International Journal of Integrated Engineering
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Catchment Delineation and LULC Classification of the Upper Catchment of the Timah-Tasoh Reservoir Using DEM and GIS
Full text linkThe catchment plays a crucial role in delineating basin boundaries and creating sub-basins within it. By using Geographic Information System (GIS), it becomes capable of identifying the sub-catchments within the Timah-Tasoh reservoir. GIS has evolved into an indispensable tool for mapping and evaluating ecosystems in given area. By employing various parameters, significant hydrological processes can be identified and quantified in both small and large catchment areas. This study aims to determine the hydrological characteristics of the reservoir’s sub-catchments. The catchment is delineated using the Digital Elevation Model (DEM), and this analysis is performed through ArcGIS. The result indicates that ArcGIS 10.7.1 can determine the catchment delineation and land use classification for the Timah-Tasoh reservoir. Following the delineation procedure, 19 sub-catchments covering a total area of 183.34 km2 were identified, and the land cover was reclassified into five categories; agriculture, built-up areas, forest, vacant land and water bodies. Therefore, considering the possibility of utilizing ArcGIS for future expansion of this study can enhance the understanding
Spatial Rainfall Interpolation and Evaluation for Seasonal Precipitation in Peninsular Malaysia
Full text linkRainfall, a major driving force in hydrology and water resources planning, poses challenges due to potential malfunctions in conventional rain gauges, necessitating effective methods for filling the data gap. This study focuses on assessing the efficacy of two spatial rainfall interpolation techniques, i.e., Local Polynomial Interpolation (LPI) and Inverse Distance Weighting (IDW) for seasonal rainfall estimation in Peninsular Malaysia. Interpolated values from both methods are compared to ground observations, and their performance is evaluated through cross-validation using statistical measures such as RMSE, MAE, and R2. Additionally, Geographically Weighted Regression (GWR) is employed to analyze the relationship between interpolated rainfall and ground elevation. The findings reveal that LPI outperforms IDW, demonstrating higher R2 values and lower MAE and RMSE, highlighting its superior accuracy in rainfall estimation and underscoring the importance of method selection in handling missing rainfall data
Effect of Fibre Orientations and Nanosilica on Mechanical Properties and Ultimate Tensile Strength of Polymer Composite Materials
Full text linkPolymer composite materials have extensively been utilised due to their superior mechanical properties. Incorporating nanosilica into the resin matrix has been demonstrated to further enhance these properties. This study investigates the ultimate tensile strength of composites made with both pure (PW) and nanosilica-enhanced Willkat resin (5NSW), examining different fibre configurations oriented at 0° and 90°. Results show that the combination of 5 wt.% nanosilica (5NSW) provides the best tensile strength properties. Increasing the nanosilica content beyond this level results in higher viscosity and agglomeration, which adversely affect the properties. Basalt (B/B) comingle fibre exhibits the highest ultimate tensile strength with 302.46 MPa, followed by glass (G/G) comingle fibre with 137.69 MPa, with the addition of 5 wt.% nanosilica. The lowest strength is obtained with Arenga pinnata (AP/AP) fibres at 25.85 MPa in 0° fibre orientation; meanwhile, it increases in strength when hybridised with basalt and glass fibres. The orientation of the fibre also has an impact on the properties of the composite, where 0° fibre orientation gives a better value than 90° fibre orientation. Additionally, the incorporation of nanosilica into the matrix enhances the overall strength of the composites
Application of Photogrammetric and The Scanline Survey Approaches for Rock Slope Stability Analysis
Full text linkThe stability of rock slopes in quarries is a critical concern, particularly under the constant threat of collapse due to ongoing blasting activities. These slopes have been assessed and analysed using a variety of approaches, including traditional field surveys and modern remote sensing techniques. Despite advancements, doubts persist regarding the accuracy and reliability of photogrammetry compared to conventional methods, despite its capability to gather vast amounts of data efficiently. This study focused on utilizing both scanline surveys and photogrammetry to gather discontinuity information on rock slopes. An Unmanned Aerial Vehicle (UAV) was employed to capture visual images, from which orientation and discontinuity features were extracted. Agisoft Metashape software facilitated the creation of a detailed 3D point cloud model. Subsequently, CloudCompare was used to process the photogrammetric outputs, enabling geological plane extraction crucial for assessing kinematic stability and identifying major discontinuity sets within the slope. The stability analysis of the rock slope was performed using PLAXIS 3D, employing both the Jointed-Rock and Mohr Coulomb models to determine Factors of Safety (FoS). Structural failure scenarios were simulated by reducing ϕ/c parameters and applying uniform vertical loads. Analysis of dip angle and dip direction data acquired from dense point clouds via the CloudCompare compass plugin demonstrated reliability, with differences of under 20 percent. The findings from scanline surveys and photogrammetry methods indicated comparable stability and a low risk of failure, as indicated by FoS values remaining above the permissible minimum threshold for stability assessment
