Universiti Malaysia Pahang

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    36847 research outputs found

    Experimental investigation of carbon-based nano-enhanced phase change materials assimilated photovoltaic thermal system: Energy, exergy and environmental assessment

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    Photovoltaic thermal systems (PVT) are advanced systems designed to simultaneously generate heat and electricity. However, their commercial performance has not yet reached optimal levels, with efficient thermal regulation being a major challenge that directly affects energy production and efficiency. Methods: This research introduces an innovative approach to enhancing PVT system performance by integrating active water cooling with passive functionalized carbon-based nano-enhanced phase change materials (NePHACMs) as a cooling medium. Four configurations were studied: PV, PVT, PVT-PHACM, and PVT-NePHACM, with fluid flow rates of 0.4-0.8 L/min. Indoor experiments were conducted for PV and PVT systems, while TRNSYS simulations assessed PVT-PHACM and PVT-NePHACM systems. The exergy approach was used to evaluate the energy available for productive use and exergy loss and entropy generation have been analyzed to enhance the electrical energy and thermal storage of the system. Additionally, carbon mitigation and carbon credit gain for all configurations were discussed. Significant Findings: The NePHACM formulation significantly enhanced the system's thermal conductivity by 104%, reduced PV temperature, and improved both electrical and thermal energy production. The system achieved an overall energy efficiency of 85.02% and an exergy efficiency of 12.37%. Additionally, the hybrid system demonstrated exceptional effectiveness in reducing CO2 emissions, highlighting NePHACM's potential to improve PVT system commercialization, especially for nocturnal applications

    The effectiveness of bio-anchorage system in reinforcing tropical residual slope

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    Geotechnical phenomena known as “land sliding” encompasses a broad spectrum of ground movements, including rock falls, deep slope failures, and shallow debris flows, particularly in tropical regions. The severity of this issue is higher in regions with a lot of residual soils, like Malaysia, due to the frequent and intense rainfall events and the unique soil properties that make these areas prone to instability. The use of vegetation in soil bioengineering has gained attention recently as an environmentally friendly technique for stabilizing slopes, as most conventional approaches are neither inexpensive nor universally accessible. The primary objective is to understand the bioinspired soil anchoring system’s interaction mechanism to improve the bonding between the residual soil structure in tropical regions. This research is conducted to determine the relationship between the tensile strength of Eugenia Oleina plant roots and the soil parameters of Gambang residual soil. Laboratory testing for soil properties and classification procedures were conducted. Root tensile strength, compressive strength, and shear strength were determined by conducting an unconfined compression test and a direct shear test. These tests are crucial in understanding the mechanical properties of the soil and how it interacts with plant roots under different stress conditions. The comparison between Eugenia Oleina (EO) and Dicranopteris Linearis (DL) plant roots was obtained to recommend the best plant roots for slope stabilization. Out of all the bioinspired soil anchoring systems for tropical slopes, the findings offer the best answer. Thus, it was determined and suggested which plant species would be the most effective tool in residual soil to reinforce tropical slopes

    Impact of natural lemongrass and agarwood essential oil diffusion on indoor airborne pollutants: A case study of office environments

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    This research explores the use of natural-based essential oils to enhance the quality of indoor air (IAQ) in an office environment using an experimental approach. Lemongrass and agarwood essential oils were studied for their potential to contribute to a healthier and sustainable indoor environment due to their antibacterial properties. The essential oil droplets were released using an Ultrasonic Diffuser, and air quality measurements were taken before and after the diffusion of essential oils. The concentration of airborne bioaerosols, VOCs, PM, and other physical parameters were monitored throughout the sampling period. Lemongrass essential oil significantly reduced the total bacterial and fungal count by 74.19% and 76.34% respectively, while agarwood only significantly reduced the total fungal count by 55.20%. This study found that physical parameters such as air velocity and relative humidity have a substantial impact on the efficiency of essential oil diffusion. With a correlation of more than 47%, lemongrass diffusion showed substantial relationships between air velocity and VOC, PM10, and PM2.5. Diffusion of agarwood showed strong correlations of more than 57% between relative humidity and VOC, TSP, PM10, and PM2.5. Temperature, as controlled by air conditioning, did not affect diffusion. The study adds to our understanding of the antibacterial and antifungal activities of lemongrass and agarwood essential oils. Diffusing essential oils, particularly lemongrass, improved IAQ as the total microbial count was able to be reduced without impacting other parameters, demonstrating a practical and efficient improvement. The beneficial effect on IAQ highlights the potential of essential oil diffusion for healthier indoor environments, hence helping the promotion of good IAQ following safety and health regulations

