检索结果-内蒙古大学图书馆

8th International Conference on Inventive systems and Control, ICISC 202

作者： Kannan, Balaji Lakshmi, R.Bagavathi Sakthivanitha, M. Maruthi, R. School of Computing Science Department of Information Technology Tamil Nadu Chennai India Hindustan Institute of Technology and Science Department of Computer Applications Tamil Nadu Chennai India

ISBN: (纸本)9798350386578

The wildlife population has been in danger due to frequent animal accidents on railway tracks. In India, animal train collisions cause an average of 20 elephant deaths every year all over the nation. At the same time railway departments are taking necessary steps to identify the cause and implement prevention methods. Despite this, lots of accidents are happening in the railway tracks near the forest areas. This problem has been addressed by proposing a well-defined technological mechanism to alert the animals to be away from the railway tracks to reduce the wildlife deaths. In this study, Machine Learning(ML) frameworks are employed to detect the animals that are coming near the railway tracks and the developed module will provide appropriate warning or signals to the animals as well as to the loco pilot. © 2024 IEEE.

关键词： Invertebrates

来源：评论

学校读者我要写书评

暂无评论

Influence of AI and MAS in Enhancing Energy Efficiency of 6G Communications

Influence of AI and MAS in Enhancing Energy Efficiency of 6G...

引用

2024 International Conference on Communication, computer sciences and Engineering, IC3SE 2024

作者： Negi, Divya Prakash, Febin Gupta, Anjali Tula's Institute Department Of Computer Science And Engineering Dehradun India Department Of Computer Science And Information Technology Bangalore India Noida Institute Of Engineering And Technology Department Of Electronical And Electronics Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350366846

Next-generation Internet of Things (IoT) is progressing rapidly due to the introduction of beyond 5G (B5G) and the approaching arrival of 6G, which have improved the dependability, productivity, and profitability of both industrial and personal operations. Nevertheless, data overload is frequently caused by the abundance of wireless sensors in commercial 6G devices. Data mining gathers useful information in order to solve this. Meanwhile, in the 6G architecture, edge computing enables automated equipment operations and intelligent decision-making in real-time. Even so, despite the drawbacks of sensor-based energy sources, the integration of many technologies has led to an increase in energy. Using a multi-agent system (MAS) approach, a system model for industrial wireless sensor networks in 6G applications has been presented in order to combat this. Sensor node clustering locates and forecasts the locations of principal nodes by employing distributed artificial intelligence (DAI). Convolutional neural networks (CNN) and back-propagation neural networks (BPNN) are used in optimisation. Allocating resources to individual nodes efficiently is made possible by the analysis of inter-cluster correlations. The outcomes of the simulation show how well the approach works to reduce resource waste, increase overall energy efficiency, and protect important data. This strategy improves network performance in industrial 6G applications while simultaneously addressing concerns about energy consumption. © 2024 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Entrodeduper: Data Deduplication Using Entropy and Secure Hash Algorithm

Entrodeduper: Data Deduplication Using Entropy and Secure Ha...

引用

2023 IEEE Conference on computer Applications, ICCA 2023

作者： Thwel, Tin Thein Maung, Hsu Mon University of Computer Studies Faculty of Information Science Yangon Myanmar Myanmar Institute of Information Technology Data Center Department Mandalay Myanmar

ISBN: (纸本)9781665435994

Being a data science era, any bulk of data concerned with specific fields need to maintain in data centers with the help of rack server. For reducing storage for data center, the need to implement the data deduplication mechanism and keeping backup of those data in data center is becoming more important. In the case of reducing redundant data from the various servers in data center, the huge amount of data become the biggest challenge. As the data deduplication mechanism not only it can reduce the size of data to be stored or to be transmit but also it can give the backup and recovery features. This paper proposed the efficient data deduplication mechanism called EntroDeduper, which is the hybrid of entropy, secure hash algorithm and indexing. The input files are divided into blocks using file separator and the redundant block is removed by applying the entropy gain theory, which is used to get not only the significant reduction rate but also the full block coverage for reconstruction. © 2023 IEEE.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

引用

Journal of Bionic Engineering 2023年第4期20卷 1766-1790页

作者： Laith Abualigah Mahmoud Habash Essam Said Hanandeh Ahmad MohdAziz Hussein Mohammad Al Shinwan Raed Abu Zitar Heming Jia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia Amman Arab University AmmanJordan Department of Computer Information System Zarqa UniversityP.O.Box 13132ZarqaJordan Deanship of E-Learning and Distance Education Umm Al-Qura UniversityMakkah21955Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates School of Information Engineering Sanming UniversitySanming365004China

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding,called *** proposed method introduces a better search space to find the optimal solution at each ***,we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level *** obtained solutions by the proposed method are represented using the image *** proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each *** performance measure for the proposed method is valid by detecting fitness function,structural similarity index,peak signal-to-noise ratio,and Friedman ranking *** benchmark images of COVID-19 validate the performance of the proposed *** results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

关键词： Bioinspired Reptile Search Algorithm Salp Swarm Algorithm Multi-level thresholding Image segmentation Meta-heuristic algorithm

来源：评论

学校读者我要写书评

暂无评论

Evaluation of User Experience in Mobile Applications Using User Experience Questionnaire and User Centered Design Methods

Evaluation of User Experience in Mobile Applications Using U...

