Journals of Universiti Tun Hussein Onn Malaysia (UTHM)
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Contractors’ Perception in Integrating Circular Economy in Industrialised Building System (IBS)
Full text linkIndustrialised Building System (IBS) is well-recognised in improving sustainable deliverables for construction projects. However, the lack of integration of a circular economy (CE) in IBS construction hinders the continual use of resources and limiting waste elimination. This study investigated the IBS contractors’ perceptions of integrating CE in managing construction and demolition (C&D) waste. The STEEP (Social, Technological, Economic, Environmental and Political) matrix adopted in this study determined the drivers, enablers, challenges, and barriers to integrating CE into the IBS application. Twenty respondents from IBS construction companies participated in semi-structured interviews to provide insights into integrating CE in C&D waste management. The results highlighted that IBS contractors in Malaysia strongly associated CE with waste separation activities, reduction of waste generation, recycling and re-use materials of building components to extend its value. Although CE harbours greater potential in terms of the level of circularity (refuse, rethink, reduce, reuse, repair, refurbish, remanufacture, re-purpose, recycle and recover), the limited knowledge of CE among IBS contractors has hindered the optimisation of IBS from contributing to sustainability. Building on the STEEP matrix, the outcomes of the study initiate further study to determine strategies to improve efficient integration of CE in managing C&D waste for IBS projects
The Role of Adaptive Reuse in Revitalizing Abandoned Buildings in Malaysia
Full text linkIn the context of urban development constraints, adaptive reuse of abandoned buildings in Malaysia presents a promising opportunity. While abandoned buildings contribute to significant economic and environmental challenges, they also hold considerable potential for revitalization through adaptive reuse projects. This study explored the key factors influencing the adaptive reuse of buildings and the challenges encountered in such initiatives. The primary aim was to examine the role of adaptive reuse in revitalizing abandoned buildings in Malaysia. Employing a Delphi study approach, data was collected from industry professionals through a questionnaire survey, which identified the factors and challenges associated with adaptive reuse projects. The study revealed several key consideration factors, including government incentives, originality, actors in decision-making, environmental and architectural merit, and social interest. Additionally, it highlighted critical challenges, such as maintenance issues, building code compliance, constraints in building performance, complications arising from multiple ownership, and uncertainties regarding renovation processes. The findings provide valuable insights and recommendations for policymakers, developers, and urban planners, advocating for a sustainable urban development model that leverages adaptive reuse to enhance economic resilience and environmental preservation in Malaysia. The study\u27s limitations include a narrow focus on the Malaysian context and the reliance on expert opinions, which may not fully capture the perspectives of all stakeholders. Future research could address these limitations by broadening the scope to include more diverse perspectives and exploring additional case studies in different regions
Diabetes Prediction Using The Smote-Cart Framework Model for Imbalanced Data Case
Full text linkDiabetes mellitus (DM) is described by chronic high blood glucose levels, which can result in long-term damage, dysfunction, and organ failure. As a result of technological advancements, many researchers are employing machine learning to predict diabetes. They collect patients’ demographics and health information, organizing them into a dataset. However, in most real-world data, the non-diabetic cases exceed the diabetic cases, contributing to bias in the majority class and resulting in low predictive diabetic cases. Therefore, a Synthetic Minority Oversampling Technique (SMOTE) has been proposed to improve diabetic prediction on the dataset samples before training the Classification and Regression Tree (CART) model. The proposed framework involved the preprocessing step (SMOTE and categorical conversion), CART training, hyperparameter tuning, and evaluation metrics. With a combination of 8 leaf numbers per node, a maximum of 10 splits, and deviance as the split criterion, the model achieves an overall accuracy of 98.72%, a precision of 98.94%, a sensitivity of 98.44%, and an F1-score of 98.67%. In conclusion, the proposed SMOTE-CART framework can effectively address the imbalanced data in a diabetes dataset and improve the accuracy of diabetes prediction
Beef Freshness Classification Using CNN with DCT and GLCM Feature Extraction
