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16th Prague Stringology Conference (PSC)

作者： Cinque, Luigi De Agostino, Sergio Lombardi, Luca Univ Roma La Sapienza Dept Comp Sci I-00198 Rome Italy Univ Pavia Dept Comp Sci I-27100 Pavia Italy

ISBN: (纸本)9788001048702

A method for compressing binary images is monochromatic pattern substitution. Monochromatic rectangles inside the image are detected and compressed by a variable length code. Such method has no relevant loss of compression effectiveness if the image is partitioned into up to a thousand blocks and each block is compressed independently. Therefore, it can be implemented in parallel on both small and large scale arrays of processors with distributed memory and no interconnections. We show in this paper that such method has a speed-up if applied sequentially to the partitioned image. Experimental results show that the speed-up happens if the image is partitioned into up to 256 blocks and sequentially each block is compressed independently. It follows that the sequential speed-up can also be applied to a parallel implementation on a small scale system.

关键词： lossless compression binary image sequential algorithm parallel computing distributed system

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Image mosaicing using sequential bundle adjustment

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IMAGE AND VISION COMPUTING 2002年第9-10期20卷 751-759页

作者： McLauchlan, PF Jaenicke, A Univ Surrey Sch EE IT & Math Guildford GU2 7XH Surrey England

We describe the construction of accurate panoramic mosaics from multiple images taken with a rotating camera, or alternatively of a planar scene. The novelty of the approach lies in (i) the transfer of photogrammetric bundle adjustment techniques to mosaicing;(ii) a new representation of image line measurements enabling the use of lines in camera self-calibration, including computation of the radial and other non-linear distortion;and (iii) the application of the variable state dimension filter to obtain efficient sequential updates of the mosaic as each image is added. We demonstrate that our method achieves better results than the alternative approach of optimising over pairs of images. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： bundle adjustment mosaic sequential algorithm recursive algorithm

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Image mosaicing using sequential bundle adjustment

Image mosaicing using sequential bundle adjustment

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11th British Machine Vision Conference (BMVC2000)

作者： McLauchlan, PF Jaenicke, A Univ Surrey Sch EE IT & Math Guildford GU2 7XH Surrey England

关键词： bundle adjustment mosaic sequential algorithm recursive algorithm

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Distributed Chunk-Based Framework for Parallelization of sequential Computer Vision algorithms on Video Big-Data 9

Distributed Chunk-Based Framework for Parallelization of Seq...

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9th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

作者： Buckla, Norhan Rehan, Mohamed Fahmy, Hossam AvidBeam Technol Cairo Egypt Cairo Univ Fac Engn Cairo Egypt

ISBN: (纸本)9781538672662

In this paper we propose a complete framework that enables big-data tools to execute sequential computer vision algorithms in a scalable and parallel mechanism with limited modifications. Our main objective is to parallelize the processing operation in order to speed up the required processing time. Most of the present big-data processing frameworks distribute the input data randomly across the available processing units to utilize them efficiently and preserve working load fairness. Therefore, the current big-data frameworks are not suitable for processing huge video data content due to the existence of interframe dependency. When processing such sequential computer vision algorithms on big-data tools, splitting the video frames and distributing them on the available cores will not yield the correct output and will lead to inefficient usage of underlying processing resources. Our proposed framework divides the input big-data video files into small chunks that can be processed in parallel without affecting the quality of the resulting output. An intelligent data grouping algorithm was developed to distribute these data chunks among the available processing resources and gather the results out of each chunk using Apache Storm. The proposed framework was evaluated against several computer vision algorithms and achieved a speedup from 2.6x up to 8x based on the algorithm.

关键词： Big-Data Computer Vision Parallel Computing Video Processing sequential algorithm

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APPLICATION OF SURROGATE BASED PARTICLE SWARM OPTIMIZATION TO THE RELIABILITY-BASED ROBUST DESIGN OF COMPOSITE PRESSURE VESSELS

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Acta Mechanica Solida Sinica 2013年第5期26卷 480-490页

作者： Jianqiao Chen Yuanfu Tang Xiaoxu Huang Department of Mechanics Hubei Key Laboratory of Engineering Structural Analysis and Safety AssessmentHuazhong University of Science and Technology

A surrogate based particle swarm optimization （SBPSO） algorithm which combines the surrogate modeling technique and particle swarm optimization is applied to the reliability- based robust design （RBRD） of composite pressure vessels. The algorithm and efficiency of SBPSO are displayed through numerical examples. A model for filament-wound composite pressure vessels with metallic liner is then studied by netting analysis and its responses are analyzed by using Finite element method （performed by software ANSYS）. An optimization problem for maximizing the performance factor is formulated by choosing the winding orientation of the helical plies in the cylindrical portion, the thickness of metal liner and the drop off region size as the design variables. Strength constraints for composite layers and the metal liner are constructed by using Tsai-Wu failure criterion and Mises failure criterion respectively. Numerical examples show that the method proposed can effectively solve the RBRD problem, and the optimal results of the proposed model can satisfy certain reliability requirement and have the robustness to the fluctuation of design variables.

