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43rd International Conference on Very Large data Bases, VLDB 2017

作者： Chen, Lu Gao, Yunjun Zheng, Baihua Jensen, Christian S. Yang, Hanyu Yang, Keyu College of Computer Science Zhejiang University Hangzhou China The Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou China School of Information Systems Singapore Management University Singapore Department of Computer Science Aalborg University Denmark

The general notion of a metric space encompasses a diverse range of data types and accompanying similarity measures. Hence, metric search plays an important role in a wide range of settings, including multimedia retrieval, data mining, and data integration. With the aim of accelerating metric search, a collection of pivotbased indexing techniques for metric data has been proposed, which reduces the number of potentially expensive similarity comparisons by exploiting the triangle inequality for pruning and validation. However, no comprehensive empirical study of those techniques exists. Existing studies each offers only a narrower coverage, and they use different pivot selection strategies that affect performance substantially and thus render cross-study comparisons difficult or impossible. We offer a survey of existing pivot-based indexing techniques, and report a comprehensive empirical comparison of their construction costs, update efficiency, storage sizes, and similarity search performance. As part of the study, we provide modifications for two existing indexing techniques to make them more competitive. The findings and insights obtained from the study reveal different strengths and weaknesses of different indexing techniques, and offer guidance on selecting an appropriate indexing technique for a given setting. © 2017 VLDB Endowment.

关键词： data integration

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A new feature-based self-embedding image watermarking scheme

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Journal of Physics: Conference Series 2019年第4期1168卷

作者： Yang Liu Zhikun Chen Haocui Liang Shaoyuan Fu School of Computer Science China University of Geosciences Wuhan 430074 China Beibu Gulf Big Data Resources Utilisation Lab Qinzhou University Qinzhou 535000 China Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation Qinzhou 535000 China

The performance of digital watermarking algorithm is mainly manifested in invisibility and robustness. At present, many algorithms improve these two aspects by sacrificing embedding capacity for the reason that if watermark embedding amount is small, the watermark has little influence on the visuality of the cover image, and its robustness is also higher. Therefore, how to improve the anti-attack performance of the algorithm without reducing the amount of embedding has become a major research direction. This paper proposed a new robust watermarking scheme based on feature extraction techniques. Firstly, the SIFT (scale invariant feature transform) algorithm is used to extract the stable feature points from cover image to form embedding region. Then watermark is composed of the cover's texture features obtained by LBP (local binary pattern) extracting method. Finally, embedding region is transformed by singular value decomposition (SVD) and the watermark is embedded into its singular value vector. The simulation results showed that the watermark embedding capacity of this algorithm is relatively high, and it has good resistance to common image processing and geometric transformation.

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Extraction of Interactions of Genes2Genes Related to Breast Cancer

Extraction of Interactions of Genes2Genes Related to Breast ...

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International Conference on Software Engineering Research, Management and Applications (SERA)

作者： Lejun Gong Daoyu Huang Shixing Sun Zhihong Gao Chuandi Pan Ronggen Yang Yongmin Li Geng Yang Jiangsu Key Lab of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Zhejiang Engineering Research Center of Intelligent Medicine The First Affiliated Hospital of Wenzhou Medical University Wenzhou China College of Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing China

ISBN: (纸本)9781538658871

Breast cancer is the most prevalent disease to females in the worldwide. Its pathology remains unclear. Genetics factors is the ways to understand the molecular mechanism. This paper proposed a computational approach to explore the interactions of genes2genes related to breast cancer. We first defined the interactions of genes2genes, and described the representation of interactions of genes2genes. Using the experimental dataset, we implemented the proposed approach for extracting the interactions of genes2genes. Moreover, we also represented the interactions of genes2genes in two forms: relationship matrix and network visualization. By manual analysis, we extracted the interactions of top 10 genes2genes is related to breast cancer, which show the approach is promising for studying molecular mechanism related to breast cancer.

关键词： Breast cancer Pipelines data mining Manuals Genetics

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Emergency Events Classification Based on Minsheng Hotline Unbalanced Short-Text

Emergency Events Classification Based on Minsheng Hotline Un...

