Search Results - (( data replication methods algorithm ) OR ( parallel estimation research algorithm ))
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Dynamic replication algorithm in data grid: Survey
Published 2008“…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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Parallel visualization approach of a 3D heart model
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Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment
Published 2022“…In order to mitigate the issues, ‘cloud data replication’ is commonly implemented for better data performance and promising business continuity. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The motivation of implementation is to make sure the data replication is easy to maintain and cost effective. …”
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Early detection of breast cancer using wave elliptic equation with high performance computing
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Investigation of QAM based on mean square error (MSE) channel estimation (CE) for MIMO-OFDM pilot based system / Mohd Ariff Ibrahim
Published 2013“…There is Channel Estimation (CE) which consists of different statement to obtain high gain and a better performance of Bit Error Rate (BER). …”
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Extended Kalman Filter (EKF)-based modular-stack Vanadium Redox Flow Battery (V-RFB) prediction model development for reducing electrode contact resistance and parallelization curr...
Published 2019“…Further works are presented for future research in geometry study of V-RFB.…”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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Iterative methods for solving split common fixed point problems in Hilbert spaces
Published 2016“…In other words, we construct parallel and cyclic algorithms for solving the split common fixed point problems for strictly pseudocontractive mappings and prove the convergence results of these algorithms. …”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin
Published 2025“…These findings indicate a high level of predictive accuracy, showcasing the robustness of the model in estimating condominium prices. This research will lead to the enrichment of our understanding of how various factors affect condominium prices, with the hope that users will become more informed in their real estate market decisions. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…The FBTS integrated with automated edge-preserving regularization algorithm is implemented in C++ programming language executed in parallel computing. …”
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…Reaching super resolution has been a challenge in image processing practices, because of their under-constrained nature that requires the missing HR image details to be reconstructed. In this research, the long-established single-image super-resolution problem is addressed by integrating the multiresolution property of Wavelet and the flexibility of Locally Anchored Neighbourhood Regression model to formulate a novel edgebased single image super resolution algorithm that allows robust estimation of missing frequency details in wavelet domain with complete enhancement procedure. …”
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