检索结果-内蒙古大学图书馆

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Suping Xu Xibei Yang Eric C. C. Tsang Eric A. Mantey Intelligent Information Processing Key Laboratory of Shanxi Province Shanxi University Taiyuan China School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhoushan China School of Economics and Management Nanjing University of Science and Technology Nanjing China Faculty of Information Technology Macau University of Science and Technology Macau China

ISBN: (纸本)9781509003914

In neighborhood rough set model, the majority rule based neighborhood classifier (NC) is easy to be misjudged with the increasing of the size of information granules. To remedy this deficiency, we propose a neighborhood collaborative classifier (NCC) based on the idea of collaborative representation based classification (CRC). NCC first performs feature selection with neighborhood rough set, and then instead of solving the classification problem by the majority rule, NCC solves a similar problem with collaborative representation among the neighbors of each unseen sample. Experiments on UCI data sets demonstrate that: 1) Our NCC achieves satisfactory performance in larger neighborhood information granules when compared with NC; 2) NCC reduces the size of dictionary when compared with CRC.

关键词： Collaboration Rough sets Training Cybernetics Numerical models Error analysis Measurement

来源：评论

学校读者我要写书评

暂无评论

Search for long-lived, massive particles in events with a displaced vertex and a muon with large impact parameter in pp collisions at s=13 TeV with the ATLAS detector

引用

Physical Review D 2020年第3期102卷 032006-032006页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya B. Achkar S. Adachi L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra F. Ahmadov W. S. Ahmed X. Ai G. Aielli S. Akatsuka T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa D. Alexandre T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali G. Alimonti J. Alison S. P. Alkire C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. Alvarez Estevez D. Álvarez Piqueras M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen C. F. Anders J. K. Anders A. Andreazza V. Andrei C. R. Anelli S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo L. Aperio Bella G. Arabidze J. P. Araque V. Araujo Ferraz R. Araujo Pereira C. Arcangeletti A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame A. Artamonov G. Artoni S. Artz S. Asai N. Asbah E. M. Asimakopoulou L. Asquith J. Assahsah K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten G. Avolio R. Avramidou M. K. Ayoub A. M. Azoulay G. Azuelos H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia M. Bahmani H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines M. Bajic C. Bakalis O. K. Baker P. J. Bakker D. Bakshi Gupta S. Balaji E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero G. CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States of America Department of Physics University of Massachusetts Amherst MA United States of America INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne IL United States of America INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb IL United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States of America IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay Franc

A search for long-lived particles decaying into hadrons and at least one muon is presented. The analysis selects events that pass a muon or missing-transverse-momentum trigger and contain a displaced muon track and a displaced vertex. The analyzed dataset of proton-proton collisions at s=13 TeV was collected with the ATLAS detector and corresponds to 136 fb−1. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particle decays that occur in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are presented as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and interpreted as exclusion limits in scenarios with pair production of long-lived top squarks that decay via a small R-parity-violating coupling into a quark and a muon. Top squarks with masses up to 1.7 TeV are excluded for a lifetime of 0.1 ns, and masses below 1.3 TeV are excluded for lifetimes between 0.01 ns and 30 ns.

关键词： Supersymmetric models

来源：评论

学校读者我要写书评

暂无评论

TQS-DP: A lightweight and active mechanism for fast scheduling based on WSN operating system TinyOS 27

TQS-DP: A lightweight and active mechanism for fast scheduli...

引用

27th Chinese Control and Decision Conference, CCDC 2015

作者： Jing, Zhang Leng, Xue Fan, Hongbo Yi, Cui Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Yunnan Academy of Scientific and Technical Information Kunming Yunnan China

