Virtual Environment Model Research Articles

The Role of Curiosity in Virtual Environments: A Conceptual Integration.

Brands need to have a digital strategy. Yet, it is difficult to grab consumers' attention in virtual environments. We present the Curiosity in Virtual Environment (CVE) model, which integrates empirical and conceptual work on virtual environments, goal content, and curiosity. The model seeks to serve as a guiding framework and tool for research scholars and practitioners working in virtual environments who want to communicate with consumers. To elaborate and present the CVE, we first discuss the main characteristics of virtual environments and types of goal contents, followed by a brief introduction to the theoretical developments of curiosity. The model is then introduced, showing four quadrants in which practitioners should have an easier (more difficult) time grabbing consumers' attention. We then conduct a selective review of experimental studies on curiosity and consumption, identifying three voids in the field. We finish the article by suggesting directions for future research and acknowledging the limitations of the CVE model.

Remotely controlled reality in the “Robotics Fundamentals” course for students of the “Information Systems and Technologies” speciality

Abstract This paper presents the distance learning technology in the “Robotics Fundamentals” course for students of the “Information Systems and Technologies” speciality. The purpose of the educational process in this course is to form students’ understanding a robotics unit and its software as an information system. We need to stress the students’ attention on importance of feedback in such complex systems. The main idea of our approach is to show the students the real production process of robotics system creation as a sequence of steps from modelling and simulation in virtual environment to testing it the in the appropriate real environment. Choice of the software and hardware for supporting the distance learning process is discussed. We suggest some technical decisions according to the remote laboratory and students’ remote communications with the robotics system. Results of conducted surveys are analysed to evaluate the efficiency of study process in the course as well to distinguish tasks for future development od our learning technology.

Construction of user experience model iniImmersive virtual environment based on ontology

With the rapid development of virtual immersion technology, immersive virtual environment (IVE) has shown its unique application potential in many fields. The purpose of this study is to explore and construct a user experience model in immersive virtual environment based on ontological theory. The key factors affecting user experience include sensory experience, interaction control, distraction factors, realism perception, ownership, motion control and location. Environmental dimension and physical dimension are the two core aspects of user experience. Sensory experience and sense of ownership have a significant positive impact on users' sense of existence in a specific environment, while control dimension, sensory dimension and realism dimension play an important role in enhancing users' sense of ontology. The different dimensions of the sense of ontology have a significant positive impact on the user's sense of immersion and presence, which verifies the central role of the sense of ontology in enhancing the user's immersion experience. We look forward to further enhancing the user's immersion experience and promoting the application of immersive virtual environment in a wider range of fields

ПІДГОТОВКА МАЙБУТНІХ ОФІЦЕРІВ РОЗВІДНИКІВ ДО ПРОФЕСІЙНОЇ ДІЯЛЬНОСТІ В УМОВАХ ЗМІШАНОГО НАВЧАННЯ ЗАСОБАМИ ІНФОРМАЦІЙНО-ОСВІТНЬОГО СЕРЕДОВИЩА

The article analyzes scientific works, the regulatory and legal framework and the content of educational and methodological documentation regarding the organization of professional training of future intelligence officers. Modern approaches related to distance learning and digitalization of professional training of future specialists of the national security and defense sector of Ukraine, as well as the European Union, have been identified. The results of previous studies have been summarized. It has been established that the professional training of future intelligence officers in the conditions of pandemics and full-scale war can be carried out in the format of blended learning using the means of a specially created informational and educational environment. It is substantiated that blended learning of future military intelligence officers consists of the educational activity in two forms: in form of training sessions in specialized classrooms under the direct supervision of the scientific and pedagogical workers and in form of independent work with electronic resources of a specially created information and educational environment. Varieties of blended learning models in the conditions of pandemic and full-scale war are distinguished, namely "rotational model", "flexible model", "person-oriented model" and "enriched virtual environment model". Pedagogical components of information and educational environment tools for blended learning of future intelligence officers have been developed, which include: independent study of new educational material, independent study of material using elements of creativity, independent improvement of theoretical knowledge and practical skills in conditions of quasi-professional activity, and independent in-depth study of material. The introduction of innovative forms, methods and means of obtaining intelligence information into the professional training of future intelligence officers in the format of blended learning by means of the information and educational environment is proposed. The experience of conducting military intelligence acquired by the intelligence units of the armies of NATO member countries and the Armed Forces of Ukraine during the de-occupation of the territories of sovereign Ukraine captured by Russian-terrorist forces is considered as part of the blended learning. Standards of individual and collective training of future intelligence officers of the Armed Forces of Ukraine and NATO are applied. Key words: future intelligence officers, blended learning, blended learning models, information and educational environment tools, pedagogical components of information and educational environment tools.

