Journal of Engineering Research最新文献

Ensuring the availability of a cost-effective method to predict soil behavior is imperative for newly developed construction sites. This research aims to create a model that can estimate the spatial distribution of soil properties and compaction characteristics using the Inverse Distance Weighting (IDW) and Geographic Weighted Regression (GWR) methods within the study area, specifically in Koya city, situated in Erbil, Iraq. To determine these soil parameters, 27 soil samples were collected from the fields based on stratified random sampling, and then tested and analyzed in the laboratory. The IDW spatial interpolation technique and GWR method were then used to create a spatial distribution map of soil properties and compaction characteristics. In the GWR model, the calculated soil properties and compaction characteristics served as the dependent variable, while the Modified Normalized Difference Water Index (MNDWI) derived from the Landsat8 satellite image was the independent variable. This process resulted in a spatial distribution map showing the soil properties and compaction characteristics. The results indicated a strong correlation between the MNDWI water indexes and various soil parameters, including water content, liquid limit, plastic limit, optimum moisture content, and maximum dry density, with respective coefficient of determination (R²) values of 0.91, 0.97, 0.98, 0.95, and 0.96. Additionally, the assessment of the precision in this correlation indicates that the results maintain a satisfactory level of accuracy, as demonstrated by the Root Mean Square Error (RMSE) values, which are 2.86 for water content, 5.4 for liquid limit, and 3.85 for plastic limit, 2.9 for optimum moisture, and 13.86 for maximum dry density. By integrating satellite-derived MNDWI water indexes with soil parameters, a fast, accurate, and cost-effective method for estimating soil parameters and modeling their spatial distribution in the study area can be developed. Additionally, the findings suggest that the IDW method, implemented using spatial analyst tools, performed exceptionally well for mapping the study area. In conclusion, the results of this research can be utilized by land use planners, municipalities, policymakers, and engineers to develop practical and effective plans.

Traffic light detection in real-world conditions is challenging because of the positioning of lights, variety in shapes and scales, and similarity with other objects. The paper presents a deep learning-based traffic light detection system by learning the fusion of handcrafted features. The handcrafted features for object detection focus on specific attributes such as shape, color, or texture. The objective of this work is to incorporate handcrafted features into the network learning process such that the resulting detector parameters are robust to input variations, sensor noise, and atmospheric noise. The proposed detection framework is based on the latest You only look once (YOLO) architecture, trained with the fusion of different information channels in the Integral Channel Features (ICF). The approach demonstrates a qualitative approach for identifying the optimal layer for additional feature injection in the network, and the selection of ICF channels to be applied for fusion. The validation of the proposed detector on the Bosch small traffic light dataset achieved the best mAP score of 55.70 % on the testing set. Further, a qualitative comparison of the proposed detector’s performance with that of other recent methods is presented, along with an analysis using auxiliary experiments.

The use of electric motors instead of internal combustion engines has been increasing in the automotive industry, particularly over the past decade. Studies attempting to use electrical energy as the only source to obtain the required movement from the wheels have run into difficulties due to the limitations of electricity storage units. Li-ion batteries as a power source have shown some interesting characteristics, especially in electric vehicles, but there is still research for development in the storage device. Findings from this research recommend combining battery and supercapacitor technology to power an electric scooter. Both of these power sources are modulated for maximum efficiency in transferring energy to the motors. For this reason, a fuzzy logic-based control algorithm for energy management is developed to keep the battery and supercapacitor at their optimal states of charge (SOC), meet load demands during braking and counter-loading, and boost the energy system's independence. An electric scooter's performance under varying loads is simulated in MATLAB and Simulink to verify the effectiveness of the EMS. The simulation results findings validate the usefulness of the proposed approach and present the novel EMS as very good solution for energy management problem using the fuzzy logic expert system to take decision.

