Journal of Techniques

Today, water pumping plays a crucial role throughout the world, due to its many uses, such as irrigation, watering livestock and supplying water for domestic needs in isolated areas not served by traditional distribution networks (of water and/or electricity in general). The use of photovoltaic solar energy offers promising, environmentally friendly prospects for pumping water in these regions. However, several factors limit the performance of these pumping systems. To achieve this goal, a significant amount of work is underway to optimize the efficiency of these photovoltaic water pumping systems. In this study, various methods for enhancing pumping system efficiency are analyzed, such as the maximum power point tracking (MPPT) methods used, highlighting their respective advantages and limitations, as well as hydraulic system architectures. The aim is therefore to suggest research proposals for improving the energy efficiency of photovoltaic water pumping systems, with a view to promoting the transition to a more environmentally friendly and sustainable energy future.

Flexible capacitive pressure sensors offer unparalleled benefits—malleability, stability, simplicity, low power consumption, and minimal sensitivity to temperature fluctuations. Yet, their expensive materials, complex, and environmentally detrimental manufacturing processes impede their widespread adoption. This study unveils a cost-effective, simple, and environmentally sustainable method to fabricate highly sensitive flexible capacitive pressure sensors that outperform costly sensors manufactured using unsustainable materials. By sandwiching a flexible polyurethane (PU) sheet between two silver-metallized fabrics (SMF) and securing them with polyethylene adhesive tape (PAT), we have eliminated the need for expensive and specialized equipment and methods. Crafting sensors of varying dimensions is now as simple as cutting fabric and PU sheets with everyday tools. The key to the sensor's performance lies in the exceptional deformability of the PU layer under applied pressure, resulting in an impressive sensitivity of 0.377358 kPa⁻¹.This surpasses the sensitivity of existing non-eco-friendly and expensive sensors reported in the literature. Additionally, the sensor exhibits excellent pressure resolution and high repeatability. Our sensor accurately detects intricate human movements like palm bends and taps, showcasing its potential across diverse applications—from robotic skins to smart wearables and seamless human-computer interactions. With a production cost as low as 0.34 USD per sensor —significantly lower than the costs of sensors reported in the literature—this study signals a significant advancement in flexible sensor technology, combining affordability, simplicity and sustainability with exceptional performance.

The Battery Energy Storage System (BESS) has become a key tool for improving power system performance. However, the use of BESS in a distribution grid has several problems including deciding where to position it and how much capacity should be used to maximize its benefits. The purpose of this study is to optimize the siting and sizing of BESS for enhanced voltage profile and reduced power losses across the distribution system. To do this, two meta-heuristic optimization algorithms are suggested in this paper, Particle Swarm Optimization (PSO) and Dragonfly Algorithm (DA). Two cases have been presented. The first case includes 33 buses, while the second has 85 buses. The results of both cases are successfully effective in reducing system losses and improving the voltage profiles in power systems. It is observed that losses reduce by 45.59% compared to the base case for Case 1. The value in Case 2 decreases by 40.09% compared to the base case. The voltage profiles in Case 1 show an increase, with a minimum voltage of 0.95 PU, compared to the base case where the minimum voltage was at 0.904 PU. In Case 2, the minimum voltage becomes 0.95 PU instead of 0.874 PU in the base case.

The identification of vehicle logos in videos and images can be considered a crucial undertaking in several applications, such as traffic surveillance systems. The accelerated progress of deep learning has resulted in an increasing need within the computer vision field for the development of efficient, robust, and outstanding services across several domains, such as the recognition and classification of automobile emblems. This survey begins with an exploration of the escalating significance of logos and the associated challenges to their detection. The core problem addressed revolves around the necessity for robust methodologies capable of accurately identifying logos in diverse scenarios. The objective of our study is to conduct a comprehensive examination of existing deep learning strategies for logo detection, unveil their real-world applications, and contribute insights into future challenges and directions in this domain. Our survey uncovers valuable insights into publicly available datasets, showcasing their diversity and relevance in evaluating logo detection algorithms. An in-depth analysis of deep learning strategies follows, elucidating their strengths and limitations and providing a nuanced understanding of their performance metrics. The survey concludes by delineating anticipated challenges and proposing future directions, thereby presenting a roadmap for researchers and practitioners seeking to advance logo detection using deep learning techniques.