Full text linkThe increasing global demand for beef, which has risen by 13.9% over the past decade, underscores the growing importance of ensuring meat quality and freshness in the food industry. Conventional methods for assessing beef freshness rely on manual visual inspection, which is time-consuming, subjective, and often inaccurate. To address these limitations, this study proposes a hybrid approach that integrates the Discrete Cosine Transform (DCT), Gray Level Co-occurrence Matrix (GLCM), and Convolutional Neural Network (CNN) techniques for automated beef freshness classification. A dataset of fresh and spoiled beef images was used, followed by a series of preprocessing steps, feature extraction using DCT and GLCM, and classification through a CNN-based model. The integration of frequency-domain and texture-based features enhances the model’s ability to capture discriminative visual patterns associated with meat freshness. Experimental results demonstrate that the proposed model achieves an overall classification accuracy of 93%, with F1-scores of 0.94 for fresh meat and 0.93 for spoiled meat. These findings indicate that the DCT, GLCM, and CNN framework provides an efficient and reliable alternative to traditional inspection methods. The proposed approach contributes to the advancement of computer vision applications in food quality assessment, promoting improved automation, objectivity, and quality control across the meat supply chain
Adapting the Entrepreneurship Model to End Poverty in Sabah
Full text linkSabah’s poverty issue becomes the focus of the study due to the high incidence of poverty rate. The government made several attempts, most of which were unsuccessful. To solve this challenge, effective entrepreneurial effort is required. APPGM-SDGs have been created to address this problem. The study aims to adapt the proper entrepreneurship initiative model by employing a qualitative method through focus group discussions. Using six impact evaluation indicators (Deep, Clear, Wide, High, SDG, Gender) as a guide, 10 beneficiary groups from 10 distinct districts participated in the FGDs. Interviews with beneficiaries— mostly entrepreneurs— were conducted to learn how they reacted to the models of eradicating poverty. The progress report created by the solution providers was also cross-checked as part of the data collection process. Although SHARE Model may be useful in identifying the good potential projects before the project commencement, it must also consider ROI and ROV. Noteworthy, incorporating TVET components and ensuring alignment with pertinent SDGs are imperative for entrepreneurs. TVET institutions are therefore actively encouraged to develop close relationships with the community. Additionally, TVET reduces costs, saves time, and streamlines the process. The current study purposely focuses on the main issue related to SDG 1 (No Poverty). Reports from the ten projects representing the Sabah West region become the main reference of the study. The fact that so few of them can link the relevant SDG to the initiative suggests that the community\u27s awareness of SDGs is inferior. Previous experiences engaging in various community projects and past research argued that understanding SDGs has to be parallel with gaining the required knowledge of entrepreneurship. Henceforth, learning what the community is lacking and understanding the return of value to any project of SDGs might elevate the community’s socioeconomics
Developing Future Teachers’ Competences in IT and Robotics Using Virtual and Augmented Reality: A Study of Teaching Effectiveness
Full text linkThe research addresses the need for innovative learning methods to develop competencies in future specialists, driven by rapid digitalization and globalization of social relations. The work aims to study the technologies of virtual (VR) and augmented reality (AR) in the context of developing the information and communication competencies of future teachers. Logical analysis, functional analysis, abstraction, deduction, and induction were utilized. The objects of the study were characterized, their key features were determined, and their role in the formation and development of information and communication competencies was identified. It was noted that using VR and AR technologies in the modern digital age is crucial for enhancing information literacy, communication competence, and motivation in the learning process. During the experiment, which involved senior students, namely 81 students from Kostanay Engineering and Economics University named after M. Dulatov and 60 students from U. Sultangazin Pedagogical Institute, Akhmet Baitursynuly Kostanay Regional University, a program using VR and AR technologies was developed and implemented. It was found that the level of communication competencies at the optimal indicator increased by 40%, and the learning efficiency increased by 31%. The study highlights the importance of structured training in enhancing communication competence and digital readiness among future educators in Kazakhstan. It suggests that teachers need to develop digital competencies, especially in using VR and AR technologies, to adapt to modern educational demands. This research enhances teacher education by equipping educators with essential digital skills for effective teaching
Technology Literacy of Vocational Students in CAD Learning Materials: A Study at Private and Public Mechanical Engineering Vocational Schools
Full text linkIn today’s digital era, technological literacy is a crucial competency, particularly in vocational education where tools like Computer-Aided Design (CAD) are essential for workforce readiness. However, students often face challenges in mastering CAD due to limited technological and graphical skills. This study investigates the level of technology literacy in CAD learning among vocational students from four private and two public schools in West Java, Indonesia. Using a cross-sectional survey method, data were collected via Google Forms from 118 Grade 12 students preparing for competency examinations. The findings revealed that most students demonstrate only a basic understanding of technological principles. Private school students generally outperformed their public-school counterparts, raising concerns about disparities in competency, especially regarding CAD proficiency. Interestingly, factors such as high motivation, adequate school facilities, and supportive environments did not significantly influence students’ technology literacy levels. This suggests that external conditions alone are insufficient to enhance technological capabilities. Instead, the findings highlight the importance of targeted interventions to address these gaps. In conclusion, the study underscores the need for improved instructional models, access to updated learning resources, and enhanced teacher training to strengthen students’ technological literacy and better prepare them for CAD-related demands in vocational context
