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A survey on federated learning:a perspective from multi-party computation

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Frontiers of Computer Science 2024年第1期18卷 93-103页

作者： Fengxia LIU Zhiming ZHENG Yexuan SHI Yongxin TONG Yi ZHANG Institute of Artificial Intelligence and Key laboratory of Mathematics Informatics Behavioral Semantics Beihang UniversityBeijing 100191China State Key laboratory of Software Development Environment and Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang UniversityBeijing 100191China Pengcheng laboratory Shenzhen 518055China Zhongguancun laboratory Beijing 100190China Institute for Mathematical Sciences and Engineering Research Center of Financial Computing and digital Engineering Renmin University of ChinaBeijing 100872China

Federated learning is a promising learning paradigm that allows collaborative training of models across multiple data owners without sharing their raw *** enhance privacy in federated learning,multi-party computation can be leveraged for secure communication and computation during model *** survey provides a comprehensive review on how to integrate mainstream multi-party computation techniques into diverse federated learning setups for guaranteed privacy,as well as the corresponding optimization techniques to improve model accuracy and training *** also pinpoint future directions to deploy federated learning to a wider range of applications.

关键词： sfederated learning multi-party ycomputation privacy-preserving data mining distributed learning

油墨粘度对卷对卷印刷有机光活性层的油墨转移速率和薄膜缺陷的影响机理

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Science China Materials 2024年第8期67卷 2600-2610页

作者：刘媛琪王振国潘雅琴刘天宇张亚宾张青莫黎昕骆群马昌期 Beijing Engineering Research Center of Printed Electronics Beijing Institute of Graphic CommunicationBeijing 102600China i-lab&Printable Electronics Research Center Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of Sciences(CAS)Suzhou 215123China Vacuum Interconnected Nanotech Workstation(Nano-X) Suzhou Institute of Nano-Tech and Nano-Bionics of Chinese Academy of Sciences(CAS)Suzhou 215123China

卷对卷(R2R)凹版印刷具有高的边缘分辨率、可图案化、高加工速度等优势,是制备大面积柔性有机太阳能电池(FOSCs)的一种可行技术.有机光活性层的薄膜质量是决定有机太阳能电池器件性能的关键.对于凹版印刷过程而言,墨水的转移是影响印刷... 详细信息

卷对卷(R2R)凹版印刷具有高的边缘分辨率、可图案化、高加工速度等优势,是制备大面积柔性有机太阳能电池(FOSCs)的一种可行技术.有机光活性层的薄膜质量是决定有机太阳能电池器件性能的关键.对于凹版印刷过程而言,墨水的转移是影响印刷薄膜厚度和质量的关键.本文深入研究了有机光活性层的墨水粘度对墨水转移率和薄膜缺陷的影响.我们开发了紫外可见光谱法,量化凹版印刷过程中墨水的转移率.通过对墨水的流变行为分析、流体动力学模拟和实验验证,深入研究了油墨粘度与油墨转移率、膜厚和膜均匀性之间的关系.结果表明,油墨粘度约为25 m Pa·s是R2R凹版印刷有机光活性层薄膜的适合粘度.通过对油墨配方的优化,我们制备了全R2R印刷FOSCs,其中1 cm^(2);电池的效率超过12%.

关键词：凹版印刷油墨粘度油墨转移率有机太阳能电池油墨配方紫外可见光谱法流体动力学模拟活性层

Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram

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Computers, Materials & Continua 2024年第3期78卷 3323-3348页

作者： Umer Sadiq Khan Zhen Liu Fang Xu Muhib Ullah Khan Lerui Chen Touseef Ahmed Khan Muhammad Kashif Khattak Yuquan Zhang School of Computer and Information Science Hubei Engineering UniversityXiaogan432000China Institute for AI Industrial Technology Research Hubei Engineering UniversityXiaogan432000China Key lab of Mountain Hazards and Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China University of Chinese Academy of Sciences Beijing100049China College of Aviation Zhongyuan University of TechnologyZhengzhou451191China Research Center of digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China School of Computer Science University of PoonchAzad Jammu Kashmir12350Pakistan School of Computer Science and Information Engineering Hubei UniversityWuhan430062China

Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture *** the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation *** this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter *** proposed model highlights the residual region with considerable information and constructs color ***,we incorporate the content-based color saliency as spatial information in the Gaussian mixture *** segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum ***,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic *** experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge *** the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.

