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IEEE Photonics Conference

作者： Amédée Lacraz Antreas Theodosiou Kyriacos Kalli Nanophotonics group Department of Electrical Engineering Computer science and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781509019076

We present a strain and temperature polymer fiber sensor with exceptional optical properties based on femtosecond inscribed fiber Bragg gratings (FBG). The gratings were interrogated with a detection setup optimized for multimode gratings. The sensors' strain and temperature response were characterized and showed promising results for realistic sensing applications.

关键词： Femtosecond laser Low loss fiber Polymer optical fiber Fiber Bragg grating

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Measurement of the and tH production rates in the H → decay channel using proton-proton collision data at = 13 TeV

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Journal of High Energy Physics 2025年第2期2025卷 1-75页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J. W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P. S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M. R. Janssen, T. Van Mechelen, P. Breugelmans, N. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Heyen, F. Lowette, S. Makarenko, I. Müller, D. Tavernier, S. Tytgat, M. Van Onsem, G. P. Van Putte, S. Vannerom, D. Bilin, B. Clerbaux, B. Das, A. K. De Lentdecker, G. Evard, H. Favart, L. Gianneios, P. Jaramillo, J. Khalilzadeh, A. Khan, F. A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Shahzad, M. A. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Gokbulut, G. Hong, Y. Knolle, J. Lambrecht, L. Marckx, D. Mota Amarilo, K. Samalan, A. Skovpen, K. Van Den Bossche, N. van der Linden, J. Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. De Favereau De Jeneret, J. Delaere, C. Donertas, I. S. Giammanco, A. Guzel, A. O. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Tran, T. T. Wertz, S. Alves, G. A. Alves Gallo Pereira, M. Coelho, E. Correia Silva, G. Hensel, C. Menezes De Oliveira, T. Moraes, A. Rebello Teles, P. Soeiro, M. Vilela Pereira, A. Aldá Júnior, W. L. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. Fonseca De Souza, S. Gomes De Souza, R. Macedo, M. Martins, J. Mora Herrera, C. Mundim, L. Nogima, H. Pinheiro, J. P. Santoro, A. Sznajder, A. Thiel, M. Bernardes, C. A. Calligaris, L. Fernandez Perez Tomei, T. R. Gregores, E. M. Maietto Silverio, I. Mercadante, P. G. Novaes, S. F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liang, Z. Liu, J. Yi, K. Chen, G. M. Chen, H. S. Chen, M. Iemmi, F. Jiang, C. H. Yerevan Physics Institute Yerevan Armenia Yerevan State University Yerevan Armenia Institut für Hochenergiephysik Vienna Austria TU Wien Vienna Austria Universiteit Antwerpen Antwerpen Belgium Institute of Basic and Applied Sciences Faculty of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium Université Libre de Bruxelles Bruxelles Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Nanjing Normal University Nanjing China The University of Iowa Iowa City U.S.A. Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China China Center of Advanced Science and Technology Beijing China China Spallation Neutron Source Guangdong China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Guangdong Provincial Key Laboratory of Nuclear Science and Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Henan Normal University Xinxiang China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Hangzhou

An analysis of the production of a Higgs boson (H) in association with a top quark-antiquark pair ( $$ \textrm{t}\overline{\textrm{t}}\textrm{H} $$ ) or a single top quark (tH) is presented. The Higgs boson decay into a bottom quark-antiquark pair (H → $$ \textrm{b}\overline{\textrm{b}} $$ ) is targeted, and three different final states of the top quark decays are considered, defined by the number of leptons (electrons or muons) in the event. The analysis utilises proton-proton collision data collected at the CERN LHC with the CMS experiment at $$ \sqrt{s} $$ = 13 TeV in 2016–2018, which correspond to an integrated luminosity of 138 fb−1. The observed $$ \textrm{t}\overline{\textrm{t}}\textrm{H} $$ production rate relative to the standard model expectation is 0.33 ± 0.26 = 0.33 ± 0.17(stat) ± 0.21(syst). Additionally, the $$ \textrm{t}\overline{\textrm{t}}\textrm{H} $$ production rate is determined in intervals of Higgs boson transverse momentum. An upper limit at 95% confidence level is set on the tH production rate of 14.6 times the standard model prediction, with an expectation of $$ {19.3}_{-6.0}^{+9.2} $$ . Finally, constraints are derived on the strength and structure of the coupling between the Higgs boson and the top quark from simultaneous extraction of the $$ \textrm{t}\overline{\textrm{t}}\textrm{H} $$ and tH production rates, and the results are combined with those obtained in other Higgs boson decay channels.