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IEEE International Conference on big Knowledge (ICBK)

作者： Li-Yuan Geng Wei Jin Han-Bing Qu Research Center for Big Data Beijing Institute of New Technology Applications Beijing China Key Lab. of Artificial Intell. & Big Data Anal. Beijing Academy of Science and Technology Beijing CN

ISBN: (纸本)9781538631218

In this work, a combined strategy is proposed to solve the unbalance problem in the classification of the short-text data sets. The improved K-means sampling method and category guide words are used to improve the classification accuracy of unbalanced data, and then VSM(vector space method) is used to express text. Finally, Naive Bayesian classifiers are used to classify the unbalanced short-text. Experiments show that this method is effective and feasible in the classification of small class events in unbalanced short-text data. The method can improve the small class classification accuracy and provide the decision basis for the government to respond quickly and precisely to emergencies.

关键词： Training Classification algorithms Feature extraction Government Text categorization Clustering algorithms Vocabulary

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An automatic biomedical ontology meta-matching technique

Journal of Network Intelligence

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Journal of Network Intelligence 2019年第3期4卷 109-113页

作者： Xue, Xingsi Yang, Haiyan Zhang, Jie Zhang, Jing Chen, Dongxu College of Information Science and Engineering Intelligent Information Processing Research Center Fujian Key Lab for Automotive Electronics and Electric Drive Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province350118 China College of Information Science and Engineering Fujian University of Technology No.33 Xuefu South Road University Town Minhou Fuzhou CityFujian Province350118 China School of Computer Science and Engineering Yulin Normal University No.299 Education Middle Road Yulin CityGuanxi Province537000 China School of Computing Ulster University Jordanstown BT370QB United Kingdom Fujian Medical University Union Hospital No.29 Xinquan Road Gulou Fuzhou CityFujian Province350001 China

Biomedical ontology matching aims at determining the heterogeneous biomed-ical concepts, and bridging the semantic gap between heterogeneous biomedical ontologies. The foundation of a biomedical ontology matching technique is the Biomedical Concept Similarity Measure (BCSM), which calculates the similarity value between two biomed-ical concepts. Since various BCSMs have different advantages, usually several BCSMs are aggregated together to improve the result’s confidence. How to tune the aggregating weights to ensure the quality of the alignment is called biomedical ontology meta-matching problem, which is a challenge in the ontology matching domain. Currently, researchers mainly focus on how to tune the aggregating weights for various similarity measures to improve the quality of the ontology alignments. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on different similarity measures significantly reduces the alignment’s quality. To overcome this drawback, in this work, we formally define the biomedical ontology meta-matching problem, and then present an Ordered Weighted Average (OWA) based approach to automatically aggregate various biomedical concept similarity measures. In our method, the aggregating weights determined for each concept mapping is associated with the ordered position of the similarity value instead of a particular concept similarity measure. The experiment utilizes the large biomed track provided by Ontology Alignment Evaluation Initiative (OAEI) to test our proposal’s performance, and the experimental results show the effectiveness of our proposal. © 2019, Taiwan Ubiquitous Information. All rights reserved.

关键词： Semantics

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Gaia data Release 3: Apsis. III. Non-stellar content and source classification

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Astronomy and Astrophysics 2023年 674卷

