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2021国际计算机前沿大会

作者： Junchao Wang Jianmin Pang Jin Wei State Key Laboratory of Mathematical Engineering and Advanced Computing School of Computer Science Fudan University Shanghai Key Laboratory of Data Science Fudan University

Users usually focus on the application-level requirements which are quite friendly and direct to them. However, there are no existing tools automating the application-level requirements to infrastructure provisioning and application deployment. Although some security issues have been solved during the development phase, the undiscovered vulnerabilities remain hidden threats to the application's security. Cyberspace mimic defense(CMD) technologies can help to enhance the application's security despite the existence of the vulnerability. In this paper,the concept of SECurity-as-a-Service(SECaaS) is proposed with CMD technologies in cloud environments. The experiment on it was implemented. It is found that the application's security is greatly improved to meet the user's security and performance requirements within budgets through SECaaS. The experimental results show that SECaaS can help the users to focus on application-level requirements(monetary costs,required security level, etc.) and automate the process of application orchestration.

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Extended state observer-based sliding mode control for epilepsy

Extended state observer-based sliding mode control for epile...

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Chinese Intelligent Systems Conference, CISC 2020

作者： Wei, Wei Li, Ping Zuo, Min School of Artificial Intelligence Beijing Technology and Business University Beijing100048 China National Engineering Laboratory for Agri-product Quality Traceability Beijing Technology and Business University Beijing100048 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing100048 China

ISBN: (纸本)9789811584497

Closed-loop neuromodulation has great potentials in epilepsy and other neurological diseases. Given the complexity and particularity of epilepsy, the control strategy should be robust enough to those uncertainties and disturbances. To reduce the dependence on model information and ensure the closed-loop regulation of epilepsy, an extended state observer-based sliding mode control scheme is designed to suppress epileptic spikes produced by the Jansens neural mass model. Simulation results confirm the extended state observer-based sliding mode control in suppressing epilepsy. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Sliding mode control

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One-Hot Coding Similarity of Vehicle Routing Particle Swarm Optimizer 8th

One-Hot Coding Similarity of Vehicle Routing Particle Swarm ...

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8th International Conference on Artificial Intelligence and Security , ICAIS 2022

作者： He, CHao Li, Zhi Su, Shoubao Xu, Liukai Wang, Chishe School of Computer Jiangsu University of Science and Technology Zhenjiang212003 China Jiangsu Key Laboratory of Data Science and Smart Software Jinling Institute of Technology Nanjing211169 China Provincial Engineering Research Center of Digital Technology for Industrial Economic Jinling Institute of Technology Nanjing211169 China School of Computer Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783031067662

Aiming at the real-time problem of vehicle routing planning, an improved particle swarm optimization method, called AVSPSO, is proposed in this paper. In the method, the path similarity of vehicle routing is calculated by adopting based on the One-Hot coding vector and by improving the constraint processing through the combination of coding mode and fixed penalty, in which dynamically adjust the inertia weight through the evolution state is to balance the ability of local mining and global development of particles. Experimental results on two practical cases of vehicle routing optimization problems and comparisons with other methods have shown that the proposed method is feasible and stable with better performances. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vehicle routing

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Potential Geographical Distributions and Spatial Shifts Trends of Ecological Tea Plantations of Camellia Sinensis VAR. Assamica in Yunnan Province, China

