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Research on optimization of repeater distribution based on cellular communication system

Tongxin Xuebao/Journal on Communications 2016年 37卷 72-77页

作者： Yan, Shao-Hong Wu, Yu-Hang Gong, Dian-Xuan Hebei Key Laboratory of Data Science and Applications Tangshan063009 China Tangshan Key Laboratory of Data Science Tangshan063009 China 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

First considering the signal in space link loss, in combination with lowest relay protection field intensity, power and the reasonable analysis and determination of parameters such as system allowance, a repeater Egli model was adopted to cover radius expression was drew. Secondly on the repeater distribution location, center incentive model of cellular communication system was improved to the center-vertex incentive model. The model area of coverage can be increased by 4%, the user coverage increased by 22%. The repeater distribution in communication system provides a good optimization. © 2016, Editorial Board of Journal on Communications. All right reserved.

关键词： Mobile telecommunication systems

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Robust latent poisson deconvolution from multiple imperfect features for web topic detection

Robust latent poisson deconvolution from multiple imperfect ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Fei Tao Junbiao Pang Chunjie Zhang Liang Li Li Su Weigang Zhang Qingming Huang Guiping Su School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China College of Metropolitan Transportation Beijing University of Technology China Key Lab on Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9781467372596

In web topic detection, detecting “hot” topics from enormous User-Generated Content (UGC) on web data poses two main difficulties that conventional approaches can barely handle: 1) poor feature representations from noisy images and short texts; and 2) uncertain roles of modalities where visual content is either highly or weakly relevant to textual cues due to less-constrained data. In this paper, following the detection by ranking approach, we address the problem by learning a robust shared representation from multiple, noisy and complementary features, and integrating both textual and visual graphs into a k-Nearest Neighbor Similarity Graph (k-N 2 SG). Then Non-negative Matrix Factorization using Random walk (NMFR) is introduced to generate topic candidates. An efficient fusion of multiple graphs is then done by a Latent Poisson Deconvolution (LPD) which consists of a poisson deconvolution with sparse basis similarities for each edge. Experiments show significantly improved accuracy of the proposed approach in comparison with the state-of-the-art methods on two public data sets.

关键词： Visualization Deconvolution Robustness Feature extraction Optimization Correlation Noise measurement

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A new model for nickname detection based on network structure and similarity propagation

A new model for nickname detection based on network structur...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Zhaoli Liu Tao Qin Dan Zhao Xiaohong Guan Tao Yang MoE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an Shaanxi China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Department of Automation Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781509006809

Users can participate in variety topics and express their opinions using different kinds of online applications, and the IDs (nickname) they used are usually virtual and difficult for finding the physical person. Which pose great challenges for network security management and user's online behavior supervision. Focus on this problem, we proposed methods for nickname detection based on the user's online connection structure and similarity propagation model. Firstly, we collected user's profile information from two popular online applications, sina microblog and RenRen network. Then we mark several matched pairs which belong to the same person from the applications with hardly manually effort, and those IDs are selected as seed set for nickname detection. Secondly, we proposed an nickname detection model based on the connection structure and similarity propagation. We selected one matched pairs from the seed set and obtain all their neighbors. Then we calculated the similarity of each pairs from the neighbor set and calculate their neighbors' connection similarity and neighbors' location similarity. If the similarity is bigger than a selected threshold, we claim they are matched pairs and insert them into the seed sets. On one hand, the correlation results can propagated based on the updated seed set. On the other hand, the computational complexity are greatly reduced as we only employ the neighbors' profiles to calculate the similarity. Experimental results verify the efficiency of the proposed method, which can lay a solid foundation for the online network management and user's behavior supervision.

关键词： Measurement

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A novel method for road centerline extraction from high spatial resolution satellite images

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Journal of Information Hiding and Multimedia Signal Processing 2016年第5期7卷 1069-1080页

作者： Xu, Rui Key Lab of Spatial Data Mining & 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 Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.3 Xueyuan Road University Town Fuzhou350108 China

An integrated method for road centerline extraction has been proposed in this paper which consists of four main steps. First, the Graph Cut algorithm using proposed similarity function is employed to segment the image, and the segmented image is thresholded to initial binary skeleton. Second, the road skeleton is refined by using a series of morphology operations and shape features. Third, the curvilinear feature of road skeleton is detected by a set of multiple filtering detectors. Finally,a regression method is performed to extract smooth and accurate road centerlines. Validation tests show that the proposed method is able to achieve a comparatively good performance in road centerline extraction from high spatial resolution satellite images. © 2016, Ubiquitous International. All Rights Reserved.

关键词： Regression analysis

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A hierarchical object-based method for suburban road extraction from remote sensing image

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ICIC Express Letters, Part B: Applications 2016年第12期7卷 2671-2676页

作者： Xu, Rui College of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Fuzhou350118 China 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

Road extraction from remote sensing image is a very popular topic. There are many methods dealing with this problem, but few of them focus on suburban roads. This paper presents a hierarchical object-based method for suburban road extraction. First, the image is preprocessed by the Normalized Difference Vegetation Index (NDVI) and the Hue-Saturation-Intensity (HSI) Index. Vegetation regions, shadows and water areas are then removed. Second, texture features are applied to classifying the preprocessed image into two categories: road and non-road. Homogeneous property is combined to remove false classification so as to generate initial road skeleton. Third, the road skeleton is refined by using a series of morphology operations and shape features. Fourth, the curvilinear feature of road skeleton is detected by a set of multiple filtering detectors. Finally, a regression method is performed to extract smooth and accurate road centerlines. The experimental results indicate that the proposed method is suitable for suburban road extraction. © 2016 ISSN 2185-2766.

关键词： Vegetation

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Constrained Energy Efficiency Optimization for Robotic Manipulators Using Neuro-dynamics Approach 34

Constrained Energy Efficiency Optimization for Robotic Manip...

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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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