Evaluation of Traffic Noise Exposure in Old Folks\u27 Homes, Batu Pahat, Johor
Full text linkExcessive noise exposure can adversely affect the elderly, causing sleep disorders, depression, and stroke. To analyze the noise levels in old folks’ homes, this study used a data logging sound level meter to evaluate traffic noise levels of three old folks’ homes located along the busy road of Jalan Kluang during peak hours of weekdays and weekend (7.30am to 9.30am and 4.30pm to 6.30pm). Traffic counts according to different classes were carried out during the first hour of the survey. The study showed that traffic volume did not affect noise levels at Rumah Sejahtera Batu Pahat and Sherun Old Folk Home (BP), but a positive correlation was found at Healthlife Old Folks Home. Noise levels (LAeq(2hrs)) recorded for Rumah Sejahtera Batu Pahat, Sherun Old Folks Homes (BP), and Healthlife Old Folks Homes were 75 dBA, 67 dBA and 70 dBA, respectively. They are all above recommended values set by the Department of Environment Malaysia (DOE) which is 60 dBA for daytime. The noise levels at nearby buildings, including old folks\u27 homes, are likely to be around or exceeding the DOE standard. The research is essential as it evaluates the seriousness of traffic noise pollution around the old folks’ homes along Jalan Kluang. This study will be helpful for future research and development of built-environment plans
Characterization of Sustainable Graphitic Biochar from Food Waste via Microwave Irradiation Technique
Full text linkThe significant rise in waste generation caused by global urbanization and industrialization may harm the environment, leading to climate change. According to the Solid garbage and Public Cleansing Management Corporation (SWCorp Malaysia), Malaysia generates an average of 1.17kg of garbage each day, which equates to around 3.5 million tons of food waste (FW) every year. Therefore, by transforming FW into valuable materials like graphite presents an appealing alternative due to high demand for it, particularly in energy-related applications. In this research, we introduce a new method for producing sustainable graphitic carbon from FW using microwave-assisted pyrolysis (MAP). The graphitic carbon obtained via microwave pyrolysis at power supply 1000 W at 5- and 45-minutes radiation time then underwent analysis such as X-ray diffraction (XRD), Thermogravimetric Analysis (TGA) and Fourier-Transform Infrared Spectroscopy (FTIR) to verify its structural characteristics, graphitic properties and chemical composition of graphitic carbon. The findings indicated that the microwave irradiation process successfully pyrolyzed food waste into biochar at 1000 W, 30 minutes, giving 23.9% of biochar yield with lower energy consumption (1800kJ). Whereas, the conversion to graphitic carbon from FW is about 60Gp degree of graphitisation. The new material has an excellent potential for electrical conductivity and mechanical endurance, making it appropriate for a variety of applications such as energy storage devices, catalysts, and composite materials. This investigation underscores the potential of utilizing microwave irradiation as an eco-friendly and effective method for converting food waste into valuable graphitic carbon, contributing to the advancement of a circular economy and diminishing the environmental consequences of waste disposal
Evaluating Thermal Exposure Effects on Dielectric and Structural Properties of Water Treatment Residuals
Full text linkEffective handling of water treatment residuals (WTRs) is essential due to their substantial volume and environmental impact. This study investigates the effects of two thermal treatment methods—microwave and oven heating—on the dielectric properties and morphological changes of WTRs. Utilizing Microwave Non-Destructive Testing (MNDT), dielectric permittivity was measured using a vector network analyzer, while morphological transformations were assessed through scanning electron microscopy (SEM). Microwave heating at power levels of 450W, 600W, and 800W resulted in a consistent increase in dielectric permittivity, ranging from 0.94 to 1.26, indicating improved dipolar alignment and material response. In contrast, oven heating produced less predictable results, with dielectric permittivity decreasing from 1.03 at 100°C to −0.55 at 200°C. SEM analysis further confirmed that microwave-treated samples exhibited more uniform structural modifications, including particle fusion and smoother surface morphology, compared to the more fragmented and heterogeneous changes observed under oven heating. The findings support the potential of microwave heating combined with MNDT as a more effective and non-invasive method for characterizing and transforming WTRs. This approach could contribute to the development of more efficient and sustainable residual management processes in the water treatment industry
