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检索条件"任意字段=16th International Conference and Workshops on Algorithms and Computation"

共 216 条记录，以下是11-20 订阅

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Research on simulation of soft tissue deformation in virtual orthodontics

Research on simulation of soft tissue deformation in virtual...

引用

16th international conference on Artificial Reality and Telexistence - workshops, ICAT 2006

作者： Feng, Ji Department of Information and Computation Science The Second Northwest University for Nationalities Yinchuan 750021 China

ISBN: (纸本)076952754X

Soft tissue deformation has become bottle-neckt in Visual Surgery technique. Based on the review of the current deformation methods and the analysis of soft tissue biology mechanics characteristic, the simple style mass-spring model is applied to soft tissue deformation in orthodontic simulation. In order to improve Algorithm complexity, a simplification massspring system dynamic equation is established and an effective equations solution method are presented. In the method, good data structure is presented based on the feature of STL teeth model. computation quantity and accuracy are controlled by using pervasion depth. Experiments show that it can stimulate the deformation change in real time and the display result is vivid. © 2006 IEEE.

关键词： Deformation

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Lexicon Knowledge Extraction with Sentiment Polarity computation 16

Lexicon Knowledge Extraction with Sentiment Polarity Computa...

引用

16th IEEE international conference on Data Mining (ICDM)

作者： Wang, Zhaoxia Tong, Victor Joo Chuan Ruan, Pingcheng Li, Fang ASTAR Inst High Performance Comp Social & Cognit Comp Singapore Singapore Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9781509059102

Sentiment analysis is one of the most popular natural language processing techniques. It aims to identify the sentiment polarity (positive, negative, neutral or mixed) within a given text. the proper lexicon knowledge is very important for the lexicon-based sentiment analysis methods since they hinge on using the polarity of the lexical item to determine a text's sentiment polarity. However, it is quite common that some lexical items appear positive in the text of one domain but appear negative in another. In this paper, we propose an innovative knowledge building algorithm to extract sentiment lexicon knowledge through computing their polarity value based on their polarity distribution in text dataset, such as in a set of domain specific reviews. the proposed algorithm was tested by a set of domain microblogs. the results demonstrate the effectiveness of the proposed method. the proposed lexicon knowledge extraction method can enhance the performance of knowledge based sentiment analysis.

关键词： Sentiment analysis Lexicon knowledge extraction Natural Language Processing Domain knowledge building Chinese microblog Weibo

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Engineering Applications of Neural Networks - 16th international conference, EANN 2015, workshops and Selected Papers

Engineering Applications of Neural Networks - 16th Internati...

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16th international conference on Engineering Applications of Neural Networks, EANN 2015

the proceedings contain 44 papers. the topics discussed include: practical considerations in training extreme learning machines;enhancing the Levenberg-Marquardt method in neural network training using the direct computation of the error cost function;analysis of electricity bill data using interactive dimensionality reduction;characterization of DEM particles by means of artificial neural networks and macroscopic experiments;exploiting the use of ensemble classifiers to enhance the precision of user's emotion classification;a 24-h forecast of solar irradiance using echo state neural networks;horizon of neural network prediction of relativistic electrons flux in the outer radiation belt of the earth;seasonality of human behavior in smart buildings;a novel machine learning data preprocessing method for enhancing classification algorithms performance;and comparison of three classifiers for breast cancer outcome prediction.

关键词： Neural networks

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An efficient method for very large scale out-of-core terrain visualization

An efficient method for very large scale out-of-core terrain...

引用

16th international conference on Artificial Reality and Telexistence - workshops, ICAT 2006

作者： Zhang, Huijie Sun, Jigui Yu, Haihong Qi, Changsong College of Computer Science and Technology Jilin University College of Computer Science Northeast Normal University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education

ISBN: (纸本)076952754X

Large scale terrain visualization with high-resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. the hierarchical structure can decimate the elevation data that must be loaded into internal memory. thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. the comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio. © 2006 IEEE.

