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PCRTAM-Net:A Novel Pre-Activated Convolution Residual and Triple Attention Mechanism Network for Retinal Vessel Segmentation

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Journal of computer science & technology 2023年第3期38卷 567-581页

作者：汪华登李紫正保罗黎兵兵潘细朋刘振丙蓝如师罗笑南 Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin 541004China school of computer science and information security Guilin University of Electronic TechnologyGuilin 541004China school of Artificial Intelligence Guilin University of Electronic TechnologyGuilin 541004China Department of Pathology Ganzhou Municipal HospitalGanzhou 341000China

Retinal images play an essential role in the early diagnosis of ophthalmic *** segmentation of retinal vessels in color fundus images is challenging due to the morphological differences between the retinal vessels and the low-contrast *** the same time,automated models struggle to capture representative and discriminative retinal vascular *** fully utilize the structural information of the retinal blood vessels,we propose a novel deep learning network called Pre-Activated Convolution Residual and Triple Attention Mechanism Network(PCRTAM-Net).PCRTAM-Net uses the pre-activated dropout convolution residual method to improve the feature learning ability of the *** addition,the residual atrous convolution spatial pyramid is integrated into both ends of the network encoder to extract multiscale information and improve blood vessel information flow.A triple attention mechanism is proposed to extract the structural information between vessel contexts and to learn long-range feature *** evaluate the proposed PCRTAM-Net on four publicly available datasets,DRIVE,CHASE_DB1,STARE,and *** model achieves state-of-the-art performance of 97.10%,97.70%,97.68%,and 97.14%for ACC and 83.05%,82.26%,84.64%,and 81.16%for F1,respectively.

关键词： retinal image segmentation triple attention mechanism atrous convolution residual network

New health-state assessment model based on belief rule base with interpretability

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science China(information sciences) 2021年第7期64卷 209-223页

作者： Zhijie ZHOU You CAO Guanyu HU Youmin ZHANG Shuaiwen TANG Yuan CHEN High-Tech Institute of Xi'an Department of information and Control Engineering Xi'an University of Technology school of computer science and information security Guilin University of Electronic Technology Department of Mechanical Industrial and Aerospace Engineering Concordia University

Health-state assessment is the foundation of optimal-maintenance decision-making for complex systems to maintain reliability and safety. Generating the assessment results in a convincing and interpretable way to avoid potential risks is of great importance. Belief rule base(BRB) as an interpretable model performs well in health-state assessment. However, the interpretability of a BRB-based model may be lost during the optimization process, which is expressed mainly as three problems: expert knowledge is not effectively used in the optimization process; the optimized rules of BRB may be in conflict with real systems; and some parameters get over-optimized, which may affect experts’ initial judgment. Three concepts — "searching intensity", "interpretability constraint of belief distribution", and "rule-activation factor" — are defined to address these problems. Using these concepts, we propose a new health-state assessment model based on the interpretable BRB and a new optimization method to improve the accuracy and preserve the interpretability of the new model. To demonstrate the effectiveness of the proposed model, we conducted an aero-engine case study.

关键词： health-state assessment belief rule base interpretability complex systems

Super-resolution compressive spectral imaging via two-tone adaptive coding

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Photonics Research 2020年第6期8卷 395-411页

作者： CHANG XU TINGFA XU GE YAN XU MA YUHAN ZHANG XI WANG FENG ZHAO GONZALO R.ARCE Key Laboratory of Photoelectronic Imaging technology and System School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China school of computer science and information security Guilin University of Electronic TechnologyGuilin 541004China Department of Electrical and computer Engineering University of DelawareNewarkDelaware 19716USA