引用

2024 International Conference on Circuit, systems and Communication, ICCSC 2024

作者： Hendrian, Ariq Hamzah, Muhammad Luthfi Zarnelly Anofrizen Ansyar, Tengku Khairil Universitas Islam Negeri Sultan Syarif Kasim Riau Faculty of Science and Technology Department of Information System Pekanbaru Indonesia

ISBN: (纸本)9798350365306

The role of BPS in the eyes of the Government of the Republic of Indonesia is very strategic as a Government Institution providing statistical data that will be used as a source of data and analysis to determine the direction of national policy. The user experience evaluation of the Sobat BPS application has been conducted using the user-centered design method and user experience questionnaire. The evaluation results show that the Sobat BPS mobile application has several shortcomings in terms of security, features and appearance, as well as user interest. As many as 97% of respondents experienced or felt many bugs that could hinder the data collection of officers/users. In addition, 70% of respondents felt that the security of the application was not guaranteed and 64% of respondents complain ed about the cluttered features and appearance. There were also 57% of respondents who experienced failure in accessing the application and 54% of respondents who felt less interested in the features provided. The new BPS UX also received a 'Good' rating on 3 aspects of UEQ (attractiveness, stimulation, and novelty) and 'Above Average' on 3 other aspects (clarity, efficiency, and accuracy). This shows that the new BPS UX is more attractive, easy to use, and by user needs. The UX redesign of the Sobat BPS application using the UCD approach has proven effective in increasing user satisfaction and providing a better user experience. Thus, it is necessary to improve the design and features of the Sobat BPS application to improve quality and increase user satisfaction. © 2024 IEEE.

关键词： Felts

来源：评论

学校读者我要写书评

暂无评论

Effects of the Attunement of an Attack Target by Whispering in AIWolf 14

Effects of the Attunement of an Attack Target by Whispering ...

引用

14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Murakami, Tomohiro Nakao, Nozomi Miyake, Hikaru Murata, Hayate Amano, Itsuki Kojima, Taisei Ando, Keisuke Ito, Nobuhiro Aichi Institute of Technology Graduate School of Business Administration and Computer Science Toyota Japan Aichi Institute of Technology Department of Information Science Toyota Japan Aichi Institute of Technology Faculty of Information Science Toyota Japan

ISBN: (纸本)9798350324228

Recently, research on AIWolf, which is artificial intelligence that plays the Werewolf game, has attracted much attention. Werewolves in the Werewolf game should cooperate using 'whispers;' which are conversations among werewolves only. However, whispers have not been used effectively in the AIWolf Competition and little research has been conducted on this topic. Therefore, the purpose of this study is to clarify the effectiveness of strategies that use whispers in AIWolf. A wide variety of strategies use whispers, but we focus on unifying attack targets, which was shown to improve the winning rate in previous studies. In the strategy of unifying attack targets, the strategy of the guiding agents is important. Therefore, we used 13 AIWolf Competition finalists with a wide variety of strategies and added statements of whom to attack in whispers to each finalist as a guide for whom to attack. Because there are three werewolf competitions in the AIWolf Competition setting, we created two agents to be attuned to the attack target of one of the guiding agents. In an experiment, we used these agents in the same setting as in the AIWolf Competition, and analyzed the differences between when the attack targets were unified and when they were not. The results showed that when the werewolves were a combination of two attuning agents and one guiding agent, the werewolves' win rate increased by an average of 2.3 percentage points. We also found that attuning to the agent with a high winning rate or high success rate in attacks improved the winning rate. These results indicate that attuning only the attack targets of agents with high winning rates and high success rates in attacks led to higher winning rates. © 2023 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Endogenous Security of FQn Networks: Adaptive system-Level Fault Self-Diagnosis

引用

IEEE Transactions on Reliability 2024年第3期73卷 1659-1668页

作者： Lin, Yuhang Lin, Limei Huang, Yanze Xu, Li Hsieh, Sun-Yuan Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

Endogenous security has the ability to discover, eliminate, and solve internal security problems and hidden dangers within the network, and is a superior technology to ensure future network security. The t/k-diagnosis strategy, as a strong and adaptive self-diagnosis strategy, is an important part for ensuring endogenous security. Moreover, the folded hypercube (FQn) as a data transmission network (e.g., optical network) topology offers new potential for the construction of large-scale, high data throughput, and low-latency systems, such as computing network, human-cyber-physical systems, and smart grid. However, there are few studies on endogenous security based on FQn networks. Therefore, this article designs an adaptive system-level fault self-diagnosis strategy, namely Fast t/k-Diagnosis Under Maeng-Malek Model (Ftk-DIAG-MM*) to diagnosis the faulty vertices in FQn network under the Maeng-Malek model (MM∗ mod). Then, we provide a proof of the algorithm correctness theoretically by the fault tolerance of FQn network. It is derived by theoretical derivation that the t/k-diagnosability inherent to the FQn network is (n+1)(k+1)-k(k+3)/2. The simulation experiments demonstrate that the designed Ftk-DIAG-MM∗ strategy can correctly diagnose all vertices within the range allowed by the diagnosability, and still has a great performance when it exceeds the range allowed by the diagnosability. It greatly enhances the fault diagnosis capability of FQn network in the circumstance of misdiagnosing a few vertices, which provides an important theoretical basis for the reliability and endogenous security of FQn networks. © 1963-2012 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