ISBN: (纸本)9781479970179

Sensor technology is a key technology in the field of Internet of Things(IoT), which has been applied to the research on task scheduling of embedded systems in wireless sensor networks (WSN), it affects the existence and uniqueness of the real-time interactive behavior for IoT service, as well as the energy consumption modeling and evaluation of WSN deployment on the background of real-time embedded control systems. In this paper, through further studies on the kernel scheduling mechanism of TinyOS, aiming at its shortcomings, a lightweight scheduling strategy - quick sort scheduling strategy based on dynamic priority of tasks queue (TQS-DP) was proposed. This strategy changes the priority of tasks dynamically, and quickly put them into queues with quick sort. Meanwhile, the timeout management of tasks is taken into consideration. Whether the priority level of the task is high or low, it can be executed in due time. Finally, the simulation experiments show that our method cannot only improve the task throughput of the whole wireless sensor networks (WSNs), but also effectively reduce the energy consumption of system, in order to ensure the real-time performance, determinacy and casuality dependency of task scheduling. © 2015 IEEE.

关键词： dynamic priority energy consumption real-time scheduling mechanism TinyOS WSN

来源：评论

学校读者我要写书评

暂无评论

Search for resonances decaying into a weak vector boson and a Higgs boson in the fully hadronic final state produced in proton−proton collisions at s=13 TeV with the ATLAS detector

引用

Physical Review D 2020年第11期102卷 112008-112008页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya B. Achkar L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra A. Ahmad F. Ahmadov W. S. Ahmed X. Ai G. Aielli S. Akatsuka M. Akbiyik T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali S. Ali M. Aliev G. Alimonti C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio F. Alonso C. Alpigiani E. Alunno Camelia M. Alvarez Estevez M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen J. K. Anders S. Y. Andrean A. Andreazza V. Andrei C. R. Anelli S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella N. Aranzabal Barrio V. Araujo Ferraz R. Araujo Pereira C. Arcangeletti A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame G. Artoni H. Asada K. Asai S. Asai T. Asawatavonvanich N. Asbah E. M. Asimakopoulou L. Asquith J. Assahsah K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten V. A. Austrup G. Avolio M. K. Ayoub G. Azuelos H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia M. Bahmani H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines C. Bakalis O. K. Baker P. J. Bakker E. Bakos D. Bakshi Gupta S. Balaji R. Balasubramanian E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay Sw. Banerjee L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne Illinois USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Physics Radboud University Nijmegen/Nikhef Nijmegen Netherlands Department of Physics Alexandru Ioan Cuza U

A search for heavy resonances decaying into a W or Z boson and a Higgs boson produced in proton−proton collisions at the Large Hadron Collider at s=13 TeV is presented. The analysis utilizes the dominant W→qq¯′ or Z→qq¯ and H→bb¯ decays with substructure techniques applied to large-radius jets. A sample corresponding to an integrated luminosity of 139 fb−1 collected with the ATLAS detector is analyzed and no significant excess of data is observed over the background prediction. The results are interpreted in the context of the heavy vector triplet model with spin-1 W′ and Z′ bosons. Upper limits on the cross section are set for resonances with mass between 1.5 and 5.0 TeV, ranging from 6.8 to 0.53 fb for W′→WH and from 8.7 to 0.53 fb for Z′→ZH at the 95% confidence level.

关键词： Hypothetical particle physics models Particle data analysis

来源：评论

学校读者我要写书评

暂无评论

Search for Higgs boson decays into two new low-mass spin-0 particles in the 4b channel with the ATLAS detector using pp collisions at s=13 TeV

引用

Physical Review D 2020年第11期102卷 112006-112006页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya B. Achkar L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra A. Ahmad F. Ahmadov W. S. Ahmed X. Ai G. Aielli S. Akatsuka M. Akbiyik T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali S. Ali M. Aliev G. Alimonti C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio F. Alonso C. Alpigiani E. Alunno Camelia M. Alvarez Estevez M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen J. K. Anders S. Y. Andrean A. Andreazza V. Andrei C. R. Anelli S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella N. Aranzabal V. Araujo Ferraz R. Araujo Pereira C. Arcangeletti A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame G. Artoni K. Asai S. Asai T. Asawatavonvanich N. Asbah E. M. Asimakopoulou L. Asquith J. Assahsah K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten V. A. Austrup G. Avolio M. K. Ayoub G. Azuelos H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia M. Bahmani H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines C. Bakalis O. K. Baker P. J. Bakker E. Bakos D. Bakshi Gupta S. Balaji E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay Sw. Banerjee L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero G. Barbour T. Barillari M-S. Barisi CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne Illinois USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Physics Radboud University Nijmegen/Nikhef Nijmegen Netherlands Department of Physics Alexandru Ioan Cuza U

