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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

TSdetector: Temporal-Spatial Self-correction Collaborative Learning for Colonoscopy Video Detection

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arXiv 2024年

作者： Wang, Kai-Ni Wang, Haolin Zhou, Guang-Quan Wang, Yangang Yang, Ling Chen, Yang Li, Shuo School of Biological Science and Medical Engineering Southeast University Nanjing China Jiangsu Key Laboratory of Biomaterials and Devices Southeast University Nanjing China Laboratory of Image Science and Technology Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China TUGE Healthcare Nanjing China Institute of Medical Technology Peking University Health Science Center China Department of Computer and Data Science Department of Biomedical Engineering Case Western Reserve University United States

CNN-based object detection models that strike a balance between performance and speed have been gradually used in polyp detection tasks. Nevertheless, accurately locating polyps within complex colonoscopy video scenes remains challenging since existing methods ignore two key issues: intra-sequence distribution heterogeneity and precision-confidence discrepancy. To address these challenges, we propose a novel Temporal-Spatial self-correction detector (TSdetector), which first integrates temporal-level consistency learning and spatial-level reliability learning to detect objects continuously. Technically, we first propose a global temporal-aware convolution, assembling the preceding information to dynamically guide the current convolution kernel to focus on global features between sequences. In addition, we designed a hierarchical queue integration mechanism to combine multi-temporal features through a progressive accumulation manner, fully leveraging contextual consistency information together with retaining long-sequence-dependency features. Meanwhile, at the spatial level, we advance a position-aware clustering to explore the spatial relationships among candidate boxes for recalibrating prediction confidence adaptively, thus eliminating redundant bounding boxes efficiently. The experimental results on three publicly available polyp video dataset show that TSdetector achieves the highest polyp detection rate and outperforms other state-of-the-art methods. The code can be available at https://***/soleilssss/TSdetector. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

DDPS: Dynamic Differential Pricing-based Edge Offloading system with Energy Harvesting Devices

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arXiv 2024年

作者： Xue, Hai Xia, Yun Xiong, Neal N. Zhang, Di Pei, Songwen School of Optical- Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States School of Electrical and Information Engineering Zhengzhou University the Henan International Joint Laboratory of Intelligent Health Information System the National Telemedicine Center National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China

Mobile edge computing (MEC) paves the way to alleviate the burden of energy and computation of mobile users (MUs) by offloading tasks to the network edge. To enhance the MEC server utilization by optimizing its resource allocation, a well-designed pricing strategy is indispensable. In this paper, we consider the edge offloading scenario with energy harvesting devices, and propose a dynamic differential pricing system (DDPS), which determines the price per unit time according to the usage of computing resources to improve the edge server utilization. Firstly, we propose an offloading decision algorithm to decide whether to conduct the offloading operation and how much data to be offloaded if conducted, the algorithm determines offloading operation by balancing the energy harvested with the energy consumed. Secondly, for the offloading case, we formulate the game between the MUs and the server as a Stackelberg game, and propose a differential pricing algorithm to determine the optimal computing resources required by MUs. Furthermore, the proposed algorithm also reallocates computing resources for delay-sensitive devices while server resources are surplus after the initial allocation, aiming to make full use of the server computing resources. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DDPS scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

Wireless/wired integrated transmission for industrial cyber-physical systems: risk-sensitive co-design of 5G and TSN protocols

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science China(information sciences) 2022年第1期65卷 56-71页

作者： Yajing ZHANG Qimin XU Xinping GUAN Cailian CHEN Mingyan LI Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management College of Computer Science Chongqing University

The growing popularity of intelligent manufacturing is driven by deterministic transmission demands of applications in industrial cyber-physical systems(ICPS). However, the ossified shortages of industrial wireless communication such as diverse quality of service(Qo S) and complex signaling processes incur a severe long tail of transmission delay distribution. As a solution, the 5 th generation(5 G) wireless communication technology provides ultra-reliable and low-latency communication(URLLC) for industry scenarios. Moreover, the newly proposed time-sensitive networking(TSN) standards guarantee the transmission determinacy by gate mechanism. In this paper, we propose a heterogeneous time-sensitive network(HTSN) co-designed by 5 G and TSN. We first develop a predictive multi-priority wireless scheduling mechanism based on semi-persistent scheduling(SPS) to reduce signaling delay by reserving resources in *** we propose an adaptive data injection mechanism for TSN based on per-stream filtering and policing(PSFP), which dynamically adjusts the priority of data for queue injection in TSN. To further reduce the long tail of delay, we employ a risk-sensitive learning method to improve the worst-case delay. Simulations on a hot rolling production scenario demonstrate that the proposed mechanisms under HTSN achieve great performance in terms of integrated delay and resource utilization.

