LAUTECH Journal of Engineering and Technology (LAUJET)
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Influence of Fractionation on the Oxidative Stability, Thermal Stability, and Fatty Acid Profile of Shea Olein Fractions
Get PDFOxidative stability can directly affect oil quality and shelf life, especially in fat and oil-containing products such as shea olein. Shea butter is becoming increasingly popular in foods, cosmetics and pharmaceutical products, but is generally unstable. The fractionation of shea butter affects the stability of shea olein. Therefore, this study investigated the effect of fractionalization on oxidative and thermal stability with fatty acid composition of shea olein. Shea butter was fractionalized using a cold centrifuge at 5 ? and -5 ? to obtain two fractions of shea olein. The stability of the shea olein fractions was evaluated with peroxide values (PV), p-anisidine value (p-AV), conjugated dienes (CD), and Thiobarbituric Acid Reactive Substances (TBARS). The thermal stability and fatty acid composition were determined using the differential scanning calorimetry method and the Gas Chromatographic method. The percentage yield for crude shea butter, shea olein (DSOA), and super shea olein (DSOB) were 37.5%, 75.59% and 50.94%, respectively. The PV, p-AV, CD and TBARS were in the ranges 0.32-1.59 meq O/kg, 7.28 - 11.51, 0.59 - 5.00 mmol/g and 0.10 to 0.14 mmol/g. The thermal stability reflects an endothermic transition of CSB, DSOA, and DSOB as -17.35 mW, -12.93 mW, and -3.85 mW, while their fatty acid profile revealed two prominent acids, arachidic acid (39.87, 40.04, and 29.26%), oleic acid (47.83%, 48.30%, and 56.23%), respectively. The study demonstrated that the oxidative and thermal stability of shea olein is achievable during fractionation, leading to a more stable oil for food formulations
Development of a bimodal biometric authentication system for automated teller machine using gray level co-occurrence matrix
Get PDFThe increasing reliance on Automated Teller Machines (ATMs) has highlighted the urgent need for advanced authentication mechanisms to safeguard user transactions against fraud and unauthorized access. However, traditional methods such as Personal Identification Numbers (PINs) and passwords remain vulnerable to attacks, while unimodal biometric systems face challenges of inter-class variance, environmental interference, and non-universality. Specifically, single-modality approaches and conventional ATM cameras fall short in capturing reliable biometric features under varying conditions, while the effectiveness of bimodal approaches in such environments has not been adequately investigated. Therefore, this study developed a bimodal biometric authentication system integrating face and iris recognition with Gray Level Co-Occurrence Matrix (GLCM) for enhanced ATM security. The system leverages GLCM for powerful texture feature extraction from both modalities, capturing intricate spatial relationships that are difficult to spoof. The extracted feature vectors were used to train Support Vector Machines (SVM) with a Radial Basis Function (RBF) kernel as classifiers for both face and iris recognition. The final authentication decision was made using Boolean OR rule fusion. The system achieved a remarkable accuracy of 98.2%, with a False Acceptance Rate (FAR) of 1.8% and a False Rejection Rate (FRR) of 1.2%. These results demonstrably outperformed comparable unimodal systems and existing biometric ATMs, validating the proposed framework as a highly secure and efficient solution for financial authentication systems
Effect of initial quenching temperature on the hardness of AA6061 aluminium alloy and C18200 copper alloy
Get PDFThis study presents a quantitative investigation of the quench sensitivity of AA6061 aluminium and C18200 copper alloys under controlled water and oil quenching across an initial temperature range of 20–80?°C. Specimens were solution-treated according to ASM-recommended procedures, followed by rapid transfer to agitated quench baths to ensure turbulent cooling. Brinell hardness measurements revealed that aluminium exhibited a pronounced decrease in hardness with increasing quench temperature, while copper showed comparatively minor changes. The Quench Sensitivity Index (QSI), calculated as the hardness loss per degree Celsius, confirmed aluminium’s higher practical sensitivity (0.283–0.405?HB/°C) relative to copper (0.152–0.183?HB/°C). Statistical analysis using ANOVA indicated that temperature effects were highly significant (p?<?0.001) for all alloy–medium combinations. Ordinary least squares regression models demonstrated strong linear relationships between hardness and quench temperature (R²?>?0.90), enabling predictive capability. Metallurgical interpretations attribute aluminium’s sensitivity to precipitation kinetics and solute supersaturation, whereas copper’s low sensitivity reflects its high thermal diffusivity. The findings emphasize the critical importance of precise quench temperature control for aluminium alloys to maximize mechanical performance, while copper alloys allow more flexible processing. Overall, the study provides a robust framework for optimizing industrial quench processes in aluminium and copper components
Waste-to-Energy Valorization: Harnessing cassava peel extract as a sustainable substrate for microalgal fuel cell bioelectricity generation
