Virtual Simulation Environment Research Articles

A multi-feedback system integrated simulation-based teacher training to scaffold pre-service teachers’ teaching skills: A phenomenological approach

AbstractBefore taking full responsibility for a real classroom, pre-service teachers (PTs) can safely experience a rich learning atmosphere in a simulated virtual classroom environment and receive feedback on their lesson planning and teaching performance. This research aims to support and examine the process of structuring PTs’ teaching skills with a multi-source feedback system integrated with simulation-based teacher training (SimInTeach-FBS). A phenomenological approach was employed in order to understand the nature of PT’s experiences from a feedback system focusing on teaching skills. Seventy PTs, twelve mentor teachers (MTs), and six teacher educators (TEs) participated in the study. Various data collection tools were used to gain a deeper understanding of the participants' experiences: reflective journals, open-ended feedback forms, and observation notes. The results of the content analysis showed that teaching experience with SimInTeach-FBS raises self-awareness and improves PTs’ teaching skills. It was revealed that teaching skills were mutually structured, feedback given to the PTs multiplied the effect of the development process, and teaching experience facilitated the transfer of acquired teaching skills to real life.

The Idea of an Integration Interface for Model-based Software Development's Processor-in-the-Loop (PiL) Simulation

Model-based design (MBD) has become a cornerstone in the development of embedded software, particularly in the automotive industry. Processor-in-the- Loop (PiL) simulation bridges the gap between virtual simulation environments and real hardware, enabling early verification and validation of control algorithms running on target processors. The design and implementation of toolchain is required for target specific code generation, compilation, and execution. Developing a toolchain specifically for the target architecture is crucial to preventing errors and ensuring smooth production. The configuration and designing of toolchain are one time effort of all Simulink model which want to be test on board. This research investigates the importance of PiL for embedded systems in the automobile area. It describes the construction of a toolchain that integrates PiL simulation with Simulink, a popular MBD tool. The paper discusses the unique integration of TRACE32, a debugger and code analysis tool, with Simulink for testing programmes on Infineon devices. TPT makes use of graphical test models that are easy to understand and have the capacity to automate complex closed loop tests in real time. It was Daimler Software Technology Research that initially developed TPT. Nowadays, vendors and automakers employ it in their development projects for production vehicles.

A Multifaceted Approach for Enhancing Anomaly Detection in Industrial Systems with Adaptive Synthetic Sampling and Machine Learning Evaluation

Anomalies in industrial systems refer to deviations from expected behaviour, indicating potential malfunctions, faults, or security breaches. These anomalies can disrupt operations, compromise safety, and lead to costly downtime, making their detection and mitigation critical for industrial reliability and security. This research addresses the imperative task of enhancing anomaly detection within industrial systems by integrating a multifaceted approach encompassing various techniques and methodologies. A primary challenge in anomaly detection, the imbalanced distribution of data, is tackled by employing Adaptive Synthetic Sampling (ADASYN), which dynamically generates synthetic samples for minority classes. This effectively mitigates the impact of class imbalance and substantially enhances detection performance. Additionally, filter-based feature selection methods are utilized, incorporating statistical measures like the Chi-Square Test and ANOVA F-Value to identify pertinent features essential for anomaly detection. The study further delves into supervised anomaly detection approaches, leveraging machine learning algorithms such as Support Vector Machines (SVM) and Gradient Boosting (GB) to differentiate between normal and anomalous activities. These algorithms undergo rigorous evaluation within a Virtual Testing Environment (VTE) simulator, meticulously replicating industrial processes for comprehensive assessment. By leveraging the VTE simulator, this research ensures thorough evaluations across diverse operational scenarios, thereby fortifying anomaly detection systems and advancing the security of industrial systems. The research evaluates anomaly detection models for industrial systems using performance metrics like precision, recall, F1-score, and AUC-ROC. It compares Support Vector Machine (SVM) and Gradient Boosting (GB) models, finding GB outperforms SVM in discrimination ability. Both models show effective anomaly detection with minimal false positives and false negatives. A comparative analysis of key performance metrics aids in selecting the most suitable approach for enhancing system reliability and safety.

Innovative Metaheuristic Optimization Approach with a Bi-Triad for Rehabilitation Exoskeletons.

