Universiti Sains Islam Malaysia

Histogram equalization (HE) is one of the common methods used for improving contrast in digital images. However, this technique is not very well suited to be implemented in consumer electronics, such as television, because the method tends to introduce unnecessary visual deterioration such as the saturation effect. One of the solutions to overcome this weakness is by preserving the mean brightness of the input image inside the output image. This paper proposes a new method, known as brightness preserving dynamic histogram equalization (BPDHE), which is an extension to HE that can produce the output image with the mean intensity almost equal to the mean intensity of the input, thus fulfill the requirement of maintaining the mean brightness of the image. First, the method smoothes the input histogram with one dimensional Gaussian filter, and then partitions the smoothed histogram based on its local maximums. Next, each partition will be assigned to a new dynamic range. After that, the histogram equalization process is applied independently to these partitions, based on this new dynamic range. For sure, the changes in dynamic range, and also histogram equalization process will alter the mean brightness of the image. Therefore, the last step in this method is to normalize the output image to the input mean brightness. Our results from 80 test images shows that this method outperforms other present mean brightness preserving histogram equalization methods. In most cases, BPDHE successfully enhance the image without severe side effects, and at the same time, maintain the mean input brightness <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .

Zinc oxide plays an important role in current industry due to its special characteristics such as anti-corrosion, anti-bacteria, has low electrons conductivity and excellent heat resistance. Therefore, the objective of this study is to synthesize zinc oxide nanostructures with the most practical ways by using sol-gel method and characterize the nanostructures. Sol-gel method is the simplest method and has the ability to control the particle size and morphology through systematic monitoring of reaction parameters. ZnO nanoparticles were synthesized via sol gel method using Zinc acetate dehydrate (Zn(CH3COO)2.2H2O) as a precursor and ethanol (CH2COOH) was used as solvent, Sodium hydroxide (NaOH) and distilled water were used as medium. ZnO nanoparticles were characterized by using XRD, EDX, FESEM, and nano-particles analyser. Result of EDX characterization shows that the ZnO nanoparticles has good purity with (Zinc content of- 55.38% and; Oxygen content of- 44.62%). XRD result spectrum displays mainly oxygen and zinc peaks, which indicate the crystallinity in nature as exhibited. FESEM micrographs shows that synthesized ZnO have a rod-like structure. The obtained ZnO nanoparticles are homogenous and consistent in size which corresponds to the XRD result that exhibit good crystallinity. ZnO nanoparticles were successfully synthesized by sol-gel method in nanosize range within 81.28 nm to 84.98 nm.

The need for high power density and high temperature capabilities in today's electronic devices continues to grow. More robust devices with reliable and stable functioning capabilities are needed, for example in aerospace and automotive industries as well as sensor technology. These devices need to perform under extreme temperature conditions, and not show any deterioration in terms of switching speeds, junction temperatures, and power density, and so on. While the bulk of research is performed to source and manufacture these high temperature devices, the device interconnect technology remains under high focus for packaging. The die attach material has to withstand high temperatures generated during device functioning and also cope with external conditions which will directly determine how well the device performs in the field. This literature work seeks to review the numerous research attempts thus far for high temperature die attach materials on wide band gap materials of silicon carbide, gallium nitride and diamond, document their successes, concerns and application possibilities, all of which are essential for high temperature reliability.

Purpose – The purpose of this paper is to understand current Shari’ah governance practices with the purpose of promoting greater understanding of some of the crucial issues and to provide relevant information in guiding the future development of Shari’ah governance system. The paper illustrates the state of Shari’ah governance practices inMalaysia,GCC countries (Kuwait, Bahrain,United ArabEmirates, Qatar and Saudi Arabia) and the UK by highlighting five main elements of good corporate governance that consist of independence, competency, transparency, disclosure and consistency.Design/methodology/approach – Since the availability of secondary data on Shari’ah governance practices is very limited, a detailed survey questionnaire is generated for sourcing primary data from Islamic Financial Institutions (IFIs). The study utilizes descriptive analysis approach in extracting and analyzing the data and factual input derived from the questionnaire feedback.Findings – The survey findings affirm that there are significant differences and diverse Shari’ah governance practices in the case countries. This position acknowledges that there are shortcomings and weaknesses to the existing governance framework which needs further enhancement and improvement.Practical implications – The paper is a very useful source of information that may provide relevant guidelines in guiding the future development of Shari’ah governance practices in IFIs. Originality/value – This paper provides fresh data and recent information on the actual Shari’ah governance practices of IFIs in three jurisdictions.