关键词： Unsupervised segmentation color saliency spatial weighted GMM random color histogram

Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and communications 2024年第6期12卷 135-151页

作者： Md. Mehedi Hasan Md. Masud Rana Abu Sayed Md. Mostafizur Rahaman Department of Information and communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

Green resource allocation for mobile edge computing

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digital communications and Networks 2023年第5期9卷 1190-1199页

作者： Anqi Meng Guandong Wei Yao Zhao Xiaozheng Gao Zhanxin Yang State Key laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China Engineering Center of digital Audio and Video Communication University of ChinaBeijing100024China School of Information and Electronics Beijing Institute of TechnologyBeijing100081China

We investigate the green resource allocation to minimize the energy consumption of the users in mobile edge computing systems,where task offloading decisions,transmit power,and computation resource allocation are jointly *** considered energy consumption minimization problem is a non-convex mixed-integer nonlinear programming problem,which is challenging to ***,we develop a joint search and Successive Convex Approximation(SCA)scheme to optimize the non-integer variables and integer variables in the inner loop and outer loop,***,in the inner loop,we solve the optimization problem with fixed task offloading *** to the non-convex objective function and constraints,this optimization problem is still non-convex,and thus we employ the SCA method to obtain a solution satisfying the Karush-Kuhn-Tucker *** the outer loop,we optimize the offloading decisions through exhaustive ***,the computational complexity of the exhaustive search method is greatly *** reduce the complexity,a heuristic scheme is proposed to obtain a sub-optimal *** results demonstrate the effectiveness of the developed schemes.

关键词： Mobile edge computing Green communications Mixed-integer programming Resource allocation

Two-phase real-time rendering method for realistic water refraction

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Virtual Reality & Intelligent Hardware 2020年第2期2卷 132-141页

作者： Hongli LIU Honglei HAN Guangzheng FEI School of Animation and digital Arts Communication University of ChinaChaoyang DistrictBeijing 100024China

Background Realistic rendering has been an important g oal of several interactive applications,which requires an efficient virtual simulation of many special effects that are common in the real ***,refraction is often ignored in these *** the refraction effect is extremely complicated and *** In this study,a simple,efficient,and fast rendering technique of water refraction effects is *** technique comprises a broad and narrow *** the broad phase,the water surface is considered *** vertices of underwater meshes are transformed based on Snell's *** the narrow phase,the effects of waves on the water surface are *** pixel on the water surface mesh is collected by a screen-space method with an extra rendering *** broad phase redirects most pixels that need to be recalculated in the narrow phase to the pixels in the rendering *** We analyzed the performances of three different conventional methods and ours in rendering refraction effects for the same *** proposed method obtains higher frame rate and physical accuracy comparing with other *** is used in several game scenes,and realistic water refraction effects can be generated *** The two-phase water refraction method produces a tradeoff between efficiency and *** is easy to implement in modern game engines,and thus improve the quality of rendering scenes in video games or other real-ti me applications.