Get PDFThe escalating global energy demand, coupled with environmental challenges, necessitates the development of sustainable bioenergy technologies. Cassava processing generates substantial agricultural waste, particularly cassava peels, which constitute 10-20% of tuber weight and present significant disposal challenges. Microbial Fuel Cells (MFCs) offer a promising waste-to-energy valorization pathway by converting organic waste into bioelectricity through microbial metabolism. This study investigates the potential of Cassava Peel Extract (CPE) as a low-cost, agro-waste-based substrate for sustainable bioelectricity generation using Parachlorella sp. in a double-chamber MFC system. A double-chamber MFC was constructedwith Parachlorella s . as biocatalyst, CPE supplemented with calcium carbonate as anolyte, while 0.01 M potassium ferricyanide as catholyte. System performance was monitored, and energy harvesting was evaluated by charging 2.7 V 1F supercapacitors. Results identified 5 mL as the optimal feed volume, yielding stable currents of 0.26–0.28 mA (batch) and 0.18–0.24 mA (continuous) over 40 days. Furthermore, a multi-way electrical configuration increased supercapacitor charging efficiency by 73% compared to a one-way setup. These findings establish Parachlorella sp. as an effective agent for cassava waste valorization and contribute to the circular bioeconomy by transforming agricultural waste into renewable energy, offering a sustainable solution for both waste management and clean energy production
Dam break analysis and development of inundation map: a case study of asa dam, ilorin, kwara state, nigeria
Get PDFThis paper presents the dam break analysis and development of inundation map for Asa dam in Ilorin, Kwara State. Empirical equations and hydrodynamic simulations with HEC-RAS software were employed to assess the potential flood impact resulting from a hypothetical dam break. The data collected on the dam’s structural and the hydrological characteristics were used to perform a detailed dam break analysis to evaluate flood risks and identify flood-prone areas downstream. MacDonald and Langridge-Monopolis and Froehlich models were used to estimate breach parameters, while HEC-RAS was applied to simulate the flood wave propagation and inundation extent. The empirical analysis produced a peak discharge of 14,152 m³/s, a breach width of 130.86 m, and a failure time of 1.48 hours. Simulation results revealed that the maximum velocity ranges from 6 - 8 m/s with flood depths exceeding 10 meters in low-lying downstream areas. Flood hazard maps identified critical locations at risk, including Coca-kola Road, Amilegbe, and Isale Koko as critical risk locations, with varying degrees of inundation severity. These maps, along with the hydrographs generated, provide valuable information for flood emergency preparedness and early warning systems. A break at Asa Dam could lead to devastating consequences for downstream communities. To prevent the ugly incidence, immediate structural reinforcement, routine maintenance, sedimentation control, and the implementation of community-based flood awareness programs are recommended as decision-making tool for engineers, policymakers, and disaster risk managers
Development of composite from bamboo shoots and elephant grass
Get PDFIn this work experimental investigation was carried out to study the effect of bamboo shoot and elephant grass at varying weight percentages to modify epoxy resin with addition of steel slag. Physical and mechanical tests carried out are density, water absorption, tensile, hardness and flexural. Tests are conducted on 100 kN servohydraulic universal testing machine under displacement mode of control, digital Rockwell hardness testing machine and impact testing machine. Bamboo shoot and elephant grass fibres at different wt% (15), steel slag wt% (5) are filled in epoxy resin and hardener wt(80). The effects of mixing bamboo and elephant grass fibres on mechanical and physical properties are studied. On the basis of mechanical testing results it is found that sample D containing elephant grass (7% wt) and bamboo fibre (8% wt) mixed with epoxy is giving optimum mechanical properties. The addition of bamboo shoot fibre has improved tensile, flexural and impact properties of epoxy resin and increased water absorption of the material. On the basis of overall study, the epoxy modified with 15% of bamboo shoot fibre is found to be better than other combinations
Development of a customer feedback-enhanced ATM locator using Dijkstra's algorithm and the Haversine formula
Get PDFAutomated teller machines (ATMs) allow customers to perform financial transactions without visiting a bank branch. ATM locators help users find the nearest ATMs based on their location. Customer satisfaction, heavily influenced by service quality, is crucial for banks. Hence, banks should actively seek customer feedback to improve services. Existing ATM locators lack features for communicating customer feedback to banks. This study aimed to enhance the ATM location experience with an Android-based ATM Locator application. The application was developed using C# for the server backend and Java for the mobile app. It allows users to find ATMs, get detailed information, and provide feedback sent via email to participating banks. The app's effectiveness was measured using accuracy (precision & recall), user satisfaction, and response time. User feedback improved the system's strength. The application was tested by 200 students from Ogun State Polytechnic of Health and Allied Sciences. Analysis of the results showed that 81% of recommended ATM locations were relevant, and 84% of these were recognized by users. The average service rating was 4 out of 5, indicating positive feedback. However, some reviews pointed out issues with cash replenishment processes, highlighting areas for further improvement
