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检索条件"机构=Computer Programming Department"

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Application-based spam detection with machine learning algorithms 27

Application-based spam detection with machine learning algor...

引用

27th International Conference on Information Society and University Studies, IVUS 2022

作者： Erbey, Ali Barışçı, Necaattin Uşak University Distance Education Vocational School Department of Computer Programming Uşak Turkey Gazi University Faculty of Technology Department of Computer Engineering Ankara Turkey

We investigated the process of unsupervised generative learning and the structure of informative generative representations of images of handwritten digits (MNIST dataset). Learning models with the architecture of sparse convolutional autoencoder with constraints to produce low-dimensional representations achieved successful generative learning demonstrated by high accuracy of generation of images. A well-defined, continuous and connected structure of generative representations was observed and described. Structured informative representations of unsupervised generative models can be an effective platform for investigation of origins of intelligent behaviors in artificial and biological learning systems. © 2022 Copyright for this paper by its authors.

关键词： Neural networks

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Models and algorithms for determining the probability of occurrence of a critical combination of events for three-element minimum sections in intelligent decision support systems 4

Models and algorithms for determining the probability of occ...

引用

4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Kolomiitsev, Oleksii Osiievskyi, Serhii Zakharchenko, Iryna Rybalchenko, Alina Tretiak, Viacheslav Heiko, Hennadii Computer Engineering and Programming Department National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Department of Mathematics and Software of ACS Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

A method for determining the probability of occurrence of a critical combination of events for the three-element minimum cross-sections of attributes of the characteristics of the software quality model of intelligent... 详细信息

ISBN: (纸本)9798350395532

关键词： Decision support systems

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Method of Assessing the Impact of External Factors on Geopositioning System Operation Using Android GPS API 16

Method of Assessing the Impact of External Factors on Geopos...

引用

16th IEEE International Conference on computer Science and Information Technologies, CSIT 2021

作者： Hovorushchenko, Tetiana Pavlova, Olga Avsiyevych, Volodymyr Computer Engineering and System Programming Department Khmelnytskyi Ukraine

ISBN: (纸本)9781665442572

The main methods of analysis the accuracy of the geolocation system were studied. The aspects of technology for obtaining geographical coordinates using Google geolocation system (GPS) were considered. The best method of obtaining data from satellites was searched. Today the geolocation system has become widely used in many industries, such as military, aviation, maritime, navigation of ordinary users. Also, a significant spread of this technology is noticed in many geographical areas, such as cartography, geodesy and is an area of interests of many scientists. A mobile app based on Android platform for conducting the experiments to determine the accuracy of geolocation services in the form of Web Quests was developed. © 2021 IEEE.

关键词： Global positioning system

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Modeling of DC Traction Motor In Ansys RMXPRT 4

Modeling of DC Traction Motor In Ansys RMXPRT

引用

4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Herasymenko, Vitalii Zakovorotnyi, Oleksandr Pliuhin, Vladyslav Mezentsev, Mykola Noskov, Valentyn Orlova, Tetyana Department of Electric Transport O. M. Beketov National University of Urban Economy in Kharkiv Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Department of the Systems of Electricity Supply and Electricity Consumption of Cities O. M. Beketov National University of Urban Economy in Kharkiv Kharkiv Ukraine Computer Engineering and Programming Department National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine

ISBN: (纸本)9798350395532

DC traction motors are widely used in all branches of urban economy. They began to be used in industry about a hundred years ago with the advent of the first calculation methods. When designing a DC motor, it is important to consider it comprehensively, together with the electric drive system. The article discusses the application of a more correct approach to modeling a series-excited DC motor using the ANSYS software package, in particular, the ANSYS RMxprt/Maxwell/Simplorer bundle. The main stages of initial data input are considered and the main calculation results are shown. Using ANSYS Maxwell allows you to quickly and automatically build a typical machine geometry using RMxprt. When solving non-standard structures, it is possible to use 3D design with step-by-step elements. The analysis of the obtained graphic dependences of electric power parameters makes it possible to judge the efficiency of the electric motor and its operational properties in idling and under load. The simulation results show excellent agreement with the data obtained experimentally. © 2023 IEEE.

关键词： Efficiency

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Optimization of Neural Network Calculations Using Integer Arithmetic

Optimization of Neural Network Calculations Using Integer Ar...

引用

Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Oleksandr Zakovorotnyi Andrii Khulap Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

Most of the sensor devices in the Internet of Things systems are based on energy-efficient microcontrollers, the computing resources of which are limited, as well as the amount of available memory. Increasing the security of the use of such devices with the help of neural networks is an important and urgent problem. The article describes the possibility of using artificial neural networks in small microcontrollers with limited resources. The purpose of this work is to check the possibility of calculating neural networks based on integer arithmetic to reduce the time of calculating a neural network and eliminate data normalization operations, as well as to evaluate the feasibility of using such neural networks in the field of security of the Internet of Things in comparison with traditional methods, such as black lists and white lists. The following results were obtained: when switching to integer arithmetic, compared to floating point, the accuracy of the result calculations is within the permissible error of neural network training, that is, it has not changed. Execution time decreased by $30-96 \%$ , depending on the architecture of the microcontroller. The program size is reduced by $22-48 \%$ , also depending on the microcontroller architecture. Conclusions: the possibility and expediency of using neural networks optimized for microcontrollers with limited resources was proved. This will increase the security of Internet of Things systems, especially against device authentication threats and intrusion detection. Prospects for further research are determined.

