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The effect of fibre loadings on the mechanical and thermal properties of sugar palm/waste tyre rubber reinforced polylactic acid hybrid composites via fused deposition modelling
Get PDFSugar palm fiber (SPF) is a renewable, biodegradable, and eco-friendly resource, while waste tire rubber (WTR) enhances the properties of these composites. Poly(lactic acid) (PLA) serves as a promising biobased and biodegradable matrix material for these green composites. The mechanical and thermal properties of hybrid composite are crucial characteristics in the development of a hybrid composite Fused Deposition Modeling (FDM) filament since the printing mechanism of FDM strongly depends on the heating and extrusion process. To enhance interfacial adhesion, WTR and SPF were treated with 6% NaOH and 3% silane, resulting in a composite formulation of 97.5% PLA and 2.5% SPF/WTR. Three different fiber loadings were assessed: 75% SPF:25% WTR, 50% SPF:50% WTR, and 25% SPF:75% WTR. The filaments produced using a twin-screw extruder were utilized to 3D print tensile specimens according to ASTM D638, impact specimens according to ASTM D256 and the test of Thermogravimetric Analysis (TGA). The results indicated that the 75% SPF:25% WTR fiber loading achieved the highest mechanical properties for tensile strength of 37.89 MPa and appropriate that 25%SPF:75%WTR fiber loading achieved the highest mechanical properties for impact strength of 4.3 KJ/m2. Scanning electron microscopy (SEM) analysis also has been studied. The TGA test displayed similar thermal degradation patterns, suggesting that the ratio of components does not significantly alter the overall thermal stability of the composites. This enhanced performance is attributed to improved interfacial adhesion between the treated fibers and the PLA matrix, along with a uniform distribution of fibers throughout the composite. These findings suggest that sugar palm and waste tire rubber hybrid composites are viable, high-performance alternatives for the filament extrusion and printability of hybrid composite filaments
Accurate skin lesion segmentation through feature fusion in dermoscopy images
Get PDFIn the diagnosis of skin cancer, dermoscopy images have to be evaluated for feature extraction. In this paper, the authors design a new method to enhance the skin dermoscopy image segmentation accuracy by eliminating artifacts and hair using photometric quasi-invariants, followed by a unique approach for skin lesion segmentation using histogram-based feature fusion. Histogram features are used to extract data range and mean images from the histogram, and these are fused with the free artifacts and hair image to generate the final image. the authors used the PH2 dataset for the proposed segmentation method because it contains the ground truth for each image. In contrast, tray to use the Skin_Hair dataset, which includes artificial hair generated with its corresponding ground truth. On the other hand, some PH2 dataset images have hair artifacts that the proposed pre-processing method can remove. According to the experimental results, our method outperforms existing methods in three aspects: accuracy, efficiency, and robustness, measured by Accuracy (Acc), Precision (Pre), Sensitivity (Sen), Specificity (Spe), Jaccard Index (JI), and Dice (D). Our proposed method achieved an average Acc 96.14, Pre 93.87, Sen 94.49, Spe 95.99, JI 88.19, and D 94.21. Furthermore, the Spe increases to 95.99%, up by about +3.2% over top performing methods. In the meanwhile, JI is brought to 88.19%, which increases by about 1.5%; D takes over and goes up to value of 94.21%. These findings suggest that our methodology can provide a more effective and accurate way of detecting skin cancer
Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm
Get PDFFuel cells (FCs) are increasingly attracting attention for their efficient conversion of chemical energy into electricity without the need for combustion. Their high efficiency and versatility make them a promising technology across various applications. Researchers are actively exploring ways to optimize FC systems to meet specific energy needs. Among the different types of fuel cells, solid oxide fuel cells (SOFCs) stand out as a promising clean energy technology that generates electricity through electrochemical reactions. However, accurately modeling SOFCs, which is essential for reducing design costs, presents a challenge due to their complex and nonlinear characteristics. An ideal model should be adaptable to varying operating pressures and temperatures. This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). A real-world case study demonstrates the superior effectiveness of DEMFFA compared to existing methods. Additionally, a sensitivity analysis evaluates the influence of temperature and pressure on the model, with results indicating that the proposed method achieves higher efficiency than other approaches. The sum of the square error of the proposed algorithm is 1.18E-11 followed by the parent algorithm, Fennec fox algorithm (FFA) (1.24E-09), and some of the compared algorithms. The computational time of the proposed algorithm is 1.001 s, followed by the parent algorithm FFA (1.199 s) and some of the compared algorithms. DEMFFA offers significant potential, enhancing renewable energy, minimizing SOFC's environmental impact, and improving real-world applications like distributed power generation and hydrogen integration