Potential Geographical Distributions and Spatial Shifts Tren...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Peirou Yang Weiheng Xu Xingyong Liu Leiguang Wang College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China Key Laboratory of National Forestry and Grassland Administration on Forestry and Ecological Big Data Southwest Forestry University Kunming China Institute of Quality Standard and Testing Technology for Agro-Products Yunnan Academy of Agricultural Sciences Kunming China College of Landscape Architecture and Horticulture Sciences Southwest Forestry University Kunming China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Camellia sinensis *** is a unique product of Geographical Indication in Yunnan province. Centennial tea plantations within plantations of *** *** can yield high-quality ecological tea. However, the limited production of ecological tea is insufficient to meet the widespread demand for high-quality tea leaves. The optimized MaxEnt model exhibits better accuracy and reliability in predicting the potential suitable distribution of small-sample species. Therefore, this study based on 80 sample data and 16 key environmental variables, optimize the MaxEnt model using the ENMeval package. The distribution and changes of the potential suitable areas of ecological tea plantations of *** *** in Yunnan province were extracted for the periods 1981-2010(History), 2011-2040(Current), and 2041-2070(Future). The research results indicate that the performance of the MaxEnt model has been enhanced, with the 10P value reduced to 0.1125 and Training AUC and Test AUC reaching 0.9516 and 0.9422, respectively. In the three periods, the potential suitable areas are mainly concentrated in the western, the south and southwest regions of Yunnan Province. The area of high suitability has decreased by a total of 259 km 2 , while the area of moderate suitability has increased by 4031 km 2 . There is potential for developing ecological tea plantations of *** *** in the western, the southern and southwestern parts of Yunnan Province. The managers and planners of tea plantations can further plan for the transformation and evaluation of tea gardens based on local policies. The results of this study will contribute to driving tea industry in Yunnan Province towards a more sustainable development path.

关键词： Industries Training Reactive power Biological system modeling Plantations Production Predictive models

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Gradient Coupled Flow: Performance Boosting on Network Pruning by Utilizing Implicit Loss Decrease

SSRN

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SSRN 2022年

作者： Kang, Xiatao Li, Ping Wu, Jiaying Yao, Jiayi School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transp Changsha410114 China

Network pruning prior to training makes generalization more challenging than ever, while recent studies mainly focus on the trainability of the pruned networks in isolation. This paper explores a new perspective on loss implicit decrease of the data to be trained caused by one-batch training during each round, whose first-order approximation we term gradient coupled flow. We thus present a criterion sensitive to gradient coupled flow (GCS), which is hypothesized to capture those weights most sensitive to performance boosting at initialization. Evaluations are empirically investigated on multiple datasets such as CIFAR10/100, Tiny-ImageNet and MNIST deployed on VGG and ResNet architectures. It is shown that GCS achieves decent performance in both single pruning and iterative pruning before training. In addition, a variant of GCS called GCS-Group performs better at low compression ratios, further confirming the role of implicit loss. Interestingly, our explorations show there exists a linear correlation between generalization and implicit loss decrease based measurements on previous works as well as GCS, which ideally describes causes of accuracy fluctuation in a fine-grained manner. © 2022, The Authors. All rights reserved.

关键词： Deep learning

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FRSM: A Novel Fault-Tolerant Approach for Redundant-Path-Enabled Service Migration in Mobile Edge Computing 1

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29th International Conference on Web Services, ICWS 2022 Held as Part of the Services Conference Federation, SCF 2022

作者： Zhao, Jiale Dai, Mengxuan Xia, Yunni Ma, Yong He, Meibin Peng, Kai Li, Jianqi Li, Fan Fu, Xiaodong School of Computer Chongqing University Chongqing400030 China School of Computer and Information Engineering Jiangxi Normal University Nanchang330022 China Department of Big Data and AI of Jiangxi Telecom Nanchang330029 China Engineering College Huaqiao University Quanzhou362021 China Global Energy Interconnection Research Institute Co. Ltd. Beijing102209 China Key Laboratory of Fundamental Synthetic Vision Graphics and Image Science for National Defense Sichuan University Chengdu610065 China Data Science Research Center Faculty of Science Kunming University of Science and Technology Kunming650031 China

ISBN: (数字)9783031235795

ISBN: (纸本)9783031235788

Mobile Edge Computing (MEC) provides users with low-latency, highly responsive services by deploying Edge Servers (ESs) near applications. MEC allows any edge-hosted application or service to be migrated between different edge resource providers without being locked into a single provider. Nevertheless, due to its complexity and dynamics, the real edge computing environment is prone to errors and failures, reducing the reliability of edge service migration. This paper proposes a novel fault-tolerant method for redundant path service migration. The method utilizes sliding-window-based model and identifies a set of service migration paths, enabling the evaluation of the time-varying failure rate of ESs. The method combines resubmission and replication mechanisms and decides the edge service migration scheme by selecting multiple redundant migration paths. We also conduct extensive simulations and show that our proposed method outperforms traditional solutions in several metrics. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mobile edge computing

