International Journal of Integrated Engineering
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Design of Miniaturized On-chip Monopole Planar Antenna with loaded Interdigital Capacitor for 5.8 GHz Devices
Get PDFMiniaturization of the on-chip antenna (OCA) in the lower frequency band is limited by the requirement for a compact chip size imposed by the larger electrical wavelength. At the same time, shrinking the antenna size reduces radiation characteristics and incurs significant losses due to lossy silicon substrate. This paper introduces a design for a miniaturized monopole planar on-chip antenna utilizing an interdigital capacitor (IDC) as an approach. The design incorporates a partially reflective surface (PRS), characterized by a high impedance surface, into the stacked structure to enhance antenna performance at a resonant frequency of 5.8 GHz. The stacked-up structure comprises a six-layer metal-insulator-semiconductor (MIS) integrated onto a monolithic silicon substrate as the host material. A model prototype was fabricated using a sputtering process, resulting in a size reduction of 45.62 % compared to conventional designs, well-suitaed for the applications of RFIC, Wi-Fi, WiMAx, RFIC, and wireless transceivers at 802.11a. The fabricated antenna is validated and realizes an improved gain of 28.63 % and a radiation efficiency of 25.26 %, with an impedance bandwidth of 0.73 GHz at a return loss of about 20 dB
The Evaluation of the Cylindrical Accuracy in Bore Honing of EN-GJL-250 Lamellar Cast Iron
Get PDFThe study of the different parameters, which describe the shape accuracy of the machined parts is important on functionally significant surfaces. The cylindrical accuracy is an essential characteristic of the machined bores of internal combustion engine blocks. The aim of the ongoing study is to explore the relationship between the shape error of the produced inner cylindrical surfaces and the setting parameters in honing. The results contribute to a wider understanding of the achievable precision of the examined finishing process by examining the relationships that have not been determined so far. In this paper, four parameters describing the cylindrical error after the honing procedure are analysed on EN-GJL-250 lamellar cast iron workpieces. The 23 factorial design is applied in the planning of experiments. Two levels of grain size, feed rate and pressure between the workpiece and the honing tool were chosen for the comprehensive analysis of the internal cylindrical honing process. The values of cylindricity, the valley maximum departure, the peak maximum departure and the cylinder taper are measured by the application of a Talyrond 365 accuracy measuring equipment. Equations were determined for the calculation of the studied parameters according to the full factorial design method. The results were evaluated in three steps: first the main effect of the process parameters are determined, then the presented equations are validated through control experiments. Finally, the detailed analysis of the results showed the alteration of the cylindrical correctness in function of the different parameters.
Investigation on the Optimum Cement–Slag Artificial Aggregates at Different CO2 Curing Regime
Get PDFCarbon dioxide (CO2) capturing is an attractive approach for producing low carbon construction materials such as artificial aggregates. Therefore, this paper investigates the optimization of cement–slag artificial aggregates under different CO2 curing regimes. The mix proportion used is 50% Ground Granulated Blast Furnace Slag (GGBS) and 50% Ordinary Portland Cement (OPC) with 20% of water under various curing conditions. The curing regimes include CO2 curing followed by water and air curing at different curing ages: 1 day of CO2 curing followed by 27 days of water and air curing, 2 days of CO2 curing followed by 26 days of water and air curing, and 3 days of CO2 curing water 25 days of water and air curing; with 28 days of total curing, respectively. After through curing process, several tests were carried out on cement–slag artificial aggregates including an individual strength test, aggregate crushing value test, visual carbonation by phenolphthalein solution and CO2 uptake by thermogravimetric analysis test. These tests provide a thorough assessment of the artificial aggregates by examining their strength and chemical characteristics under various curing conditions. The results indicated that 3 days of CO2 curing followed by 25 days of air curing is optimal, showing 6.71 MPa of individual crushing strength and 18.56% of aggregate crushing value. Thermogravimetric analysis indicated that calcium hydroxide (Ca(OH)2) played a significant role in synthesizing calcium silicate hydrate (C–S–H) gel, contributing to aggregate strength. The carbonation of Ca(OH)2 to calcium carbonate (CaCO3) enhanced aggregate durability by reducing permeability and increasing material density. The findings show that the optimal curing regime produces the best results in terms of strength and CO2-capturing properties, which was the main goal of this study
Adaptive Production Capacity Planning Under Variable Electricity Cost Using Deep Reinforcement Learning
