Virtual Experiment Platform Research Articles

Exploration of the Teaching Reform of Computer Composition Principles with Ideological and Political Education at Anqing Normal University

The teaching mode of the Computer Composition Principles includes theoretical and practical teaching. At present, there is a problem of inconsistency in the teaching content of the two methods in our school. To this end, this paper conducts online and offline hybrid teaching based on the learning platform and the virtual simulation experiment platform, and cleverly applies ideological and political elements to theoretical and practical teaching to practice ideological and political education. Finally, the combination of theoretical and practical teaching modes can further help students firmly grasp the core knowledge points and improve the teaching quality and level of this course.

Construction of Virtual Experiment Teaching Platform based on 5E Teaching Mode and VI Technology

Virtual instruments have many advantages such as low cost, comprehensive functionality, easy scalability, and easy replication. At the same time, they can also meet the special requirements of time and space for remote experiments. Based on Web technology and virtual instrument technology, a virtual experiment system is constructed, which combines data sharing, remote control, and real-time operation. More conducive to utilizing experimental and scientific research resources. At the same time, virtual instruments have high flexibility and are no longer limited by traditional experimental teaching modes, which can save a lot of repeated investment costs. They can also keep the teaching equipment in the laboratory up-to-date and closely follow the development trend of science and technology. As a compulsory course for mechanical engineering majors, although the existing experimental system has achieved certain results, there are still limitations to 'Mechanical Engineering Testing Technology'. This article aims to address the problems of insufficient instrument sets and outdated equipment in the experimental teaching of "Mechanical Engineering Testing Technology", as well as students' poor ability to apply theory to practice and insufficient innovation ability. By integrating the 5E teaching mode, a virtual experimental teaching platform based on VI (Virtual Instrument) technology is established. Students can break through traditional experimental methods and conduct various experiments through the network, obtaining experimental experiences that are very similar to real experiments. At the same time, it can deepen their understanding and recognition of experiments, and better grasp theoretical knowledge.

Analysis of virtual simulation training teaching problems of intellectual property law based on real working situations

This article aims to take AI intelligent training software and real business drills of intellectual property as the training mode to carry out intellectual property-related training in fields such as data intellectual property creation, application, management, transformation, and education, and truly achieve the educational goal of integrating science, education and industry. First, innovate the intellectual property training platform. Through AI question-and-answer led by digital human images, introduce front-line practical experts in the field of intellectual property into the virtual simulation training teaching process, build a training scene for the entire chain protection of intellectual property and real working situations, and improve the practical effect of training and cultivating intellectual property talents. Second, deepen the social service system of intellectual property. Project team members guide students and trainees to actively participate in patent navigation, patent group projects, pilot projects, intellectual property protection projects, etc., exercise and promote the continuous improvement of the social service capabilities of various intellectual property talents. At the end of the article, it is proposed that while intellectual property law teaching adapts to the development needs of the digital age, it should take the construction and teaching application of a virtual simulation experiment platform in real work situations as the core, respond to the practical needs of social practice work, and improve students' ability to adapt to society. The organic integration of AI technology, digital human technology and practical training teaching of intellectual property law has certain reference significance for the realization of the metaverse vision.

A Virtual Reality Gearbox Experiment Platform Based on Hand Tracking and Natural Language Processing

In manufacturing engineering education, the gearbox is an essential mechanical component and a fundamental skill students must master. Recent data suggests that insufficient understanding of its load capacity and exceeding operational limits can damage internal components, potentially leading to severe consequences like fires. In order to address the challenges faced by physical laboratories and existing traditional virtual labs in the new engineering disciplines, including the lack of insufficient experimental safety, operational real-ism, insufficient personalized learning support, and the difficulty in creating immersive learning environments, we introduce a Virtual Reality Gearbox Experiment Platform Based on Hand Tracking and Natural Language Processing (VRGEPHTNLP). This platform aims to enhance the realism of detailed interactions, provide personalized learning experiences, and create immersive environments, thereby improving students' learning efficiency and practical skills. In order to enhance the teaching of gearboxes, we have developed the VRGEPHTNLP by integrating hand-tracking technology, the GPT3.5 large language model (GPT3.5 LLM), and Azure technology. This application allows for comprehensive observation and assembly-disassembly teaching functionalities of parts. We offer an interaction experience rich in detail and environmental immersion, alongside personalized feed-back and guidance in response to student inquiries. Compared to traditional computer-based virtual labs and conventional VR laboratories, our VRGEP-HTNLP exhibits significant advantages in improving user interaction realism, enhancing personalized learning support, and optimizing the immersion of the learning environment.

