Search Results - (( data visualization using algorithm ) OR ( using vector problem algorithm ))
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Proceeding Paper -
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Subspace Techniques for Brain Signal Enhancement
Published 2009“…Next, the validity and the effectiveness of the algorithms to detect the P100's (used in objective assessment of visual pathways) are evaluated using real patient data collected from a hospital. …”
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Book Section -
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DCT domain stegasvm-shifted LSB model for highly imperceptible and robust cover-image
Published 2015“…The importance of information security in protecting and hiding information has increased due to the increased use of computers and Internet.Information hiding technology such as Digital Image steganography embeds secret messages inside other files.Least Square Bit (LSB) is the most popular technique used in image steganography that hides data behind a cover-image in a spatial and discrete cosine transform (DCT) domain.Support Vector Machine (SVM) is another technique that is used to strengthen the embedding algorithm.The main aim of image steganography is to keep the secret-message remain secret regardless of the techniques used.But many of the previously proposed techniques failed to attain this aim.The main concerns to this problem are the non-random changes of a cover-image that constantly occurred after the embedding process and the non-robustness of the embedding algorithm to image processing operation.This study therefore proposes a new model that utilises Human Visual System (HVS) and embedding technique through shifted LSB called StegaSVM-Shifted LSB in DCT domain to preserve the imperseptibility and increase the robustness of stego-images.The proposed technique shows better performances compared to other existing techniques.…”
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Conference or Workshop Item -
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Thesis -
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Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia
Published 2019“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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Thesis -
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Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
Published 2012“…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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Conference or Workshop Item -
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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Thesis -
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Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions
Published 2013“…The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. …”
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Article -
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A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)
Published 2009“…However, it is impractical to solve MOOP by using classical methods due to its complexity. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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Final Year Project Report / IMRAD -
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A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport
Published 2017“…To solve the problem, a test vector minimizer algorithm is proposed to eliminate redundant test vectors that do not contribute to reproduction of a test failure, hence, improving the debug throughput. …”
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Thesis -
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Conference or Workshop Item -
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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Thesis -
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Risk assessment of dengue in Betong Sarawak using simple mathematical model
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Student Project -
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Improving performance of mobile ad hoc networks using efficient Tactical On Demand Distance Vector (TAODV) routing algorithm
Published 2012“…The proposed TAODV algorithm performs better for solving routing problems in Mobile Ad Hoc networks. …”
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Article -
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Convergence and Diversity Evaluation for Vector Evaluated Particle Swarm Optimization
Published 2013“…An extended PSO algorithm called Vector Evaluated Particle Swarm Optimization (VEPSO) has been introduced to solve multi-objective optimization problems. …”
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Conference or Workshop Item -
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization
Published 2013“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Article -
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The Development Of System For Algorithms Visualization Using Simjava
Published 2020“…Algorithms are a captivating use case for visualization. …”
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