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Bipolar Picture Fuzzy Graph Based Multiple Attribute Decision Making Approach–Part I 1

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Gong, Shu Hua, Gang Department of Computer Science Guangdong University of Science and Technology Dongguan523083 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

The multiple attribute decision making (MADM) is a one of most crucial topic in decision making and computer science. The key technology for MADM is to learn the correlation between different attributes, and the graph model is an appropriate tool to analyze it. In this work, the MADM problem is formulated in the bipolar picture fuzzy graph framework, and decision making algorithms are designed to characterize the relationships among attributes. The numerical example is introduced in this paper to show how to handle the MADM problem in terms of bipolar picture graph model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy sets

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A comparative study of four nonlinear dynamic methods and their applications in classification of ship-radiated noise

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Defence technology（防务技术） 2022年第2期18卷 183-193页

作者： Yu-xing Li Shang-bin Jiao Bo Geng Qing Zhang You-min Zhang School of Automation and Information Engineering Xi’an University of TechnologyXi’an710048China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Department of Mechanical Industrial and Aerospace EngineeringConcordia UniversityMontrealQuebec H3G 1M8Canada

Refined composite multi-scale dispersion entropy(RCMDE),as a new and effective nonlinear dynamic method,has been applied in the field of medical diagnosis and fault *** this paper,we first introduce RCMDE into the field of underwater acoustic signal processing for complexity feature extraction of ship radiated noise,and then propose a novel classification method for ship-radiated noise based on RCMDE and k-nearest neighbor(KNN),termed *** results of a comparative experiment show that the proposed RCMDE-KNN classification method can effectively extract the complexity features of ship-radiated noise,and has better classification performance under one and two scales than the other three classification methods based on multi-scale permutation entropy(MPE)and KNN,multi-scale weighted-permutation entropy(MW-PE)and KNN,and multi-scale dispersion entropy(MDE)and KNN,termed MPE-KNN,MW-PE-KNN,and *** is proved that the RCMDE-KNN classification method for ship-radiated noise is feasible and effective,and can obtain a very high recognition rate.

关键词： Nonlinear dynamic Refined composite multi-scale dispersion entropy(RCMDE) Multi-scale dispersion entropy(MDE) Multi-scale weighted-permutation entropy (MW-PE) Multi-scale permutation entropy(MPE) Classification of ship-radiated noise

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Deep Learning-based Source Code Classification and Visualization of Decision Rationales 28th

Deep Learning-based Source Code Classification and Visualiza...

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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： Oeda, Shinichi Mitsumori, Seiya Department of Information and Computer Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Kisarazu City Chiba Japan Advanced Course of Control and Information Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Kisarazu City Chiba Japan

In programming education, it is crucial to provide instruction that is tailored to students' proficiency levels. For this purpose, an objective evaluation of each student's coding ability is essential. Additionally, it is necessary to understand the characteristics of source code written by both beginners and advanced students. Previous research has successfully converted the structural information of source code into graphs and assessed coding skills using deep learning, achieving high accuracy. However, it remains unclear which specific structural elements significantly influence these assessments. This study addresses this gap by transforming source code into abstract syntax trees and developing a model that uses Graph Convolutional Networks to categorize code as either beginner or advanced users based on learned structural information. Furthermore, we apply Integrated Gradients to visualize the decision-making basis of our model and elucidate the structural characteristics distinguishing source code written by beginner and advanced users. © 2024 The Authors.

关键词： Adversarial machine learning

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Decision Making Analysis of Traffic Accidents on Mountain Roads in Yunnan Province 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Gong, Shu Hua, Gang Department of Computer Science Guangdong University Science and Technology Dongguan523083 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

Bipolar objects are widespread in nature, and they describe the opposition and unity of the things. Inspired by decision making characterizing in terms of fuzzy graph structures, we propose a bipolar fuzzy graph-based case study on mountain road traffic accident analysis in Yunnan province. The bipolar membership functions on corresponding bipolar graph are proposed and a novel algorithm for mountain road traffic accident in specific area is given. We analyze the result and give a reasonable explanation for this phenomenon. Some suggestions for reducing the number of mountain traffic accident are proposed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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Computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

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A Real-Time System for Classification of Pakistan Sign Language using Machine Learning 17

A Real-Time System for Classification of Pakistan Sign Langu...

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17th International Conference on Open Source Systems and Technologies, ICOSST 2023

作者： Rahman, Muhammad Zia Ur Akbar, Muhammad Azeem Usman, Muhammad Tahir, Muhammad Hurrirah Shahzaib Riaz, Muhammad Tanveer Khan, Muhammad Abbas Lahore Faisalabad Campus Mechatronics and Manufacturing Engineering Dept. of Mechanical Faisalabad Pakistan Lappeenranta University of Technology Department of Information Technology Lappeenranta53851 Finland Lahore Faisalabad Campus Dept. of Mechatronics and Control Engineering Faisalabad Pakistan Balochistan University of Information Technology Engineering and Management Sciences Department of Electrical Engineering Quetta87300 Pakistan

ISBN: (纸本)9798350381320

Sign language is used by the deaf to interact with hearing individuals in the community. Despite the fact that sign language is often used, the general population is unaware of it, and only hearing-impaired people are familiar with its usage. In this article, we have created a system for real-Time sign language recognition in order to communicate with folks who are deaf or hard of hearing by using Pakistan Sign Language (PSL) as its sign language. Ten types or indications of PSL are differentiated in this study. Flex sensors in the glove can detect the position of certain fingers. The MPU-6050, a micro-electro-mechanical device is used to capture the unique characteristics of the hand's movement in a 3D space. In this setup, a Raspberry Pi 3B serves as the microcontroller. MPU-6050 and Flex sensors performance are integrated with additional elements including mean, energy, variance, and correlation for classification. In our investigation, we have collected information from over 3,000 movement feature samples from different people. To increase the precision of the proposed methodology, we have incorporated several machine learning classification algorithms. © 2023 IEEE.