The Neurophysiological Costs of Learning in a Noisy Classroom: An Ecological Virtual Reality Study.

Many real-life situations can be extremely noisy, which makes it difficult to understand what people say. Here, we introduce a novel audiovisual virtual reality experimental platform to study the behavioral and neurophysiological consequences of background noise on processing continuous speech in highly realistic environments. We focus on a context where the ability to understand speech is particularly important: the classroom. Participants (n = 32) experienced sitting in a virtual reality classroom and were told to pay attention to a virtual teacher giving a lecture. Trials were either quiet or contained background construction noise, emitted from outside the classroom window. Two realistic types of noise were used: continuous drilling and intermittent air hammers. Alongside behavioral outcomes, we measured several neurophysiological metrics, including neural activity (EEG), eye-gaze and skin conductance (galvanic skin response). Our results confirm the detrimental effect of background noise. Construction noise, and particularly intermittent noise, was associated with reduced behavioral performance, reduced neural tracking of the teacher's speech and an increase in skin conductance, although it did not have a significant effect on alpha-band oscillations or eye-gaze patterns. These results demonstrate the neurophysiological costs of learning in noisy environments and emphasize the role of temporal dynamics in speech-in-noise perception. The finding that intermittent noise was more disruptive than continuous noise supports a "habituation" rather than "glimpsing" hypothesis of speech-in-noise processing. These results also underscore the importance of increasing the ecologically relevance of neuroscientific research and considering acoustic, temporal, and semantic features of realistic stimuli as well as the cognitive demands of real-life environments.

Investigating the impact of virtual simulation experiment and massive open online course (MOOC) on medical students’ wound debridement training: a quasi-experimental study

ObjectiveThis study aims to evaluate the impact of virtual simulation experiment teaching model and Massive Open Online Course (MOOC) teaching model on the teaching effect in debridement teaching.MethodsThe study adopted a quasi-experimental design and used virtual simulation technology to construct a virtual simulation experimental teaching platform for debridement. This study was conducted at the Second Clinical College of Wuhan University. The experimental group was composed of 135 third-year clinical medicine students in the 2020 grade, who received the virtual simulation experimental teaching model; the control group was 122 third-year students in the same major in the 2019 grade, who used the MOOC teaching model. The performance of the two groups of students was evaluated through theoretical tests and animal experiment operation. In addition, the effectiveness of the experimental teaching model and student satisfaction were evaluated through questionnaire surveys.ResultsThe theoretical test scores and animal experiment report scores of the experimental group were significantly higher than those of the control group, and the debridement animal experiment operation time of the experimental group was shorter than that of the control group, and the difference was statistically significant (P < 0.05). The post-class questionnaire survey of the experimental group showed that most students were satisfied with the virtual simulation experimental teaching model and believed that it represented the future teaching trend.ConclusionsIn the teaching of debridement, virtual simulation experiment is an effective t teaching model, which not only helps to improve student performance, but also significantly reduces skill operation time and is recognized by students.

Design of microcomputer principle virtual experiment teaching platform and study on teaching mode

In view of the characteristics of "Microcomputer Principle and Interface Technology" experiment course, such as complex abstraction, easy damage of experimental instruments and poor reuse, this paper proposes to use virtual simulation technology to digitize the microcomputer principle experiment circuit and experiment process, so that students can complete the relevant experiment content on the virtual experiment platform. The virtual experiment platform provides students with an efficient, flexible, open and free experiment environment, enhances students' interest in experiment, improves experiment efficiency and experiment quality, and is of great help to improving students' independent innovation practice ability.

