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Maqasid syariah tonggak jaminan sistem kawalan makanan halal
Full text linkDalam dunia yang semakin kompleks, pemahaman mengenai ilmu Maqasid Syariah menjadi semakin penting, terutama dalam konteks industri makanan halal. Dengan kesedaran untuk berkongsi ilmu, karya ini dihasilkan untuk mempromosikan nilai halal, mendukung pemahaman serta menyokong pembangunan industri makanan halal. Buku "Maqasid Syariah Tonggak Jaminan Sistem Kawalan Makanan Halal" ini diinspirasikan daripada dapatan kajian lapangan yang telah dijalankan oleh penulis bersama pasukan penyelidik. Buku ini membawakan analisis tentang peranan Maqasid Syariah dalam memperkukuh sistem kawalan makanan halal. Pembangunan industri makanan halal di Malaysia ditunjangi oleh dasar dan strategi yang berkesan. Walaupun begitu, industri ini masih berdepan dengan kepincangan yang memerlukan perhatian terutamanya dari aspek kawalan. Sistem kawalan makanan halal adalah komponen penting dalam memastikan integriti dan kualiti produk makanan halal. Dari perspektif teori, penulis mengupas bagaimana prinsip Magasid Syariah berperanan memberi panduan dalam pelaksanaan proses kawalan terhadap sesuatu produk makanan dan minuman yang dilabelkan halal. Melalui kajian empirikal, buku ini menggariskan prinsip Magasid Syariah dan formula yang relevan untuk diterjemahkan dalam pelaksanaan kawalan makanan halal. Namun, cabaran seperti integriti pengusaha, pengetahuan pengendali, dan kesediaan pematuhan memerlukan strategi pengurusan yang berkesan untuk memastikan industri halal dapat berkembang dengan mampan dan memenuhi tuntutan masyarakat
Enhancement of flat spiral antenna for non-radiated inductive wireless energy transfer
Full text linkThe book, "Enhancement of Flat Spiral Antenna for Non-Radiated Inductive Wireless Energy Transfer", offers a comprehensive study of inductive wireless energy transfer (WET) systems, emphasizing the enhancement of transfer efficiency through optimum flat spiral antenna designs. The primary methodology of the book focuses on theoretical modelling, various technique, simulation, and experimental validation to improve antenna performance in WET applications. The book emphasizes the critical importance of antenna shape, material, distance and design structure in improving transfer efficiency. The improved flat spiral antenna demonstrates significant enhancements in energy transfer and size reduction, crucial for mobile and compact devices. Through the modification of the number of turns, loop gap, and material selection, the author achieves significant enhancements in efficiency without requiring larger antennas. The book offers significant improvements to the advancement of inductive WET systems, namely in improving energy transfer efficiency while preserving compact and mobile-friendly designs. Ideal for researchers, engineers, and students, this book helps readers understand the fundamental principles and advanced techniques in wireless energy transfer
Graphene based Perovskite solar cells : The rise of emerging photovoltaic technology
Full text linkGraphene-Based Perovskite Solar Cells: The Rise of Emerging Photovoltaic Technology explores the transformative potential of graphene in revolutionising solar energy. This book examines the fundamental principles of perovskite solar cells (PSCs), their challenges, and how graphene's unique properties can enhance performance, efficiency, and stability. By addressing issues such as material degradation, improving charge transport, and enabling flexible solar cells, graphene's role in PSCs is set to drive the next generation of renewable energy solutions. Written for professionals and enthusiasts, the book highlights the latest advancements in graphene integration, offering insights into the industrialisation and commercialisation of PSC technology. Whether you are a researcher, engineer, or energy enthusiast, this comprehensive resource provides an in-depth understanding of the future of solar energy
Resilient supply chains in Malaysia's manufacturing sector: A comparative analysis of priority industries affected by COVID-19
Full text linkThe COVID-19 pandemic exposed vulnerabilities within global supply chains, with Malaysia’s manufacturing sector, a cornerstone of the nation’s economy, experiencing significant disruptions. This study explores the interplay between supply chain risk management (SCRM), supply chain resilience (SCR), and sustainability efforts (SE) within the context of Malaysia’s priority manufacturing sectors—namely aerospace, chemicals, electrical and electronics (E&E), pharmaceuticals, and medical devices. Employing a quantitative research approach, data were collected from 360 firms, and the hypothesized relationships were analyzed using structural equation modeling. The findings confirm that effective SCRM practices significantly enhance SCR across all sectors, with the E&E industry exhibiting the strongest relationship due to its reliance on globalized networks. Furthermore, SCR positively influences supply chain performance (SCP), highlighting its critical role in maintaining operational efficiency, delivery reliability, and customer satisfaction during disruptions. The study also reveals a nuanced moderating role of SE on the SCRM-SCR relationship, with significant effects observed in the aerospace sector, underscoring the sector-specific dynamics of resilience-building efforts. This research offers one of the first empirical assessments of these dynamics across Malaysia’s most strategic manufacturing industries, providing sector-specific insights aligned with the country’s New Industrial Master Plan 2030. The findings offer valuable guidance for Malaysian businesses and policymakers seeking to enhance supply chain robustness, sustainability, and competitive advantage in preparation for future disruptions
Finding new similarities measures for Type-II Diophantine neutrosophic interval valued soft sets and its basic operations
No full textThe Type-II Diophantine neutrosophic interval valued soft set (Type-II DioNSIVSS) and related similarity measure are presented in this study. An extension of the neutrosophic interval valued soft set (NSIVSS) and the Diophantine fuzzy soft set is the Type-II DioNSIVSS. The suggested measure for Type-II DioNSIVSS assessment. We support a method of solving the problem using the Type-II soft set model. To demonstrate
how they can be applied to successfully handle uncertainty-related challenges, illustrative examples are given
Effect of adding al2o3ceramic in wire arc additive manufacturing 308LSi stainless steel
No full textWire Arc Additive Manufacturing (WAAM) is a process that allows for efficient in-situ production of components or remanufacturing based on its capabilities to produce at a greater rate of deposition at a lower cost. However, WAAM components suffer from heat dissipation during the deposition process that causes the growth of coarse columnar grains resulting in poor mechanical properties that will limit industrial applications. Thus, this research investigates the role of introducing Al2O3 ceramic powder particle inoculants to the AWS A5.9 ER308LSi stainless steel wall structure to enhance the mechanical performance capabilities by refining the grain process. During deposition, the Al2O3 ceramic powder particle was manually added to each layer when the temperature drops to 150ᵒC. A complete series of tensile testing was executed to bridge those knowledge gaps. WAAM walls were fabricated and the microstructure of the sample were analysed. The results revealed that the highest tensile strength of WAAM SS308LSi components recorded at 560 MPa in the deposition direction, which increased by 6% compared to the non-inoculated sample. The improvement was due to the success of grain refinement and heterogeneous nucleation. The study demonstrates the potential of the technique to improve the mechanical properties and microstructure during WAAM components fabrication or remanufacturing
Effect of filler size on the properties of oil palm empty fruit bunch high-load filler biocomposite
Full text linkThis work aimed to study the effect of filler size on the performance of an empty palm oil fruit bunch (OPEFB)
high-load filler epoxy resin biocomposite (80 vol.% OPEFB and 20 vol.% epoxy resin). The particle sizes of OPEFBs
used to prepare the biocomposites were 60, 80, 100, 120 and 140 mesh. The biocomposite samples were prepared by the
press method. The physical (density, porosity, thickness swelling), mechanical, and thermal properties of the
biocomposite were evaluated. A universal testing machine, thermogravimetric analysis, and scanning electron microscopy were utilized to characterize the biocomposite samples. The results show that the physical, mechanical, and thermal properties of the OPEFB epoxy resin biocomposite are significantly affected by the particle size of OPEFBs. As the particle size was reduced from 0.250 to 0.105 mm, the density improved from 0.974 to 1.101 g/cm3, the porosity decreased from 15.1 to 9.1 %, and the thickness swelling decreased from 14.2 to 7.4 %. The modulus of rupture and modulus of elasticity improved from 9.7 to 22.8 MPa and 1,667 to 2,403 MPa, respectively. Thermal analysis indicated that finer fillers enhanced thermal stability. The OPEFB biocomposite remained stable up to 300 °C. Smaller filler sizes exhibited improved biocomposite properties, which were attributed to better interfacial bonding and uniform dispersion within the matrix. The results of this study demonstrate that the performance of biocomposites can be significantly enhanced by reducing the size of the fillers. These findings indicate that filler size is crucial for high-load filler biocomposites
An efficient irrigation based on hargreaves potential evapotranspiration to improve yield for tomato plantation
