Search Results (244)

This paper presents the design, development, and preliminary validation of a haptic virtual reality simulator for Shielded Metal Arc Welding (SMAW) at the Pontificia Universidad Católica de Valparaíso, Chile, aimed at enhancing psychomotor training for mechanical engineering students in line with Industry 4.0 demands. The system integrates Unity 3D, a commercial haptic device, and a custom 3D-printed electrode holder replicating the welding booth, enabling interaction through visual, auditory, and tactile feedback. Thirty students with minimal welding experience and seven experts participated in usability and realism assessments. The results showed that 80% of students perceived motor skill improvement, 60% rated realism as adequate, and 90% preferred hybrid training (simulator + workshop). The prototype was practically implemented at the mechanical engineering school, requiring only a mid-range workstation, the Touch haptic device, and the developed software, demonstrating feasibility in real academic settings. The findings indicate potential to build confidence, support motor coordination, and provide a safe, resource-efficient training environment, while experts emphasized the need for automated feedback and improved haptic fidelity. The modular architecture allows scalability, extension to other welding processes, and adaptation for inclusive education. This prototype demonstrates how locally developed immersive technologies can modernize technical education while promoting sustainability, accessibility, and skill readiness. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article

The calculation of internal forces is a critical aspect in the design of statically indeterminate structures. Local trapezoidal loads, as a common loading configuration in practical engineering (e.g., earth pressure, uneven surcharge), make it essential to investigate how to compute the internal forces of statically indeterminate structures under such loads by using the displacement method. The key to displacement-based analysis lies in deriving the fixed-end moment formulas for local trapezoidal loads. Traditional methods, such as the force method, virtual beam method, or integral method, often involve complex computations. Therefore, this study aims to derive a general formula for fixed-end moments in statically indeterminate beams subjected to local trapezoidal loads by using the integral method, providing a more efficient and clear theoretical tool for engineering practice while addressing the limitations of existing educational and applied methodologies. The integral method is employed to derive fixed-end moment expressions for three types of statically indeterminate beams: (1) a beam fixed at both ends, (2) an an-end-fixed another-end-simple-support beam, and (3) a beam fixed at one end and sliding at the other. This approach eliminates the redundant equations of the traditional force method or the indirect transformations of the virtual beam method, directly linking boundary conditions through integral operations on load distributions, thereby significantly simplifying the solving process. Three representative numerical examples validate the correctness and universality of the derived formulas. The results demonstrate that the solutions obtained via the integral method align with software-calculated results, yet the proposed method yields analytical expressions for structural internal forces. Comparative analysis shows that the integral method surpasses traditional approaches (e.g., force method, virtual beam method) in terms of conceptual clarity and computational efficiency, making it particularly suitable for instructional demonstrations and rapid engineering calculations. The proposed integral method provides a systematic analytical framework for the internal force analysis of statically indeterminate structures under local trapezoidal loads, combining mathematical rigor with engineering practicality. The derived formulas can be directly applied to real-world designs, substantially reducing computational complexity. Moreover, this method offers a more intuitive theoretical case for structural mechanics education, enhancing students’ understanding of the mathematical–mechanical relationship between loads and internal forces. The research outcomes hold both theoretical significance and practical engineering value, establishing a solving paradigm for the displacement-based analysis of statically indeterminate structures under complex local trapezoidal loading conditions. Full article

With the growing adoption of CLO 3D in the fashion industry and educational settings, the need for accurate material representation and fit simulation in virtual environments is increasing. This study aimed to evaluate whether CLO 3D, without the aid of physical samples, can reliably simulate clothing pressure for compression wear made from different materials. Unlike previous CLO 3D studies that focused on design or pattern accuracy, this study critically examined material-specific simulation limitations and proposed technical enhancements. Two types of leggings with varying spandex content were tested across five yoga poses using the CLO 3D software(version 2024.2.214). The results showed that CLO 3D did not detect differences in clothing pressure caused by variations in spandex content. Furthermore, the pressure values remained constant across different poses for both fabrics, failing to reflect realistic mechanical differences. The highest total clothing pressure was recorded in the Lunge pose (277.02 kPa), and the lowest in the Plow pose (241.37 kPa). These findings suggest that the current simulation engine lacks sensitivity to fabric-specific mechanical properties and movement-based variation. To address these limitations, this study proposes five optimization functions for CLO 3D, including material property input, technical textile databases, environmental condition settings, AI-based comfort prediction, and data management tools. These proposals are expected to strengthen the scientific validity, functional realism, and user-centered applicability of CLO 3D in designing sportswear, medical compression garments, and customized apparel. Full article

