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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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Object-Attribute-Relation Representation Based Video Semantic Communication

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IEEE Journal on Selected Areas in Communications 2025年第7期43卷 2446-2461页

作者： Du, Qiyuan Duan, Yiping Yang, Qianqian Tao, Xiaoming Debbah, Merouane Tsinghua University Department of Electronic Engineering Beijing China Beijing China State Key Laboratory of Space Network and Communications Beijing China Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Xinjiang University School of Computer Science and Technology Xinjiang China Khalifa University KU6G Research Center Department of Computer and Information Engineering Abu Dhabi127788 United Arab Emirates University Paris-Saclay CentraleSupelec Gif-sur-Yvette91192 France

With the rapid growth of multimedia data volume, there is an increasing need for efficient video transmission in applications such as virtual reality and future video streaming services. Semantic communication is emerging as a vital technique for ensuring efficient and reliable transmission in low-bandwidth, high-noise settings. However, most current approaches focus on joint source-channel coding (JSCC) that depends on end-to-end training. These methods often lack an interpretable semantic representation and struggle with adaptability to various downstream tasks. In this paper, we introduce the use of object-attribute-relation (OAR) as a semantic framework for videos to facilitate low bit-rate coding and enhance the JSCC process for more effective video transmission. We utilize OAR sequences for both low bit-rate representation and generative video reconstruction. Additionally, we incorporate OAR into the image JSCC model to prioritize communication resources for areas more critical to downstream tasks. Our experiments on traffic surveillance video datasets assess the effectiveness of our approach in terms of video transmission performance. The empirical findings demonstrate that our OAR-based video coding method not only outperforms H.265 coding at lower bit-rates but also synergizes with JSCC to deliver robust and efficient video transmission. © 1983-2012 IEEE.

关键词： Video streaming

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Hiding information in a Reordered Codebook Using Pairwise Adjustments in Codewords 5

Hiding Information in a Reordered Codebook Using Pairwise Ad...

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5th International Conference on computer Vision and Computational Intelligence, CVCI 2024

作者： Chang, Chin-Chen Liu, Jui-Chuan Chang, Ching-Chun Lin, Yijie Department of Information Engineering and Computer Science Feng Chia University Taichung407 Taiwan Information and Communication Security Research Center Feng Chia University Taichung407 Taiwan

ISBN: (数字)9781510680067

ISBN: (纸本)9781510680050

The fundamental data structure of our proposed scheme is a pixel pair. The pixel values are adjusted through simple yet well-designed equations depending on different conditions. The computation method provides an easy recovery of the original values for the pixel pair as well. For some applications, it’s important to extract the hiding data as well as to recover the original media. In order to apply to a wider range of applications, more and more reversible data hiding (RDH) schemes are introduced or enhanced in the recent decades. Therefore, the two goals of the novel scheme proposed are to increase embedding capacity and to recover original media easily. For vector quantization (VQ) compression, it’s a well-known and efficient method to compress images. A well-trained codebook is crucial to maintain the visual quality of recovered images as good as possible. An index table is generated based on the codebook to full-fill the purpose of compression. Most of studies utilize index tables as the embedding carriers for VQ or VQ-variant compression methods. There are a few state-of-the-art schemes make use of codebooks to embed secret and our proposed scheme extends the study on the codebook embedding. The codewords in a codebook are divided into pixel pairs and secret bits are embedded by adjusting the pixel values of these split pairs to form a stego codebook. During extraction, secret bits are extracted first out from the stego codebook and a recovered codebook is obtained before recovering VQ compressed images. © 2024 SPIE.

关键词： Pixels

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Fuzzy-Based Weighted Federated Machine Learning Approach for Sustainable Energy Management with IoE Integration

Fuzzy-Based Weighted Federated Machine Learning Approach for...

