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A Comparison Study of FC-RDVM and RIWM Router Placement Methods for WMNs: Performance Evaluation Results by WMN-PSOHC Simulation System Considering Chi-Square Distribution and Different Instances 1

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37th International Conference on Advanced information Networking and Applications, AINA 2023

作者： Sakamoto, Shinji Barolli, Admir Liu, Yi Kulla, Elis Barolli, Leonard Takizawa, Makoto Department of Information and Computer Science Kanazawa Institute of Technology 7-1 Ohgigaoka Ishikawa Nonoichi921-8501 Japan Department of Information Technology Aleksander Moisiu University of Durres L.1 Rruga e Currilave Durres Albania Department of Computer Science National Institute of Technology Oita College 1666 Maki Oita870-0152 Japan Department of System Management Fukuoka Institute of Technology 3-30-1 Wajiro-Higashi Higashi-Ku Fukuoka811-0295 Japan Department of Information and Communication Engineering Fukuoka Institute of Technology 3-30-1 Wajiro-Higashi Higashi-Ku Fukuoka811-0295 Japan Department of Advanced Sciences Faculty of Science and Engineering Hosei University Tokyo Kajino-Machi Koganei-Shi184-8584 Japan

ISBN: (数字)9783031290565

ISBN: (纸本)9783031290558

In this work, we deal with the node placement problem in Wireless Mesh Networks (WMNs). We present a hybrid intelligent simulation system called WMN-PSOHC, which combines Particle Swarm Optimization (PSO) and Hill Climbing (HC). We implement in WMN-PSOHC system the Fast Convergence Rational Decrement of Vmax Method (FC-RDVM) and Random Inertia Weight Method (RIWM) router replacement methods. By using WMN-PSOHC system, we carry out simulations the access the performance of these two methods considering Chi-Square distribution of mesh clients and two different instances. The simulation results show that FC-RDVM performs better then RIWM in the considered scenario. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Particle swarm optimization (PSO)

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A systematic literature review to implement large language model in higher education: issues and solutions

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Discover Education 2025年第1期4卷 1-25页

作者： Guizani, Sghaier Mazhar, Tehseen Shahzad, Tariq Ahmad, Wasim Bibi, Afsha Hamam, Habib College of Engineering Alfaisal University Riyadh 11533 Saudi Arabia School of Computer Science National College of Business Administration and Economics Lahore 54000 Pakistan Department of Computer Science and Information Technology School Education Department Government of Punjab Layyah 31200 Pakistan Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan Department of Computing School of Arts and Creative Technology University of Greater Manchester Manchester BL15AB United Kingdom Department of Computer and Software Technology University of Swat Swat 19200 Pakistan Faculty of Engineering Uni de Moncton Moncton E1A3E9 NB Canada School of Electrical Engineering University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles Libreville BP 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role in automating instructional tasks and promoting personalized learning experiences. Despite integration concerns and ethical debates, LLMs showcase the potential of AI to improve educational practices. Our research concludes that LLMs offer transformative opportunities for education. However, their incorporation requires careful ethical considerations, data privacy measures, and a balance between human educators and AI technologies. The findings suggest strategies for integrating LLMs into educational frameworks to enhance learning outcomes while preserving educational integrity. © The Author(s) 2025.

关键词： Artificial intelligence Education Large language models Learning systems Natural language processing systems Neural networks

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Efficient Joint Key Authentication Model in E-Healthcare

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computers, Materials & Continua 2022年第5期71卷 2739-2753页

作者： Muhammad Sajjad Tauqeer Safdar Malik Shahzada Khurram Akber Abid Gardezi Fawaz Alassery Habib Hamam Omar Cheikhrouhou Muhammad Shafiq Department of Computer Science Air University Multan CampusMultan60000Pakistan Faculty of Computing The Islamia University of BahawalpurBahawalpur 63100Pakistan Department of Computer Science COMSATS University IslamabadIslamabadPakistan Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada CES Laboratory National School of Engineers of SfaxUniversity of SfaxSfax3038Tunisia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and *** devices and mobile applications are now increasingly used and integrated through the medical Internet of Things(mIoT).mIoT is an important part of the digital transformation of healthcare,because it can introduce new business models and allow efficiency improvements,cost control and improve patient *** the mIoT system,when migrating from traditional medical services to electronic medical services,patient protection and privacy are the priorities of each ***,it is recommended to use different user authentication and authorization methods to improve security and *** this paper,our prosed model involves a shared identity verification process with different situations in the e-health *** aim to reduce the strict and formal specification of the joint key authentication *** use the AVISPA tool to verify through the wellknown HLPSL specification language to develop user authentication and smart card use cases in a user-friendly *** model has economic and strategic advantages for healthcare organizations and healthcare *** medical staff can increase their knowledge and ability to analyze medical data more *** model can continuously track health indicators to automatically manage treatments and monitor health data in real ***,it can help customers prevent chronic diseases with the enhanced cognitive functions *** necessity for efficient identity verification in e-health care is even more crucial for cognitive mitigation because we increasingly rely on mIoT systems.