作者： Delchambre, L. Bailer-Jones, C.A.L. Bellas-Velidis, I. Drimmel, R. Garabato, D. Carballo, R. Hatzidimitriou, D. Marshall, D.J. Andrae, R. Dafonte, C. Livanou, E. Fouesneau, M. Licata, E.L. Lindstrøm, H.E.P. Manteiga, M. Robin, C. Silvelo, A. Abreu Aramburu, A. Álvarez, M.A. Bakker, J. Bijaoui, A. Brouillet, N. Brugaletta, E. Burlacu, A. Casamiquela, L. Chaoul, L. Chiavassa, A. Contursi, G. Cooper, W.J. Creevey, O.L. Dapergolas, A. De Laverny, P. Demouchy, C. Dharmawardena, T.E. Edvardsson, B. Frémat, Y. García-Lario, P. García-Torres, M. Gavel, A. Gomez, A. González-Santamaría, I. Heiter, U. Jean-Antoine Piccolo, A. Kontizas, M. Kordopatis, G. Korn, A.J. Lanzafame, A.C. Lebreton, Y. Lobel, A. Lorca, A. Magdaleno Romeo, A. Marocco, F. Mary, N. Nicolas, C. Ordenovic, C. Pailler, F. Palicio, P.A. Pallas-Quintela, L. Panem, C. Pichon, B. Poggio, E. Recio-Blanco, A. Riclet, F. Rybizki, J. Santoveña, R. Sarro, L.M. Schultheis, M.S. Segol, M. Slezak, I. Smart, R.L. Sordo, R. Soubiran, C. Süveges, M. Thévenin, F. Torralba Elipe, G. Ulla, A. Utrilla, E. Vallenari, A. Van Dillen, E. Zhao, H. Zorec, J. Institut D Astrophysique et de Géophysique Université de Liège 19c Allée du 6 Août Liège4000 Belgium Max Planck Institute for Astronomy Königstuhl 17 Heidelberg69117 Germany National Observatory of Athens I. Metaxa and Vas. Pavlou Palaia Penteli Athens15236 Greece INAF Osservatorio Astrofisico di Torino Via Osservatorio 20 TO Pino Torinese10025 Italy CIGUS CITIC Department of Computer Science and Information Technologies University of A Coruña Campus de Elviña s/n A Coruña15071 Spain Dpto. de Matemática Aplicada y Ciencias de la Computación Univ. de Cantabria ETS Ingenieros de Caminos Canales y Puertos Avda. de los Castros s/n Santander39005 Spain Department of Astrophysics Astronomy and Mechanics National and Kapodistrian University of Athens Panepistimiopolis Zografos Athens15783 Greece IRAP Université de Toulouse CNRS UPS CNES 9 Av. colonel Roche BP 44346 ToulouseCedex 4 31028 France Niels Bohr Institute University of Copenhagen Juliane Maries Vej 30 Copenhagen2100 Denmark DXC Technology Retortvej 8 Valby2500 Denmark CIGUS CITIC Department of Nautical Sciences and Marine Engineering University of A Coruña Paseo de Ronda 51 A Coruña15071 Spain Thales Services for CNES Centre Spatial de Toulouse 18 avenue Edouard Belin ToulouseCedex 9 31401 France Camino bajo del Castillo s/n Urbanizacion Villafranca del Castillo Villanueva de la Cañada Madrid28692 Spain Université Côte D Azur Observatoire de la Côte D Azur CNRS Laboratoire Lagrange Bd de l Observatoire CS 34229 NiceCedex 4 06304 France Laboratoire D Astrophysique de Bordeaux Univ. Bordeaux CNRS B18N allée Geoffroy Saint-Hilaire Pessac33615 France INAF Osservatorio Astrofisico di Catania Via S. Sofia 78 Catania95123 Italy Telespazio for CNES Centre Spatial de Toulouse 18 avenue Edouard Belin ToulouseCedex 9 31401 France GEPI Observatoire de Paris Université PSL CNRS 5 place Jules Janssen Meudon92190 France CNES Centre Spatial de Toulouse 18 avenue Edouard B

Context. As part of the third Gaia data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b|& 5. *** DR3 includes 1591 million sources with DSC classifications;56 million sources to which the OA clustering is applied;1.4 million sources with redshift estimates from UGC;6.4 million sources with QSOC redshift;and 3.1 million level 9 HEALPixes of size 0.013 deg2where the extinction is evaluated by TGE. Conclusions. Validation shows that results are in good agreement with values from external catalogues;for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while

关键词： Galaxies

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A Case Study of Hierarchical Clustering for Maritime Industry

A Case Study of Hierarchical Clustering for Maritime Industr...

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2017 2nd International Conference on Advanced Materials science and Environment Engineering(AMSEE2017)

作者： Fang HAN Hao WANG Big Data Lab Department of ICT and Natural Sciences Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology

data in the contemporary world has penetrated into every industry and is increasingly becoming a necessity in enterprises, simultaneously it has also become an important factor of production. Maritime transport is one of the most vital transport systems and maritime big data is attracting increase interest from both the industry and academia. In this paper, we present a case study using hierarchical clustering on a dataset about a vessel's behavior during operations. We have also produced visually appealing graphs and charts to assist the data analysis.

关键词： big data Machine learning Hierarchical clustering

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Kuramoto dilemma alleviated by optimizing connectivity and rationality

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Physical Review E 2018年第2期98卷 022201-022201页

作者： Han-Xin Yang Tao Zhou Zhi-Xi Wu Department of Physics Fuzhou University Fuzhou 350116 People's Republic of China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu 611731 People's Republic of China CompleX Lab Web Sciences Center University of Electronic Science and Technology of China Chengdu 611731 People's Republic of China Big Data Research Center University of Electronic Science and Technology of China Chengdu 611731 People's Republic of China Institute of Computational Physics and Complex Systems Lanzhou University Lanzhou Gansu 730000 People's Republic of China

Recently, Antonioni and Cardillo proposed a coevolutionary model based on the intertwining of oscillator synchronization and evolutionary game theory [Phys. Rev. Lett. 118, 238301 (2017)], in which each Kuramoto oscillator can decide whether to interact or not with its neighbors, and all oscillators can receive some benefits from the local synchronization, but those who choose to interact must pay a cost. Oscillators are allowed to update their strategies according to payoff difference, wherein the strategy of an oscillator who has obtained higher payoff is more likely to be followed. Utilizing this coevolutionary model, we find that the global synchronization level reaches the highest level when the average degree of the underlying interaction network is moderate. We also study how synchronization is affected by the individual rationality in choosing strategy.