关键词： Efficiency

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computation Results of the Riemann Zeta Search Project 20

Computation Results of the Riemann Zeta Search Project

引用

20th international Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Tihanyi, Norbert Kovacs, Attila Eotvos Lorand Univ Fac Informat Dept Comp Algebra Budapest Hungary

ISBN: (纸本)9781728106250

the paper summarizes the computation results of the Riemann Zeta Search Project. the aim of the project was to find extremely large values of the Riemann zeta function on the critical line. the computing method is based on the RS-PEAK algorithm which was presented in the 16th SYNASC conference in 2014. the computation environment was served by the SZTAKI Desktop Grid operated by the Laboratory of Parallel and Distributed Systems at the Hungarian Academy of Sciences. Applying the RS-Peak algorithm 5597001 candidates were found where large values of the Riemann-Siegel Zfunction are expected. the largest known values are presented and published on the project website https://***.

关键词： Riemann zeta function Distributed computing Large Z(t) values

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Block-checksum-based Fault Tolerance for Matrix Multiplication on Large-Scale Parallel Systems 20

Block-checksum-based Fault Tolerance for Matrix Multiplicati...

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20th IEEE international conference on High Performance Computing and Communications (HPCC) / 16th IEEE international conference on Smart City (SmartCity) / 4th IEEE international conference on Data Science and Systems (DSS)

作者： Zhu, Yanchao Liu, Yi Li, Mingzhen Qian, Depei Beihang Univ Sino German Joint Software Inst Beijing Peoples R China

ISBN: (纸本)9781538666142

With the scaling up of high performance computers, resilience has become a big challenge. Among various kinds of software-based fault-tolerant approaches, the algorithm-based fault tolerance (ABFT) has some attractive characteristics in the era of exa-scale systems, such as high efficiency and light-weight. In particular, considering that many engineering and scientific applications rely on some fundamental algorithms, it is possible to provide algorithm-based fault-tolerant mechanisms in low level and make it application-independent. Previous fault-tolerant mechanisms for matrix computation use row and column checksums, which cannot be directly used in large-scale parallel systems. this paper proposes an algorithm-based fault tolerant approach for matrix multiplication on large-scale parallel systems. the mechanism uses block-checksum which not only meets the requirement of matrix computations on large-scale parallel systems but also reduces the overhead of fault-tolerance compared to traditional schemes based on row and column checksums. In addition, this paper gives method for choosing the size of blocks to achieve balance between accuracy and efficiency. the complexity analysis and examples demonstrate effectiveness and feasibility of our approach.

关键词： algorithm-based fault tolerance large-scale parallel system matrix multiplication matrix computation

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the Case for the Anonymization of Offloaded computation 16

The Case for the Anonymization of Offloaded Computation

引用

IEEE 16th international conference on Cloud Computing (IEEE CLOUD)

作者： Al Azad, Md Washik Sarwar, Shifat Taki, Sifat Ut Mastorakis, Spyridon Univ Notre Dame Notre Dame IN 46556 USA Univ Nebraska Omaha Omaha NE USA

ISBN: (纸本)9798350304817

computation offloading (often to external computing resources over a network) has become a necessity for modern applications. At the same time, the proliferation of machine learning techniques has empowered malicious actors to use such techniques in order to breach the privacy of the execution process for offloaded computations. this can enable malicious actors to identify offloaded computations and infer their nature based on computation characteristics that they may have access to even if they do not have direct access to the computation code. In this paper, we first demonstrate that even non-sophisticated machine learning algorithms can accurately identify offloaded computations. We then explore the design space of anonymizing offloaded computations through the realization of a framework, called Camouflage. Camouflage features practical mechanisms to conceal characteristics related to the execution of computations, which can be used by malicious actors to identify computations and orchestrate further attacks based on identified computations. Our evaluation demonstrated that Camouflage can impede the ability of malicious actors to identify executed computations by up to 60%, while incurring modest overheads for the anonymization of computations.