Construction of Virtual Simulation Experiment Platform for Intelligent Construction Based on Statistical Machine Learning System Modelling

In the construction of a virtual simulation experiment platform for intelligent construction, cutting-edge technologies converge to revolutionize traditional project management methodologies. By harnessing the power of virtual reality, statistical modeling, and machine learning, this platform empowers stakeholders to predict, optimize, and simulate construction projects with unprecedented accuracy and efficiency. This paper introduces the Virtual Statistical Machine Learning (VS-ML) platform and demonstrates its application in intelligent construction processes. Through comprehensive experimentation and simulation, the VS-ML platform accurately estimates construction project parameters, optimizes resource utilization, schedules tasks efficiently, and classifies project outcomes with high accuracy. Numerical results from our study showcase the platform's effectiveness in various aspects of construction project management. For instance, in construction projects estimation, scenarios ranging from Scenario 1 to Scenario 10 exhibit project durations between 100 to 150 days, cost estimates ranging from $470,000 to $550,000, and safety ratings varying from "Good" to "Excellent". Furthermore, labor efficiency and material waste estimations across scenarios demonstrate percentages ranging from 85% to 93% and 3% to 7%, respectively, with corresponding safety ratings. Additionally, task computations elucidate the durations, start dates, end dates, and resource allocations for individual tasks within construction projects. Lastly, classification results exhibit the predicted probabilities and class labels for samples, showcasing the platform's ability to accurately predict project outcomes. Overall, the findings underscore the potential of VS-ML in revolutionizing traditional construction practices through data-driven approaches, leading to improved project management, cost savings, and enhanced safety standards in the construction industry.

Research on Range of Appropriate Spatial Scale of Underground Commercial Street Based on Psychological Perception Evaluation

Developing and utilizing underground space is a vital direction for urban growth. Underground commercial streets, as a significant component of underground space accommodating extensive human social activities, consequently necessitate the creation of human-scale spaces. In the evolution of urban design development towards more significant, more terrific refinement, applying architectural theories and excessively subjective designs has resulted in a deficient human-centered design and a disordered spatial environment. This study merges environmental psychology and architectural theory to determine the appropriate length of spatial scale. Two experiments focusing on spatial perception evaluation were conducted using a virtual experimental platform that featured varying dimensions of spatial scale combinations. These quantified combinations were correlated with the perception evaluation, and a regression analysis was employed to identify appropriate scale ranges, which were superimposed with the range of length selection. Finally, the optimal length and scale combination for underground commercial street spaces was established, providing a reference for the human-centered design of these environments.

Incorporating Symbolic Discrete Controller Synthesis into a Virtual Robot Experimental Platform: An Implementation with Collaborative Unmanned Aerial Vehicle Robots

We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through the reactive synchronous environment ReaX to generate controllers that fulfill specified objectives. These resulting controllers were subsequently deployed on the virtual robot experimental platform Simscape. To demonstrate and validate our approach, we provide an implementation example involving collaborative UAV robots.

Outcomes-based Teaching Reform of Introduction of Ships Based on Virtual Simulation Technology

The Introduction of Ships course is characterized by strong professionalism, perspective, and practicality, which is one of the core courses in the field of ship engineering. To solve the problem of poor teaching effect caused by the large amount of information and dispersion of the course, this paper proposes a reform plan for the education mode of Introduction of Ships based on the Outcomes-Based Education (OBE) concept and virtual simulation technology. Relying on the online virtual experiment platform, the course teaching resources are expanded and an integrated teaching model is constructed including pre-course, in-course, and post-course. The novel education mode is problem-oriented, closely integrates practical content with theoretical knowledge, and a customized teaching mode is realized through project-driven, case study, and comprehensive assessment and evaluation. A hybrid online and offline teaching channel is formed by synthesizing a variety of teaching strategies, so as to expand the flexibility of teaching activities. The proposed education mode can stimulate enthusiasm of students for active participation and independent learning, effectively achieve the student-centered teaching goal. Meanwhile, it has good expandability and can provide guidance and reference for the teaching of similar professional courses.

Design and Implementation of Web-based Database Virtual Experiment Platform

Against the backdrop of the COVID-19 pandemic, many courses face challenges in online teaching. Enhancing the teaching quality of online experimental sections in current higher vocational database courses is an urgent need. This paper constructs a lightweight web-based database virtual experiment platform. The results show that the platform can effectively solve the problems of difficult implementation and uncertain experimental effects in experimental sections under the blended learning mode of database courses, effectively ensuring the quality of online teaching for such courses.