SmAuto: A domain-specific-language for application development in smart environments

A common problem in the development of Internet-of-Things (IoT) and Cyber-Physical System (CPS) applications is the complexity of these domains, due to their hybrid and distributed nature in multiple layers (hardware, network, communication, application etc.). Apart from other issues, this inherent complexity often gives room for implementation errors, which can be in many cases fatal and drive the application and/or the system to undesired states. The current work aspires to alleviate this problem by introducing a low-code approach for building IoT and CPS applications. We argue that, through the proposed approach it is possible to lower development time and risk (errors/bug-related ones) and allow a wide range of end-users to build and monitor applications for state-of-the-art domains, such as smart home and smart industry. In this context, Model-Driven Engineering (MDE) approaches are explored and SmAuto, a Domain-specific Language (DSL) is proposed for creating and executing automation tasks for smart environments. Through SmAuto it is possible to handle the heterogeneity and complexity issues of the IoT and CPS domains, this way allowing end-users are non-technical application experts to build well-designed and properly functioning smart applications. The proposed DSL implements a Sense-Think-Act-Communicate model for smart environments and enables the creation, validation, and dynamic execution of composite automation models in physical, virtual and hybrid environments, while it also enables automated code generation of virtual entities for verification purposes. By using layered abstractions to automate the development process, end-users can concentrate on the real problem instead of dwelling into technical details, thus increasing their productivity. The results of the empirical evaluation and the comparison to existing approaches show that SmAuto can make application development more rigorous, improves productivity of end-users including non-experts, i.e. citizen developers and satisfies several functional and non-functional requirements of modern DSLs, such as tool support, modular deployment, reusability, availability and extensibility.

Optimization Algorithm for Multimedia Interaction of Computer-Aided Design Models in Virtual Reality Environments

Optimization Algorithm for Multimedia Interaction of Computer-Aided Design Models in Virtual Reality Environments

Variable Time-Step Physics Engine with Continuous Compliance Contact Model for Optimal Robotic Grinding Trajectory Planning.

In the transition from virtual environments to real-world applications, the role of physics engines is crucial for accurately emulating and representing systems. To address the prevalent issue of inaccurate simulations, this paper introduces a novel physics engine uniquely designed with a compliant contact model designed for robotic grinding. It features continuous and variable time-step simulations, emphasizing accurate contact force calculations during object collision. Firstly, the engine derives dynamic equations considering spring stiffness, damping coefficients, coefficients of restitution, and external forces. This facilitates the effective determination of dynamic parameters such as contact force, acceleration, velocity, and position throughout penetration processes continuously. Secondly, the approach utilizes effective inertia in developing the contact model, which is designed for multi-jointed robots through pose transformation. The proposed physics engine effectively captures energy conversion in scenarios with convex contact surface shapes through the application of spring dampers during collisions. Finally, the reliability of the contact solver in the simulation was verified through bouncing ball experiments and robotic grinding experiments under different coefficients of restitution. These experiments effectively recorded the continuous variations in parameters, such as contact force, verifying the integral stability of the system. In summary, this article advances physics engine technology beyond current geometrically constrained contact solutions, enhancing the accuracy of simulations and modeling in virtual environments. This is particularly significant in scenarios wherein there are constant changes in the outside world, such as robotic grinding tasks.

An Interactive Digital-Twin Model for Virtual Reality Environments to Train in the Use of a Sensorized Upper-Limb Prosthesis

In recent years, the boost in the development of hardware and software resources for building virtual reality environments has fuelled the development of tools to support training in different disciplines. The purpose of this work is to discuss a complete methodology and the supporting algorithms to develop a virtual reality environment to train the use of a sensorized upper-limb prosthesis targeted at amputees. The environment is based on the definition of a digital twin of a virtual prosthesis, able to communicate with the sensors worn by the user and reproduce its dynamic behaviour and the interaction with virtual objects. Several training tasks are developed according to standards, including the Southampton Hand Assessment Procedure, and the usability of the entire system is evaluated, too.

Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning

Cyber-Physical Systems (CPS) continuously interact with their physical environments through embedded software controllers that observe the environments and determine actions. Field Operational Tests (FOT) are essential to verify to what extent the CPS under analysis can achieve certain CPS goals, such as satisfying the safety and performance requirements, while interacting with the real operational environment. However, performing many FOTs to obtain statistically significant verification results is challenging due to its high cost and risk in practice. Simulation-based verification can be an alternative to address the challenge, but it still requires an accurate virtual environment model that can replace the real environment interacting with the CPS in a closed loop. In this article, we propose ENVI (ENVironment Imitation), a novel approach to automatically generate an accurate virtual environment model, enabling efficient and accurate simulation-based CPS goal verification in practice.To do this, we first formally define the problem of the virtual environment model generation and solve it by leveraging Imitation Learning (IL), which has been actively studied in machine learning to learn complex behaviors from expert demonstrations. The key idea behind the model generation is to leverage IL for training a model that imitates the interactions between the CPS controller and its real environment as recorded in (possibly very small) FOT logs. We then statistically verify the goal achievement of the CPS by simulating it with the generated model. We empirically evaluate ENVI by applying it to the verification of two popular autonomous driving assistant systems. The results show that ENVI can reduce the cost of CPS goal verification while maintaining its accuracy by generating accurate environment models from only a few FOT logs. The use of IL in virtual environment model generation opens new research directions, further discussed at the end of the article.

Rural Environmental Landscape Construction Based on Virtual Reality Technology

With the recent shift in public aesthetics, tourism agriculture, which combines tourism with modern agriculture, has become a new and popular form of tourism, exhibiting great potential. Internationally, tourism is known as a sunrise industry that will never decline because the benefits and impact introduced by tourism are not only limited to the industry itself but also the development of other fields. It stimulates the labor force by creating job vacancies, consumption, economic benefits, and opportunities for the surrounding areas. Therefore, paying attention to the development of tourism and focusing on the trending frontier issues of the industry are of practical value to the development of social economy and culture. Traditional forms of tourism develop economic value by focusing on people’s direct experiences at specific times and places. However, this approach is somewhat limited by time and space constraints, preventing the full exploitation of the economic and cultural value of tourism landscapes. In contrast, modern rural tourism models based on virtual environment modeling and virtual reality technology can address this issue, enhancing the development of rural tourism industries. Virtual environment modeling designs specific spatial environments and simulates internal elements, providing authenticity to environments and a sense of reality using textures. Virtual reality technology goes further in creating highly realistic virtual environments that are generated by computers, encompassing visual, auditory, linguistic, force, tactile, motion, and olfactory elements, and enabling natural interactions between various sensory devices of the operator and the landscape model. The combination of these two approaches offers a broader scope and more nuanced physical and mental experiences for the rural tourism industry. This paper explores the optimization role of virtual environment and environmental landscape modeling based on virtual reality technology in designing rural tourism landscapes. It examines the specific elements of optimization within this type of technology and, using algorithms, demonstrates that these methods provide a 15.73% optimization rate in the sightseeing process compared to traditional tourism models, making them widely applicable in the design of rural tourism landscape environments.

Branching the limits: Robust 3D tree reconstruction from incomplete laser point clouds

Accurate individual tree reconstruction based on laser point clouds is vital for precise biomass estimation, virtual geographic environment modeling, and simulation. However, mobile laser 3D scanning systems often capture tree point clouds obscured by leaves, resulting in missing or incomplete branch data, posing significant challenges to detailed tree reconstruction. In this paper, a novel method for fine-grained 3D tree model reconstruction from incomplete point clouds is proposed. This approach addresses the structural reconstruction of trees, tackling two main problems: reconstructing the main trunk and branches based on data completeness. Initially, a 3D morphological algorithm is employed to separate the main trunk and branches in the point cloud. Next, branch point clouds are node-aggregated using clustering, and the trunk’s skeleton point is computed using a multi-scale curve fitting method. To account for incomplete branch point clouds, the Alpha shape is calculated and used as a constraint for the growth model of the L-system, enabling the automatic generation of branch structures. Finally, a morphologically constrained multi-level trunk fusion method is utilized to achieve complete tree model reconstruction. To validate the effectiveness of this method, five trees with varying structures and levels of complexity were selected for structural reconstruction and compared with state-of-the-art (SOTA) methods. Experimental results evince that the method delineated in this study exhibits an aptitude for adeptly approximating tree nodes, even in scenarios characterized by incomplete point cloud data. This approach transcends the reconstruction accuracy manifested by SOTA algorithms specific to three-dimensional tree modeling, simultaneously demonstrating a pronounced resilience to noise and enhanced robustness.

