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Ordinal Optimization for Optimal Orientation Problems in 3D Printing

IFAC-PapersOnLine 2020年第5期53卷 97-102页

作者： Can Luo Gang Xiong Zhishuai Li Zhen Shen Li Wan MengChu Zhou Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan China Ten Dimensions (Guangdong) Technology Co. Ltd. Foshan China Macau University of Science and Technology Taipa Macau

Compared with a traditional manufacturing process, 3D printing has advantages of performance and cost in personalized customization and has been applied in many fields. The problem of 3D model orientation optimization is a crucial one in practice. In this paper, based on the mathematical relationship between model orientation and printing time, surface quality, and supporting area, the model orientation problem is transformed into a multi-objective optimization problem with goal of minimizing printing time, surface quality, and supporting area. Ordinal Optimization (OO) is not only applicable to problems with random factors, but also to solve complex deterministic problems. The model orientation is a complex deterministic problem. We solve it with OO in this paper and use linear weighting to convert the multi-objective optimization problem into single-objective one. Finally, we compare the experimental results of solving 3D model orientation problems solved by OO and Genetic Algorithm (GA). The results show that OO requires less calculation time than GA while achieving comparable performance.

关键词： Digital Manufacturing Genetic Algorithm Intelligent Optimization Machine Learning Ordinal Optimization Orientation Optimization 3D Printing

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IVS O5: New developments and research trends for intelligent vehicles

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IEEE Intelligent systems 2005年第4期20卷 10-14页

作者： Wang, Fei-Yue Li, Li Song, Jingyan Niehsen, Wolfgang Zheng, Nan-Ning University of Arizona Chinese Academy of Science United States University of Arizona United States Tsinghua University China Chinese Academy of Sciences China Robert Bosch Corporate Research United States Xi'an Jiaotong University China Department of Automation Tsinghua University Beijing China University of Arizona's Systems Industrial Engineering Department United States University's Program in Advanced Research of Complex Systems United States Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences China Robert Bosch Corporate Research United States Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China

Recent advances and research trends for intelligent vehicles were studied. Vehicle-state sensing focuses on measuring a vehicle's movement and monitoring its actuators. Individual-vehicle-control research focuses mainly on guaranteeing driving safety. The results suggest that intervehicle, vehicle-roadside, and vehicle-driver information sharing currently the most attractive trend in intelligent-vehicle research.

关键词： Intelligent vehicle highway systems

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Superexponential diffusion in nonlinear non-Hermitian systems

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Physical Review A 2020年第6期102卷 062213-062213页

作者： Wen-Lei Zhao Longwen Zhou Jie Liu Peiqing Tong Kaiqian Huang School of Science Jiangxi University of Science and Technology Ganzhou 341000 China Department of Physics College of Information Science and Engineering Ocean University of China Qingdao 266100 China Graduate School of China Academy of Engineering Physics Beijing 100193 China CAPT HEDPS and IFSA Collaborative Innovation Center of the Ministry of Education Peking University Beijing 100871 China Department of Physics and Institute of Theoretical Physics Nanjing Normal University Nanjing 210023 China Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Nanjing Jiangsu 210023 China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials SPTE South China Normal University Guangzhou 510006 China

We investigate the quantum diffusion of a periodically kicked particle subjected to both nonlinearity-induced self-interactions and PT-symmetric potentials. We find that, due to the interplay between the nonlinearity and non-Hermiticity, the expectation value of the mean square of momentum scales with time in a superexponential form 〈p2(t)〉∝exp[βexp(αt)], which is faster than any known rates of quantum diffusion. In the PT-symmetry-breaking phase, the intensity of a state increases exponentially with time, leading to the exponential growth of the interaction strength. The feedback of the intensity-dependent nonlinearity further turns the interaction energy into the kinetic energy, resulting in a superexponential growth of the mean energy. These theoretical predictions are in good agreement with numerical simulations in a PT-symmetric nonlinear kicked particle. Our discovery establishes a mechanism of diffusion in interacting and dissipative quantum systems. Important implications and possible experimental observations are discussed.