ABET-Compliant Training Program Implementation Impact on Improvement of Training Quality
Full text linkImproving engineering education quality is essential to meet modern labor market demands and enhance global competitiveness. Accreditation by the Accreditation Board for Engineering and Technology (ABET) is widely recognized as a benchmark for high-quality educational programs. Despite ABET’s international prominence, limited research explores its impact on Vietnamese universities, particularly in adapting curricula to international standards. This study assesses the impact of ABET accreditation on the quality of education at the Industrial University of Ho Chi Minh City (IUH), a prominent Vietnamese institution striving to align with global standards, while contextualising its findings within the broader regional and international landscape. A mixed-methods approach was employed, including surveys of 500 students and 60 faculty members, comparative analyses of pre- and post-accreditation data, and statistical evaluations of key indicators such as GPA, publication rates, and employment statistics. Implementing ABET standards led to significant improvements in education quality at IUH. Average GPAs, initially reflecting a borderline neutral/disagree stance (2.7), improved slightly to 2.9, moving towards agreement. Additionally, student satisfaction increased from 60% to 75%, and faculty satisfaction grew from 73% to 82%, indicating notable enhancements in perceived quality. ABET accreditation proved transformative, bridging academia-industry gaps and preparing students for global careers. Sustaining these outcomes requires ongoing curriculum refinement, stakeholder engagement, and resource investment
Enhancing English Communicative Competence through AI Tools in Vocational Higher Education: A Study Among English for Professional Purposes (EPP) Students
Full text linkThis paper explores the impact of AI tools in promoting language competence (LC) among English for Professional Purposes (EPP) students in vocational higher education. Low LC among EPP learners has implications for academic performance, social integration, and self-confidence at the individual level, and overall student quality and graduate output at the institutional level. A qualitative study was implemented with a focus on exploring the AI tools being employed by EPP learners for language learning, the frequency of use, and the features of the AI tools that promote language competence among EPP learners. Qualitative interview data from nine (9) respondents were analyzed for codes related to the research objectives. Findings highlighted the role of AI features that support feedback, translation, vocabulary auto-suggestion, assessment, and self-monitoring in promoting language competence. Participants also believe higher language competence is related to more frequent use of these AI tools. The study bridges the current gap in the enhancement of communicative competence among EPP students and contributes to ongoing discourse on the specific role of AI-Assisted Language Learning (AALL) within the broader technology-aided language learning (TALL) and language learning strategies (LLS) discourse. Future studies employing quantitative approaches and longitudinal studies will contribute to enhancing the findings while also addressing the development of a clear model for promoting the various components and overall communicative competence of vocational EPP students
Morphology and Physiochemical Characterization of Perfluorosulfonic Acid (PFSA) Membrane for Electrochemical Application
No full textThis report provides a thorough examination of the surface morphology, chemical content, and physical properties of Perfluorosulfonic Acid (PFSA) membrane which is commonly utilised as a conductive membrane in fuel cells, ionic batteries, and electrolysers. This experimental effort is separated into two parts: morphological characterisation and physicochemical analysis, which aim to improve understanding of the membrane functional qualities. The membrane surface and cross-sectional characteristics were examined at varied magnifications using Field Emission Scanning Electron Microscopy (FESEM) and Energy-Dispersive X-ray Spectroscopy (EDX). The EDX results revealed that the membrane surface is predominantly composed of carbon (C), oxygen (O), manganese (Mn), and nickel (Ni), accounting for 22.82% by mass, whereas the cross-section analysis revealed higher mass percentages of titanium (Ti), sulphur (S), oxygen (O), carbon (C), and fluorine (F), totalling 53.51%. Tensile testing confirmed the membrane\u27s strength, with a tensile stress of 13.71 N/mm² and an elongation at break of 73.73%. Thermal stability and breakdown behaviour were determined using Thermogravimetric Analysis (TGA), which validated this membrane thermal endurance at 422oC degradation temperatures. These findings provide significant understanding into the surface morphology and structural functional features of PFSA membrane which allow its optimisation for advanced electrochemical applications