关键词： industrial cyber-physical systems (ICPS) 5G-TSN co-design wireless/wired integrated network risk-sensitive reinforcement learning deterministic communication

Target-Oriented WiFi Sensing for Respiratory Healthcare: from Indiscriminate Perception to In-Area Sensing

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IEEE Network 2024年

作者： Wang, Meng Huang, Jinyang Zhang, Xiang Liu, Zhi Li, Meng Zhao, Peng Yan, Huan Sun, Xiao Dong, Mianxiong Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligence Machine School of Computer and Information Hefei230601 China University of Science and Technology of China CAS Key Laboratory of Electromagnetic Space Information Hefei230026 China The University of Electro-Communications Department of Computer and Network Engineering Tokyo1828585 Japan Guizhou Normal University School of Big Data and Computer Science Guiyang550025 China Muroran Institute of Technology Department of Sciences and Informatics 0508585 Japan

Driven by the vision of integrated sensing and communication (ISAC) toward 6G technology, the WiFi-based respiration sensing approach has emerged as a highly competitive candidate for advanced healthcare services. Nevertheless, the indiscriminate perception of all the moving objects within the sensing area raises challenges for system stability and robustness for real-world deployment, especially for the susceptibility to motion interference from other people. Meanwhile, thanks to the emerging in-area wireless sensing technologies, i.e., beamforming, the dynamic environment tolerance of these technologies gives crucial opportunities for target-oriented WiFi-based healthcare services. This article discusses the compelling intersection of in-area WiFi sensing and the future of target-oriented intelligent respiratory healthcare network services. We first present a novel WiFi-based healthcare-assisting framework tailored for inter-user motion interference-tolerable (IMIT) sensing. The detailed components of low-level signal preprocessing, target-direction signal extraction, and healthcare-related services are discussed. By utilizing CSI beamforming technology, which adjusts a directional beam toward the desired direction and adaptively places beam nulls in noisy directions, we can mitigate motion interference and achieve target-oriented healthcare sensing. Finally, we discuss open challenges and potential solutions for target-oriented WiFi healthcare sensing. © 1986-2012 IEEE.

关键词： Wireless local area networks (WLAN)

CoMiX: Cross-Modal Fusion with Deformable Convolutions for HSI-X Semantic Segmentation

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arXiv 2024年

作者： Zhang, Xuming Gu, Xingfa Tian, Qingjiu Bruzzone, Lorenzo International Institute for Earth System Science Nanjing University Nanjing210023 China Key Laboratory of Computational Optical Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Department of Information Engineering and Computer Science University of Trento Trento38050 Italy

Pixel-wise semantic segmentation of hyperspectral images (HSIs) enables detailed and accurate analysis of complex scenes, benefiting various applications. Improving HSI semantic segmentation by exploiting complementary information from a supplementary data type (here denoted as X-modality) is promising but challenging due to differences in imaging sensors, image content, and resolution. Current cross-model fusion techniques have limitations in enhancing modality-specific and modality-shared information, as well as in capturing dynamic information interactions and fusion between different modalities. In response, this study proposes CoMiX, a cross-modal fusion framework with deformable convolutions (DCNs) for pixel-wise HSI-X semantic segmentation. CoMiX is an asymmetric encoder-decoder architecture designed to extract, calibrate, and fuse information from HSI and X modalities. Its pipeline includes an encoder with two parallel and interacting backbones and a lightweight all-multilayer perceptron (ALL-MLP) decoder. Within the encoder, four stages are deployed, each incorporating 2D DCN blocks for the X-model to adapt to geometric variations, and 3D DCN blocks for HSIs to adaptively aggregate spatial-spectral features. Additionally, each stage includes a Cross-Modality Feature enhancement and eXchange (CMFeX) module and a feature fusion module (FFM). CMFeX is designed to exploit spatial and spectral correlations from both modalities to recalibrate and enhance modality-specific and modality-shared features while adaptively exchanging complementary information between them. Outputs from CMFeX are fed into the FFM for fusion and passed to the next stage for further information learning. Finally, the outputs from each FFM are integrated by the ALL-MLP decoder for final prediction. Extensive experiments demonstrate that our CoMiX achieves superior performance and generalizes well to various multimodal recognition tasks. The CoMiX code will be released. Copyright © 2024, Th

关键词： Semantic Segmentation

Simulation Mathematical Modeling of Radar Signals with a Low Probability of Their Unauthorized Reception 3

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Simulation Mathematical Modeling of Radar Signals with a Low...