This paper describes a search for beyond the Standard Model decays of the Higgs boson into a pair of new spin-0 particles subsequently decaying into b-quark pairs, H→aa→(bb¯)(bb¯), using proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at center-of-mass energy s=13 TeV. This search focuses on the range 15 GeV≤ma≤30 GeV, where the decay products are collimated; it is complementary to a previous search in the same final state targeting the range 20 GeV≤ma≤60 GeV, where the decay products are well separated. A novel strategy for the identification of the a→bb¯ decays is deployed to enhance the efficiency for topologies with small separation angles. The search is performed with 36 fb−1 of integrated luminosity collected in 2015 and 2016 and sets upper limits on the production cross section of H→aa→(bb¯)(bb¯), where the Higgs boson is produced in association with a Z boson.

关键词： Extensions of Higgs sector Particle interactions Higgs bosons Hadron colliders Particle data analysis

来源：评论

学校读者我要写书评

暂无评论

Network energy consumption analysis and dormancy mechanism based on ant colony algorithm in cloud computing environment for IOT service and real-time embedded industrial control system 27

Network energy consumption analysis and dormancy mechanism b...

引用

27th Chinese Control and Decision Conference, CCDC 2015

作者： Shi, Shaoling Jing, Zhang Chen, Moliang Hui, Rong Yi, Cui Fu, Xiaodong Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming Yunnan China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan China Faculty of Art and Design Kunming Metallurgy College Kunming Yunnan China Yunnan Academy of Scientific and Technical Information Kunming Yunnan China

ISBN: (纸本)9781479970179

At present, cloud computing technology is widely used in IOT(Internet of Things) service and real-time embedded industrial control system energy consumption, problem in the cloud computing has always been the hot topic of industry and academic research. This paper analyzes the energy consumption of each equipment under the dormancy mechanism in the cloud computing environment. Meanwhile, this paper introduces the ant colony algorithm into a basic network energy consumption model, thereby building a new model for the energy consumption optimization. The simulation experiments were implemented on a cloud computing simulation platform CLOUDSIM. In comparison with two algorithms - Min LP and Dijkstra, the model presented in this paper was proved to be effective and more energy-efficient. © 2015 IEEE.

关键词： ant colony algorithm cloud computing dormancy mechanism energy consumption analysis IOT service real-time embedded industrial control system

来源：评论

学校读者我要写书评

暂无评论

Exploration of Image Search Results Quality Assessment

引用

IEEE Transactions on Big Data 2015年第3期1卷 95-108页

作者： Tian, Xinmei Lu, Yijuan Stender, Nate Yang, Linjun Tao, Dacheng CAS Key Laboratory of Technology Geo-Spatial Information Processing and Application Systems University of Science and Technology of China Hefei230027 China Department of Computer Science Texas State University San MarcosTX78666 United States Department of Computer Science University of Nebraska-Lincoln LincolnNE68588 United States Microsoft Corporation RedmondWA98052-7329 United States Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

Image retrieval plays an increasingly important role in our daily lives. There are many factors which affect the quality of image search results, including chosen search algorithms, ranking functions, and indexing features. Applying different settings for these factors generates search result lists with varying levels of quality. However, no setting can always perform optimally for all queries. Therefore, given a set of search result lists generated by different settings, it is crucial to automatically determine which result list is the best in order to present it to users. This paper aims to solve this problem and makes four main innovations. First, a preference learning model is proposed to quantitatively study and formulate the best image search result list identification problem. Second, a set of valuable preference learning related features is proposed by exploring the visual characters of returned images. Third, a query-dependent preference learning model is further designed for building a more precise and query-specific model. Fourth, the proposed approach has been tested on a variety of applications including reranking ability assessment, optimal search engine selection, and synonymous query suggestion. Extensive experimental results on three image search datasets demonstrate the effectiveness and promising potential of the proposed method. © 2015 IEEE.

关键词： Image retrieval

来源：评论

学校读者我要写书评

暂无评论

Efficient Searchable Symmetric Encryption for Storing Multiple Source Data on Cloud

Efficient Searchable Symmetric Encryption for Storing Multip...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Chang Liu Liehuang Zhu Jinjun Chen Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application School of Computer Science and Technology Beijing Institute of Technology Beijing China Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia

ISBN: (纸本)9781467379533

Cloud computing has greatly facilitated large-scale data outsourcing due to its cost efficiency, scalability and many other advantages. Subsequent privacy risks force data owners to encrypt sensitive data, hence making the outsourced data no longer searchable. Searchable Symmetric Encryption (SSE) is an advanced cryptographic primitive addressing the above issue, which maintains efficient keyword search over encrypted data without disclosing much information to the storage provider. Existing SSE schemes implicitly assume that original user data is centralized, so that a searchable index can be built at once. Nevertheless, especially in cloud computing applications, user-side data centralization is not reasonable, e.g. an enterprise distributes its data in several data centers. In this paper, we propose the notion of Multi-Data-Source SSE (MDS-SSE), which allows each data source to build a local index individually and enables the storage provider to merge all local indexes into a global index afterwards. We propose a novel MDS-SSE scheme, in which an adversary only learns the number of data sources, the number of entire data files, the access pattern and the search pattern, but not any other distribution information such as how data files or search results are distributed over data sources. We offer rigorous security proof of our scheme, and report experimental results to demonstrate the efficiency of our scheme.

关键词： Indexes Cloud computing Servers Encryption Distributed databases

来源：评论

学校读者我要写书评

暂无评论

Context-aware computing for smart home environment

引用

Journal of Computational Information Systems 2015年第15期11卷 5453-5460页

作者： Liu, Li Fu, Xiaodong Liu, Lijun Huang, Qingsong Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China State-Province Joint Laboratory of Digital Home Interactive Applications School of Information Science & Technology Sun Yat-sen University Guangzhou China

Context-aware computing has proven to be successful in collecting and understanding various sensor data. However, providing an intelligent service by exploiting the collected context data from heterogeneous sensors is difficult on smart home because it is a complex environment with various devices and appliances. In this paper, we propose a context-aware computing approach for heterogeneous smart home environments. The key idea in this work is to integrate large-scale home context information from multiple heterogeneous sensors. We first define a semantic decision by context-aware inference including rule, inference and pattern driven. Then, a designed architecture that manages home environment is developed between large numbers of heterogeneous information entities and enhances intelligence abilities. Using the established rules and inferences, the proposed method is applicable for intelligent home to further discover more useful representative activities and personalized services with inhabitant needs. Experimental results show the effectiveness of our proposed method. Copyright © 2015 Binary Information Press.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

3D garment segmentation based on semi-supervised learning method

引用

Journal of Fiber Bioengineering and Informatics 2015年第4期8卷 657-665页

作者： Huang, Mian Liu, Li Liu, Ruomei Fu, Xiaodong Liu, Lijun Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China National Engineering Research Center of Digital Life State-Province Joint Laboratory of Digital Home Interactive Applications School of Data and Computer Science Sun Yat-sen University Guangzhou China

In this paper, we propose a semi-supervised learning method to simultaneous segmentation and labeling of parts in 3D garments. The key idea in this work is to analyze 3D garments using semi-supervised learning method which can label parts in various 3D garments. We first develop an objective function based on Conditional Random Field (CRF) model to learn the prior knowledge of garment components from a set of training examples. Then, we exploit an effective training method that utilizes JointBoost classifiers based on the co-analysis for garments. And we modify the JointBoost to automatically cluster the segmented components without requiring manual parameter tuning. The purpose of our method is to relieve the manual segmentation and labeling of components in 3D garment collections. Finally, the experimental results show the performance of our proposed method is effective. © 2015 Binary Information Press & Textile Bioengineering and Informatics Society December 2015.

关键词： Random processes

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：