MMU Press (Multimedia University)
Not a member yet
714 research outputs found
Sort by
Performance Analysis of Partial Shading Effect on PV Plant
No full textPartial shading of PV plants mitigate the maximum power generation of solar modules. As a result, the power output is lower than expected. It is affected not only by the number of shaded modules but also by the shaded patterns. This paper examined a PV plant rated at 15 kW connected in series-parallel for various shading patterns, such as row-wise and column-wise partial shading. This solar plant's behavior is also investigated under various irradiation levels and degrees of shading. The number of solar modules required for this plant was also evaluated. The performance results of solar modules under partial shading conditions, such as power, voltage, and current, are revealed by using the Matlab/Simulik model. From the analysis, the result shows that the column-wise shading condition generates more power output than the row-wise shading condition.
Manuscript Received: 15 February 2023, Accepted: 12 March 2023, Published: 15 March 2023, ORCiD: 0009-0008-8009-117
A Comparative Study on the Concept of Accountability Between Vietnam and Japan
No full textThis paper aims to describe the civil servant reform process in Vietnam. Also, the government concentrated on accountability of the public administration aligning with the civil servant system’s development. With the specialty of the socialist country, the concept and characteristics of accountability have contained uniqueness, especially in the Japanese paradigm. Thus, this paper will investigate accountability from the perspective of civil servants’ duties in Vietnam. In the comparative legal study, the research also refers to Japanese experiences. Some legal problems of accountability related to the civil servant law scheme will be pointed out to understand further obstacles of Vietnam in public administration reform over twenty years
The Song of the Kedidi: The Embodiment of a Hero in a Malay Folktale as an Intangible Cultural Heritage
No full textThe present study is part of a movement to safeguard Malay folktales as an unsung intangible cultural heritage (ICH). A folktale is a representation of oral traditions and expressions. This study converges on literary folktales as a revitalised form of oral folktales. As urged by UNESCO, the viability of the ICH is achievable via scientific research, among other things. Therefore, considering the small amount of study on Malay folktales at the moment, the current study endeavours to examine the folktale The Song of the Kedidi (TSoK) of its hero embodiment as one of the dramatis personae. The framework of Propp’s dramatis personae, which is based on Russian folktales, grounds the examination. This study examines whether the heroes from the Russian folktales embody TSoK. The thematic qualitative text analysis (TQTA) was employed to examine TSoK. It was conducted in Atlas.ti environment to assure rigour and trustworthiness. The study’s findings suggest that TSoK embodies heroes from Russian folktales. However, a conundrum exists in the embodiment of the hero. There is a conflict between the dramatis personae’s role, and such an enigma calls for the involvement of other dramatis personae, which is reserved for future works. As a crusade to safeguard the Malay folktales as the unsung ICH, the findings create a platform for scholars of similar interests to pursue the examination of heroes in other Malay folktales. Most importantly, the findings are necessary for endless recreation and transmission of knowledge to safeguard the Malay folktale as a living heritage. This act echoes one of UNESCO’s formal education measures to foster society’s respect, recognition, and awareness of the ICH
Factors Influencing Academic Achievement of University Students
No full textAcademic achievement is one of the significant outcomes of the formal education processes. Thus, understanding the factors which influence academic performance is timely. This study aims to examine the determinants that impact the academic performance of students. The determinants include student engagement, general knowledge, social skills, and communication skills. This study applied a quantitative research design, with an online survey questionnaire distributed to the students of a private university in Klang Valley, and 150 valid responses were solicited. The Pearson’s product-moment correlations in the current study demonstrated that student engagement had a positive and strong relationship with student’s academic achievement. General knowledge and social skills were found to have a positive and moderate relationship with academic achievement; however, communication skills were found to have a positive but weak correlation with academic achievement. Multiple regression analysis found that student engagement, general knowledge, and social skills were predictors of academic achievement. However, communication skills were not the predictor. In addition, this study significantly contributes to students’ social life aspects as it is consistent with the Malaysian Ministry of Higher Education's initiative to integrate soft skills into the curriculum and learning processes. This will urge the university's management to develop initiatives and programmes that equip students with various soft skills to make them competent in the market force after graduation. This study also discusses the conclusion, implications, and future research directions
QR Food Ordering System with Data Analytics
