaining the room temperature at a given temperature. The air conditioner generates a stream of air by pre-cooling or heating it. When the temperature reaches the required value, the air conditioner turns off (goes to sleep mode), continues to take the air temperature values, and when the temperature changes, it turns on again. The system uses the results of calculating a one-dimensional heat conduction problem to correct the trained neural model and makes a decision about switching on/off and changing the temperature regime of a certain air conditioner depending on the predicted data. In these methods, only the temperature close to the air conditioner is calculated using the temperature sensor of the air conditioner itself, and this does not give us a complete picture of the temperature distribution in the room. The temperature sensor located on the air conditioner itself does not reflect the general picture of the temperature distribution and, due to the characteristics of the room, the temperature in different areas can vary greatly. Also, the operation of the air conditioner does not take into account the operation of other air conditioners, the operation of each air conditioner is autonomous and is controlled only based on the readings of the associated temperature sensor.","PeriodicalId":318915,"journal":{"name":"2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124953645","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

A novel Intervention to Enhance Transoceanic Fiber Effectiveness Through Advanced QX 5252 CMOS Driver 通过先进的QX 5252 CMOS驱动器提高跨洋光纤效率的新型干预措施

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465889

Elsayed Imadeldin Elmutasim, Mohd Izzeldin

{"title":"A novel Intervention to Enhance Transoceanic Fiber Effectiveness Through Advanced QX 5252 CMOS Driver","authors":"Elsayed Imadeldin Elmutasim, Mohd Izzeldin","doi":"10.1109/SIST50301.2021.9465889","DOIUrl":"https://doi.org/10.1109/SIST50301.2021.9465889","url":null,"abstract":"Submarine fiber networks are considered the backbone of communication between countries, hence the operators expecting to get high quality and performance efficiency. Due to that, sea cable manufacturers ramping up the efforts to enhance the bandwidth availability, reliability, and entire performance satisfactory to the customers’ demand because they well know laying out new transoceanic fiber is more expensive than other ground cables. On the other hand, separation of power cable from the fiber in the submarine system making the repair, troubleshooting, and even survey test likewise costly due to utilizing the different platforms, tools, and expertise to achieve the task. This paper undertakes an extensive test in fiber optic including submarine cable through give a spotlight to the attenuation elements such as reflection loss as well as the power cable standalone impact in the submarine fiber network. The investigation based on the real survey test which considers the cable from the beach manhole to the main station shelter and proposes to use an advanced QX5252 CMOS to incorporate, magnifying the voltage and power discharge depends on the system requirements. The advanced chip also able to sense the signal thus would occupy many aspects in addition to care for the earthing process via overload discharge. The scientific approach of the proposal assessed the potential solution to mitigate the challenges in the submarine cable as well as fiber optic.","PeriodicalId":318915,"journal":{"name":"2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127900764","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

Building a System for Predicting the Yield of Grain Crops Based On Machine Learning Using the XGBRegressor Algorithm 基于XGBRegressor算法的机器学习谷物产量预测系统的构建

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465938

Zhagparov, Z. Buribayev, S. Joldasbayev, A. Yerkosova, M. Zhassuzak

{"title":"Building a System for Predicting the Yield of Grain Crops Based On Machine Learning Using the XGBRegressor Algorithm","authors":"Zhagparov, Z. Buribayev, S. Joldasbayev, A. Yerkosova, M. Zhassuzak","doi":"10.1109/SIST50301.2021.9465938","DOIUrl":"https://doi.org/10.1109/SIST50301.2021.9465938","url":null,"abstract":"The use of machine learning to predict crop yields is important for development, since the proposal of this solution will improve and facilitate the task of the whole department of the agricultural sector in calculations and predictions, will help to focus on optimizing the infrastructure for the production of crops. In this paper, a solution is proposed for automating the forecast of grain yield based on machine learning using the XGBRegressor algorithm with a collected dataset of 44 parameters in the territory of the Republic of Kazakhstan and for each region of the Republic of Kazakhstan separately. Comparisons were made with the Linear Regression and Decision Tree Regressor algorithms. Validation was carried out for the period 01.2012 - 09.2020, the test was carried out at 10.2020. As a result, a model was obtained that predicts the yield quite accurately compared to other algorithms, and the results were interpreted using the RMSE metric to understand the difference more accurately between the algorithms and the errors made by the model.","PeriodicalId":318915,"journal":{"name":"2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133509758","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: 9

Distance learning at KazNPU Named after Abai: Models and Technologies 以阿拜命名的KazNPU远程教育:模型和技术

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465980

T. Balykbayev, D. Issabayeva, L. Rakhimzhanova, Shaizat Zhanysbekova

引用次数: 2

Automatic Language Identification from Spectorgam Images 从光谱图像自动语言识别

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465996

Aizada Kaiyr, S. Kadyrov, A. Bogdanchikov

引用次数: 1

Research of the Regression Analysis Methods for Predicting the Growth of Patients with Diabetes Mellitus 预测糖尿病患者生长的回归分析方法研究

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465975

A. Mukasheva, Z. Akanov, D. Yedilkhan

引用次数: 1

Modelling of the Intelligent Agent’s Behavior Scheduler Based on Petri Nets and Ontological Approach 基于Petri网和本体方法的智能体行为调度建模

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI: 10.1109/SIST50301.2021.9465994

V. Lytvyn, M. Bublyk, V. Vysotska, V. Panasyuk, O. Brodyak, M. Luchkevych

引用次数: 0