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Combinatorial algorithms 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： thierry Lecroq Laurent Mouchard

ISBN: (数字)9783642452789

ISBN: (纸本)9783642452772

this book constitutes the thoroughly refereed post-workshop proceedings of the 24th international workshop on Combinatorial algorithms, IWOCA 2013, held in Rouen, France, in July 2013. the 33 revised full papers presented together with 10 short papers and 5 invited talks were carefully reviewed and selected from a total of 91 submissions. the papers are organized in topical sections on algorithms on graphs; algorithms on strings; discrete geometry and satisfiability.

关键词： Discrete Mathematics in Computer Science Combinatorics Algorithm Analysis and Problem Complexity Mathematical Logic and Formal Languages data structures Symbolic and Algebraic Manipulation

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Frequent pattern mining and knowledge indexing based on zero-suppressed BDDs

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5th international workshop on Knowledge Discovery in Inductive databases

作者： Minato, Shin-Ichi Arimura, Hiroki Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido 0600814 Japan

ISBN: (纸本)9783540755487

Frequent pattern mining is one of the fundamental techniques for knowledge discovery and data mining. During the last decade, several efficient algorithms for frequent pattern mining have been presented, but most algorithms have focused on enumerating the patterns that satisfy the given conditions, considering the storage and indexing of the pattern results for efficient inductive analysis to be a separate issue. In this paper, we propose a fast algorithm for extracting all/maximal frequent patterns from transaction databases and simultaneously indexing a huge number of patterns using Zero-suppressed Binary Decision Diagrams (ZBDDs). Our method is comparably fast as existing state-of-the-art algorithms and not only enumerates/lists the patterns but also compactly indexes the output data in main memory. After mining, the pattern results can be analyzed efficiently by using algebraic operations. BDD-based data structures have previously been used successfully in VLSI logic design, but our method is the first practical application of BDD-based techniques in the data mining area.

关键词： data mining

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dIP: A non-intrusive debugging IP for dynamic data race detection in many-core

dIP: A non-intrusive debugging IP for dynamic data race dete...

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10th international Symposium on Pervasive Systems, algorithms, and Networks, I-SPAN 2009

作者： Wen, Chi-Neng Chou, Shu-Hsuan Chen, Tien-Fu National Chung-Cheng University Chia-Yi Taiwan

ISBN: (纸本)9780769539089

Traditional debug facilities are limited in providing debugging requirements for multicore parallel programming. Synchronization problems or bugs due to race conditions are particularly difficult to detect with software debugging tools. this work presents a fast and feasible hardware-assistant solution for many-core non-intrusive debugging. the key idea is to keep tracks of data accesses of shared memory areas and their lock synchronization activities by proposed data structures in proposed debugging IP (dIP). A page-based shared variable cache is provided to keep shared variables as long as possible, and an inexpensive pluggable off-chip RAM can eliminate the false-positive rate efficiently. To decrease the debugging traffic block, this work provides a thread library to specify shared memory/lock events and transmit those events to the dIP by a small proper hardware co-processor (eXtend dIP) of each core. Our experimental result shows the debugging traffic block (worse-case) by increasing cores, and adding tolerance buffers in XdIP can efficiently ease off. Moreover, the real workloads (SPLASH-2, MPEG-4, and H.264) are executed by the dIP non-instructive race-detection with only 4.7%-12.2% slow down in average. Finally, the hardware cost of dIP is also low when the growing of many-core. © 2009 IEEE.

关键词： Fault tolerance

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Equalizing data Science Curriculum for Computer Science Pupils 20

Equalizing Data Science Curriculum for Computer Science Pupi...

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20th Koli Calling Conference on Computing Education Research, Koli Calling 2020

作者： Mike, Koby Hazan, Tamir Hazzan, Orit Faculty of Education in Science and Technology Technion-Israel Institute of Technology Haifa Israel Faculty of Industrial Engineering and Management Technion-Israel Institute of Technology Haifa Israel

ISBN: (纸本)9781450389211

data science is a new interdisciplinary field of research that focuses on extracting value from data. As an interdisciplinary science it integrates knowledge and methods from computer science, mathematics and statistics, and the domain knowledge of the data. As data science is still forming as a domain, several points of view exist on how to teach data science. the curriculum of many undergraduate data science programs includes advanced knowledge and skills in mathematics, statistics, computer science, and one or more data domains. Several initiatives for designing high school data science curricula have emerged recently. Since it is unrealistic to teach all the above-mentioned advanced topics at the high school level, the high school data science curriculum focuses on a broad understanding of the data science workflow rather than on mathematical and algorithmic details that characterize undergraduate programs. High school computer science pupils, however, are expected to have a deep understanding of algorithms, as algorithms are the heart of computer science. In this paper, we present our attempt to adapt a data science course to computer science high school pupils that incorporates both a broad view on data science and data workflow, as well as deep understanding of data processing algorithms and specifically, machine learning. this course is taught for 10th grade computer science pupils in an Israeli public school, and was also taught in a summer workshop for computer science teachers. © 2020 ACM.