This paper describes the development and testing of an Arduino-based audiometer for measuring ten levels of sound generated by a speaker. The device uses an Arduino UNO platform and includes an OLED display, a MAX7219 matrix LED, and a push-button for the person being tested to indicate when they hear a sound level. The results showed that the device could accurately measure sound levels and provide a reliable measure of hearing sensitivity. Arduino-based audiometers have several advantages over traditional audiometers, including low cost, portability, and customizability. However, the accuracy of these devices compared to traditional audiometers is still an area of concern, and further research is needed to validate their use in clinical settings. This paper contributes to the growing body of literature on the development and validation of Arduino-based audiometers and demonstrates the potential of these devices to provide an affordable and accessible way to diagnose hearing loss.

Concrete is one of the most used construction materials., Mineral admixtures with pozzolanic characteristics, like silica fume, fly ash, ground granulated blast-furnace slag, and metakaolin, are often used to replace Portland cement in construction projects partially. Concrete faces persistent challenges, such as low tensile strength, brittleness, and a propensity to crack. This comprehensive study explores the improvement of partial substitution of Portland cement concrete properties with fly ash and reinforced with steel fibers and iron filings. In total, 45 cubes (150 mm) and prisms (100x100x500 mm) were tested using an M25 mix, varying the steel fiber volume fractions at 0%, 0.5%, and 1.0%. These specimens were subjected to given curing periods, after which compressive and split tensile strength tests were conducted to assess their performance. For comparison, plain concrete specimens of the same mix were also tested. Also, iron filings were incorporated into the concrete mix at three different percentages (0%, 0.5%, and 1%) to assess their influence on compressive and tensile strengths after 28 days. The results demonstrate that the addition of steel fibers significantly enhances the mechanical properties of concrete. After 28 days, compressive strength increased by 8.5% to 24%, tensile strength improved by 15% to 49.43%, and flexural strength increased by 38.5% to 85%. Similarly, the inclusion of iron filings improved compressive strength by 9.78% initially, followed by a decrease of 13.84% at higher content. Tensile strength increased by 24.05% to 34.43%, while flexural strength improved by 21% to 29.7%. However, both steel fibers and iron filings slightly reduced workability, with slump values ranging from 63 mm to 92 mm depending on the material and its proportion. The outcomes provide a comparative analysis of the effect of steel fibers and iron filings on the mechanical characteristics of concrete, and present valuable understandings for optimizing concrete behavior in construction applications.

Water quality monitoring is important for water resource management, but traditional methods are expensive and limited. Remote sensing provides a practical solution to access accurate information at the lowest cost and in the fastest time. The research aims to study the changes in dissolved materials in the water of the Al-Gharraf River, which is located in the Al-Hay area in Wasit Governorate and is considered one of the main sources of surface water in Iraq. Seasonal data (winter and summer of 2021 and 2022) of water quality parameters collected from the water quality monitoring station in the study area were taken as field observations, and Landsat 8 images formed the remote sensing data for the research. Landsat images were processed using the maximum likelihood classification (MLC) algorithm and water bodies in the area were identified. The performance of MLC was evaluated with precision and precision criteria. The average classification accuracy for the train data was 0.954 and 0.970, and for the test data, they were 0.936 and 0.97, respectively. To detect water bodies, the correlation between six spectral bands, two spectral indices, and 12 different combinations of spectral bands and water quality parameters was calculated using Pearson's coefficient. The results were different depending on the qualitative criteria, but the observed high correlation coefficients showed that the remote sensing data used in the research were useful for monitoring changes in dissolved materials in the water of the Garraf River. The spatial trend of changes was analyzed by the Mann-Kendall test and the temporal trend was analyzed by fifth-order polynomial fitting. The study revealed uniform spatial and seasonal changes in river water quality standards, which affect the environment, aquatic life, and citizens. Landsat satellite data provide valuable information to monitor these changes and help decision makers manage water resources effectively.