    Determination of the surface sterilization protocol and optimization of ficus carica callus induction: Unveiling the potential of auxins and low kinetin concentration on callogenesis

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    Ficus carica, commonly referred as fig, is a fruit-bearing tree that has high nutritional and medicinal value. Despite its potential, low proliferation rates and high susceptibility to contamination are the major challenges for the cultivation of F.carica. Micropropagation is the in vitro approach used for the propagation of fig trees that relies on effective surface sterilization and optimal plant growth regulators (PGRs) enriched in the culture medium. The objectives of this study were to determine the surface sterilization protocol for F. carica and to optimize the callus induction in F. carica using a combination of different auxins (naphthalene acetic acid and 2,4-Dichlorophenoxyacetic acid) and cytokinin (kinetin) at varied concentrations. In this study, four surface sterilization treatments were evaluated for their efficiency in minimizing the contamination percentage while enhancing the survival percentage of F. carica. Results showed that M3 treatment (70 % ethanol+20 % Clorox+two drops of Tween 20) showed the highest efficacy, resulting in a minimal contamination percentage of 20.8%, coupled with 66.7% of both leaf survival percentage and callus induction. For callus induction, a combination of kinetin and 2,4-D in the MS basal medium outperformed NAA+2,4-D, with the optimum concentration identified as 1.5 mg/L NAA+1.5 mg/L 2,4-D. Surprisingly, a lower concentration of kinetin (0.2 mg/L)+2.0 mg/L 2,4-D exhibited superior callus induction (100%) compared to higher kinetin concentrations (1.5 mg/L)+1.0 mg/L 2,4-D (94.44%). In conclusion, a lower cytokinin concentration proved optimal for maximum callus induction when combined with auxin, providing valuable insights for improving F. carica micropropagation protocols

    Investigation of moisture content and higher heating value in refusederived fuel from agricultural residues using statistical modelling

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    There is an increasing interest in using agricultural residues and wastes for energy production due to concerns regarding climate change and energy security issues. One of the alternative fuels considered is Refuse-derived fuel (RDF) from biomass, which has a Higher Heating Value (HHV) comparable to coal. This study aims to investigate the relationship between the moisture content and the HHV value. Palm kernel shells (PKS), coconut husks (CH), and coconut shells (CS) were blended at various ratios (10%–80%) and moisture levels (5%, 7%, 10%). The HHV was analyzed through a proximate analysis, with JMP Pro 17.0 modelling the HHV against the moisture content. Then, the Tukey-Kramer analysis identified the optimal energy ratio, thus providing insights into maximizing the RDF efficiency. The result showed that the highest HHV was 21.617 MJ/kg with the RDF2 formulation. Notably, the RDF2 energy content was less than 4% of that of coal, thus demonstrating the potential of utilizing agricultural waste to produce solid fuel with a positive environmental impact

    Synthesis and assessment of Metal-Organic Frameworks (MOFs) adsorbents for CO2 capture: A comparative work of the CO2 adsorption capability of Mono-and Bimetal-based MOFs adsorbents

