16 research outputs found

    Factors influencing consumer's purchase for electrical appliances with SIRIM certification mark / Harsa Ardila Mat Sakim

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    Consumers make many buying decisions every day. Some of the products are of quality and some are not. This leads to consumers seeking guidelines in making their purchases. This is important to prevent consumers from being cheated by irresponsible traders. Malaysian regulatory body has set electrical appliances as some of the mandatory products that need to be tested and certified by Sirim. This means that they need to get the Sirim Certification Mark. However, not all electrical appliances in the present market have been tested. With increase in trade and a corresponding increase in demand for quality and safety by government authorities, purchasers and consumer, there is a need for a means of providing assurance that a product complies with specified standards or specifications. The Product Certification Scheme aims to provide this confidence through an independent assurance of quality and safety. Consumer's purchases are influenced strongly by cultural, social, personal and psychological characteristics. Somehow, does consumers decision on buying electrical appliances with the SCM influenced by these factors. This research focuses in studying the factors influencing consumer's purchase for electrical appliances with Sirim Certification Mark of consumers in Shah Alam. Therefore this research is designed to identify the relationship between cultural factors, social factors, personal factors, psychological factors and consumer's purchase which involve of electrical appliances with SCM. The study sample comprised of 66 consumers. A profile analysis of respondent, frequencies of all factors and correlation between consumer's purchase and cultural, social, personal and psychological factor were conducted. Findings revealed that the cultural, personal and psychological factor have strong relationship with consumer's purchase for electrical appliances with SCM. In addition, there are moderate relationship between consumer's purchase and social factor

    A Survey On Medical Digital Imaging Of Endoscopic Gastritis.

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    This paper focuses on researches related to medical digital imaging of endoscopic gastritis

    Density Based Breast Segmentation For Mammograms Using Graph Cut Techniques.

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    In this work we explore the application of graph cuts techniques to the problem of finding the boundary of different breast tissue regions in mammograms

    Suitable MLP Network Activation Functions For Breast Cancer And Thyroid Disease Detection.

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    This paper presents a comparison study of various MLP activation functions for detection and classification problems

    Emperor penguin optimizer: A comprehensive review based on state-of-the-art meta-heuristic algorithms

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    Meta heuristics is an optimization approach that works as an intelligent technique to solve optimization problems. Evolutionary algorithms, human-based algorithms, physics-based algorithms and swarm intelligence are categorized under meta-heuristic algorithms. This study presents a critical review of meta-heuristic algorithms for future reference, including concepts, applications, advantages and disadvantages, before focusing on one specific meta-heuristic algorithm, namely, Emperor Penguin Optimizer (EPO). It is an intelligent algorithm developed after observing the behaviour of emperor penguins during cold winters. This technique was introduced by Dhiman in 2018 and adopted to solve optimization problems. The study reviews the algorithm variants starting from its invention in 2018 until 2022. The literature is comprehensively reviewed to reflect on the progress of the algorithm’s adoption, highlighting a new area for improvement. The most significant result is that the proposed algorithm has been proven an effective technique. The merits and demerits of the algorithm are explored to provide valuable perspectives for future research. This study answers the question regarding meta-heuristic algorithms’ effectiveness, especially EPO. Both beginners and experts of EPO research can use the findings of this study as guidelines for enhancing current concepts and applications of state-of-the-art algorithms for future development works

    Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts

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    Breast cancer mostly arises from the glandular (dense) region of the breast. Consequently, breast density has been found to be a strong indicator for breast cancer risk. Therefore, there is a need to develop a system which can segment or classify dense breast areas. In a dense breast, the sensitivity of mammography for the early detection of breast cancer is reduced. It is difficult to detect a mass in a breast that is dense. Therefore, a computerized method to separate the existence of a mass from the glandular tissues becomes an important task. Moreover, if the segmentation results provide more precise demarcation enabling the visualization of the breast anatomical regions, it could also assist in the detection of architectural distortion or asymmetry. This study attempts to segment the dense areas of the breast and the existence of a mass and to visualize other breast regions (skin-air interface, uncompressed fat, compressed fat, and glandular) in a system. The graph cuts (GC) segmentation technique is proposed. Multiselection of seed labels has been chosen to provide the hard constraint for segmentation of the different parts. The results are promising. A strong correlation () was observed between the segmented dense breast areas detected and radiological ground truth
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