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IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： Fan Wang Ruihong Jiang Yuan Liu Tingnan Bao Mugen Peng State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Zhejiang Laboratory Research Center for Space Computing System Hangzhou China School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada

ISBN: (数字)9798350362312

ISBN: (纸本)9798350362329

The rising demand for reliable, high-bandwidth satellite communications in far-reach areas drives the integration of low earth orbit (LEO) satellites into future 6G networks. In this paper, we investigate the deployment of reconfigurable intelligent surface (RIS) technology and rate splitting multiple access (RSMA) within LEO satellite systems to improve communication quality and system capacity. We derive closed-form expressions for outage probability (OP) and reliable throughput that validate the theoretical advantages of these technologies under various signal-to-noise ratio conditions. Numerical results demonstrate that, compared with traditional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) approaches, our RSMA and RIS-integrated framework significantly can reduce OP and enhance reliable throughput with an appropriate power-splitting factor, showcasing its superiority in RIS-enabled satellite communication scenarios.

关键词： NOMA Satellites Closed-form solutions computer network reliability Low earth orbit satellites Reconfigurable intelligent surfaces Reliability theory Throughput Multiaccess communication Satellite communications

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Fast and Scalable Gate-Level Simulation in Massively Parallel systems

Fast and Scalable Gate-Level Simulation in Massively Paralle...

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IEEE International Conference on computer-Aided Design

作者： Haichuan Hu Zichen Xu Yuhao Wang Fangming Liu Services Computing Technology and System Lab Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Mathematics and Computer Science Nanchang University Nanchang China Pengcheng Laboratory Shenzhen China

The natural bijection between a proposed circuit design and its graph representation shall allow any graph optimization algorithm deploying into many-core systems efficiently. However, this process suffers from the exponentially growing overhead and heavy memory footprint with the signal propagation. To conquer the unique challenge, we systematically study the simulation with millions of gates, and identify that the processing complexity could grow exponentially from the signal inputs, the skewness of the computational graph stays. Thus, we present ZhouBi, a fast and scalable gate-level simulation framework to fully exploit the parallelism from many-core systems. ZhouBi contributes in threefolds, (I) a graph representation that colors gate-level netlists and identifies skew partitions based on the graph skewness; (II) A set of heuristic algorithms that picks opportunistic and conservative algorithms to accelerate the simulation; (III) A system facility that supports selective mapping between simulation and many-core, providing a tradeoff between the risk of concurrent simulation fail and performance gain. We have prototyped ZhouBi and evaluated it with practical baselines. ZhouBi can achieve a 27.6× performance gain, as compared to the state-of-the-practice Veriwell without compromising any correctness. Our framework supports large graphs enabling scale-out gate-level simulations for chip design.

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Paired regions for shadow removal approach based on multi-features

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High Technology Letters 2023年第2期29卷 174-180页

作者：张之政 GUO Mingqiang WU Liang HUANG Ying CHEN Xueye Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034P.R.China National Engineering Research Center of Geographic Information System China University of GeosciencesWuhan 430074P.R.China School of Computer Science China University of GeosciencesWuhan 430074P.R.China Wuhan Zondy Cyber Technology Co. Ltd.Wuhan 430074P.R.China

The existence of shadow leads to the degradation of the image qualities and the defect of ground object *** removal is therefore an essential research topic in image processing *** biggest challenge of shadow removal is how to restore the content of shadow areas correctly while removing the shadow in the *** regions for shadow removal approach based on multi-features is proposed, in which shadow removal is only performed on related sunlit *** distance between regions is calculated to find the optimal paired regions with considering of multi-features(texture, gradient feature, etc.) *** in different scenes with peak signal-to-noise ratio(PSNR) and structural similarity(SSIM) evaluation indexes are chosen for *** results are shown with six existing comparison methods by visual and quantitative assessments, which verified that the proposed method shows excellent shadow removal effect, the brightness, color of the removed shadow area, and the surrounding non-shadow area can be naturally fused.

关键词： paired region feature distance texture peak signal-to-noise ratio(PSNR) structural similarity(SSIM)

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Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency

Detecting Backdoors During the Inference Stage Based on Corr...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Xiaogeng Liu Minghui Li Haoyu Wang Shengshan Hu Dengpan Ye Hai Jin Libing Wu Chaowei Xiao School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Software Engineering Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan University School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab Arizona State University

Deep neural networks are proven to be vulnerable to backdoor attacks. Detecting the trigger samples during the inference stage, i.e., the test-time trigger sample detection, can prevent the backdoor from being triggered. However, existing detection methods often require the defenders to have high accessibility to victim models, extra clean data, or knowledge about the appearance of backdoor triggers, limiting their practicality. In this paper, we propose the test-time corruption robustness consistency evaluation (TeCo) 1 1 https://***/CGCL-codes/TeCo, a novel test-time trigger sample detection method that only needs the hard-label outputs of the victim models without any extra information. Our journey begins with the intriguing observation that the backdoor-infected models have similar performance across different image corruptions for the clean images, but perform discrepantly for the trigger samples. Based on this phenomenon, we design TeCo to evaluate test-time robustness consistency by calculating the deviation of severity that leads to predictions' transition across different corruptions. Extensive experiments demonstrate that compared with state-of-the-art defenses, which even require either certain information about the trigger types or accessibility of clean data, TeCo outperforms them on different backdoor attacks, datasets, and model architectures, enjoying a higher AUROC by 10% and 5 times of stability.

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DSDFormer: An Innovative Transformer-Mamba Framework for Robust High-Precision Driver Distraction Identification

arXiv

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arXiv 2024年

作者： Chen, Junzhou Zhang, Zirui Yu, Jing Huang, Heqiang Zhang, Ronghui Xu, Xuemiao Sheng, Bin Yan, Hong Guangdong Provincial Key Laboratory of Intelligent Transportation System School of Intelligent Systems Engineering Sun Yat-Sen University Guangzhou510275 China The School of Computer Science and Engineering South China University of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University China The Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong

Driver distraction remains a leading cause of traffic accidents, posing a critical threat to road safety globally. As intelligent transportation systems evolve, accurate and real-time identification of driver distraction has become essential. However, existing methods struggle to capture both global contextual and fine-grained local features while contending with noisy labels in training datasets. To address these challenges, we propose DSDFormer, a novel framework that integrates the strengths of Transformer and Mamba architectures through a Dual State Domain Attention (DSDA) mechanism, enabling a balance between long-range dependencies and detailed feature extraction for robust driver behavior recognition. Additionally, we introduce Temporal Reasoning Confident Learning (TRCL), an unsupervised approach that refines noisy labels by leveraging spatiotemporal correlations in video sequences. Our model achieves state-of-the-art performance on the AUC-V1, AUC-V2, and 100-Driver datasets and demonstrates real-time processing efficiency on the NVIDIA Jetson AGX Orin platform. Extensive experimental results confirm that DSDFormer and TRCL significantly improve both the accuracy and robustness of driver distraction detection, offering a scalable solution to enhance road safety. Copyright © 2024, The Authors. All rights reserved.

关键词： Highway accidents

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An Haptic Display for Visually Impaired Pedestrian Navigation 1st

An Haptic Display for Visually Impaired Pedestrian Navigatio...

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1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Alzighaibi, Sara Bouaziz, Rahma Kammoun, Slim Information System Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia Computer Science Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia ReDCAD University of Sfax Sfax Tunisia Research Laboratory of Technologies of Information and Communication & Electrical Engineering University of Tunis Tunis Tunisia

ISBN: (纸本)9789811560477

Sight is one of the major senses that allows people to travel safely, freely, and independently of others. In their daily life, visually impaired people are confronting challenging tasks such as reading or writing. Navigation and direction finding, particularly in the unfamiliar environment, are remaining as one of the main issues for visually impaired (VI) individuals. Several ways have been emerged to help VI orientation and mobility such as electronic orientation aids which can be further studied and developed. This work aims to improve VI navigation by proposing a new tactile interface that will be designed and implemented with the use of vibrators and Arduino board. The proposed interface targets to increase the quality of life and independence for VI. Also, evaluation performed with VI pedestrian will give us further information and knowledge regarding haptic perceptions and effectiveness of such interface and interaction technique. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Navigation

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Effective Concurrency Testing for Go via Directional Primitive-Constrained Interleaving Exploration

Effective Concurrency Testing for Go via Directional Primiti...

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IEEE International Conference on Automated Software engineering (ASE)

作者： Zongze Jiang Ming Wen Yixin Yang Chao Peng Ping Yang Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System ByteDance Beijing China School of Computer Science and Technology Huazhong University of Science and Technology China

The Go language (Go/Golang) has been attracting increasing attention from the industry over recent years due to its strong concurrency support and ease of deployment. This programming language encourages developers to use channel-based concurrency, which simplifies the development of concurrent programs. Unfortunately, it also introduces new concurrency problems that differ from those caused by the mechanism of shared memory concurrency. However, there are only few works that aim to detect such Go-specific concurrency issues. Even state-of-the-art testing tools will miss critical concurrent bugs that require fine-grained and effective interleaving exploration. This paper presents GoPie, a novel testing approach for detecting Go concurrency bugs through primitive-constrained interleaving exploration. GoPie utilizes execution histories to identify new interleavings instead of relying on exhaustive exploration or random scheduling. To evaluate its performance, we applied GoPie to existing benchmarks and large-scale open-source projects. Results show that GoPie can effectively explore concurrent interleavings and detect significantly more bugs in the benchmark. Furthermore, it uncovered 11 unique previously unknown concurrent bugs, and 9 of which have been confirmed.

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A Lightweight Attention Network for Camouflaged Object Fixation Prediction

A Lightweight Attention Network for Camouflaged Object Fixat...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Qingbo Wu Guanxing Wu Shengyong Chen Key Laboratory of Computer Vision and Systems (Ministry of Education) Tianjin University of Technology Tianjin China Engineering Research Center of Learning-Based Intelligent System (Ministry of Education) Tianjin University of Technology Tianjin China School of Computer Science and Engineering Tianjin University of Technology Tianjin China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

This paper proposes a novel encoder-decoder architecture for camouflaged object fixation prediction (COFP), which builds on a large-kernel decomposition technique and depth-wise separable convolution embedded attention. Specifically, the encoder with the large-kernel decomposition adopts a Visual Attention Network (VAN) as the backbone to extract more accurate features, and the decoder predicts fixation maps from concealed objects using the attention module incorporating depth-wise separable convolution. Both designs aim to reduce the number of learnable parameters, making the model lighter and simultaneously maintaining the performance of COFP. In addition, we propose using the reverse Kullback-Leibler Divergence (KLDiv) as the loss function. Extensive experiments demonstrate that the proposed method performs well against SOTA approaches in quality and quantity.

关键词： Industrial electronics Visualization Accuracy Convolution Feature extraction Decoding

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On-board Time-varying Topology Self Prediction Routing Network Communication Technology 15

On-board Time-varying Topology Self Prediction Routing Netwo...

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15th IEEE International Conference on Advanced Infocomm Technology, ICAIT 2023

作者： Yu, Jiyang Huang, Dan Wu, Nan Li, Jinyang Li, Wenjie Wang, Xianjie Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China Chongqing University of Technology China Research & Development Academy of Machinery Equipment Chongqing China Fangzhou Key Technology Laboratory Beijing Institute of Computer Technology and Applications Beijing China Chongqing Feima Innovation Research Institute Beijing Blackstone Matrix Technology Co. Ltd Chongqing China Chongqing University of Technology College of Computer Science and Engineering Chongqing China

ISBN: (纸本)9798350314120

Facing the difficulties of large-scale networked satellite communication, such as unstable topology, diversified channel types, and uncertain satellite link failure, this paper proposes a general optimal routing path calculation method based on historical data prediction, and establishes a Statistical model based on historical data prediction for inter satellite communication transmission, which is not limited to transient failures caused by aging energy, storage, and load. At the same time, in the process of calculating the transmission rate and packet loss rate of the communication link, historical data is introduced to form a channel rate function that changes over time, which is used to achieve communication prediction within the transmission time and achieve self-sensing of the communication link's state. Based on the self-prediction state of the communication link, combined with the domain search algorithm, the maximum probability optimal solution of the long-term interactive routing process is considered to achieve real-time optimal solution for data transmission in the constellation of Jupiter in orbit. A simulation verification was conducted for a large number of randomly distributed routing applications in a short period of time, and parameters such as link stability, load capacity, and business time delay were compared with previous designs. The results show that the proposed method has good stability, which is more than 10% higher than previous designs;The link load is significantly lower compared to previous designs;Under the condition of a large number of routing applications, the service delay has been reduced by 27% compared to previous designs, ensuring routing communication under the time-varying topology of the constellation group. © 2023 IEEE.

关键词： Time delay

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Large-Range and High-Sensitivity Displacement Sensing Based on Extrinsic Fabry–Perot Interferometer Assisted Microwave Photonic Filter

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Li, Shiyu Jie, Ruimin Alsalman, Osamah Huang, Jie Zhu, Chen Wuxi University School of Integrated Circuit Science and Engineering Jiangsu Province Engineering Research Center of Photonic Devices and System Integration for Communication Sensing Convergence Wuxi214105 China Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO65401 United States King Saud University College of Engineering Department of Electrical Engineering Riyadh11421 Saudi Arabia Zhejiang Laboratory Hangzhou311100 China

Displacement is a pivotal physical parameter, and advancements in displacement sensor technology have enabled the creation of a diverse array of physical and mechanical sensors through seamless integration with mechanical transducers. In this study, we introduce a displacement sensing technique leveraging an extrinsic Fabry-Perot interferometer (EFPI) assisted microwave photonic (MWP) filter. By translating displacement-induced variations in the EFPI’s optical reflection into peak frequency shifts within its frequency response, we achieve large-dynamic-range displacement measurements with outstanding signal quality and demodulation ease. Proof-of-concept demonstrations showcase a substantial 5-mm range with a remarkable sensitivity of 1.148 GHz/mm, achieved using a basic single-mode fiber-based EFPI with a movable external mirror. Besides, nanometer-scale displacement monitoring is experimentally validated through a phase-measurement approach. Notably, the sensitivity and dynamic range can be tailored by adjusting the MWP filter system’s parameter, i.e., the dispersion parameter of the dispersive element in the system. Furthermore, we introduce a strategy to enhance the dynamic range further by employing a virtual frequency downconversion technique with an additional interferometer. This proposed technique opens avenues for developing a series of high-sensitivity and broad operating-range physical and mechanical sensors based on a simplified EFPI measurement configuration. © 1963-2012 IEEE.

关键词： Fabry-Perot interferometers

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