Underwater images are affected by reduced contrast and non-uniform colour cast due to the absorption and scattering of light in the aquatic environment. This affects the quality and reliability of image processing and therefore colour correction is a necessary pre-processing stage. In this paper, we propose an Unsupervised Colour Correction Method (UCM) for underwater image enhancement. UCM is based on colour balancing, contrast correction of RGB colour model and contrast correction of HSI colour model. Firstly, the colour cast is reduced by equalizing the colour values. Secondly, an enhancement to a contrast correction method is applied to increase the Red colour by stretching red histogram towards the maximum (i.e., right side), similarly the Blue colour is reduced by stretching the blue histogram towards the minimum (i.e., left side). Thirdly, the Saturation and Intensity components of the HSI colour model have been applied for contrast correction to increase the true colour using Saturation and to address the illumination problem through Intensity. We compare our results with three well known methods, namely Gray World, White Patch and Histogram Equalisation using Adobe Photoshop. The proposed method has produced better results than the existing methods.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This letter presents a novel two-stage noise adaptive fuzzy switching median (NAFSM) filter for salt-and-pepper noise detection and removal. Initially, the detection stage will utilize the histogram of the corrupted image to identify noise pixels. These detected “noise pixels” will then be subjected to the second stage of the filtering action, while “noise-free pixels” are retained and left unprocessed. Then, the NAFSM filtering mechanism employs fuzzy reasoning to handle uncertainty present in the extracted local information as introduced by noise. Simulation results indicate that the NAFSM is able to outperform some of the salt-and-pepper noise filters existing in literature. </para>

Among the various forms of malware, botnets are emerging as the most serious threat against cyber-security as they provide a distributed platform for several illegal activities such as launching distributed denial of service attacks against critical targets, malware dissemination, phishing, and click fraud. The defining characteristic of botnets is the use of command and control channels through which they can be updated and directed. Recently, botnet detection has been an interesting research topic related to cyber-threat and cyber-crime prevention. This paper is a survey of botnet and botnet detection. The survey clarifies botnet phenomenon and discusses botnet detection techniques. This survey classifies botnet detection techniques into four classes: signature-based, anomaly-based, DNS-based, and mining-base. It summarizes botnet detection techniques in each class and provides a brief comparison of botnet detection techniques.

The aim of this study was to determine the changes of short chain fatty acids (SCFAs) in faeces of inflammatory bowel disease (IBD) patients compared to healthy subjects. SCFAs such as pyruvic, lactic, formic, acetic, propionic, isobutyric and butyric acids were analyzed by using high performance liquid chromatography (HPLC). This study showed that the level of acetic, 162.0 micromol/g wet faeces, butyric, 86.9 micromol/g wet faeces, and propionic acids, 65.6 micromol/g wet faeces, decreased remarkably in IBD faecal samples when compared with that of healthy individuals, 209.7, 176.0, and 93.3 micromol/g wet faeces respectively. On the contrary, lactic and pyruvic acids showed higher levels in faecal samples of IBD than in healthy subjects. In the context of butyric acid level, this study also found that the molar ratio of butyric acid was higher than propionic acid in both faecal samples. This might be due to the high intake of starch from rice among Malaysian population. It was concluded that the level of SCFAs differ remarkably between faecal samples in healthy subjects and that in IBD patients providing evidence that SCFAs more likely play an important role in the pathogenesis of IBD.