关键词： Training Microcontrollers Neural networks Memory management Intrusion detection Switches Security Internet of Things Optimization Arithmetic

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Academic Fraud Detection in Online Exams with DNN's Multilayer Model

Academic Fraud Detection in Online Exams with DNN's Multilay...

引用

International Symposium on Digital Forensic and Security (ISDFS)

作者： Bahaddin Erdem Murat Karabatak Department of Computer Programming Bitlis Eren University Bitlis Turkey Department of Software Engineering Firat University Elaziğ Turkey

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

This study aims to reveal the best deep learning models that are improved and optimized by predicting undesirable behavior patterns using a dataset consisting of artificial and real exam data of students taking online distance education courses in an online environment through the distance education system. Using online exam data of 129 students, the researchers conducted analysis with two different scenarios to determine the best prediction performance through regression and classification models. The model we proposed was determined as a four-layer DNN with 80.4% test performance in detecting students who “cheated” from undesirable behavior patterns, which was performed with K-10, K-5 and K-3 cross-validation. The results prove that students' online distance education exam data can be easily applied to the DNN model. The models presented in the study provide a roadmap for educational institutions to evaluate their online examination practices and develop more effective strategies for academic honesty.

关键词： Deep learning Analytical models Digital forensics Predictive models Nonhomogeneous media Data models Educational courses Fraud Security

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Model Based Development Methodology in Compliance with ISO 26262 for Safe Automotive ECU

Model Based Development Methodology in Compliance with ISO 2...

引用

Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Muhammad Ikram Hafiz Department of Computer Architecture and System Programming University of Kassel Kassel Germany

This work presents a practical approach of designing a functionally safe ECU for automotive application by implementing the Model Based Development (MBD) methodology. Functional safety (FuSa) in automotive can be achieved by strictly following the processes of electrical and electronic systems development as given in the ISO 26262. The scope of FuSa encompasses the risks emerging from systematic failures and random hardware failures. One approach to mitigate these failures is the Model Based Development (MBD) on which the ISO 26262 provides guidance. This approach enables to model an ECU and accelerates an IP creation by automatic RTL code generation for rapid prototyping on an FPGA level. In this work the MBD is implemented in accordance to the ISO 26262 to design and test a hardware model of an embedded ECU. The embedded Design under Test (DUT) is simulated and its output verified in Matlab/Simulink. Upon successful results, the RTL codes of the DUT are generated for a target FPGA. The RTL codes are simulated and the functionality of the DUT is verified at the FPGA level.

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Detection computer Network Intrusion Using Deep Neural Networks

Detection Computer Network Intrusion Using Deep Neural Netwo...

引用

Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Vadym Poltoratskyi Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

In this work, the effectiveness of using classical machine learning methods and modern deep neural network models for intrusion detection in computer networks has been investigated. The purpose of this work is to develop a model for detecting intrusions into computer networks based on the Transformer model using tabular input data. In this work, the UNSW-NB15 dataset is used as the source data. This dataset contains information about normal network behaviour as well as during synthetic intrusions. Models for intrusion detection in computer networks based on machine learning methods were investigated: Decision Tree, KNN, Logistic Regression, SVM, Gradient Boosting, Random Forest. A method of converting tabular data into images was developed, which made it possible to build intrusion detection models based on Vision Transformer and Vision Transformer for small-size datasets on modern Transformer architecture. The research results showed that developed model based on Vision Transformer and Vision Transformer for small-size datasets improves the quality of identification, and eliminates the need for a preprocessing step such as dimensionality reduction.

关键词： Support vector machines computer vision Computational modeling Intrusion detection Artificial neural networks Forestry Transformers Data models computer networks Regression tree analysis

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Optimization on Cognitive Models 15

Optimization on Cognitive Models

引用

15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Solomatin, A.N. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

The concept of acceptable systems with a limited level of systemic pathologies and dysfunctions is considered. The main provisions of cognitive modeling are given and the tasks of single- and multi-criteria optimizati... 详细信息

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

关键词： Pathology

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Heterogeneous Ensemble Classifier in Medical Decision Support Systems

Heterogeneous Ensemble Classifier in Medical Decision Suppor...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Anatol y Povoroznyuk Oksana Povoroznyuk Anna Filatova Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The work is devoted to solving the current scientific and technical problem of constructing a diagnostic decision support system in medicine based on a heterogeneous ensemble classifier model that implements two approaches to formulating a diagnostic conclusion: a probabilistic one based on the analysis of the training sample, and expert information on the structure of symptom complexes. The choice of prototype matching method as a probabilistic component is justified. Formalization of expert information on the structure of symptom complexes was carried out by representing symptom complexes of diseases with numerical intervals of linguistic variables. Options for taking into account expert assessments about the structure of symptom complexes in an ensemble classifier are considered. Test verification of the developed classifier was done on real medical data and confirmed the effectiveness of its work.

关键词： Decision support systems Training Analytical models Prototypes Linguistics Probabilistic logic Medical diagnostic imaging Diseases

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