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Construction of the recognition model for trigger words of Chinese acupuncture and moxibustion events

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Journal of Information Hiding and Multimedia Signal Processing 2017年第6期8卷 1283-1293页

The recognization of trigger words for Chinese acupuncture and moxibustion events is a key step in the extraction of Chinese acupuncture and moxibustion events. It plays an important role in knowledge mining in the field of Chinese acupuncture and moxibustion. This paper extracts the manually annotated trigger words from the training corpus, constructs the table of trigger words for Chinese acupuncture and moxibustion events, then expands this table with the Tongyici Cilin (Chinese thesaurus), and identifies the candidate trigger words for Chinese acupuncture and moxibustion events based on the extended trigger word table;and then according to characteristics of the expressions in the field of Chinese acupuncture and moxibustion, this paper prepares the filtering rules for candidate trigger words for Chinese acupuncture and moxibustion events. This paper uses the above techniques to construct the recognition model of trigger words for Chinese acupuncture and moxibustion events that integrates dictionary matching and rule-based filtering. The results of the experiment show that this model has a good trigger word recognition function, and F-measure of trigger words recognition for the cure and health events reaches 88.28% and 34.15% respectively. © 2017, Ubiquitous International. All rights reserved.

关键词： Vocabulary control

Comments on a privacy preserving public auditing mechanism for shared cloud data 17

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Comments on a privacy preserving public auditing mechanism f...

4th Multidisciplinary International Social Networks Conference, MISNC 2017

作者： Wu, Tsu-Yang Lin, Yueshan Wang, King-Hang Chen, Chien-Ming Pan, Jeng-Shyang Wu, Mu-En Fujian Provincial Key Laboratory of Big Data Mining and Applications National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou350118 China Harbin Institute of Technology Shenzhen Graduate School Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Department of Mathematic Soochow University Taipei Taiwan

ISBN: (纸本)9781450348812

Auditing mechanisms are received much attentions from researchers due to the developing of cloud storage. Recently, Wang et al. proposed a privacy preserving public auditing mechanism for shared cloud data with supporting group dynamic. However, we find some security flaws in their mechanism. In this paper, a forgery attack and a data corruption attack are proposed to demonstrate the insecurity. Then, we propose a modified scheme based on their mechanism. The security analysis is demonstrated that our improvement can resist the mentioned two attacks. © 2017 ACM.

关键词： Cloud storage

Copacabana: A Probabilistic Membership Assignment Method for Galaxy Clusters

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arXiv 2024年

作者： Esteves, J.H. Pereira, M.E.S. Soares-Santos, M. Annis, J. Farahi, A. Andrade-Oliveira, F. Barchi, P. Palmese, A. Lin, H. Welch, B. Wu, H.-Y. Aguena, M. Alves, O. Bacon, D. Bocquet, S. Brooks, D. Rosell, A. Carnero Carretero, J. Costanzi, M. da Costa, L.N. De Vicente, J. Doel, P. Everett, S. Flaugher, B. Frieman, J. García-Bellido, J. Gruen, D. Gruendl, R.A. Gutierrez, G. Hinton, S.R. Hollowood, D.L. Honscheid, K. James, D.J. Kuehn, K. Lidman, C. Lima, M. Marshall, J.L. Mena-Fernández, J. Miquel, R. Myles, J. Ogando, R.L.C. Pieres, A. Malagón, A.A. Plazas Romer, A.K. Sanchez, E. Sanchez Cid, D. Santiago, B. Schubnell, M. Sevilla-Noarbe, I. Smith, M. Suchyta, E. Swanson, M.E.C. Weaverdyck, N. Wiseman, P. Yamamoto, M. Department of Physics University of Michigan Ann ArborMI48109 United States Hamburger Sternwarte Universität Hamburg Gojenbergsweg 112 Hamburg21029 Germany Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Departments of Statistics and Data Science University of Texas at Austin AustinTX78757 United States Department of Physics Carnegie Mellon University PittsburghPA15312 United States Observational Cosmology Lab NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Astronomy University of Maryland College Park20742 United States Department of Physics Boise State University BoiseID83725 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom University Observatory Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Instituto de Astrofisica de Canarias La Laguna Tenerife E-38205 Spain Universidad de La Laguna Dpto. Astrofísica La Laguna Tenerife E-38206 Spain The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Astronomy Unit Department of Physics University of Trieste via Tiepolo 11 TriesteI-34131 Italy INAF-Osservatorio Astronomico di Trieste via G. B. Tiepolo 11 TriesteI-34143 Italy Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy Madrid Spain Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Dr. PasadenaCA91109 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Instituto de Fisica Teorica UAM CSIC Universidad Autonoma de Madrid Madrid28049 Spain Center for Astrophysical Surveys National Center for S

Cosmological analyses using galaxy clusters in optical/NIR photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89% membership accuracy with a mild dependency on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (μ★) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation. These results indicate the potential of Copacabana and μ★ to be used in cosmological analyses of optically selected clusters in the future. © 2024, CC BY.

