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Artificial Intelligence in Medicine for Chronic Disease Classification Using Machine Learning

Artificial Intelligence in Medicine for Chronic Disease Clas...

引用

International Conference on Application of information and Communication technologies (AICT)

作者： Mekhriddin Rakhimov Ravshanjon Akhmadjonov Shahzod Javliev Department of Artificial Intelligence Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan Department of System and Application Programming Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan Department of Computer System Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665451635

Artificial intelligence (AI) systems in medicine are one of the most important modern trends in global healthcare. Artificial intelligence technologies are fundamentally changing the global healthcare system, making it possible to radically rebuild the system of medical diagnostics while reducing healthcare costs. AI is actively used in research to develop methods for diagnosing coronary heart disease (CHD). There are different types of CHD. Before treating a disease, it is necessary to determine which class of diseases it belongs to. Based on the feature space of the disease, it is possible to classify the type of CHD. Machine learning algorithms can solve this problem. The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve classification problems. The dataset is the more important part of the supervised machine learning algorithm for training. Gathering data is the most important step in solving any supervised machine learning problem. But choosing more important part from the collected data is one of the tasks to be solved. The main purpose of this study is to select more useful parametric attributes from the dataset to obtain a high F1-score of CHD classification.

关键词： Heart Training Machine learning algorithms Machine learning Market research Classification algorithms information and communication technology

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Research of Energy Detection Method in Spectrum Sensing in Cognitive Radio Networks

Research of Energy Detection Method in Spectrum Sensing in C...

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International Conference on information Science and Communications technologies (ICISCT)

作者： Ernazar Reypnazarov Halimjon Khujamatov Doston Khasanov Zamira Allamuratova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Computer Enjineering Faculty Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Data Communication Networks and Systems Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Information-Computer Technologies and Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper presents the threshold value determination model, its implementation algorithm, and the characteristics of the threshold value depending on the probability of false signal detection, developed for the purpose of researching the method of energy determination in spectrum sensing in cognitive radio networks. Also, the main methods of single-band spectrum sensing in cognitive radio networks were initially studied in the article, and the main spectrum detection algorithms were comparatively analyzed.

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Promising Developments in Cyber Physical System Tools for Background Monitoring of Reserve Landscape 11

Promising Developments in Cyber Physical System Tools for Ba...

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11th International Conference on Advanced computer information technologies, ACIT 2021

作者： Nykolaychuk, Yaroslav Grynchychyn, Taras Pitukh, Ihor Petrashchuk, Yaroslav Nykolaychuk, Lyubov Hryha, Volodymyr West Ukrainian National University Department of Specialized Computer Systems Ternopil Ukraine Nadvirna Vocational College by National Transport University Department of Programming and Information Technologies Nadvirna Ukraine Gorgany Nature Reserve Nadvirna Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Social Communication and Law Ivano-Frankivsk Ukraine Vasyl Stefanyk Precarpathian National University Department of Computer Engineering and Electronics Ivano-Frankivsk Ukraine

Experience in designing and building cyber physical interactive distributed monitoring systems for industrial facilities and reserve landscapes is analyzed. Advantages of the existing interactive and dialogue computerized systems, replicated by many companies, are systematized and their functional limitations are determined. The legal and system requirements for the implementation of this class of information system components, which can be applied in strict Nature Reserve, are clarified. It is proposed to expand the functionality and increase the reliability of the ring-star system for background monitoring of nature reserves based on binary-manipulated optical signals. A sensor system for measuring the height of snow cover along the monitoring route is developed using a relay sensor network and quadcopters. © 2021 IEEE.

关键词： Cyber Physical System

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Design of Intelligent Decision Support System With Ensembled Machine Learning to Predict Students' Performance

Design of Intelligent Decision Support System With Ensembled...

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Communication, computer Sciences and Engineering (IC3SE), International Conference on

作者： S Deepan Dineshkumar Rajendran Navdeep Dhaliwal K Praveena Melanie Lourens Anandhi R J School of CS & AI SR University Warangal Telangana India Computer Games Design and Programming School of Computing and Innovative Technologies British University Vietnam Vietnam Lovely Professional University Phagwara India Institute of Aeronautical Engineering Dundigal Hyderabad Deputy Dean Faculty of Management Sciences Durban University of Technology South Africa Department of Information Science Engineering New Horizon College of Engineering Bangalore