Full text linkWith a tropical climate in Malaysia, varieties of vegetables can grow all year round. Nevertheless, during the hot season, watering the plant is challenging, especially for vegetables that are intolerant to heat such as tomato plants. Over-watering or under-watering could decrease the yield and quality of tomatoes. Therefore, in this study, we proposed an efficient irrigation system based on Hargreaves’s potential evapotranspiration to improve the yield and quality of tomato plants in Melaka, Malaysia. Using the Hargreaves equation, the correlation between the surrounding temperature and the amount of water needed by the tomato plants is investigated. Three growth stages are considered: early stage (0−30 days of planting), middle stage (31−76 days of planting), and final stage (77−105 days of planting). Based on a 30-day analysis, on average, tomato plants require 45.5 mL/day, 87.4 mL/day, and 60.8 mL/day respectively for the early, middle, and final stages of growth. A mobile monitoring application is also developed using MIT App Inventor for users to monitor
the temperature, humidity, soil moisture, pH level, status of water pumps, and the amount of water released to
the plants. The proposed system can increase the efficiency of the irrigation process and ultimately, reduce the farming cost
The influence of laser cutting parameters on the heat-affected zone in fast-growing Malaysian wood species
Full text linkWood is a naturally occurring renewable resource widely used in various industries, including in construction, packaging, furniture, and paneling. In Malaysia, 80%
of furniture products are made from wood, making it a crucial material in this sector. Laser cutting is an advanced machining technique that enhances precision and minimizes
material waste, yet its thermal effects, particularly the heat-affected zone (HAZ), remain a challenge. This study investigates how laser cutting parameters—including the laser power, traverse speed, and focus position—affect HAZ formation in two fast-growing Malaysian wood species, Acacia mangium and Azadirachta excelsa. This research seeks to determine the optimal laser settings that minimize HAZ dimensions while maintaining cutting precision. A diode laser cutting system was used to analyze the effects of three
laser power levels (800, 1500, and 2400 mW), three traverse speeds (2, 5, and 10 mm/s), and three focus positions (on-focus, +0.2 mm, and −0.2 mm). We employed statistical analysis, including a two-way ANOVA, to assess the significance of these parameters and their interactions (p < 0.001). The results indicate that a higher laser power and slower speeds significantly increase the HAZ’s width and depth, with Azadirachta excelsa exhibiting a greater HAZ width but shallower penetration compared to Acacia mangium. A slight above-focus position (+0.2 mm) reduces the HAZ’s width, whereas a below-focus position (−0.2 mm) increases the HAZ’s depth. The optimal parameters for minimizing HAZ dimensions while ensuring efficient cutting were identified as a 1500 mW laser power, a 10 mm/s
traverse speed, and an on-focus position (0 mm). This study provides practical insights into laser parameter optimization for tropical wood species, contributing to improved
precision in laser machining and sustainable wood processing practices. These findings support industries in adopting advanced, high-quality laser cutting techniques tailored to
fast-growing wood resources
Location independent human activity recognition using self-training CSI-based techniques for wireless sensor networks
No full textHuman activity recognition (HAR) using WiFi is applied across various domains ranging from smart environments, the Internet of Things (IoT) and immersive virtual gaming. The environmental effects of WiFi sensing lie in its susceptibility to variations in physical surroundings, which influence signal strength and accuracy in detecting human activity. Innovative solutions are needed to meet these demands, such as activity-adapted learning for seamless feature transfer
and recognition across various locations, reducing the reliance on extensive training datasets. This work proposes a framework incorporating a confidence threshold to filter unreliable samples, a progressive self-training strategy to integrate unlabeled data, and a weighted self-training approach to counter class imbalance. The proposed model explores HAR and its improved performance by integrating self-training techniques. This work enhances HAR by reconciling self-training’s potential with challenges and
offering practical insights for reliable activity recognition within wireless sensor networks. The results of experiments show that the self-training method, which uses channel state information based features to train the model with unlabeled data, is up to 97.5% accurate. Additionally, experiments using HAR datasets validate the proposed method and displays performance improvements over baselines