关键词： structural optimization reliability based robust design composite pressure vessel,surrogate based particle swarm optimization sequential algorithm

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A D-Optimal Design for Estimation of Parameters of an Exponential-Linear Growth Curve of Nanostructures

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TECHNOMETRICS 2014年第4期56卷 432-442页

作者： Zhu, Li Dasgupta, Tirthankar Huang, Qiang Harvard Univ Dept Stat Cambridge MA 02138 USA Univ So Calif Dept Ind & Syst Engn Los Angeles CA 90089 USA

We consider the problem of determining an optimal experimental design for estimation of parameters of a class of complex curves characterizing nanowire growth that is partially exponential and partially linear. Locally D-optimal designs for some of the models belonging to this class are obtained by using a geometric approach. Further, a Bayesian sequential algorithm is proposed for obtaining D-optimal designs for models with a closed-form solution, and for obtaining efficient designs in situations where theoretical results cannot be obtained. The advantages of the proposed algorithm over traditional approaches adopted in recently reported nanoexperiments are demonstrated using Monte Carlo simulations. The computer code implementing the sequential algorithm is available as supplementary materials.

关键词： sequential algorithm Bayesian design Nonlinear model

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Step graphs and their application to the organization of commodity flows in networks

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JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL 2016年第2期55卷 222-231页

作者： Grinberg, Ya. R. Russian Acad Sci Kharkevich Inst Informat Transmiss Problems Bolshoi Karetnyi Per 19 Moscow 127051 Russia

The concepts of step graphs and networks in which the edges are divided into ordered classes (shortage classes) are introduced. Each path in such graphs is assigned a tuple (an ordered sequence of nonnegative integers). The tuples are compared lexicographically. The problem of finding the path with the minimum tuple according to this ordering is stated. Functionals are compared using the lexicographic rule. An algorithm for finding the optimal path is described, and the relationship between step networks and weighted networks is investigated. The proposed formalism is applied to the problem of filling a network subject to constraints imposed on communication line capacities with communication flows under the condition that requests for the organization of such flows arrive to the network sequentially in time and the filling strategy must maximize the number of satisfied requests. The idea of an algorithm for the approximate solution of the integer multicommodity problem that uses the concepts of step networks and sequential algorithms is proposed.

关键词： Organizations Satisfaction sequential algorithm tuple commodities optimal path Network FUNCTIONALS

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Threshold group testing with consecutive positives

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DISCRETE APPLIED MATHEMATICS 2014年 169卷 68-72页

作者： Chang, Huilan Tsai, Yi-Lin Natl Univ Kaohsiung Dept Appl Math Kaohsiung 811 Taiwan

Threshold group testing introduced by Damaschke (2006) is a generalization of classical group testing where a group test yields a positive (negative) outcome if it contains at least u (at most!) positive items, and an arbitrary outcome for otherwise. Motivated by applications to DNA sequencing, group testing with consecutive positives has been proposed by Balding and Torney (1997) and Colbourn (1999) where n items are linearly ordered and up to d positive items are consecutive in the order. In this paper, we introduce threshold-constrained group tests to group testing with consecutive positives. We prove that all positive items can be identified in [log(2)(n/u-1)] + 2[log(2)(u+2)] +log(2)(u+ 1)]-2 tests for the gap-free case (u = l+1) while the information-theoretic lower bound is [log(2) n(d- u+1)]-1 when n >= d+u-2 and for u = 1 the best adaptive algorithm provided by Juan and Chang (2008) takes at most rlog2 ni rlog2 di tests. We further show that the case with a gap (u > l + 1) can be dealt with by the subroutines used to conquer the gap-free case. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Group testing sequential algorithm Threshold Consecutive positives

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SYNTHESIZING LINEAR-ARRAY algorithmS FROM NESTED FOR LOOP algorithmS

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IEEE TRANSACTIONS ON COMPUTERS 1988年第12期37卷 1578-1598页

作者： LEE, P KEDEM, ZM Dept. of Comput. Sci. Courant Inst. of Math. Sci. New York Univ. NY USA

The mapping of algorithms structured as depth-p nested FOR loops into special-purpose systolic VLSI linear arrays is addressed. The mappings are done by using linear functions to transform the original sequential algorithms into a form suitable for parallel execution on linear arrays. A feasible mapping is derived by identifying formal criteria to be satisfied by both the original sequential algorithm and the proposed transformation function. The methodology is illustrated by synthesizing algorithms for matrix multiplication and a version of the Warshall-Floyd transitive closure algorithm

关键词： sequential algorithm WWOX gene algorithms linear function linear arrays Loops parallel execution Matrix multiplication transformation function

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A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2007年第4期13卷 337-351页

作者： Sbihi, Abdelkader Univ Lancaster Sch Management Optimisat Res Ctr Lancaster LA1 4YX England

In this paper, we propose an optimal algorithm for the Multiple-choice Multidimensional Knapsack Problem MMKP. The main principle of the approach is twofold: (i) to generate an initial feasible solution as a starting lower bound, and (ii) at different levels of the search tree to determine an intermediate upper bound obtained by solving an auxiliary problem called MMKPaux and perform the strategy of fixing items during the exploration. The approach which we develop is of best-first search strategy. The method was able to optimally solve the MMKP. The performance of the exact algorithm is evaluated on a set of small and medium instances, some of them are extracted from the literature and others are randomly generated. This algorithm is parallelizable and it is one of its important feature.

关键词： combinatorial optimization branch and bound sequential algorithm Knapsack

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