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2019 Jiangsu Annual Conference on Automation, JACA 2019

作者： Han, Ling Wang, Xiangyu Li, Shihua Liu, Jiyu School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China Aviation Key Laboratory of Science and Technology on Aircraft Control Facri Xian710065 China

This study studies the height and attitude tracking control problem of an unmanned helicopter system with disturbances. A composite controller based on the combination of harmonic disturbance observers and backstepping technique is proposed to achieve asymptotic tracking for height and attitude. Firstly, harmonic disturbance observers (HDOB) are designed to estimate the unknown disturbances affecting each channel. Then, a composite controller is proposed by integrating the backstepping control technique and the HDOB technique together to achieve the height and attitude tracking goal. Stability analysis of the closed-loop system is given. Finally, numerical simulations are presented to verify the efficiency of the proposed control scheme. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Backstepping

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Correction: Impact of ligand fields on Kubas interaction of open copper sites in MOFs with hydrogen molecules: an electronic structural insight

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RSC advances 2024年第44期14卷 32471页

作者： Trang Thuy Nguyen Hoan Van Tran Linh Hoang Nguyen Hoang Minh Nguyen Thang Bach Phan Toan Nguyen-The Yoshiyuki Kawazoe Faculty of Physics University of Science Vietnam National University Hanoi Vietnam nguyenthuytrang@hus.edu.vn. Key Laboratory for Multiscale Simulation of Complex Systems University of Science Vietnam National University Hanoi Vietnam. School of Engineering Physics Hanoi University of Science and Technology Hanoi Vietnam. Center for Innovative Materials and Architectures Vietnam National University Ho Chi Minh City Vietnam. Vietnam National University Ho Chi Minh City Vietnam. New Industry Creation Hatchery Center Tohoku University Sendai 980-8579 Japan. Department of Physics and Nanotechnology SRM Institute of Science and Technology Kattankulathur 603203 Tamilnadu India. School of Physics Institute of Science Suranaree University of Technology 111 University Avenue Nakhon Ratchasima 30000 Thailand.

[This corrects the article DOI: 10.1039/D4RA03946G.].

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Query modeling for click data based image recognition using graph based propagation and sparse coding

Query modeling for click data based image recognition using ...

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9th International Conference on Internet Multimedia Computing and Service, ICIMCS 2017

作者： Wu, Weichen Tan, Min Zheng, Guangjian Yu, Jun Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789811085291

We address the fine-grained image recognition problem using user click data, wherein each image is represented as a semantical query-click feature vector. Usually, the query set obtained from search engines is large-scale and redundant. We propose a novel query modeling approach to merge semantically similar queries and construct a compact click feature. We represent each query as a click feature, and design a graph based propagation approach to predict the zero-clicks, ensuring similar images have similar clicks. Afterwards, using this feature, we formulate the problem as a sparse coding based recognition task, wherein the dictionary is discriminatively trained. We evaluate our method for fine-grained image recognition on the public Clickture-Dog dataset. It is shown that, the propagated click feature performs much better than the original one. Also, sparse coding performs better than K-means in query merging. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Image recognition

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The 2024 Motile Active Matter Roadmap

arXiv

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arXiv 2024年

作者： Gompper, Gerhard Stone, Howard A. Kurzthaler, Christina Saintillan, David Peruani, Fernado Fedosov, Dmitry A. Auth, Thorsten Cottin-Bizonne, Cecile Ybert, Christophe Clément, Eric Darnige, Thierry Lindner, Anke Goldstein, Raymond E. Liebchen, Benno Binysh, Jack Souslov, Anton Isa, Lucio di Leonardo, Roberto Frangipane, Giacomo Gu, Hongri Nelson, Bradley J. Brauns, Fridtjof Marchetti, M. Cristina Cichos, Frank Heuthe, Veit-Lorenz Bechinger, Clemens Korman, Amos Feinerman, Ofer Cavagna, Andrea Giardina, Irene Jeckel, Hannah Drescher, Knut Theoretical Physics of Living Matter Institute for Advanced Simulation Forschungszentrum Jülich Jülich Germany Princeton University Department of Mechanical and Aerospace Engineering PrincetonNJ United States Max Planck Institute for the Physics of Complex Systems Center for Systems Biology Dresden Cluster of Excellence Physics of Life TU Dresden Dresden Germany University of California San Diego United States CY Cergy Paris University France Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut Lumière Matière Villeurbanne France Laboratoire PMMH-ESPCI UMR 7636 CNRS-PSL-Research University Sorbonne Université Université Paris Cité Paris France Institut Universitaire de France Paris France Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom Technische Universität Darmstadt Darmstadt64289 Germany Institute of Physics Universiteit van Amsterdam Science Park 904 Amsterdam1098 XH Netherlands T.C.M. Group Cavendish Laboratory University of Cambridge CambridgeCB3 0HE United Kingdom Laboratory for Soft Materials and Interfaces Department of Materials ETH Zurich Zurich8093 Switzerland Dipartimento di Fisica Sapienza Università di Roma Italy Department of Physics University of Konstanz Konstanz Germany Institute of Robotics and Intelligent Systems ETH Zürich Zurich Switzerland Kavli Institute for Theoretical Physics University of California Santa BarbaraCA93106 United States Department of Physics University of California Santa BarbaraCA93106 United States Molecular Nanophotonics Leipzig University Leipzig04013 Germany UMI FILOFOCS Israel Department of Physics of Complex Systems Weizmann Institute of Science Israel Rome Italy Dipartimento di Fisica Sapienza Università di Roma INFN Unità di Roma 1 Rome Italy Department of Biology and Biological Engineering California Institute of Technology Pasadena91125 United States Biozentrum University of Basel Basel4056 Switzerl