Objectives This review aims to: (1) explore the social support measures in studies examining the association between social support and depression among community-dwelling older adults in Asia and (2) the evidence of association. Design A systematic review was conducted using electronic databases of CINAHL, PubMed, PsychINFO, Psychology and Behavioural Sciences Collection, SocINDEX and Web of Science for articles published until the 11th of January 2018. Eligibility criteria All observational studies investigating the association between social support and depression among community-dwelling older adults in Asia were included. Participants Older adults aged 60 years and more who are living in the community. Exposure measures Social support. Outcome measures Depression. Results We retrieved16 356 records and screened 66 full-text articles. Twenty-four observational studies were included in the review. They consisted of five cohort studies and 19 cross-sectional studies. Social support was found to be measured by multiple components, most commonly through a combination of structural and functional constructs. Perceived social support is more commonly measured compared with received social support. Good overall social support, having a spouse or partner, living with family, having a large social network, having more contact with family and friends, having emotional and instrumental support, good support from family and satisfaction with social support are associated with less depressive symptoms among community-dwelling older adults in Asia. Conclusions There were 20 different social support measures and we applied a framework to allow for better comparability. Our findings emphasised the association between good social support and decrease depression among older adults. Compared with western populations, family support has a greater influence on depression among community-dwelling older adults in Asia. This indicates that the family institution needs to be incorporated into designed programmes and interventions when addressing depression in the Asian context. Trial registration number CRD42017074897.

Many histogram equalization based methods have been introduced for the use in consumer electronics in recent years. Yet, many of these methods are relatively complicated to be implemented, and mostly require a high computational time. Furthermore, some of the methods require several predefined parameters from the user, which make the optimal results cannot be obtained automatically. Therefore, this paper presents Bi-Histogram Equalization with a Plateau Level (BHEPL) as one of the options for the system that requires a short processing time image enhancement. First, BHEPL divides the input histogram into two independent sub-histograms. This is done in order to maintain the mean brightness. Then, these sub-histograms are clipped based on the calculated plateau value. By doing this, excessive enhancement can be avoided. Experimental results show that this method only requires 34.20ms, in average, to process images of size 3648x2736 pixels (i.e. 10 Mega pixels images). The proposed method also gives better enhancement results as compared with some multi-sections mean brightness preserving histogram equalization methods <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .

From the behavioral perspective, this study analyzed the entrepreneurial readiness of youth in terms of opportunity identification, motivational factors, resources, and entrepreneurial ability. The study examined the effect of entrepreneurship training on young people's readiness to engage in entrepreneurial activity and the components behind successful startups. SEM was applied to a sample of 490 students from the Universiti Sains Islam Malaysia. The findings highlight the positive effect of opportunity identification, motivation, and resources on entrepreneurship and the central role of entrepreneurship training in all factors, including entrepreneurial ability. The role of entrepreneurship training implies that young individuals are able to develop their entrepreneurial ability. The study thus shows the individual's ability to change over the course of a lifetime. For individuals interested in the startup process, this study provides information capable of influencing their new business ventures.

Purpose This study aims to investigate the impact of board diversity characteristics, namely, independence, gender, age and nationality of directors on the level of corporate social responsibility (CSR) disclosures. Design/methodology/approach Content analysis was used to determine CSR disclosure. This study used panel data analysis to investigate the influence of board diversity characteristics on CSR disclosures. Findings Panel data analysis show that the level of CSR disclosure has increased over the period of study. Results also reveal a positive and significant association between the level of CSR disclosure and board diversity variables. Research limitations/implications This study examined only companies listed on Amman Stock Exchange. Therefore, the generalisation of the results might be limited to the listed companies only. Practical implications Findings are relevant to policymakers, professional organisations and practitioners in Jordan and in other Arab countries. Social implications The role of women in the boardroom is important to ensure more CSR activities by the listed companies. Jordan being a Muslim country should take the initiative to introduce laws to increase the number of women to the board. Originality/value This study offers significant contributions to existing CSR literature in Jordan and in other Arab countries by introducing female directors. Findings are important to policymakers. They should implement quotas for women in the boardroom, and adopting such a policy will increase the participation of women in the decision-making process of the companies and reduce gender bias.