Study on vibration characteristics of structural components based on virtual reality technology

In order to more effectively and intuitively obtain the modal characteristics of steel structural components, a graphical analysis scheme is proposed based on dynamic testing, finite element simulation, and virtual reality technology. Based on the external excitation method, the vibration sensors and measurement point positions were reasonably arranged according to the number of nodes in the structural components. Through the data processing of the detection unit, the vibration response can be effectively obtained and provide a verification basis for the simulation results. The finite element software Midas Civil was used to model and analyze structural component models, and the results of the first five modes and natural frequencies were obtained. The structural data of modal analysis will be compared and integrated into the virtual environment model through VRML. Due to the ease of modifying the parameters of the virtual model, compared to traditional methods, it is faster and more accurate in detection and scientifically reasonable in control.

Temporal graph attention network for building thermal load prediction

Machine learning models have seen widespread application in predicting building thermal loads. Yet, these existing models generally predict the thermal load for a single thermal zone or an entire building, overlooking buildings with multiple thermal zones. Moreover, interactions between thermal zones are seldom accounted for these methods. Addressing this gap, our study introduces a graph-based approach that employs a Temporal Graph Attention Network (TGAT) model for building thermal load prediction. This model accommodates both the spatial and temporal dependence across different thermal zones. Specifically, the TGAT model initially utilizes graph attention neural networks (GATs) to identify the spatial relationships between thermal zones. The spatial representation thus obtained is subsequently processed via Gated Recurrent Units (GRUs) to ascertain temporal dependencies. Lastly, a fully connected layer is engaged to decode the representation for the final output. Our model incorporates 11 features as inputs to depict the characteristics of outdoor environment and thermal zones. Testing the proposed TGAT model in a small office virtual environment for heating load prediction revealed that a configuration of four GAT attention heads achieved optimal result for predicting the ensuing hour’s heating load with a six-hour lookback. Additionally, we scrutinized and discussed the efficacy of feature selection and the GAT module. This research thus establishes a novel groundwork for forthcoming studies on zone-based building energy management optimization.

A large-scale neurocomputational model of spatial cognition integrating memory with vision

We introduce a large-scale neurocomputational model of spatial cognition called ’Spacecog’, which integrates recent findings from mechanistic models of visual and spatial perception. As a high-level cognitive ability, spatial cognition requires the processing of behaviourally relevant features in complex environments and, importantly, the updating of this information during processes of eye and body movement. The Spacecog model achieves this by interfacing spatial memory and imagery with mechanisms of object localisation, saccade execution, and attention through coordinate transformations in parietal areas of the brain. We evaluate the model in a realistic virtual environment where our neurocognitive model steers an agent to perform complex visuospatial tasks. Our modelling approach opens up new possibilities in the assessment of neuropsychological data and human spatial cognition.

Advancing Forest Monitoring and Assessment Through Immersive Virtual Reality

Abstract. The recent influx of remote and proximal sensing data provides new opportunities to understand environmental processes. A potential application of these datasets is to facilitate forestry operations. However, forest management decision-making through sensing techniques faces many challenges, partly due to the involvement of stakeholders with different knowledge levels and objectives. We present a virtual reality application developed for forest monitoring and assessment to address some of these challenges. First, a workflow for visualizing different sources of environmental sensing data is introduced to reconstruct digitally forest and terrain characteristics. Then, the VR experience is introduced in which users can observe, manipulate, and measure LiDAR-derived forest and tree models in immersive virtual environments. Finally, a heuristic expert evaluation to assess the overall user experience and the usability of individual application features is reported. We also gathered open-ended responses from domain experts to reflect on the potential and actual uses of the application in forest-related practices.