关键词： E-health systems joint key authentication mutual authentication

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A lightweight distillation CNN-transformer architecture for remote sensing image super-resolution

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International Journal of Digital Earth 2023年第1期16卷 3560-3579页

作者： Yu Wang Zhenfeng Shao Tao Lu Lifeng Liu Xiao Huang Jiaming Wang Kui Jiang Kangli Zeng State Key Laboratory for Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanPeople’s Republic of China School of General Aviation Jingchu University of TechnologyJingmenPeople’s Republic of China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of TechnologyWuhanPeople’s Republic of China Department of Engineering University of DurhamDurhamUK Department of Environmental Sciences Emory UniversityAtlant1GAUSA School of Computer Science and Technology Harbin Institute of TechnologyHarbinPeople’s Republic of China NERCMS School of Computer ScienceWuhan UniversityWuhanPeople’s Republic of China

Remote sensing images exhibit rich texture features and strong *** the super-resolution(SR)method of remote sensing images based on convolutional neural networks(CNN)can capture rich local information,the limited perceptual field prevents it from establishing long-distance dependence on global information,leading to the low accuracy of remote sensing image ***,it is difficult for existing SR methods to be deployed in mobile devices due to their large network parameters and high computational *** this study,we propose a lightweight distillation CNN-Transformer SR architecture,named DCTA,for remote sensing SR,addressing the aforementioned ***,the proposed DCTA first extracts the coarse features through the coarse feature extraction layer and then learns the deep features of remote sensing at different scales by fusing the feature distillation extraction module of CNN and *** addition,we introduce the feature fusion module at the end of the feature distillation extraction module to control the information propagation,aiming to select the informative components for better feature *** extracted low-resolution(LR)feature maps are reorganized through the up-sampling module to obtain high-resolution(HR)feature maps with high accuracy to generate highquality HR remote sensing *** experiments comparing different methods demonstrate that the proposed approach performs well on multiple datasets,including NWPU-RESISC45,Draper,and UC *** is achieved by balancing reconstruction performance and network complexity,resulting in both competitive subjective and objective results.

关键词： Super-resolution remote sensing lightweight network CNN-Transformer

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Visualization of Judicial Precedents on Power Harassment Issues Using Relationship Chart

Visualization of Judicial Precedents on Power Harassment Iss...

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Thematic area Human Interface and the Management of information, HIMI 2022 Part of the 24th HCI International Conference, HCII 2022

作者： Tanaka, Soichiro Kano, Toru Akakura, Takako Department of Information and Computer Technology Graduate School of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan

ISBN: (纸本)9783031064234

Power harassment has become a problem in Japan recently. However, it has been found that reading judicial precedents is one of the ways to prevent it. In this paper, in order to promote the reading of judicial precedents, we visualized the relationships between people in judicial precedents, which are not easy for non-experts to read. We first extracted the words from the text of judicial precedents that represent people using morphological analysis. Next, we then extracted information about the relationship between the persons using dependency analysis. We then determined the direction of the extracted relationship. Finally, based on the automatically extracted relations between the persons, we visualized the structure of the case as relationship charts and fishbone diagrams. To confirm the usefulness of the proposed diagrams in reading judicial precedents, we conducted an evaluation experiment using both judicial precedents and diagrams on six Tokyo University of Science students. The results suggest that diagrams make it easier to read judicial precedents. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphic methods

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Expedited Block Transmission in Blockchain Network by using Clusters

Expedited Block Transmission in Blockchain Network by using ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Hua, Xiaoqi Chen, Jian Zhang, Peiyun Fu, Zhangjie Zhu, Haibin Lu, Kezhong Ren, Jigang School of Software Nanjing University of Information Science and Technology Nanjing210044 China Engineering Research Center of Digital Forensics of Ministry of Education The School of Computer Science Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science Nanjing University of Information Science and Technology Nanjing210044 China Nipissing University Department of Computer Science and Mathematics North BayONP1B 8L7 Canada School of Big Data and Artificial Intelligence Chizhou University Chizhou247000 China

ISBN: (纸本)9781665410205

Blockchain technology has garnered increasing attention from researchers. Because blockchain systems may contain malicious or spatially limited nodes that may delay block verification and reduce block transmission rate, this work proposes a block transmission model by designing and using special clusters. This work proposes the cluster formation and selection mechanisms. Nodes are grouped into clusters in a blockchain, and clusters with high fitness values are chosen to transmit blocks by calculating their trust values and block transmission rates. The proposed method is compared with the peers: Layer-Chain, BlockP2P-EP and RNS. According to experimental findings, the proposed method is superior to its peers regarding the time needed for block synchronization and transmission, block occupation storage ratio, transaction throughput, and block transmission success ratio. © 2024 IEEE.