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of microrobotic systems to achieve similar functionality. With many fundamental properties of motile active matter now reasonably well understood and under control, the ground is prepared for the study of physical aspects and mechanisms of motion in complex environments, of the behavior of systems with new physical features like chirality, of the development of novel micromachines and microbots, of the emergent collective behavior and swarming of intelligent self-propelled particles, and of particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics. The 2024 motile active matter roadmap of Journal of Physics: Condensed Matter reviews the current state of the art of the field and provides guidance for further progress in t

关键词： Microrobots

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An evaluation method for network communication system efficiency based on multi-source information fusion 37

An evaluation method for network communication system effici...

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37th Chinese Control Conference, CCC 2018

作者： Yuan, Cao Yue-Ping, Wang Xue-Mei, Tang Xiao-Fang, Zhao Science and Technology on Complex Land Systems Simulation Laboratory Beijing100012 China Beijing Institute of Spacecraft System Engineering 100094 China

ISBN: (纸本)9789881563941

The number of experimental data obtained under different conditions is large, and there are some differences in the distribution characteristics of samples. If a large number of different types of data are mixed and the network communication Effectiveness evaluation is carried out, the characteristics of some samples may be drowned out, on the other hand, the information of many experimental samples is not fully utilized. In order to solve this problem, this paper proposes a method of network communication effectiveness evaluation based on multi-source information fusion. This method firstly analyzes the communication success rate of the cell communication node by longitudinal fusion of experimental information. Based on this, the confidence degree is used to construct the weighting coefficient, and the whole communication success rate of the network information system is evaluated by the experiment information of multiple nodes. Thus, the comprehensive evaluation of the communication efficiency of the unit node and the network Information system is realized. © 2018 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Efficiency

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On Exploring Undetermined Relationships for Visual Relationship Detection

On Exploring Undetermined Relationships for Visual Relations...

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Yibing Zhan Jun Yu Ting Yu Dacheng Tao Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney

ISBN: (纸本)9781728132945

In visual relationship detection, human-notated relationships can be regarded as determinate relationships. However, there are still large amount of unlabeled data, such as object pairs with less significant relationships or even with no relationships. We refer to these unlabeled but potentially useful data as undetermined relationships. Although a vast body of literature exists, few methods exploit these undetermined relationships for visual relationship detection. In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection. We propose a novel multi-modal feature based undetermined relationship learning network (MF-URLN) and achieve great improvements in relationship detection. In detail, our MF-URLN automatically generates undetermined relationships by comparing object pairs with human-notated data according to a designed criterion. Then, the MF-URLN extracts and fuses features of object pairs from three complementary modals: visual, spatial, and linguistic modals. Further, the MF-URLN proposes two correlated subnetworks: one subnetwork decides the determinate confidence, and the other predicts the relationships. We evaluate the MF-URLN on two datasets: the Visual Relationship Detection (VRD) and the Visual Genome (VG) datasets. The experimental results compared with state-of-the-art methods verify the significant improvements made by the undetermined relationships, e.g., the top-50 relation detection recall improves from 19.5% to 23.9% on the VRD dataset.

关键词： Visualization Fuses Dataset

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Power Characterization of Memory Intensive Applications: Analysis and Implications 1st

Power Characterization of Memory Intensive Applications: Ana...

