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8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Forghani, Majid Firstkov, Artyom Alyannezhadi, Mohammad. M. Forghani, Kazem Krasovskii Institute of Mathematics & Mechanics Mathematical Programming Lab. Yekaterinburg Russia University of Science and Technology of Mazandaran Department of Science Behshahr Iran Iran University of Science and Technology Computer Science Department Tehran Iran

ISBN: (纸本)9781665476232

The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care;molecular biology & immunology;and phylogenetic & epidemiological studies. © 2022 IEEE.

关键词： Database systems

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Advanced IOT Traffic Light Control System 5

Advanced IOT Traffic Light Control System

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5th International Conference on Advances in Computational Tools for Engineering Applications, ACTEA 2023

作者： Hamad, Martin Abou El Hajj, Antonio Daou, Roy Abi Zeid Hayek, Ali Haidar, Gaby Abou Lebanese German University Faculty of Public Health Biomedical Technologies Department Lebanon MART Learning Education and Research Center Lebanon University of Kassel Department of Computer Architecture and System Programming Kassel Germany American University of Science and Technology Engineering Faculty Zahle Lebanon

ISBN: (纸本)9798350309959

For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more and more critical, and if not treated smartly this issue will negatively affect drivers by wasting time and fuel gas while waiting for hours in lanes. This paper presents a new and smart way to mitigate this issue in an affordable cost, minimum processing power, and low power consumption. This concept takes into consideration the majority of the cases that may cause congestion and presents a smart and accurate outputs to ease traffic flow leading to the prediction of the peak hours of traffic congestion for smarter control. A model is designed to study the case of a four lanes crossroad with two traffic lights and two LCD monitors. The strategy in reading data is divided into two parts: real data from sensors and pre collected data from google maps to create a kind of a predicted pattern over a certain time interval. The responsiveness of the system is analyzed thoroughly, and the accuracy of all possible cases is carefully considered and evaluated. Each part of the system was tested alone, and the overall system is still in an ongoing testing phase. The results have shown minimum faulty errors and accepted outputs that can lead to safe traffic control decisions. Finally, integrating more IoT devices and sensors between V2V, V2P, V2I with the help of artificial intelligence will definitely optimize this system with higher accuracy. © 2023 IEEE.

关键词： Traffic congestion

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Bi-level programming for Stackelberg Game with Intuitionistic Fuzzy Number: a Ranking Approach

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Journal of the Operations Research Society of China 2021年第1期9卷 131-149页

作者： Sumit Kumar Maiti Sankar Kumar Roy School of Applied Sciences and Humanities Haldia Institute of TechnologyPurba MidnaporeWB 721657India Department of Applied Mathematics with Oceanology and Computer ProgrammingVidyasagar UniversityMidnaporeWB 721102India

This paper introduces a ranking function procedure on a bi-level programming for Stackelberg game involving intuitionistic fuzzy *** fuzzy num-ber is considered in many real-life situations,so it makes perfect sense to address decision-making problem by using some specified intuitionistic fuzzy *** this paper,intuitionistic fuzziness is characterized by a normal generalized triangular intuitionistic fuzzy number.A defuzzification method is introduced based on the pro-portional probability density function associated with the corresponding membership function,as well as the complement of non-membership *** the proposed ranking technique,a methodology is presented for solving bi-level programming for Stackelberg *** application example is provided to demonstrate the applica-bility of the proposed methodology,and the achieved results are compared with the existing methods.

关键词： Bi-levelprogramming Triangular intuitionistic fuzz ynumber Ranking function Nonlinear programming Optimal solution

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Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic

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Materials Today: Proceedings 2022年 56卷 2213-2216页

作者： Boddu, Raja Sarath Kumar Karmakar, Partha Bhaumik, Ankan Nassa, Vinay Kumar Vandana Bhattacharya, Sumanta Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India Government of West Bengal Bikash Bhawan Salt Lake W.B. Kolkata India Dept. of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore India Department of Computer Science Engineering South Point Group of Institutions Sonepat Haryana India Department of Mathematics Dasmesh Khalsa College Zirakpur India Department of Science and Technology and Biotechnology MAKAUT India

Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic

关键词： COVID-19

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Design and Implementation of an EMG-based System for Monitoring and Help Request

Design and Implementation of an EMG-based System for Monitor...

