This study explores the feasibility of using additive manufacturing for constructing hydraulic prototypes by comparing experimental data with computational simulations of pressure loss in perforated plates. Based on the experimental results presented by Souza (2024), numerical simulations were performed using Ansys CFX, which applies the Reynolds-Averaged Navier-Stokes (RANS) model and the geometric ones—likely due to the plate’s short height and relatively large diameter. short height and relatively large diameter. The findings suggest that additive manufacturing is a promising alternative for building experimental components, and that well-calibrated computational models may accurately predict their hydraulic performance. Future studies should investigate geometries that enhance the influence of surface roughness, enabling a more detailed assessment of its impact on flow behavior

— Smart and wearable devices for visually impaired individuals have advanced significantly, but often face limitations such as limited functionality, high cost, and usability issues. Despite numerous studies and available solutions, providing comprehensive and accessible support remains challenging. This study identifies these gaps through various literature reviews and market analyses, proposing an innovative approach by integrating ultrasonic sensors with the Arduino Pro Mini board to create a 'third eye for the blind.' This device uses ultrasonic waves to detect obstacles and alerts users with buzzer sounds or vibrations, enabling confident and swift navigation. Leveraging advancements in computer science, electrical engineering, and medicine, this solution addresses the limitations of traditional aids like the white cane. According to WHO, 39 million people globally are visually impaired, facing significant daily challenges. Existing technologies offer alternatives, but the given solution uniquely enhances mobility by allowing users to locate and recognize objects in their vicinity, providing alerts through vibrations or beeps when objects are detected. This approach offers a practical, cost-effective, and user-friendly alternative, significantly improving the quality of life for visually impaired individuals by enhancing their ability to travel safely and independently.

The curved structural components of aircraft, automobiles, and marine vessels, such as cylindrical panels, are primarily exposed to loading, which can result in bending failure, particularly in lightweight structures. The bending analysis of cylindrical panels made of functionally graded multiwall carbon nanotube (FG-MWCNT) epoxy composites is subjective in this study. In the first section, FG-MWCNT composite cylindrical panels are simulated in the ANSYS software. There are three methods for distributing uniaxially aligned reinforcements. The material properties of the carbon nanotubes uniformly distributed and functionally graded over the thickness of the shell structure are estimated using an extended rule of mixture micromechanical model that incorporates certain useful characteristics. To demonstrate the effectiveness and applicability of the proposed finite element approach, deflection data are presented. The analysis of the shell structure's bending includes an investigation of the impact of CNT volume fraction, boundary condition, lengthto-thickness ratio, and other geometrical factors

In order to engage with customers in completely immersive virtual worlds, businesses have undergone unprecedented changes since the metaverse emerged. Traditional marketing strategies, the majority of which are meant for traditional digital or physical environments, face numerous challenges in this new frontier. Businesses find it difficult to interact with target audiences in the metaverse, gauge the success of their virtual marketing campaigns, develop memorable brand experiences as they go, and assess the impression left on customers. Understanding how the metaverse's virtual marketing landscape is evolving and how it affects customer-centred strategies is the aim of this research. Its two primary goals are: Initially, it seeks to assess the extent to which various types of individuals are use the metaverse. Examining variations in rates according to age, gender, and socioeconomic position is part of this. Second, the study aims to investigate consumers' perceptions of virtual marketing, with a particular focus on potential disparities in perception across different age groups. Lastly, it seeks to do a comparative analysis of virtual and conventional marketing techniques. This will facilitate the evaluation of how well each strategy locates and engages the intended audience.

In response to the challenges posed by climate change and the need for sustainable food supply, this study addresses the problem of efficiently categorizing and predicting the weight of fish in aquaculture. Leveraging machine learning and deep learning algorithms, we propose a regression model to predict fish weight and classification models for species identification based on weight, width, and length parameters. The focus is on automating fish farming processes to ensure uninterrupted food supply amidst environmental uncertainties. Comparative analysis of various machine learning algorithms reveals promising accuracy levels, with deep learning sequential models achieving 99.77% accuracy under specific conditions. This research aims to contribute to the advancement of automated fish farming practices, mitigating the impact of climate change on food securi