关键词： Real-time rendering Refraction Liquid renderings

Clinically adaptable machine learning model to identify early appreciable features of diabetes

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Intelligent Medicine 2024年第1期4卷 22-32页

作者： Nurjahan Nipa Mahmudul Hasan Riyad Shahriare Satu Walliullah Koushik Chandra Howlader Mohammad Ali Moni Department of Information and communication Technology Bangabandhu Sheikh Mujibur Rahman Digital UniversityBangladeshKaliakairGazipur1750 Bangladesh Department of Applied Mathematics Noakhali Science and Technology UniversityNoakhali3814Bangladesh Department of Management Information Systems Noakhali Science and Technology UniversityNoakhali3814Bangladesh Department of Computer Science and Telecommunication Engineering Noakhali Science and Technology UniversityNoakhali3814Bangladesh Department of Computer Science North Dakota State UniversityFargo58105NDUnited States School of Health and Rehabilitation Sciences Faculty of Health and Behavioural SciencesThe University of QueenslandSt LuciaQLD 4072Australia

Objective Diabetes mellitus is a serious disease where the body of affected patients are failed to produce enough insulin that causes an abnormality of blood *** disease happens for a number of reasons including modern lifestyle,lethargic attitude,unhealthy food consumption,family history,age,overweight,*** aim of this study was to propose a machine learning based prediction model that detected diabetes at the *** In this work,we collected 520 patients records from the University of California,Irvine(UCI)machine learning repository of Sylhet Diabetes Hospital,***,a similar questionnaire of that hospital was followed and assembled 558 patients records from all over Bangladesh through this ***,we accumulated patient records of these two *** the next step,these datasets were cleaned and applied thirty five state-of-arts classifiers such as logistic regression(LR),K nearest neighbors(KNN),support vector classifier(SVC),Nave Byes(NB),decision tree(DT),random forest(RF),stochastic gradient descent(SGD),Perceptron,AdaBoost,XGBoost,passive aggressive classifier(PAC),ridge classifier(RC),Nu-support vector classifier(NuSVC),linear support vector classifier(LSVC),calibrated classifier CV(CCCV),nearest centroid(NC),Gaussian process classifier(GPC),multinomial NB(MNB),complement NB,Bernoulli NB(BNB),categorical NB,Bagging,extra tree(ET),gradiant boosting classifier(GBC),Hist gradiant boosting classifier(HGBC),one vs rest classifier(OVsRC),multi-layer perceptron(MLP),label propagation(LP),label spreading(LS),stacking,ridge classifier CV(RCCV),logistic regression CV(LRCV),linear discriminant analysis(LDA),quadratic discriminant analysis(QDA),and light gradient boosting machine(LGBM)to explore best stable predictive *** performance of the classifiers has been measured using five metrics such as accuracy,precision,recall,F1-score,and area under the receiver operating ***,these outcomes were interpret

关键词： Diabetes Early features Machine learning Classification

Artificial intelligence in physiological characteristics recognition for internet of things authentication

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digital communications and Networks 2024年第3期10卷 740-755页

作者： Zhimin Zhang Huansheng Ning Fadi Farha Jianguo Ding Kim-Kwang Raymond Choo School of Computer and communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing100083China Faculty of Informatics Engineering Aleppo UniversityAleppoSyria Department of Computer Science Blekinge Institute of Technology37179KarlskronaSweden Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249-0631USA

Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)***,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral *** characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in ***,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate ***,we review the literature on the use of AI in physiological characteristics recognition pub-lished after *** use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their *** also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

关键词： Physiological characteristics recognition Artificial intelligence Internet of things Biological-driven authentication

Spectral efficiency analysis of OCDMA systems

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Chinese Optics Letters 2009年第3期7卷 183-185页

作者：闫辉邱昆凌云 Key lab of Broadband Optical Fiber communication and communication Networks Technology University of Electronic Science and Technology of China

We discuss several kinds of code schemes and analyze their spectral efficiency, code utilizing efficiency, and the maximal spectral efficiency. Error correction coding is used to increase the spectral efficiency, and it can avoid the spectral decrease with the increase of the length. The extended primer code （EPC） has the highest spectral efficiency in the unipolar code system. The bipolar code system has larger spectral efficiency than unipolar code system, but has lower code utilizing efficiency and the maximal spectral efficiency. From the numerical results, we can see that the spectral efficiency increases by 0.025 （b/s）/Hz when the bit error rate （BER） increases from 10^-9 to 10^-7.

关键词： Bit error rate Error correction