A comparative analysis of drilling process parameters for small and large holes in jute reinforced polyester composites using Box-Behnken design
Get PDFThe present work evaluates how selected levels of the drilling parameters contribute to the delamination in drilling natural fibre-reinforced composites, specifically small and large holes. The jute/ unsaturated polyester composites were fabricated through a combination of vacuum bagging and hot compression moulding using 40 vol. % woven jute fabric. The primary effects and interactions on delamination due to feed rate (20 – 100 mm/min), spindle speed (500 – 1500rpm) and drill tool diameter (small bits of 4 – 8 mm and large bits of 20 – 30 mm) were organized using Response Surface Methodology (RSM) and Box Behnken design. The optimal drilling parameters for the smallest delamination factor at feed rate of 60.00 mm/min, spindle speed (1000.00 rpm) and drill diameter (6.00 mm). For the larger hole, the delamination factor is at the lowest when using a feed rate of 30.00 mm/min, spindle speed of 700.00rpm and drill diameter of 20.00 mm. The outcomes revealed that the feed rate and spindle speed are the most critical factors in the delamination of jute/ unsaturated polyester composite during the drilling process
Integrating GIS into traffic incident management: A web-based system
Get PDFThe increasing frequency and severity of road accidents in Malaysia, driven by a significant disparity between vehicle growth and infrastructure capacity, present a pressing need for advanced traffic management solutions. This study details the design, development, and evaluation of a Web-GIS Traffic Incident Management System (WGTIMS), an integrated platform designed to enhance incident reporting, spatial visualization, and multi-stakeholder coordination. The system was constructed using a structured methodology of planning, design, development, and implementation, with deliberate integrations for performance and security. Built on an open-source stack (PHP, MySQL, Leaflet.js), WGTIMS employs a role-based architecture to serve administrators, police officers, and public users. A rigorous evaluation strategy was employed, combining black-box testing with preliminary user feedback. The technical testing demonstrated that the system successfully met all specified functional requirements, with test cases for critical workflows—including user authentication, incident reporting, and spatial data visualization, yielding the expected outcomes and robust error handling. User sessions indicated that the interface was intuitive and the GIS visualization was particularly effective for situational awareness. These findings confirm that WGTIMS is a viable and robust platform for improving response times and analytical decision-making in traffic incident management. Future work will focus on large-scale field deployment, cloud integration, and incorporating AI models for predictive analytics to further elevate its operational impact
Low-cost satellite receiver system using RTL-SDR technology for weather monitoring
Get PDFThis paper presents the development of a low-cost satellite receiver system using RTL-SDR technology for capturing NOAA weather satellite signals. The system integrates a cross-dipole antenna and a Low-Noise Amplifier (LNA) to enhance signal reception in the 137-138 MHz frequency range. Software components include SDR# for signal processing and WXtoImg for image generation from Automatic Picture Transmission (APT) signals. Results demonstrate effective signal reception with high Signal-to-Noise Ratios (SNR) and wide antenna coverage, enabling real-time imaging of weather phenomena. The system demonstrates potential applications in meteorology, disaster management, and climate research, offering accessible tools for real-time weather monitoring and analysis. By addressing the barriers of cost and accessibility, it serves as a model for
expanding weather-monitoring capabilities, particularly in regions with limited infrastructure. Future improvements aim to optimize antenna design and software capabilities for broader deployment in remote and underserved areas
Review on the air temperature and humidity produce by solar dryer and potential to be reused