Development Of Convolutional Neural Network-Based Pelican Optimization Algorithm for Handwriting Identification System
Get PDFHandwriting identification remains a significant challenge in the field of information processing and Optical Character Recognition (OCR) due to the diverse nature of human writing styles. Traditional Convolutional Neural Network (CNN) models, although widely used, often suffer from overfitting, hyperparameter sensitivity, and limited adaptability to different handwriting patterns. This research addressed these challenges by optimizing Convolutional Neural Network (CNN) with Pelican Optimization Algorithm (POA) for Handwriting identification System (HRS). A handwriting dataset comprising 3000 forged handwriting samples and 3000 original handwriting samples was obtained from Kaggle,com. The images were resized, normalized, and augmented to enhance model generalization. POA-CNN was developed by using Pelican Optimization Algorithm to fine-tune CNN hyperparameters of learning rate, layer size, activation functions, and batch sizes with Keras support packages. The POA-CNN model was implemented in MATLAB R(2023a).The system’s performance was evaluated across varying decision thresholds with six key metrics employed: False Positive Rate (FPR), Specificity (SPEC), Sensitivity (SEN), Precision (PREC), Accuracy (ACC), and Computational Time (CT). The model was compared with traditional CNN. The optimum threshold was 0.51. The FPR, SPEC, SEN, PREC, ACC and CT for POA-CNN were 3.20%, 96.80%, 96.70%, 96.80%, 96.75%, and 81.95 s, respectively. The corresponding values for CNN were 4.77%, 95.23%, 95.13%, 95.23%, 95.18%, and 91.20 s, respectively. The developed POA-CNN for handwriting identification system demonstrated better performance than the traditional CNN, across all metrics. Overall, the results demonstrate that POA-based hyperparameter optimization significantly improves the accuracy and reliability of CNN-based handwriting identification for effective forgery detection
Determination of optimal sampling strategy and water quality characterization of Ikere reservoir, Iseyin, south-west Nigeria
Get PDFWater resources are essential for sustaining human life and socioeconomic activities, with reservoirs serving as critical water bodies. However, limited data on the Ikere reservoir’s current water quality hinders effective management. This research aims to assess the quality of water variation to develop an optimal sampling strategy for the Ikere Gorge Dam, Iseyin, Oyo State. Nigeria. Laboratory analysis was conducted on six (6) water samples from both the rainy and dry seasons at the study area, adhering to APHA (2017) Standard Methods for the Examination of Water and Wastewater, and encompassing physicochemical and biological parameters as well as heavy metals. The results were compared to Nigeria's Food and Drug Administrative Control (NAFDAC, 2020) and World Health Organization (WHO, 2017) standards. Principal Component Analysis (PCA) and Cluster Analysis (CA) were employed for the statistical analysis of the water quality parameter data to determine the optimal sampling strategy within the study area. The physicochemical, heavy metals, and biological parameters for the rainy and dry seasons, including pH, electrical conductivity, temperature, turbidity, total dissolved solids, E. coli e.t.c showed values ranging from 6.41 to 6.77, 72.23 to 91.37 µS, 24.10 to 29.23°C, 1.30 to 10.23 NTU, 0.01 to 0.10 mg/L, and 12.33 to 47.67 MPN/100mL. Parameters such as turbidity, phosphates, DO, and E. coli exceeded WHO and NAFDAC standards. This indicates potential health risks and environmental pollution. PCA results indicate the variance distribution across five principal components, with significant clustering patterns. In conclusion, integrating CA and PCA is essential for effective water quality assessment at Ikere Gorge Dam. CA identified distinct clusters, while PCA revealed key factors like COD and hardness reflecting natural influences and turbidity and copper indicating pollution
Mechanical and structural impacts of fly-ash reinforcement on graphite-aluminum composites
Get PDFMaterials with light-weight, optimum thermo-mechanical properties are in great demand for thermal management systems. Graphite-Aluminum (Gr-Al) composites are being reinforced to achieve the above objectives. This paper reports the effects of fly-ash powder on the mechanical and structural characteristics of spark plasma-sintered Gr-Al composites. Graphite powder (53 ?m) and 20%wt aluminum powder (1-2 ?m), were reinforced with 0, 10, 20, and 30 %wt fly-ash powder (53 ?m), designated as GA, GAF-1, GAF-2, and GAF-3, respectively. Sintering was conducted at a heating rate of 50 oC/min, temperature of 550 oC, pressure of 5x10-2 mbar, and 10-minute holding time. Characterization was based on morphology, microhardness, displacement, relative density, peak intensity ratios, and tensile strength. The fly-ash particles had a cup-like shape, with dominance clearly noticeable in GAF-3. GAF-1 had the highest increase in peak intensity of 12.67%. GA showed the highest displacement rate (0.983 mm/min within the first 4 minutes of heating) and instantaneous relative density (0.97). However, an increase in fly-ash led to a 11.22% increase in porosity and a 35.85% increase in the micro-hardness while GAF-3 gave the highest ultimate tensile strength of 388.92 MPa. Reinforcing the Gr-Al matrix with Fly-ash makes it suitable for industrial applications