Teaching Practice of PLC Programming in Elevator Virtual Simulation Experiment Platform

Virtual simulation technology is now becoming the main focus of the experimental practice teaching link. The article describes how to design the control program of the PLC control system of a single 6-floor elevator based on EETbasic elevator simulation experiment platform and combined with Botou V18 and S7-PLCSIM Advanced V5.0 software under Siemens and apply it to teaching practice. The article first introduces the structure of the elevator system and the characteristics of EETbasic software, as well as the control principle of the elevator control system. Secondly, the settings of the virtual simulation software, the configuration settings of the Boto, and the communication settings between the software are introduced. Then, the modular and structured programming method of a single elevator control program based on FB block is introduced. Finally, the teaching situation and teaching effect of this virtual simulation experimental platform applied for 4 years are introduced. It is finally concluded that this virtual simulation teaching, not only improves the setting of related courses but also has a great promotion effect on students' systematic mastery of theoretical knowledge and enhancement of innovation ability, which can achieve the purpose of improving the quality of teaching.

Design and Implementation of Workshop Virtual Simulation Experiment Platform Based on Digital Twin

In an era where countries worldwide are emphasizing the process of educational informatization, traditional experimental teaching methods encounter inherent limitations, such as constraints related to the availability of experimental sites and the amount of experimental equipment. Consequently, it becomes a challenge to provide students with an unconstrained, open, and collaborative experimental environment. The digital twin, as a pivotal technology for achieving interactive mapping of the physical world and the information world, possesses attributes characterized by real time interactivity and the seamless fusion of virtual and tangible elements. As a result, various virtual simulation experimental teaching platforms grounded in digital twin technology are now extensively integrated into talent development initiatives. In the context of the “Production Planning and Control” course at Harbin Institute of Technology (HIT), the virtual simulation experimental teaching method is examined, leading to the creation of a virtual simulation instructional platform that blends the virtual and tangible realms, thanks to the foundation of digital twin technology. The virtual simulation experimental teaching platform detailed in this paper, specifically designed for optimizing scheduling within assembly line workshops, represents a pioneering model practice in the integration of digital twin technology into workshop-based experimental instruction and assumes an influential role in enhancing students’ grasp of theoretical knowledge and their capacity for practical innovation.

The practice and prospect of algorithm-driven virtual simulation technology in medical undergraduate education

Abstract Amid growing interest in the use of virtual simulation platforms in educational settings, the reform of medical education increasingly looks to virtual simulation technology as a promising new avenue. This study aims first to analyze the components of a virtual simulation system and to enhance the functionality of virtual simulation technology by optimizing the network model algorithm. Utilizing cloud computing technology, a virtual simulation teaching experiment platform was constructed. Further, a virtual simulation medical education system based on the BOPPPS teaching model was developed to address the constraints of practical experience in the traditional undergraduate medical education model. Empirical analysis of the virtual simulation medical education mode reveals that the CPU utilization rate on the constructed cloud platform ranged from 2% to 35%, and the memory usage varied between 15 and 25 GB. In comparative assessments of medical education practices, this study found that students trained under the virtual simulation technology-enhanced model scored 0.96 to 1.53 points higher in various skill assessments than those trained under traditional methods. Moreover, the total scores for communication abilities increased by 5.48 points, highlighting a significant improvement. These results affirm the superiority of the virtual simulation technology medical education model presented in this study. They underscore its practicality and feasibility for application and development in undergraduate medical education, providing a substantive pathway for integrating advanced virtual simulation technologies into medical training.

Physics-informed machine learning enabled virtual experimentation for 3D printed thermoplastic.

The performance of 3D printed thermoplastics largely depends on the ink formulation, which is composed of tremendous chemical space as an increased number of monomers, making it very difficult to identify an optimum one with desired properties. To tackle this challenge, we demonstrate a virtual experimentation platform that is enabled by a physics-informed machine learning algorithm. As a case study, the algorithm was trained based on a multilayer perceptron (MLP) model to predict the experimental stress-strain curves of the 3D printed thermoplastics given the ink compositions made of six monomers. To solve the issue of experimental data scarcity, we first reduced the dimensions of the curves to eight principal components (PCs), which serve as the outputs of the model. In addition, we incorporated the physics-informed descriptors into the input dataset. These two strategies afford the model with a prediction accuracy of R2 of 0.97 and an RMSE value of 1.01 for fracture strength, and an R2 of 0.95 and a RMSE of 0.40 for toughness. To perform virtual experimentation, the well-trained model was then utilized to predict 100 000 sets of the PCs from the randomly given 100 000 ink formulations. The PC sets were then converted back to the corresponding stress-strain curves. To validate the prediction results, some of the virtual experiments were performed. The results showed a good match between the predicted and experimental curves. This methodology offers a general and efficient pathway to virtual experimentation for establishing the correlation between the complex input variables and the output performance metrics of new materials.