In pursuing energy-efficient building solutions, renewable energy sources like solar power are increasingly utilized in ventilation and cooling systems. This study specifically investigates a solar-powered desiccant cooling system's performance against the traditional fan coil unit (FCU) in residential settings. It highlights the potential for energy savings and improved environmental outcomes. A model employing a solar heater with a vacuum tube is developed and simulated using TRNSYS to perform a critical thermal analysis of these systems. Key results show that increasing the input current to the collectors reduces the necessary collector area, thereby enhancing overall system efficiency. Energy evaluations reveal that the FCU, with a room moisture content of 79.4%, fails to provide adequate cooling due to its inability to meet the desired 45% moisture threshold. The drying process consumes the most energy, accounting for 38% of total usage. However, the solar hybrid dehumidifier cooling method demonstrates economic efficiency, achieving 18.4% in structures with high residual loads. Ambient temperatures and moisture content are effectively lowered to 24.8 – 25 °C, and 63%–67%, respectively, using the two-phase solar dehumidifier cooling device. This adjustment leads to 28.7% and 34.6% energy savings for convection and recirculating options. These findings underscore the potential of solar-powered systems to enhance energy efficiency and reduce environmental impacts in tropical climates.

The resistance spot welding (RSW) technique is widely used for joining two or more metal sheets by involving heat generated by electrical resistance. Due to its efficiency and cost-effectiveness, it is commonly utilized in the automotive, aerospace, and manufacturing industries.
Despite its advantages, RSW faces several challenges, including inconsistent joint quality, surface defects, and variations in mechanical strength. These problems are often attributed to welding current, welding time, electrode wear, and heat distribution inconsistencies, which can compromise the structural integrity of welded components.
Various advanced processes have been developed to address these problems, including numerical modeling, real-time monitoring systems, vibration analysis, and machine learning-based optimization. These methods enhance weld quality, detect defects early, and optimize welding parameters for improved performance.
This study examines the vibration characteristics of resistance spot welds in carbon steel AISI 1005. It employs experimental and numerical approaches to analyze the relationship between vibration behavior and weld integrity. The findings are expected to contribute to developing predictive models for assessing weld quality and enhancing process reliability in industrial applications.

Recently, epoxy resin-based composite structures have been widely used in many engineering applications due to their superior mechanical properties, thermal insulation and acoustic damping. However, to further improve the mechanical performance, several studies indicate significant benefits can be achieved using woven carbon fibers and different core material reinforcements for sandwich composite materials. The present review includes a comprehensive review of the most important composite material manufacturing techniques such as hand layup, spray layup, compression moulding, extrusion compound, filament winding, moulding injection, pultrusion, resin transfer moulding, and vacuum infusion or vacuum-assisted resin transfer, and the advantages of each method. In addition to the mechanical performance of epoxy composites and the possibility of improving these properties by using different strategies to enhance interfacial bonding and mechanical performance. These strategies include the incorporation of nanoparticles, surface modifications, the use of advanced resin systems, and a review of the latest studies in this field. Each approach aims to interaction improvement between carbon fibers and the epoxy matrix, thus enhancing properties such as tensile strength, compression strength, impact resistance, and interlaminar shear strength. To establish a systematic understanding of design criteria, this work intends to summarize all studies in the open literature about this topic. It is concluded that enhancing the mechanical performance of sandwich structural composites depends on the selection of the appropriate manufacturing method, which is determined by material properties, cost considerations, processing requirements, and specific applications.