关键词： Blockchain

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Gaze Analysis and Modeling of Cognitive Process During Debugging for Novice Programmers’ Learning

Gaze Analysis and Modeling of Cognitive Process During Debug...

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Thematic area Human Interface and the Management of information, HIMI 2022 Part of the 24th HCI International Conference, HCII 2022

作者： Yoshimori, Kohei Kano, Toru Akakura, Takako Graduate School of Engineering Department of Information and Computer Technology Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Faculty of Engineering Department of Information and Computer Technology Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan

ISBN: (纸本)9783031064234

Recently, the demand for IT human resources has increased. Therefore, the expansion of programming education should be considered to strengthen the supply of it. This study aimed to propose debugging learning support for novice programmers using experts’ gaze behavior. First, we gave feedback to proficient users on their gazing behavior during program debugging and interviewed them about their cognitive processes. Based on the results, we developed a cognitive process model of expert debugging. However, most of the visualized information was based on gaze transitions, and it was difficult to see the characteristics of the cognitive process. This study helped to improve the previously proposed model and developed one that focuses more on the cognitive process during program debugging. Data from students with little programming experience were collected and compared with the cognitive process model of programming experts. This enabled the identification of the characteristics of the program debugging process of non-experts. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Program debugging

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Vader protocol based sentiment analysis technique using LSTM for Stock Trend prediction 14

Vader protocol based sentiment analysis technique using LSTM...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Ticku, Amrita Tripathy, Niva Mishra, Pankaj Kumar Sinha, Anurag Jadon, Shivangi Raj, Aditya Kulshrestha, Harsh Rai, Vipin Shamim, Rejuwan Bharti Vidyapeeth's College of Engineering India Driems Autonomous Engineering College Cuttack India Rungta College of Engg. & Technology R1 Department of Electronics and Telecommunication Engg. CG Bhilai India Ignou School of Computing and Information Science New Delhi India Galgotias University Dept. of Computer Science and Engineering Noida India Galgotias University Department of Computer Science and Engineering Noida India Maharishi University of Information Technology Dept. of Computer Science and Engineering with Data Science Noida India

ISBN: (纸本)9798350335095

Stock prediction has always been a difficult task, and numerous strategies for predicting stock market behavior have been offered. Researchers have recently begun to investigate the use of sentimental analysis and deep learning models such as Long Short-Term Memory (LSTM) to predict stock prices. We offer a stock prediction model that integrates sentimental analysis and LSTM in this research. The model considers the mood of stock market news items and use LSTM to forecast future stock prices. The results of our suggested model's evaluation on the S& P 500 dataset reveal that it outperforms traditional stock prediction approaches. © 2023 IEEE.

关键词： Forecasting

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Radio Map Based UAV Target Localization 48

Radio Map Based UAV Target Localization

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： He, Chen Gong, Weisheng Dong, Yangrui Xie, Xie Wang, Z. Jane Northwest University School of Information Science and Technology Xi'an China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

ISBN: (纸本)9781728163277

Acting as the dynamic base stations, the unmanned aerial vehicles has a significant advantage over the conventional base station for target localization. When localizing a target, UAV can move toward the estimated target location after each estimation, making the received signals stronger after each iteration, and hence yield more localization precision for each iteration. In this paper, we propose target localization by UAV with radio maps as prior knowledge, which are generated from real topographic maps. We derived the minimum mean square error (MMSE) estimator for target localization by UAV with the radio map. Numerical results show that with radio map knowledge and the MMSE estimator, localization precision can be considerably improved. © 2023 IEEE.

关键词： Mean square error

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Data hiding method for AMBTC compressed images

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Journal of Ambient Intelligence and Humanized Computing 2023年第11期14卷 14785-14793页

作者： Chen, Yung-Yao Hsia, Chih-Hsien Jhong, Sin-Ye Lin, Hsin-Ju Graduate Institute of Automation Technology National Taipei University of Technology No. 1 Sec. 3 Zhongxiao E. Rd. Daan Dist. Taipei106 Taiwan Department of Computer Science and Information Engineering National Ilan University No. 1 Sec. 1 Shennong Rd. Yilan County Yilan City260 Taiwan

With the current growth of multimedia applications, a substantial amount of visual data, including images and videos, is transmitted daily, making information forensics and security essential. Thus, protecting secret data from attackers is critical. In this work, we propose a AMBTC-based data-hiding method, in which secret data are concealed in individual image blocks that are compressed using absolute moment block truncation coding technique. By placing high or low mean values at the corner of each block, the secret data are then extracted reversibly and the original host image can be recovered at the decoding end. In addition, the quality of stego images is maintained, which protects the embedded visual data from the suspicion of attackers. From the experimental results, we show that the proposed method outperforms other state-of-the-art methods. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Steganography

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