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World Congress on Intelligent control and Automation (WCICA)

作者： Yunze Cai Hengyu Duan Hua O. Wang Weidong Zhang Department of Automation Key Laboratory of System Control and Information Processing Shanghai China Department of Mechanical Engineering Boston University Boston MA USA

ISBN: (纸本)9781467384155

In state estimation (filtering) applications, state vector of a target always includes some a priori constraints, and utilizing such constraints will help obtain a more precise estimation. While in some cases, a significant issue lies in that when such constraints are not perfect, how we exploit them and improve the performance of estimation. information contains “imperfection” sometimes because our knowledge of the real world is not absolutely right. This essay proposes a deep research on multi-agent systems with imperfect constraints and highly artificial intelligence: firstly, by using the projection method, results of traditional Kalman Filtering are projected onto the constrain subspace; secondly, based on consensus, this essay has thoroughly introduced the local information exchange and fusion strategy; and thirdly, simulations on target tracking have proved the feasibility and precision of the algorithms mentioned within this essay.

关键词： Decision support systems Intelligent control Automation Next generation networking DVD

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Fixed-lag Linear Unbiased Smoother for Networked control systems with Randomly Multi-Step Sensor Delays

Fixed-lag Linear Unbiased Smoother for Networked Control Sys...

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第35届中国控制会议

作者： Hai Lin Jingcheng Wang Qi Xia Bohui Wang Xiaocheng Li Hongyuan Wang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Department of Processing Business Shanghai Institute of Laser Technology

ISBN: (纸本)9781509009107

This paper concerns with the fixed-lag linear unbiased smoothing problem for a new networked control system with randomly multi-step sensor *** develop a unified model to describe the mixed uncertainties of no sensor delays and multistep sensor delays by multiple random *** a result,there will be a matrix contained multiple random variables in the computational process when we use the traditional method of state augmentation to deal with the unified *** method of mathematical induction is proposed in this paper,and the fixed-lag linear unbiased smoother that only depend on probabilities is developed successfully via this new ***,including comparison to the existing approach for randomly multi-step sensor delays,are provided to show the advantage of the proposed fixed-lag linear unbiased smoother.

关键词： Networked control system Sensor delay Fixed-lag linear unbiased smoother

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Secrecy Energy Efficiency Performance of UAV-Enabled Communication Networks

arXiv

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arXiv 2017年

作者： Qi, Xiaohui Li, Bin Chu, Zheng Fei, Zesong Huang, Kaizhi Chen, Hongbin National Digital Switching System Engineering & Technological Research Center Zhengzhou450002 China School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of Science and Technology Middlesex University LondonNW4 4BT United Kingdom Key Laboratory of Cognitive Radio and Information Processing Guilin University of Electronic Technology Guilin541004 China

This paper proposes a tractable analysis framework to evaluate the reliability, security and secrecy energy efficiency (SEE) performance in a UAV-enabled communication network via a threshold-based access scheme and multi-antenna technique. Specifically, the UAV-enabled transmitters, legitimate receivers and eavesdroppers are deployed randomly. To achieve reliable results for general communication scenarios, this paper assumes both line-of-sight and non-line-of-sight paths with Rayleigh fading for air-to-ground channel model. In particular, we first exploit the association probability of a randomly located receiver and the activation probability of UAV-enabled transmitters. Then, we analyze the security, reliability, and SEE of the UAV-enabled networks. Simulation results are finally provided to show the effect of the predetermined access threshold, the transmitter’s resource block, the height of UAVs, the density of legitimate receivers, and the density of eavesdroppers on the reliability as well as security performance, and determine the optimal design parameters for a given UAV-enabled network to maximize the SEE. Copyright © 2017, The Authors. All rights reserved.