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various features related to fundamental student traits and behaviours that manage massive amounts of data efficiently processes these. To handle student records that included information about students' behaviour and how it related to their academic performance, the companies employed models of classification with mining concepts. Additionally, the quality of result classification can be substantially improved by using learning analytics and Educational Data Mining (EDM). The educational establishments are making an effort to lower the low student performance. To address this issue, numerous methods for assessing student performance have been devised, allowing the relevant faculties to intervene and enhance the final product. Three classes—Low Performance Student, Average Student, and Smart Student—were created using the K-Mean Clustering methodology for classifying student records. Features including grade point, number of deficits, student attendance, medium of education, and board of education are taken into account when classifying the data. In this case, the WEKA tool is also utilized for implementing the model and outcome assessments.

关键词： Deep learning Decision support systems Analytical models Data analysis Automation Education Companies

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Application of computer-Aided technologies for Analysis if Statistical Data of Collectors Wearing Measurements and for Diagnosis of Traction Motors

Application of Computer-Aided Technologies for Analysis if S...

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2020 International Multi-Conference on Industrial Engineering and Modern technologies, FarEastCon 2020

作者： Zolkin, A.L. Magomedov, I.A. Kucher, O.V. Povolzhskiy State University of Telecommunications and Informatics Computer and Information Sciences Department Samara Russia Chechen State University Programming Information and Communication Technologies Department Grozny Russia Kuban State Agricultural University Named after I.T. Trubilin Economic Cybernetic Department Krasnodar Russia

ISBN: (纸本)9781728169514

This article is dedicated to the study of an integrated approach to technological process of control of measurement of wearing parameters of traction electric motor collectors. Also the article presents the results of studies on the organization of an automated calculation and control system for the wearing of traction electric motor collectors at the stage of their repair using modern software. Special software product that allows to perform quick and truthful calculation of the wearing parameters of traction electric motor collectors depending on their run distance is proposed for implementation. After the entering of initial values, the statistical dependence of the collector diameter and its wearing on the run distance of the locomotive as well as theoretical distribution are calculated. The comparability of the theoretical and empirical distributions and sample regression coefficients that reflect the degree of connection between the theoretical and empirical distributions are estimated. © 2020 IEEE.

关键词： Traction motors

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Structure and Functioning of information Systems of Background Monitoring of Landscape Elements of Gorgany Nature Reserve 10

Structure and Functioning of Information Systems of Backgrou...

引用

10th International Conference on Advanced computer information technologies, ACIT 2020

作者： Nykolaychuk, Yaroslav Petrashchuk, Yaroslav Slobodian, Olena Pitukh, Ihor Grynchyshyn, Taras Nykolaychuk, Lyubov Hryha, Volodymyr Ternopil National Economic University Department of Specialized Computer Systems Ternopil Ukraine Gorgany Nature Reserve Nadvirna Ukraine Nadvirna College by National Transport University Department of Programming and Information Technologies Nadvirna Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Social Communication and Law Ivano-Frankivsk Ukraine Vasyl Stefanyk Precarpathian National University Department of Computer Engineering and Electronics Ivano-Frankivsk Ukraine

This paper discusses the structural organization of the background monitoring system (BMS) of the transboundary UNESCO World Heritage Site 'Beech forests of the Carpathians and ancient beech forests of Germany' using actual data and information from Gorgany Nature Reserve in Ivano-Frankivsk, Ukraine. The features of the structure and functions of background monitoring of the protected natural resources, forests and wildlife of Gorgany Nature Reserve is based on modern methods of collecting and processing of digital data, implementation of the principles of Internet of Things and cloud technologies, combined with GPS-systems, sensor networks with the use of optical and fiber-optic telecommunication channels. The information technology of the background monitoring system is based on figurative cluster models of monitoring objects according to theoretical principles of statistical, correlatory, spectral, cluster, logic-statistical and entropy analysis. © 2020 IEEE.

关键词： Sensor networks

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Special Processors Simulation for Forming and Digital Processing of Error-Correcting Codes in computer Systems

Special Processors Simulation for Forming and Digital Proces...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and computer Science

作者： Taras Grynchyshyn Volodymyr Hryha Artur Voronych Mykhaylo Ilko Department of Programming and Information Technologies National Transport University Nadvirna UKRAINE Department of Computer Engineering and Electronics Vasyl Stefanyk Precarpathian National University Ivano-Frankivsk UKRAINE Department of Computer System and Networks Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk UKRAINE

ISBN: (数字)9781728155661

ISBN: (纸本)9781728155678

The methods of digital and pulse signal modulation in modern computer systems of data transmission are analysed. Process of forming non-redundant coding that use the errors detection and correction in the Galois basis are offered. Structures of special processors for forming signal correcting codes are built. Working algorithms for proposed coding methods are developed and their software implementation are offered. Circuit design of Galois code sequence generator is implemented. Work simulation and synthesis on FPGA of Xilinx are performed.

