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Telecommunications and Intelligent Systems (ICTIS), International Conference on

作者： Mohamed Rafik Aymene Berkani Ammar Chouchane Yassine Himeur Anes Abdennebi Seref Sagiroglu Abbes Amira Research Laboratory in Advanced Electronics Systems (LSEA) University Yahia Fares of Medea Medea Algeria Laboratory of LI3C University Biskra University Center of Barika Barika Algeria College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Software and Information Technology Engineering École de Technologie Supérieure Montréal Canada Artificial Intelligence and Big Data Analytics Security R&D Center Gazi University Ankara Turkey Department of Computer Science University of Sharjah Sharjah United Arab Emirates

ISBN: (数字)9798331527396

ISBN: (纸本)9798331527402

Ensuring safety in smart buildings is crucial due to the increasing prevalence of smoke and fire hazards in modern environments. This paper introduces a novel privacy-preserving FL approach based on a CNN1D for smoke and fire detection in smart buildings. Our system integrates data from wearable environmental sensors to train a lightweight, edge-deployable DL-CNN1D model, ensuring data privacy while enabling collaborative learning across distributed clients using Federated Averaging (FedAvg) aggregation. Experiments conducted on a comprehensive air measurement dataset for smoke and fire detection demonstrate exceptional performance, with the global model achieving 99.97% accuracy, 99.96% precision, in smoke and fire recognition. Our model demonstrates a low communication cost of 0.4 MB, underscoring its efficiency for real-time applications. Our FL-based approach represents a significant step towards balancing the need for robust safety systems with growing privacy concerns in smart building environments.

关键词： Privacy Smart buildings Costs Federated learning Atmospheric modeling Data models Convolutional neural networks Wearable sensors Monitoring Intelligent sensors

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A Tutorial on Movable Antennas for Wireless Networks

arXiv

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arXiv 2025年

作者： Zhu, Lipeng Ma, Wenyan Mei, Weidong Zeng, Yong Wu, Qingqing Ning, Boyu Xiao, Zhenyu Shao, Xiaodan Zhang, Jun Zhang, Rui Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Chengdu611731 China National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electronic and Information Engineering Beihang University Beijing100191 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada State Key Laboratory of CNS/ATM MIIT Key Laboratory of Complex-field Intelligent Sensing Beijing Institute of Technology Beijing100081 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigatio

关键词： Antenna arrays

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A Distributed Privacy Preservation Approach for Big Data in Public Health Emergencies Using Smart Contract and SGX

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computers, Materials & Continua 2020年第10期65卷 723-741页

作者： Jun Li Jieren Cheng Naixue Xiong Lougao Zhan Yuan Zhang Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China School of Compute Science and Cyberspace Security Hainan UniversityHaikou570228China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA Key Laboratory of Internet Information Retrieval of Hainan Province Hainan UniversityHaikou570228China

security and privacy issues have become a rapidly growing problem with the fast development of big data in public ***,big data faces many ongoing serious challenges in the process of collection,storage,and *** them,data security and privacy problems have attracted extensive *** an effort to overcome this challenge,this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions(SGX).First of all,we define SGX as a trusted edge computing node,design data access module,data protection module,and data integrity check module,to achieve hardware-enhanced data privacy ***,we design a smart contract framework to realize distributed data access control management in a big data *** crucial role of the smart contract was revealed by designing multiple access control contracts,register contracts,and history *** control contracts provide access control methods for different users and enable static access verification and dynamic access verification by checking the user’s properties and history *** contract contains user property information,edge computing node information,the access control and history smart contract information,and provides functions such as registration,update,and *** contract records the historical behavior information of malicious users,receives the report information of malicious requestors from the access control contract,implements a misbehavior check method to determines whether the requestor has misbehavior,and returns the corresponding ***,we design decentralized system architecture,prove the security properties,and analysis to verify the feasibility of the *** demonstrate that our method can effectively improve the timeliness of data,reduce network latency,and ensure the security,reliability,and traceability of data.

关键词： SGX big data privacy protection smart contract access control

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Near-Field Beam Focusing Pattern and Grating Lobe Characterization for Modular XL-Array

Near-Field Beam Focusing Pattern and Grating Lobe Characteri...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Xinrui Li Zhenjun Dong Yong Zeng Shi Jin Rui Zhang National Mobile Communications Research Laboratory and Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Purple Mountain Laboratories Nanjing China The Chinese University of Hong Kong (Shenzhen) and Shenzhen Research Institute of Big Data Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

In this paper, we investigate the near-field modelling and analyze the beam focusing pattern for modular extremely large-scale array (XL-array) communications. As modular XL-array is physically and electrically large in general, the accurate characterization of amplitude and phase variations across its array elements requires the non-uniform spherical wave (NUSW) model, which, however, is difficult for performance analysis and optimization. To address this issue, we first present two ways to simplify the NUSW model by exploiting the unique regular structure of modular XL-array, termed sub-array based uniform spherical wave (USW) models with different or common angles, respectively. Based on the developed models, the near-field beam focusing patterns of XL-array communications are derived. It is revealed that compared to the existing collocated XL-array with the same number of array elements, modular XL-array can significantly enhance the spatial resolution, but at the cost of generating undesired grating lobes. Fortunately, different from the conventional far-field uniform plane wave (UPW) model, the near-field USW model for modular XL-array exhibits a higher grating lobe suppression capability, thanks to the non-linear phase variations across the array elements. Finally, simulation results are provided to verify the near-field beam focusing pattern and grating lobe characteristics of modular XL-array.