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Measurement of the inclusive cross section in final states with at least one lepton and additional jets with 302 pb−1 of pp collisions at = 5.02 TeV

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Journal of High Energy Physics 2025年第4期2025卷 1-44页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J. W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P. S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Waltenberger, W. Wulz, C.-E. Janssen, T. Van Laer, T. Van Mechelen, P. Breugelmans, N. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Heyen, F. Lowette, S. Makarenko, I. Müller, D. Tavernier, S. Tytgat, M. Van Onsem, G. P. Van Putte, S. Vannerom, D. Bilin, B. Clerbaux, B. Das, A. K. De Lentdecker, G. Evard, H. Favart, L. Gianneios, P. Jaramillo, J. Khalilzadeh, A. Khan, F. A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Shahzad, M. A. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Gokbulut, G. Hong, Y. Knolle, J. Lambrecht, L. Marckx, D. Mota Amarilo, K. Skovpen, K. Van Den Bossche, N. van der Linden, J. Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. De Favereau De Jeneret, J. Delaere, C. Donertas, I. S. Giammanco, A. Guzel, A. O. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Tran, T. T. Wertz, S. Alves, G. A. Alves Gallo Pereira, M. Coelho, E. Correia Silva, G. Hensel, C. Menezes De Oliveira, T. Mora Herrera, C. Moraes, A. Rebello Teles, P. Soeiro, M. Vilela Pereira, A. Aldá Júnior, W. L. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. Fonseca De Souza, S. Gomes De Souza, R. Laux Kuhn, T. Macedo, M. Martins, J. Mundim, L. Nogima, H. Pinheiro, J. P. Santoro, A. Sznajder, A. Thiel, M. Bernardes, C. A. Calligaris, L. Fernandez Perez Tomei, T. R. Gregores, E. M. Maietto Silverio, I. Mercadante, P. G. Novaes, S. F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Laroze, D. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liang, Z. Liu, J. Chen, G. M. Chen, H. S. Chen, M. Iemmi, F. Jiang, C. H. Kapoor Yerevan Physics Institute Yerevan Armenia Yerevan State University Yerevan Armenia Institut für Hochenergiephysik Vienna Austria TU Wien Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium Université Libre de Bruxelles Bruxelles Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China China Center of Advanced Science and Technology Beijing China China Spallation Neutron Source Guangdong China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Guangdong Provincial Key Laboratory of Nuclear Science and Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Henan Normal University Xinxiang China The University of Iowa Iowa City USA Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineeri

A measurement of the top quark pair ( $$ \textrm{t}\overline{\textrm{t}} $$ ) production cross section in proton-proton collisions at a centre-of-mass energy of 5.02 TeV is presented. The data were collected at the LHC in autumn 2017, in dedicated runs with low-energy and low-intensity conditions with respect to the default configuration, and correspond to an integrated luminosity of 302 pb−1. The measurement is performed using events with one electron or muon, and multiple jets, at least one of them being identified as originating from a b quark (b tagged). Events are classified based on the number of all reconstructed jets and of b-tagged jets. Multivariate analysis techniques are used to enhance the separation between the signal and backgrounds. The measured cross section is $$ 62.5\pm 1.6{\left(\textrm{stat}\right)}_{-2.5}^{+2.6}\left(\textrm{syst}\right)\pm 1.2\left(\textrm{lumi}\right) $$ pb. A combination with the result in the dilepton channel based on the same data set yields a value of 62.3 ± 1.5 (stat) ± 2.4 (syst) ± 1.2 (lumi) pb, to be compared with the standard model prediction of $$ {69.5}_{-3.7}^{+3.5} $$ pb at next-to-next-to-leading order in perturbative quantum chromodynamics.

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Mixture of learners for cancer stem cell detection using CD13 and H and e stained images 4

Mixture of learners for cancer stem cell detection using CD1...

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4th Medical Imaging 2016: Digital Pathology

作者： Oguz, Oguzhan Akbas, Cem Emre Mallah, Maen Tagdemir, Kaslm Akhan Güzelcan, Ece Muenzenmayer, Christian Wittenberg, Thomas Üner, Aygegül Cetin, A.E. Atalay, Rengul Çetin Department of Electrical and Electronics Engineering Bilkent University Ankara Turkey Department of Computer Engineering Abdullah Gul University Kayseri Turkey Graduate School of Informatics Middle East Technical University Ankara Turkey Fraunhofer-Institute for Integrated Circuits IIS Erlangen Germany Cancer Institute Hacettepe University Ankara Turkey

ISBN: (纸本)9781510600263

In this article, algorithms for cancer stem cell (CSC) detection in liver cancer tissue images are developed. Conventionally, a pathologist examines of cancer cell morphologies under microscope. computer aided diagnosis systems (CAD) aims to help pathologists in this tedious and repetitive work. The first algorithm locates CSCs in CD13 stained liver tissue images. The method has also an online learning algorithm to improve the accuracy of detection. The second family of algorithms classify the cancer tissues stained with H and E which is clinically routine and cost effective than immunohistochemistry (IHC) procedure. The algorithms utilize 1D-SIFT and Eigen-Analysis based feature sets as descriptors. Normal and cancerous tissues can be classified with 92.1% accuracy in H and E stained images. Classification accuracy of low and high-grade cancerous tissue images is 70.4%. Therefore, this study paves the way for diagnosing the cancerous tissue and grading the level of it using H and E stained microscopic tissue images. © 2016 SPIE.