关键词： digital signal processing chips encoding error correction codes error detection codes field programmable gate arrays Galois fields logic design microprocessor chips Error correction codes Field programmable gate arrays digital signal processing chips error detection codes computer systems Galois fields Microprocessor chips Logic design coding Forming Galois sequence generator Digital signal processing

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Virtual Keyboard and Fingers

Virtual Keyboard and Fingers

引用

International Conference on information Science and Communications technologies (ICISCT)

作者： Bakhrom Kabulov Nadira Tashpulatova Marguba Akbarova Department of Applied Mathematics Joint-stock Company "Uzneftegazinformatika" Tashkent Uzbekistan Department of Information science and Computer Graphic Tashkent University of Information Technologies Tashkent Uzbekistan Department of System and applied programming Tashkent University of Information Technologies Tashkent Uzbekistan

ISBN: (数字)9781728125640

ISBN: (纸本)9781728125657

The problem of data entry in mobile devices is considered. The shortcomings of virtual projected keyboards are analyzed. The new input technology called VKF (Virtual Keyboard and Fingers) is offered. It is shown that VKF is more convenient not only in comparison with projected virtual keyboards, but also with data entry methods including use of on-screen keyboards.

关键词： Keyboards Virtual reality Human computer interaction Mobile handsets

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Structure and Functioning of information Systems of Background Monitoring of Landscape Elements of Gorgany Nature Reserve

Structure and Functioning of Information Systems of Backgrou...

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International Conference on Advanced computer information technologies (ACIT)

作者： Yaroslav Nykolaychuk Yaroslav Petrashchuk Olena Slobodian Ihor Pitukh Taras Grynchyshyn Lyubov Nykolaychuk Volodymyr Hryha Department of Specialized Computer Systems Ternopil National Economic University Ternopil Ukraine Gorgany nature reserve Nadvirna Ukraine Department of Programming and Information Technologies Nadvirna College by National Transport University Nadvirna Ukraine Department of Social Communication and Law Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Department of Computer Engineering and Electronics Vasyl Stefanyk Precarpathian National University Ivano-Frankivsk Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

This paper discusses the structural organization of the background monitoring system (BMS) of the transboundary UNESCO World Heritage Site “Beech forests of the Carpathians and ancient beech forests of Germany” using actual data and information from Gorgany Nature Reserve in Ivano-Frankivsk, Ukraine. The features of the structure and functions of background monitoring of the protected natural resources, forests and wildlife of Gorgany Nature Reserve is based on modern methods of collecting and processing of digital data, implementation of the principles of Internet of Things and cloud technologies, combined with GPS-systems, sensor networks with the use of optical and fiber-optic telecommunication channels. The information technology of the background monitoring system is based on figurative cluster models of monitoring objects according to theoretical principles of statistical, correlatory, spectral, cluster, logic-statistical and entropy analysis.

关键词： Monitoring Forestry Correlation Optical fiber sensors Optical fibers Biological system modeling

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Method for calculating of R-learning traffic peakedness 4

Method for calculating of R-learning traffic peakedness

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4th International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S and T 2017

作者： Kuchuk, Nina Mozhaiev, Oleksandr Mozhaiev, Mykhailo Kuchuk, Heorgii Department of Computer Science Faculty V.N. Karazin Kharkiv National University Kharkiv Ukraine Department of Information Technologies Kharkiv National University of Internal Affairs Kharkiv Ukraine Laboratory on Speech and Audio Computer Engineering and Telecommunication Kharkov SRI examinations named Dist. prof. N.S. Bokariusa Kharkiv Ukraine Department of Computer science and programming National Technical University Kharkiv Polytechnic Institute Kharkiv Ukraine

ISBN: (纸本)9781538609835

In this article e-leaming traffic which is served by system on the hyper convergent platform is considered. It was done the analysis of the known methods of determine the degree of pulsation of traffic. The method for calculating of e-learning traffic peakedness is proposed. Simulation and calculation results peakedness is analyzed. © 2017 IEEE.

关键词： E-learning

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