A. Khalifeh, A. Al-Qammaz, Khalid A. Darabkh, L. Abualigah, Ahmad M. Khasawneh, Z. Zinonos
{"title":"An AI Based Irrigation and Weather Forecasting System utilizing LoRaWAN and Cloud Computing Technologies","authors":"A. Khalifeh, A. Al-Qammaz, Khalid A. Darabkh, L. Abualigah, Ahmad M. Khasawneh, Z. Zinonos","doi":"10.1109/ElConRus51938.2021.9396431","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396431","url":null,"abstract":"Artificial Intelligence (AI) has been flourishing recently as a viable solution for many applications and scenarios, including smart irrigation and weather forecasting systems. In these systems, it is crucial to have an accurate prediction for the weather and soil conditions to optimize the irrigation process such that the minimal amount of water is provided. In this paper, a smart irrigation system utilizing Artificial Intelligence (AI) and Long Range Wide Area Network (LoRaWAN) communication link is proposed. The system is composed of sensors that are used to measure soil moisture, atmosphere temperature, and humidity. This information is sent via LoRaWAN communication link to a remote center that gathers, analyzes the captured information, quantifies the appropriate amount of water for irrigation, and then sends the decision back to the irrigation system. Furthermore, the collected information will be stored in the cloud for wider accessibility. This paper describes the technical implementation of the smart irrigation system and focuses on the weather forecasting process, which is performed using the Wind Driven Optimization - Least Square Support Vector Machine (WDO-LS-SVM) algorithm. The obtained results show a better performance when compared to the LS-SVM, which verifies the effectiveness of jointly utilizing the WDO with the LS-SVM.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114328413","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}
I. Kondratev, V. Bazanov, Daniil A. Uskov, Anna V. Kuchebo, Tatyana E. Sereda
{"title":"Comparative Analysis of Methods for Detecting Fraudulent Transactions","authors":"I. Kondratev, V. Bazanov, Daniil A. Uskov, Anna V. Kuchebo, Tatyana E. Sereda","doi":"10.1109/ElConRus51938.2021.9396074","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396074","url":null,"abstract":"This article is focused on the comparative analysis of machine learning models used to identify fraudulent transactions. During the research, models of three different algorithms were considered, and their optimization for the task was performed. The accuracy of the models was compared, the advantages and disadvantages of each model were identified, recommendations for their use were given, and conclusions were drawn. The experiment was conducted to evaluate the effectiveness of various machine learning models in transaction classification problems.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114526071","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}
Oleg A. Kaunov, M. Kochetkov, Vladimir F. Petrov, Aleksey I. Terent’ev
{"title":"Model of Collective Object Recognition at the Control Unit of a Robot Systems Group","authors":"Oleg A. Kaunov, M. Kochetkov, Vladimir F. Petrov, Aleksey I. Terent’ev","doi":"10.1109/ElConRus51938.2021.9396144","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396144","url":null,"abstract":"Nowadays an actual task is large territories monitoring in areas of natural and anthropogenic disasters. Group use of robots makes it possible to enlarge the size of the controlled zone, increase the probability of detecting objects of various purposes. At the same time, there appear new problems related to the task of objects recognition in conditions of a priori uncertainty regarding their observation conditions.The article offers a new approach to solving the problem of collective object recognition of a group robotic complexes, when the primary object recognition by autonomous robots, and the final solution is developed at the control point, taking into account the specific conditions under which decisions on primary recognition were developed.A general model of collective object recognition is presented, certain stages of information processing are considered, and the necessary formula dependencies are given. The features of the proposed approach are explained by examples.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116166441","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}
M. Y. Fomichev, M. A. Makhiboroda, N. Djuzhev, A. Dedkova, E. Gusev
{"title":"Development of Adhesive Wafer Bonding Technology","authors":"M. Y. Fomichev, M. A. Makhiboroda, N. Djuzhev, A. Dedkova, E. Gusev","doi":"10.1109/ElConRus51938.2021.9396080","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396080","url":null,"abstract":"This paper shows the result of working out the operations of permanent bonding of Si-Si wafers and temporary bonding of Si-quartz wafers. The equipment was selected for the process of applying a thin-film material to increase the uniformity of the thickness of the adhesive, anti-adhesive, and photoresist layers. Also, the effects of flowing applied fluids to the back of the wafer are eliminated. The dependence of the thickness of the adhesive, anti-adhesive, and photoresist layers on the speed of rotation of the centrifuge was experimentally determined. It was compared with material developers' data. The curvature of the assembly does not exceed 10 μm after permanent bonding of Si-Si wafers with a diameter of 150 mm and a thickness of 675 μm. In the process of temporary bonding, the thickness of the device Si wafer after thinning was 93 ± 3 μm. The deflection of the thinned assembly does not exceed 30 µm.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116469695","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}
D. Seleznev, Artem Egupov, G. Greshnyakov, S. Dubitsky