关键词： Energy efficiency

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Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

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Archives of virology 2021年第12期166卷 3567-3579页

作者： Jens H Kuhn Scott Adkins Bernard R Agwanda Rim Al Kubrusli Sergey V Alkhovsky Gaya K Amarasinghe Tatjana Avšič-Županc María A Ayllón Justin Bahl Anne Balkema-Buschmann Matthew J Ballinger Christopher F Basler Sina Bavari Martin Beer Nicolas Bejerman Andrew J Bennett Dennis A Bente Éric Bergeron Brian H Bird Carol D Blair Kim R Blasdell Dag-Ragnar Blystad Jamie Bojko Wayne B Borth Steven Bradfute Rachel Breyta Thomas Briese Paul A Brown Judith K Brown Ursula J Buchholz Michael J Buchmeier Alexander Bukreyev Felicity Burt Carmen Büttner Charles H Calisher Mengji Cao Inmaculada Casas Kartik Chandran Rémi N Charrel Qi Cheng Yuya Chiaki Marco Chiapello Il-Ryong Choi Marina Ciuffo J Christopher S Clegg Ian Crozier Elena Dal Bó Juan Carlos de la Torre Xavier de Lamballerie Rik L de Swart Humberto Debat Nolwenn M Dheilly Emiliano Di Cicco Nicholas Di Paola Francesco Di Serio Ralf G Dietzgen Michele Digiaro Olga Dolnik Michael A Drebot J Felix Drexler William G Dundon W Paul Duprex Ralf Dürrwald John M Dye Andrew J Easton Hideki Ebihara Toufic Elbeaino Koray Ergünay Hugh W Ferguson Anthony R Fooks Marco Forgia Pierre B H Formenty Jana Fránová Juliana Freitas-Astúa Jingjing Fu Stephanie Fürl Selma Gago-Zachert George Fú Gāo María Laura García Adolfo García-Sastre Aura R Garrison Thomas Gaskin Jean-Paul J Gonzalez Anthony Griffiths Tony L Goldberg Martin H Groschup Stephan Günther Roy A Hall John Hammond Tong Han Jussi Hepojoki Roger Hewson Jiang Hong Ni Hong Seiji Hongo Masayuki Horie John S Hu Tao Hu Holly R Hughes Florian Hüttner Timothy H Hyndman M Ilyas Risto Jalkanen Dàohóng Jiāng Gilda B Jonson Sandra Junglen Fujio Kadono Karia H Kaukinen Michael Kawate Boris Klempa Jonas Klingström Gary Kobinger Igor Koloniuk Hideki Kondō Eugene V Koonin Mart Krupovic Kenji Kubota Gael Kurath Lies Laenen Amy J Lambert Stanley L Langevin Benhur Lee Elliot J Lefkowitz Eric M Leroy Shaorong Li Longhui Li Jiànróng Lǐ Huazhen Liu Igor S Lukashevich Piet Maes William Marciel de Souza Marco Marklewitz Sergio H Marshall Shin-Yi L Marzano Se Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Frederick MD USA. kuhnjens@mail.nih.gov. United States Department of Agriculture Agricultural Research Service US Horticultural Research Laboratory Fort Pierce FL USA. Zoology Department National Museums of Kenya Nairobi Kenya. Jomo Kenyatta University of Agriculture & Technology Nairobi Kenya. Division Phytomedicine Faculty of Life Sciences Humboldt-Universität zu Berlin Berlin Germany. D.I. Ivanovsky Institute of Virology of N.F. Gamaleya National Center on Epidemiology and Microbiology of Ministry of Health of Russian Federation Moscow Russia. Department of Pathology and Immunology Washington University School of Medicine St. Louis MO USA. Faculty of Medicine University of Ljubljana Ljubljana Slovenia. Centro de Biotecnología y Genómica de Plantas Universidad Politécnica de Madrid-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Campus de Montegancedo Pozuelo de Alarcón Madrid Spain. Departamento de Biotecnología-Biología Vegetal Escuela Técnica Superior de Ingeniería Agronómica Alimentaria y de Biosistemas Universidad Politécnica de Madrid Madrid Spain. Center for Ecology of Infectious Diseases Department of Infectious Diseases Department of Epidemiology and Biostatistics Insitute of Bioinformatics University of Georgia Athens GA USA. Institute of Novel and Emerging Infectious Diseases Friedrich-Loeffler-Institut Federal Research Institute for Animal Health Greifswald-Insel Riems Germany. Department of Biological Sciences Mississippi State University Mississippi State MS USA. Center for Microbial Pathogenesis Institute for Biomedical Sciences Georgia State University Atlanta GA USA. Edge BioInnovation Consulting and Mgt Frederick MD USA. Institute of Diagnostic Virology Friedrich-Loeffler-Institut Greifswald-Insel Riems Germany. UFyMA INTA-CONICET Cordoba Argentina. Genomics and Bioinformatics D