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A New Simple Stochastic Gradient Descent Type Algorithm With Lower Computational Complexity for Bilevel Optimization

arXiv

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arXiv 2023年

作者： Huo, Haimei Liu, Risheng Su, Zhixun The School of Mathematical Sciences Dalian University of Technology Dalian116024 China The DUT-RU International School of Information Science and Engineering Dalian University of Technology China The Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian116024 China The State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian116024 China The Key Laboratory for Computational Mathematics and Data Intelligence of Liaoning Province Dalian116024 China

Bilevel optimization has been widely used in many machine learning applications such as hyperparameter optimization and meta learning. Recently, many simple stochastic gradient descent(SGD) type algorithms(without using momentum and variance techniques) have been proposed to solve the bilevel optimization problems. However, all the existing simple SGD type algorithms estimate the hypergradient via stochastic estimation of Neumann series. In the paper, we propose to estimate the hypergradient via SGD-based Estimation(i.e., solving the linear system with SGD). By using warm start initialization strategy, a new simple SGD type algorithm SSGD based on SGD-based Estimation is proposed. We provide the convergence rate guarantee for SSGD and show that SSGD outperforms the best known computational complexity achieved by the existing simple SGD type algorithms. Our experiments validate our theoretical results and demonstrate the efficiency of our proposed algorithm SSGD in hyperparameter optimization applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear systems

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CIRSM-Net: A Cyclic Registration Network for SAR and Optical Images

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Wang, Peng Liu, Yuzhou Liang, Xiao Zhu, Daiyin Gong, Xunqiang Ye, Yuanxin Lee, Harry F. Huang, Bo Nanjing University of Aeronautics and Astronautics Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education Nanjing210016 China Optoelectronic Measurement and Intelligent Perception Zhongguancun Open Laboratory Beijing100190 China City University of Macau Faculty of Data Science 999078 China Beijing Institute of Control Engineering Beijing100190 China East China University of Technology Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake Ministry of Natural Resources Nanchang330013 China Southwest Jiaotong University Faculty of Geosciences and Environmental Engineering Chengdu611756 China Chinese University of Hong Kong Department of Geography and Resource Management SAR Hong Kong Hong Kong University of Hong Kong Department of Geography SAR Hong Kong Hong Kong

The registration of synthetic aperture radar (SAR) and optical images is critical in multimodal remote sensing image fusion. In recent years, deep learning-based registration networks have been continuously introduced. However, owing to the significant disparities in viewing angles and radiometric properties between SAR and optical images, current deep learning methods struggle to fully exploit the physical properties of radar imaging. In addition, many existing matching networks typically perform only a forward pass, resulting in suboptimal model performance. This article proposes a cyclic iterative registration SAR mechanism network (termed as CIRSM-Net) for the registration of SAR and optical images. First, we design a learning module that integrates the radar equation with a microwave scattering model to capture deep features from SAR images, and design a corresponding scattering feature loss to aid in better generalization across various radar images. Then, to explore optimization methods for matching networks, this study proposes a strategy of multiple iterative optimizations within the matching network. Specifically, it integrates speeding-up radiation-variation insensitive feature transform (RIFT2) supervision in the backend matching network and iteratively optimizes the final output. Finally, during the iteration process, we propose an innovative matching loss function that combines the rotation invariance supervision of RIFT2 with iterative optimization techniques to enhance feature matching accuracy. Experimental results on both public and our own datasets additionally confirm the effectiveness and superiority of the proposed approach, demonstrating its significant potential for practical applications. © 2025 IEEE.