关键词： Curricula

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15th international workshop on Computer Science Logic, CSL 2001 and 10th Annual Conference of the European Association for Computer Science Logic, EACSL 2001

引用

15th international workshop on Computer Science Logic, CSL 2001 and 10th Annual Conference of the European Association for Computer Science Logic, EACSL 2001

ISBN: (纸本)3540425543

the proceedings contain 42 papers. the special focus in this conference is on Descriptive Complexity, Semantics, Higher-Order Programs and Modal Logics. the topics include: Local reasoning about programs that alter data structures;from the rules of logic to the logic of rules;the expressive power of horn monadic linear logic;quadratic correctness criterion for non-commutative logic;an algebraic foundation for Higraphs;semantic characterisations of second-order computability over the real numbers;an improved extensionality criterion for higher-order logic programs;a logic for abstract state machines;modal logic and the two-variable fragment;a logic for approximate first-order reasoning;categorical and kripke semantics for constructive s4 modal logic;labelled natural deduction for interval logics;decidable navigation logics for object structures;the decidability of model checking mobile ambients;an effective extension of the Wagner hierarchy to blind counter automata;decision procedure for an extension of ws1s;limiting partial combinatory algebras towards infinitary lambda-calculi and classical logic;well-founded recursive relations;uniform derivation of decision procedures by superposition;equational tree automata for associative and commutative theories;recursion for higher-order encodings and monotone inductive and coinductive constructors of rank 2.

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Damage Detection Using Supervised Machine Learning algorithms for Real-World Engineering structures 10th

Damage Detection Using Supervised Machine Learning Algorithm...

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10th European workshop on Structural Health Monitoring (EWSHM)

作者： Turrisi, Simone Zappa, Emanuele Cigada, Alfredo Kumar, Songshitobrota Politecn Milan I-20156 Milan Italy

ISBN: (纸本)9783031072581;9783031072574

Vibration-based structural health monitoring represents an efficient way to evaluate structural integrity and the presence of damage at an early stage. these methods usually assume that damage manifests itself as a deviation in the modal properties of the structure with respect to its normal conditions. Traditional procedures for modal parameters estimation require the use of a dense sensor arrangement and complex logic techniques, thus making them not particularly suitable for the case of large engineering structures, where the need for cost-effective monitoring solutions is of utmost importance because of the large number of substructures to be monitored. this paper proposes the use of simple statistical and spectral features as a mean to characterize accelerations signals. Starting from this set of features, the principal component analysis (PCA) is first used to reduce data dimensionality still preserving the relevant information about the structural conditions, then a k-Nearest Neighbors (k-NN) procedure is adopted as a supervised machine learning method to classify different types of damage. the procedure is validated using the experimental data from the permanent monitoring system of the G. Meazza stadium grandstands of, where one accelerometer per stand is installed to get vibration data during the main events. Four grandstands located on the same ring and having the same nominal geometry are considered. the leading idea is to reproduce different scenarios where, due to the impossibility of imposing realistic damages, one grandstand is assumed to be the safe structure, while the others represent a proxy for small structural changes to be identified.

关键词： Structural health monitoring Vibration monitoring Damage detection Supervised learning Engineering structures

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CEUR workshop Proceedings

CEUR Workshop Proceedings

引用

10th international Conference on Concept Lattices and their Applications, CLA 2013

the proceedings contain 27 papers. the topics discussed include: a practical application of relational concept analysis to class model factorization: lessons learned from a thematic information system;used for use case modeling;computing similarity dependencies with pattern structures;decomposition of intervals in the space of anti-monotonic functions;attribute exploration with fuzzy attributes and background knowledge;an efficient java implementation of the immediate successors calculation;pedagogical software on lattice cryptomorphisms and lattice properties;computing the concept lattice using dendritical neural networks;a conceptual-KDD approach and its application to cultural heritage;analogical proportions and the factorization of information in distributive lattices;and Boolean factor analysis of multirelational data.

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An SHM data-Driven Methodology for the Remaining Useful Life Prognosis of Aeronautical Subcomponents 10th

An SHM Data-Driven Methodology for the Remaining Useful Life...

