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An Improved Algorithm Based on Landweber-Tikhonov Alternating Iteration for ECT Image Reconstruction

Journal of Physics: Conference Series 2018年第1期1069卷

作者： Chunman Yan Daoliang Zhang Genyuan Lu Junsong Dong College of Physics and Electronic Engineering Northwest Normal University Lanzhou 730070 China Engineering Research Center of Gansu Province for Intelligent Inforamtion Technology and Application Lanzhou 730070 China

Aiming at the problem of 'soft field' and ill state existing in image reconstruction proceeding of electrical capacitance tomography (ECT) system. An improved image reconstruction algorithm is proposed in this paper. For which, the pseudo-inverse matrix instead of transport matrix of sensitivity is directly used as the initial image value, and an alternate iteration procedure based on Landweber-Tikhonov algorithm is adopted to perform direct image reconstruction. Firstly, the Landweber algorithm is used to improve the initial value, and then the results are used as the inputs of Tikhonov regularization algorithm. The procedure is repeated alternately to search an ideal reconstructed image. This strategy can effectively solve the problem caused by the 'soft field' and ill-state problems which always grows out poor quality of the reconstructed image. To test the availability and the effectiveness of the proposed algorithm, it is used to the image reconstruction of ECT system. The correlation coefficient and relative error are used as evaluation criteria for image quality, and the representative algorithms (e.g., LBP, Tikhonov, and Landweber ) are selected for comparison. Simulation experiments show that our algorithm is with well performance both in terms of subjective imaging effect and objective criteria under the same iteration steps with the compared algorithms. Moreover, the convergence speed of the proposed algorithm outperforms the compared algorithms.

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Correction: Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction

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Journal of Materials Chemistry A 2019年第11期7卷 6572-6572页

作者： Wenping Liu Chiming Wang Lijie Zhang Houhe Pan Wenbo Liu Jun Chen Dongjiang Yang Yanjuan Xiang Kang Wang Jianzhuang Jiang Xiangdong Yao Beijing Key Laboratory for Science and Application of Functional Molecular and Crystalline Materials Department of Chemistry University of Science and Technology Beijing Beijing 100083 China Collaborative Innovation Center for Marine Biomass Fibers Materials and Textiles of Shandong Province College of Chemical and Environmental Engineering Qingdao University Qingdao 266071 China Intelligent Polymer Research Institute ARC Centre of Excellence for Electromaterials Science AIIM Facility University of Wollongong Innovation Campus Wollongong NSW 2522 Australia State Key Laboratory of Catalytic Material and Reaction Engineering Research Institute of Petroleum Processing SINOPEC Beijing 100083 China Queensland Micro- and Nanotechnology Centre Griffith University Nathan Campus QLD 4111 Australia

Correction for ‘Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction’ by Wenping Liu et al., J. Mater. Chem. A, 2019, 7, 3112–3119.

Correction for ‘Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction’ by Wenping Liu et al., J. Mater. Chem. A, 2019, 7, 3112–3119.

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Controllability of giant connected components in a directed network

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Physical Review E 2017年第4期95卷 042318-042318页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Center for Complex Network Research and Department of Physics Northeastern University Boston Massachusetts 02115 USA

When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=pm. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by pm〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

关键词： Network structure

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Search for heavy neutral resonances decaying to tau lepton pairs in proton-proton collisions at s=13 TeV

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Physical Review D 2025年第11期111卷 112004-112004页