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Permutation polynomials x~(2k+1+3)+ax2k+2+bx over F_(22k) and their differential uniformity

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science China(information sciences) 2020年第10期63卷 255-257页

作者： Jie PENG Lijing ZHENG Chunsheng WU Haibin KAN Mathematics and Science College Shanghai Normal University School of Mathematics and Physics University of South China Department of Mathematics Lianyungang Normal University Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan University Fudan-Zhongan Joint Laboratory of Blockchain and Information Security Shanghai Blockchain Engineering Research Center Shanghai Institute for Advanced Communication and Data Science Shanghai Institute of Intelligent Electronics & Systems

Dear editor,A polynomial f（x）∈Fq[x] is called a permutation polynomial （PP） over the finite field Fq if the associated mapping f:c （?） f（c） from Fq to itself is bijective.A PP f is called a complete permutation polynomial if f（x）+x is a *** over finite fields of even characteristic have wide applications,including cryptography,coding theory,and communication *** many block ciphers with substitution-permutation network structure,the substitution box is usually a PP over F_(22k)for some positive integer *** resist the differential attacks,the differential uniformity of this

关键词： Finite fields Permutation polynomial Binomial Trinomial Differential uniformity

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YOLO-TP: A process detection model of tunnel real scene based on gradient information interaction

YOLO-TP: A process detection model of tunnel real scene base...

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computer, Big Data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Jiaying Fan Shuping Pan Xinbo Jiang Shengtao Zhang Hongliang Liu Chuan Wang Jianghua Li Chenglin Ke Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Technological Innovation Department Shandong Hi-Speed Group Co Ltd JiNan China School of Qilu Transportation Shandong University JiNan China China Railway 14th Bureau Group First Engineering Development Co. Ltd RiZhao China

ISBN: (数字)9798331533991

ISBN: (纸本)9798331534004

Target detection technology is an effective method to detect tunnel operation safety. Although the field has made some progress in detection models, the lack of datasets and detection models has hindered its development. We produce and propose Tunnel Processes data (TP), a challenging dataset of high-precision real-world tunnel process target detection that reduces the limitations of research in this field. TP has a high resolution: 1920×1080, 1734images,9 categories. TP is the first tunnel process data set under construction to date, and its fidelity exceeds that of other tunnel process datasets in the field of target detection. In addition, we also propose a YOLO-TP benchmark model to make up for the lack of a high-precision tunnel process image target detection baseline model. Experiments on TP datasets demonstrate their validity, and experiments on the dataset presented in this paper demonstrate the validity of the benchmark model.

关键词： Accuracy Image resolution Computational modeling Object detection Benchmark testing Big Data Feature extraction Data models Safety Artificial intelligence

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Multiregion Multiscale Image Segmentation with Anisotropic Diffusion 25th

Multiregion Multiscale Image Segmentation with Anisotropic D...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Prasath, V. B. Surya Thanh, Dang Ngoc Hoang Hai, Nguyen Hoang Dvoenko, Sergey Department of Electrical Engineering and Computer Science University of Cincinnati CincinnatiOH45221 United States Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Information Technology School of Business Information Technology University of Economics Ho Chi Minh City Ho Chi Minh City Viet Nam Department of Computer Science Vietnam-Korea University of Information and Communication Technology – The University of Danang Danang Viet Nam Department of Information Security Institute of Applied Mathematics and Computer Science Tula State University Tula city Russia

ISBN: (纸本)9783030688202

We present a multiregion image segmentation approach which utilizes multiscale anisotropic diffusion based scale spaces. By combining powerful edge preserving anisotropic diffusion smoothing with isolevel set linking and merging, we obtain coherent segments which are tracked across multiple scales. A hierarchical tree representation of the given input image with progressively simplified regions is used with intra-scale splitting and inter-scale merging for obtaining multiregion segmentations. Experimental results on natural and medical images indicate that multiregion, multiscale image segmentation (MMIS) approach obtains coherent segmentation results. © 2021, Springer Nature Switzerland AG.

关键词： Diffusion

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Efficient Channel Estimation for Millimeter Wave and Terahertz Systems Enabled by Integrated Super-resolution Sensing and Communication

arXiv

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arXiv 2024年

作者： Xu, Jingran Wang, Huizhi Zeng, Yong Xu, Xiaoli Wu, Qingqing Yang, Fei Chen, Yan Jamalipour, Abbas The National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China The Wireless Technology Lab. 2012 Lab Shanghai Huawei Technologies Co. Ltd. Shanghai201206 China The School of Electrical and Computer Engineering The University of Sydney CamperdownNSW2006 Australia

Integrated super-resolution sensing and communication (ISSAC) has emerged as a promising technology to achieve extremely high precision sensing for those key parameters, such as the angles of the sensing targets. In this paper, we propose an efficient channel estimation scheme enabled by ISSAC for millimeter wave (mmWave) and TeraHertz (THz) systems with a hybrid analog/digital beamforming architecture, where both the pilot overhead and the cost of radio frequency (RF) chains are significantly reduced. The key idea is to exploit the fact that subspace-based super-resolution algorithms such as multiple signal classification (MUSIC) can estimate channel parameters accurately without requiring dedicate a priori known pilots. In particular, the proposed method consists of two stages. First, the angles of the multi-path channel components are estimated in a pilot-free manner during the transmission of data symbols. Second, the multi-path channel coefficients are estimated with very few pilots. Compared to conventional channel estimation schemes that rely solely on channel training, our approach requires the estimation of much fewer parameters in the second stage. Furthermore, with channel multi-path angles obtained, the beamforming gain can be achieved when pilots are sent to estimate the channel path gains. To comprehensively investigate the performance of the proposed scheme, we consider both the basic line-of-sight (LoS) channels and more general multipath channels. We compare the performance of the minimum mean square error (MMSE) of channel estimation and the resulting beamforming gains of our proposed scheme with the traditional scheme that rely exclusively on channel training. It is demonstrated that our proposed method significantly outperforms the benchmarking scheme. Simulation results are presented to validate our theoretical findings. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

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A Hybrid Deep Learning Paradigm for Robust Feature Extraction and Classification for Cataracts

Applied AI Letters

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Applied AI Letters 2025年第2期6卷

作者： Ramakrishnan, Akshay Bhuvaneswari Madavan, Mukunth Manikandan, R. Gandomi, Amir H. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD United States Mukunth Madhavan AI Security Engineer Banglore India School of Computing SASTRA Deemed University Thanjavur India Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary Department of Computer Science Khazar University Baku Azerbaijan

The study suggests using a hybrid convolutional neural networks-support vector machines architecture to extract reliable characteristics from medical images and classify them as an ensemble using four different models. Manual processing of fundus images for the automated identification of ocular disorders is laborious, error-prone, and time-consuming. This necessitates computer-assisted technologies that can automatically identify different ocular illnesses from fundus images. The interpretation of the photos also plays a massive role in the diagnosis. Automating the diagnosing procedure reduces human mistakes and helps with early cataract detection. The oneDNN library available in the oneAPI Environment provided by Intel has been used to optimize all transfer learning models for better performance. The suggested approach is verified through a range of metrics in experiments using the openly accessible Ocular Disease Intelligent Recognition dataset. The MobileNet Model outperformed other transfer learning techniques with an accuracy of 0.9836. © 2025 The Author(s). Applied AI Letters published by John Wiley & Sons Ltd.

关键词： cataract computer-assisted fundus hybrid ocular oneAPI oneDNN transfer learning

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Multi-Functional Beamforming Design for Integrated Sensing, Communication, and Computation

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IEEE Transactions on Communications 2024年

作者： Zhao, Yapeng Wu, Qingqing Chen, Wen Zeng, Yong Liu, Ruiqi Mei, Weidong Hou, Fen Ma, Shaodan Shanghai Jiao Tong University Department of Electronic Engineering 200240 China University of Macau State Key Laboratory of Internet of Things for Smart City 999078 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China ZTE Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518057 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Macau Department of Electrical and Computer Engineering 999078 China

Integrated sensing and communication (ISAC) systems may face a heavy computation burden since the sensory data needs to be further processed. This paper studies a novel system that integrates sensing, communication, and computation, aiming to provide services for different objectives efficiently. This system consists of a multi-antenna multi-functional base station (BS), an edge server, a target, and multiple single-antenna communication users. The BS needs to allocate the available resources to efficiently provide sensing, communication, and computation services. Due to the heavy service burden and limited power budget, the BS can partially offload the tasks to the nearby edge server instead of computing them locally. We consider the estimation of the target response matrix, a general problem in radar sensing, and utilize Cramér-Rao bound (CRB) as the corresponding performance metric. To tackle the non-convex optimization problem, we propose both semidefinite relaxation (SDR)-based alternating optimization and SDR-based successive convex approximation (SCA) algorithms to minimize the CRB of radar sensing while meeting the requirement of communication users and the need for task computing. Furthermore, we demonstrate that the optimal rank-one solutions of both the alternating and SCA algorithms can be directly obtained via the solver or further constructed even when dealing with multiple functionalities. Simulation results show that the proposed algorithms can provide higher target estimation performance than state-of-the-art benchmarks while satisfying the communication and computation constraints. © 1972-2012 IEEE.

关键词： Convex optimization

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