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International Journal of Interactive Mobile Technologies 2025年第5期19卷 22-44页

作者： Ewais, Ahmed Dalipi, Fisnik Abualrob, Marwan Ferati, Mexhid Kurti, Arianit Computer Science Department Faculty of Information Technology Arab American University Jenin Palestine Department of Informatics Faculty of Technology Linnaeus University Växjö Sweden Elementary Education Department Faculty of Arts Arab American University Jenin Palestine

The integration of augmented reality (AR) into educational environments will depend on its perceived effectiveness in enhancing teaching practices and the attitudes toward the use of this technology. Therefore, the main objective is to investigate the teachers’ attitude and motivation to adopt AR in educational settings, which also looks at a cross-cultural context. Furthermore, this research reveals different aspects that have an impact on teachers’ attitudes toward adopting AR in the teaching process. To investigate this, we conducted a study with 87 K-12 teachers belonging to two different education systems, i.e., Sweden and Palestine. The mixed-methods approach enhances the validity of the study and provides a broad understanding through numerical data, while qualitative insights offer deeper explanations of the findings. The results indicate a statistically significant difference in teachers’ attitudes about AR, with a mean 3.99 for teachers coming from Palestine showing a more positive attitude towards AR-supported learning. Therefore, it is important for educational institutions and application developers to consider a range of learning and teaching methods, as well as specific needs, throughout the process of developing and incorporating AR into the curriculum. © 2025 by the authors of this article.

关键词： attitudes augmented reality (AR) education learning schools teachers

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Video forgery localization using inter-frame denoising and intra-frame segmentation

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Multimedia Tools and Applications 2025年 1-17页

作者： Banerjee, Debanik Chittaragi, Nagaratna B. Koolagudi, Shashidhar G. Department of Computer Science and Engineering National Institute of Technology Karnataka Karnataka Surathkal575025 India Department of Information Science and Engineering Siddaganaga Institute of Technology Karnataka Tumkur572103 India

Video forgery detection has been necessary with recent spurt in fake videos like Deepfakes and doctored videos from multiple video capturing devices. In this paper, we provide a novel technique of detecting fake videos by creating an ensemble network, based on statistical and deep learning methods to detect interframe forgery and intraframe forgery in forged videos separately. In this paper, Noise signature extraction of a particular image capturing sensor and an Autoencoder-based Convolutional Neural Network model (CNN) are used to localize the forged regions. We have trained the model to localize Deepfake video forgeries as well as copy-paste forgeries with effective results in the test data. The proposed fake video detector can be applied at the back-end of on-line video aggregating services and check their authenticity to verify the genuineness of videos. The results achieved have shown better performances in detecting fake videos compared to existing methods. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Lifetime Maximization Using Grey Wolf Optimization Routing Protocol with Statistical Technique in WSNs

Informatica (Slovenia)

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Informatica (Slovenia) 2023年第5期47卷 75-82页

作者： Khudor, Baida'a Abdul Qader Hussein, Dheyaa Mezaal Kheerallah, Yousif Abdulwahab Alkenani, Jawad Alshawi, Imad S. Department of Computer Science College of Computer Science and Information Technology University of Basrah Basrah Iraq University of Technology Office of the President of the University Basra Iraq Department of Computer Science Shatt Al-Arab University College Basra Iraq

The main challenge in Wireless Sensor Networks (WSNs) is to maximize the lifespan of sensor nodes powered by low-cost batteries with limited power. Energy conservation is crucial, and routing mechanisms play a vital role in preserving energy. Energy-efficient routing methods can save battery power and extend the network's lifespan. This study introduces the Grey Wolf Optimization Routing Protocol (GWORP), enhanced with a novel routing mechanism that detects the statistically optimal path. It enables the discovery and reuse of an ideal route from the source to the destination, ensuring balanced energy consumption across WSN nodes and reducing path discovery time. GWORP outperforms the PSORP (Particle Swarm Optimization Routing Protocol) algorithm, significantly reducing energy usage and minimizing end-to-end latency. The findings suggest that GWORP could potentially increase the network lifespan by approximately 73% compared to PSORP. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Routing protocols

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Multi-strategy Hybrid Coati Optimizer:A Case Study of Prediction of Average Daily Electricity Consumption in China

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Journal of Bionic Engineering 2024年第5期21卷 2540-2568页

作者： Gang Hu Sa Wang Essam H.Houssein Department of Applied Mathematics Xi’an University of TechnologyXi’an710054China School of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China Faculty of Computers and Information Minia UniversityMinia61519Egypt