3rd IEEE KhPI Week on advanced Technology, KhPI Week 2022

作者： Galkyn, Sergii Khriapkin, Oleksandr Kaliuzhnyi, Mykola Guo, Qiang National Technical University «kharkiv Polytechnic Institute» Department of Computer Science and Intellectual Property Kharkiv Ukraine Kharkiv National University of Radio Electronics Department of System Engineering Kharkov Ukraine Kharkiv National University of Radio Electronics Problem Research Laboratory Kharkiv Ukraine College of Information and Telecommunication Harbin Engineering University Harbin China

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

a technique and software for modeling radar signals with a low probability of their unauthorized reception at the input of the monitoring tool receiver are presented. The technique is illustrated by the formation of a signal model based on the Costas sequence. The methodology and software are designed to develop methods and algorithms: detection, measurement of parameters, recognition of radio emissions of radio electronic equipment, recognition of radio electronic equipment © 2022 IEEE.

关键词： Radar

Hierarchical Recording Architecture for Three-Dimensional Magnetic Recording

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arXiv 2025年

作者： Jian, Yugen Luo, Ke Chen, Jincai Fong, Xuanyao Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Computer of Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan430074 China

Three-dimensional magnetic recording (3DMR) is a highly promising approach to achieving ultra-large data storage capacity in hard disk drives. One of the greatest challenges for 3DMR lies in performing sequential and correct writing of bits into the multi-layer recording medium. In this work, we have proposed a hierarchical recording architecture based on layered heat-assisted writing with a multi-head array. The feasibility of the architecture is validated in a dual-layer 3DMR system with FePt-based thin films via micromagnetic simulation. Our results reveal the magnetization reversal mechanism of the grains, ultimately attaining appreciable switching probability and medium signal-to-noise ratio (SNR) for each layer. In particular, an optimal head-to-head distance is identified as the one that maximizes the medium SNR. Optimizing the system’s noise resistance will improve the overall SNR and allow for a smaller optimal head-to-head distance, which can pave the way for scaling 3DMR to more recording layers. Copyright © 2025, The Authors. All rights reserved.

关键词： Hard disk storage

The Knowledge of Cyber-Security Vulnerabilities in an Institution of Higher and University Education. A Case of ISP-Bukavu (Institut Supérieur Pédagogique de Bukavu) (TTC = Teachers’ Training College)

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Journal of computer and Communications 2023年第4期11卷 12-32页

作者： Dominique Wasso Kiseki Vincent Havyarimana Therence Niyonsaba Désiré Lumonge Zabagunda Walumbuka Ilundu Wail Thabo Semong Computer Engineering University of Burundi (UB) Bujumbura Burundi Ecole Normale Supérieure (ENS) Bujumbura Burundi University Research Laboratory in Modeling and Applied Statistical Engineering (LURMISTA) Nyamugerera Bujumbura Department of Physics and Technology ISP Bukavu Democratic Republic of Congo Department of Management Computer Science ISP Bukavu Democratic Republic of Congo Departement of Computer science and Information System Bostwana International University of Science and Technology Palapye Bostwana

This study pursues the objective of analyzing and verifying the knowledge of the agents of the Institut Supérieur Pédagogique/ISP-Bukavu (TTC = Teachers’ training College) in relation to the practical flaws resulting from the lack of knowledge of the observable rules in information system security. In a clearer way, it aims to verify the level of knowledge of the vulnerabilities, to verify the level of use of the antivirus software, to analyze the frequency of use of Windows update, the use of an anti-spyware software as well as a firewall software on the computer. Through a survey conducted on a sample of 100 agents of the Institut Supérieur Pédagogique/ISP-Bukavu (TTC = Teachers’ training College), the results revealed that 48% of the sample has no knowledge on computer vulnerabilities;for the use of antivirus software: 47% do not use the antivirus;for Windows update: 29% never update the Windows operating system;for anti-spyware: 48% never use;for the firewall: 50% are not informed. In fine, our results proposed a protection model VMAUSP (Vulnerability Measurability Measures Antivirus, Update, Spyware and Firewall) to users based on the behavioral approach, learning how the model works.

关键词： Threats Vulnerabilities Cybersecurity Anti-Spyware Firewall Cyber-Attack Antivirus