BACKGROUND: Coronavirus disease 2019 or COVID-19 is caused by a newly discovered coronavirus, SARS-CoV-2. The Malaysian government has planned to procure COVID-19 vaccine through multiple agencies and companies in order to vaccinate at least 70% of the population. This study aimed to determine the knowledge, acceptance and perception of Malaysian adults regarding the COVID-19 vaccine. METHODOLOGY: An online survey was conducted for two weeks in December 2020. A bilingual, semi-structured questionnaire was set up using Google Forms and the generated link was shared on social media (i.e., Facebook and WhatsApp). The questionnaire consisted of questions on knowledge, acceptance and perception of COVID-19 vaccine. The association between demographic factors with scores on knowledge about COVID-19 vaccine were analysed using the Mann-Whitney test for two categorical variables, and the Kruskal-Wallis test used for more than two categorical variables. RESULTS: A total of 1406 respondents participated, with the mean age of 37.07 years (SD = 16.05) years, and among them 926 (65.9%) were female. Sixty two percent of respondents had poor knowledge about COVID-19 vaccine (mean knowledge score 4.65; SD = 2.32) and 64.5% were willing to get a COVID-19 vaccine. High knowledge scores associated with higher education background, higher-income category and living with who is at higher risk of getting severe COVID-19. They were more likely to be willing to get vaccinated if they were in a lower age group, have higher education levels and were female. CONCLUSION: Even though knowledge about vaccine COVID-19 is inadequate, the majority of the respondents were willing to get vaccinated. This finding can help the Ministry of Health plan for future efforts to increase vaccine uptake that may eventually lead to herd immunity against COVID-19.

Mental disorders (MDs) with onset in childhood or adolescence include neurodevelopmental disorders (NDDs) (intellectual disability and specific learning disabilities, such as dyslexia, attention deficit disorder (ADHD), and autism spectrum disorders (ASD)), as well as a broad range of mental health disorders (MHDs), including anxiety, depressive, stress-related and psychotic disorders. There is a high co-morbidity of NDDs and MHDs. Globally, there have been dramatic increases in the diagnosis of childhood-onset mental disorders, with a 2- to 3-fold rise in prevalence for several MHDs in the US over the past 20 years. Depending on the type of MD, children often grapple with social and communication deficits and difficulties adapting to changes in their environment, which can impact their ability to learn effectively. To improve outcomes for children, it is important to provide timely and effective interventions. This review summarises the range and effectiveness of AI-assisted tools, developed using machine learning models, which have been applied to address learning challenges in students with a range of NDDs. Our review summarises the evidence that AI tools can be successfully used to improve social interaction and supportive education. Based on the limitations of existing AI tools, we provide recommendations for the development of future AI tools with a focus on providing personalised learning for individuals with NDDs.

Purpose This study aims to explore the corporate social responsibility disclosure (CSRD) practices of the Islamic banks in the Gulf Cooperation Council (GCC) countries during the period 2010-2014 and examines the determinants of CSRD and its effects on firm value. Design/methodology/approach Based on the Accounting and Auditing Organization for Islamic Financial Institutions Governance Standard No. 7 guidelines and using content analysis, the paper develops a comprehensive CSRD index for GCC Islamic banks. The study applies ordinary least squares regression analysis for hypothesis testing and for finding determinants of respective dependent variables. Findings The results show a very low level of CSRD among the sample Islamic banks in GCC countries. When using corporate governance characteristics to examine the determinants of CSRD, this study provides evidence of a significant positive association between board size and CSRD practice in Islamic banks and a significant negative relationship of chief executive officer (CEO) duality with CSRD, as per expectation. For the economic consequences of CSRD, the study documents an inverse performance effect of CSRD while board size, board composition and CEO duality indicate significant positive effects on firm value. Research limitations/implications The relatively small sample size of GCC Islamic banks may limit the application of the findings to other Islamic financial institutions such as Takaful and the Islamic unit trust company. Practical implications The findings of this study initiate the global debate on the need for corporate governance reform in Islamic banks by providing insights on the role played by corporate governance mechanisms in encouraging and enhancing CSRD practices among Islamic banks. The findings also have important implications for investors, managers, regulatory bodies, policymakers and Islamic banks in the GCC countries. Social implications The results of the study do not support the idea that Islamic banks operating on Islamic principles can meet their social responsibilities through promoting corporate social responsibility (CSR) activities and by differentiating themselves from non-Islamic banks. Originality/value This is the first study to examine the determinants of CSRD in GCC Islamic banks using comprehensive CSRD and corporate governance variables and, therefore, adds value to the existing CSR literature in banking.

A general analytical model, formulated in 2-D polar coordinates, is developed to predict the unbalanced magnetic force, which results in permanent-magnet brushless ac and dc machines having a diametrically asymmetric disposition of slots and phase windings. It is shown that the unbalanced magnetic force can be significant in machines having a fractional ratio of slot number to pole number, particularly when the electric loading is high. The developed model is validated by finite-element calculations on 9-slot/8-pole and 3-slot/2-pole machines. In addition, the unbalanced magnetic force has been measured on a prototype 3-slot/2-pole machine and shown to be in excellent agreement with predicted results.

