Search Results - (( parallel estimation method algorithm ) OR ( processes evaluation method algorithm ))
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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“…The model is highly practical and easy to interpret, making it very suitable for real-world applications. The methods used in this simulation study will be summarized within a comprehensive report, along with the process used in evaluating the appropriateness of using search heuristics in tandem with parallel systems and prospective real-world applications. …”
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Cryptanalysis on the modulus N=p2q and design of rabin-like cryptosystem without decryption failure
Published 2015“…We then conduct a comparative analysis toward estimating the running time during the encryption and decryption process. …”
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Parallel visualization approach of a 3D heart model
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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems
Published 2016“…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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Early detection of breast cancer using wave elliptic equation with high performance computing
Published 2008“…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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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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Image reconstruction using iterative transpose algorithm for optical tomography
Published 2007“…This paper describes a transpose algorithm for use with an optical tomography system. …”
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Evaluation of dynamic programming among the existing stereo matching algorithms
Published 2015“…This can propose the dynamic programming method to be used on many applications in image processing.…”
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…In addition, the weight of importance is critical for evaluating the performance of MaOO algorithms. All evaluation studies for MaOO algorithms have ignored to assign such weight for the target criteria during evaluation process. …”
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Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended so...
Published 2020“…Evaluation and benchmarking of many-objective optimization (MaOO) methods are complicated. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The tone mapping algorithm was first compressed using global tone mapping method. …”
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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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Adopting AHP in evaluating nurse scheduling methods
Published 2004“…When comparing and evaluating two or more scheduling methods the need to use a multiple criteria decision making technique arises.Instead of just employing a qualitative approach of evaluating the methods, one can integrate the qualitative and the quantitative data in the evaluation process through the use of the analytic hierarchy process (AHP).Hence, this paper reports the evaluation of two nurse scheduling methods where the AHP technique is employed to support the selection process of these methods.Five decision criteria are used in the process.The main objective of the scheduling methods (models) is to assign work shifts and off days of the nurses in a particular hospital unit such that, it fulfils certain specified constraints while ensuring continuous high-quality patient care services.The first method is a heuristic procedure that is currently in practice.The other one is a prototype in which a memetic algorithm is adopted in the approach.The application of AHP has been found to provide a better transparency of the capability and efficiency of the scheduling methods. …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images
Published 2018“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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