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Correction to: Estimation of most effected cycles and busiest network route based on complexity function of graph in fuzzy environment

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Artificial Intelligence Review 2023年第12期56卷 15567-15567页

作者： Ghorai, Ganesh Poulik, Soumitra Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

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Intelligent Agent for Support of Decision Making on Civil Law Regulation of Contract for the Provision of in Vitro Fertilization 15

Intelligent Agent for Support of Decision Making on Civil La...

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15th IEEE International Scientific and Technical Conference on computer Sciences and Information Technologies, CSIT 2020

作者： Hovorushchenko, Tetiana Herts, Alla Hnatchuk, Yelyzaveta Computer Engineering and System Programming Department Khmelnytskyi Ukraine Ivan Franko National University of Lviv Civil Law and Legal Proceedings Department Lviv Ukraine

ISBN: (纸本)9781728174433

Nowadays in Ukraine, there is a need for automation and removal of human from the processes of decision making on civil law regulation of contract for the provision of in vitro fertilization, which can significantly increase the correctness of the concluded contract in terms of civil law and medical law. So, the purpose of this study is the development of an intelligent agent for support of decision making on civil law regulation of contract for the provision of in vitro fertilization. The method of activity of intelligent agent for support of decision making on civil law regulation of contract for the provision of in vitro fertilization was first developed in this paper, which concludes that the content of the contract for the provision of in vitro fertilization is correct or incorrect, as well as a recommendation to conclude a contract (if its content is correct) or to revise the contract (if its content is incorrect). © 2020 IEEE.

关键词： Decision making

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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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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Alexander Chernikov Elena Smirnova Oleg Zhavoronkov Higher School of Automation and Robotics Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Department of System Programming Saint Petersburg State University St. Petersburg Russia Computer Vision Systems LLC St. Petersburg Russia

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation – 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526.

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Fixed-Charge Solid Transportation Problem with Budget Constraints Based on Carbon Emission in Neutrosophic Environment

Research Square

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Research Square 2021年

作者： Ghosh, Shyamali Roy, Sankar Kumar Verdegay, Jose Luis Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India Department of Computer Science and Artificial Intelligence University of Granada Granada Spain

This paper is to integrate among solid transportation problem, budget constraints and carbon emission with probable maximum profit. The limits of air pollution and climate variation are solely dependent by exerting CO2 gas and rest greenhouse gases due to myriad transportation system. Henceforth, it is our apt mission to minimize carbon emission for pollution free environment. Again transportation system with single objective is hardly applicable to the situation with more than one criterion. Therefore multi- objective decision making is incorporated for designing real-life transportation problem. Due to time pressure, data limitation, lack of information or measurement errors in practical problems, there exist some hesitations or suspicions. Based on the fact, decision maker considers indeterminacy in the designed problems. To overcome the restriction on occurrence and non-occurrence of fuzzy and intuitionistic fuzzy, neutrosophic set is very important and suitable to accommodate such general structure of problems. Therefore neutrosophic environment with neutrosophic linear programming, fuzzy programming and global criterion method are profiled to search the compromise solution of the multi- objective transportation problem (MOTP). Thereafter, the performance of the considered model is useful by evaluating a numerical example;and then the derived results are compared. Finally sensitivity analysis and conclusions with upcoming works of this research are stated hereafter. © 2021, CC BY.

关键词： Greenhouse gases

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research Institute - GIRI.

关键词： Malware

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Design and Implementation of a QoL Improvement System for Visually Impaired Patients

Design and Implementation of a QoL Improvement System for Vi...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Roy Abi Zeid Daou Jad Beaino Johnny Hawat Ramy Ibrahim Ali Hayek Josef Boercsoek Jose Javier Serrano Olmedo Mechatronics department Faculty of Engineering Université La Sagesse Beirut Lebanon MART Learning Education and Research Center Chananir Lebanon Department Lippstadt 2 Hardware Engineering University of Applied Science Hamm-Lippstadt Hamm Department of Computer Architecture and System Programming Faculty of Electrical Engineering/Computer Science University of Kassel Germany Lab of Bioinstrumentation and Nanomedicine Centro de Tecnología Biomédica Universidad Politécnica de Madrid Spain