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2024 Systems and information Engineering Design Symposium, SIEDS 2024

作者： Ghazal, Taher M. Iqbal Janjua, Jamshaid Abbas, Sagheer Fatima, Areej Saleem, Muhammad Khan, Muhammad Adnan Alqarafi, Abdulrahman Khalifa University Centre for Cyber Physical Systems Computer Science Department Abu Dhabi United Arab Emirates Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Selangor Malaysia National College of Business Administration and Economics School of Computer Sciences Lahore Pakistan Al-Khawarizmi Institute of Computer Science Lahore Pakistan Bahria University Department of Computer Science Lahore Pakistan LGU Department of Computer Science Lahore Pakistan Minhaj University School of Computer Science Lahore Pakistan Skyline University College School of Computing Sharjah United Arab Emirates Riphah International University Riphah School of Computing and Innovation Lahore Pakistan Taibah University College of Computer Science and Engineering Medina42353 Saudi Arabia

ISBN: (纸本)9798350385144

The considerable surge in energy consumption due to population growth and the use of new technology has posed significant challenges to energy security and the environment. Managing energy consumption on the consumer side is crucial as the demand for energy continues to increase. Consumers need to monitor their daily usage and understand consumption standards to prepare themselves for energy efficiency and cost savings. To address these challenges, a Smart Energy Management System (SEMS) based on the Internet of Energy (IoE) has been developed. This system uses day-Ahead planning and accurate energy availability forecasting to manage energy demand in a smart environment with high sustainable energy penetration. The Fuzzy based Weighted Federated Learning (FWFML) approach is integrated into the system to optimize energy management. The SEMS system monitors energy usage at the user level, and a review of management plans has been introduced to improve energy efficiency in terms of 93.5% accuracy, and 6.5% miss-rate. This research work also highlights future challenges in developing SEMS to increase energy efficiency in a more robust manner. © 2024 IEEE.

关键词： Energy management systems

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E-textiles for emotion interaction: a scoping review of trends and opportunities

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Personal and Ubiquitous Computing 2024年第3-4期28卷 549-577页

作者： Jiang, Mengqi Wang, Yimin Nanjappan, Vijayakumar Bai, Ziqian Liang, Hai-Ning School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Computer Science and Information Technology University College Cork Cork Ireland Center for Ubiquitous Computing University of Oulu Oulu Finland Department of Computing Xi’an Jiaotong-Liverpool University Suzhou China

There has been a proliferation of emotion-related interactive textiles in recent years. This research conducted a comprehensive scoping review of the literature on emotion-related interactive textiles design. In total, 75 design studies were identified from their abstracts and analyzed with social network analysis and text mining methods. These studies were categorized into different aims (emotion expression, emotion communication, emotion reflection, emotion regulation, emotional effect, emotional experience, and emotion analysis). This review also analyzed details of prototypes and experimental design, such as textile form, textile function, feedback mechanism, experiment method, evaluation scale, and empirical findings. Then we evaluated these studies based on the relationship of their research aim, textiles, emotion, interaction mechanism, etc. The findings suggest that interactive textiles can aid in emotion presentation, modulation, and creating unique emotional experiences. Interactive textiles, feedback mechanisms, and bodily interaction all serve essential functions and benefit emotional interaction. Last, this review reflected on the critical research directions of emotion-related interactive textiles, including connecting interactive textiles with biofeedback, designing interactive textiles with sensory feedback mechanisms, and increasing bodily interaction for dynamic emotion. Further, this research provided insights into the research gaps, from elaborating on the experiment and exploring the materiality of interactive textiles to concerning privacy and user acceptance. Interactive textiles bridge textiles and emotion together to aid emotional well-being in people’s daily lives. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Smart textiles

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IDSDeep-CCD: intelligent decision support system based on deep learning for concrete cracks detection

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Multimedia Tools and Applications 2025年第12期84卷 10013-10026页