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Qiu, Yeliang Jiang, Congfeng Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

DRAM is a significant source of server power consumption especially when the server runs memory intensive applications. Current power aware scheduling assumes that DRAM is as energy proportional as other components. However, the non-energy proportionality of DRAM significantly affects the power and energy consumption of the whole server system when running memory intensive applications. Thus good knowledge of server power characterization under memory intensive workloads can help better workload placement with power reduction. In this paper, we investigate the power characteristics of memory intensive applications on real rack servers of different generations. Through comprehensive analysis we find that (1) Server power consumption changes with workload intensity and concurrent execution threads. However, fully utilized memory systems are not the most energy efficient. (2) Powered memory modules of installed memory capacity, i.e. the memory capacity per processor core has significant impact on the application’s performance and server power consumption even if the memory system is not fully utilized. (3) Memory utilization is not always a good indicator for server power consumption when it is running memory intensive applications. Our experiments show that hardware configuration, workload types, as well as concurrently running threads have significant impact on a server’s energy efficiency when running memory intensive applications. Our findings presented in this paper provide useful insights and guidance to system designers, as well as data center operators for energy efficiency aware job scheduling and power reductions. © 2019, Springer Nature Switzerland AG.

关键词： Energy efficiency

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Scalability Evaluation of Big Data Processing Services in Clouds 1st

Scalability Evaluation of Big Data Processing Services in Cl...

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Zhou, Xin Jiang, Congfeng Qiu, Yeliang Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

Currently, many cloud providers deploy their big data processing systems as cloud services, which helps users conveniently manage and process their data in clouds. Among different service providers’ big data processing services, how to evaluate and compare their scalability is an interesting and challenging work. Most traditional benchmark tools focus on performance evaluation of big data processing systems, such as aggregated throughput and IOPS, but fail to conduct a quantitative analysis of their scalability. In this paper, we propose a measurement methodology to quantify the scalability of big data processing services, which makes the cloud services scalability comparable. We conduct a group of comparative experiments on AliCloud E-MapReduce and Baidu MRS, and collect their respective scalability characteristics under Hadoop and Spark workloads. The scalability characteristics observed in our work could help cloud users choose the best cloud service platform to set up an optimized big data processing system to achieve their specific goals more successfully. © 2019, Springer Nature Switzerland AG.

关键词： Big data

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Priority-Based Optimization of I/O Isolation for Hybrid Deployed Services 15th

Priority-Based Optimization of I/O Isolation for Hybrid Depl...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Zhang, Jiancheng Li, Youhuizi Zhou, Li Ren, Zujie Wan, Jian Wang, Yuan Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Zhejiang Lab Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Key Enterprise Research Institute of NetEase Big Data of Zhejiang Province Netease Hangzhou Network Co.Ltd Hangzhou China

ISBN: (纸本)9783030301453

With the increasing of software complexity and user demands, collaborative service is becoming more and more popular. Each service focuses on its own specialty, their cooperation can support complicated task with high efficiency. To improve the resources utilization, virtualization technology like container is used and it enables multiple services running in the same physical machine. However, since the host physical machine is shared by several services, the resource competition is inevitable. Isolation is an effective solution, but the weak isolation mechanisms of container cannot handle such complicated scenarios. In the worst situation, the performance of services cannot meet the requirements and the system may crash. In order to solve this problem, we propose a priority-based optimization mechanism for I/O isolation after analyzing the characteristics of typical service workloads. Based on the real-time performance data, priority is automatically assigned to each service and corresponding optimization methods are applied. We evaluate the optimization effects of the priority-based mechanism in both static and dynamic workload cases, besides, the influence of different priority order is also analyzed. The experimental results show that our approach can indeed improve the system performance and guarantee the requirements of all the running services are satisfied. © 2019, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Containers

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Effect of temporal disorder on wave packet dynamics in one-dimensional kicked lattices

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Chinese Physics B 2018年第12期27卷 85-91页

作者： Yuting Wang Yi Gao Peiqing Tong Center for Quantum Transport and Thermal Energy Science School of Physics and TechnologyNanjing Normal UniversityNanjing 210023China jiangsu Key Laboratory on Opto-Electronic Technology School of Physics and TechnologyNanjing Normal UniversityNanjing 210023China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal UniversityNanjing 210023China

Inspired by the recent experimental progress in noisy kicked rotor systems,we investigate the effect of temporal disorder or quasi-periodicity in one-dimensional kicked lattices with pulsed on-site *** found that,unlike the spatial disorder or quasi-periodicity which usually leads to localization,the effect of the temporal one is more complex and depends on the spatial *** the kicked on-site potential is periodic in real space,then the wave packet will stay diffusive in the presence of temporal disorder or *** the other hand,if the kicked on-site potential is spatially quasi-periodic,then the temporal disorder or quasi-periodicity may lead to a shift of the transition point of the dynamical localization and destroy the dynamical localization in a certain parameter *** results we obtained can be readily tested by experiments and may help us better understand the dynamical localization.

关键词： temporal disorder quasi-periodicity dynamical localization

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