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2022 International Conference on Smart Systems and Power Management, IC2SPM 2022

作者： Zeine, Carla Daou, Roy Abi Zeid Telawi, Samer Boercsoek, Josef Hayek, Ali Haidar, Gaby Abou University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Kassel Germany Lebanese German University Faculty of Public Health Jounieh Department of Computer Architecture and System Programming Biomedical Technologies Department Jounieh Lebanon Université la Sagesse Faculty of Engineering Furn El Chebbak Mechatronics Department Beirut Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany American University of Science and Technology Faculty of Engineering Zahle Lebanon

ISBN: (数字)9781665452915

ISBN: (纸本)9781665452915

Integrating electrophysiological signals in larger systems is getting wider due to the fact that such modalities facilitate the daily tasks of users. However, the high cost of monitoring systems (e.g., oscilloscopes) limits the testing and analysis of the acquired signal from such noisy systems (i. e., electrophysiological devices). The proposed system is a part of a larger proj ect that deals with the identification of sign language movements through the use of Muscle-computer Interfaces. On one hand, the user is able to display the signal acquired by the electrodes on an LCD screen. On the other hand, the system helps a mute patient to issue a special message to his surrounding environment that does not know the sign language to ask for help. The second feature is not unique, as it can be replaced by any other application based on the user's needs. The system was tested on several persons, and the results are promising. © 2022 IEEE.

关键词： Liquid crystal displays

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Creating a Dynamic Online Learning Environment with AI Integration

Creating a Dynamic Online Learning Environment with AI Integ...

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International computer Sciences and Information Technologies (CSIT)

作者： Oleksandra Bulgakova Zarina Viniarska Viacheslav Zosimov P.M Platonov Educational and Scientific Institute of Computer Engineering Automation Robotics and Computer Programming Odesa National University of Technology Odesa Ukraine Department of Applied information systems Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

Educational, online learning has become a common practice due to rapid digitalization and recent global events. This study focuses on developing a comprehensive online learning platform that addresses users' needs by integrating advanced AI capabilities for personalized support and adaptive learning. The platform supports user registration and authentication, course and lesson management, and offers interactive features like AI-driven chat support. In this study, we show the importance of creating user-friendly online learning platforms with the implementation of modern AI trends. The development and testing of this platform is ongoing to determine the adaptation of the system to different learning styles.

关键词： Adaptive learning Electronic learning Authentication Passwords Market research Real-time systems Artificial intelligence Information technology Standards Testing

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Multi-criteria Radio Frequency Identification Approach for Manufacturing Company Selection Based on Partitioned Maclaurin Symmetric Mean Operators Under Complex Intuitionistic Fuzzy Set Environment

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International Journal of Fuzzy Systems 2024年第5期26卷 1730-1748页

作者： Azam, Muhammad Jana, Chiranjibe Khan, Muhammad Sajjad Ali Pal, Madhumangal Xin, Qin Yang, Shilin Sarkar, Biswajit Faculty of Science Beijing University of Technology Beijing100022 China Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Mathematics Khushal Khan Khattak University Karak Khyber Pakhtunkhwa Karak27200 Pakistan Faculty of Science and Technology University of the Faroe Islands Tórshavn Faroe Islands Department of Industrial Engineering Yonsei University 50 Yonsei-ro Sinchon-dong Seodaemun-gu Seoul03722 Korea Republic of Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu 600077 Chennai India Department of Industrial Engineering and Management National Taipei University of Technology Taipei City 106344 Taiwan Chennai602105 India