Coded apertures with random patterns are extensively used in compressive spectral imagers to sample the incident scene in the image *** samplings,however,are inadequate to capture the structural characteristics of the underlying signal due to the sparsity and structure nature of sensing matrices in spectral *** paper proposes a new approach for super-resolution compressive spectral imaging via adaptive *** this method,coded apertures are optimally designed based on a two-tone adaptive compressive sensing(CS)framework to improve the reconstruction resolution and accuracy of the hyperspectral imager.A liquid crystal tunable filter(LCTF)is used to scan the incident scene in the spectral domain to successively select different spectral *** output of the LCTF is modulated by the adaptive coded aperture patterns and then projected onto a lowresolution detector *** coded aperture patterns are implemented by a digital micromirror device(DMD)with higher resolution than that of the *** to the strong correlation across the spectra,the recovered images from previous spectral channels can be used as a priori information to design the adaptive coded apertures for sensing subsequent spectral *** particular,the coded apertures are constructed from the a priori spectral images via a two-tone hard thresholding operation that respectively extracts the structural characteristics of bright and dark regions in the underlying ***-resolution image reconstruction within a spectral channel can be recovered from a few snapshots of low-resolution *** no additional side information of the spectral scene is needed,the proposed method does not increase the system *** on the mutual-coherence criterion,the proposed adaptive CS framework is proved theoretically to promote the sensing efficiency of the spectral *** and experiments are provided to demonstrate and assess the proposed adaptive cod

关键词： resolution spectral image

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Collision-Based Chosen-Message Simple Power Clustering Attack Algorithm

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China Communications 2013年第5期10卷 114-119页

作者：陈艾东许森陈运秦志光 school of computer science and Engineering University of Electronic Science and Technology of China information security Institute Chengdu University of Information Technology school of electronic information and Electrical Engineering Shanghai Jiao Tong University

Chosen-message pair Simple Power Analysis (SPA) attacks were proposed by Boer, Yen and Homma, and are attack methods based on searches for collisions of modular multiplication. However, searching for collisions is difficult in real environments. To circumvent this problem, we propose the Simple Power Clustering Attack (SPCA), which can automatically identify the modular multiplication collision. The insignificant effects of collision attacks were validated in an Application Specific Integrated Circuit (ASIC) environment. After treatment with SPCA, the automatic secret key recognition rate increased to 99%.

关键词： crypt analysis side channel attack collision attack chosen-message attack clustering algorithm

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Sensitive information security Based on Elliptic Curves

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World Journal of Engineering and technology 2024年第2期12卷 274-285页

作者： Nadine Nibigira Vincent Havyarimana Zhu Xiao school of Engineering sciences University of Burundi Doctoral School Bujumbura Burundi Department of Applied sciences Burundi Higher Institute of Education (ENS) Bujumbura Burundi College of computer science and electronic Engineering Hunan University Changsha China

The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.

关键词： Cryptography Elliptic Curves Digital security Data Sensitive Data Implementation

K-Means Clustering with Local Distance Privacy

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Big Data Mining and Analytics 2023年第4期6卷 433-442页

作者： Mengmeng Yang Longxia Huang Chenghua Tang the Data61 Commonwealth Scientific and Industrial Research OrganizationMelbourne 3168Australia the school of computer science and Communication Engineering Jiangsu UniversityZhenjiang 212013China. the school of computer science and information security Guilin University of Electronic TechnologyGuilin 541010China

With the development of information technology,a mass of data are generated every *** and analysing these data help service providers improve their services and gain an advantage in the fierce market competition.K-means clustering has been widely used for cluster analysis in real ***,these analyses are based on users’data,which disclose users’*** differential privacy has attracted lots of attention recently due to its strong privacy guarantee and has been applied for clustering ***,existing K-means clustering methods with local differential privacy protection cannot get an ideal clustering result due to the large amount of noise introduced to the whole dataset to ensure the privacy *** solve this problem,we propose a novel method that provides local distance privacy for users who participate in the clustering *** of making the users’records in-distinguish from each other in high-dimensional space,we map the user’s record into a one-dimensional distance space and make the records in such a distance space not be distinguished from each *** be specific,we generate a noisy distance first and then synthesize the high-dimensional data *** propose a Bounded Laplace Method(BLM)and a Cluster Indistinguishable Method(CIM)to sample such a noisy distance,which satisfies the local differential privacy guarantee and local dE-privacy guarantee,***,we introduce a way to generate synthetic data records in high-dimensional *** experimental evaluation results show that our methods outperform the traditional methods significantly.