关键词： computation Anonymization Machine Learning computation Offloading Cloud Computing computation Graphs

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Automated Machine Learning using Evolutionary algorithms 16

Automated Machine Learning using Evolutionary Algorithms

引用

IEEE 16th international conference on Intelligent Computer Communication and Processing (ICCP)

作者： Anton, Mihai Babes Bolyai Univ Cluj Napoca Romania

ISBN: (数字)9781728190808

ISBN: (纸本)9781728190808

As the global data quantity already follows an exponential trend, machine learning has become present in every application, creating a great demand for general know-how, be it data scientists or computer scientists with related knowledge. Currently, the demand for work to be done surpasses the offer of such professionals, thus automatic solutions have to be found. the classical machine learning process involves data engineering, model selection, and hyperparameter tuning for the chosen model. Due to the highly repetitive nature of trial and error of these tasks, automation can play a big role in optimizing time spent on them. Automated Machine Learning comes to help the process by adding different optimization techniques that help data scientists be more productive and achieve similar or better results in a shorter time. this paper provides a novel approach to Automated Machine Learning using Evolutionary algorithms and proves Its performance by presenting top results in benchmark tests.

关键词： Machine learning Optimization Evolutionary computation Machine learning algorithms Data models Task analysis Statistics

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Track Loss versus computation Time Dilemma in Multitarget Ground Target Tracking Performance

Track Loss versus Computation Time Dilemma in Multitarget Gr...

引用

16th international conference on Information Fusion (FUSION)

作者： Korkmaz, Yusuf Baykal, Buyurman Middle E Tech Univ Dept Elect & Elect Engn TR-06531 Ankara Turkey

ISBN: (纸本)9786058631113

Tracking of multiple ground targets with airborne Ground Moving Target Indicator (GMTI) sensor measurements is a challenging problem where heavy and dense false alarms with high target density are inevitably encountered in the surveillance scenes. Hence, optimal approaches require heavy computational load where the duration of overall computation rises exponentially with the number of target tracks and measurements in observation per scan. Consequently, more practical suboptimal approaches, such as Linear Multi-Target (LM) approach, is explored due to linear number of operations in the number of target tracks with a negligible performance loss compared to optimal approaches. Although LM approach performs modestly adequate with significantly less computation duration than optimal approaches, it is highly susceptible to track loss, as in the rest of suboptimal approaches, when the targets are closely spaced and the number of targets and measurements are considerably high. Simulations are carried out in realistic test scenarios to compare single target tracking algorithms including IMM-PDA and IMM-IPDA algorithms;Optimal approaches in multitarget tracking including IMM-JPDA, IMM-IJPDA and IMM-JIPDA algorithms and an example of Linear Multi-target approaches in multitarget tracking including IMM-LMIPDA algorithm. Benchmarkings of these algorithms are done under RMSE performance, track loss and computation time evaluation results.

关键词： Target tracking multiple target tracking Targets algorithms operation number computational time Track ground Heavy Dilemma

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algorithms and architectures for parallel processing: ICA3PP 2016 collocated workshops: SCDT, TAPEMS, BigTrust, UCER, DLMCS Granada, Spain, December 14-16, 2016 proceedings 16th

Algorithms and architectures for parallel processing: ICA3PP...

引用

16th international conference on algorithms and Architectures for Parallel Processing - ICA3PP 2016 Collocated workshops: 1st Workshop on Supercomputing Co-Design Technology, SCDT-2016, 1st international Workshop on theoretical Approaches to Performance Evaluation, Modeling and Simulation, TAPEMS 2016, 1st international Workshop on Trust, Security and Privacy for Big Data, BigTrust 2016, 1st edition of the workshop on Ultrascale Computing for Early Researchers, UCER 2016 and 1st international Workshop on Data Locality in Modern Computing Systems, DLMCS 2016

作者： Carretero, Jesus

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