关键词： Radar imaging

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中国碳收支:1980~2021年

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Science Bulletin 2024年第1期69卷 114-124页

作者：夏晓圣任培阳王旭辉刘丹陈修治丹利何斌何洪林居为民梁敏琪陆星劼彭静覃章才夏江周郑博魏静乐旭于贵瑞朴世龙袁文平 School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon CycleSun Yat-sen UniversityZhuhai 510245China Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing 100091China State Key Laboratory of Tibetan Plateau Earth System Resources and EnvironmentInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Earth Surface Processes and Resource Ecology College of Global Change and Earth System ScienceBeijing Normal UniversityBeijing 100875China Synthesis Research Center of China’s Ecosystem Research Network Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China International Institute for Earth System Science Nanjing UniversityNanjing 210023China Tianjin Key Laboratory of Water Resources and Environment Tianjin Normal UniversityTianjin 300387China Institute of Environment and Ecology Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjing 210044China

As one of the world's largest emitters of greenhouse gases,China has set itself the ambitious goal of achieving carbon peaking and carbon ***,it is crucial to quantify the magnitude and trend of sources and sinks of atmospheric carbon dioxide(CO_(2)),and to monitor China's progress toward these *** state-of-the-art datasets and models,this study comprehensively estimated the anthropogenic CO_(2)emissions from energy,industrial processes and product use,and waste along with natural sources and sinks of CO_(2)for all of China during *** recognize the differences among various methods of estimating greenhouse emissions,the estimates are compared with China's National Greenhouse Gas Inventories(NGHGIs)for 1994,2005,2010,2012,and *** CO_(2)emissions in China have increased by 7.39 times from 1980 to 12.77 Gt CO_(2)a^(-1)in *** benefiting from ecological projects(e.g.,Three Norths Shelter Forest System Project),the land carbon sink in China has reached 1.65 Gt CO_(2)a^(-1)averaged through 2010-2021,which is almost 15.81 times that of the carbon sink in the *** average,China's terrestrial ecosystems offset 14.69%±2.49%of anthropogenic CO_(2)emissions through *** provincial-level administrative regions of China,Xizang and Qinghai,have achieved carbon neutrality according to our estimates,but nearly half of the administrative regions of China have terrestrial carbon sink offsets of less than 10%of anthropogenic CO_(2)*** study indicated a high level of consistency between NGHGIs and various datasets used for estimating fossil CO_(2)emissions,but found notable differences for land carbon *** estimates of the terrestrial carbon sinks of NGHGIs urgently need to be verified with process-based models which integrate the comprehensive carbon cycle processes.

关键词： CO_(2)emission Land carbon sink China Carbon neutrality Carbon budget

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Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix

arXiv

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arXiv 2023年

作者： Lv, Shaogao Wen, Gang Liu, Shiyu Wei, Linsen Li, Ming Department of Statistics and Data Science Nanjing Audit University China University of Electronic Science and Technology of China China School of Astronautics Northwestern Polytechnical University China Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University Jinhua China Key Laboratory of Scientific and Engineering Computing Ministry of Education Shanghai Jiao Tong University China

To improve the robustness of graph neural networks (GNN), graph structure learning (GSL) has attracted great interest due to the pervasiveness of noise in graph data. Many approaches have been proposed for GSL to jointly learn a clean graph structure and corresponding representations. To extend the previous work, this paper proposes a novel regularized GSL approach, particularly with an alignment of feature information and graph information, which is motivated mainly by our derived lower bound of node-level Rademacher complexity for GNNs. Additionally, our proposed approach incorporates sparse dimensional reduction to leverage low-dimensional node features that are relevant to the graph structure. To evaluate the effectiveness of our approach, we conduct experiments on real-world graphs. The results demonstrate that our proposed GSL method outperforms several competitive baselines, especially in scenarios where the graph structures are heavily affected by noise. Overall, our research highlights the importance of integrating feature and graph information alignment in GSL, as inspired by our derived theoretical result, and showcases the superiority of our approach in handling noisy graph structures through comprehensive experiments on real-world datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphic methods

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