作者： A. Hayrapetyan A. Tumasyan W. Adam J. W. Andrejkovic L. Benato T. Bergauer S. Chatterjee K. Damanakis M. Dragicevic P. S. Hussain M. Jeitler N. Krammer A. Li D. Liko I. Mikulec J. Schieck R. Schöfbeck D. Schwarz M. Sonawane W. Waltenberger C.-E. Wulz T. Janssen T. Van Laer P. Van Mechelen N. Breugelmans J. D’Hondt S. Dansana A. De Moor M. Delcourt F. Heyen S. Lowette I. Makarenko D. Müller S. Tavernier M. Tytgat G. P. Van Onsem S. Van Putte D. Vannerom B. Bilin B. Clerbaux A. K. Das I. De Bruyn G. De Lentdecker H. Evard L. Favart P. Gianneios J. Jaramillo A. Khalilzadeh F. A. Khan K. Lee M. Mahdavikhorrami A. Malara S. Paredes M. A. Shahzad L. Thomas M. Vanden Bemden C. Vander Velde P. Vanlaer M. De Coen D. Dobur G. Gokbulut Y. Hong J. Knolle L. Lambrecht D. Marckx K. Mota Amarilo K. Skovpen N. Van Den Bossche J. van der Linden L. Wezenbeek A. Benecke A. Bethani G. Bruno C. Caputo J. De Favereau De Jeneret C. Delaere I. S. Donertas A. Giammanco A. O. Guzel Sa. Jain V. Lemaitre J. Lidrych P. Mastrapasqua T. T. Tran G. A. Alves E. Coelho G. Correia Silva C. Hensel T. Menezes De Oliveira C. Mora Herrera P. Rebello Teles M. Soeiro A. Vilela Pereira W. L. Aldá Júnior M. Barroso Ferreira Filho H. Brandao Malbouisson W. Carvalho J. Chinellato E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza R. Gomes De Souza T. Laux Kuhn M. Macedo J. Martins L. Mundim H. Nogima J. P. Pinheiro A. Santoro A. Sznajder M. Thiel C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores I. Maietto Silverio P. G. Mercadante S. F. Novaes B. Orzari Sandra S. Padula A. Aleksandrov G. Antchev R. Hadjiiska P. Iaydjiev M. Misheva M. Shopova G. Sultanov A. Dimitrov L. Litov B. Pavlov P. Petkov A. Petrov E. Shumka S. Keshri D. Laroze S. Thakur T. Cheng T. Javaid L. Yuan Z. Hu Z. Liang J. Liu G. M. Chen H. S. Chen M. Chen F. Iemmi C. H. Jiang A. Kapoor H. Liao Z.-A. Liu R. Sharma J. N. Song J. Tao C. Wang J. Wang Z. Wang H. Zhang J. Zhao A. Agapitos Y. Ban A. Carvalho Antunes De Oliveira S. Deng B. Guo C. Jiang A. Yerevan Physics Institute Yerevan Armenia Also at Yerevan State University Yerevan Armenia. Institut für Hochenergiephysik Vienna Austria Indian Institute of Technology Madras Madras India Also at TU Wien Vienna Austria. Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Also at Ghent University Ghent Belgium. Université Libre de Bruxelles Bruxelles Belgium Korea University Seoul Korea Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Also at Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil. Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Also at Universidade Estadual de Campinas Campinas Brazil. Also at Federal University of Rio Grande do Sul Porto Alegre Brazil. Also at UFMS Nova Andradina Brazil. Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China Also at University of Chinese Academy of Sciences Beijing China. Also at China Center of Advanced Science and Technology Beijing China. University of Puerto Rico Mayaguez Puerto Rico USA California Institute of Technology Pasadena California USA University of Florida Gainesville Florida USA Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Deutsches Elektronen-Synchrotron Hamburg Germany Kyung Hee University Department of Physics Seoul Korea Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University

A search for heavy neutral gauge bosons (Z′) decaying into a pair of tau leptons is performed in proton-proton collisions at s=13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 fb−1. The observations are found to be in agreement with the expectation from standard model processes. Limits at 95% confidence level are set on the product of the Z′ production cross section and its branching fraction to tau lepton pairs for a range of Z′ boson masses. For a narrow resonance in the sequential standard model scenario, a Z′ boson with a mass below 3.5 TeV is excluded. This is the most stringent limit to date from this type of search.

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A model based method of pedestrian abnormal behavior detection in traffic scene 1

A model based method of pedestrian abnormal behavior detecti...

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1st IEEE International Smart Cities Conference, ISC2 2015

作者： Qianyin, Jiang Guoming, Li Jinwei, Yu Xiying, Li Research Center of Intelligent Transportation System School of Engineering Sun Yat-sen University Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Transportation System Guangzhou China Key Laboratory of Video and Image Intelligent Analysis and Application Technology of MPS Guangzhou China

ISBN: (纸本)9781467365529

In order to reduce traffic accidents caused by the pedestrian, five kinds of dangerous pedestrian abnormal behaviors are studied in the paper. A behavior model between the pedestrian trajectory and the road is built to describe the five kinds of dangerous pedestrian abnormal behaviors: crossing road border, illegal stay, crossing the road, moving along the curb, entering road area. The method contains pedestrian detection, shadow elimination, pedestrian recognition, pedestrian tracking and abnormal behavior detection. Background subtraction method is used to detect moving targets. After shadow elimination, pedestrians are distinguished from vehicles according to the ratio. Then, pedestrian trajectories are gotten by pedestrian tracking. Finally, based on the relation between trajectory and road, the model of five kinds of pedestrian abnormal behaviors is established, and abnormal behaviors are detected according this model. Experiments show that the method can distinguish and detect the pedestrian abnormal behaviors effectively in short time, and it is suitable to use in real time traffic monitoring. © 2015 IEEE.

