Online-Journals.org (International Association of Online Engineering)
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Interactive Learning Redefined: How Multimedia Scenario Editors Enhance Immersive Education and Feedback
Get PDFThe Multimedia Scenario Editor developed by e-REAL Labs represents a major advancement in experiential learning and simulation-based education. This innovative tool enhances traditional simulation methods by integrating interactive multimedia elements, creating highly immersive and multisensory learning environments. Educators can incorporate visual, auditory, and, in some cases, kinesthetic and olfactory stimuli, significantly enhancing engagement and realism. Its flexible and adaptive design allows for real-time customization, enabling educators to tailor learning experiences to meet individual learner needs. This paper examines the capabilities of the Multimedia Scenario Editor, highlighting its practical applications in simulation-based education and its role in enhancing the debriefing process. Additionally, implementation strategies are discussed, providing educators with actionable insights to maximize the technology’s impact. By enriching educational experiences and fostering deeper learner engagement, the Multimedia Scenario Editor is a comprehensive and scalable solution for modern training environments
The Use of Simulated Scenarios in the Training of the National Police: Pedagogical Innovation in SERÁS FORMACIÓN
Get PDFSimulated scenarios have emerged as an effective pedagogical tool in the training of National Police officers, allowing trainees to develop critical skills in a controlled and realistic environment. This article explores the implementation of simulated scenarios in SERÁS FORMACIÓN, highlighting their theoretical basis, benefits and practical application. A specific example of a scenario related to domestic violence is presented, highlighting how these simulations contribute to the development of technical, emotional and ethical competencies essential in police performance
Image Captioning for Medical Surveillance in Smart Home Environments Using Vision Transformers
Get PDFMedical surveillance in smart homes represents a transformative approach to patient care by utilizing advancements in computer vision to monitor and analyze patient behavior continuously. This study builds upon previous research by fine-tuning vision transformer (ViT) neural networks with a curated dataset that includes diverse scenarios of patients in both normal and abnormal conditions. The proposed model generates descriptive captions from surveillance camera images, effectively capturing contextual information and identifying potential medical indicators. These insights are integrated into an automated notification system designed to alert healthcare providers promptly, enabling timely and informed interventions. To evaluate the effectiveness of the approach, the fine-tuned ViT model is compared against traditional convolutional neural networks (CNNs) state-of-the-art model, demonstrating superior performance with an accuracy of 87.2%, a BLEU-4 score of 0.351, and a ROUGE-2 score of 0.591. These results highlight the model’s ability to generate accurate and contextually relevant captions, outperforming CNN-LSTM baselines in accuracy, robustness, and contextual understanding. The findings underscore the critical role of artificial intelligence (AI) in detecting changes in patient conditions and providing personalized care through real-time monitoring. This proof-of-concept highlights the feasibility of deploying AI-driven solutions in medical surveillance systems, paving the way for innovative healthcare technologies. By addressing key challenges in patient monitoring, the study establishes ViT as a reliable and scalable tool for enhancing the quality and efficiency of healthcare delivery in smart home environments
Undergraduate Students’ Motivation in Chemistry Lessons
Get PDFChemistry is a core subject in most engineering degrees. The study of chemistry in particular, and of science in general, contributes to the integral development of individuals as it promotes the development of intellectual attitudes and habits such as argumentation, reasoning, and discussion, all of which are of great value to engineering students. Additionally, understanding the phenomena occurring in our environment helps in rational interpretation of reality and fosters critical attitudes toward everyday events. In this paper, we make an attempt to introduce different strategies that could increase students’ motivation to learn chemistry. Chemistry teachers often struggle to engage students, create stimulating learning environments, and manage classrooms effectively. Recently, there have been numerous attempts to motivate students by making chemistry more engaging through its application to everyday situations. The effectiveness of these endeavors depends on the connection between the phenomena under consideration, their scientific basis, and the students’ level of comprehension. To meet these expectations, it’s essential to cater to students’ interests according to their stage of cognitive development while still covering essential content and theories. The role of a number of motivational approaches, such as showcasing the relevance of chemistry in everyday situations, highlighting the challenges that society presents to this discipline in the immediate future, and aligning teaching methodologies with scientific strategies, are discussed as possible ways to stimulate students’ curiosity and improve their performance in the classroom
Assessing the Effectiveness of Personalized Adaptive Learning in Teaching Mathematics at the College Level
Get PDFPersonalized adaptive learning tailors’ education to each student’s unique needs by adjusting materials, tasks, and feedback based on their individual skill levels and progress. This paper details the development and implementation of a personalized adaptive learning platform designed to assess students’ mathematical abilities and offer customized exercises that align with their strengths and areas for improvement. A pilot study conducted with 118 students at Aktobe Higher Polytechnic College (Kazakhstan) demonstrated that this approach led to significant improvements in academic performance, engagement, and motivation compared to traditional teaching methods. By providing individualized learning paths and real-time feedback, the platform enhanced students’ problem-solving abilities and overall understanding of mathematics. This paper also explores the platform’s design, adaptive algorithms, and the measurable impact on student outcomes, highlighting the potential of personalized adaptive learning to transform educational practices and improve learning effectiveness in diverse academic environments
A Study of Xtremely Reconfigurable Drone
Get PDFAdvances in drone technology have significantly improved their applications, but traditional designs often limit their flexibility and efficiency in different operating conditions [5]. This paper presents the concept of the Xtreme reconfigurable drone, an innovative system that can dynamically change its layout in flight to adapt to different mission requirements. The drone features variable-pitch and adjustable-diameter propellers made of flexible materials controlled by a sophisticated layout control module [7]. The module uses real-time sensor data and machine-learning algorithms to maintain transition balance and stability [6]. Additionally, the chassis has a standard gearbox that allows torque and RPM adjustments, optimizing performance on demand [7]. Our approach incorporates origami-inspired folding techniques to minimize the number of required actuators, thereby improving the system’s efficiency [10]. Prototyping included computer-aided design (CAD) modeling, 3D printing, and integrating advanced materials and electronics. Extensive testing was conducted to evaluate the drone’s performance in various configurations and environmental conditions [3]. The results showed significantly improved flexibility, stability, and maneuverability compared to traditional drones [1], [4]. The Xtreme reconfigurable drone represents a significant advancement in drone technology, offering unprecedented adaptability for various applications. Future work will focus on refining control algorithms and exploring advanced materials to improve performance and durability [6]
Modeling Spatial-Temporal Social Interactions for Pedestrians Trajectory Prediction on Real and Synthetic Datasets
Get PDFHumans moving in crowded spaces adapt their pace or alter their initial path. A variety of sociocultural factors and personal preferences influence these interactions. With the development of autonomous moving platforms that need to share their physical environment with humans, this task has become increasingly valuable. In this paper, we present a way to conveniently evaluate the ability of a model to predict social interactions between pedestrians. In this manner, we conduct experiments on two prediction models: Social long short-term memory (LSTM) and Vanilla LSTM models. We use real datasets by generating synthetic datasets for which we can define the impact of social interactions on the motion of pedestrians. These hand-tailored datasets exclude individual interactions and focus on the interactions between individuals. By comparing the models’ performances on these datasets, we show that while the Social LSTM model can predict social interactions, the Vanilla LSTM model cannot. For our analysis, we introduce evaluation metrics that focus on the interactions between pedestrians, and these metrics go beyond the commonly used average and final displacement error for trajectory prediction. In particular, we analyze the prediction errors in regions of trajectories highly influenced by social interactions. Furthermore, we analyze the collision behavior of the model’s predictions and classify trajectories concerning their degree of non-linearity. This allows us to compare the models’ performances on motions differently influenced by social interactions
Optimising Interactive Cloud Gaming for Mobile Learning: GPU Virtualisation, Codec Efficiency, and UI Design
Get PDFMobile learning environments increasingly demand sophisticated interactive technologies capable of delivering engaging educational experiences while overcoming traditional hardware limitations. This integrative literature review examines cloud gaming infrastructure advancements for mobile learning. Results from both technical research and practical educational experiences are compared to understand how technology supports learning. Analysis reveals that hardware-assisted GPU virtualisation frameworks achieve substantial performance improvements on mobile devices, enabling sophisticated educational simulations. Video codec optimisations significantly reduce latency and bandwidth consumption, while touchscreen controls and haptic systems enhance learning effectiveness. Recognition of pedagogical innovations across different domains highlights their tremendous potential. STEM simulation platforms utilising molecular modelling and mathematical visualisation demonstrate significantly higher student engagement. Medical training applications enable learners. Collaborative learning environments facilitate enhanced problem-solving through shared virtual spaces, while language learning applications demonstrate superior vocabulary retention. The analysis establishes cloud gaming infrastructure as a transformative enabler for mobile learning, democratising access to sophisticated educational tools
AI-Powered and Mobile-Integrated Assessment Models Using Random Forest: Redefining Examinations and Grading
Get PDFThe proposed system applies a completely different method for examinations and grading by using the supervisor learning technique, namely Random type Forest algorithms. Leveraging the power of artificial intelligence (AI), the process of evaluation is becoming automatic, thereby increasing the efficiency and accuracy in the students’ grading? this breakthrough technique is characterized by its hybrid supervised learning setup that exploits both labeled and unlabeled data to come up with a model that is extremely adaptive to unseen examination data. This not only substantially reduces the necessity of human intervention but also dramatically improves the model’s ability to perform reliable predictions based on the prevalent patterns. This AI-driven assessment model can be further integrated into a mobile platform to enable real-time student engagement. The integration can benefit the students as the interactive mobile applications can enable the students to enhance their performance by providing instant outcome, and flexibility to take assessments. The mobile applications can contribute to skill enhancement by providing student assessment data related to quizzes, formative assessments or project-based learning assessments, for the random forest (RF) model. Interactive mobile applications can also assist faculty in tracking student performance and analyzing their progress along with improving the accessibility of data. The system, through a comprehensive evaluation of student responses, introduces a more customized and equitable grading system. That is, fundamentally, the traditional assessment methods are being reimagined, and at the same time, they ensure that educational environments globally are both scalable and fair
ChequeGuard: A Mobile-Enabled Blockchain Framework to Mitigate Fake Cheque Scams
Get PDFFake cheque scams remain a pressing financial concern, leading to substantial monetary losses and legal challenges. The absence of real-time authentication mechanisms often results in delayed scam detection by financial institutions. This report presents a mobilebased blockchain system using wireless communication and distributed ledger technology to authenticate cheques in real-time and prevent fraud. Our system integrates Namecoin, SHA-256 hashing, and elliptic curve digital signature algorithm (ECDSA) into a secure mobile computing environment to enable accessibility and scalability. The system has two significant operational phases: cheque issue and authentication. When issued, banks retain cheque information on the blockchain using Lagrange polynomials, and aggregation is achieved rapidly. Authentication at the point of withdrawal confirms the cheque as valid by verifying blockchain-stored data, preventing reuse and forgery. This framework helps achieve financial inclusion through the enabling of ubiquitous mobile access to secure cheque authentication services, resulting in cost-effective, real-world applications. By virtue of applying mobile technology infrastructures and safe wireless networks, the solution not only enhances transaction safety but also adheres to the changing trends in adaptive digital finance and industrial applications. Mobile apps facilitate users to scan and verify and get instant fraud alerts, highly promoting accessibility, especially for rural dwellers