Get PDFReinforcement learning is gaining traction for its ability to solve complex tasks that are intractable or impossible for other machine learning techniques. This paper proposes a novel approximation technique for production capacity and inventory planning using deep reinforcement learning (DRL). To address practical implementation challenges, we incorporate demand uncertainty and time-of-use electricity price-driven demand response patterns (PDDR) into the model. We compare the performance of two DRL techniques, A3C and PPO, in learning to optimize production planning over time to minimize total cost. The Discrete-Time MILP with new changeover constraint equations was formulated to take the model\u27s optimal solution as an upper benchmark. Our results show that the PPO outperforms the A3C and expert heuristics with an optimality gap of 4.03% compared to MILP, and its simulation time is 2,502 times faster than that of MILP. Furthermore, our findings suggest that PPO is more robust regarding demand fluctuations than A3C due to its objective clipping mechanism stabilizing policy updates. This makes our PPO-based production planning model a promising candidate for real-world applications where demand fluctuations are common
Distance Estimation using Deep Learning Approaches for Rear-end Collision Avoidance Alerts
Get PDFAutonomous Emergency Braking (AEB) and Autonomous Emergency Steering (AES) are part of the advanced driver assistance system (ADAS) equipped in intelligent vehicles. AEB is a system that warns drivers of potential collisions and assists them in utilizing the vehicle\u27s maximum capabilities. AES is an active safety system that aids in evasive steering. If it detects a potential collision, unlike AEB, the AES system will autonomously adjust the steering to prevent it. The challenges for AEB and AES include determining how much space is required to avoid an accident while turning or braking and how much distance is required to avoid an impact when braking and turning simultaneously. Considering such inquiries, it is necessary to devise a system to estimate the distance between the vehicles. Therefore, this study proposes a Monocular Vision Distance Estimation (MVDE) method employing deep learning techniques for accurately calculating the distance between vehicles, particularly for use in AEB and AES systems. The MVDE technique uses monocular vision, emphasizing object detection and distance estimation. In contrast to complex depth estimation techniques, the proposed method employs a Single Shot Detector (SSD) with MobileNet architecture for object recognition and Deep Artificial Neural Networks (Deep ANN) for accurate distance estimation. Using a real-world dataset collected in Cyberjaya, Malaysia, this study rigorously assesses the performance of this method. Results indicate that the MVDE method with four hidden layers in Deep ANN outperforms earlier techniques, with a maximum measured error of 4m to actual distances. In addition, it is competitive with RADAR-based systems and offers a cost-effective alternative for widespread adoption. These findings support the potential of MVDE for augmenting vehicle safety, shaping future automotive standards, and facilitating the widespread implementation of AEB and AES systems
Assessing Solid Waste Management Practices of Shoreline Cottages in First Class Municipality Public Beach Resorts: A Quantitative Analysis in South Cebu, Philippines
Get PDFBeach resorts are vital to the tourism industry, providing relaxation and recreation for both locals and visitors. However, the enjoyment they offer often comes at a cost to the environment, particularly in the form of solid waste. This study takes a closer look at how shoreline cottages in public beach resorts located in South Cebu, Philippines, manage their waste. Guided by the principles of the Ecological Solid Waste Management Act of 2000, the research assessed current waste generation patterns and evaluated management practices in two first-class municipalities: Argao and Dalaguete. Using a quantitative and descriptive approach, data were gathered from 68 participants, comprising business owners, resort staff, and local government officials, through surveys, interviews, and actual waste sampling. The findings reveal a noticeable difference in the amount of waste produced on busy versus unbusy days, with recyclable materials being the most common type of waste generated. While awareness of proper waste disposal is generally high, issues remain in waste segregation and consistent policy enforcement. Importantly, the study found strong correlations between the local government\u27s waste management efforts and those of the resorts, particularly in areas like segregation, disposal, and compliance with penalties. The results highlight the need for a more integrated and collaborative approach to waste management—one that strengthens existing practices, improves compliance, and supports sustainable tourism
Thermophysiological Comfort Assessment of Football Jersey Fabrics used in Hot and Humid Weather