关键词： Galaxies

LEADER FORMATION WITH MEAN-FIELD BIRTH AND DEATH MODELS

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arXiv 2018年

作者： Albi, Giacomo Bongini, Mattia Rossi, Francesco Solombrino, Francesco Department of Computer Science University of Verona Str. Le Grazie 15 VeronaIT-37134 Italy Big Data and Marketing Analytics CRIF Via M. Fantin 3 BolognaIT-40131 Italy Department of Mathematics "Tullio Levi-Civita" University of Padova Via Trieste 63 PadovaIT-35121 Italy Department of Mathematics and Applications "R. Caccioppoli" University of Naples "Federico II" Via Cintia Monte S. Angelo NaplesIT-80126 Italy

We provide a mean-field description for a leader-follower dynamics with mass transfer among the two populations. This model allows the transition from followers to leaders and vice versa, with scalar-valued transition rates depending nonlinearly on the global state of the system at each time. We first prove the existence and uniqueness of solutions for the leader-follower dynamics, under suitable assumptions. We then establish, for an appropriate choice of the initial datum, the equivalence of the system with a PDE-ODE system, that consists of a continuity equation over the state space and an ODE for the transition from leader to follower or vice versa. We further introduce a stochastic process approximating the PDE, together with a jump process that models the switch between the two populations. Using a propagation of chaos argument, we show that the particle system generated by these two processes converges in probability to a solution of the PDE-ODE system. Finally, several numerical simulations of social interactions dynamics modeled by our system are *** Codes 35Q82, 35Q91, 70F45, 65M08, 82C22, 82B21 Copyright © 2018, The Authors. All rights reserved.

关键词： Markov processes

Dark Energy Survey Year 3 Results: Mis-centering calibration and X-ray-richness scaling relations in redMaPPer clusters

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arXiv 2023年

作者： Kelly, P. Jobel, J. Eiger, O. Abd, A. Jeltema, T.E. Giles, P. Hollowood, D.L. Wilkinson, R.D. Turner, D.J. Bhargava, S. Everett, S. Farahi, A. Romer, A.K. Rykoff, E.S. Wang, F. Bocquet, S. Cross, D. Faridjoo, R. Franco, J. Gardner, G. Kwiecien, M. Laubner, D. McDaniel, A. O’Donnell, J.H. Sanchez, L. Schmidt, E. Sripada, S. Swart, A. Upsdell, E. Webber, A. Aguena, M. Allam, S. Alves, O. Bacon, D. Brooks, D. Burke, D.L. Rosell, A. Carnero Carretero, J. Collins, C.A. Costanzi, M. da Costa, L.N. Pereira, M.E.S. Davis, T.M. Doel, P. Ferrero, I. Frieman, J. García-Bellido, J. Giannini, G. Gruen, D. Gruendl, R.A. Hilton, M. Hinton, S.R. Honscheid, K. James, D.J. Kuehn, K. Mann, R.G. Marshall, J.L. Mena-Fernández, J. Miller, C.J. Miquel, R. Myles, J. Palmese, A. Pieres, A. Malagón, A.A. Plazas Rooney, P.J. Sahlen, M. Sanchez, E. Cid, D. Sanchez Schubnell, M. Sevilla-Noarbe, I. Smith, M. Stott, J.P. Suchyta, E. Swanson, M.E.C. Tarle, G. To, C. Viana, P.T.P. Weaverdyck, N. Wiseman, P. University of California Santa Cruz Santa CruzCA95064 United States University of California Davis 1 Shields Ave DavisCA95616 United States Santa Cruz Institute for Particle Physics Santa CruzCA95064 United States SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo ParkCA94025 United States Swinburne University of Technology John St HawthornVIC3122 Australia Department of Physics and Astronomy Pevensey Building University of Sussex BrightonBN1 9QH United Kingdom 2 place Maurice-Quentin Paris France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Dr. PasadenaCA91109 United States Departments of Statistics and Data Science University of Texas at Austin AustinTX78757 United States Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Los Altos High School United States University of California Berkeley University Avenue and Oxford St BerkeleyCA94720 United States University Observatory Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Homestead High School United States De Anza College 21250 Stevens Creek Blvd CupertinoCA United States Department of Physics and Astronomy Clemson University Kinard Lab of Physics ClemsonSC29634-0978 United States California State University San Marcos 333 S Twin Oaks Valley Rd San MarcosCA92096 United States Dougherty Valley High School United States University of New Hampshire 105 Main St DurhamNH03824 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Department of Physics University of Michigan Ann ArborMI48109 United States Institute of Cosmology and G