Get PDFThis article presents a comprehensive review of recent advancements in the reuse of waste heat from solar food dryers, a strategy that holds significant potential to improve system efficiency and sustainability. Solar drying systems typically discharge air at temperatures between 40°C and 70°C, resulting in a substantial loss of free solar thermal energy up to 50% of total energy. This review introduces novel approaches to capturing and reusing this low-quality heat, including the integration of desiccant materials that can boost drying efficiency by up to 64%, and innovative designs like rotating dryer wheels, which increase effective heat gains by an average of 153%. Unlike previous studies, this article not only aggregates and analyzes field test data such as outlet temperatures, humidity levels, and heat recovery efficiencies but also identifies practical and scalable solutions for heat reuse, such as water heating, space heating, and heating nearby cold rooms. By providing quantitative results and exploring the potential for continuous 24-hour operation through advanced heat management techniques, this review offers new insights and practical guidelines for engineers and researchers aiming to make solar drying processes more energy-efficient and commercially viable. This work is particularly relevant for those interested in developing sustainable agricultural practices, as it highlights the most promising methods for reducing energy waste and enhancing the overall performance of solar dryers. The novel synthesis of existing technologies and the identification of key areas for future research make this article a valuable resource for advancing the field of solar drying
Citizen satisfaction of e-policing system in the UAE
Get PDFIntegrating technology has become a key component of evolving global police operations in the quickly evolving field of law enforcement today. In this regard, the United Arab Emirates is distinguished as a leader in innovation, demonstrating a dedication to technical progress by introducing electronic policing, or e-policing. This study looks into how many aspects affect how satisfied citizens are with e-policing systems, a topic that is becoming more and more important in the digital era. E-policing systems, which use technology to improve law enforcement services, are now necessary to guarantee that the public and police can engage and communicate effectively. The purpose of this study is to pinpoint the precise components of e-policing that have a major impact on citizen satisfaction in order to offer a thorough grasp of the factors that contribute to favorable public impression. Through the use of a robust methodology that includes bootstrapping techniques in SmartPLS 4.0 software and Partial Least Squares Structural Equation Modeling (PLS-SEM), the study looks at how citizen satisfaction is influenced by perceived integrity, transparency, responsiveness, interactivity, serviceability, community engagement, and response time. A standardized questionnaire was utilized to gather data from a randomly chosen sample of participants, guaranteeing an impartial and representative sample for the investigation. Perceived responsiveness, integrity, response time do not significantly affect citizen satisfaction, according to the data, but perceived transparency, interactivity, serviceability, and community engagement conduct significantly. In conclusion, three of the seven direct effect hypotheses integrity, responsiveness, and response time were not supported, while four transparency, interactivity, serviceability, and community engagement were supported. There was no substantial mediation role, as evidenced by the fact that none of the seven demographic segmentation-related hypotheses were supported. These findings highlight how crucial it is for e-policing systems to promote transparent communication, interactive platforms, effective service delivery, and quick reaction times in order to increase public satisfaction and trust. The constructs' validity and reliability were ensured by the establishment of convergent validity, whereby all variables satisfied the criteria for Cronbach's Alpha, Composite Reliability, and Average Variance Extracted (AVE). Through the provision of empirical data on the crucial elements impacting citizen satisfaction with e-policing systems, this study adds to the body of knowledge already in existence. In order to cultivate good attitudes among citizens, it emphasizes the significance of transparency, interactivity, serviceability, response times, and community engagement. In order to raise citizen satisfaction and improve e-policing services, the study provides policymakers and law enforcement organizations with useful ideas. Law enforcement organizations can more effectively serve the communities they serve and better satisfy public expectations by concentrating on these important areas
Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization
Get PDFThe reduction of fossil fuels, rising oil prices and environmental awareness have attracted attention to the use of renewable energy (RE)-based distributed generation (DG) systems. Among the various types of renewable energy-based DG, photovoltaic (PV) and fuel cell (FC) technology have shown great potential in electricity generation due to rapid technological development, high efficiency, clean operation and slight influence by weather conditions. To ensure optimal DG output, the RE system must be coordinated using a voltage controller and optimisation techniques to determine the optimal DG output voltage and power value. To improve the AC bus arrangement, battery power is connected to a down/up converter to ensure continuous power flow between the Alternating Current (AC) bus and the battery. In order to control the