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41st computer Graphics International Conference, CGI 2024

作者： Duan, Wantong Bao, Yongtang Qi, Yue State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Shandong University of Science and Technology Qingdao266590 China Jingdezhen Research Institute of Beihang University Jingdezhen333000 China Qingdao Research Institute of Beihang University Qingdao266000 China

ISBN: (纸本)9783031820236

Compare to traditional Scene Completion (SC), Semantic Scene Completion (SSC) is a challenging task that aims to generate complete and semantically consistent 3D scene from partial and sparse input data, which is fundamental to fully understanding the scene and being able to interact with it. Consequently, the SSC task has received much attention in recent years. Most of the methods are voxel-based approaches, but they have high computational and memory requirements. A few works based on point cloud do not sufficiently exploit the correlation between semantic segmentation and geometric completion subtasks, while focusing too much on point cloud shape features and ignoring the rich texture information that RGB images can provide. In this paper, we present SSCCPC-Net (Semantic Scene Completion with CLIP on Point Cloud-Net), a novel network architecture for point cloud semantic scene completion using a combination of 2D and 3D features. Inspired by recent works of large pretrained vision-language models in semantic segmentation, we explore to accomplish SSC task with the help of Contrastive Language-Image Pre-Training (CLIP) model. Specifically, we use the CLIP features for guidance to fuse the 2D features extracted from the RGB image and the 3D features extracted from the point cloud. The fused features are then fed into our designed Semantic-Completion Decoder for per-point semantic prediction and semantic labeling-assisted point cloud completion. Finally, we obtain the complete semantically point cloud. Numerous experiments have demonstrated that our method has higher effectiveness and generalizability compared to state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantic Segmentation

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Reconstruction of Thermal Protection System Aeroheating Using a Green’s Function Approach

Reconstruction of Thermal Protection System Aeroheating Usin...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： McAfee, Kenneth Rabin, Oded Alpert, Hannah S. Department of Aerospace Engineering University of Maryland College ParkMD20742 United States Department of Aerospace Engineering Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Entry Systems and Vehicle Development Branch NASA Ames Research Center Moffett FieldCA94035 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Inverse heat transfer (IHT) techniques are often used to reconstruct the surface heating conditions on spacecraft thermal protection systems (TPS) during atmospheric entry. Current IHT techniques for entry spacecraft applications, however, demand substantial computational resources, and are impractical for analyses such as uncertainty quantification and real-time health monitoring. In this paper, a Green’s function sensor fusion approach is used to reconstruct the TPS surface aeroheating conditions on experimental spaceflight and ground test systems from collocated temperature and heat flux sensors embedded in the TPS. The algorithm leverages Green’s functions to model the heat conduction within the spacecraft TPS and stabilizes the recovery of the surface heat flux boundary condition using the direct heat flux sensor measurement. The algorithm is validated using arc-jet ground test data and applied to the reconstruction of the Mars 2020 backshell heating during Martian atmospheric entry. The performance of the algorithm is benchmarked against a current state-of-the-art IHT framework, FIAT_Opt. The Green’s function-based reconstruction algorithm recovers the net hot-wall heat flux absorbed by the TPS and the incident heat flux from the atmospheric entry environment in close agreement with FIAT_Opt. Notably, computation of the surface heating conditions is completed in three orders of magnitude less time with the Green’s function sensor fusion approach using a consumer-grade PC, versus with FIAT_Opt running on a high-performance computer cluster. The efficiency of the algorithm is leveraged to compute the uncertainty contributions of input parameters to the total uncertainty of reconstructed Mars 2020 backshell heating conditions for the full atmospheric entry heat pulse. The sensitivity analysis uncovers that, at different times throughout the entry heat pulse, uncertainties in the TPS specific heat, thermal conductivity, and emissivity are all dominant drivers of t

关键词： Sensitivity analysis

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A Data-and-Model-Driven Acceleration Approach for Large-Scale Network-Constrained Unit Commitment Problem With Uncertainty

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IEEE Transactions on Sustainable Energy 2025年

作者： Zhou, Yuzhou Han, Zhihan Zhai, Qiaozhu Wu, Lei Cao, Xiaoyu Guan, Xiaohong Xi'an Jiaotong University Systems Engineering Institute MOEKLINNS Lab Xi'an710049 China Sichuan Digital Economy Industry Development Research Institute Sichuan Chengdu610037 China Xi'an Jiaotong University Systems Engineering Institute Xi'an710049 China Stevens Institute of Technology Department of Electrical and Computer Engineering Hoboken07030 United States Tsinghua University Department of Automation Center for Intelligent and Networked Systems Beijing100084 China