The present work proposes a comprehensive metaheuristic methodology for the development of a medical robot for the upper limb rehabilitation, which includes the topological optimization of the device, kinematic models (5 DOF), human-robot interface, control and experimental tests. This methodology applies two cutting-edge triads: (1) the three points of view in engineering design (client, designer and community) and (2) the triad formed by three pillars of Industry 4.0 (autonomous machines and systems, additive manufacturing and simulation of virtual environments). By applying the proposed procedure, a robotic mechanism was obtained with a reduction of more than 40% of its initial weight and a human-robot interface with three modes of operation and a biomechanically viable kinematic model for humans. The digital twin instance and its evaluation through therapeutic routines with and without disturbances was assessed; the average RMSEs obtained were 0.08 rad and 0.11 rad, respectively. The proposed methodology is applicable to any medical robot, providing a versatile and effective solution for optimizing the design and development of healthcare devices. It adopts an innovative and scalable approach to enhance their processes.

Research on Intelligent Control Model of Laboratory Safety Risks in Colleges and Universities Based on Digital Twins

This paper focuses on developing an intelligent management model for safety risks in university laboratories based on digital twin technology to improve safety management efficiency and accuracy. The virtual simulation environment of the laboratory is constructed by using digital twin technology, which is combined with the DEMATEL-ISM method for risk identification and analysis. Fault tree analysis (FTA) method was utilized to construct a laboratory safety accident fault tree to identify and assess potential risk factors. It was found that safety risks in laboratories can be effectively identified and controlled by digital twin technology. The risk assessment showed that unregulated drug storage, lack of monitoring and warning devices, insufficient safety awareness, inadequate systems and unreasonable layout of water, electricity and gas pipelines were the main risk factors. The empirical analysis of 11 university laboratories revealed that most of the laboratories were at a “relatively safe” level. The intelligent management model of safety risk in university laboratories based on digital twins can effectively identify and assess the safety risk, provide a scientific basis for the formulation of safety management measures, and thus improve the efficiency and accuracy of laboratory safety management.

A Conceptual Framework for Immersive Acoustic Auralisation: Investigating the Key Attributes

In architectural acoustics, the assessment of sound propagation in interior and/or environmental conditions has now become progressively more prominent throughout the past few decades, as a response to the development of advanced prediction tools. Within the adaptation of virtual reality (VR) systems, it is necessary to considerably expedite the prediction and simulation software as well as to enable flexible and responsive data analysis during simulation and 3D audio sensory projection. To generate ideal immersion in a simulated virtual environment, the generated stimulus across all senses should therefore be coherent. Accordingly, in the domain of acoustic in virtual reality, the system sound simulation must be constructed efficiently in order to convey the auditory stimuli to the user in an appropriate manner. This necessitates the implementation of virtual reality system as an advanced prediction tool that can accurately anticipate and replicate realistic audio experiences. Therefore, this study explores the realm of acoustic virtual reality (AVR) through a critical review with the purpose of elucidating design attributes and determining factors in generating immersive acoustic VR experiences. In light of these findings, the aim of this paper is to develop a comprehensive conceptual framework that will serve as a beneficial guide and road map for future researchers and developers in the field.

Creating a Framework for Virtual Reality Learning Environment (VRLE) for Studio-Based Learning

Higher education academics are lacking the knowledge on how to implement Design Thinking (DT) for transdisciplinary design studies that would produce Fourth Industrial Revolution Workforce Skills (4IRSkills), due to the sparsity in literature and implementation guidelines. This article discusses on the creation process of a Teaching and Learning Framework (TLF) for transdisciplinary design studies with a desktop-based Virtual Reality Learning Environment (VRLE) simulation of studio-based learning. The framework was created using a Selander’s Learning Design Sequence (LDS) with DT approach. The LDS helped the researcher to understand the processes of teaching and learning, especially on the affordances of various modes. The DT approach was used to facilitate the process of solving problems through the practice of empathy, reframing, prototyping, experimentation, testing, and redesign. A sequential explanatory mixed method was used, and the data were analyzed through inferential statistical analysis, thematic analysis and convergent coding matrix triangulation protocol. The findings indicated that the TLF with VRLE showed a positive and significant relationship with students' achievement of 4IRSkills. The TLF Design Process and Collaborative Design variables were positively correlated with students' 4IRSkills, while there was no correlation for the VRLE Representational Fidelity and Learner Interaction variables. In conclusion, the TLF with VRLE proves to be an effective and suitable method for guiding the implementation of pedagogies that teaches 4IRSkills at the tertiary level in fully online learning environments.