Allergic conjunctivitis is the main usual red eye cause influencing many people. Allergic conjunctivitis is like an umbrella that includes different types of clinical manifestations, from a mild but annoying form of IgE-dependent allergy to inhaled allergens to very severe forms such as keratoconjunctivitis. Cornea involvement in allergic conjunctivitis needs the steroids use, which can cause severe eye complications. Research on allergic conjunctivitis should focus more on more severe forms of eye allergies to gain a better the pathophysiology understanding of the disease, diagnosis methods should be standardized and new treatment methods should be suggested. In the recent study, due to high therapeutic effects of Camellia sinensis, we used its aqueous extract for green-synthesizing of the silver nanoparticles and allergic conjunctivitis treatment in the in vivo condition. UV–Vis spectroscopy, FE-SEM and TEM were used for characterization of nanoparticles. This research therefore evaluated the AgNPs@Camellia sinensis antiallergic potential in ovalbumin-induced allergic conjunctivitis and attempted to predict its mode of action. ELISA determined serum ovalbumin-specific total IgE, IgE and IgG. Clinical scores for allergic conjunctivitis induced by intraperitoneal ovalbumin sensitization and topical conjunctival challenge in Dunkin-Hartley guinea pigs were estimated after treatment with 10, 20, 40 and 80 µg kg⁻¹ AgNPs@Camellia sinensis, 10 mg kg⁻¹ chlorpheniramine, 30 mg kg⁻¹ prednisolone, or 10 mL kg⁻¹ PBS. Serum ovalbumin-specific total IgE, IgE and IgG decreased significantly (p < 0.01). The conjunctival tissue in AgNPs@Camellia sinensis treated guinea pigs had mild mononuclear infiltration compared to the PBS-treated ones, which had intense conjunctival tissue inflammatory infiltration. The 40 and 80 mg kg⁻¹ AgNPs@Camellia sinensis treatment resulted in allergic conjunctivitis low clinical score.

Occurrence of tracking and erosion on surface of polymer insulator leads to breakdown of these materials and has negative impact on their quality. Contaminants forms surface layer on insulators and chemically interact with it. This effect reduces smoothness of surface insulator and forms conducting paths. It allow passage of higher values of leakage current and cause ionization of field around insulator and rise temperature of surfaces, this leads to formation phenomenon of tracking and erosion.it cause deterioration, ageing and collapse of insulator, which affect safety of electric system. How to significantly enhance the tracking and erosion properties of nitrile butadiene rubber (NBR) are a major topic in electric insulators. With a view to enhancing the tracking and erosion properties of NBR used in power systems, nanoparticles are usually added to pure materials to enhance their electrical and physical properties. This work deals with experimental studies on tracking and erosion properties on NBR loaded with [0, 0.5, 1, 1.5, and 3 part per hundred part of rubber (Phr.)] titanium dioxide (TiO₂) nanoparticles. Composite materials have been experimentally tested by inclined plane test (IPT) according to the ASTM D2303 standard. When it is necessary to explore a new insulating material, the inclined plane test is used. This is because IPT is used to evaluate the properties of laboratory modified polymers under different voltages. The times to track during the test were recorded. Data processing, analog to digital systems, and data acquisition have been used to measure leakage current passing through samples. When comparing result of leakage current measurements, it was noted that its value was lower for modified samples compared to virgin samples. This positive effect indicates to enhancement of NBR as a result of formation of stable chemical bonds.

This study seeks to investigate the heat transfer analysis of hybrid nanofluids containing fractionalized water and kerosene oil, which flow through a vertical channel via convection. To represent the problem in terms of fractional partial differential equations, we utilized the Prabhakar time-fractional derivative, a recent advancement in the concept of fractional derivatives. The governing equations were then solved using physical initial and boundary conditions that include momentum, concentration, and energy equations. Stehfest and Tzou's Laplace inversion techniques are used to provide semi-analytical solutions for governed equations, such as temperature, concentration, and momentum profiles, and we applied the fractional Laplace transformation to find solutions in the transform domain. Furthermore, the resultant solutions in tabular form are also derived using Tzou and Stehfest's numerical methods for Laplace inversion to ensure the accuracy of our findings. According to our research, an increase in volumetric fraction causes a reduction in fluid velocity. Due to the physical properties of the investigated nanoparticles, the water-based hybrid nanofluid has a bigger effect on the temperature and momentum profile than the kerosene oil-based hybrid nanofluid.