The smartphone has evolved into a little computer that can perform all of our daily tasks, including social media use, email correspondence, and banking. The use of smartphones is also increasing quickly. Because there are more and more connected biases in the network field every day, cyberattacks are also increasing. All connected device linked to the Internet has become the target of cyberattacks as new types of network attacks have emerged. Consequently, network data security cannot be disregarded. Not only is operating system and device usage directly related to mobile security, but internet and communication with stoners, data encryption, and the sequestration consciousness of drug users are also important factors. the primary donation and the study's conclusionare to collect information about mobile security, Mobile hazards and network security in the present and future. research in this area on mobile vulnerabilities, attack types, and malware. Every mobile device has a number of vulnerabilities due to different features and terrain. Cybersecurity has become crucial for the service, associations, and specific computer users. Since the advent of the internet, security has become a top priority, and the development of safety technology is informed by security history. Positive safety pitfalls are made possible by the net shape itself. But only if the Internet's design is altered. will decrease the potential attacks that could be made across the network.

The memory wall presents a significant challenge in computing, highlighting the increasing gap between processor and memory speeds. This discrepancy has sparked extensive research efforts to bridge the divide between memory units and processors. An approach is to minimize latency by integrating memory and processing units, specifically aiming to enhance memory processing capabilities. In this context, in-memory computing has emerged as a solution offering swift performance and streamlined data retrieval. This study addresses the memory wall issue by employing Block RAM (BRAM), a common component in digital design and FPGA programming, as an in-memory logic. The focus is on utilizing BRAM to store partial products from a Wallace Tree Multiplier (WTM), thereby facilitating rapid and efficient data storage within the FPGA fabric. The effectiveness of this method was demonstrated through simulation using Xilinx Vivado, showcasing its potential in overcoming the challenges posed by the memory wall.

This study explores the development trends of AI in education through a bibliometric analysis of literature from 2011 to 2021. Using the Biblioshiny toolkit for Bibliometrix in R language, we analyzed titles, authors, abstracts, keywords, citations, and affiliations. The findings reveal research changes and hot directions in AI education, forecasting future developments. While regions like the US and UK have achieved success in AI education, China is integrating AI into teaching disciplines. The rise of AIGC and companies like OpenAI is accelerating AI integration in education, creating opportunities for personalized learning, adaptive education, and intelligent educational management. Collaboration among stakeholders and comprehensive strategies are crucial for successful AI implementation in education

With the rapid increase in the number of vehicles fueled by gasoline plying on the roads, there has been a rising need in the search for alternative fuels, which are more environmental friendly in order to reduce the amount of vehicular exhaust emissions. This can be achieved by using blended mixtures of gasoline with alcoholic fuels among which, ethanol is found to be most suitable due to its easy availability, low costs, safety and low impact on the engine performance. This study aims to investigate the performance of a single-cylinder, four-stroke spark-ignition engine using different ethanol-gasoline blends, namely E0, E10, E20 and E30. The engine's torque, brake power, brake thermal efficiency, brake-specific fuel consumption, and exhaust emissions were analysed using numerical simulation. Results revealed that raising the proportion of ethanol in the fuel mixture resulted in reduced brake power and torque upto 16% as a result of decrease in calorific value of the mixture. The engine's brake thermal efficiency decreased by upto 3% while the brake-specific fuel consumption increased upto 12% with increase in ethanol concentration. Exhaust emissions, including NOx and HC, were found to be influenced by engine speed, with NOx emissions increasing and HC emissions decreasing as speed increased. The study also revealed that increasing ethanol concentration in the fuel resulted in reduced engine exhaust emissions by upto 47% and 10% for NOX and HC emissions respectively. The study concluded that among all the blends used, optimum performance was obtained for E30 blend with reduction in exhaust emissions but at the expense of slight reduction in engine performance.

— Thermal efficiency of flat collector surface solar air heater (SAH) is relatively poor due to poor heat transfer coefficient. This article’s primary objective is to evaluate the heat transfer and pressure loss characteristics of counter flow SAH (CFSAH) by adopting novel discrete multi-V-shaped and staggered rib geometry. The experimentations are performed for various flow Reynolds number (Re) ranging from 3000- 21000 and rib parameters including relative gap distance (Gd /Lv) from 0.24 -0.69 and relative gap width (g/e) from 0.5-1.5 while other parameters are kept as constant. The study revealed that the maximum increment in heat transfer as 4.52 times and friction factor as 3.13 times as compared to non-roughened duct has been obtained. Further, the thermohydraulic performance parameter (TPP) has also been investigated to obtain the optimum parameters. The minimum and maximum value of TPP has been achieved as 1.94 and 3.88 corresponding to Re=2000 and Re=16000 respectively. Therefore, the present work can be fruitful for heating and drying application