Exploratory Anomaly Detection with Blood Glucose Level Time Series Prediction
Full text linkDiabetes patients need effective blood glucose (BG) management to avoid developing serious health complications. Real-time BG prediction and anomaly detection through deep learning techniques improve diabetes care in this project. This study utilized the ShanghaiT1DM dataset to train Long Short-Term Memory networks for blood glucose prediction with a dataset split of 70% training and 30% testing aimed at optimizing a 30-minute prediction horizon. The study imputed missing data before validating stationarity through both the Augmented Dickey-Fuller and the Kwiatkowski-Phillips-Schmidt-Shin tests. The evaluation of anomaly detection methods included the rule-based approach alongside the statistical technique of Z-score and the machine learning algorithm of the isolation forest method. The highest accuracy for the detection of hypoglycemia was attained by the isolation forest (0.948), followed by the rule-based (0.887) and Z-score (0.791) methods. In the detection of hyperglycemia, the most effective method was the rule-based (0.847), followed by lower accuracies from the Z-score (0.715) and isolation forest (0.550) methods. Furthermore, the rule-based method exhibited superior performance in both the detection of hypoglycemia (accuracy = 0.887) and hyperglycemia (accuracy = 0.847), exhibiting high precision, recall, and F1-scores throughout, hence established as the strongest method for the detection of anomalies. The results from this research attest that the combination of LSTM-based prediction of blood glucose and rule-based detection of anomaly yields the most accurate method for the detection of hypoglycemia and hyperglycemia from the dataset analyzed. Though the rule-based method proved superior over statistical and machine learning methods, the Z-score and isolation forest methods retain potential for improvement
Flow Channeling And Restriction Zone Identification in Gas Mask Filter Cartridges using CFD
Full text linkGas mask filters are critical for protecting against hazardous gases and airborne pollutants, yet their performance is strongly influenced by internal airflow behavior. In this study, Computational Fluid Dynamics (CFD) was employed to investigate pressure drop, velocity distribution, and air age (residence time) within a gas mask cartridge. The simulations revealed a maximum pressure drop of 41.94 Pa, well within acceptable breathing resistance limits, but with non-uniform distribution across the absorbent bed. Velocity contours showed flow channeling forming near the inlet and outlet, leaving regions further from the outlet underutilized. Air age analysis confirmed these patterns, with some regions achieving the required 0.67–0.80 s contact time for effective adsorption, while others fell below this threshold. Under humid conditions, resistance increased, leading to longer residence times but reduced overall airflow renewal. These findings highlight that both cartridge can affect airflow uniformity, adsorption efficiency, and sorbent utilization. The findings can guide the optimization of filter design in achieve more balanced flow distribution and improved performance.
 
Aerodynamic Analysis of S809 Airfoil: A Stall Validation with RANS k-ω Turbulence Models
Full text linkThis study examines the aerodynamic efficacy of the S809 airfoil at six angles of attack: −14.23°, −5.15°, 0°, 5.13°, 9.22°, and 10.21°. It uses steady two-dimensional RANS with two closures: k–ω SST (Menter) and k–ω Standard. It also checks the results against wind-tunnel data from NREL. We digitized experimental pressure distributions with calibrated axes, which meant that there was a vertical error of ±0.03 in Cp was used, and the uncertainty in the integrated lift is about 10⁻³. Without re-processing, the reported experimental uncertainties from NREL were kept. The study links coefficient trends to the measured surface-pressure fields so that you don\u27t have to use integrals to see if they agree. Both models have a pre-stall range of 5.13° to 9.22°, and the curves and wake thickness match the measurements. The slope of the lift curve is also very close to what was found. There are differences between the start of the stall and the end of the load. The k–ω SST model gets the order of the stalls right, but it makes them less intense. This means that the lift is a little too high and the pressure drag is a little too low at 9.22° and 10.21°. The k–ω Standard model keeps separation from happening longer and gives the biggest lift overprediction and the lowest drag in the same range. When the incidence is negative, both models predict fewer losses than the tunnel data. The solutions show a small positive lift and drag matches well at about 0°. This means that the problem is with the residual circulation offset and not the friction model. The results show that design and control can work well between 5.13° and 9.22°. They also show where you need to calibrate or control the transition as the separation gets closer. A subsequent study will employ URANS to broaden the scope into the post-stall regime to rectify unsteady phenomena