引用

10th European workshop on Structural Health Monitoring (EWSHM)

作者： Galanopoulos, Georgios Eleftheroglou, Nick Milanoski, Dimitrios Broer, Agnes Zarouchas, Dimitrios Loutas, theodoros Univ Patras Dept Mech Engn & Aeronaut Appl Mech Lab Rion 26504 Greece Delft Univ Technol Fac Aerosp Engn Struct Integr & Composites Grp Kluyverweg 1 NL-2629 HS Delft Netherlands Delft Univ Technol Aerosp Engn Fac Ctr Excellence Artificial Intelligence Struct Delft Netherlands

ISBN: (纸本)9783031072543;9783031072536

Prognosis of the Remaining Useful Life (RUL) of a structure from Structural Health Monitoring data is the ultimate level in the SHM hierarchy. Reliable prognostics are key to a Condition Based Maintenance paradigm for aerospace systems and structures. In the present work, we propose a methodology for RUL prognosis of generic aeronautical elements i.e. single stringered composite panels subjected to compression/compression fatigue. Strain measurements are utilized in this direction via FBG sensors bonded to the stiffener feet. the strain data collected during the fatigue life are processed and used for the RUL prognosis. In order to accomplish this task, it is essential to produce Health Indicators (HIs) out of raw strain that can properly capture the degradation process. To create such HIs a new pre/post-processing technique is employed and a variety of different HIs are developed. the quality of the HIs can enhance the performance of the prognostic algorithms, hence a fusion methodology is proposed using genetic algorithms. the resulted fused HI is used for the RUL estimation of the SSCPs. Gaussian processes and Hidden Semi Markov Models are employed for RUL prognosis and their performance is compared. Despite the complexity the raw data we demonstrate the feasibility of successful RUL prognostics in a SHM-data driven approach.

关键词： Structural Health Monitoring RUL prognosis Composite panels Health Indicators Fibber Bragg Gratings

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3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research 10th

3D Slicer Craniomaxillofacial Modules Support Patient-Specif...

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10th international workshop on Multimodal Learning for Clinical Decision Support.(ML-CDS) / 9th international workshop on Clinical Image-based Procedures - From Planning to Intervention (CLIP)

作者： Bianchi, Jonas Paniagua, Beatriz Ruellas, Antonio Carlos De Oliveira Fillion-Robin, Jean-Christophe Prietro, Juan C. Goncalves, Joao Roberto Hoctor, James Yatabe, Marilia Styner, Martin Li, TengFei Gurgel, Marcela Lima Chaves Junior, Cauby Maia Massaro, Camila Garib, Daniela Gamba Vilanova, Lorena Castanha Henriques, Jose Fernando Aliaga-Del Castillo, Aron Janson, Guilherme Iwasaki, Laura R. Nickel, Jeffrey C. Evangelista, Karine Cevidanes, Lucia Univ Michigan 1011 North Univ Ave Ann Arbor MI 48109 USA Kitware Incorp Carrboro NC 27510 USA Univ N Carolina Chapel Hill NC 27599 USA Sao Paulo State Univ BR-14801903 Araraquara SP Brazil Univ Fed Ceara BR-60020181 Fortaleza CE Brazil Univ Sao Paulo BR-17011220 Bauru SP Brazil Oregon Hlth & Sci Univ Portland OR 97201 USA Univ Fed Goias BR-74690900 Goiania Go Brazil

ISBN: (纸本)9783030609450;9783030609467

the biggest challenge to improve the diagnosis and therapies of Craniomaxillofacial conditions is to translate algorithms and software developments towards the creation of holistic patient models. A complete picture of the individual patient for treatment planning and personalized healthcare requires a compilation of clinician-friendly algorithms to provide minimally invasive diagnostic techniques with multimodal image integration and analysis. We describe here the implementation of the open-source Craniomaxillofacial module of the 3D Slicer software, as well as its clinical applications. this paper proposes data management approaches for multisource data extraction, registration, visualization, and quantification. these applications integrate medical images with clinical and biological data analytics, user studies, and other heterogeneous data.

关键词： Personalized medicine data management data analytics Craniomaxillofacial diseases Dental research

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Mixed shared-distributed hash tables approaches for parallel state space construction

Mixed shared-distributed hash tables approaches for parallel...

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2011 10th international Symposium on Parallel and Distributed Computing, ISPDC 2011

作者： Saad, Rodrigo T. Zilio, Silvano Dal Berthomieu, Bernard CNRS LAAS 7 ave. Colonel Roche F-31077 Toulouse France Université de Toulouse ISAE LAAS F-31077 Toulouse France

ISBN: (纸本)9780769545400

We propose an algorithm for parallel state space construction based on an original concurrent data structure, called a localization table, that aims at better spatial and temporal balance. Our proposal is close in spirit to algorithms based on distributed hash tables, with the distinction that states are dynamically assigned to processors, i.e. we do not rely on an a-priori static partition of the state space. In our solution, every process keeps a share of the global state space. data distribution and coordination between processes is made through the localization table, that is a lockless, thread-safe data structure that approximates the set of states being processed. the localization table is used to dynamically assign newly discovered states and can be queried to return the identity of the processor that own a given state. With this approach, we are able to consolidate a network of local hash tables into an (abstract) distributed one without sacrificing memory affinity - data that are "logically connected" and physically close to each others - and without incurring performance costs associated to the use of locks to ensure data consistency. We evaluate the performance of our algorithm on different benchmarks and compare these results with other solutions proposed in the literature and with existing verification tools. © 2011 IEEE.

关键词： data structures

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