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  • Open Access


    Design of ANN Based Non-Linear Network Using Interconnection of Parallel Processor

    Anjani Kumar Singha1, Swaleha Zubair1, Areej Malibari2, Nitish Pathak3, Shabana Urooj4,*, Neelam Sharma5

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3491-3508, 2023, DOI:10.32604/csse.2023.029165

    Abstract Suspicious mass traffic constantly evolves, making network behaviour tracing and structure more complex. Neural networks yield promising results by considering a sufficient number of processing elements with strong interconnections between them. They offer efficient computational Hopfield neural networks models and optimization constraints used by undergoing a good amount of parallelism to yield optimal results. Artificial neural network (ANN) offers optimal solutions in classifying and clustering the various reels of data, and the results obtained purely depend on identifying a problem. In this research work, the design of optimized applications is presented in an organized manner.… More >

  • Open Access


    Parallel Iterative FEM Solver with Initial Guess for Frequency Domain Electromagnetic Analysis

    Woochan Lee1, Woobin Park1, Jaeyoung Park2, Young-Joon Kim3, Moonseong Kim4,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1585-1602, 2023, DOI:10.32604/iasc.2023.033112

    Abstract The finite element method is a key player in computational electromagnetics for designing RF (Radio Frequency) components such as waveguides. The frequency-domain analysis is fundamental to identify the characteristics of the components. For the conventional frequency-domain electromagnetic analysis using FEM (Finite Element Method), the system matrix is complex-numbered as well as indefinite. The iterative solvers can be faster than the direct solver when the solver convergence is guaranteed and done in a few steps. However, such complex-numbered and indefinite systems are hard to exploit the merit of the iterative solver. It is also hard to… More >

  • Open Access


    Key-Value Store Coupled with an Operating System for Storing Large-Scale Values

    Jeonghwan Im1, Hyuk-Yoon Kwon2,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3333-3350, 2022, DOI:10.32604/cmc.2022.029566

    Abstract The key-value store can provide flexibility of data types because it does not need to specify the data types to be stored in advance and can store any types of data as the value of the key-value pair. Various types of studies have been conducted to improve the performance of the key-value store while maintaining its flexibility. However, the research efforts storing the large-scale values such as multimedia data files (e.g., images or videos) in the key-value store were limited. In this study, we propose a new key-value store, WR-Store++ aiming to store the large-scale… More >

  • Open Access


    Moving Object Detection and Tracking Algorithm Using Hybrid Decomposition Parallel Processing

    M. Gomathy Nayagam1,*, K. Ramar2, K. Venkatesh3, S. P. Raja4

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1485-1499, 2022, DOI:10.32604/iasc.2022.023953

    Abstract Moving object detection, classification and tracking are more crucial and challenging task in most of the computer vision and machine vision applications such as robot navigation, human behavior analysis, traffic flow analysis and etc. However, most of object detection and tracking algorithms are not suitable for real time processing and causes slower processing speed due to the processing and analyzing of high resolution video from high-end multiple cameras. It requires more computation and storage. To address the aforementioned problem, this paper proposes a way of parallel processing of temporal frame differencing algorithm for object detection More >

  • Open Access


    Building a Trust Model for Secure Data Sharing (TM-SDS) in Edge Computing Using HMAC Techniques

    K. Karthikeyan*, P. Madhavan

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4183-4197, 2022, DOI:10.32604/cmc.2022.019802

    Abstract With the rapid growth of Internet of Things (IoT) based models, and the lack amount of data makes cloud computing resources insufficient. Hence, edge computing-based techniques are becoming more popular in present research domains that makes data storage, and processing effective at the network edges. There are several advanced features like parallel processing and data perception are available in edge computing. Still, there are some challenges in providing privacy and data security over networks. To solve the security issues in Edge Computing, Hash-based Message Authentication Code (HMAC) algorithm is used to provide solutions for preserving More >

  • Open Access


    Enhanced GPU-Based Anti-Noise Hybrid Edge Detection Method

    Sa’ed Abed, Mohammed H. Ali, Mohammad Al-Shayeji

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

    Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically.… More >

  • Open Access


    Core – An Optimal Data Placement Strategy in Hadoop for Data Intentitive Applications Based on Cohesion Relation

    Vengadeswaran, Balasundaram

    Computer Systems Science and Engineering, Vol.34, No.1, pp. 47-60, 2019, DOI:10.32604/csse.2019.34.047

    Abstract The tremendous growth of data being generated today is making storage and computing a mammoth task. With its distributed processing capability Hadoop gives an efficient solution for such large data. Hadoop’s default data placement strategy places the data blocks randomly across the nodes without considering the execution parameters resulting in several lacunas such as increased execution time, query latency etc., Also, most of the data required for a task execution may not be locally available which creates data-locality problem. Hence we propose an innovative data placement strategy based on dependency of data blocks across the More >

  • Open Access


    Real-Time Hybrid Simulation of Seismically Isolated Structures with Full-Scale Bearings and Large Computational Models

    Alireza Sarebanha1,*, Andreas H. Schellenberg2, Matthew J. Schoettler3, Gilberto Mosqueda4, Stephen A. Mahin

    CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 693-717, 2019, DOI:10.32604/cmes.2019.04846

    Abstract Hybrid simulation can be a cost effective approach for dynamic testing of structural components at full scale while capturing the system level response through interactions with a numerical model. The dynamic response of a seismically isolated structure depends on the combined characteristics of the ground motion, bearings, and superstructure. Therefore, dynamic full-scale system level tests of isolated structures under realistic dynamic loading conditions are desirable towards a holistic validation of this earthquake protection strategy. Moreover, bearing properties and their ultimate behavior have been shown to be highly dependent on rate-of-loading and scale size effects, especially… More >

  • Open Access


    Solution Methods for Nonsymmetric Linear Systems with Large off-Diagonal Elements and Discontinuous Coefficients

    Dan Gordon1, Rachel Gordon2

    CMES-Computer Modeling in Engineering & Sciences, Vol.53, No.1, pp. 23-46, 2009, DOI:10.3970/cmes.2009.053.023

    Abstract Linear systems with very large off-diagonal elements and discontinuous coefficients (LODC systems) arise in some modeling cases, such as those involving heterogeneous media. Such problems are usually solved by domain decomposition methods, but these can be difficult to implement on unstructured grids or when the boundaries between subdomains have a complicated geometry. Gordon and Gordon have shown that Björck and Elfving's (sequential) CGMN algorithm and their own block-parallel CARP-CG are very robust and efficient on strongly convection dominated cases (but without discontinuous coefficients). They have also shown that scaling the equations by dividing each equation… More >

  • Open Access


    Multiscale Simulations Using Generalized Interpolation Material Point (GIMP) Method And SAMRAI Parallel Processing

    J. Ma1, H. Lu1, B. Wang1, S. Roy1, R. Hornung2, A. Wissink2, R. Komanduri1,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.8, No.2, pp. 135-152, 2005, DOI:10.3970/cmes.2005.008.135

    Abstract In the simulation of a wide range of mechanics problems including impact/contact/penetration and fracture, the material point method (MPM), Sulsky, Zhou and Shreyer (1995), demonstrated its computational capabilities. To resolve alternating stress sign and instability problems associated with conventional MPM, Bardenhagen and Kober (2004) introduced recently the generalized interpolation material point (GIMP) method and implemented for one-dimensional simulations. In this paper we have extended GIMP to 2D and applied to simulate simple tension and indentation problems. For simulations spanning multiple length scales, based on the continuum mechanics approach, we present a parallel GIMP computational method… More >

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