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A nonprofiled side-channel analysis based on variational lower bound related to mutual information

science China(information sciences) 2023年第1期66卷 277-295页

作者： Chi ZHANG Xiangjun LU Pei CAO Dawu GU Zheng GUO Sen XU School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Zhi Xun Crypto Testing and Evaluation Technology Co. Ltd. Viewsource Information Science and Technology Co. Ltd.

In this paper, we attempt to improve the practical performance of the nonprofiled side-channel analysis(Non SCA) with the help of neural networks. We first derive a variational lower bound related to mutual information(VLBRMI) optimized for the context of Non SCA, which possesses a set of adjustable parameters and whose maximum value linearly depends on the mutual information. Then, we propose a new Non SCA method called neural mutual information analysis(NMIA) that exploits the maximum VLBRMI as the distinguisher. We present an estimator of the maximum VLBRMI, which uses neural networks to instantiate the VLBRMI and trains the neural networks to approximate the maximum VLBRMI so that we can implement the NMIA efficiently. Finally, we evaluate the NMIA on several datasets. The experimental results show that NMIA outperforms the correlation power analysis, the mutual information analysis(MIA)based on histograms, the MIA based on kernel density estimation, and the state-of-the-art Non SCA method based on neural networks.

关键词： side-channel analysis nonprofiled method variational lower bound mutual information neural networks

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An Improved YOLOv8n Algorithm for Object Detection with CARAFE, MultiSEAMHead, and TripleAttention Mechanisms 7

An Improved YOLOv8n Algorithm for Object Detection with CARA...

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7th International Conference on Computer information science and Application technology, CISAT 2024

作者： Tang, Hao Jiang, Yuepeng Beijing Information Science and Technology University School of Instrument Science and Opto-electronic Engineering Beijing China

ISBN: (纸本)9798350375107

To improve the accuracy of the YOLOv8n algorithm for object detection, this paper proposes an enhanced YOLOv8n algorithm. This algorithm introduces the CARAFE module, TripleAttention mechanism, and MultiSEAMHead module into the YOLOv8n backbone network to enhance feature extraction capabilities. Extensive experiments were conducted on the NWPU dataset. Experimental results show that compared with the original YOLOv8n algorithm, the enhanced algorithm improves precision, recall, and mean average precision (mAP) by 2.4%, 3.0%, and 4.0%, respectively. These results validate the effectiveness and robustness of the proposed method. © 2024 IEEE.

关键词： Object recognition

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Pindel-TD:A Tandem Duplication Detector Based on A Pattern Growth Approach

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Genomics, Proteomics & Bioinformatics 2024年第1期22卷 99-104页

作者： Xiaofei Yang Gaoyang Zheng Peng Jia Songbo Wang Kai Ye School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Center for Mathematical Medical the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Faculty of Science Leiden UniversityLeiden 2311 EZNetherland

Tandem duplication(TD)is a major type of structural variations(SVs)that plays an important role in novel gene formation and human ***,TDs are often missed or incorrectly classified as insertions by most modern SV detection methods due to the lack of specialized operation on TD-related mutational ***,we developed a TD detection module for the Pindel tool,referred to as Pindel-TD,based on a TD-specific pattern growth ***-TD is capable of detecting TDs with a wide size range at single nucleotide *** simulated and real read data from HG002,we demonstrated that Pindel-TD outperforms other leading methods in terms of precision,recall,F1-score,and ***,by applying Pindel-TD to data generated from the K562 cancer cell line,we identified a TD located at the seventh exon of SAGE1,providing an explanation for its high ***-TD is available for non-commercial use at https://***/xjtu-omics/pindel.

关键词： Tandem duplication Pattern growth Short-read sequencing Structural variation SAGE1

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Enhanced intelligent water drops with genetic algorithm for multi-objective mixed time window vehicle routing

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Neural Computing and Applications 2024年 1-15页

作者： Guo, Zhibao Karimi, Hamid Reza Jiang, Baoping Wu, Zhengtian Cheng, Yukun School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou100190 China Mechanical Engineering Politecnico di Milano Milan10587 Italy School of Business Jiangnan University Wuxi214122 China

In the context of addressing the multi-objective vehicle routing problem, a hybrid time window multi-objective vehicle model was established using integer programming and the intelligent water drop algorithm. To overcome the limitation of the intelligent water drop algorithm potentially converging to local optimal solutions, enhancements were proposed through genetic algorithms, particularly by introducing genetic crossover and single-point recombination operators. Subsequently, the intelligent water drop algorithm was refined, and its effectiveness was evaluated through a real-world case study. Comparative analyses were conducted among three algorithms: IWD, GA, and SA. The results demonstrate that the improved algorithm effectively alleviates the common issue of traditional algorithms converging to local optimal solutions. Therefore, an enhanced solution is provided for the discrete hybrid time window problem, achieving superior optimization outcomes. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Genetic algorithms