Numerous binary variables and constraints greatly affect the computation of large-scale network-constrained unit commitment (NCUC) problems. With the integration of massive renewable energy and distributed loads, binary variables and network power flows face more frequent changes to cope with uncertainties. How to ensure the calculation efficiency and accuracy of NCUC problems against uncertainties and frequent changes becomes a common challenge for academia and industry. Inspired by data-driven and model-driven technologies, this paper presents a hybrid reduction approach for variables and constraints to accelerate the solving of large-scale NCUC problems, which achieves "one plus one much greater than two" effect. Specifically, an offline database of nodal net load clusters and the corresponding NCUC solutions is established, which also captures the impacts of changes in renewables, loads, topology, etc. on UC solutions. With this database, a data-and-modeldriven reduction method is proposed to fix binary variables and reduce constraints, while considering the changes of prices and net loads in online NCUC instances. Moreover, the reduction method was further developed to accelerate various NCUC problems, including scenario-based methods, robust optimization methods, etc. Thus, the computation burden of online large-scale NCUC problems is greatly mitigated while ensuring good solution quality. Numerical tests implemented on IEEE 24-bus system, 118-bus system, and Polish 2383-bus system illustrate the efficiency of the proposed approach. © 2025 IEEE. All rights reserved.

关键词： Mendelevium

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Experimental implementation of chaos-based video encryption using visible light communication technology

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Applied Optics 2025年第9期64卷 C101-C118页

作者： Fotso, Sorel Bagio Nono Mbé, Jimmi Hervé Talla Takotue, Jean Ernest Takougang, Armand Cyrille Nzeukou Ndjiongue, Alain Richard Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang P.O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer Department of Electrical Engineering IUT-FV Bandjoun University of Dschang P.O. Box: 134 Bandjoun Cameroon Laboratory of Industrial Systems and Environmental Engineering Fotso Victor University Institute of Technology University of Dschang P.O. Box 134 Bandjoun Cameroon School of Electrical and Information Engineering Faculty of Engineering and the Built Environment University of the Witwatersrand Johannesburg South Africa

Simulations are commonly used to develop and evaluate video encryption algorithms. Although these approaches are useful for demonstrating theoretical feasibility and algorithm performance, they neglect practical challenges and real-world communication conditions. This oversight creates a critical gap in evaluating their effectiveness and security in practical applications. In this paper, we describe a novel, to the best of our knowledge, video encryption scheme that employs a modified chaotic Colpitts oscillator, a customized Josephus problem, and ribonucleic acid (RNA) operations, and is implemented in visible light communication (VLC) environment. The modified Colpitts oscillator reveals significant phenomena, the most prominent for this study being chaos. The encryption scheme involves block scrambling and pixel-level permutation employing a customized Josephus problem and a column and row shifting technique. Diffusion is then achieved through a custom Josephus problem-oriented RNA operation combined with basic RNA operations and cipher block chaining (CBC). Based on the results, we found that the customized Josephus problem-based permutation performed more efficiently than traditional methods, whereas the column and row shifting permutation was more robust. By eliminating key sequence coding and item-to-item operations, the proposed RNA operation reduces computational overhead. This video encryption scheme is proven to be effective and resilient at securing video data transmitted over the VLC channel, and it constitutes a significant advancement in areas such as surveillance, medical imaging, and military communication requiring robust secured video data. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Medical imaging

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Decoupling While Coupling: Towards More Accurate Stereo Image Sand Removal Beyond Certainty

Decoupling While Coupling: Towards More Accurate Stereo Imag...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wei, Bingcai Liu, Hui Qian, Chuang Jia, Yi Wu, Wangyu Li, Zhishan School of Computer Science Wuhan University Wuhan China GNSS Research Center Wuhan Unicersity Wuhan China Intelligent Transport Systems Research Center Wuhan University of Technology Wuhan China College of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China University of Liverpool Liverpool United Kingdom School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350368741