关键词： Grading

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Enviro-geno-pheno state approach and state based biomarkers for differentiation, prognosis, subtypes, and staging

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Applied informatics 2016年第1期3卷 1-14页

作者： Lei Xu Department of Computer Science and Engineering Centre for Brain-inspired Computing and Bio-Health Informatics The School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China

Finding biomarkers for differentiation, prognosis, subtypes, and staging takes a key role in precision medicine, usually featured by association analysis on geno-measures and pheno-measures. Recent efforts turn to identifying the role of a biomarker under certain condition or in a particular environment, represented by a set of enviro-measures. This paper proposes to consider the joint domain of geno-measures, pheno-measures, and enviro-measures, in which one element (i.e., each triple jointly taken by the three measures) represents a possible behaviour of the bio-system under investigation. A collection of elements that locate adjacently and share a common system status represents a ‘state’, and the system is characterised by a number of such states learned from samples. Instead of directly using one or a set of geno-measures as a biomarker, such an enviro-geno-pheno state (E-GPS) is considered as a biomarker, indicating ‘health/normal’ versus ‘risk/abnormal’ together with its associated enviro-geno-pheno conditions. Association analyses for differentiation, prognosis, subtypes, and staging can be performed between such E-GPS biomarkers and those measures representing clinical phenotypes and treatments, made either on one state or cross multiple states. Moreover, potential applications are suggested for analyses of expression data, sequencing data, and their integrative uses.

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Methods for interpreting and understanding deep neural networks

arXiv

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arXiv 2017年

作者： Montavon, Grégoire Samek, Wojciech Müller, Klaus-Robert Department of Electrical Engineering and Computer Science Technische Universität Berlin Marchstr. 23 Berlin10587 Germany Department of Video Coding and Analytics Fraunhofer Heinrich Hertz Institute Einsteinufer 37 Berlin10587 Germany Department of Brain and Cognitive Engineering Korea University Anam-dong 5ga Seongbuk-gu Seoul136-713 Korea Republic of Max Planck Institute for Informatics Stuhlsatzenhausweg Saarbrucken66123 Germany

This paper provides an entry point to the problem of interpreting a deep neural network model and explaining its predictions. It is based on a tutorial given at ICASSP 2017. It introduces some recently proposed techniques of interpretation, along with theory, tricks and recommendations, to make most efficient use of these techniques on real data. It also discusses a number of practical applications. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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The development of android – based children’s nutritional status monitoring system

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AIP Conference Proceedings 2017年第1期1818卷

作者： Agus Suryanto Octavianti Paramita Feddy Setio Pribadi Informatics and Computer Engineering Education Electrical Engineering Department Universitas Negeri Semarang Semarang Indonesia Home Economics Department Universitas Negeri Semarang Semarang Indonesia

The calculation of BMI (Body Mass Index) is one of the methods to calculate the nutritional status of a person. The BMI calculation has not yet widely understood and known by the public. In addition, people should know the importance of progress in the development of child nutrition each month. Therefore, an application to determine the nutritional status of children based on Android was developed in this study. This study restricted the calculation for children with the age of 0-60 months. The application can run on a smartphone or tablet PC with android operating system due to the rapid development of a smartphone or tablet PC with android operating system and many people own and use it. The aim of this study was to produce a android app to calculate of nutritional status of children. This study was Research and Development (R & D), with a design approach using experimental studies. The steps in this study included analyzing the formula of the Body Mass Index (BMI) and developing the initial application with the help of a computer that includes the design and manufacture of display using Eclipse software. This study resulted in android application that can be used to calculate the nutritional status of children with the age 0-60 months. The results of MES or the error calculation analysis using body mass index formula was 0. In addition, the results of MAPE percentage was 0%. It shows that there is no error in the calculation of the application based on the BMI formula. The smaller value of MSE and MAPE leads to higher level of accuracy.