The synthesis and secretion of cortisol are controlled by the hypothalamic-pituitary-adrenal axis. Cortisol exhibits a proper 24-h circadian rhythm that affects the brain, the autonomic nervous system, the heart, and the vasculature that prepares the cardiovascular system for optimal function during these anticipated behavioral cycles. A literature search was conducted using databases such as Google Scholar, PubMed, and Scopus. Relevant search terms included "circadian rhythm and cardiovascular", "cortisol", "cortisol and acute coronary syndrome", "cortisol and arrhythmias", "cortisol and sudden cardiac death", "cortisol and stroke", and "cardioprotective agents". A total of 120 articles were obtained on the basis of the above search. Lower levels of cortisol were seen at the beginning of sleep, while there was a rise towards the end of sleep, with the highest level reached at the moment the individual wakes up. In the present review, we discuss the role of 11β-hydroxysteroid dehydrogenase (11β-HSD1), which is a novel molecular target of interest for treating metabolic syndrome and type-2 diabetes mellitus. 11β-HSD1 is the major determinant of cortisol excess, and its inhibition alleviates metabolic abnormalities. The present review highlights the role of cortisol, which controls the circadian rhythm, and describes its effect on the cardiovascular system. The review provides a platform for future potential cardioprotective therapeutic agents.

The presence of natural antioxidant in plants is well known. This paper reports the antioxidative activities of some methanolic plant extracts namely ‘ulam raja’ (Cosmos caudatus), ‘kesum’ (Polygonum minus), ‘selom’ (Oenanthe javanica), ‘pegaga’ (Centella asiatica) and ‘curry leaf’ (Murraya koenigii). The analysis carried out was total phenolic content, ferric reducing power, ferric thiocyanate (FTC) and thiobarbituric acid (TBA) tests. From the analyses, M. koenigii had the highest yield extraction (1.65%), highest total phenolic content (38.60 mg TAE/ 100 g fresh weight) and antioxidant activity (70.60%) using FTC method. Increasing the concentration of the extracts resulted in increased ferric reducing antioxidant power for all methanolic extracts tested. TBA analysis showed that C. caudatus extract had the highest antioxidant effect. Total phenolic content had positive correlation with antioxidant capacity (r = 0.451). This shows that the plants, especially M. koeniigi, may be potent source of natural antioxidants.

Cardiovascular diseases (CVDs) such as angina, hypertension, myocardial ischaemia and heart failure are the leading causes of morbidity and mortality worldwide. One of the major transcription factors widely associated with CVDs is nuclear factor-kappa B (NFκB). NFκB activation initiate the canonical and non-conical pathways that promotes activation of transcription factors leading to inflammation, such as leukocyte adhesion molecules, cytokines, and chemokines. Flavonoids are bioactive polyphenolic compounds found abundantly in various fruits, vegetables, beverages (tea, coffee), nuts and cereal products with cardiovascular protective properties. Flavonoids can be classified into six subgroups based on their chemical structures: flavanones, flavones, flavonols, flavan-3-ols, isoflavones and anthocyanidins. As NFκB inhibitors, these flavonoids may modulate the expression of pro-inflammatory genes leading to the attenuation of the inflammatory responses underlying various cardiovascular pathology. This review presents an update on the anti-inflammatory actions of flavonoids via inhibition of NFκB mechanism supporting the therapeutic potential of these natural compounds in various CVDs.

Clustering algorithms have successfully been applied as a digital image segmentation technique in various fields and applications. However, those clustering algorithms are only applicable for specific images such as medical images, microscopic images etc. In this paper, we present a new clustering algorithm called Adaptive Fuzzy-K-means (AFKM) clustering for image segmentation which could be applied on general images and/or specific images (i.e., medical and microscopic images), captured using different consumer electronic products namely, for example, the common digital cameras and CCD cameras. The algorithm employs the concepts of fuzziness and belongingness to provide a better and more adaptive clustering process as compared to several conventional clustering algorithms. Both qualitative and quantitative analyses favour the proposed AFKM algorithm in terms of providing a better segmentation performance for various types of images and various number of segmented regions. Based on the results obtained, the proposed algorithm gives better visual quality as compared to several other clustering methods. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .