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第三十四届中国控制会议

作者： XU Peng WANG Liyang LI Zhijun SU Chun-Yi The Key Lab of Autonomous System and Network Control Ministry of Education and College of Automation Science and Engineering South China University of Technology Department of Electronic Engineering Shunde Polytechnic

ISBN: (纸本)9781467374439

In the paper, a neurodynamic-based energy efficiency optimization strategy(NEE-OS) is proposed to decrease the energy expenditure of robotic manipulators. Different from the traditional approaches, the proposed NEE-OS integrates several necessary constrains from the environment and the robotic manipulator, which could affect energy consumptions of the robotic manipulator in engineering applications to a large extent. To handle the constraints formulated as equalities and inequalities, the energy efficiency optimization problem is converted into a constrained quadratic programming(QP) problem, which is solved using a linear variable inequality-based primal-dual neural network(PDNN) efficiently.

关键词： robotic manipulator,energy optimization,quadratic programming,neural network

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The Middle of the Specified Node Set of Shortest Path Algorithm

The Middle of the Specified Node Set of Shortest Path Algori...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Jie Jia Jeng-Shyang Pan Hua-Rong Xu Innovative Information Industry Research Center Shenzhen Graduate SchoolHarbin Institute of Technology IIIRCHITSZ Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology Innovative Information Industry Research Center Shenzhen Graduate SchoolHarbin Institute of Technology Department of Computer Science and Technology Xiamen University of Technology CSTXMUT

the vast majority of researches about the shortest path algorithm, nowadays, focus just on the case starting from the beginning point and ending at the ending point. If additional condition that the shortest path must go through some given nodes of which number is uncertain must be met, then most of the existing classic algorithms are not applicable. A general method based on the Virus Co-Evolutionary Genetic algorithm and greedy algorithm is presented to solve this kind of problem. The time complexity of the algorithm is given by theoretical analysis and the effectiveness of the algorithm is verified by programming calculation. Furthermore, this algorithm in HUAWEI Code Craft 2016 makes 17 th score in preliminary to the semi-finals.

关键词： shortest path algorithm VEGA greedy algorithm path planning

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Passively Q-switching of Erbium-doped fiber laser using ferrite as saturable absorber 11

Passively Q-switching of Erbium-doped fiber laser using ferr...

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11th Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2015

作者： Bai, Xuekun Yuan, Jun Wang, Shaofei Fan, Dengfeng Gu, Jie Huang, Yi Zhao, Yunhe Zhang, Qianwu Pu, Shengli Zeng, Xianglong Key Lab of Specialty Fiber Optics and Optical Access Network Shanghai University Shanghai200072 China College of Science University of Shanghai for Science and Technology Shanghai200093 China

We report on passive Q-switching of a erbium-doped fiber laser with ferrite saturable absorber achieving for the first time short (∼3.2 μs) pulse durations with a low threshold pump power (∼15 mW). © 2015 IEEE.

ISBN: (纸本)9781467371094

关键词： Saturable absorbers

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Improved protein residue-residue contacts prediction using learning-to-rank

Improved protein residue-residue contacts prediction using l...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoyang Jing Qiwen Dong School of Computer Science Fudan University Shanghai People's Republic of China Shanghai Key Laboratory of Intelligent Information Processing Shanghai People's Republic of China Key Laboratory of Network Oriented Intelligent Computation Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong People's Republic of China Institute for Data Science and Engineering East China Normal University Shanghai People's Republic of China

ISBN: (纸本)9781509016129

Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.

关键词： Proteins Protein engineering Training Predictive models Feature extraction Classification algorithms Prediction algorithms

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Research on decision making of optimal communication system based on user

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Tongxin Xuebao/Journal on Communications 2016年 37卷 219-223页

作者： Wu, Yu-Hang Yan, Shao-Hong College of Science North China University of Science and Technology Tangshan063009 China Mathematical Modeling Innovation Lab North China University of Science and Technology Tangshan063009 China Hebei Key Laboratory of Data Science and Applications Tangshan063009 China

In order to study the problem of how to choose the wireless channel connection system to meet the needs of users in the wireless communication environment, according to the number of users using the Irish call loss, the estimated number of users need to meet the channel should be provided. Followed by the number of channels to establish the relation model between user requirements and system capacity, introducing comprehensive evaluation factors to evaluate FDMA, TDMA and CDMA communication system. Finally a solution was put forward to meet the optimal decision the needs of users. This scheme not only realizes the effective utilization of the channel, and the channel has certain redundancy, avoid the system reconstruction caused by future user growth, capital waste, provides a measure of win-win choice for different number of users of the communication system. © 2016, Editorial Board of Journal on Communications. All right reserved.

关键词： Time division multiple access

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International Symposium on Computational Intelligence and Design, ISCID

作者： Lijun Yang Chao Ding Meng Wu College of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China College of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Key Lab of “Broadband Wireless Communication and Sensor Network Technology” of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781509035595

The node replica attack is known to be dangerous to wireless sensor networks (WSNs) because it enables the adversary to extend the damage throughout the network with very low cost. To stop such attack, we propose a similarity estimation based scheme with group deployment knowledge. Compared with prior works, our proposal provides extra functionality that prevent replica from generating false location claims. Through simulation experiment, we evaluate the performance of the proposed scheme and demonstrate that our scheme achieves effectiveness and efficiency under different situations and attack strategies.

关键词： Wireless sensor networks Authentication Telecommunications Electronic mail Measurement Encoding

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A multistage method for road extraction from optical remotely sensed imagery

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Journal of Information Hiding and Multimedia Signal Processing 2016年第2期7卷 438-447页

作者： Xu, Rui Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Spatial Information Research Center of Fujian Province Fuzhou University No.523 Gongye Road Fuzhou350002 China College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Fuzhou350108 China

This paper presents a multistage framework for road extraction from remotely sensed imagery. The framework is a combination of multifeature-based mean shift, SVM classifier, and shape feature filter. Mean shift is first employed to cluster the remotely sensed images in the fusion of spectral-texture features and then a classifier of SVM is applied to classify the segmented images into two classes: the road class and the non-road class. Finally, the road class is refined by using road shape features. The experimental results show that this method is efficient in extracting road from remotely sensed imary. © 2016.

关键词： Classification (of information)

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Pathological brain detection based on online sequential extreme learning machine

Pathological brain detection based on online sequential extr...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Siyuan Lu Hainan Wang Xueyan Wu Shuihua Wang School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China State Key Lab of CAD & CG Zhejiang University Hangzhou Zhejiang China Key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin University Changchun Jilin China Key Laboratory of Statistical information technology and data mining State Statistics Bureau Chengdu Sichuan China Department of Electrical Engineering CUNY New York NY USA

ISBN: (纸本)9781509034857

Magnetic resonance imaging (MRI) is a kind of imaging modality, which offers clearer images of soft tissues than computed tomography (CT). It is especially suitable for brain disease detection. It is beneficial to detect diseases automatically and accurately. We proposed a pathological brain detection method based on brain MR images and online sequential extreme learning machine. First, seven wavelet entropies (WE) were extracted from each brain MR image to form the feature vector. Then, an online sequential extreme learning machine (OS-ELM) was trained to differentiate pathological brains from the healthy controls. The experiment results over 132 brain MRIs showed that the proposed approach achieved a sensitivity of 93.51%, a specificity of 92.22%, and an overall accuracy of 93.33%, which suggested that our method is effective.

关键词： Entropy Discrete wavelet transforms Feature extraction Pathology Training Magnetic resonance imaging Diseases

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An ISP-Friendly Hierarchical Overlay for P2P Live Streaming

An ISP-Friendly Hierarchical Overlay for P2P Live Streaming

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IEEE Global Communications Conference

作者： Mengjuan Liu Xiaoshuan Ma Xucheng Luo Fei Lu Zhiguang Qin Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China

ISBN: (纸本)9781479959532

Recent studies have demonstrated that overlay localization can reduce the inter-ISP traffic efficiently, however, fully localized overlays generally impair the streaming quality. In this paper, we first investigate the effects of overlay localization and then present a novel ISP-friendly hierarchical overlay, termed HOPES, to achieve a favorable tradeoff between the inter-ISP traffic and the streaming quality. In HOPES, there are four components: (1) an algorithm for determining the abstract interconnections of all ISP domains;(2) a super peer selection scheme;(3) an algorithm for constructing the inter-ISP connections between super peers;(4) an algorithm for constructing the intra-ISP connections within each same ISP domain. Simulation results indicate that under various scenarios a significant reduction in the inter-ISP traffic is achievable while the streaming quality is enhanced by shrinking the inter-ISP depth and latency of the delivery path of each chunk.

关键词： P2P streaming ISP-friendly Hierarchical overlay

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