An effective automatic detection of tooth cavity using machine cum deep learning concepts and ICDAS measurement

引用

Materials Today: Proceedings 2022年 64卷 542-548页

作者： K S, Jayareka P, Sobiyaa Dr.A.C.Kaladevi Vinodhini.V Suman, Bashetty Department of Computer Science & Engineering Sona College of Technology Tamilnadu Erode India Department of Information Technology Bannari Amman Institute of Technology Tamilnadu Sathyamangalam Erode India Department of Computer Science & Engineering MLR Institute of Technology Telangana Hyderabad India

A full scan x-ray machine scans the mouth and detects the tooth with decay or abnormal tooth is identified using the automatic machine learning algorithm. The machine learning algorithm will detect the defected place accurately with the positional number and its intensity come severity and what treatment can be done within duration span everything will be listed to the normal user with the handheld system. Already existing methodologies are just detects using sensors and those are very high cost. © 2022

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Prerequisite Relations among Knowledge Units:A Case Study of computer science Domain

引用

computer Modeling in Engineering & sciences 2022年第12期133卷 639-652页

作者： Fatema Nafa Amal Babour Austin Melton Department of Computer Science Salem State UniversitySalemMA 01970USA Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Kent State UniversityKentOH 44240USA

The importance of prerequisites for education has recently become a promising research *** work proposes a statistical model for measuring dependencies in learning resources between knowledge *** are expected to present knowledge units in a semantically well-organized manner to facilitate students’understanding of the *** proposed model reveals how inner concepts of a knowledge unit are dependent on each other and on concepts not in the knowledge *** help understand the complexity of the inner concepts themselves,WordNet is included as an external knowledge base in *** goal is to develop a model that will enable instructors to evaluate whether or not a learning regime has hidden relationships which might hinder students’ability to understand the *** evaluation,employing three textbooks,shows that the proposed model succeeds in discovering hidden relationships among knowledge units in learning resources and in exposing the knowledge gaps in some knowledge units.

关键词： Knowledge graph text mining knowledge unit graph mining

来源：评论

学校读者我要写书评

暂无评论

Enhanced U-Net and PSO-Optimized ANFIS for Classifying Fish Diseases in Underwater Images

引用

International Journal of Fuzzy systems 2024年第8期26卷 2518-2535页

作者： Khabusi, Simon Peter Huang, Yo-Ping Lee, Mong-Fong Tsai, Meng-Chun Department of Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Electrical Engineering National Penghu University of Science and Technology Penghu88046 Taiwan Department of Computer Science and Information Engineering National Taipei University New Taipei City23741 Taiwan Department of Information and Communication Engineering Chaoyang University of Technology Taichung41349 Taiwan Department of Aquaculture National Penghu University of Science and Technology Penghu88046 Taiwan General Competency Center National Penghu University of Science and Technology Penghu88046 Taiwan

Fish diseases are among the major limiting factors to increase global aquaculture production. They lead to increased fish mortality, low breeding and growth rates, and low meat quality. The success of aquaculture is heavily dependent on the timely identification of disease. Therefore, we propose a fuzzy U-Net model to automatically identify fish disease from underwater images. U-Net is enhanced with multi-head channel and spatial attention and used to segment infected fish regions from fish disease images. Color pixel intensity features are then extracted from the localized regions, a form of guided feature extraction. Fuzzy C-means clustering is then used to find the cluster centroids and data distribution within the clusters, for the design of fuzzy membership functions. Moreover, the number of clusters are determined by silhouette score. Adaptive neuro-fuzzy inference system (ANFIS) is then trained, tested, and cross-validated for fish disease identification. The model parameters are optimized using particle swarm optimization (PSO) algorithm and compared with gradient-based methods. For image segmentation, the enhanced U-Net achieved a mean intersection over union (IoU) of 86.29%, mean pixel accuracy of 90.94%, mean precision of 93.58%, and mean recall value of 89.94% on 42 test images. Subsequently, ANFIS with PSO achieved overall superior performance on fish disease identification over gradient-based methods, with accuracy of 99.31%, precision of 99.00%, recall of 99.00%, and F1-score of 99.00%. The high-performance results of the optimized ANFIS confirm the robustness and efficacy of the proposed method to automatically identify fish diseases in aquaculture. © The Author(s) under exclusive licence to Taiwan Fuzzy systems Association 2024.

关键词： Fuzzy inference

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：