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Fresh and Hardened Properties of Different Percentages of Hybrid Kenaf-Glass Fibres Reinforced Geopolymer Concrete under Ambient Curing Condition
No full textGeopolymer concrete (GPC) has become one of the alternative green materials to normal concrete due to its inherent advantages in minimizing carbon emissions for a sustainable environment. However, geopolymers have a brittle nature, hence integration of hybrid fibres in geopolymer concrete enhances its strength and ductility, mitigating fracture propagation. In this research, two types of fibres namely kenaf (KF) and glass fibres (GF) are hybrid to 1% of the total volume fraction added in fly Ash and GGBFS-based geopolymer concrete known as hybrid fibre-reinforced geopolymer concrete (HFGPC) with different percentages to identify the optimal percentage of the fibre mixture. The composite fresh and hard properties are determined from eight mixes to determine the workability, density, compressive strength and crack patterns. ANOVA was used to analyse the compressive strength results, indicating statistically significant enhancements in performance. The experimental results showed that the optimum HFGPC is 0.3KF-0.7GF mix achieved higher compressive strength characteristics around 51.2 MPa by 27% and 10.8% improvement compared with single KFs or GFs inclusion respectively. Moreover, increasing density and reducing crack propagation have been observed for the optimum hybrid mixture. This work provides insight into the performance of HFGPC, Promoting the utilization of sustainable construction materials in practical engineering
Melestarikan Warisan Linguistik dan Budaya : Dokumentasi Istilah Etnobotani Komuniti Bisaya di Limbang, Sarawak.
Get PDFKajian ini memberi tumpuan kepada dokumentasi istilah etnobotani dalam kalangan komuniti Bisaya di Limbang, Sarawak. Komuniti ini mempunyai pengetahuan tradisional berkaitan penggunaan tumbuhan dalam perubatan, makanan dan ritual budaya. Namun, perubahan gaya hidup dan kemerosotan penguasaan bahasa ibunda telah menyebabkan istilah-istilah ini semakin terpinggir. Dengan pendekatan etnolinguistik dan metodologi kualitatif, penyelidikan ini mengenal pasti serta menganalisis beberapa istilah utama yang mengandungi nilai budaya dan makna linguistik. Kajian mendapati wujudnya pola linguistik seperti reduplikasi, simbolisme gender dan metafora alam dalam istilah tersebut. Hasil ini memberi asas kepada pembangunan glosari dan pangkalan data warisan linguistik bagi tujuan pemuliharaan dan pendidikan generasi akan datang
Comparative Analysis of Local and Transferred ANN Models in Landslide Susceptibility Prediction in a Tropical Region
Get PDFLandslides are a common form of natural disaster in the tropics due to heavy rainfall in the wet season. Due to the hazards that come with landslides, determining the susceptibility of an area is of utmost importance. Currently, this is done through an MLbased approach. However, some areas may lack the required data. Thus, this study focused on comparing the impact of a transferred ML model from a comprehensive data region to a localized model. This was done by developing an ANN model trained on data
from Western Sarawak and comparing it to the localized model in the west coast of Sabah and Selangor. The transferred ANN model results were acceptable, with recall scores of 0.89 and 0.86 for the west coast of Sabah and Selangor, respectively, while the localized models both achieved a recall score of 1. AUC scores were also comparable, at 0.988 and 0.995 for the west coast of Sabah and Selangor, respectively, while the localized models both achieved an AUC of 1. For the LSMs, in both target areas, the transferred ANN model predictions were heavily skewed in comparison to the localised model. It is recommended that future studies test the transferability in other tropical regions beyond Southeast Asia
Optimising Biogas Utilisation from Palm Oil Mill Effluent in Dual-Fuel Engines : A CFD Simulation Approach
Get PDFThe transition towards sustainable energy is crucial for mitigating climate change and reducing dependence on limited fossil fuels. This study aims to optimise the utilisation
of biogas generated from palm oil mill effluent (POME) in dual fuel engines through computational fluid dynamics (CFD) simulation. However, this study addressed the challenge of variation in the composition of raw biogas. These differences may make it difficult to effectively control the combustion of internal combustion engines. Thus, to
overcome this challenge, the composition of biogas is fixed throughout the cleaning and reforming stages in this study. Using a three-dimensional computational model to evaluate the operation of a single-cylinder compression ignition engine at 1300 rpm under traditional diesel and dual fuel conditions. Due to the symmetry of the cylinder and the periodic pattern of the injector nozzle holes, a 60-degree sector grid representing one-sixth of the cylinder was selected to simulate the entire geometric shape. Using ANSYS Forte software for CFD combustion simulation, this study
investigates the effects of reforming biogas substitution on the indicated average effective pressure, total power, thermal efficiency, combustion efficiency and emission
characteristics of nine different biogas diesel components (from 0% to 0%). 80% biogas substitution is 20% step size. The research results indicate that replacing diesel with
gas fuels such as reformed biogas in dual-fuel engines can affect the performance and efficiency of the engine. Although combustion efficiency and thermal efficiency may
initially increase, they will significantly decrease at higher substitution rates, especially at 80%. Nevertheless, reforming biogas still has advantages such as reducing emissions and maintaining output power at medium to high loads. However, compared to traditional diesel engines, challenges such as decreased volumetric efficiency and
indicated mean effective pressure (IMEP) lead to an overall decline in engine performance
Enhancing the performance of hybrid bio-composites reinforced with natural fibers by using coupling agents
Get PDFNatural fiber-reinforced hybrid bio-composites are emerging as sustainable alternatives to traditional composites due to their environmental benefits and desirable properties. However, the interfacial interaction between natural fiber and polymer matrix is very weak. Thus, this study looks into the effect of maleic anhydride (MAH) coupling agents on the performance of natural fiber-reinforced hybrid biocomposites. The bio-composites were prepared using jute fiber, kenaf fiber, and polylactic acid (PLA) through the hot compression method. We treated both natural fibers with MAH coupling agents before using them in the production of biocomposites. Comprehensive characterization techniques, including tensile strength, modulus, and impact strength, were employed to evaluate the mechanical properties of the composites. The mechanical results indicated a significant improvement in mechanical properties for the bio-composites treated with coupling agents. The tensile strength of
bio-composites increased by 35%, tensile modulus by 15%, and impact strength by 20% after modification with MAH coupling agents. The surface morphology and chemical interactions between the fiber and polymer matrix were investigated using SEM and FTIR studies. The FTIR result reveled that the intensity of C=O peaks enhanced after MAH treatment. Moreover, SEM images exposed better fiber dispersion and adhesion, corroborated by FTIR spectra showing enhanced chemical bonding where MAH reacted with the cellulose backbone of the fibers and formed fiber cellulose ester.
Furthermore, TGA results revealed that adding MAH coupling agent to the fiber increased the thermal stability of biocomposites
Connecting the Dots: Exploring Means-End Theory in the Context of Customer Decision-Making for Sustainable Practices in Hospitality
Get PDFUnderstanding customer decision-making towards sustainable hospitality practises is crucial in today's environmentally sensitive society and this study examined means-end theory (MEC) to display how customers' decisions are influenced by product features and perceived outcomes and values as the study presented a Consumer Decision Map (CDM) using quantitative methods to reveal consumer behaviour’s main decision patterns. Consumers' environmental concerns and willingness to pay more for hotels with strong green initiatives are strongly correlated and this emphasised over the importance of MEC and social identity theory and how values influenced consumer decisions. Similarly, the study also shed light on how hotel type affects consumers' willingness to pay (WTP) for sustainability as the luxury and mid-priced hotel visitors are more likely to pay for green efforts, suggesting a sustainability-based market distinction. Further investigation established that attitudes towards sustainability, perceived costs and benefits while perceived behavioural control are key to sustainable consumer behaviour (SCB) among luxury hotel customers under which the study focused over the need to expand the means-end theory (MEC) to fully understand SCB in the context of perceived costs and rewards.
These results indicated major consequences for marketers and politicians under which effective communication and branding tactics that match consumers' beliefs and goals are crucial while the marketers would use CDM data to emphasize the link between sustainability and customer well-being, increasing green project acceptability and these data would also help policymakers create targeted policies to encourage sustainable hospitality practices. In this manner the research exposed the complex relationship between consumer values, hospitality decision-making and environmental measures while it linked means-end philosophy, customer behaviour and environmental concerns to create a more sustainable hospitality future.
keywords: context, perceived, sustainability, willingnes
Improved Colour Visualization in Pap Smear Images Based on HSV Channel Analysis
Get PDFCervical cancer is caused by abnormal cell growth in the female cervix. It is among the most well-known causes of women's deaths globally. Early detection of cervical cancer
can reduce the mortality rate and increase the chance of survival. One of the most critical components of the auto-detection system is image pre-processing. The main factors that could influence the accuracy of the diagnosis are the Pap smear image quality and contrast. Therefore, this paper aims to analyse various approaches to ensure smooth
segmentation and determine which pre-processing techniques are best for a nucleus auto-detection system. Two hundred images were used as input from the Herlev dataset. There are two pre-processing stages: noise removal and contrast enhancement. To preserve the colour, only the colour images' brightness (V) channel will go through the pre-processing. Without noise, the anticipated resultant image depicts only the object (nuclei and cytoplasm) and background. Results show that the median filter produces the best result regarding smoothening and debris removal in visual analysis. At the same time, Pairing Adaptive Gamma and Clipping Histogram Equalisation (PAGCHE) method produces the best brightness and contrast improvement results based on visual
and quantitative analysis. The results were compared with anisotropic diffusion, Non-Local Haar (NLH), and bilateral filters in the denoise stage and histogram equalisation,
contrast stretching, and Contrast Limited Adaptive Histogram Equalisation (CLAHE) for the contrast enhancement stage. The performance was evaluated based on mean, absolute mean brightness error (AMBE), standard deviation (STD), structural similarity index metric (SSIM), peak signal-to-noise ratio (PSNR), and entropy. The average PAGCHE shows the highest Mean and AMBE values at 148.07 and 21.96, respectively, while the STD value is the second highest compared to other methods at 60.4. The median filter produces the lowest SSIM score and low PSNR scores compared to the others but relatively high values at 0.71 and 15.38, respectively, with an entropy of 7.30, indicating a good noise removal ability that can be observed in visual analysis
Spatial Autocorrelation Analysis of Infectious Disease Incidence Rates at State and District Level Using Supra-Adjacency Weights Matrix
No full textThe spatiotemporal correlation in disease incidence rates resulting from the spatial arrangement of neighboring geographical units is often conceptualized
through constructing contiguity-based spatial weights. However, these weights specifications are not meant for capturing the spatial relationships across multiple spatial scales and disjoint spatial units. Modifications to existing
spatial weights specifications are highly required. Hence, this study used supra-adjacency matrix in network science to analyze the spatial autocorrelation of COVID-19 incidence rates at Sarawak’s district and Malaysia’s state levels. Flight routes between these regions were embedded as spatial interaction submatrix to represent their inter-layer adjacency. Segmentation of data based on respective
Sarawak’s and Malaysia’s daily cases was conducted to investigate the consistency in the spatial autocorrelation and the type of local clustering. When global spatial autocorrelations at state level were high, both the Sarawak districts’ and Malaysia states’ incidence rates became more spatially related with the inclusion of spatial interaction. Several districts, including Sibu, in Sarawak were now
classified as high-high cluster with supra-adjacency weights. These high-high clusters can only be discovered with second-order contiguity weights in previous literature. The numbers of significant spatial clusters and outliers in district level were substantially greater than its state-level counterpart. This research provides evidence on how spatial dependencies of disease incidence rates between
two spatial aggregation levels and geographically disjoint regions can be quantified using supra-adjacency matrix for disease surveillance. Capturing inter-layer spatial dependencies allows for more targeted interventions such as optimizing vaccine distribution and planning mobility restrictions during pandemic
Self-Perceived Employability and Readiness for Reentry into Society : Insights from Prerelease Inmates in Sarawak, Malaysia
No full textReentry involves a multifaceted reintegration process following incarceration, requiring social, psychological, and economic adjustments. This study examined the relationship between self-perceived employability and readiness for reentry among 384 prerelease inmates in six Sarawak prisons in Malaysia. Most participants were Malay males aged 25–29 years, with upper secondary education and multiple convictions, primarily for drugrelated offences. Statistical analysis revealed a significant positive correlation between self-perceived employability and reentry readiness. These findings highlight the role of employability in successful reintegration and provide policymakers with place-based evidence to design tailored interventions aligned with Malaysia’s commitment to sustainable development goal 16
Manual Counselling Supervision
No full textManual Counselling Supervision offers a comprehensive guide to supporting counsellors through structured, theory-based, and reflective supervision. This manual explores the historical evolution of supervision, its purposes, and various types and styles used to tailor the experience to individual needs. It delves into theoretical frameworks and models such as System Approach to Supervision Model, Contextual Factors of Supervision, Discrimination Model of Supervision, and Developmental Model, providing practical tools for effective supervision interventions. Key themes include managing the roles and relationships between supervisors and supervisees, addressing multicultural considerations, and fostering professional development. Additionally, the manual emphasizes navigating legal and ethical challenges to ensure quality practice and safeguard both client and counsellor well-bein