关键词： Anderson localization Atomic, optical & lattice clocks Diffusion Nonlinear optics Quantum transport Spatiotemporal chaos Wave chaos

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Encapsulation of Co/Co3o4 Hetero-Nanoparticles within the Inner Tips of N-Doped Carbon Nanotubes: engineering Mott-Schottky Nanoreactors for Efficient Bifunctional Oxygen Electrocalysis Toward Flexible Zinc-Air Batteries

SSRN

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SSRN 2022年

作者： Zhang, Binbin Lu, Tingyu Ren, Yiping Huang, Longzhen Pang, Huan Zhao, Qun Tian, Shu Yang, Jun Xu, Lin Tang, Yawen Tian, Xinlong School of Chemistry and Materials Science Jiangsu Key Laboratory of New Power Batteries Jiangsu Collaborative Innovation Centre of Biomedical Functional Materials Nanjing Normal University Nanjing210023 China School of Chemistry and Chemical Engineering Yangzhou University Yangzhou225009 China College of Chemistry and Chemical Engineering Nantong University Nantong226019 China Nanjing IPE Institute of Green Manufacturing Industry Nanjing211100 China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine Chemistry School of Chemical Engineering and Technology Hainan University Haikou570228 China

We demonstrate a typical Mott-Schottky electrocatalyst by ingeniously encasing Co/Co3O4 hetero-nanoparticles within the inner tips of N-doped carbon nanotubes (abbreviated as Co/Co3O4@N-CNTs hereafter) through a facile and scalable hydrogel-bridged pyrolysis strategy. Experimental and theoretical findings collectively manifest that the spontaneous charge redistribution at the Co/Co3O4 heterointerfaces is essential to promote the charge transfer capability, lower down the reaction barriers for oxygen electrocatalysis, and ultimately boost the intrinsic activities. Accordingly, the well-designed Co/Co3O4@N-CNTs exhibit admirable ORR and OER activities and long-term robustness in KOH medium, exceeding the commercial Pt/C and RuO2 benchmarks, respectively. Furthermore, the Co/Co3O4@N-CNTs-assembled flexible all-solid-state zinc-air battery displays a high power density, remarkable rate capability, excellent rechargeablity and outstanding mechanical flexibility even under severe deformations, predicting the great potentials in diverse next-generation wearable electronic devices. The rationale of the construction of Mott-Schottky heterojunctions may provide an innovative and instructive avenue to design diversified energy nanomaterials. © 2022, The Authors. All rights reserved.

关键词： Doping (additives)

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OSN Rumor Control Model Based on Community Immunization

OSN Rumor Control Model Based on Community Immunization

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Ming Dong Zhiqiang Sun Zhenhua Tan Bin Zhang School of Computer Science and Engineering Northeastern University Shenyang China Software College Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

This paper proposes a rumor control model based on community immunization. Based on the community division and the trust network inference algorithm, the model redefines the standard to measure the importance of nodes in the network. First, the model uses the Louvain clustering algorithm based on the Ochiai coefficient to discover the network community and then presents the trust network inference algorithm. By analyzing the key factors that affect trust transfer between nodes, the trust evaluation between unfamiliar nodes is inferred, and important nodes with a high degree of trust in the network community are calculated. Finally, combined with the characteristics of inner degree and outer degree centrality of nodes in the network community, five types of important nodes in the network are screened out. To avoid repeated selection of nodes, this paper identifies a group of key nodes in the network community for local immunization by means of deduplication and taking intersection, so as to realize effective control of rumors in the network.

关键词： Distributed processing Clustering algorithms Inference algorithms Standards Open data

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A Test Suite and An Optimizer for Dietary Nutrition Optimization Problem: From Constrained Many-Objective Perspective

A Test Suite and An Optimizer for Dietary Nutrition Optimiza...

引用

Congress on Evolutionary Computation

作者： Yaqi Ti Changhe Li Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space.

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Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images

arXiv

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arXiv 2019年

作者： Zhang, Dong-dong Zhang, Lei Zaborovsky, Vladimir Xie, Feng Wu, Yan-wen Lu, Ting-ting Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China MOE International Joint Lab of Trustworthy Software East China Normal University Shanghai China Department of Computer Systems and Software Engineering Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Institute of Technical Physics Chinese Academy of Sciences Shanghai China

During the rapid urbanization construction of China, acquisition of urban geographic information and timely data updating are important and fundamental tasks for the refined management of cities. With the development of domestic remote sensing technology, the application of Gaofen-2 (GF-2) high-resolution remote sensing images can greatly improve the accuracy of information extraction. This paper introduces an approach using object-oriented classification methods for urban feature extraction based on GF-2 satellite data. A combination of spectral, spatial attributes and membership functions was employed for mapping the urban features of Qinhuai District, Nanjing. The data preprocessing is carried out by ENVI software, and the subsequent data is exported into the eCognition software for object-oriented classification and extraction of urban feature information. Finally, the obtained raster image classification results are vectorized using the ARCGIS software, and the vector graphics are stored in the library, which can be used for further analysis and modeling. Accuracy assessment was performed using ground truth data acquired by visual interpretation and from other reliable secondary data sources. Compared with the result of pixel-based supervised (neural net) classification, the developed object-oriented method can significantly improve extraction accuracy, and after manual interpretation, an overall accuracy of 95.44% can be achieved, with a Kappa coefficient of 0.9405, which objectively confirmed the superiority of the object-oriented method and the feasibility of the utilization of GF-2 satellite data. Copyright © 2019, The Authors. All rights reserved.