作者： Abualigah, Sayel M. Al-Naimi, Ahmad F. Sachdeva, Gagan AlAmri, Omran Abualigah, Laith Department of Computer Information Systems Jordan University of Science and Technology Irbid Jordan Gagan Sachdeva Dubai United Arab Emirates Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Computer Science Department Al al-Bayt University Mafraq25113 Jordan Research Center University of Tabuk Tabuk71491 Saudi Arabia MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied Science Research Center Applied Science Private University Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

In an era where Intelligent Decision Support Systems (IDSS) are integral to managing the vast data from Internet of Everything (IoE) systems, this study introduces IDSDeep-CCD, a novel IDSS approach for detecting concrete cracks, a critical issue in civil infrastructure maintenance. Traditional visual inspection methods for crack detection are time-consuming and error-prone. To address this, IDSDeep-CCD employs deep learning, utilizing an open-source dataset of concrete crack images for enhanced accuracy. The system's two-stage approach, featuring feature extraction via pre-trained models and a fully connected network for classification, significantly outperforms existing methods. Our results demonstrate a remarkable 99.9% accuracy rate in crack detection without data augmentation, marking a notable advancement in automatic detection technology. This breakthrough offers practical benefits for the industry by enabling more precise and efficient identification of concrete cracks, paving the way for timely and accurate remedial actions. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep neural networks

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CHART:Intelligent Crime Hotspot Detection and Real-Time Tracking Using Machine Learning

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computers, Materials & Continua 2024年第12期81卷 4171-4194页

作者： Rashid Ahmad Asif Nawaz Ghulam Mustafa Tariq Ali Mehdi Tlija Mohammed AEl-Meligy Zohair Ahmed University Institute of Information Technology PMAS Arid Agriculture UniversityRawalpindi46000Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia Jadara University Research Center Jadara UniversityIrbid21110Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Science and Engineering Central South UniversityChangsha410083China

Crime hotspot detection is essential for law enforcement agencies to allocate resources effectively,predict potential criminal activities,and ensure public *** methods of crime analysis often rely on manual,time-consuming processes that may overlook intricate patterns and correlations within the *** some existing machine learning models have improved the efficiency and accuracy of crime prediction,they often face limitations such as overfitting,imbalanced datasets,and inadequate handling of spatiotemporal *** research proposes an advanced machine learning framework,CHART(Crime Hotspot Analysis and Real-time Tracking),designed to overcome these *** proposed methodology begins with comprehensive data collection from the police *** dataset includes detailed attributes such as crime type,location,time and demographic *** key steps in the proposed framework include:Data Preprocessing,Feature Engineering that leveraging domain-specific knowledge to extract and transform relevant *** Map Generation that employs Kernel Density Estimation(KDE)to create visual representations of crime density,highlighting hotspots through smooth data point distributions and Hotspot Detection based on Random Forest-based to predict crime likelihood in various *** Experimental evaluation demonstrated that CHART shows superior performance over benchmark methods,significantly improving crime detection accuracy by getting 95.24%for crime detection-I(CD-I),96.12%for crime detection-II(CD-II)and 94.68%for crime detection-III(CD-III),*** designing the application with integrating sophisticated preprocessing techniques,balanced data representation,and advanced feature engineering,the proposed model provides a reliable and practical tool for real-world crime *** of crime hotspots enables law enforcement agencies to strategize effectively,focusing resources on high-risk areas and thereby enhanc

关键词： Crime hotspot heat map kernel density estimation(KDE) support vector machine(SVM)

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Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding

arXiv

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arXiv 2024年

作者： Leng, Jiaqi Li, Joseph Peng, Yuxiang Wu, Xiaodi Department of Mathematics University of Maryland College Park United States Department of Computer Science University of Maryland College Park United States Joint Center for Quantum Information and Computer Science University of Maryland United States