关键词： Evolutionary dynamics Network structure Synchronization

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Exploring the Impact of Processing Guarantees on Performance of Stream data Processing

Exploring the Impact of Processing Guarantees on Performance...

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2017 17th IEEE International Conference on Communication Technology (ICCT 2017)

作者： Syed Muhammad Abrar Akber Changfu Lin Hanhua Chen Fan Zhang Hai Jin Cluster and Grid Computing Lab Services Computing Technology and System Lab Big Data Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology

Processing semantics ensure tuple processing guarantees during system recovery from failures. It determines whether particular tuples are re-processed or not upon system recovery. Processing semantics facilitate to maintain real-time response as well as correctness of results in stream data processing. Existing literature is in real deficit to provide sufficient resources exclusively on processing semantics. This work focuses on reviewing processing semantics in stream data processing *** article aims at exploring the impact of processing guaran-tees on performance of stream data processing. We summarize current research directions to guarantee processing semantics,based on prominent stream processing engines. Furthermore,we compare throughput for a couple of representative stream processing engines under all possible processing *** experiments show that at-most once processing guarantee provides the highest throughput among other guarantees. Lastly,challenges for further research are also discussed in this paper.

关键词： stream data processing processing semantic processing guarantee at-least once at-most once exactly-once

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Differential item functioning for the Tendency of Avoiding Physical Activity and Sport Scale across two subculture samples: Taiwanese and mainland Chinese university students

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Heliyon 2023年第12期9卷 e22583页

作者： Chia-Wei Fan Po-Ching Huang I-Hua Chen Yu-Ting Huang Jung-Sheng Chen Xavier C C Fung Ji-Kang Chen Yung-Ning Yang Kerry S O'Brien Chung-Ying Lin Mark D Griffiths Department of Occupational Therapy AdventHealth University Orlando FL USA. School of Physical Therapy and Graduate Institute of Rehabilitation Science College of Medicine Chang Gung University Taoyuan 333 Taiwan. Chinese Academy of Education Big Data Qufu Normal University Shandong China. Institute of Allied Health Sciences College of Medicine National Cheng Kung University Tainan 701 Taiwan. Department of Medical Research E-Da Hospital I-Shou University Kaohsiung 824 Taiwan. Department of Rehabilitation Sciences The Hong Kong Polytechnic University Hong Kong. Department of Social Work Chinese University of Hong Kong Hong Kong. Department of Pediatrics E-Da Hospital School of Medicine I-Shou University Kaohsiung Taiwan. Behavioural Sciences Research Lab Monash University Australia. University of Religions and Denominations Qom Iran. Biostatistics Consulting Center National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan 701 Taiwan. Department of Public Health College of Medicine National Cheng Kung University Tainan 701 Taiwan. Department of Occupational Therapy College of Medicine National Cheng Kung University Tainan 701 Taiwan. Psychology Department Nottingham Trent University Nottingham NG1 4BU UK.

Aims:The aims of the study were to examine the differential item functioning (DIF) of the Tendency of Avoiding Physical Activity and Sport Scale (TAPAS) among three subgroups (gender, weight status, and region) and to test the construct and concurrent validities of the scale. Methods:Using an online survey, university students (608 Taiwanese and 2319 mainland Chinese) completed the TAPAS. Rasch analysis examined if all the 10 TAPAS items fitted the same construct and displayed no substantial DIF across three subgroups: gender (male vs. female), weight status (overweight vs. non-overweight), and region (Taiwan vs. China). Concurrent validity was examined using the scores on the Weight Self-Stigma Questionnaire (WSSQ) and Weight Bias Internalization Scale (WBIS). Results:All TAPAS items, except for Item 10 (), fitted the same construct. None of the TAPAS items displayed DIF in any of the subgroups except for Item 10 across participants from Taiwan and China (DIF contrast = -1.41). Conclusion:The TAPAS can appropriately assess the tendency to avoid physical activity and sport among both Taiwanese and mainland Chinese university students. However, Item 10 may need to be further examined.

关键词： Physical activity Psychometrics Rasch analysis Stigma Weight

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