The Architecture, Engineering, and Construction (AEC) industry in the State of Kuwait has witnessed a decline in efficiency with most projects going above budget and past project deadlines. Building Information Modeling (BIM) creates a collaborative common-data working environment between various stakeholders leading to improved productivity and efficiency while also minimizing technical challenges, and reducing design errors. Moreover, adding the concept of time to the model (4D BIM) for the purposes of planning and scheduling further optimizes inter-disciplinary collaboration. The first phase of this research aims to evaluate current BIM adoption rates and implementation depth in Kuwait through a survey distributed to organizations in the Union of Kuwait Engineering Offices and Consultant Houses. The results indicated that the rate of BIM adoption, represented by whether or not organizations have used BIM in previous/current projects is relatively high. Implementation depth, represented by the percentage of projects for which BIM is being used, is concluded to be low. In terms of willingness to adopt BIM, most organizations use and are considering using BIM as a visualization tool. The second phase aims to examine the applicability of generating predefined process templates for Tract Houses in the northwest Sulibikhat area constructed by the Public Authority of Housing Welfare (PAHW) used for 4D BIM. The Process Pattern Recognition approach is applied to a BIM-based construction schedule where the schedule is extracted, decomposed, processed, and filtered. Relevant and potentially relevant processes are identified and verified leading to defined process templates. This research contributes to the AEC industry by aiding in transitioning from current Computer-Aided-Design (CAD) practices to BIM technology.

Achieving financial sustainability is a critical challenge for Public higher education institutions ‎worldwide. This study aims to provide modified strategic planning tools for planning financial ‎sustainability in higher education institutions. The paper employs modified forms of three ‎strategic planning tools: a strategy map (SM), the balanced scorecard (BSC), and business-‎model-canvas (BMC), which were applied to support the analysis of planning financial ‎sustainability at King Abdulaziz University (KAU). These tools enhance the planning process ‎and contribute to the outcomes. The paper also draws a roadmap of key milestones for ‎financial sustainability at the university by identifying sources and indicators of the university's ‎financial capacity. This paper contributes to the literature on financial sustainability in higher ‎education institutions and offers novel insights for other universities that seek to adopt similar ‎plans. Furthermore, four recommendations are suggested to boost business development and ‎connect with the university investment network. These recommendations involve investing in ‎competent human resources, increasing financial assets, and utilizing technical capabilities. ‎Further research includes examining the applicability of this novel approach in other contexts ‎and identifying potential challenges and limitations of implementing and achieving financial ‎sustainability.

Assembly line balancing is a compulsory approach which enables mass production of similar parts with proper efficacy. Multiple heuristics are proposed in literature to solve single model assembly line balancing problems (SALBP-1). Previous work has focused on developing and evaluating assembly line balancing heuristics and apply them to different fields. Other work investigates the factors affecting the performance of particular assembly line balancing heuristic. However, there is still a need for a guideline for selecting the most suitable heuristic for a particular application with insights into multiple performance measures. This research presents a grey relational analysis (GRA)-based approach to aid process designers in selecting the heuristic generating that yields the best line balancing. Specifically, combinations of factors of cycle time, order strength, number of tasks, and time variability are considered as operational setups of the line balancing process. The solution of each setup is solved by each heuristic, and the performance of the solution is evaluated. Then, GRA is applied to rank the heuristics on basis of the resulting grey rational grades. The proposed approach provides useful insights into the combinations suitable for a particular heuristic. In this study, time variability and cycle time are shown to have the greatest impact on the overall performance of the considered heuristics.

This research presents a review of computer-based production planning, scheduling, and control (CPPSC). The purpose of this study is to illustrate the progress made in the current research on the planning and control of production and scheduling. Twenty-two papers selected for this study focused on the recent trends, approaches, and problems associated with CPPSC. Progress in the manufacturing paradigm in engineering justified why CPPSC could be applied to a set of systems to increase the production of goods and services and to further highlight the relevance of the decisions made and why substantial progress was made in the development of the theory regarding decision making in each of those areas in the past. The integration of line balancing and process plan selection in the Smart Manufacturing System would lead to more efficient production processes, reduced downtime, and improved resource utilization. Additionally, it would provide a comprehensive view of the production environment, allowing for data-driven decision-making and optimization strategies. To demonstrate the effectiveness of this novelty approach, researchers could set up a real-world pilot in a manufacturing facility. They can compare production performance before and after implementing the AI-driven Smart Manufacturing System. Key performance indicators (KPIs) such as production throughput, machine utilization, cycle time, and lead time can be used to quantify the improvements. Furthermore, case studies and simulation scenarios can be used to validate the system's potential benefits in various manufacturing settings.