The power sector is an important factor in ensuring the development of the national *** simulation and prediction of power consumption help achieve the balance between power generation and power *** this paper,a Multi-strategy Hybrid Coati Optimizer(MCOA)is used to optimize the parameters of the three-parameter combinatorial optimization model TDGM(1,1,r,ξ,Csz)to realize the simulation and prediction of China's daily electricity ***,a novel MCOA is proposed in this paper,by making the following improvements to the Coati Optimization Algorithm(COA):(ⅰ)Introduce improved circle chaotic mapping strategy.(ⅱ)Fusing Aquila Optimizer,to enhance MCOA's exploration capabilities.(ⅲ)Adopt an adaptive optimal neighborhood jitter learning *** improve MCOA escape from local optimal solutions.(ⅳ)Incorporating Differential Evolution to enhance the diversity of the ***,the superiority of the MCOA algorithm is verified by comparing it with the newly proposed algorithm,the improved optimiza-tion algorithm,and the hybrid algorithm on the CEC2019 and CEC2020 test ***,in this paper,MCOA is used to optimize the parameters of TDGM(1,1,r,ξ,Csz),and this model is applied to forecast the daily electricity consumption in China and compared with the predictions of 14 models,including seven intelligent algorithm-optimized TDGM(1,1,r,ξ,Csz),and seven forecasting *** experimental results show that the error of the proposed method is minimized,which verifies the validity of the proposed method.

关键词： Forecast of average daily electricity consumption in China Coati optimization algorithm Three-parameter combination optimization model Circle chaotic mapping

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Inductive Lottery Ticket Learning for Graph Neural Networks

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Journal of computer science & technology 2024年第6期39卷 1223-1237页

作者： Yong-Duo Sui Xiang Wang Tianlong Chen Meng Wang Xiang-Nan He Tat-Seng Chua School of Data Science University of Science and Technology of ChinaHefei 230027China Department of Electrical and Computer Engineering The University of Texas at AustinAustin 78712U.S.A School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China School of Computing National University of SingaporeSingapore

Graph neural networks (GNNs) have gained increasing popularity, while usually suffering from unaffordable computations for real-world large-scale applications. Hence, pruning GNNs is of great need but largely unexplored. The recent work Unified GNN Sparsification (UGS) studies lottery ticket learning for GNNs, aiming to find a subset of model parameters and graph structures that can best maintain the GNN performance. However, it is tailed for the transductive setting, failing to generalize to unseen graphs, which are common in inductive tasks like graph classification. In this work, we propose a simple and effective learning paradigm, Inductive Co-Pruning of GNNs (ICPG), to endow graph lottery tickets with inductive pruning capacity. To prune the input graphs, we design a predictive model to generate importance scores for each edge based on the input. To prune the model parameters, it views the weight’s magnitude as their importance scores. Then we design an iterative co-pruning strategy to trim the graph edges and GNN weights based on their importance scores. Although it might be strikingly simple, ICPG surpasses the existing pruning method and can be universally applicable in both inductive and transductive learning settings. On 10 graph-classification and two node-classification benchmarks, ICPG achieves the same performance level with 14.26%–43.12% sparsity for graphs and 48.80%–91.41% sparsity for the GNN model.

关键词： lottery ticket hypothesis graph neural networks neural network pruning

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The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-Long Han Lin Li Xiao Chen Sheng Wen Yang Xiang the School of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the School of Computer and Mathematical Sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the School of Information and Physical Sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

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Multi-head attention graph convolutional network model:End-to-end entity and relation joint extraction based on multi-head attention graph convolutional network

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CAAI Transactions on Intelligence technology 2023年第2期8卷 468-477页

作者： Zhihua Tao Chunping Ouyang Yongbin Liu Tonglee Chung Yixin Cao School of Computer Science University of South ChinaHengyangChina Department of Computer Science and technology Tsinghua UniversityBeijingChina School of Computer and Information Systems Singapore Management UniversitySingaporeSingapore

At present,the entity and relation joint extraction task has attracted more and more scholars'attention in the field of natural language processing(NLP).However,most of their methods rely on NLP tools to construct dependency trees to obtain sentence structure *** adjacency matrix constructed by the dependency tree can convey syntactic *** trees obtained through NLP tools are too dependent on the tools and may not be very accurate in contextual semantic *** the same time,a large amount of irrelevant information will cause *** paper presents a novel end-to-end entity and relation joint extraction based on the multihead attention graph convolutional network model(MAGCN),which does not rely on external *** generates an adjacency matrix through a multi-head attention mechanism to form an attention graph convolutional network model,uses head selection to identify multiple relations,and effectively improve the prediction result of overlapping *** authors extensively experiment and prove the method's effectiveness on three public datasets:NYT,WebNLG,and *** results show that the authors’method outperforms the state-of-the-art research results for the task of entities and relation extraction.

