In this paper, a Hadoop MapReduce framework is presented in order to perform distributedprocessing used for CBIR system. Moreover, Hadoop MapReduce framework is used with the intention of increasing the performance o...
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ISBN:
(纸本)9781479922574
In this paper, a Hadoop MapReduce framework is presented in order to perform distributedprocessing used for CBIR system. Moreover, Hadoop MapReduce framework is used with the intention of increasing the performance of two main functionalities of data insertion and query processing. Therefore, the main objective of the study is distribution of the image data over a large number of nodes. Some of the techniques used in the paper includes: image indexing and retrieval, parallelprocessing of indexing, and comparing the similarity of retrieved images
The current trend of distributing computations over a network is here, as a novelty, applied to a safety critical system, namely a railway interlocking system. We show how the challenge of guaranteeing safety of the d...
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ISBN:
(纸本)9781509060580
The current trend of distributing computations over a network is here, as a novelty, applied to a safety critical system, namely a railway interlocking system. We show how the challenge of guaranteeing safety of the distributed application has been attacked by formally specifying and model checking the relevant distributed protocols. By doing that we obey the safety guidelines of the railway signalling domain, that require formal methods to support the certification of such products. We also show how formal modelling can help designing alternative distributed solutions, while maintaining adherence to safety constraints.
image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a novel IQFT-inspired algorithm is propo...
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ISBN:
(纸本)9798350311990
image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a novel IQFT-inspired algorithm is proposed and implemented by leveraging the underlying mathematical structure of the IQFT. Specifically, the proposed method takes advantage of the phase information of the pixels in the image by encoding the pixels' intensity into qubit relative phases and applying IQFT to classify the pixels into different segments automatically and efficiently. To the best of our knowledge, this is the first attempt of using IQFT for unsupervised image segmentation. The proposed method has low computational cost comparing to the deep learning based methods and more importantly it does not require training, thus make it suitable for real-time applications. The performance of the proposed method is compared with K-means and Otsuthresholding. The proposed method outperforms both of them on the PASCAL VOC 2012 segmentation benchmark and the xVIEW2 challenge dataset by as much as 50% in terms of mean Intersection-Over-Union (mIOU).
The triangular Shepard interpolation method is an extension of the well-known bivariate Shepard's method for interpolating large sets of scattered data. In particular, the classical point-based weight functions ar...
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ISBN:
(纸本)9781665469586
The triangular Shepard interpolation method is an extension of the well-known bivariate Shepard's method for interpolating large sets of scattered data. In particular, the classical point-based weight functions are substituted by basis functions built upon triangulation of the scattered points. As shown in the literature, this method exhibits advantages with respect to other interpolation methods for interpolating scattered bivariate data. Nevertheless, as the size of the data set increases, an efficient implementation of the method becomes more and more necessary. In this paper, we present a parallel implementation of the triangular Shepard interpolation method that beside exploiting benefits due to the parallelization itself, introduces a novel approach for the triangulation of the scattered data.
With the increasing importance of multiple multiplaform remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Firstly, an...
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ISBN:
(纸本)0769523803
With the increasing importance of multiple multiplaform remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Firstly, an overview of development of automatic and parallel global image registration is given. And then, based on the analyses of existing three parallelmethods of wavelet-based global registration, a new parallel strategy is proposed. Moreover, towards the quantitative evaluation, first results of the intercomparision of four parallel global registration algorithms are presented in theory and in experiments.
At present, with the rapid development of big data processing technology, streaming data processing and real-time data analysis have gradually become new research hotspots. Both the industry and the academia have inve...
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ISBN:
(纸本)9781538673089
At present, with the rapid development of big data processing technology, streaming data processing and real-time data analysis have gradually become new research hotspots. Both the industry and the academia have invested a lot of research into the efficient processingmethods of massive data generated in the environment such as the Internet and e-commerce. Meanwhile, high-performance computing technology and supercomputers are also looking for new business growth points. The convergence of big data processing and high performance computing technology is the general trend of big data analysis in the future. This paper will give a brief overview of typical technologies in the fusion process of big data processing and high-performance computing.
As the algorithms that are used to reconstruct medical images from measurable projection data continue to become mature, medical image reconstruction has remained an interesting and important topic to medical research...
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ISBN:
(纸本)1932415262
As the algorithms that are used to reconstruct medical images from measurable projection data continue to become mature, medical image reconstruction has remained an interesting and important topic to medical researcher. The main challenge in medical image reconstruction is how to establish an economical and efficient computing system that can be used to perform. fast image reconstructions. In this paper, we present a distributed computing system that is based on P2P technologies;and demonstrate how the design and implementation of this system addresses the challenge through a case study of an iterative EM medical image reconstruction algorithm. Computational experiments are designed to study the performance of the EM algorithm using the system. In the aggregate, this study provides an insights into the large-scale computation of iterative medical image reconstruction in a Grid environment.
parallelprocessing of thresholding based on image between-class variance (BCV) is studied in this paper. In parallelprocessing, a frame of image is divided into M sub-images with the same size. Computation of the no...
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Cellular Automata (CA) are parallel models well suited for studying complex systems that are based on local rules of evolution. Notable examples of application are found in fluid-dynamics, crowd simulation, flow-simul...
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ISBN:
(纸本)9781728165820
Cellular Automata (CA) are parallel models well suited for studying complex systems that are based on local rules of evolution. Notable examples of application are found in fluid-dynamics, crowd simulation, flow-simulation and many more. Nevertheless, CA can be fruitfully exploited as a support in numerical approaches, such as finite element and finite volume methods. Though easily parallelizable by domain partitioning among the nodes of a parallel system, the performance and scalability of cellular automata executed on parallel/distributed machines are limited due to the need of synchronizing nodes at each computational step. With the aim of reducing the synchronization burden, we here present a preliminary study on techniques stemmed from the Discrete Event Simulation field for the optimization of CA on distributed memory architectures. Preliminary results, executed in a distributed memory environment, have shown the usefulness of the considered approach in reducing execution times and therefore in improving the speed up of the parallel execution of the test case.
In object-based systems, objects supporting abstract methods are replicated to increase the performance, reliability, and availability. We discuss a novel object-based locking (OBL) protocol to lock replicas of object...
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ISBN:
(纸本)0818686030
In object-based systems, objects supporting abstract methods are replicated to increase the performance, reliability, and availability. We discuss a novel object-based locking (OBL) protocol to lock replicas of objects by extending the quorum-based protocol for read and write to abstract methods. Unless two methods conflict, subsets of the replicas locked by the methods do not intersect even if the methods change the replicas. methods not computed on a replica A but computed on another replica are computed on, if when a method conflicting with the methods are issued to A in the OBL protocol. We newly propose a version vector to identify what methods are computed on a replica.
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