Many promising quantum applications depend on the efficient quantum simulation of an exponentially large sparse Hamiltonian, a task known as sparse Hamiltonian simulation, which is fundamentally important in quantum computation. Although several theoretically appealing quantum algorithms have been proposed for this task, they typically require a black-box query model of the sparse Hamiltonian, rendering them impractical for near-term implementation on quantum devices. In this paper, we propose a technique named Hamiltonian embedding. This technique simulates a desired sparse Hamiltonian by embedding it into the evolution of a larger and more structured quantum system, allowing for more efficient simulation through hardware-efficient operations. We conduct a systematic study of this new technique and demonstrate significant savings in computational resources for implementing prominent quantum applications. As a result, we can now experimentally realize quantum walks on complicated graphs (e.g., binary trees, glued-tree graphs), quantum spatial search, and the simulation of real-space Schrödinger equations on current trapped-ion and neutral-atom platforms. Given the fundamental role of Hamiltonian evolution in the design of quantum algorithms, our technique markedly expands the horizon of implementable quantum advantages in the NISQ era. Copyright © 2024, The Authors. All rights reserved.

关键词： Hamiltonians

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The Prospects of quantum Secure Communication for Secret Sharing

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IEEE Nanotechnology Magazine 2023年第2期17卷 38-44页

作者： Chou, Yao-Hsin Tseng, Kuo-Chun Kuo, Shu-Yu Kuo, Sy-Yen Sheu, Bing National Chi Nan University Department of Computer Science and Information Engineering Nantou Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan Taiwan National Taiwan University Department of Physics and Center for Theoretical Physics Taipei Taiwan National Taiwan University Department of Electrical Engineering Taipei Taiwan Chang Gung University Department of Electronics Engineering Taoyuan Taiwan

quantum computing and secure communication have gained considerable interest in recent years, as quantum computing has a potent ability to accelerate certain complex problems, such as factoring problems and discrete logarithms, which are important foundations of traditional computer security. With the rapid development of quantum computers, some secure communication protocols based on certain mathematical problems will face a significant danger, and quantum properties can be used to construct quantum secure communication and quantum cryptography that can achieve unconditional security. Among many topics of quantum cryptography, quantum secret sharing (QSS) is an important and challenging issue that provides scenarios to store highly sensitive, important, and confidential information. In this article, we systematically illustrate the development of QSS and how it operates, as well as its challenging issues and future directions. © 2007-2011 IEEE.

关键词： quantum entanglement

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Real-Time Finger-Video Analysis for Accurate Identity Verification in Mobile Devices

Real-Time Finger-Video Analysis for Accurate Identity Verifi...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Shrestha, Sulabh Marasco, Emanuela Norouzlou, Babek H. George Mason University Department of Computer Science VA United States George Mason University Center for Secure Information Systems VA United States

ISBN: (纸本)9798350362480

The rapid advancement of smartphone technology, driven by sophisticated cameras and accelerated computing capabilities, has fueled the demand for reliable and secure identity verification solutions. Finger photo recognition has emerged as a popular and touchless alternative for secure smartphone unlocking. However, systems reliant solely on single RGB images face substantial challenges, including device variability, inconsistent backgrounds, and varying lighting conditions, which can compromise their effectiveness. This research addresses the limitations of current finger-based biometric systems by introducing a novel identity verification system that leverages the rich and dynamic information captured in finger-video data. The proposed approach, VIDVerify, combines binary classification, reduced information redundancy, and loss of cosine embedding to create a robust identity verification pipeline. VIDVerify employs a Siamese architecture with joint embeddings and three complementary loss functions: VICReg loss for redundancy reduction, focal loss for self-class balancing, and cosine embedding loss for video data optimization. The system is evaluated using the Multi-Movement Finger-Video (MMFV) database, which captures finger movements across multiple axes. By comparing convolutional backbones (ResNets, MobileNets) with transformer-based backbones (Swin Transformers), this research establishes a new benchmark for finger-video-based identity verification, paving the way for future advancements in this field. The code is available on GitHub: ***/sulabh-shr/fingerprint. © 2024 IEEE.

关键词： Smartphones

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