No full textAs the epidemic starts to slow down and Malaysians are more confident about containing the outbreak with the norm of vaccination, diners have been aching to return to dining rooms, with many restaurants functioning at full capacity, but staffing is an entirely different story. As restaurateurs try to keep their businesses running at full speed and solve limited staff issues, there is only one solution: process automation. This paper aims to design a food ordering system that covers the benefits of automating the ordering process using the QR code and provides visualised insightful information based on the business data. Customers place the food order by scanning the QR code on the restaurant table, and it is then brought to a digital version of the restaurant's menu and make orders. The proposed system automates customer bills after the order, and it helps reduce human error in calculating bills. On the other hand, the proposed system has an admin interface that enables restaurant owners to modify the restaurant's menu, generate QR codes for the new dining table, receive orders from customers, and get automated bills generated by customers' orders. Most importantly, the system allows restaurant owners to have an insightful view of their business data such as visualised charts on sales data, highlighted crucial data and so on to improve decision-making and forecasting future demand using data analysis techniques which are not populated in similar systems currently. Machine learning has become a huge trend nowadays, it is also included to in the proposed system to forecast more valuable data for the business
Utilizing Fuzzy Algorithm for Understanding Emotional Intelligence on Individual Feedback
No full textAlthough previous studies looked at how employees should seek assistance, the issue is the researchinvestigation into how behavioral intelligence affects employee satisfaction is limited. This study examines several significant usages and developments of fuzzy mental modelling. The primary objective of the current section is to provide an innovative technique for modelling an emotion-based acceleration of the compressor for individuals. Methodologies of experiential thinking postulate that our comprehension of facial emotional reactions depends significantly on facial behavior imitation and the reactions as opportunities. Considering the theoretical foundations of combined logical reasoning. In addition, the hypothesis of probability, it additionally is not effective to build a comprehensive hypothesis concerning impressions. Combining emotional intelligence with fuzzy logic as a combination, we were able to tackle issues with current techniques that neither artificial intelligence nor fuzzy mathematics alone could
Ensuring Privacy and Security on Banking Websites in Malaysia: A Cookies Scanner Solution
No full textIn this new era of science and technology, data can be said to be an extremely valuable asset for individuals, corporations, and even countries. Different parties attempt to obtain users' data occasionally, and the collection of web cookies is a prominent example. When users use a computer network, their data will be saved by the web server as cookies, including their private information. As people with bad intentions obtain this information, they can use it to commit cybercrimes and cause losses to the information owners. Thus, cookies management is vital for web users to protect their data. This paper proposes a cookies scanner for banking websites in Malaysia to help web users manage cookies. The scope is focused on banking websites as it is the most targeted website by cybercriminals. The proposed scanner will help users identify, understand, and manage cookies to keep their banking information safe. This paper explores existing cookie scanners to determine the proposed system's design and identify improvement areas. In this paper, we proposed a framework to develop the cookie scanner in the browser extension format. The system's access mode, workflow, functionalities, technical specifications, and requirements are discussed throughout the paper. To show our contribution, a copy of the proposed code implementation has been made available at https://github.com/gnohiy/cookies-scanner-for-banking-websites-in-malaysia.git
A Fundamental Study of an Alternative Learning Framework Utilizing Natural User Interface (NUI) for Physically Disabled Students
No full textAn alternative learning framework utilizing a natural user interface (NUI) can be applied in the context of education for students whose needs are not catered for in the current learning environment in Malaysia. The alternative learning program would still follow the current subject syllabus, but with differences in how the lessons are delivered, learned and executed. A conceptual framework that enables the adoption of the alternative learning program using Microsoft Kinect in Malaysian education system was then proposed to minimize the gaps found in the current learning setting to cater for the special needs of physically disabled children in Malaysia, in particular, primary school children, using the National Curriculum as a guide. Since this is a new framework, the validity and reliability of the proposed framework will be analyzed. A usability test would also be conducted to gauge the acceptance of the proposed framework amongst the children.
Manuscript received: 2 Dec 2022 | Revised: 17 Feb 2023 | Accepted: 10 Mar 2023 | Published: 30 Apr 202
Prostate Cancer Classification Based on Histopathological Images
No full textProstate cancer is a significant health concern, ranking as the third most common cancer in Malaysian men, with increasing incidence in Asia. The importance of automating the prostate cancer classification process lies in its potential to significantly improve diagnostic accuracy, reduce subjectivity, and enhance overall efficiency compared to the manual approach. The objective of this thesis is two-fold: firstly, to effectively enhance and segment crucial features in the images to aid in the classification process, and secondly, to implement a binary classification task that indicates the presence or absence of malignant tissue on histopathology images. The study compares the performance of two image enhancement approaches, stain normalization with adaptive histogram equalization (AHE) and sharpening, and stain normalization with traditional histogram equalization (HE) and sharpening. Additionally, three machine learning models, namely SVM, DenseNet121, and InceptionResNetV2, are implemented and evaluated for prostate cancer binary classification. The findings reveal that AHE contributes to better contrast enhancement and image quality preservation. Moreover, the InceptionResNetV2 model demonstrates superior performance in terms of accuracy (97.25%), sensitivity (97.5%), specificity (97.5%), and area under the curve (AUC) (97.5%).
Manuscript received: 1st May 2023 | Revised: 30th July 2023 | Accepted: 21st August 2023 | Published: 30 September 202