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Sylabus and Matrials Design for Vocational Student and Its Dissemination Using Website

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Astro Julida Harahap Erianto Ongko Hotler Manurung Dian Kurnia H Hartono Dahlan Abdullah Cut Ita Erliana Hardianto Djanggih Kundharu Saddhono Dian Rianita Muhammad Ikhsan Setiawan Yuliyanto Budi Setiawan Rosida Tiurma Manurung S Sriadhi Mangasi Sinurat Aisyah Siregar Rapat Piter Soni Hutauruk Nico Benjamain Sibarani Department of Informatics Akademi Teknologi Industri Immanuel Medan Indonesia Department of Computer Systems Universitas Pancabudi Medan Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Law Universitas Tompotika Luwuk Banggai Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Administration University of Lancang Kuning Pekanbaru Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia Study Program of Communication Studies Universitas Semarang Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia STIE Bina Karya Tebing Tinggi Indonesia

The learners' needs are an important factor in designing syllabus and materials design, this research deals with the syllabus and material design based on the professional's needs. It is expected that the syllabus and materials designes are communicatively applicable to the professional academy. Descriptive method is applied in this research. The sample of this research is 30 students of ATII Immanuel Academy Medan. They were selected by random sampling to get the data, the questioners were administered to students. the questioners consisted of 54 items and the semi structured interview consisted of 5 questions, the finding indicated that learners' needs were focused on reading and speaking skills. With reference appropriately and proportionally derived for students of the Professional Academy. Further on the basis of the syllabus, materials are designed in which the skills of using language become a priority. The results of this research will be disseminated using the website

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Procedural content generation via machine learning (PCGML)

arXiv

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arXiv 2017年

作者： Summerville, Adam Snodgrass, Sam Guzdial, Matthew Holmgård, Christoffer Hoover, Amy K. Isaksen, Aaron Nealen, Andy Togelius, Julian Department of Computational Media University of California Santa CruzCA95064 United States College of Computing and Informatics Drexel University PhiladelpiaPA19104 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Duck and Cover Games ApS Copenhagen K1311 Denmark College of Arts Media and Design Northeastern University BostonMA02115 United States Department of Computer Science and Engineering New York University BrooklynNY11201 United States

This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content. As the importance of PCG for game development increases, researchers explore new avenues for generating high-quality content with or without human involvement;this paper addresses the relatively new paradigm of using machine learning (in contrast with search-based, solver-based, and constructive methods). We focus on what is most often considered functional game content such as platformer levels, game maps, interactive fiction stories, and cards in collectible card games, as opposed to cosmetic content such as sprites and sound effects. In addition to using PCG for autonomous generation, co-creativity, mixed-initiative design, and compression, PCGML is suited for repair, critique, and content analysis because of its focus on modeling existing content. We discuss various data sources and representations that affect the generated content. Multiple PCGML methods are covered, including neural networks: long short-term memory (LSTM) networks, autoencoders, and deep convolutional networks;Markov models: n-grams and multi-dimensional Markov chains;clustering;and matrix factorization. Finally, we discuss open problems in PCGML, including learning from small datasets, lack of training data, multi-layered learning, style-transfer, parameter tuning, and PCG as a game mechanic. Copyright © 2017, The Authors. All rights reserved.

关键词： Knowledge representation

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A local algorithm for constructing spanners in minor-free graphs 19

A local algorithm for constructing spanners in minor-free gr...

引用

19th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2016 and the 20th International Workshop on Randomization and Computation, RANDOM 2016

作者： Levi, Reut Ron, Dana Rubinfeld, Ronitt MPI for Informatics Saarbröcken Germany School of Electrical Engineering Tel Aviv University Tel Aviv Israel CSAIL MIT CambridgeMA United States Blavatnik School of Computer Science Tel Aviv University Tel Aviv Israel

ISBN: (纸本)9783959770187

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge e is in a specific spanning tree, without computing the whole spanning tree, but rather by inspecting the local neighborhood of e. The challenge is to maintain consistency. That is, to answer queries about different edges according to the same spanning tree. Since it is known that this problem cannot be solved without essentially viewing all the graph, we consider the relaxed version of finding a spanning subgraph with (1+ϵ)n edges instead of n-1 edges (where n is the number of vertices and ϵ is a given approximation/sparsity parameter). It is known that this relaxed problem requires inspecting (p n) edges in general graphs (for any constant ϵ), which motivates the study of natural restricted families of graphs. One such family is the family of graphs with an excluded minor (which in particular includes planar graphs). For this family there is an algorithm that achieves constant success probability, and inspects (d/ϵ)poly(h) log(1/ϵ) edges (for each edge it is queried on), where d is the maximum degree in the graph and h is the size of the excluded minor. The distances between pairs of vertices in the spanning subgraph G′ are at most a factor of poly(d, 1/ϵ, h) larger than in G. In this work, we show that for an input graph that is H-minor free for any H of size h, this task can be performed by inspecting only poly(d, 1/ϵ, h) edges in G. The distances between pairs of vertices in the spanning subgraph G′ are at most a factor of O∼(h log(d)/ ϵ) larger than in G. Furthermore, the error probability of the new algorithm is significantly improved to Θ(1/n). This algorithm can also be easily adapted to yield an efficient algorithm for the distributed (message passing) setting.

关键词： Computation theory

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