voltage source inverter (VSI) of the PV/fuel cell/battery cell system, conventional methods of control voltage modes and currents with improved controllers of the artificial intelligence (AI) of both the internal current control loop and the output voltage were built. The proposed tuned Artificial Neural Network (ANN) controller has an advantage over the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller while maintaining the simplicity and robustness of the Proportional Integral (PI) controller. The inverter-based DG model is applied to the microgrid system to review its effectiveness as a complete model as well as to evaluate the performance of its use in large network systems. Since the VSI model is built on a P-Q control scheme that allows separate control of active and reactive power output, DG can operate based on active and reactive power reference on the inverter. A new smart technique has been developed to manage active and reactive power reference for DG by using ANN to ensure that the DG unit operates at optimal power values while reducing the amount of power loss as well as maintaining the voltage profile within acceptable limits. The results showed that the proposed tuned ANN technique could accurately predict the active and reactive power references of DG with minimal error. A comparison was made between the ANN DG controller and the ANFIS DG controller for the power management strategy in terms of the generation by standard forecasting metrics. The comparison between the proposed AI controller and the conventional PI controller has been conducted, and the results showed that the proposed tuned artificial NN technique could accurately predict the active and reactive power references of DG with minimal error. For active power of Battery, is 0.23%, Fuel Cell is 0.23%, reactive power of Battery is 0.0175%, Fuel Cell is 0.097%, Photovoltaic PV1, 0.078% and PV2 is 0.021%. At the end of the research, the AI controller was evaluated/validated for effectiveness by comparative means also conducted to assess the performance and forecast accuracy of the tuned AI that has been chosen by forecasting metrics, which show good estimation performance in only 1.6E-14% for the coefficient of determination (R²), 5.86E-05% for root mean square error (RMSE), 9.1E-06% mean absolute error (MAE) and 0.011% for mean absolute percentage error (MAPE)
Big data technology information extraction and fusion from non-homogenous web data sources
Get PDFBig data has played an ever-increasing role in various sectors of the economy. Despite the availability of big data technologies, many companies and organizations in Malaysia remain reluctant to adopt them. This study was conducted to develop a web extraction framework to extract data from the internet to assist adoption of big data technology. Web scrapping has been a popular method for collecting data from websites. This is because data on the internet is updated frequently thus making it a good source for getting accurate information. Analyzing data requires a large quantity of information to yield a good analysis result. However, the non-homogeneous nature of each website may cause the data from the different internet web sources to have different data making the quality of the data inconsistent. Previous study has propose the use of record linkage method to merge data from multiple website. The record linkage method proposed by previous study used deterministic technique to match data which match the string of matching variable to merge data. However, deterministic technique requires the matching variable to be an exact match to be able to match. Therefore, deterministic matching cannot take into account the dissimilarity such as spacing and different letter cases which can be common in web data due to it non￾homogenous nature. This study will explore the use of fuzzy matching technique in matching web data. Fuzzy matching uses Levenshtein distance to calculate the similarity of string and a threshold will be used to decide how similar to trigger a match. This enables fuzzy matching to match string that are only partially match instead of exact match. This study will begin by conducting a systematic review to determine the challenge of big data adoption and what data to extract. This study will implement the Technology-Organization-Environment (TOE) framework to examine the challenges faced by Malaysian organizations with regards to big data adoption. After the systematic review, a web data extraction framework will be developed to extract data that can assist big data adoption. The extracted data will then be merged to enhance the quality of the data. A comparison is made between deterministic matching and fuzzy matching on the performance of merging web data. The finding from this comparison shows that fuzzy matching has a slightly better performance in merging web data. This is due to fuzzy matching can match the string of matching variable that has different spacing and letter cases. A survey case study carried out in this study also shows that the extracted data is very helpful in helping user while purchasing the required big data software on the software market