Operating systems such as Windows, Linux, and macOS include built-in commands that enable administrators to perform essential tasks. These same commands can be exploited by attackers for malicious purposes that may go undetected by traditional security solutions. This research identifies an unmitigated risk of misuse of a standard command to disconnect network services on victim devices. Thus, we developed a novel Proof-of-Concept (PoC) malware named DCmal-2025 and documented every step of its lifecycle, including the core idea of the malware, its development, impact, analysis, and possible countermeasures. The proposed DCmal-2025 malware can cause a Denial-of-Service (DoS) condition without exploiting any software vulnerabilities; instead, it misuses legitimate standard commands and manipulates the routing table to achieve this. We developed two types of DCmal-2025: one that triggers a DoS immediately and another that initiates it after a predefined delay before restoring connectivity. This study evaluated 72 antivirus detection rates of two malware types (DCmal-2025 Type 1 and Type 2) written in C and Rust using VirusTotal. The source code for both types was undetected by any of the antivirus engines. However, after compiling the source code into executable files, only some Windows executables were flagged by general keywords unrelated to DCmal-2024 behaviour; Linux executables remained undetected. Rust significantly reduced detection rates compared to C—from 7.04% to 1.39% for Type 1 and from 9.72% to 4.17% for Type 2. An educational institution was chosen as a case study. The institution’s network topology was simulated using the GNS3 simulator. The result of the case study reveals that both malware types could cause a successful DoS attack by disconnecting targeted devices from all network-based services. The findings underscore the need for enhanced detection methods and heightened awareness that unexplained network disconnections may be caused by undetected malware, such as DCmal-2025. Full article

The development of green technologies in recent years in the field of wind energy conversion into electricity implies a technology transfer from the static switching field to the energy field. This paper presents a wind turbine simulator using a hardware solution following the energy conversion of a real turbine. We implemented this solution for educational and research purposes to train students in the process of electrical conversion in wind turbines. For the simulation, we chose an E82/2300 turbine, installed by ENERCON in a nearby geographical area. The turbine has the capacity to generate 2300 kW of electricity into grids. It has a direct coupling structure of the propeller to the generator. The solution is implemented on a multi-processor architecture with analog signal processing. The structure of a wind turbine is divided into three consecutive blocks, namely TUGEN, DCDC4X, and SIN3F. Each block of the simulator is designed with electronic components. The input and output signals of these blocks have similar waveforms to real signals, and their succession is interconditioned by process parameters. The innovation of the proposed solution is provided by software engineering applied to a hardware structure. The ratio between the simulated and real values is 1:60 in order to visualize the signals on a digital oscilloscope, mainly for educational purposes. Full article

The development of information technology has transformed various aspects of life, including education, by making it more flexible, interactive, and accessible. One platform that plays an important role in this transformation is YouTube, a video sharing platform that allows users to upload, watch, share, and comment on videos online. YouTube is not only a medium of entertainment, but also a significant source of additional learning, especially in higher education such as the Informatics Engineering Department. The platform provides various learning materials, such as programming tutorials, computer network concepts, and software development, which can be accessed anytime and anywhere. YouTube’s advantages lie in its accessibility and the ability for users to repeat videos, making it easier to understand complex material. However, using YouTube as a learning resource also has its challenges, such as the difficulty in finding relevant and high-quality content, as well as the variety of academic standards used in the delivery of the material. Therefore, this study aims to evaluate the effectiveness of YouTube as an additional learning media and provide recommendations for the best channels for Informatics Engineering students. Factors, such as the number of views, the number of subscribers, the frequency of uploading new content, and the background of the content creator, are considered in channel selection. The Weighted Product (WP) method in the Decision Support System (SPK) is used to evaluate the effectiveness of YouTube based on predetermined standards. The research results are expected to provide recommendations for the most relevant and high-quality YouTube channels so as to improve students’ understanding of educational materials and optimize the use of digital learning resources. Full article