Visually impaired people encounter several challenges in their mobility and navigation. Their daily activities are obstructed due to their inability to adapt or recognize accurately their surroundings, especially outside their house which they are more familiar with. Thus, it becomes the main reason of accidents, falling off, getting lost in unknown areas, etc. Furthermore, one of the sensory systems that helps the body to process data about the external environment is the visual system. Blind people also lose touch with the outside world, develops poor motor habits, which results in postural problems as a result. This project will assist visually impaired people in their daily life and simplify normal tasks through a system combining two previously designed projects, “Smart Shoes for Blind and Visually Impaired People”, and “Human posture monitoring device”. The multifunctional system is developed with the goal of securing safe movements for visually impaired people as well as maintaining a good back posture by detecting leaning postures (LP). The purpose of the smart shoe is to identify obstacles and protect the user from unintended accidents. A compatible Android application has been developed to alert the user when there is an obstruction or when he is walking on a wet surface. Voice alarms will be used to acoustically alert the user. If the user collapses, a message with their position will be sent right away to a relative. On the other hand, the smart vest will identify the position of the user's back and alert him to maintain a straight posture through the same application as well. As the system is dealing with human health, some safety measurements would be taken into consideration to implement a safe electrical system in order to reduce error and to increase accuracy.

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Research on Reasonable Color Matching Method of Interior Decoration Materials Based on Image Segmentation

Research on Reasonable Color Matching Method of Interior Dec...

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International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： Lokesh Kalapala Raghunandan K R D. Shyam Saravanan R K Krishnakumar C. Sivasankar Department of Mechanical Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India Department of Computer Science and Engineering NMAM Institute of Technology Nitte (Deemed University) Karnataka India Department of EEE Rajalakshmi Engineering College Thandalam Chennai Department of ECE PSNA College of Engineering and Technology Dindigul Tamilnadu India Department of Programming Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India

In recent years, with the continuous growth of social and economic level, people's living standard has also been constantly improved. Under this background, contemporary people highly respect a good living environment, and the importance of building interior decoration engineering has been fully reflected. As one of the important design contents of interior decoration, the use level and effect of color will directly affect the overall visual effect of interior decoration and the comfort of interior space. Through the rational collocation of colors, the artistic characteristics of interior decoration can be displayed, which can also show the important role of color in interior decoration. In modern interior decoration, the use of colors is gradually enriched, and the use of multiple colors leads to the problem of actual color matching. Image segmentation, which is the premise of image recognition and tracking, divides an image into regions with different characteristics and extracts interesting objects. This technology has been widely used in military affairs, medicine, intelligent transportation, pedestrian detection, product inspection, sports, remote sensing, machine vision and other fields. Therefore, good color matching is very important in the actual interior decoration practice.

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Optimum Production through variational principle with the time quadratic demand, fuzzy time period and fuzzy integrand

arXiv

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arXiv 2023年

作者： Roul, J.N. Maity, K. Kar, S. Maiti, M. Patha Bhavana Visva-Bharati West Bengal Santiniketan731235 India Department of Mathematics M G Mahavidyalaya Bhupatinagar W.B. 721425 India Department of Mathematics National Institute of Technology W.B. Durgapur713209 India Department of Applied Mathematics with Oceanology Computer Programming Vidyasagar University W.B. Midnapore711201 India

Here a real life optimal control problem under fuzzy time period using variational principle is formulated and Solved. The unit production cost is a function of production rate and also dependent on raw material cost, development cost due to durability and wear-tear cost. The holding cost is assumed to be non-linear, dependent on time. The profit function which consists of revenue, production cost and holding cost is formulated as a Fuzzy-Final Time and Fixed State System optimal control problem with fuzzy time period. Here production rate is unknown and considered as a control variable and stock level is taken as a state variable. It is formulated to optimize the production rate so that total profit is maximum. The non-linear optimization technique-Generalised Reduced Gradient Method (LINGO 11.0) is used. The optimum results are illustrated both numerically and *** Codes 49XX Copyright © 2023, The Authors. All rights reserved.

关键词： Profitability

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