关键词： Trajectories

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Corrigendum to “A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building”

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Journal of Sensors 2016年第1期2016卷

作者： Songmin Jia Ke Wang Xiuzhi Li Tao Xu College of Electronic and Control Engineering Beijing University of Technology Beijing 100124 *** Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 *** Engineering Research Center of Digital Community Ministry of Education Beijing 100124 *** School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang 453003 ***

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A new hybrid tracking strategy based on Pulse Coupled Neural Network

A new hybrid tracking strategy based on Pulse Coupled Neural...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Tao Xu Zhengyin Dong Xiuzhi Li Peng Zhang College of Electronic and Control Engineering Beijing University of Technology Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang China

ISBN: (纸本)9781467391054

Visual object tracking is a fundamental research topic in computer vision. In this paper, we proposed a novel hybrid tracking method based on Pulse Coupled Neural Network (PCNN) and Multiple Instance Learning (MIL). Most modern trackers may be inaccurate when the training samples are imprecise which causes drift. To resolve these problems, MIL method is introduced into the tracking task, which can alleviate drift to some extent. However, the MIL tracker may detect the positive sample that is less important. PCNN is different from traditional artificial neural networks, which can be applied in many image processing fields, such as image segmentation. So, the PCNN was employed as sample detector which can know the most important sample when training the classifier. Then, a more robust and much faster tracker is proposed to approximately maximize the bag likelihood function. Empirical results on a large set of sequences demonstrate the superior performance of the proposed approach in robustness, stability and efficiency to state-of-the-art methods in the literature.

关键词： Target tracking Neurons Visualization Object tracking Image segmentation Computer vision Computational modeling

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Authentication scheme between the vehicle alarm with remote control and mobile phone

Authentication scheme between the vehicle alarm with remote ...

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2nd International Conference on Innovation Manufacturing and engineering Management, IMEM 2012

作者： Niu, Quanying Zhang, Wenyi Shang, Mingzhe Intelligent Automotive Electronic Engineering Technology Research Center in College Universities of Henan Province Jiaozuo Henan China Engineering Research Center for vehicle-borne electronic anti-theft devices in Jiaozuo Jiaozuo Henan China College of Electrical Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9783037855881

The existing vehicle alarms with remote control are facing security challenges due to their own characteristics. Their security mechanism should take into account both the security and the system performance. Authentication is an elementary protocol in constructing a secure system. A new authentication scheme is proposed here, in which a remote control becomes effective after it is certified by the owner's mobile phone, and then its registration information is stored in the vehicle alarm. In addition, the mobile phone can make the remote control lose its effectiveness by sending signal to the alarm. The authentication scheme settles the problem of security which is caused by the remote control lost or stolen. © (2013) Trans Tech Publications, Switzerland.

关键词： Authentication

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High security design of 2.4GHz remote controller in car anti-theft

High security design of 2.4GHz remote controller in car anti...

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2nd International Conference on Innovation Manufacturing and engineering Management, IMEM 2012

作者： Zhang, Wenyi Niu, Quanying Shang, Mingzhe Engineering Research Center for vehicle-borne electronic anti-theft devices in Jiaozuo Jiaozuo Henan 454001 China Intelligent Automotive Electronic Engineering Technology Research Center in Colleges and Universities of Henan Province Jiaozuo Henan454000 China College of Electrical Engineering Dalian University of Technology Dalian 116024 China

ISBN: (纸本)9783037855881

The effectiveness of car anti-theft relies upon the security of signal from its remote control. However, the signal is easily captured and decrypted for common remote controller. In this paper, the dynamic encryption technology is adopted to enhance the security of signal transmission in the theft-against system. Two random numbers were invoked in the encryption technology. The data was double encrypted according to the two algorithms which were obtained by the two random numbers, respectively. So a same data corresponding to an instruction can be encrypted into a different data. The encrypted data were emitted by NRF24L01. The corresponding instruction was not implemented until the encrypted data were double decrypted by the alarm. The encryption technology can avoid the signal decrypted and coped by the special wireless equipment. © (2013) Trans Tech Publications, Switzerland.

关键词： Remote control

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