Project-based learning provides a common context for STEM education at all educational levels. However, before future chemistry teachers can implement it in their teaching, they need to have experience in completing complex projects by themselves. According to previous research, an engineering perspective in STEM projects has been difficult to implement. Therefore, this design-based research project focuses on producing pedagogical resources for conducting STEM projects based on authentic engineering practices. Through three-cycle design research, we crafted Excel templates that support a step-by-step framework for completing complex engineering projects and an evaluation matrix that includes formative and summative tools. The design solutions were validated through empirical problem analysis, which yielded qualitative insights into the possibilities and challenges of the produced tools. From this data, we formulated five best practices for teachers to focus on achieving successful project outcomes, with priority being to support the progress of the engineering approach and support it via guidance and peer collaboration. For future chemistry teachers, artificial intelligence tools offer support, especially for hardware assembly and software coding. The research produced educational artifacts that support conducting STEM projects in higher education and insights into their best practices. Since design solutions are based on research and real-life engineering practices, they are useful for all fields in higher education that conduct STEM projects and aim to teach authentic engineering skills. Full article

Online laboratories have emerged as a viable alternative for providing hands-on experience to engineering students, especially in fields related to computer, software, and electrical engineering. In particular, remote laboratories enable users to interact in real time with physical hardware via the internet. However, current remote laboratory systems often restrict access to a single user per session, limiting broader participation. Embedded systems laboratory activities have traditionally relied on in-person instruction and direct interaction with hardware, requiring significant time for code development, compilation, and hardware testing. Students typically spend an important portion of each session coding and compiling programs, with the remaining time dedicated to hardware implementation, data collection, and report preparation. This paper proposes a remote laboratory implementation that optimizes remote laboratory stations’ availability, allowing users to lock the system only during the project debugging and testing phases while freeing the remote laboratory station for other users during the code development phase. The implementation presented here was developed for a microprocessor laboratory course. It enables users to code the solution in their preferred local or remote environments, then upload the resulting source code to the remote laboratory hardware for cross-compiling, execution, and testing. This approach enhances usability, scalability, and accessibility while preserving the core benefits of hands-on experimentation and collaboration in online embedded systems education. Full article

Providing students with effective learning resources is essential for improving educational outcomes—especially in complex and conceptually diverse fields such as Mathematics and Computer Science. To better understand how these subjects are communicated, this study investigates the linguistic structures embedded in academic texts from selected subfields within both disciplines. In particular, we focus on meta-languages—the linguistic tools used to express definitions, axioms, intuitions, and heuristics within a discipline. The primary objective of this research is to identify which subfields of Mathematics and Computer Science share similar meta-languages. Identifying such correspondences may enable the rephrasing of content from less familiar subfields using styles that students already recognize from more familiar areas, thereby enhancing accessibility and comprehension. To pursue this aim, we compiled text corpora from multiple subfields across both disciplines. We compared their meta-languages using a combination of supervised (Neural Network) and unsupervised (clustering) learning methods. Specifically, we applied several clustering algorithms—K-means, Partitioning around Medoids (PAM), Density-Based Clustering, and Gaussian Mixture Models—to analyze inter-discipline similarities. To validate the resulting classifications, we used XLNet, a deep learning model known for its sensitivity to linguistic patterns. The model achieved an accuracy of 78% and an F1-score of 0.944. Our findings show that subfields can be meaningfully grouped based on meta-language similarity, offering valuable insights for tailoring educational content more effectively. To further verify these groupings and explore their pedagogical relevance, we conducted both quantitative and qualitative research involving student participation. This paper presents findings from the qualitative component—namely, a content analysis of semi-structured interviews with software engineering students and lecturers. Full article

Virtual reality offers unique opportunities to personalize learning by adapting instructions to individual learning styles. This study explores the relationships between learning styles, cognitive load, and learning outcomes in a virtual reality environment designed for engineering education. Drawing on Kolb’s experiential learning theory, the research investigates how immersion and flow, in relation to learning styles, influence learning outcomes within the Submarine Simulator, an educational tool for underwater engineering. To enhance instructional design in virtual reality, this study proposes to aggregate existing and validated models, such as Kolb’s framework, to develop new models tailored specifically for learning environments in virtual reality. This research aims to highlight the interplay of these variables in a learning process focused on acquiring knowledge in the Science, Technology, Engineering, and Mathematics fields, specifically hydrodynamics, through designing and operating a simulated submarine model in virtual reality. A cohort of 26 students from MINES Paris—PSL participated in a three-phase testing process to evaluate the effectiveness of original virtual reality software designed to support learning in underwater engineering. The findings enhance our understanding of how learning styles influence learner engagement and performance and how virtual reality environments can be optimized through adaptive instructional design guided by these novel models tailored specifically for such immersive settings. Full article

