The Role of Adaptive Reuse in Revitalizing Abandoned Buildings in Malaysia

In 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

Diabetes 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

The 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

Contractors’ Perception in Integrating Circular Economy in Industrialised Building System (IBS)

Industrialised 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

Characterization of The Properties of South Lampung Clay as Lightweight Expanded Clay Aggregate

Bloating properties are essential to determine clay\u27s ability to expand and form pore structures for lightweight expanded clay (LECA) applications. South Lampung clay was taken from four different places: TN, TB1, TB2, and TJ. The clay was dried at 110oC until the water content was 7%, then ground using a ball mill to 200 mesh. The clay was formed into balls with a diameter of 10 mm and then heated at 1,050oC for 15 minutes. The chemical composition was analyzed by X-ray fluorescence. X-ray diffraction was used to analyze the crystal structure formed. Topography was analyzed using FESEM. The bloating coefficient (Cb) was calculated by comparing the volume before and after heating. Based on SiO2, TN and TB1 meet the self-bloating standard with 52.28 and 56.82% content, respectively. However, based on Al2O3, only TB1 meets the minimum standard with a value of 17.46%. Based on the total flux being below 10%, all clay has the potential for self-bloating. The type of clay is kaolinite with feldspar and kaolin phases. The bloated clay was found in TB1 and TJ with values ​​of 1.08 and 1.46. Additives are needed to increase an expansion. This study can be developed to obtain the composition of local clay, which can be applied to various fields

Microstructure and Mechanical Characteristics of Welded AISI 1020 Low Carbon Steel Based on the Influence of Weld Joint Design and Shielded Metal Arc Welding Process

This study examines the impact of joint design on the microstructure and mechanical properties of welded AISI 1020 low carbon steel using Shielded Metal Arc Welding (SMAW) with E6013 electrodes. Bevel, butt, and half-lap joints were welded under identical conditions and assessed for mechanical and microstructural performance. The bevel joint exhibited the best overall performance, with improved tensile strength (188.39 MPa), yield strength (113.98 MPa), and impact strength (34.54 J/mm²) compared to butt and half-lap joints due to better weld penetration and load distribution. Microstructural analysis using optical microscope confirmed the presence of distinct ferrite morphologies, including ferrite, Widmanstätten ferrite, and acicular ferrite in the weld metal. The uniform distribution of phases and minimal welding defects in the weld metal zones of the bevel joint further support its mechanical superiority. These results highlight the importance of joint design in optimizing welded steel structures, with the bevel joint proving most suitable for high-strength applications. Hence, the research contributes to the understanding of the effects of joint geometry on welded steel properties and provides practical insights for industrial welding applications

Are Malaysia\u27s Graduates Prepared The Fourth Industrial Revolution Workforce?: A systematic Literature Review

The Fourth Industrial Revolution is defined by artificial technologies and the Internet of Things, leading to the disappearance of some jobs while creating new ones. Most emerging technologies require advanced technical expertise and academic qualifications, significantly impacting employment, education, and TVET training for skilled workers. Skilled labor is essential for economic advancement and achieving a high-income economy, making it crucial to enhance the quality and participation in TVET. This literature review identifies the new skills needed in the workforce for the Fourth Industrial Revolution, focusing on "fourth industrial revolution skills" and "graduate readiness." The literature is categorized into nine Malaysia Future-Proof Skills: 1) Creativity & Innovation, 2) Holistic, Entrepreneurial & Balance, 3) Resilience, 4) Leadership, 5) Compassion & Mindfulness, 6) Value & Ethics, 7) Flexibility & Adaptability, 8) Critical Thinking & Problem Solving, and 9) Communication & Language Proficiency. Utilizing a systematic literature review methodology and the PRISMA procedure, this study synthesizes findings from journals and industry reports. The findings suggest that the nine Future-Proof Skills are consistent with the requirements of businesses that are in search of 4IR professionals. Therefore, further research on human resource perspectives regarding 4IR skills is necessary. Strengthening these skills among Malaysian graduates is vital to fostering high-quality, future-proof talent. To thrive in the machine-human technology era of 4IR, Malaysian graduates must embrace all nine future-proof skills. This study aims to enhance understanding of 4IR skills among graduates, institutions, and industries