We use Dark Energy Survey Year 3 (DES Y3) clusters with archival X-ray data from XMM-Newton and Chandra to assess the centering performance of the redMaPPer cluster finder and to measure key richness observable scaling relations. In terms of centering, we find that 10-20% of redMaPPer clusters are miscentered with no significant difference in bins of low versus high richness (20 40) or redshift (0.2 X-λ scatter of 0.21 ± 0.01. While the scatter in TX-λ is consistent in bins of redshift, we do find modestly different slopes with high-redshift clusters displaying a somewhat shallower relation. Splitting based on richness, we find a marginally larger scatter for our lowest richness bin, 20 © 2023, CC BY.

关键词： Galaxies

An Integrated Tone Mapping for High Dynamic Range Image Visualization

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An Integrated Tone Mapping for High Dynamic Range Image Visu...

作者： Lei Liang Jeng-Shyang Pan Yongjun Zhuang Department of Computer Science and Technology Shenzhen Graduate School Harbin Institute of Technology Qihan Research Qihan Technology Co. LTD Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Techology

There are two type tone mapping operators for high dynamic range(HDR) image visualization. HDR image mapped by perceptual operators have strong sense of reality, but will lose local details. Empirical operators can maximize local detail information of HDR image, but realism is not strong. A common tone mapping operator suitable for all applications is not available. This paper proposes a novel integrated tone mapping framework which can achieve conversion between empirical operators and perceptual operators. In this framework, the empirical operator is rendered based on improved saliency map, which simulates the visual attention mechanism of the human eye to the natural scene. The results of objective evaluation prove the effectiveness of the proposed solution.

关键词： image An Integrated Tone Mapping for High Dynamic Range Image Visualization HDR Mapping

Advances in Intelligent Systems and Computing

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Preface

Advances in Intelligent Systems and Computing 2018年 579卷 V页

作者： Lin, Jerry Chun-Wei Pan, Jeng-Shyang Chu, Shu-Chuan Chen, Chien-Ming School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School ShenzhenGuangdong China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian China School of Computer Science Engineering and Mathematics Flinders University Bedford Park SA Australia

A parallel evolutionary extreme learning machine scheme for electrical load prediction

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A parallel evolutionary extreme learning machine scheme for ...

science and Information Conference (SAI)

作者： Peikun Chen Wanhua Li Yuzhong Chen Kun Guo Yuzhen Niu College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou Fujian Collaborative Innovation Center for Big Data Applications in Governments Fuzhou Fuzhou China

ISBN: (纸本)9781509054442

Application of cloud computing technologies in power system has made a great contribution to the establishment of smart grid. Among applications of smart grid, electrical load prediction plays an important role in efficient use of power resource. However, the exponential growth of data has posed a great challenge to the existing algorithms. In this paper, we firstly propose a novel parallel hybrid algorithm, combining the Improved Particle Swarm Optimization (PSO) with ELM, named PIPSO-ELM. Here a modified particle swarm optimization is presented to find the optimal number of hidden neurons as well as the corresponding input weights and hidden biases. Furthermore, in the iterative search process of PSO, an update strategy employs the mutation operator of evolutionary algorithms is introduced for further improving the global search capability and convergence speed of PSO. After that, to handle the large-scale dataset efficiently, the parallel implementation of PIPSO-ELM is achieved using Spark. Finally, extensive experiments on real-life electrical load data and comprehensive evaluation are conducted to verify the performance of PIPSO-ELM in electrical load prediction. Extensive experimental results demonstrate that PIPSO-ELM outperforms the compared algorithms in terms of stability, efficiency and scalability simultaneously.