STEM education is constantly seeking innovative methods to enhance student learning. Virtual Reality technology can represent a critical tool for effectively teaching complex engineering subjects. This study evaluates an original Virtual Reality software application, entitled Submarine Simulator, which is developed specifically to support competencies in hydrodynamics within an Underwater Engineering course at MINES Paris—PSL. Our application uniquely integrates a customized physics engine explicitly designed for realistic underwater simulation, significantly improving user comprehension through accurate real-time representation of hydrodynamic forces. The study involved a homogeneous group of 26 fourth-year engineering students, all specializing in engineering and sharing similar academic backgrounds in robotics, electronics, programming, and computer vision. This uniform cohort, primarily aged 22–28, enrolled in the same 3-month course, was intentionally chosen to minimize variations in skills, prior knowledge, and learning pace. Through a combination of quantitative assessments and Confirmatory Factor Analysis, we find that Virtual Reality affordances significantly predict user flow state (path coefficient: 0.811) which then predicts user engagement and satisfaction (path coefficient: 0.765). These findings show the substantial educational potential of tailored Virtual Reality experiences in STEM, particularly in engineering, and highlight directions for further methodological refinement. Full article

This review provides a comprehensive overview of the evolution and application of artificial intelligence (AI) and large language models (LLMs) in engineering, with a specific focus on chemical engineering. The review traces the historical development of LLMs, from early rule-based systems and statistical models like N-grams to the transformative introduction of neural networks and transformer architecture. It examines the pivotal role of models like BERT and the GPT series in advancing natural language processing and enabling sophisticated applications across various engineering disciplines. For example, GPT-3 (175B parameters) demonstrates up to 87.7% accuracy in structured information extraction, while GPT-4 introduces multimodal reasoning with estimated token limits exceeding 32k. The review synthesizes recent research on the use of LLMs in software, mechanical, civil, and electrical engineering, highlighting their impact on automation, design, and decision-making. A significant portion is dedicated to the burgeoning applications of LLMs in chemical engineering, including their use as educational tools, process simulation and modelling, reaction optimization, and molecular design. The review delves into specific case studies on distillation column and reactor design, showcasing how LLMs can assist in generating initial parameters and optimizing processes while also underscoring the necessity of validating their outputs against traditional methods. Finally, the review addresses the challenges and future considerations of integrating LLMs into engineering workflows, emphasizing the need for domain-specific adaptations, ethical guidelines, and robust validation frameworks. Full article

This study explores the application of 3D printing as a strategic tool in engineering education and robotics development. An embedded control system for a 3D-printed MK2 manipulator is implemented, including an Arduino microcontroller, servo motors, an analog joystick interface, and an LCD, with software developed in Arduino IDE. The design uses PLA material and a modular architecture for flexibility and extensibility. The platform is applied in laboratory training to develop algorithmic thinking and engineering creativity, demonstrating the potential of 3D printing as an integrated educational and engineering tool. Full article

This study investigates the integration of LTspice simulations and structured reflective practices within a project-based learning (PBL) framework in a Microelectronic Circuits course. The course was designed to improve students’ conceptual understanding, problem-solving abilities, and engagement by embedding simulation-based assignments and guided reflections within a final design project. A qualitative case study was conducted with 49 third-year undergraduate electrical engineering students. The data sources included structured reflection submissions, researcher observations, and evaluations of project presentations. Thematic analysis identified five recurring themes: linking theory to practice, iterative problem-solving strategies, metacognitive awareness, peer engagement, and reflections on integration challenges and benefits. The results indicate that the LTspice simulations enabled the students to visualize circuit behavior, experiment with design parameters, and observe the effects of design trade-offs. The integration of structured reflection prompted deeper learning by helping the students recognize misconceptions, articulate troubleshooting strategies, and build confidence in circuit analysis. Although some students initially struggled with the complexity of the simulation software, the iterative and collaborative nature of the PBL process increased their motivation and promoted meaningful engagement. This study contributes to the growing body of research on active learning in engineering education and offers practical recommendations for implementing simulation-based learning environments that promote critical thinking, metacognition, and technical competence. Full article