Education 2030 - Achievements of TVET in Asia and The Pacific along with The Fourth Industrial Revolution

The modernization of TVET has not occurred with a system-wide approach covering the entire spectrum of TVET institutes worldwide. The literature that incorporates the Sustainable Development Goal for Education (SDG4) and the fourth industrial revolution in TVET is very rare to be found from international and comparative standpoints since these areas are still emerging. Further, case-based or single country-based experiences do not provide sufficient information to make informed decisions. Therefore, more empirical studies are needed on the adoption of SDG4 in TVET institutes to gain a broad-based understanding of the prevailing context.  Given these gaps in the scholarship, the present study investigated the status of the adoption of SDG4 in TVET institutes. Accordingly, the study collected data covering the areas of 1) the teaching and learning context, 2) steps taken to impart skills for employment, and 3) steps taken to enhance the capacities of staff in response to the changing world of work from fifteen Asian and Pacific countries. Four hundred and twenty-eight TVET staff responded to the survey. The findings showed significant differences by the regional classification of the country and by the type of TVET institute. The findings of the study are novel and provide ample evidence for the status of TVET in incorporating SDG4 in the fourth industrial revolution era. The findings also showed that the policymaking bodies must take active measures to increase responsiveness in fulfilling SDG4 and addressing challenges brought about by the fourth industrial revolution technologies

Enhancing Spare Parts Inventory Control in Automotive SMEs: A Digital Approach with Google Tools Integration

Smooth operation of manufacturing processes is critical for maintaining production efficiency, and machine downtime can significantly disrupt operations, leading to substantial financial losses. One of the primary contributors to extended downtime is the unavailability of replacement parts due to inadequate spare parts management. Traditional manual inventory control often results in unclear spare part statuses, leading to stockouts and further production delays. This study aims to digitalize and optimize spare parts inventory management for small and medium-sized enterprises (SMEs) in the automotive sector by developing an integrated system using Google-based tools. The system leverages Google Sheets as the central database, AppSheet for mobile-based data input and transaction management, and Looker Studio for real-time visualization of inventory status through interactive dashboards. Key features of the system include stock level alerts, barcode scanning for faster data entry, and predictive analytics for demand forecasting. The integration of these tools creates a cohesive system that eliminates manual record-keeping, enhances the accuracy of spare parts tracking, and prevents issues such as stockouts and overstocking. Additionally, the system allows easy access to critical information, including supplier details, pricing, and specifications. Through effective spare parts management, the system not only reduces machine downtime but also optimizes operational costs and improves decision-making processes in inventory management, contributing to more efficient and cost-effective manufacturing operations

Variation Management in Construction Contracts: A Comparative Study of PWD 203A (Rev. 01/2010) and PAM 2018

The Malaysian construction and development sector plays a vital role in driving national economic growth. Yet, project performance often suffers when stakeholders manage variations ineffectively, causing delays and reducing overall efficiency. Variations in major contracts typically result in financial overruns and extended project durations. Though standard contracts outline procedures, inconsistent application often leads to disputes and operational inefficiencies. Empirical evidence highlights the dynamic and uncertain nature of variation practices, wherein inadequate implementation exacerbates risks to project outcomes. This research seeks to offer a thorough insight in best practice through a comparative examination of Malaysia’s prevalent standard forms of contracts (SFOC), PWD 203A (Rev. 01/2010) and PAM 2018. This research aims to investigate the current variation management procedures outlined in PWD 203A (Rev. 01/2010) and PAM 2018, assess effective variation control methods, and formulate best practice models. A dual methodology was employed, which integrated comprehensive document reviews and semi-structured interviews with six interviewees: two project managers, one architect, one contract administrator, one contract manager, and one consultant from industry professionals, all contributing to a robust contractual analysis. Comparative analysis employs four strategies, which will be examined and supported by academic sources, professional standards, and contractual documentation from 2010 to 2024. Findings aim to reveal success determinants in effective communication, rapid decision-making, and contractual clarity enhancing variation governance and efficiency