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International Conference on Machine Learning and Applications (ICMLA)

作者： Jianping Fan Tianyi Zhao Zhenzhong Kuang Zhou Yu Jun Yu Department of Computer Science UNC-Charlotte Charlotte NC USA Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China

In this paper, a deep mixture algorithm is developed to support large-scale visual recognition (e.g., recognizing tens of thousands of object classes) by seamlessly combining a set of base deep CNNs (AlexNet) with diverse task spaces, e.g., such base deep CNNs (i.e., diverse experts) are trained to recognize different subsets of tens of thousands of object classes rather than the same set of object classes. Our experimental results have demonstrated that our deep mixture algorithm can achieve very competitive results on large-scale visual recognition.

关键词： Ontologies Proposals Prediction algorithms Visualization Semantics Atomic layer deposition

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BPaaS: A platform for artifact-centric business process customization in cloud computing 29

BPaaS: A platform for artifact-centric business process cust...

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29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017

作者： Gao, Min Yin, Yu Wang, Xingfei Li, Ying Chen, Zaidie Guo, Lipeng Key Laboratory of Complex Systems Modeling and Simulation of Ministry of Education College of Electrical Engineering Hangzhou Dianzi University Zhejiang China College of Computer Science Zhejiang University Zhejiang Hangzhou China College of Computer Science Fudan University Shanghai China Hangzhou Housing Management Bureaus Hangzhou Zhejiang China

ISBN: (纸本)1891706411

As a new service paradigm of Software-As-A-Service (SaaS),Business Process-As-A-Service (BPaaS). BPaaS is used to build a cost-effective Business Process Management (BPM) system. Based on universal Artifacts, we develop a framework named SeGA (Self-Guided Artifact). In SeGA, a BPM system is capable of executing business processes from multiple clients, and responding query at runtime. what's more, by the template-based cascading data mapping method, entity to be synchronized with database automatically, so each BP instance can modify its process entity without worrying about the database access. In this paper, we conduct a deep research and implement a prototype system for Artifact process design.

关键词： Process design

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Ru-Ni alloy nanosheets as tandem catalysts for electrochemical reduction of nitrate to ammonia

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Nano Research 2024年第6期17卷 4815-4824页

作者： Xingchao You Jiawei Xu Zechao Zhuang Junkai Xia Suwen Wang Haiyan Wei Yongfu Li Yanjiang Cai Hai Xiang Bing Yu State Key Laboratory of Subtropical Silviculture Zhejiang A&F UniversityHangzhou 311300China Ecological-Environment&Health College(EEHC) Zhejiang A&F UniversityHangzhou 311300China Jiangsu Key Laboratory of Numerical Simulation of Large Scale Complex Systems and School of Chemistry and Materials Science Nanjing Normal UniversityNanjing 210023China Department of Chemistry Tsinghua UniversityBeijing 100084China Department of Chemical Engineering Columbia UniversityNew YorkNY 10027USA

Developing electrocatalysts that exhibit both high activity and ammonia selectivity for nitrate reduction is a significant and demanding challenge,primarily due to the complex nature of the multiple-electron reduction process *** encouraging approach involves coupling highly active precious metals with transition metals to enhance catalytic performance through ***,we report a ruthenium-nickel alloy catalyst with nanosheets(Ru-Ni NSs)structure that achieves a remarkable ammonia Faradaic efficiency of approximately 95.93%,alongside a yield rate of up to 6.11 g·h^(−1)·cm^(−2).Moreover,the prepared Ru-Ni NSs exhibit exceptional stability during continuous nitrate reduction in a flow reactor for 100 h,maintaining a Faradaic efficiency of approximately 90%and an ammonia yield of 37.4 mg·L^(−1)·h^(−1)using 0.05 M nitrate alkaline *** studies reveal that the catalytic process follows a two-step pathway,in which HONO serves as a migration *** presence of a partially oxidized Ru(002)surface enhances the adsorption of nitrate and facilitates the release of the migration intermediate by adjusting the strength of the electrostatic and covalent interactions between the adsorbate and the surface,*** the other hand,the Ni(111)surface promotes the utilization of the migration intermediate and requires less energy for NH_(3)*** tandem process contributes to a high catalytic activity of Ru-Ni NSs towards nitrate reduction.

关键词： alloy catalyst nitrate reduction ammonia synthesis Faradaic efficiency

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An LQP-Based Two-Step Method for Structured Variational Inequalities

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Journal of the Operations Research Society of China 2017年第3期5卷 301-317页

作者： Hong-Jin He Kai Wang Xing-Ju Cai De-Ren Han Department of Mathematics School of ScienceHangzhou Dianzi UniversityHangzhou 310018China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore School of Mathematical Sciences Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex SystemsNanjing Normal UniversityNanjing 210023China

t The logarithmic quadratic proximal(LQP)regularization is a popular and powerful proximal regularization technique for solving monotone variational inequalities with nonnegative *** this paper,we propose an implementable two-step method for solving structured variational inequality problems by combining LQP regularization and projection *** proposed algorithm consists of two *** first step generates a pair of predictors via inexactly solving a system of nonlinear ***,the second step updates the iterate via a simple correction *** establish the global convergence of the new method under mild *** improve the numerical performance of our new method,we further present a self-adaptive version and implement it to solve a traffic equilibrium *** numerical results further demonstrate the efficiency of the proposed method.