{"title":"Combining Resistive and Capacitive Stress Grading in High Voltage Cable Joints","authors":"D. Seleznev, Artem Egupov, G. Greshnyakov, S. Dubitsky","doi":"10.1109/ElConRus51938.2021.9396152","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396152","url":null,"abstract":"The commonly used pre-moulded slip-one cable joint is proposed to replace with a combination of heat-shrinkable cylindrical tubes. The working principle of effective electrical stress grading is based on combining the resistive and capacitive stress grading approaches. Both resistive and capacitive stress graders are coaxial heat-shrinkable tubes of carefully designed profile, position, and dielectric properties. Optimal sizing and material properties of each tube are found by FEA modeling of electric field taking into account the leakage current. Proposed optimal parameters confirmed by preliminary laboratory test of a 110 kV cable joint","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121485217","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}
Marina K. Altukhova, Igor R. Gotoullin, Maria A. Lyulina, Irina E. Ryndina, V. S. Chudny
{"title":"Method of Forming a Model for Adaptive Control of Dynamic Properties of an Electric Power System","authors":"Marina K. Altukhova, Igor R. Gotoullin, Maria A. Lyulina, Irina E. Ryndina, V. S. Chudny","doi":"10.1109/ElConRus51938.2021.9396173","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396173","url":null,"abstract":"A method for forming a multiparameter characteristic polynomial based on a set of model transfer functions of the stabilization parameters of several stations of the electric power system is developed.It is shown that the necessary transfer functions can be restored from the known experimental mode frequency responses obtained under operating conditions.A recurrent notation form of the characteristic polynomial is established for variations in the number of selected control points in the electric power system. When using this polynomial, it is possible to organize the most effective parallel multivariate procedure of optimization of parameters of power system stabilizer.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114764694","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}
{"title":"Technical Vision Based Autonomous Navigation Intelligent System of a Mobile Robot","authors":"A. Usov, S. S. Rzaev, N. Markovkina","doi":"10.1109/ElConRus51938.2021.9396458","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396458","url":null,"abstract":"Intelligent autonomous navigation system based on technical vision is considered as part of a training and research project. The Autonomous navigation system and its elements are considered. Problems of creating a prototype are described. The goal of this project is to develop this system for a four-wheeled robot. There are some problems with design: the first one is the hard artificial intelligence (AI) part. The similar AI programms are made for autopilots by Tesla [1] and Google. Also, we are used to look at robots that can move straight. But if you want to turn right or left the robots have to stop and then swerve. This problem is called Dubin’s path. The third problem is the problem of extracting unnecessary elements. They can either disorient the system or add extra calculations inside the program. Next problem is the problem of detecting human. We know that road safety is the most important part of transportation. You need to devote most of your time to this aspect. More precisely, the development of the system as a safety assistant.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114780077","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}
A. Feshin, E. Popkov, A. S. Adalev, V. Kuchinskiy, L. A. Koshcheev
{"title":"The Macromodel of a Six-Phase Synchronous Machine with Combined Excitation for Electric Power Systems Processes Study","authors":"A. Feshin, E. Popkov, A. S. Adalev, V. Kuchinskiy, L. A. Koshcheev","doi":"10.1109/ElConRus51938.2021.9396617","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396617","url":null,"abstract":"A macromodel of a six-phase synchronous machine has been developed in the phase coordinate system, which is excited by a magnetic flux from both the field winding and permanent magnets. Equations are presented that describe the electromagnetic and electromechanical processes in such a machine. The effect of permanent magnets on the phase windings is taken into account by a harmonic approximation of the induced EMF. A short circuit simulation at the field winding terminals of a six-phase synchronous motor with combined excitation is carried out. The results obtained prove the efficiency of the proposed macromodel.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"538 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124353920","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}
{"title":"A Multi-Purpose Testbench for Determining the Parameters of Moving Objects Based on the Processing of Heterogeneous Sensory Information in the On-Board System of an Autonomous Robot","authors":"M. A. Volkova, A. Romanov","doi":"10.1109/ElConRus51938.2021.9396127","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396127","url":null,"abstract":"This paper proposes a multi-purpose testbench for determining the parameters of moving objects in controlled laboratory conditions. The testbench include different types of the sensors, which are based on different physical principal and simultaneously observe multiple mobile robots. The paper discuses data acquisition and processing methods as well as experimental studies scenarios, that can be investigated using proposed testbench.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124078786","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}
{"title":"Application of Neural Networks in the Tasks of Automation at Industrial Enterprises","authors":"A. Petrova, Alexander M. Sinitca","doi":"10.1109/ElConRus51938.2021.9396114","DOIUrl":"https://doi.org/10.1109/ElConRus51938.2021.9396114","url":null,"abstract":"currently, it is becoming relevant to use modern data analysis tools for automation of processes at industrial enterprises. One such tool is neural networks, which are heavily used in areas where forecasting and deep understanding of data are required. This article discusses the possibility of using neural networks in the tasks of monitoring and predicting gas imbalance in gas distribution systems. An algorithm for collecting and processing data is proposed, a mechanism for training neural networks and generating predictive values is disassembled, directions for further development of this topic are proposed","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124091009","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}