This paper analysed the effects of bending on the performance of a textile antenna wherein the antenna under test was made of felt substrate for both industrial, scientific, and medical (ISM) band and WBAN applications at 2.45GHz. Moreover, the conductive material was used for the patch, and the ground plane used a 0.17mm Shieldit textile. Meanwhile, the antenna structure was in the form of rectangular, with a line patch in between elements to abate the mutual coupling effect. The measured operating frequency range of the antenna spanned from 2.33GHz to 2.5GHz with a gain of 4.7 dBi at 2.45GHz. In this paper, the antenna robustness was examined by bending the structure on different radii and degrees along both X- and Y-axis. Next, the effects on return loss, bandwidth, isolation, and radiation characteristics were analysed. This paper also discovered that the antennas performance remained acceptable as it was deformed, and the measured results agreed well with the simulation.

The Mahalanobis–Taguchi System (MTS) is a pattern recognition tool employing Mahalanobis Distance (MD) and Taguchi Robust Engineering philosophy to explore and exploit data in multidimensional systems. The MD metric provides a measurement scale to classify classes of samples (Abnormal vs. Normal) and gives an approach to measuring the level of severity between classes. An accurate classification result depends on a threshold value or a cut-off MD value that can effectively separate the two classes. Obtaining a reliable threshold value is very crucial. An inaccurate threshold value could lead to misclassification and eventually resulting in a misjudgment decision which in some cases caused fatal consequences. Thus, this paper compares the performance of the four most common thresholding methods reported in the literature in minimizing the misclassification problem of the MTS namely the Type I–Type II error method, the Probabilistic thresholding method, Receiver Operating Characteristics (ROC) curve method and the Box–Cox transformation method. The motivation of this work is to find the most appropriate thresholding method to be utilized in MTS methodology among the four common methods. The traditional way to obtain a threshold value in MTS is using Taguchi’s Quadratic Loss Function in which the threshold is obtained by minimizing the costs associated with misclassification decision. However, obtaining cost-related data is not easy since monetary related information is considered confidential in many cases. In this study, a total of 20 different datasets were used to evaluate the classification performances of the four different thresholding methods based on classification accuracy. The result indicates that none of the four thresholding methods outperformed one over the others in (if it is not for all) most of the datasets. Nevertheless, the study recommends the use of the Type I–Type II error method due to its less computational complexity as compared to the other three thresholding methods.

The goal of this study is to assess the efficiency of Artificial Bee Colony (ABC) algorithm in finding the optimal solution of curve fitting problem specifically for medical images. Data of Computed Tomography (CT) images from two different patients were collected. The procedure of curve fitting for medical images include conversion of Digital and Communications in Medicine (DICOM) images to binary images, boundary and corner point detection, parameterization, and curve reconstruction by using ABC algorithm. Then, Sum Square Error (SSE) was used to calculate the distance of the fitted Cubic Bezier curve with the boundary of the original images. Based on the calculation and parameter tuning that had been done, the smallest error of both skulls is57.5754and28.8628, respectively. The finding of this study illustrated that the proposed method had efficiently produced fitted Bezier curve that resemble the original medical images. In addition, the used of Douglas Peucker algorithm helps to improve the performance of the proposed method since computational time can be minimized. This study had shown that the proposed method can be used as an alternative method in order to reconstruct or redesigned the medical images since it produces a small error. For future work, we are planning to explore and applied the ABC algorithm to reconstruct the missing part of the skull since it can reduce the time taken to produce the skull implant as well as reducing the cost of producing it.

Taguchi’s T-Method is one of the Mahalanobis Taguchi System- (MTS-) ruled prediction techniques that has been established specifically but not limited to small, multivariate sample data. The prediction model’s complexity aspect can be further enhanced by removing features that do not provide valuable information on the overall prediction. In order to accomplish this, a matrix called orthogonal array (OA) is used within the existing Taguchi’s T-Method. However, OA’s fixed-scheme matrix and its drawback in coping with the high-dimensionality factor led to a suboptimal solution. On the contrary, the usage of SNR (dB) as its objective function was a reliable measure. The application of Binary Bitwise Artificial Bee Colony (BitABC) has been adopted as the novel search engine that helps cater to OA’s limitation within Taguchi’s T-Method. The generalization aspect using bootstrap was a fundamental addition incorporated in this research to control the effect of overfitting in the analysis. The adoption of BitABC has been tested on eight (8) case studies, including large and small sample datasets. The result shows improved predictive accuracy ranging between 13.99% and 32.86% depending on cases. This study proved that incorporating BitABC techniques into Taguchi’s T-Method methodology effectively improved its prediction accuracy.

The increasing number of reported child abuse cases in Malaysia is alarming, with more than 1000 cases reported every year. If this trend continues, it may have detrimental effects on children’s mental development, and far-reaching negative effects for wider society. Examining whether there is some relationship between divorce, unemployment, poverty, inflation, economic growth, and child abuse in Malaysia may help shed some light on the issue and any potential solutions. This study employs the ARDL approach by using data from 1989 to 2019. The results reveal that unemployment, inflation, and economic growth have significant relationships with reported child abuse cases in the long run. However, divorce and poverty do not affect the number of reported child abuse cases in the long run. In the short run, the results show that divorce, economic growth, and unemployment can positively affect the number of reported child abuse cases. Poverty, on the other hand, has a significant and negative relationship with the number of reported child abuse cases in the short run. Family stress originating from economic and social distress and the potential inability of couples to manage stress may exacerbate the risk of child abuse in Malaysia. Social programs are likely needed to help couples handle stress at home, in the form of state-sponsored counselling, educational programs for parents, the provision of social support for an increasing number of dual-career couples, assistance for spouses dealing with divorce, and the protection of children from hostile environments at home, as well as general approaches to the alleviation of poverty.