Stereo image sand removal is crucial to improve the perceptual quality for autonomous driving perception. Existing methods often fall short in accurately estimating the uncertainty inherent in degraded images, leading to suboptimal outcomes. To address this, we introduce a novel framework named Decoupling While Coupling(DWC). DWC pioneers the integration of inter-view uncertainty estimation, cross-view uncertainty-aware interaction and block-wise uncertainty representation for superior stereo image sand removal. For cross-view information interaction, we propose an Uncertainty-aware Cross-view Attentive Interaction module(UCAI) to cope with the lack of uncertainty estimation ability in the existing cross-view information interaction mechanism. For the uncertainty perception and information interaction within the inter-view, we propose a Distribution Modeling Coupling Block(DMCB), which transmits the representation of uncertainty between each backbone module. For block-wise uncertainty estimation, we use our proposed Uncertainty-aware Distribution Feature Modulator(UDFM) as the backbone of DWC to modulate the uncertainty inside the neural network itself. Extensive experimental validations on our proposed stereo image sand removal dataset SandST confirm the efficacy of DWC. Our method not only achieves higher PSNR and SSIM, but also exhibits enhanced robustness against various sand degrees and patterns. © 2025 IEEE.

关键词： Cross-view Inter-view Sand removal Stereo image Uncertainty estimation

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Exploring blockchain solutions: Integrating cryptocurrency with IoT for enhanced security

Exploring blockchain solutions: Integrating cryptocurrency w...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Shravan, M. Kakad, Shital Mulani, Umar M Sharma, Geeti Tiwari, Mohit Mary Shiba, C. Sr University School of Business Telangana Warangal India Vishwakarma Institute of Technology Artificial Intelligence and Data Science Maharashtra Pune India Kj College of Engineering and Management Research Pune India India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi Delhi India R.M.K Engineering College Department of Computer Science and Business Systems Thiruvallur India

ISBN: (纸本)9798331508685

Blockchain, initially developed as the underlying technology for Bitcoin, has garnered significant attention for its applications beyond cryptocurrency, particularly in complex non-monetary domains. Utilizing cryptographic methods like hashing and asymmetric encryption, combined with a distributed consensus model, Blockchain-based ledgers achieve high levels of security and immutability, effectively removing the need for third-party intermediaries. Meanwhile, the rapid growth in Internet of Things (IoT) devices being connected to networks raises substantial concerns around security and privacy. Addressing these security challenges is essential for the expanding IoT landscape. This paper explores the blockchain solution by integrating cryptocurrency with IoT for enhanced security, reviewing recent studies and applications to evaluate Blockchain's role in IoT security, pinpoint challenges, and propose Blockchain-driven solutions to improve security in the IoT ecosystem. © 2025 IEEE.

关键词： Blockchain Cryptocurrency Internet of Things privacy Security

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Flexiswap: A Cross-Chain Decentralized Exchange Protocol

Flexiswap: A Cross-Chain Decentralized Exchange Protocol

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International Communication systems and Networks and Workshops, COMSNETS

作者： Kirti Singh Vinay J. Ribeiro Susmita Mandal Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India Institute for Development and Research in Banking Technology Hyderabad India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Decentralized exchanges (DEXs) have emerged as a promising solution to enhance trustlessness in blockchain ecosystems and mitigate security threats associated with centralized exchanges. While platforms like Uniswap offer certain advantages, their limitation to exchanging tokens within a single blockchain restricts their utility. Moreover, exchanges relying on atomic swaps, such as AtomicDEX, are susceptible to grief attacks and exhibit low success ratios. In response to these challenges, we introduce FlexiSwap, an auction-based decentralized exchange protocol that leverages atomic swaps for exchanging native tokens between smart contract-compatible blockchains. FlexiSwap stands out by combining multiple bids to facilitate one-to-many exchanges, resulting in improved exchange values, successful execution of large-volume exchanges, and an improved success ratio. The protocol incorporates a penalization mechanism to deter grief attacks, ensuring that participants cannot withdraw from an exchange without incurring a loss once the counterparty has committed its assets. We also prove the protocol’s safety, liveness, and grief prevention. Our simulation results demonstrate that combining multiple bids helps achieve better exchange values and order-matching success rates. Additionally, we implemented our protocol on Ethereum-based blockchains. The experimental results show that combining bids increases overall gas usage, but the increase in the average gas user per bid is marginal.