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A Multi-Agent Based Model for User Interest Mining on Sina Weibo

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China Communications 2022年第2期19卷 225-234页

作者： Meijia Wang Qingshan Li School of Electronic Information and Artifical Intelligence Shaanxi University of Science and TechnologyXi’an 710021China Software Engineering Institude Xidian UniversityXi’an 710071China

User interest mining on Sina Weibo is the basis of personalized recommendations,advertising,marketing promotions,and other *** great progress has been made in this area,previous studies have ignored the differences among users:the varied behaviors and habits that lead to unique user data *** is unreasonable to use a single strategy to mine interests from such varied user ***,this paper proposes an adaptive model for user interest mining based on a multi-agent system whose input includes self-descriptive user data,microblogs and *** method has the ability to select the appropriate strategy based on each user’s data *** experimental results show that the proposed method performs better than the baselines.

关键词： multi-agent system user interest mining adaptive model Sina Weibo online social network

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Stabilization for Discrete-Time Stochastic Systems with Multiple Input Delays

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Journal of Systems science & Complexity 2023年第5期36卷 1961-1980页

作者： LI Lin ZHANG Huanshui College of Mechanical and Electronic Engineering Shandong Agricultural UniversityTaian 271018China School of Information Science and Engineering Shandong Agricultural UniversityTaian 271018China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China

A stabilization problem for stochastic systems with multiple input delays is investigated herein.A new method to construct an optimal control problem with input constraints is adopted.A sufficient stabilization condition is established via Riccati-type equations,whose verification is computationally simple because the variable dimension of the equations does not increase with regard to the delay.A stabilization controller is proposed,and it is a feedback of the state and a history *** controller uses less history information than those with distributed *** numerical examples illustrate the effectiveness of the obtained results.

关键词： Riccati-type equations stabilization stochastic systems time-delay systems

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Terahertz metasurface temperature sensors based on strontium titanate films prepared by RF magnetron sputtering and air annealing

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Photonics Research 2025年第5期13卷 1242-1248页

作者： YONG GANG ZHANG ZHAOYANG SHI LANJU LIANG ZIQUN WANG XIN YAN HAIYUN YAO ZHENHUA LI XIAOFEI HU YUANPING LI JINTAO WU SHIWU MA QINGYI WANG YONGZHEN CHEN HUIHAN TIAN XINGYU ZHANG FEI HUAI School of Electrical and Information Engineering Anhui University of Science and Technology School of Opto-electronic Engineering Zaozhuang University School of Physical Science and Information Engineering Liaocheng University

A terahertz temperature sensor is developed by combining an Al metasurface with polycrystalline strontium titanate (STO) prepared by RF magnetron sputtering and air annealing. Leveraging the excellent dielectric properties of STO, we design terahertz temperature sensors based on amorphous and polycrystalline STO. In the temperature range of 300–620 K, as the temperature increases, the transmission curve of the amorphous STO temperature sensor only exhibits a frequency shift phenomenon. Owing to the different lattice structures, the dielectric response of polycrystalline STO causes frequency shifts and significant amplitude changes in the transmission curve, indicating that it has dual-dimensional temperature sensing capabilities. Through quantitative analysis,a dual-dimensional polycrystalline STO terahertz temperature sensor with the maximum sensitivity of 0.21 GHz/K and maximum transmittance of 13%is obtained. This study not only provides a new strategy for the application of polycrystalline STO in the development of terahertz temperature sensors but also demonstrates that such sensors are characterized by excellent performance, low cost, and ease of processing.