关键词： information retrieval natural language processing

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Project Assessment in Offshore Software Maintenance Outsourcing Using Deep Extreme Learning Machines

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computers, Materials & Continua 2023年第1期74卷 1871-1886页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Saqib Raza Ahmad Salman Khan Yasir Mahmood Nazri Kama Azri Azmi Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala NerusMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyahKuwait Department of Computer Science Sharif College of Engineering&TechnologyLahore54000Pakistan

Software maintenance is the process of fixing,modifying,and improving software deliverables after they are delivered to the *** can benefit from offshore software maintenance outsourcing(OSMO)in different ways,including time savings,cost savings,and improving the software quality and *** of the hardest challenges for the OSMO vendor is to choose a suitable project among several clients’*** goal of the current study is to recommend a machine learning-based decision support system that OSMO vendors can utilize to forecast or assess the project of OSMO *** projects belong to OSMO vendors,having offices in developing countries while providing services to developed *** the current study,Extreme Learning Machine’s(ELM’s)variant called Deep Extreme Learning Machines(DELMs)is used.A novel dataset consisting of 195 projects data is proposed to train the model and to evaluate the overall efficiency of the proposed *** proposed DELM’s based model evaluations achieved 90.017%training accuracy having a value with 1.412×10^(-3) Root Mean Square Error(RMSE)and 85.772%testing accuracy with 1.569×10^(-3) RMSE with five DELMs hidden *** results express that the suggested model has gained a notable recognition rate in comparison to any previous *** current study also concludes DELMs as the most applicable and useful technique for OSMO client’s project assessment.

关键词： Software outsourcing deep extreme learning machine(DELM) machine learning(ML) extreme learning machine assessment

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A New Strategy for Dynamic Channel Allocation in CR-WMN Based on RCA

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computers, Materials & Continua 2023年第9期76卷 2631-2647页

作者： Kaleem Arshid Jianbiao Zhang Muhammad Yaqub Mohammad Daud Awan Habiba Ijaz Imran Shabir Chuhan Faculty of Information Technology Beijing University of TechnologyBeijing100124China Department of Computer Science Preston University KohatIslamabad CampusIslamabad44000Pakistan Department of Computer Science and Information Technology University of SargodhaPunjab40100Pakistan College of Applied Sciences Beijing University of TechnologyBeijing100124China

Channel assignment has emerged as an essential study subject in Cognitive Radio-basedWireless Mesh Networks(CR-WMN).In an era of alarming increase in Multi-Radio Multi-Channel(MRMC)network expansion interference is decreased and network throughput is significantly increased when non-overlapping or partially overlapping channels are correctly *** of its ad hoc behavior,dynamic channel assignment outperforms static channel *** reduces network throughput in the *** a result,there is an extensive research gap for an algorithm that dynamically distributes channels while accounting for all types of *** work presents a method for dynamic channel allocations using unsupervisedMachine Learning(ML)that considers both coordinated and uncoordinated *** machine learning uses coordinated and non-coordinated interference for dynamic channel *** determine the applicability of the proposed strategy in reducing channel interference while increasingWMNthroughput,a comparison analysis was *** the simulation results of our proposed algorithm are compared to those of the Routing Channel Assignment(RCA)algorithm,the throughput of our proposed algorithm has increased by 34%compared to both coordinated and non-coordinated interferences.

关键词： Carrier sensing interference coordination overlapping channels orthogonal channels

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Copy-Right protection of color videos using robust watermarking based geometrically invariant moments of fractional orders and logistic sine cosine chaotic map

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Multimedia Tools and Applications 2024年 1-26页

作者： Alsahafi, Yousef S. Darwish, Mohamed M. Hosny, Khalid M. Department of Information Technology Khulis College University of Jeddah Jeddah Saudi Arabia Department of Computer Science Faculty of Computers and Information Assiut University Assiut Egypt Department of Computer Science University College of Al Wajh University of Tabuk Tabuk Saudi Arabia Department of Information Technology Faculty of Computers and Informatics Zagazig University Zagazig Egypt

Digital video watermarking research has yielded numerous promising breakthroughs in recent years. As more people grow interested in videos, the copyright protection of videos has become an urgent issue that must be addressed. Digital video watermarking is a significant method for copyright protection of videos because of the growing need to safeguard video data’s intellectual property. Some existing works cannot resist geometric attacks effectively, while others fail to address the balance between robustness and visual imperceptibility. Significant progress has been made in studying fractional orthogonal moments due to their geometric invariance and beneficial image description capabilities. For these reasons, this paper proposes a robust watermarking algorithm for color video using accurate quaternion fractional Gegenbauer moments (QFrGMs), which are constructed relying on a combination of quaternion theory and accurate fractional Gegenbauer moments (FrGMs). The proposed algorithm is designed to address existing deficiencies in some related works and improve resilience. This algorithm is imperceptibly invisible and resistant to various kinds of attacks. In the proposed algorithm, the watermark information is embedded into accurately selected coefficients of QFrGMs for the selected frame of the cover video. This algorithm is robust to geometric attacks due to the outstanding geometric invariance of QFrGMs. To ensure security and improve the suggested algorithm’s security, we employed a chaotic map termed a one-dimensional Logistic Sine Cosine (LSC) map with superior chaotic characteristics to scramble the watermark. Numerical experiments were performed regarding imperceptibility and robustness to test the effectiveness. The experimental results demonstrated that the proposed method provides high visual quality and robustness against common signal processing, geometric, frame averaging, frame swapping, and frame dropping attacks. Furthermore, the proposed algorithm e

关键词： Image watermarking

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