关键词： Image classification

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Indirect influence in social networks as an induced percolation phenomenon (vol 119, e2100151119, 2022)

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2022年第24期119卷 e2100151119-e2100151119页

作者： Xie, Jiarong Wang, Xiangrong Feng, Ling Zhao, Jin-Hua Liu, Wenyuan Moreno, Yamir Hu, Yanqing School of Computer Science and Engineering Sun Yat-sen University 510006 Guangzhou China Institute of Future Networks Southern University of Science and Technology 518055 Shenzhen China Peng Cheng Laboratory 518066 Shenzhen China Institute of High Performance Computing A*STAR 138632 Singapore Department of Physics National University of Singapore 117551 Singapore Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University 510006 Guangzhou China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University 510006 Guangzhou China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Institute for Biocomputation and Physics of Complex Systems University of Zaragoza 50018 Zaragoza Spain Department of Theoretical Physics University of Zaragoza 50018 Zaragoza Spain ISI Foundation 10126 Torino Italy Department of Statistics and Data Science College of Science Southern University of Science and Technology 518055 Shenzhen China

Percolation theory has been widely used to study phase transitions in network systems. It has also successfully explained various macroscopic spreading phenomena across different fields. Yet, the theoretical frameworks have been focusing on direct interactions among nodes, while recent empirical observations have shown that indirect interactions are common in many network systems like social and ecological networks, among others. By investigating the detailed mechanism of both direct and indirect influence on scientific collaboration networks, here we show that indirect influence can play the dominant role in behavioral influence. To address the lack of theoretical understanding of such indirect influence on the macroscopic behavior of the system, we propose a percolation mechanism of indirect interactions called induced percolation. Surprisingly, our model exhibits a unique anisotropy property. Specifically, directed networks show first-order abrupt transitions as opposed to the second-order continuous transition in the same network structure but with undirected links. A mix of directed and undirected links leads to rich hybrid phase transitions. Furthermore, a unique feature of the nonmonotonic pattern is observed in network connectivities near the critical point. We also present an analytical framework to characterize the proposed induced percolation, paving the way to further understanding network dynamics with indirect interactions.

关键词： percolation indirect interactions social network phase transition behavioral contagion

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Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot

Structure-Constrained Obstacles Recognition for Power Transm...

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2006 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Siyao Fu Weiming Li Yunchu Zhang Zize Liang Zengguang Hou Min Tan Wenbo Ye Bo Lian Qi Zuo Key laboratory of complex systems and intelligence science Institute of Automation Chinese Academy and Sciences Beijing China National laboratory of pattern recognition Institute of Automation Chinese Academy and Sciences Beijing China Faculty of Information and Electrical Engineering Shandong University of Architecture and Engineering Jinan China Zunyi Power Supply Bureau Guizhou Power Grid Corporation Zunyi China Department of Automation North-China University of Technology Beijing China

Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the power transmission line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV power transmission line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the power transmission line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real power transmission line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles

关键词： Power transmission lines Inspection Mobile robots Robotics and automation Sensor arrays Robot sensing systems Intelligent robots Insulation Power system reliability Laboratories

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Connecting Disconnected Agents in Multiagent systems via Federated Control

Connecting Disconnected Agents in Multiagent Systems via Fed...

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European Control Conference (ECC)

作者： Rongrong Qian Zhisheng Duan Yuan Qi Tao Peng Wenbo Wang School of Artificial Intelligence Beijing University of Posts and Telecommunications (BUPT) Beijing China State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing China School of Electronic Engineering Beijing University of Posts and Telecommunications (BUPT) Beijing China Wireless Signal Processing and Network Lab (Key Lab. of Universal Wireless Communication Ministry of Education) Beijing University of Posts and Telecommunications (BUPT) Beijing China

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This study develops a control technique, called federated control, to connect disconnected agents in multiagent systems aided by control stations. Specifically, we first use a federated architecture to model multiagent systems with control stations. Based on this architecture, a federated-control procedure is proposed for the task of connecting disconnected agents, together with an initialization procedure. Then, how the federated-control procedure connects disconnected agents by incorporating simple global coordination (i.e., global averaging) is analyzed. We derive the close-form expression of the time sufficient to connect disconnected agents, which possesses interesting properties including early computability and delay independence. The convergence of the formation of multiagent systems and the velocities of all agents can also be proved.

关键词： Robot kinematics Oceans Computer architecture Control systems Space-air-ground integrated networks Path planning Delays

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