关键词： Neurons Particle swarm optimization Algorithm design and analysis Prediction algorithms Smart grids Encoding Convergence

The XMM Cluster Survey: Exploring scaling relations and completeness of the Dark Energy Survey Year 3 redMaPPer cluster catalogue

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arXiv 2023年

作者： Upsdell, E.W. Giles, P.A. Romer, A.K. Wilkinson, R. Turner, D.J. Hilton, M. Rykoff, E. Farahi, A. Bhargava, S. Jeltema, T. Klein, M. Bermeo, A. Collins, C.A. Ebrahimpour, L. Hollowood, D. Mann, R.G. Manolopoulou, M. Miller, C.J. Rooney, P.J. Sahlén, Martin Stott, J.P. Viana, P.T.P. Allam, S. Alves, O. Bacon, D. Bertin, E. Bocquet, S. Brooks, D. Burke, D.L. Kind, M. Carrasco Carretero, J. Costanzi, M. da Costa, L.N. Pereira, M.E.S. De Vicente, J. Desai, S. Diehl, H.T. Dietrich, J.P. Everett, S. Ferrero, I. Frieman, J. García-Bellido, J. Gerdes, D.W. Gutierrez, G. Hinton, S.R. Honscheid, K. James, D.J. Kuehn, K. Kuropatkin, N. Lima, M. Marshall, J.L. Mena-Fernández, J. Menanteau, F. Miquel, R. Mohr, J.J. Ogando, R.L.C. Pieres, A. Raveri, M. Rodriguez-Monroy, M. Sanchez, E. Scarpine, V. Sevilla-Noarbe, I. Smith, M. Suchyta, E. Swanson, M.E.C. Tarle, G. To, C. Weaverdyck, N. Weller, J. Wiseman, P. Department of Physics and Astronomy University of Sussex BrightonBN1 9QH United Kingdom Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 Stanford CA94305 United States Department of Statistics and Data Sciences The University of Texas at Austin AustinTX78712 United States AIM CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité Gif-sur-YvetteF-91191 France Santa Cruz Institute for Particle Physics University of California Santa Cruz 1156 High St Santa CruzCA95064 United States Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Astrophysics Research Institute Liverpool John Moores University Liverpool Science Park 146 Brownlow Hill LiverpoolL3 5RF United Kingdom Instituto de Astrofísica e Ciências do Espaço Universidade do Porto CAUP Rua das Estrelas Porto4150-762 Portugal Departamento de Física e Astronomia Faculdade de Ciências Universidade do Porto Rua do Campo Alegre 687 Porto4169-007 Portugal Institute for Astronomy University of Edinburgh Royal Observatory Blackford Hill EdinburghEH9 3HJ United Kingdom Astronomy Department University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy Uppsala University UppsalaSE-751 20 Sweden Department of Physics Lancaster University LancasterLA1 4YB United Kingdom Department of Physics University of Michigan Ann ArborMI48109 United States Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom Sorbonne Universités UPMC Univ Paris 06 UMR 7095 Institut d’Astrophysique de Paris ParisF-75014 France University Observatory Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich

We cross-match and compare characteristics of galaxy clusters identified in observations from two sky surveys using two completely different techniques. One sample is optically selected from the analysis of three years of Dark Energy Survey observations using the redMaPPer cluster detection algorithm. The second is X-ray selected from XMM observations analysed by the XMM Cluster Survey. The samples comprise a total area of 57.4 deg2, bounded by the area of 4 contiguous XMM survey regions that overlap the DES footprint. We find that the X-ray selected sample is fully matched with entries in the redMaPPer catalogue, above λ >20 and within 0.1X − TX), luminosity-richness (LX − λ) and temperature-richness (TX − λ) scaling relations. We find that the fitted forms of the LX − TX relations are consistent between the two selection methods and also with other studies in the literature. However, we find tentative evidence for a steepening of the slope of the relation for low richness systems in the X-ray selected sample. When considering the scaling of richness with X-ray properties, we again find consistency in the relations (i.e., LX − λ and TX − λ) between the optical and X-ray selected samples. This is contrary to previous similar works that find a significant increase in the scatter of the luminosity scaling relation for X-ray selected samples compared to optically selected samples. © 2023, CC BY.

关键词： Luminance