关键词： Protocols Prevention and mitigation Simulation Ecosystems Trustless services Blockchains Safety Security

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Chained HotStuff Under Performance Attack

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Niu, Jianyu Wang, Minjie Gai, Fangyu Jalalzai, Mohammad M. Feng, Chen Zhang, Yinqian Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems School of Computer Science and Engineering China University of British Columbia School of Engineering Canada

Chained HotStuff is a state-of-the-art Byzantine fault-tolerant protocol for building decentralized systems like blockchains. Although chained HotStuff has been wildly adopted in many systems, its performance (e.g., throughput and latency) under attacks is still under-explored. In this paper, we develop a multi-metric evaluation framework to quantitatively analyze the performance of chained HotStuff with respect to its chain growth rate, chain quality, and latency. We propose several new attack strategies and evaluate their effects on the performance of chained HotStuff. Our analysis shows that the chain growth rate (resp, chain quality) of chained HotStuff under our attacks can drop to 4/9 (resp, 12/17 ) of that without attacks when one-third of nodes are Byzantine. In addition, we use our framework to evaluate a variant of chained HotStuff, DiemBFT and find that some engineering optimizations render it more vulnerable to some attacks than the original chained HotStuff. Finally, we provide two countermeasures, i.e., broadcasting QCs and the longest chain rule, to thwart these attacks. Our analysis shows that the proposed countermeasures can significantly reduce the latency (almost half of that in chained HotStuff) and make it impossible for an attacker to lower the chain quality by simple attacks. © 2004-2012 IEEE.

关键词： Fault tolerance

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Leveraging Edge Optimize Vision Transformer for Monkeypox Lesion Diagnosis on Mobile Devices

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computers, Materials & Continua 2025年第5期83卷 3227-3245页

作者： Poonam Sharma Bhisham Sharma Dhirendra Prasad Yadav Surbhi Bhatia Khan Ahlam Almusharraf Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia Centre for Research Impact and Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer Engineering&Applications G.L.A.UniversityMathura281406India Department of Data Science University of SalfordManchesterM54WTUK University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia Division of Research and Development Lovely Professional UniversityPhagwara144411India Department of Management College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Rapid and precise diagnostic tools for Monkeypox(Mpox)lesions are crucial for effective treatment because their symptoms are similar to those of other pox-related illnesses,like smallpox and *** morphological similarities between smallpox,chickenpox,and monkeypox,particularly in how they appear as rashes and skin lesions,which can sometimes make diagnosis *** lesions appear in many simultaneous phases and are more diffuse,often beginning on the *** contrast,monkeypox lesions emerge progressively and are typically centralized on the face,palms,and *** provide accessible diagnostics,this study introduces a novel method for automated monkeypox lesion classification using the HMTNet(Hybrid Mobile Transformer Network).The convolutional layers and Vision Transformers(ViT)are combined to enhance the spatial *** addition,we replace the classical MHSA(Multi-head self-attention)with the WMHSA(Window-based Multi-Head Self-Attention)to effectively capture long-range dependencies within image patches and depth-wise separable convolutions for local feature *** trained and validated HMTNet on the two datasets for binary and multiclass *** model achieved 98.38% accuracy for multiclass classification using cross-validation and 99.25% accuracy for binary *** findings show that the model has the potential to be a useful diagnostic tool for monkeypox,especially in environments with limited resources.

关键词： Monkeypox disease classification local global transformer

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research on Task Migration Problem Based on Link Uncertainty in Adversarial Scenarios 25th

Research on Task Migration Problem Based on Link Uncertainty...

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25th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2024

作者： Xing, Xiangxiang Li, Pan Zuo, Tianyu Jiang, Yuanshuang Di, Kai Wang, Xin Jiao, Xun Jiang, Yichuan Chen, Dan School of Cyber Science and Engineering Southeast University Jiangsu Nanjing211189 China School of Computer Science and Engineering Southeast University Jiangsu Nanjing211189 China No. 8511 Research Institute of CASIC Jiangsu Nanjing210007 China Institute of Systems Engineering Academy of Military Science Beijing China College of Electronics and Information Engineering Beibu Gulf University Guangxi Qinzhou535000 China

ISBN: (纸本)9789819642069

With developments in artificial intelligence, computer science, and network technologies, modern confrontational scenarios are increasingly related to multi-agent systems characterized by multi-network. To reduce the effects of external factors on task execution, a task migration algorithm based on link uncertainty in adversarial scenarios is designed. Firstly, this thesis models the underlying problem as an integer programming problem, defining the optimization objectives and constraints accordingly. Subsequently, inter- and intra-network layer task migration is carried out based on gene expression programming to ensure the optimization objective and improve the load balance. Finally, experimental results demonstrate the algorithm’s efficacy in improving migration benefits and mitigating the impact of uncertainty. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gene expression programming Optimization Objectives Task migration Uncertainty

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