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Design and Analysis of Secure Routing Protocol for Wireless Sensor Networks

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IOP Conference Series: Materials Science and Engineering 2017年第1期242卷

作者： Jiong Wang Hua Zhang Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(MinJiang University) Fuzhou 350121 China

In recent years, with the development of science and technology and the progress of the times, China's wireless network technology has become increasingly prosperous and it plays an important role in social production and life. In this context, in order to further to enhance the stability of wireless network data transmission and security enhancements, the staff need to focus on routing security and carry out related work. Based on this, this paper analyzes the design of wireless sensor based on secure routing protocol.

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Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

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International Journal of Automation and computing 2015年第1期12卷 77-82页

作者： Kai Ma Liang Li Jie Yang Zhi-Xin Liu Xin-Bin Li Xin-Ping Guan School of Electrical Engineering Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education

Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution(NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.

关键词： Femtocell cluster inter-femtocell interference bandwidth allocation Nash bargaining solution(NBS)

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Transform-invariant convolutional neural networks for image classification and search 24

Transform-invariant convolutional neural networks for image ...

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24th ACM Multimedia Conference, MM 2016

作者： Shen, Xu Tian, Xinmei He, Anfeng Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

ISBN: (纸本)9781450336031

Convolutional neural networks (CNNs) have achieved stateof-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of images. Intuitively, with sufficient layers and parameters, hierarchical combinations of convolution (matrix multiplication and nonlinear activation) and pooling operations should be able to learn a robust mapping from transformed input images to transform-invariant representations. In this paper, we propose randomly transforming (rotation, scale, and translation) feature maps of CNNs during the training stage. This prevents complex dependencies of specific rotation, scale, and translation levels of training images in CNN models. Rather, each convolutional kernel learns to detect a feature that is generally helpful for producing the transforminvariant answer given the combinatorially large variety of transform levels of its input feature maps. In this way, we do not require any extra training supervision or modification to the optimization process and training images. We show that random transformation provides significant improvements of CNNs on many benchmark tasks, including small-scale image recognition, large-scale image recognition, and image retrieval. © 2016 ACM.

关键词： Mathematical transformations

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Nucleic acid secondary structures prediction with planar Pseudoknots using genetic algorithm 11th

Nucleic acid secondary structures prediction with planar Pse...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Kai, Zhang Shangyi, Li Juanjuan, He Yunyun, Niu School of Computer Science Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430081 China School of Information Engineering China University of Geosciences Beijing100083 China

ISBN: (纸本)9789811036132

Nucleic acid nanotechnology offers many methods to fold into a variety of complex and functional nanostructures. These selfassemble scaffolds are valuable in various applications, such as molecular programming, sensing, drug delivery and nanofabrication. However, existing algorithms are typically lacking on predicting pseudoknots structure fast and accurately. This paper proposes a novel genetic algorithm to predict nucleic acid secondary structure including pseudoknots. The length of continues base pairs stacking and free energy are considered to evaluate individuals. Furthermore, the performance of our algorithm is compared with RNAStructure using PseudoBase benchmark instances, and the results show that our algorithm outperforms on accuracy and efficiency. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Nucleic acids

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Applying K-means clustering and genetic algorithm for solving MTSP 11th

Applying K-means clustering and genetic algorithm for solvin...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Lu, Zhanqing Zhang, Kai He, Juanjuan Niu, Yunyun School of Computer Science Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430081 China School of Information Engineering China University of Geosciences Beijing100083 China

ISBN: (纸本)9789811036132

In this paper, a new algorithm is designed to solve Multiple Traveling Salesman Problem (MTSP) that avoiding the path intersection among the traveling salesmen. There are three objectives in this problem including the shortest path of every salesman, the balance of each salesmans task and avoiding the crosses of each routes. We combine the K-means algorithm and genetic algorithm. K-means algorithm is designed to divide all points into several subsets and choose the start city for the genetic algorithm, and then using GA to process every subsets in parallel. This method not only achieve these multiple objectives, but also use much less time, since we have divided all the points into several parts and make them calculated at the same time. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Genetic algorithms

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