A Deep Reinforcement Learning Strategy for Surrounding Vehicles-Based Lane-Keeping Control.

As autonomous vehicles (AVs) are advancing to higher levels of autonomy and performance, the associated technologies are becoming increasingly diverse. Lane-keeping systems (LKS), corresponding to a key functionality of AVs, considerably enhance driver convenience. With drivers increasingly relying on autonomous driving technologies, the importance of safety features, such as fail-safe mechanisms in the event of sensor failures, has gained prominence. Therefore, this paper proposes a reinforcement learning (RL) control method for lane-keeping, which uses surrounding object information derived through LiDAR sensors instead of camera sensors for LKS. This approach uses surrounding vehicle and object information as observations for the RL framework to maintain the vehicle's current lane. The learning environment is established by integrating simulation tools, such as IPG CarMaker, which incorporates vehicle dynamics, and MATLAB Simulink for data analysis and RL model creation. To further validate the applicability of the LiDAR sensor data in real-world settings, Gaussian noise is introduced in the virtual simulation environment to mimic sensor noise in actual operational conditions.

The Use of Virtual Reality as an Aid Tool in the Implementation of a Radiopharmacy Center in a Nuclear Medicine Service

The preparations of radiopharmaceuticals must follow the parameters of quality, efficacy, and safety (pharmaceutical and nuclear), complying with all the requirements established in good manufacturing practices, guaranteed by the physical structure, layout, safety, and radiological protection, which are also fundamental for the correct flow to be followed for excellence in the functioning of the service. One of the main problems is related to the flow of radiopharmaceuticals, which implies exposure to ionizing radiation, which in turn poses serious biological risks to the human body. simple erythema (redness) to the acute radiation syndrome, which can even be lethal. Factors like this corroborate the need for training that simulate real situations, however, situations like this are limited, due to the risk to which a non-specialized professional can be exposed if radioprotection standards are not obeyed. The present work aims to propose and evaluate the use of virtual reality (VR) technology for training and qualification of professionals in a radiopharmacy. The applied methodology was divided into four stages, initially the rules and regulations regarding the Nuclear Medicine Service published by ANVISA, CNEN and international recommendations by the IAEA were analyzed in detail, in the second stage visits were carried out in public and private hospitals in the Rio de Janeiro that present the nuclear medicine service, in the third stage the virtual environment (simulator) was built, and the fourth stage proposed strategies to carry out training, considering a new technique for teaching. The use of virtual reality, through a simulator, allowed the creation of a graphical environment with a realistic appearance, in which the user can navigate in this environment and manipulate the virtual world. Therefore, it is expected that this tool can help in the planning and training of radiopharmacy professionals.

Breaking boundaries and opening borders by clicking into an inclusive virtual simulated learning environment

Breaking boundaries and opening borders by clicking into an inclusive virtual simulated learning environment

Does an outdoor virtual environment projected in a head-mounted display affect balance in healthy young adults?

BackgroundVirtual reality head-mounted display (VR-HMD) is increasingly used for balance evaluation and rehabilitation. However, more studies must be conducted on virtual environments (VE) effects. This study aimed to assess the impact of an outdoor VE projected in a high-quality VR-HMD and of the VR-HMD mass on postural stability, postural control and leaning. MethodsThis study involved ten healthy young men who performed five 30-s stabilometric trials. Four experimental conditions were randomly performed: eyes open (EO) or eyes closed (EC), with (VR) or without (No VR) VR-HMD. Postural stability (antero-posterior (AP) and medio-lateral (ML) ranges of the center of pressure (CoP), 90% confidence ellipse area), postural control (CoP velocity (global, AP and ML)) and standard deviation of the CoP mean position), and postural leaning (AP/ML CoP mean position) were assessed. The comparisons between EO VR and EO No VR were used to analyze the VE effects and comparisons between EC VR and EC No VR for the VR-HMD mass effects. ResultsSpatiotemporal parameters that characterised postural stability and postural control, except ML velocity (p > 0.05), were significantly influenced by the simulated VE with higher values in EO VR than EO No VR (p < 0.05), but not by the VR-HMD mass. The mean position of the CoP showed no significant differences between conditions. SignificancePostural stability and postural control modification due to the VE used in this study revealed that this VE could be interesting for VR-HMD rehabilitation and assessment. VR-HMD is not a factor to be considered for stabilometric analysis.

Design and performance analysis of braking system in an electric vehicle using adaptive neural networks

Research article emphasizes on the impact of braking concepts considering regenerative braking system and energy consumption aspects in electric vehicles through a new perspective. The electric vehicle system is modeled and simulated using the MATLAB/Simulink software. A dataset is developed using the virtual simulation environment created by co-simulation using the MATLAB/Simulink and the IPG Carmaker software. This dataset is also used in a neural network model based on adaptive neuro fuzzy logic and the system performance is analyzed. Parameters considered for training the neural network are the brake pedal displacement, braking change rate and the need for brake application. The highlight of this study is the focus on a front wheel driven electric vehicle, which uses a standard drive cycle input to validate the model. The significant parameters evaluated in this study include the braking effects, kinetic energy, regenerative braking torque, battery state of the charge and the motor torque. The torque generation and its intended braking force requirements based on the acceleration, deceleration and braking conditions are the notable observations. The regenerative capability of this proposed system design is also illustrated along with the surface plots based on the training dataset. Investigation and analysis reveal that, the battery state of charge could be revived throughout the drive with a steady and stable increase. Transitions of motor torques between tractive and regenerative phases are also illustrated and explained for clarity and brevity.

Creation of a virtual and interactive simulation environment in Excel for the study of Ohm's Law

The article highlights the growth of virtual laboratories as technological and pedagogical tools. It presents an example of a virtual laboratory in Excel® to assist in teaching and develop specific skills in users. The virtual laboratory of Ohm's Law includes multimeters, power supply, protoboard, and resistor for studying electrical measurements, resistance reading, ohmic behavior, and graphical analysis. It does not require an internet connection and does not use advanced programming languages, allowing the creation of customized virtual laboratories for various learning needs.

A Review of the Application of VR Technology in Medical Training

As one of the most fashionable technologies, VR(Virtual Reality) technology has the characteristics of high interaction and strong immersion, and has been widely used in medical training and has achieved remarkable results. The virtual simulation environment established by it helps teachers to show students the structure of the human body and organs more intuitively in the teaching process, and its simulation training system helps students practice relevant skills in the virtual environment. The development of future technology will surely solve the shortcomings of VR technology and make it better used in medical training.

Virtual Multi-Criterial Calibration of Operating Strategies for Hybrid-Electric Powertrains

In hybrid vehicle development, the operating strategy has a decisive role in meeting the development goals, such as compliance with emission standards and high energy efficiency. A considerable number of interactions and cross-influences on other topics, such as emissions, on-board diagnostics, or drivability, must be considered during the calibration process. In this context, the given time constraints pose further challenges. To overcome these, approaches for virtualization of the calibration process are an effective measure. For this purpose, in the current study, a real engine control unit is embedded into a virtual simulation environment on so-called hardware-in-the-loop (HiL) testbenches, which allow virtual calibration and validation of the complete target vehicle. In this context, the paper presents a novel method for virtual calibration of operating strategies for hybrid-electric propulsion systems. This includes an innovative multi-criterial approach that considers the requirements of several development tasks, such as emission and OBD calibration. Measurement data for this optimization is generated on a HiL testbench setup tailored for the described methodology, including both the electrical setup and the simulation environment. To validate the selection of modeling approaches and the parametrization, the simulation environment is operated in open loop. The results of the open loop validation show promising behavior regarding the proposed use case. Finally, the presented methodology is evaluated regarding time and cost savings compared to a conventional approach.

Obstacle avoidance USV in multi-static obstacle environments based on a deep reinforcement learning approach

Unmanned surface vehicles (USVs) are intelligent platforms for unmanned surface navigation based on artificial intelligence, motion control, environmental awareness, and other professional technologies. Obstacle avoidance is an important part of its autonomous navigation. Although the USV works in the water environment (e.g. monitoring and tracking, search and rescue scenarios), the dynamic and complex operating environment makes the traditional methods not suitable for solving the obstacle avoidance problem of the USV. In this paper, to address the issue of poor convergence of the Twin Delayed Deep Deterministic policy gradient (TD3) algorithm of Deep Reinforcement Learning (DRL) in an unstructured environment and wave current interference, random walk policy is proposed to deposit the pre-exploration policy of the algorithm into the experience pool to accelerate the convergence of the algorithm and thus achieve USV obstacle avoidance, which can achieve collision-free navigation from any start point to a given end point in a dynamic and complex environment without offline trajectory and track point generation. We design a pre-exploration policy for the environment and a virtual simulation environment for training and testing the algorithm and give the reward function and training method. The simulation results show that our proposed algorithm is more manageable to converge than the original algorithm and can perform better in complex environments in terms of obstacle avoidance behavior, reflecting the algorithm’s feasibility and effectiveness.

Evaluating cable tension distributions of CDPR for virtual reality motion simulator

This paper presents a study on modeling, analysis, and control of an over-constrained Cable-Driven Parallel Robot taking into account the deformation of the cable transmission system due to the elastic model of the transmission mechanism and the affection of tension distribution for cables. The Cable-Driven Parallel Robot is used for a virtual reality motion simulation system with a simulation cabin mounted on a moving platform. A nonlinear cable length controller with tension feedback is designed to control the cabin to move along a trajectory extracted from the virtual simulated environment. The tension distribution algorithm is integrated into the controller to compensate for the dynamic error caused by the two redundant cables and the elastic characteristic of the transmission mechanism. The tensions are calculated based on the constraints of the workspace, the structure of the system, and the force limits of actuators. The cable tension feedback control algorithm was tested on the concept Cable-Driven Parallel Robot, the experimental results show that the joint trajectories meet the desired moving trajectory with high accuracy, and the cable tensions are controlled in the optimal region to ensure safety and save energy, but still suitable for the control requirements of the virtual reality motion simulator system.

Physical risk assessment of drone integration in construction using 4D simulation

Drones are increasingly being used in construction for various applications. However, this integration has increased interactions between drones and workers, posing significant safety challenges for workers. This paper assessed the physical risks of drones on construction sites using VR-based 4D simulations. Roofs, ladders, and scaffolds were identified as the top high-risk environments where workers were at an increased risk of accidents when working around drones. A system-level virtual simulation environment was developed to run 2700 simulations per scenario with varying parameters, mimicking and visualizing potential interactions between workers, structures, equipment, and drones flying at different distances of workers: Near-Drone (<4 ft) and Distant-Drone (>4 ft). The results suggest that the Distant-Drone had a higher frequency of collision incidents with equipment and the ground, while the Near-Drone had a higher frequency of collision incidents with buildings and workers. This differential impact of flight parameters and interaction distance on drone collisions implied the need for targeted safety strategies for different working contexts.

A New Framework for Gaining Emotional Health Knowledge Through Virtual Reality-IoT Technology

This work presents a new framework for studying the emotional and physical conditions of workers in Virtual Reality (VR) environments. The framework collects data from simulated virtual environments and helps develop adaptable models for different contexts. It introduces an architecture based on immersion in virtual reality (IVR), focusing on sensory perception, natural actions, narrative engagement, and social features. The author proposes categories to assess the impact of each concept on IVR applications, supported by an artificial intelligence module for data analysis and feedback. The framework also enables the collection of physiological parameters using VR glasses with storage and processing capacity. This facilitates control, performance, and integration with IoT contexts. The primary objective is to identify behavioral patterns for decision-making and employee emotional health management.

Virtual Simulation Education Using Multiuser Virtual Environments and Standardized Patients for Child Healthcare in the Community Setting: A Multisite Pilot Study

BackgroundTo improve child health promotion in the community, pediatric nursing education should provide appropriate learning environments and resources. MethodsA multisite, pretest-posttest design with a mixed-methods approach was used to evaluate the effects of simulation in a multiuser virtual environment. ResultsNursing competencies scores significantly increased. The major themes of participants’ experience were identified: Performing and thinking like a nurse, Experiencing realistic nursing encounters, Interesting learning experiences, Helpful learning processes, and Difficulties and adaptation. ConclusionsVirtual simulations using multiuser virtual environments and standardized patients can effectively prepare nursing students for primary healthcare and children's health promotion in the community.