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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Wu, Yijia Zhang, Congpin Xu, Zhengwei Li, Ligang Chinese Academy of Sciences National Space Science Center Key Laboratory of Electronics and Information Technology for Space System Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences China School of Computer and Information Engineering Henan Normal University Henan Xinxiang China

ISBN: (纸本)9798350330014

Physically based ray tracing is a technique that involves creating a photo-realistic image from a 3D scene description by utilizing the laws of physics to simulate the behavior of light and matter. However, due to the random length of light samples and irregular memory access patterns, it can suffer from low scalability and severe load imbalance. As a result, the development of a framework for multi-node parallelism algorithm in physically based ray tracing is a significant challenge. To tackle these issues, this paper introduces a novel algorithm named distributed parallel physically based bidirectional path tacing algorithm (DP-BDPT). Through analyzing the physical essence of bidirectional path tracing algorithm and the light transport equation, we have devised a framework that carefully divides tasks between inter-compute nodes and intra-compute nodes. To support high scalability, we have developed a physically based architecture. Additionally, we have proposed a hybrid scheduling method to achieve load balancing. To further enhance performance, we have analyzed several key factors that affect rendering performance and implemented adaptive optimization techniques. The experiments conducted on the Tianhe-2 Supercomputer involving typical and challenging 3D scenes, namely the Cornell-box, Veach-bidir, and Teapot-full experiments, have illustrated that DP-BDPT demonstrate near-linear speedups as the number of CPU cores scales from 1200 to 9600, thereby demonstrating their efficiency when operating on a ten-thousand-core system. © 2023 IEEE.

关键词： Ray tracing

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Transferable Features from 1D-Convolutional Network for Industrial Malware Classification

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computer Modeling in engineering & Sciences 2022年第2期130卷 1003-1016页

作者： LiweiWang Jiankun Sun Xiong Luo Xi Yang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Shunde Graduate School University of Science and Technology BeijingFoshan528399China Beijing Intelligent Logistics System Collaborative Innovation Center Beijing101149China

With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and *** identify and classify new malware variants,different types of deep learning models have been widely explored ***,sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ***,in current practical applications,an ample supply of data is absent in most specific industrial malware detection *** learning as an effective approach can be used to alleviate the influence of the small sample size *** addition,it can also reuse the knowledge from pretrained models,which is beneficial to the real-time requirement in industrial malware *** this paper,we investigate the transferable features learned by a 1D-convolutional network and evaluate our proposed methods on 6 transfer learning *** experiment results show that 1D-convolutional architecture is effective to learn transferable features for malware classification,and indicate that transferring the first 2 layers of our proposed 1D-convolutional network is the most efficient way to reuse the learned features.

关键词： Transfer learning malware classification sequence data modeling convolutional network

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Distributed Real-time State Estimation for Combined Heat and Power systems

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Journal of Modern Power systems and Clean Energy 2021年第2期9卷 316-327页

作者： Tingting Zhang Wen Zhang Qi Zhao Yaxin Du Jian Chen Junbo Zhao the Key Laboratory of Power System Intelligent Dispatch and Control Ministry of EducationShandong UniversityJinan 250061China the Department of Electrical and Computer Engineering Mississippi State UniversityStarkvilleMS 39762USA

This paper proposes a distributed real-time state estimation(RTSE)method for the combined heat and power systems(CHPSs).First,a difference-based model for the heat system is established considering the dynamics of heat *** heat system model is further used along with the power system steady-state model for holistic CHPS state estimation.A cubature Kalman filter(CKF)-based RTSE is developed to deal with the system nonlinearity while integrating both the historical and present measurement ***,a multi-timescale asynchronous distributed computation scheme is designed to enhance the scalability of the proposed method for largescale *** distributed implementation requires only a small amount of information exchange and thus protects the privacy of different energy *** carried out on two CHPSs show that the proposed method can significantly improve the estimation efficiency of CHPS without loss of accuracy compared with other existing models and methods.

关键词： Combined heat and power system(CHPS) cubature Kalman filter(CKF) heat dynamics multi-time-scale asynchronous distributed scheme real-time state estimation(RTSE)

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Deep Multi-Instance Learning with Adaptive Recurrent Pooling for Medical Image Classification

Deep Multi-Instance Learning with Adaptive Recurrent Pooling...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Ding, Yi Zhao, Lu Yuan, Liming Wen, Xianbin School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China School of Computer and Information Engineering Tianjin Chengjian University Tianjin300384 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin300384 China

ISBN: (纸本)9781665468190

Recently, deep multi-instance neural networks have been successfully applied for medical image classification, where only image-level labels rather than fine-grained patch-level labels are available for use. One key issue for these multi-instance neural networks is how to aggregate all patch (instance) features into an entire image (bag) representation, referred to as multi-instance pooling, e.g., max, mean, and attention based pooling. Nevertheless, these multi-instance pooling operations do not take the structural information within an image into account. This is obviously inappropriate for medical image classification since there often exist certain dependencies among regional patches/lesions. We propose an adaptive recurrent pooling based deep multi-instance neural network in this paper. In this network, we first extract multi-view global structural features from every bag using the self-attention mechanism, and then aggregate these multi-view features into a whole bag representation based on the adaptive recurrent pooling operation in order to further capture the contextual information within the bag. Moreover, we introduce the cross-normalization operation used in the Unit Force Operated Vision Transformer into the self-attention module to reduce its computational complexity. We have experimentally evaluated the performance of the proposed network on three medical image datasets, namely UCSB breast, Messidor, and Colon cancer. The results demonstrate the advantage of our network over current state-of-the-art deep multi-instance networks in terms of classification accuracy and interpretability. © 2022 IEEE.