A multi-agent framework for collaborative geometric modeling in virtual environments

The use of collaborative applications in which several individuals interact to solve a problem is an important strategy both in educational settings as well as professional environments. Virtual Reality (VR) technology, in particular, has acquired a predominant role in many industries. However, as the level of immersion and realism of the VR experience increases, so does the demand for computational resources, as rendering processes become increasingly intensive and can negatively affect other communication processes that are critical in collaborative environments. In this paper, we present a software framework based on multi-agent systems that enables the separation of rendering processes from internal data management tasks and communication processes between users, which are prevalent in collaborative virtual reality applications. The results of our validation studies show that, compared to other techniques based on protocol or network enhancements, the proposed architecture can significantly improve collaborative processes in general, and virtual reality-based applications in particular.

The Virtual Learning Environment Model on Cloud using Hybrid Learning

The objectives of this research are (1) to study and synthesise the conceptual framework of the virtual learning environment model on cloud using hybrid learning, (2) to develop the virtual learning environment model on cloud using hybrid learning, and (3) to study the results after using the virtual learning environment model on cloud using hybrid learning. The participants in this research include 10 experts from various institutions, all of whom are specialised in design and development of instruction models and instruction systems. The research tools herein consist of (1) the virtual learning environment model on cloud using hybrid learning, and (2) the evaluation form on the suitability of the virtual learning environment model on cloud using hybrid. According to the results of this research, it is found that (1) the overall suitability of the development of the virtual learning environment model on cloud using hybrid learning (overall elements) is at the highest level (Mean = 4.62, SD. = 0.49), and (2) the overall suitability of the development of the virtual learning environment model on cloud using hybrid learning is at the highest level (Mean = 4.66, SD. = 0.48).

Didactic Principles of Modeling Virtual Learning Environments: the Analysis of Theoretical and Empirical Value

The article aims to analyze a range of didactic principles that have to be included in methodological substantiation when creating a model of Virtual Learning Environment (VLE) or other models of distance learning. To systematize and range the didactic principles in order of their pedagogical importance, several quantitative and qualitative research methods were used, including content analysis, questionary-based survey, and statistical data processing. The main aim of the study was to compare the didactic principles’ theoretical impact, which is based on the content analysis results, and their empirical value, indicated by students’ responses to the survey. The initial findings indicate the substantial difference between the didactic principles that are most frequently referenced in theoretical studies and the principles that are practically required to address students’ needs. The main outcome of the research is the assignment of the didactic principles into three categories: those having low theoretical and empirical value; those having low theoretical but high empirical value; and those having both high theoretical and empirical value. As such, the results of the study allow for the development of VLEs in various disciplines using relevant didactic principles that have both theoretical and empirical value.

Correction to: Modeling and simulation of virtual learning environment for automatic control principle

Correction to: Modeling and simulation of virtual learning environment for automatic control principle

The Effect of Complexity of Ambulance Missions on Shared Mental Models in Virtual Teams

Background Empirical research on shared mental models (SMM) in virtual environments are almost non-existent. Pre-hospital emergencies presents an opportunity to examine team processes in virtual teams because the dispatcher is geographically separated from the ambulance and at the same time plays a significant role in coordinating, organizing, obtaining, evaluating, and conveying relevant information to the deployed ambulance. The present study aimed at mapping team behavior and cognition in critical real-life emergency medical missions based on the concept of SMM. Methods By investigating the frequencies of coordinating mechanisms and team competencies based on voice recordings from real-life missions, differences in team behavior between low and high-complexity missions were investigated. Results Lower frequencies of team competencies and coordinating mechanisms were found in high compared to low-complexity missions. The results showed a different profile in communication between high and low-complexity missions with more frequent use of both coordinating mechanisms and team competencies in low-complexity missions. Furthermore, the profiles revealed that SMM and closed loop communication were the only coordinating mechanism used, and leadership and team orientation were the only competencies exercised. Conclusion It was concluded that the lack of visual input of a team member during team interaction could lead to team process loss due to a breakdown of the team into sub-units. Potential improvement of team behavior is discussed within the SMM framework.