关键词： Support vector machines

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Perturbation Event Oriented Dynamic Task Scheduling Algorithm for Parallel Testing of control Systems

Perturbation Event Oriented Dynamic Task Scheduling Algorith...

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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and control, SDPC 2024

作者： Chen, Jingyi Wang, Shenhang Tong, Xiaoxuan Xiang, Gang Yu, Yang Zhan, Ziyuan School of Electronic and Information Engineeer Harbin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute System Design Department Beijing China Beijing Aerospace Automatic Control Institute Beijing China Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China

ISBN: (纸本)9798350388855

Task scheduling algorithms are key to research and practice in parallel testing techniques, especially in control system applications. The complexity of control system testing requires higher scheduling efficiency. However, perturbation events caused by test equipment problems, data transmission obstacles, or task changes are almost unavoidable and may reduce the scheduling effectiveness or even lead to system crashes. Therefore, in this paper, based on the analysis of the dynamic test scheduling model, a disturbance factor is designed to judge the urgency of disturbance events for evaluating the dynamic scheduling cycle. On this basis, based on the comprehensive rescheduling index, a suitable adjustment strategy is selected to formulate the dynamic test scheduling scheme. The experimental results show that the algorithm proposed in this paper can achieve fast response capability for different disturbance events and exhibit good adaptivity. © 2024 IEEE.

关键词： Scheduling algorithms

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Gauss Gradient and SURF Features for Landmine Detection from GPR Images

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Computers, Materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma M.El-Ghamry Walid El-Shafai Mahmouad I.Abdalla Ghada M.El-Banby Abeer D.Algarni Moawad I.Dessouky Adel S.Elfishawy Fathi E.Abd El-Samie Naglaa F.Soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

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Improving Security and Performance of Databases Through Single Cache System 4

Improving Security and Performance of Databases Through Sing...

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4th International Conference on Blockchain technology and information Security, ICBCTIS 2024

作者： Ul Haq, Ikram Khan, Salabat Khan, Mansoor Tamsal, Saher School of Computer Science and Technology Southwest University of Science and Technology Mianyang China School of Computer and Information Engineering Qilu Institute of Technology Jinan China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China University of Agriculture Department of Computer Science Faisalabad Pakistan

ISBN: (纸本)9798331528324

In today's world, connectivity and performance-driven technology are rapidly advancing each year, and new platforms and mechanisms are being utilized to enhance the security and performance of databases and cloud computing, which are trending in the global market. This examination focused on customer information security in cloud computing, i.e., information stockpiling security issues and how to control unapproved access to data by proposing access control;valuable measures were characterized subsequently, and an entrance control show was prescribed. Cloud computing can be described as an innovation that depends on the web and the sharing of resources. It has an adaptable foundation that customers can use with much of a stretch. With its wide event relationship, there are numerous obstacles to continuing with cloud computing because of security issues, mostly considering customer data security. The proposed study helped hesitant clients sensibly continue forward in the cloud while understanding the dangers of cloud computing. The research objective is to examine the security techniques employed in cloud technology to improve its performance by utilizing data mining within a unified cache system. We will apply the Apriori algorithm as a proposed solution to be used in a single cache while considering the security measures in the cloud. The study expects to apply this method to all cloud providers and vendors by entering data into a single cache mechanism that can be extended into different components and implemented using SPSS modelers to improve the security of the database. © 2024 IEEE.

关键词： Cloud security

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Reconnaissance Robot for Rescue Services 14

Reconnaissance Robot for Rescue Services

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14th International Conference ELEKTRO, ELEKTRO 2022

作者： Bujnak, Marek Pirnik, Rastislav Kuchar, Pavol Kanalikova, Alzbeta University of Žilina Faculty of Electrical Engineering and Information Technology Department of Control and Information Systems Žilina010 26 Slovakia

ISBN: (纸本)9781665467261

The spherical robots are becoming very popular in the field for many scientists and researchers working with surveillance, military, or transportation systems. This paper deals with comparing of each driving mechanism of the spherical robot. The vast majority of spherical robots only have inertial sensors, which they use for movement, positioning, travel balancing, etc. Few spherical robots can interact with the environment. Those who can do this have sensors that can measure the properties of the environment or can influence the environment in some way. The article also deals with the possibility to use sensors like cameras, gas sensors, thermocouples, and LiDARs. Data from these sensors will be processed using artificial intelligence techniques to detect anomalies in the environments. Chosen sensors can expand a robot's sensing capabilities which are usually very narrow. The aim of the article is to design s special type of spherical robot. If we join all these components together we can create a reconnaissance spherical robot for rescue services special designated for tunnels or closed *** prototype is a financially inexpensive robot, which is also suitable for the teaching process, as an element that collects data from the environment (sensors, video, etc.), which will be used for working with AI tools. © 2022 IEEE.

关键词： Robots

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