关键词： Aggregates

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Split Lohmann computer holography: fast generation of 3D hologram in single-step diffraction calculation

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Advanced Photonics Nexus 2024年第3期3卷 1-13页

作者： Chenliang Chang Xian Ding Di Wang Zhizhou Ren Bo Dai Qi Wang Songlin Zhuang Dawei Zhang University of Shanghai for Science and Technology School of Optical-Electrical and Computer EngineeringEngineering Research Center of Optical Instrument and SystemMinistry of Education and Shanghai Key Laboratory of Modern Optics SystemShanghaiChina Beihang University School of Instrumentation and Optoelectronic EngineeringBeijingChina

Holographic display stands as a prominent approach for achieving lifelike three-dimensional(3D)reproductions with continuous depth ***,the generation of a computer-generated hologram(CGH)always relies on the repetitive computation of diffraction propagation from point-cloud or multiple depthsliced planar images,which inevitably leads to an increase in computational complexity,making real-time CGH generation ***,we report a new CGH generation algorithm capable of rapidly synthesizing a 3D hologram in only one-step backward propagation calculation in a novel split Lohmann lens-based diffraction *** introducing an extra predesigned virtual digital phase modulation of multifocal split Lohmann lens in such a diffraction model,the generated CGH appears to reconstruct 3D scenes with accurate accommodation abilities across the display *** with the conventional layer-based method,the computation speed of the proposed method is independent of the quantized layer numbers,and therefore can achieve real-time computation speed with a very dense of depth *** simulation and experimental results validate the proposed method.

关键词： computer holography holographic display diffraction calculation.

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MBTDiff: Multi-segmentation Brain Tumor Model with Diffusion Probabilistic Model 9

MBTDiff: Multi-segmentation Brain Tumor Model with Diffusion...

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9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Zeng, Shuqi Liu, Jun Xu, Ji Luo, Yuan School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Key Laboratory of Biomarkers and In Vitro Diagnosis Translation Zhejiang province Hangzhou China Hubei Engineering Research Center for Intelligent Digital Technology in New Power System Hubei Central China Technology Development of Electric Power Co. Ltd Wuhan China

ISBN: (纸本)9798350385991

The diffusion probability model has recently garnered remarkable achievements in image generation, emerging as a prominent research focus within computer vision. It has been observed through numerous studies that the diffusion probability model holds potential for application across various domains within computer vision. Drawing inspiration from these models, we present a novel approach to extend their utility to the realm of brain tumor medical image segmentation. Our method entails training the model utilizing a diffusion framework, followed by iterative refinement of segmentation outcomes by incorporating additional encoding layers and decoders. This method employs an end-to-end training approach without relying on pre-trained backbone networks. Given the probabilistic nature of the results generated by the diffusion model and to simulate the actual decision-making process of doctors, we will generate multiple segmentation results and apply denoising techniques to obtain a stable output. These results will then be integrated into the final segmentation map to achieve more precise segmentation. © 2024 IEEE.

关键词： Image segmentation

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DasAtom: A Divide-and-Shuttle Atom Approach to Quantum Circuit Transformation

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Huang, Yunqi Gao, Dingchao Ying, Shenggang Li, Sanjiang Faculty of Engineering and Information Technology SydneyNSW2007 Australia Institute of Software Chinese Academy of Sciences Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science China

Neutral atom (NA) quantum systems are emerging as a leading platform for quantum computation, offering superior or competitive qubit count and gate fidelity compared to superconducting circuits and ion traps. However, the unique features of NA devices, such as long-range interactions, long qubit coherence time, and the ability to physically move qubits, present distinct challenges for quantum circuit compilation. In this paper, we introduce DasAtom, a novel divide-and-shuttle atom approach designed to optimise quantum circuit transformation for NA devices by leveraging these capabilities. DasAtom partitions circuits into subcircuits, each associated with a qubit mapping that allows all gates within the subcircuit to be directly executed. The algorithm then shuttles atoms to transition seamlessly from one mapping to the next, enhancing both execution efficiency and overall fidelity. For a 30-qubit Quantum Fourier Transform (QFT), DasAtom achieves a 415.8x improvement in fidelity over the move-based algorithm Enola and a 10.6x improvement over the SWAP-based algorithm Tetris. Notably, this improvement is expected to increase exponentially with the number of qubits, positioning DasAtom as a highly promising solution for scaling quantum computation on NA platforms. © 1982-2012 IEEE.

关键词： Qubits

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Multi-fidelity Gaussian Process for Distribution system Voltage Probabilistic Estimation with PVs 6

Multi-fidelity Gaussian Process for Distribution System Volt...

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6th IEEE Conference on Energy Internet and Energy system Integration, EI2 2022

作者： Zhang, Jinxian Zhao, Junbo Ye, Ketian Ding, Fei University of Connecticut Department of Electrical and Computer Engineering StorrsCT06268 United States National Renewable Energy Laboratory Power System Engineering Center GoldenCO80401 United States

ISBN: (纸本)9798350347159

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches. © 2022 IEEE.

关键词： Visibility

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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