关键词： Logarithmic quadratic proximal Projection method Variational inequality problem Traffic equilibrium problem

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Satellite Interference Signal Classification Using Improved MLP Model

Satellite Interference Signal Classification Using Improved ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Xie, Liwei Zhuang, Yaqiang Zhuang, Xuebin Zeng, Xiaohui School of Systems Science and Engineering Sun Yat-Sen University Guangzhou China School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing China Science and Technology On Complex Aviation Systems Simulation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In response to the existing style of deceptive jamming of Global Position System (GPS) receivers by aerial jammer carriers, a method using improved multi-layer perceptron (MLP) model is proposed to identify and classify interference sources based on the rate of change of satellite incoming angle. The work firstly constructs an airborne GPS interference source localization deployment model, then analyzes and verifies the rationality of this simulation data model, and finally emphasizes the superiority of the proposed method using the classical classification algorithm as a comparison method. The simulation results indicated that the proposed method is capable to identify the corresponding interferers with a greater rate of recognition compared with other method in the built multi-interference source environment, which provides a reference for dealing with the interference identification and classification in the networked GPS interference source deployment environment. © 2022 IEEE.

关键词： Antennas

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Convolutional neural networks for intestinal hemorrhage detection in wireless capsule endoscopy images

Convolutional neural networks for intestinal hemorrhage dete...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Panpeng Li Ziyun Li Fei Gao Li Wan Jun Yu Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University School of Communication Engineering Hangzhou Dianzi University College of Computer Science Chongqing University

ISBN: (纸本)9781509060689

Wireless capsule endoscopy (WCE) can painlessly capture a large number of images inside the intestine. However, only a small portion of these WCE images contain hemorrhage. It is thus critical to develop automated hemorrhage detection method to facilitate the diagnosis of intestinal diseases. However, automated hemorrhage detection is complicated by 1) the extreme imbalance between the amount of hemorrhage images and that of normal images; and 2) the variety of the appearance, texture, and luminance inside the intestine. In this paper, we proposed to learn a robust intestinal hemorrhage detection model via Convolutional Neural Networks (CNNs), because of CNNs' extraordinary performance in solving various image understanding tasks. Specially, we explored different CNN architectures and data augmentation methods. Besides, we investigated the correlation between hemorrhage detection accuracy and image quality. Across about 1.3k hemorrhage images and 40k normal images, the learned CNN model achieves an F-measure of 98.87%.

关键词： Hemorrhaging Optical wavelength conversion Endoscopes Machine learning Biomedical imaging Training Wireless communication

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A credible mechanism of service about data resource in cloud computing

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International Journal of Network Security 2018年第4期20卷 754-761页

作者： Li, Yunfa Shen, Yangyang Li, Mingyi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Hangzhou Dianzi University Xiasha Higher Education Zone Hangzhou Zhejiang Province310018 China

In order to protect the security of service in cloud computing, we propose a credible mechanism of service for data resource. In the mechanism, we first build a system model and put forward its implementation process. Then, we design an encryption method used in the system model. On this basis, we discuss the function of the third party trusted platform. All of these constitute a credible mechanism of service about data resource in cloud computing. In order to verify the feasibility of the mechanism, a series of experiments have been done. The experimental results show that it is feasible to ensure the security of service about data resource in cloud computing. © 2018, Femto Technique Co., Ltd.

关键词： Cryptography

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Demo: A multi-agent communication reinforcement learning Cooperative Detection System 23

Demo: A multi-agent communication reinforcement learning Coo...

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Proceedings of the Eighth ACM/IEEE Symposium on Edge Computing

作者： Hongye Gao Yichen Shi Weixiong Rao Qiongmin Ma Tongji University Shanghai China National Key Laboratory for Complex Systems Simulation Beijing China

ISBN: (纸本)9798400701238

Communication is an effective mechanism to coordinate the behavior of mobile multi-agents. We propose a general multi-agent communication framework. With help of graph neural networks and reinforcement learning, this framework can provide a cooperative detection method with more powerful capabilities. In this paper, we demonstrate the configurable co-detection simulation system. Moreover, the evaluation of the multi-agent communication framework validates that the agents can effectively cooperate with each other through decentralized communication, and effectively reduce computation overhead meanwhile with high scalability.

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Reliability Assessment of LCC-HVDC links Using Protection Devices 1

Reliability Assessment of LCC-HVDC links Using Protection De...

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1st International Conference on Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition, ICRSEtoSET 2023

作者： Hameurlaine, Abdelhadi Boukezzi, Larbi Karef, Salah Sayah, Haouari University of Djelfa Laboratory of Applied Automation & Industrial Diagnostics Djelfa Algeria University of Djelfa Materials Science and Informatics Laboratory Msil Djelfa Algeria University of Djelfa Com Laboratory of Modeling Optimization and Simulation of Real Complex Systems Djelfa Algeria University of SidiBel-Abbes Intelligent Control and Electrical Power System Laboratory SidiBel-Abbes Algeria

ISBN: (纸本)9798350346336

the DC/AC interaction and the presence of the high nonlinearity in the HVDC links, these problems needs to examine the behavior of the system in steady-state and transient conditions in order to define the great role of protection functions and control parameters. Furthermore, Control and protection systems are a vital part of an HVDC system to guarantee the safety, reliability, and stability of its operation. This research aim is to provide the solutions for control and protection problems that can occur in HVDC link. In this paper, we study how we mitigate this serious malfunction of commutation failure process in the operation of HVDC converters. Indeed some protection functions like the commutation failure prevention. Furthermore, HVDC transmission systems are vulnerable to DC faults and its protection becomes ever more important with the fast growth in the number of installations. Finally, the dynamics of the studied power system including the HVDC link is thoroughly investigated through various simulation scenarios. © 2023 IEEE.

关键词： HVDC power transmission

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer modeling in Engineering & Sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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