Zainor Ridzuan Yahya
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Preferred name
Zainor Ridzuan Yahya
Official Name
Zainor Ridzuan, Yahya
Alternative Name
Yahya, Zainor Ridzuan
Yahya, Z. R.
Ridzuan Yahya, Zainor
Main Affiliation
Scopus Author ID
50862369800
Researcher ID
GNH-4483-2022

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Artificial bee colony for curve reconstruction using quartic bézier

2022-03-31 , Nur' Afifah Rusdi , Zainor Ridzuan Yahya , Wan Zuki Azman Wan Muhamad , Nurshazneem Roslan

This work presents the use of Artificial Bee Colony Algorithm (ABC) for curve reconstruction using Quartic Bézier. Quartic Bézier curve is rarely used by the researchers in the application of medical images. Therefore, by increasing the degree of the Bézier curve, a better curve with small error can be obtain. The process of curve reconstruction involved was boundary and corner point detection of the medical image, parameterization and curve reconstruction by using ABC. By applying these processes, the fitted Quartic Bézier is obtained. The Sum Square Error (SSE) is used to record the error between the fitted Quartic Bézier curve with the original image. The results of SSE is recorded after the process is repeated 10 times with the average error of 3.4463e03 . Because the final output of the fitted curve resembles the original image, the suggested method can be considered as an option method for curve reconstruction applications. ABC algorithm is an interesting algorithm that can be explored in more detail and can be applied in various problems.

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Shape preserving data interpolation using rational cubic ball functions

2015 , Ayser Nasir Hassan Tahat , Abd Rahni Mt Piah , Zainor Ridzuan Yahya

A smooth curve interpolation scheme for positive, monotone, and convex data is developed.This scheme uses rational cubic Ball representation with four shape parameters in its description. Conditions of two shape parameters are derived in such a way that they preserve the shape of the data, whereas the other two parameters remain free to enable the user to modify the shape of the curve. The degree of smoothness is 𝐶1.The outputs from a number of numerical experiments are presented.

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Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset

2023 , Chow Yong Huan , Wan Zuki Azman Wan Muhamad , Zainor Ridzuan Yahya , Nor Hizamiyani Abdul Azziz , Tan Chye Lih , Tan Xiao Jian

The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisation process. To address this issue, the Binary Whale Optimisation Algorithm (BWOA) is proposed as an improved search algorithm for MTS. This paper aims to develop a novel hybrid method that enhances the efficiency of the Mahalanobis Taguchi System (MTS). The performance of feature selection ability due to different MTS hybrid algorithms were also compared. BWOA simulates the hunting behaviour of humpback whales and works by exploring new regions of the solution space, gradually narrowing the search space, and fine-tuning the solution. MTS-BWOA demonstrated its enhanced capability in feature optimisation compared to traditional MTS methods and has the potential to be applied in other medical imaging domains.

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Iteration Variational Method for Solving Two-Dimensional Partial Integro-Differential Equations

2020-08-13 , Hussain A.K. , Fadhel F.S. , Nursalasawati Rusli , Zainor Ridzuan Yahya

The two-dimensional integro-differential partial equations is one of the so difficult problems to be solved analytically and/or approximately, and therefore, a method that is efficient for solving such type of problems seems to be necessary. Therefore, in this paper, the iteration methods, which is so called the variational iteration method have been used to provide a solution to such type of problems approximately, in which the obtained results are very accurate in comparison with the exact solution for certain well selected examples which are constructed so that the exact solution exist. Main results of this work is to derive first the variational iteration formula and then analyzing analytically the error term and prove its convergence to zero as the number of iteration increases.

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Confusion matrix as performance measure for corner detectors

2022-01-01 , Ramli N.E. , Zainor Ridzuan Yahya , Said N.A.

Nowadays, corner detection algorithms have been proposed by several researchers who described them contrarily, depending on their respective viewpoints to obtain the data and information as a human eye does. Basically, no researchers have come up with a technique to compare corner detectors with another’s. Thus, this study proposed to adapt the confusion matrix technique as a performance measure for corner detectors. The judgement accuracy of every corner detector will only be pleased if the actual corner points are already known. Therefore, this study is attracted to explore the accuracy of corner detectors, namely the Global and Local Curvature Scale space (GLCSS), Affine Resilient Curvature Scale Space (ARCSS), and Harris. These corner detectors were analysed using the nine characters selected from Jawi, Chinese, and Tamil characters, three characters each, respectively. This study specifically detected the true corners for these characters using the determined corner detectors. The actual corner of all these characters was confirmed through a survey of twenty respondents. The majority of marked corners by respondents were considered actual corner points. Then, the input image for all characters was converted into a grayscale image. Every image will undergo pre-processing step, the process of boundary extraction using Canny edge detector. Thus, the edge image was extracted to get the corner point by applying the corner detectors, and the corner point detected was marked on that image. Above and beyond, the study aims to introduce a confusion matrix approach as a performance measure to carry out the most outstanding algorithm in detecting the true corner points for all the tested characters. From the evaluation, GLCSS and Harris algorithms have shown good accuracy. Henceforth, the study is not trying to judge the goodness of each corner detector but only to introduce confusion matrix as a tool that can be considered to measure the performance of the corner detector.

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A survey on improvement of Mahalanobis Taguchi system and its application

2023-11-01 , Tan L.M. , Wan Zuki Azman Wan Muhamad , Zainor Ridzuan Yahya , Ahmad Kadri Junoh , Nor Hizamiyani Abdul Azziz , Ramlie F. , Harudin N. , Abu M.Y. , Tan X.J.

Mahalanobis Taguchi System (MTS) is used for pattern recognition and classification, diagnosis, and prediction of a multivariate data set. Mahalanobis Distance (MD), orthogonal array (OA), and signal-to-noise ratio (SNR) are used in traditional MTS in order to identify and optimize the variables. However, the high correlation among variables shows an effect on the inverse of the correlation matrix that uses in the calculation of MD and hence affects the accuracy of the MD. Therefore, Mahalanobis-Taguchi-Gram-Schmidt (MTGS) system is proposed in order to solve the problem of multicollinearity. The value of MD can be calculated by using the Gram-Schmidt Orthogonalization Process (GSOP). Besides, the computational speed and the accuracy in optimization using OA and SNR are other issues that are concerned the authors. Hence, the combination of MTS and other methods such as Binary Particles Swarm Optimization (BPSO) and Binary Ant Colony Optimization (NBACO) is proposed to improve the computational speed and the accuracy in optimization. The purpose of this paper is to review and summarize some works that developed and used the hybrid methodology of MTS as well as its application in several fields. Moreover, a discussion about the future work that can be done related to MTS is carried out.

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A Modified Artificial Bee Colony Based Test Suite Generation Strategy for Uniform T-Way Testing

2020-03-20 , Rashid Ali M.S.A. , Rozmie Razif Othman , Zainor Ridzuan Yahya , Mohd Zamri Zahir Ahmad

Today, t-way testing has been widely known with the ability to reduce test suite size compared to exhaustive testing. At the same time, it has been proven by many researchers to provide maximum bug detection capability. Thus, various t-way strategies were developed since the past three decades. The paper proposed a new test generation strategy, named Modified Artificial Bee Colony T-Way Test Suite Generation (MABCTS). It supports uniform strength t-way testing. Experimentation results are compared with present strategies and produced comparable results. Since t-way testing is considered an NP-hard problem, there are no strategies that can be demanded to produce the best results.

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