Retracted: The Construction of Virtual Experiment Platform Based on the Fuzzy System

Retracted: The Construction of Virtual Experiment Platform Based on the Fuzzy System

A Virtual System and Method for Autonomous Navigation Performance Testing of Unmanned Surface Vehicles

An overall framework of the virtual testing system has been established based on the analysis of the virtual testing requirements for autonomous navigation performance of unmanned surface vehicles (USVs). This system consists of several modules, including the environment module, motion module, sensor module, and 3D visualization module. Firstly, within the robot operating system (ROS) environment, a three-dimensional navigation environment was generated by combining actual wave spectra with Gerstner waves. By designing a power plugin for USV navigation, the system was made to reflects the coupled motion model of USVs in wind, waves and currents, along with predictive results. Regarding the four typical sensor information on USVs, the actual sensors were virtualized, and a simulation approach for virtual sensor information is provided. The three-dimensional visualization of USV’s motion enables the intuitive display and analysis of the virtual testing process. Based on the prediction of coupled motion characteristics in wind, waves and currents, the interaction between USVs and the virtual testing system has been realized. A platform for virtual testing experiments to determine the autonomous navigation performance of USVs was established, and the effectiveness of the platform was verified in terms of perception and environmental interference. In virtual environmental interference validation, the average amplitude deviation of the heave motion of USVs under sea state 3 reaches 0.74 m, and the average amplitude deviation of the pitch motion reaches 0.25 rad, showing the gradually increasing disturbance of the sea state. Finally, virtual testing experiments were conducted on a specific USV to evaluate its autonomous navigation perception performance, trajectory tracking performance, and autonomous obstacle avoidance. The evaluation results indicate that the platform can achieve the functionality of virtual testing for the autonomous navigation performance of USVs from the perspective of cost function, taking the reaction distance, regression distance, and obstacle avoidance time into consideration. A representative example is that the cost function deviation rates of overtaking obstacle avoidance between static and dynamic seas reach 5.11%, 8.98% and 18.43%, respectively. The gradually increasing data shows that the virtual simulating method matches the drifting-off-course tendency of boats in rough seas. This includes acquiring perception information of navigation and simulating the motion and navigation processes for visualization. The platform provides new means for testing and evaluating the autonomous navigation performance of USVs.

A Virtual Simulation Experimental Platform for Smart Home based on Unity3D

Smart home provides people with a more convenient and intelligent way of living and it is one of the most widely used application of Internet of Things (IoT). However, building a smart home laboratory for students to visit and learn is labor intensive and time consuming. In order to meet the demand of experimental teaching in higher education, this paper designed and developed a Virtual Simulation Experimental Platform (VSEP) for smart home. Firstly, we introduced goals, platform architecture and functional modules of the system. Then, the development process was discussed. Specifically, the model of smart home was quickly built in SketchUp and imported into Unity 3D project, and both the scene roaming and interactive functions were achieved by coding C# scripts. Finally, we described the key methods in details and accomplished the development work. The proposed platform provides an immersive virtual environment for students to learn concepts and principles of related theoretical knowledge, and offers a new method for experimental teaching.

Visual learning analysis of physical virtual simulation experiments based on heterogeneous data features

Abstract In order to provide a way to develop the teaching effectiveness of physics experiments, this paper optimizes the platform search engine by combining heterogeneous data features and representing document information as feature vectors based on visual learning analysis methods. The algorithm is dynamically adjusted according to the authority to build a network database. And the virtual physics experiments have interacted with virtual experimental equipment to build a physics virtual simulation experiment platform. The results show that the overall level of visual student portrait analysis is above 40%, and the average completion efficiency of visual evaluation tasks 1-9 is 87.9%, which helps the digital transformation and upgrading of experimental physics teaching and promotes the construction of high-quality virtual simulation experimental teaching system.