The theory of intuitionistic fuzzy sets (IFSs) plays an essential role to deal with uncertainty and ambiguity. However, the IFSs deal only with anticipation, not periodicity. But, complex IFSs (CIFS) can handle both uncertainties and periodicity at a time. Therefore, this paper focuses on a new multi-criteria decision making (MCDM) approach using Maclaurin symmetric mean (MSM) operator in connection with the CIFS setting. Then, we develop some CIF partitioned based MSM (CIFPMSM) operators and their weighted form by considering that all the criteria can be arranged into some groups. The proposed operators not only deal with the interrelationship among criteria but also deal with the partitioned relationship among criteria. We discuss the properties of these proposed operators and investigate their cases. Finally, a decision-making approach for radio frequency identification (RFID) for manufacturing companies is developed based on the proposed operators and compared the results with the existing method to show the application and feasibility of the proposed method. © The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association 2024.

关键词： Decision making

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A blockchain-oriented covert communication technology with controlled security level based on addressing confusion ciphertext

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Frontiers of computer Science 2025年第2期19卷 133-135页

作者： Lejun ZHANG Bo ZHANG Ran GUO Zhujun WANG Guopeng WANG Jing QIU Shen SU Yuan LIU Guangxia XU Zhihong TIAN Sergey GATAULLIN Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China Research and Development Center for E-Learning Ministry of EducationBeijing 100039China College of Information Engineering Yangzhou UniversityYangzhou 225009China School Math and Computer Science Quanzhou Normal UniversityQuanzhou 362000China Pazhou Lab Guangzhou 510330China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of SciencesMoscow 117418Russia Industrial Programming Department MIREA-Russian Technological UniversityMoscow 119454Russia

1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods also exist,such as peer-to-peer networks and distributed hash *** technology,which is decentralized,anonymous,non-tamperable and anti-attack,can be applied to covert communication to solve the problems of traditional methods and improve the quality of communication.

关键词： communication tables networks

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Cyclic Quasi-Orthogonal Matrices in Image and Signal Encoding

Cyclic Quasi-Orthogonal Matrices in Image and Signal Encodin...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Sergeev Alexandr Department of computer technology and programming Saint Petersburg State University of Aerospace Instrumentation Saint Petersburg Russia

orthogonal and quasi-orthogonal matrices with a limited number of element values and structured in some way are of considerable interest for many technical applications related to image processing and signal coding. The paper classifies and considers cyclic matrices and matrices with cyclic blocks. Descriptions of noise-resistant encoding methods of images and their protective masking using such matrices are given. Based on the analysis of the autocorrelation functions of new code sequences obtained from strings of modified cyclic quasi-orthogonal matrices and the simulation performed, numerical values of the quality parameters of the new code sequences are given. It is shown that their application makes it possible to reduce the maximum level of the side lobe of the aperiodic autocorrelation function, which allows us to conclude that their application is promising and that signal coding algorithms can be revised.

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Word-Based Turkish Lip Reading System with Two Stream 3dcnn and Bilstm

SSRN

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SSRN 2023年

作者： Erbey, Ali Barışçı, Necaattin Department of Computer Programming Distance Education Vocational School Usak University Usak64200 Turkey Department of Information Systems Informatics Institute Gazi University Ankara Turkey Department of Computer Engineering Faculty of Technology Gazi University Ankara06500 Turkey

Lip reading is a technique that aims to understand spoken words by analyzing people's lip movements. Deep learning algorithms are used as a powerful tool for detecting and recognizing lip movements more accurately. In this study, we present a lip-reading architecture for the Turkish language. The architecture is trained to recognize Turkish words using 3DCNN (3D Convolutional Neural Network) architecture and two-stream deep learning methods. The model was trained on video data representing lip movements and learned to classify words accurately. The Turkish lip reading system has been trained and tested on a large Turkish lip reading dataset. In the experiments, an accuracy of 87.12% was achieved with the proposed model, indicating successful results in the Turkish language. The proposed model demonstrates high accuracy rates in recognizing Turkish words, showcasing its effectiveness. This paper introduces a novel architecture, a lip-reading system that employs deep learning techniques, providing a robust tool for successful Turkish lipreading applications. © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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