关键词： K-means clustering local differential privacy data analysis

Secure searchable public key encryption against insider keyword guessing attacks from indistinguishability obfuscation

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science China(information sciences) 2018年第3期61卷 228-230页

作者： Lixue SUN Chunxiang XU Mingwu ZHANG Kefei CHEN Hongwei LI Center for Cyber security School of Computer Science and EngineeringUniversity of Electronic Science and Technology of China school of computer science Hubei University of Technology school of science Hangzhou Normal University Laboratory of science and technology on Communication security

Public key encryption with keyword search(PEKS)enables one to search encrypted data containing some keyword without decrypting the data in public key *** et al.[1]introduced the notion of PEKS,but later Byun et al.[2]showed the scheme in[1]is vulnerable to the outsider/insider keyword guessing attacks(KGA).Many previous PEKS studies have tackled the

关键词： SKS IND PKI MAC SKR Mac PKR

SpectraTr:A novel deep learning model for qualitative analysis of drug spectroscopy based on transformer structure

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Journal of Innovative Optical Health sciences 2022年第3期15卷 107-117页

作者： Pengyou Fu Yue Wen Yuke Zhang Lingqiao Li Yanchun Feng Lihui Yin Huihua Yang school of computer science and information security guilin university of electronic technology 1 jinji road Guilin 541004P.R.China school of Artīcial Intelligence Beijing university of Posts and Telecommunications 10 Xitucheng road Beijing 100876P.R.China school of International Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China National Institutes for Food and Drug Control 10 Tiantanxili road Beijing 100050P.R.China

The drug supervision methods based on near-infrared spectroscopy analysis are heavily dependent on the chemometrics model which characterizes the relationship between spectral data and drug *** preliminary application of convolution neural network in spectral analysis demonstrates excellent end-to-end prediction ability,but it is sensitive to the hyper-parameters of the *** transformer is a deep-learning model based on self-attention mechanism that compares convolutional neural networks(CNNs)in predictive performance and has an easy-todesign model ***,a novel calibration model named SpectraTr,based on the transformer structure,is proposed and used for the qualitative analysis of drug *** experimental results of seven classes of drug and 18 classes of drug show that the proposed SpectraTr model can automatically extract features from a huge number of spectra,is not dependent on pre-processing algorithms,and is insensitive to model *** the ratio of the training set to test set is 8:2,the prediction accuracy of the SpectraTr model reaches 100%and 99.52%,respectively,which outperforms PLS DA,SVM,SAE,and *** model is also tested on a public drug data set,and achieved classification accuracy of 96.97%without preprocessing algorithm,which is 34.85%,28.28%,5.05%,and 2.73%higher than PLS DA,SVM,SAE,and CNN,*** research shows that the SpectraTr model performs exceptionally well in spectral analysis and is expected to be a novel deep calibration model after Autoencoder networks(AEs)and CNN.

关键词： Near-infrared spectroscopy analysis drug supervision transformer structure deep learning chemometrics

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反向连边在大型分层网络中的影响（英文）

Engineering 2024年第5期 240-249页

作者：曹浩森胡斌斌莫小雨陈都鑫高建喜袁烨陈关荣 Tamás Vicsek 管晓宏张海涛 MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology school of Mechanical and Aerospace Engineering Nanyang Technological University Jiangsu Key Laboratory of Networked Collective Intelligence School of Mathematics Southeast University Department of computer science Rensselaer Polytechnic Institute Department of electronic Engineering City University of Hong Kong Department of Biological Physics E?tv?s University MOE Key Laboratory for Intelligent Networks and Network security School of Automation Science and Engineering Xi'an Jiaotong University

Hierarchical networks are frequently encountered in animal groups, gene networks, and artificial engineering systems such as multiple robots, unmanned vehicle systems, smart grids, wind farm networks,and so forth. The structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes, such as lagging birds' howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social group. This study reveals that, for most large-scale real hierarchical networks, the majority of the reverse edges do not affect the synchronization process of the entire network; the synchronization process is influenced only by a small part of these reverse edges along specific paths. More surprisingly, a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%. The effect of such edges depends not on the network size but only on the average in-degree of the involved subnetwork. The overwhelming majority of active reverse edges turn out to have some kind of ‘‘bunchingo effect on the information flows of hierarchical networks, which slows down synchronization processes. This finding refines the current understanding of the role of reverse edges in many natural, social, and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these networks. Our study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

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