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    Adsorption utilising porous solid adsorbent has been considered a feasible option for conventional CO2 absorption over the past few decades. As a preliminary investigation towards obtaining Metal-Organic Frameworks (MOFs) adsorbent for CO2 capture, the CO2 adsorption efficiency using mono-and bimetal-based MOFs was assessed in this study. Among the numerous MOFs, Mg-MOF-74 exhibits the best CO2 uptake at low pressures because of its open metal sites. A strategy to incorporate Zn in Mg-based MOF as a co-metal node is required to enhance the CO2 adsorption performance of solid adsorbent. Selecting Zn as a metal node in MOF synthesis allows for the creation of stable, versatile, and functional materials for CO2 adsorption. Therefore, combining several metals in a structure to develop a new MOF with an improved gas uptake is quite a useful approach to further harness the immense potential of MOFs. This study aims to compare the performance of mono-and bimetallic-MOFs and select the most suitable adsorbent for CO2 capture. The performance of CO2 adsorption was conducted using three parameters: the effect of metal loading on MOFs, pressure (1–5 bar) and adsorbent dosage (0.2–0.5g). Based on the characterisation findings, the studies confirm the formation of Mg-MOF-74, ZnMOF and 50wt.%Zn/50wt.%Mg-MOF. Overall, it was found that the bimetal adsorbent with 50 wt.%Zn/50wt.%Mg-MOF displayed the highest CO2 adsorption capacity (323 mgCO2/gadsorbent) when compared to the monometallic MOFs (Zn-MOF (134mgCO2/gadsorbent) and Mg-MOF-74) (122 mgCO2/gadsorbent) indicating a 50% increase in adsorption capacity over monometallic MOFs

    Development of lightweight engineered wood produced from derived sugarcane bagasse and coir fiber: Evaluation of the bending and thermal properties

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    This study aimed to investigate the bending and thermal properties of lightweight engineered wood produced from sugarcane bagasse and coir fiber as reinforcement, with a mixture of tapioca starch (TPS) and polyvinyl acetate (PVAc) as the matrix. Sugarcane bagasse and coir fibers were prepared with varying weight ratios (30:70, 70:30, and 50:50) and subsequently incorporated into the TPS/PVAc matrix via a molding technique, thus forming the lightweight engineered wood. The bending and thermal properties of the lightweight engineered wood were evaluated. The results demonstrate that increasing the proportion of coir fiber and the percentage of the matrix improves density, bending strength, thermal stability, and resistance. The lowest thermal conductivity, 0.062 W/mK, was observed in sample EW8, which also exhibited a density of 0.26 g/cm3. The engineered wood comprising a 30 wt% sugarcane bagasse and 70 wt% coir fiber mixture, with a TPS/PVAc matrix blend of 70 wt%, exhibited the highest bending modulus of rupture of 2.47 MPa. The study proposes the use of sugarcane bagasse and coir fibers as a potential alternative for building insulation materials in the form of engineered wood

    Mohammed Shawal Ian Fitri earns two degrees in Railway Engineering

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    BEIJING, 8 January 2024 – Mohammed Shawal Ian Fitri, 25, gained a unique and valuable learning experience as he graduated from two universities, completing a Dual Degree Programme in Railway Engineering at Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) during his first and second years before continuing his studies at Beijing Jiaotong University (BJTU), China, sponsored by the Public Service Department (JPA) for his third and fourth years

    UMPSA Young Scientists achieve International Recognition at Microbiome Summit 2025

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    HONG KONG, 11 January 2025 – Research conducted by postgraduate students from Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) won the Best Research Abstract Award and Best Poster Presentation Award at the Microbiome Summit 2025

    The implementation of long-short term memory for tourism industry in Malaysia

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    Across the world, tourism is known as the largest contributor towards economy and the fastest developing industry. It has the capability of generating income, creating job opportunities and help people to understand the culture diversity of other countries. Therefore, tourism demand forecasting is really needed to help the practitioners involved as well as government in pricing setting, in assessing future requirements of capacity to fulfil the customers’ demand or in making wise decisions on whether to explore new market or not. This study focuses on tourism demand forecasting based on the number of tourist arrival using recurrent neural network (RNN), which is long-short term memory (LSTM) model. The data used in this study is historical data of number of tourist arrivals in Malaysia before the onset of Movement Control Order (MCO) starting from January 2000 to February 2020 due to the COVID-19 outbreak. The data set was divided into two subsets, training and testing data sets based on ratio 80:20. The objective of this study is to determine an accurate forecasting model especially in tourism industry in Malaysia. The forecast evaluation implemented to predict the error of each model are Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) and the analyses for this model was performed by using Python software. Based on the results obtained, the LSTM model was considered as one of the accurate prediction methods for tourism demand in Malaysia due to the least error produced. It is hoped that these results can help the government as well as practitioners in tourism industry to make a right judgement and formulate better tourism plans in order to minimize any consequences in the future

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