关键词： Optical properties Ring resonators Temperature sensors Terahertz time-domain spectroscopy Thin films X-ray diffraction

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CS2DIPs: Unsupervised HSI Super-Resolution Using Coupled Spatial and Spectral DIPs

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IEEE Transactions on Image Processing 2024年 33卷 3090-3101页

作者： Fang, Yuan Liu, Yipeng Chi, Chong-Yung Long, Zhen Zhu, Ce University of Electronic Science and Technology of China School of Communication and Information Engineering Chengdu611731 China National Tsing Hua University Institute of Communications Engineering Department of Electrical Engineering Hsinchu30013 Taiwan

In recent years, fusing high spatial resolution multispectral images (HR-MSIs) and low spatial resolution hyperspectral images (LR-HSIs) has become a widely used approach for hyperspectral image super-resolution (HSI-SR). Various unsupervised HSI-SR methods based on deep image prior (DIP) have gained wide popularity thanks to no pre-training requirement. However, DIP-based methods often demonstrate mediocre performance in extracting latent information from the data. To resolve this performance deficiency, we propose a coupled spatial and spectral deep image priors (CS2DIPs) method for the fusion of an HR-MSI and an LR-HSI into an HR-HSI. Specifically, we integrate the nonnegative matrix-vector tensor factorization (NMVTF) into the DIP framework to jointly learn the abundance tensor and spectral feature matrix. The two coupled DIPs are designed to capture essential spatial and spectral features in parallel from the observed HR-MSI and LR-HSI, respectively, which are then used to guide the generation of the abundance tensor and spectral signature matrix for the fusion of the HSI-SR by mode-3 tensor product, meanwhile taking some inherent physical constraints into account. Free from any training data, the proposed CS2DIPs can effectively capture rich spatial and spectral information. As a result, it exhibits much superior performance and convergence speed over most existing DIP-based methods. Extensive experiments are provided to demonstrate its state-of-the-art overall performance including comparison with benchmark peer methods. © 1992-2012 IEEE.

关键词： Tensors

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A lightweight attention-guided semantic segmentation network using a group convolution pyramid 2

A lightweight attention-guided semantic segmentation network...

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2nd International Conference on Computing, Communication, Perception and Quantum technology, CCPQT 2023

作者： Yu, Siyu Huang, Dandan Wang, Guixian Yao, Anni Changchun University of Science and Technology School of Electronic Information Engineering Changchun China Name of Changchun University of Science and Technology School of Electronic Information Engineering Changchun China

ISBN: (纸本)9798350342697

Semantic segmentation is a key part of computer vision tasks, but its application is greatly limited by memory capacity and computational cost. This paper proposes a lightweight attention-guided semantic segmentation network (LAGNet) that adopts a joint group convolution pyramid strategy. Specifically, we introduced a lightweight symmetric double attention module (LS-DAM) and an adaptive selection interaction module (ASIM). In the LS-DAM, the self-attention adopts adaptive maximum pooling and average pooling instead of its previous form, in which the pixel-by-pixel similarity is calculated. Moreover, The ASIM has the capability to seamlessly integrate both high-level semantic information and low-level geometric information, leading to a remarkable enhancement in the performance of semantic segmentation. We evaluate our proposed LAGNet model using mean intersection over union (mIoU) on PASCAL VOC 2012 and Cityscapes, two commonly used datasets in the field of semantic segmentation, and finally achieve state-of-the-art performance of 81.73% and 81.90%, respectively. © 2023 IEEE.

关键词： Semantic Segmentation

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Readout electronics for the gamma detector of the HIRFL-CSR external target facility

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Nuclear science and Techniques 2025年第2期36卷 71-81页

作者： Xian-Qin Li Hai-Bo Yang Xiao-Meng Ma Chao-Jie Zou Tao Liu Xian-Cai Zhou Duo Yan Yang-Zhou Su Shu-Wen Tang Shi-Tao Wang Yu-Hong Yu Zhi-Yu Sun Cheng-Xin Zhao Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China School of Physics and Electronic Engineering Northwest Normal UniversityLanzhou 730070China School of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China

The Cooling Storage Ring of the Heavy Ion Research Facility in Lanzhou(HIRFL-CSR)was constructed to study nuclear physics,atomic physics,interdisciplinary science,and related *** External Target Facility(ETF)is located in the main ring of the *** gamma detector of the ETF is built to measure emitted gamma rays with energies below 5 MeV in the center-of-mass frame and is planned to measure light fragments with energies up to 300 *** readout electronics for the gamma detector were designed and *** readout electronics consist of thirty-two front-end cards,thirty-two readout control units(RCUs),one common readout unit,one synchronization&clock unit,and one sub-trigger *** using the real-time peak-detection algorithm implemented in the RCU,the data volume can be significantly *** addition,trigger logic selection algorithms are implemented to improve the selection of useful events and reduce the data *** test results show that the integral nonlinearity of the readout electronics is less than 1%,and the energy resolution for measuring the 60 Co source is better than 5.5%.This study discusses the design and performance of the readout electronics.

关键词： HIRFL-CSR Gamma detector External target facility Readout electronics Readout control unit Common readout unit Peak-detection algorithm

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