Get PDFOptimizing thermophysiological comfort is crucial for enhancing athletic performances and well-being during intense exercise in hot and humid climates. This study assessed the comfort properties of four commercially available 100% polyester microfibre fabrics used in football jerseys: mini mesh (MM), polar eyelet (PE), eyelet (EY), and interlock (IT). Fabric assessments were conducted to evaluate thermal resistance, water vapour resistance, water vapour permeability, air permeability, and moisture management properties. Among the fabrics, the PE fabric demonstrated to give the most superior thermophysiological properties, with the lowest thermal resistance (0.009 m²K/W), the lowest water vapour resistance (0.44 m²Pa/W), and the highest water vapour permeability (237.7 g/m²/day) and air permeability (2149.2 mm/s). These values are attributed to the fabric’s porous, open-knit structure that enhances heat and moisture dissipation, resulting in improved breathability and wearer comfort. Statistical analysis confirmed significant differences among the fabric structures, reinforcing the influence of fabric design on comfort performance. The findings suggest that, among the fabrics, the PE fabric performs better as sportswear for tropical climates like Malaysia
Human-Centered Design and Development of an Adjustable Crutch: Enhancing Usability and Functionality for Physical Disabilities
Get PDFCrutches are becoming more and more critical as the number of physically disabled individuals in a nation rises. The need for multidimensional and multivariate crutches to assist people with disabilities is more significant today. Before making a variant of the standard crutch, a proper study must be done to construct a stable crutch for high load-carrying capacity. Additionally, various crutch models are also available. A new challenge is the development of an entirely new crutch model. Numerous types of analysis were carried out in this research to create a reliable and effective product, including market analysis, quality function deployment, functional structure development, Kano model development, specification and design analysis, materials and manufacturing processes, and cost analysis. All facets of product development, such as consumer requirements, assembly schematics, and recycling practices, were explored in the study. The most intriguing additions were the product’s capacity to fold and the seating tool facility. A load analysis was conducted to meet this requirement, utilizing data from a survey of disabled persons employed in the business regarding the equipment required for people with physical challenges, especially when selecting materials. Another unique feature of our product is an adjustment system that helps the user to adjust its height. These features are new and thus make our product more memorable compared to existing products on the market. Ultimately, the product was developed and utilized successfully through the research
Experimental Investigation on Combustion, Performance, Emissions, and Vibrations in a Diesel-Hydrogen Dual-Fuel Engine with an On-Demand Hydrogen Generation System
Get PDFThe study addresses the challenge of onboard hydrogen storage in transportation by proposing an innovative solution involving an on-demand hydrogen generation system. This system operates via a chemical reaction between aluminum sulphate (Al₂(SO₄)₃) and sodium borohydride (NaBH₄), producing hydrogen gas in real-time. The research examines the performance of a Variable Compression Ratio (VCR) diesel engine running in a dual-fuel mode, where hydrogen is supplied from the reactor. Engine behaviour was systematically analyzed under varying operating conditions, including compression ratios of 16, 17, and 18, and engine loads ranging from no load up to 12 kg, increasing in 3 kg steps. Additionally, the hydrogen flow rate was adjusted between 0 and 15 liters per minute. The results indicate that the engine achieved its best performance, in terms of efficiency, combustion, emissions, and vibration characteristics, at a compression ratio of 18 and a hydrogen flow rate of 15 liters per minute. These findings offer valuable insights for the advancement of on-demand hydrogen reactors, highlighting their potential for integration with VCR diesel engines to promote cleaner and more sustainable transport solutions
Application of Support Vector Machine and Gaussian Process Regression for Carbon Emission Prediction in Building Construction
Get PDFIn light of the heightened awareness of climate change, the construction industry is under significant pressure to reduce its carbon footprint. This study aims to apply two advanced intelligent methods, Support Vector Machine (SVM) and Gaussian Process Regression (GPR), to predict carbon emissions during the building construction stage. The models are trained and tested using four input parameters: quantity of construction machinery, fuel consumption rate, carbon emission factor per unit of fuel or electricity consumed, and operating hours of the machinery. The performance of the models is compared to determine the most accurate and reliable predictor. The results demonstrate that the GPR model consistently outperforms the SVM model in terms of accuracy and consistency. The proposed GPR model is poised to be a valuable tool for policymakers and organizations in making informed decisions to mitigate carbon emissions