Virtual Approach Research Articles

Modern Data Storage Technologies in the Context of Industry 4.0

Existing and currently widely used data storage technologies are considered. It is noted that the growth in the volume of digital information resources at an astronomical pace has led to the rapid development of technologies for their creation, storage, and access to them. In the context of Industry 4.0, the use of digital technologies to create intelligent and interconnected production and data processing processes is of particular importance. Blockchain technology and cloud technologies have become integral components of modern digital transformation. Taking into account the current state of data storage and blockchain technologies, network capabilities, enterprise needs and other factors, the possibilities of selecting and using storage tools and technologies, principles of joint implementation and application of different technologies, as well as modern virtualization approaches and blockchain technology for solving distributed data storage issues have been explored.

A Virtual Reality Approach to Overcome Glossophobia among University Students

In the contemporary academic landscape, university students frequently deliver presentations in front of their peers and faculty, often leading to heightened levels of Public Speaking Anxiety (PSA). This study explores the potential of Virtual Reality Exposure Therapy (VRET) to alleviate PSA among students. Our study introduces "Manch," a realistic VR environment that simulates classroom public speaking scenarios with lifelike audience interactions and a slide-deck presentation feature. The study was conducted with N=28 participants, showing a significant reduction in PSA levels post-VR exposure, thereby establishing VR's efficacy in mitigating PSA. Additionally, we also incorporated a unique qualitative analysis through participant interviews, offering deeper insights into individual experiences with VRET. Manch shows great promise as a tool for future studies and interventions aimed at reducing PSA, particularly among university students.

Intercultural communication, faith and impression management: former Muslims’ engagement with social media

ABSTRACT This study adopts a virtual ethnographic approach to delve into the intercultural communication of eight purposively selected Malaysian former Muslims through social media. It focuses on postings that contest Islamic beliefs while excluding general criticisms of Islam. Data generated, through an extended observation of participants' Facebook and Twitter accounts, were analysed using discourse analysis, focusing on impression management strategies. The findings unveiled the former Muslims' recurrent engagement in and interplay of self-promotion, ingratiation, supplication, and exemplification which elucidated their adept utilisation of IM strategies, particularly humanisation and rationalisation, in shaping their image as advocates of humanity and rational thinking.

Perception of Dentistry Students Regarding Virtual Classes During the COVID-19 Pandemic

The COVID-19 pandemic implied changes and challenges in university education around the world. In the area of ​​dental education, the virtual approach or virtual teaching was a challenge for both students and teachers. Although digital platforms, conferences and virtual courses have already been used in Dentistry as a complementary resource, the pandemic meant a completely virtual modality. However, teaching in virtuality is complex since the didactic and pedagogical processes are related to areas or specialties linked to the clinical part of this profession, where the virtual approach related to the restorative, rehabilitation or even surgical area, It is insufficient for the dental student to adequately develop procedural skills. The objective of this study is to know the perception of Dentistry students regarding virtual classes during the pandemic in order to know their opinion about this issue, in addition to managing the improvement of teaching methods on virtual platforms, training teachers and students in the management of information and communication technology in virtual environments. Likewise, the use of haptic simulators can be integrated with virtual reality systems, technology that is already being used in Russian universities. In addition to contributing to the development of students' learning in times of pandemic, would also allow them to acquire and develop clinical skills that are required before having contact with the patient.

Virtual validation of a Metro rolling-stock for exterior and interior noise in standard controlled conditions

Validation of rolling-stock is a time and cost expensive task during the development of train. Replacing type tests by simulation (virtual validation) that fits the need of the complete railway industry in terms of accuracy and uncertainty, is possible in some cases. Simulation is widely used by train manufacturers during development of new products with good accuracy of prediction in a controlled environment as free field and ballasted track. Methodologies available are able to predict correctly in controlled conditions (ISO 3095/3381) interior and exterior noise for different operating conditions. In this paper, simulation cases will be presented for a standard metro product operating in controlled conditions. Simulations will be compared with experimental data for interior and exterior noise. Exterior noise modelling and propagation is done with analytical tools while interior noise is modeled using an experimental-numerical (beam-tracing) approach. Input data for simulations corresponds to numerical models of rolling noise and measured sound power level of equipment. Validation of the models are discussed and analyzed to confirm the reliability of virtual validation for rolling stock operating at controlled conditions. A proposal of a virtual validation approach based on uncertainties of the simulation is also discussed.

Applying Media and Virtual Approaches to the Institutionalization of Puzhou Opera

Puzhou opera, also known as Puju, originated in Puzhou in ancient China, which is now renamed as Yuncheng city, Shanxi province. Puju has been recorded since the Yuan dynasty and has become one of China’s most important operas because of its long history and influence on surrounding opera styles. This article explores challenges related to the institutionalization of Puju and how to use the modern technology of virtual media to ensure the sustainable development of traditional opera. In addition, as an insider of Yuncheng University, the researcher explored the application process of virtual media in promoting the institutionalized development of Puju and how to realize the learning, preservation, and inheritance of education and modern technology. To summarize, this study investigates the existing problems and challenges in using this virtual and media approaches and applies the media through virtual approach in the institutionalization of Puju to expand audiences and provide a new dissemination of opportunities.

Meet and Greet Sessions: A Unique Virtual Opt-Out Approach to Support Trainee Well-Being.

Background Interventions to support graduate medical education (GME) trainee well-being at the institutional level continue to be an area for continuous improvement. Objective To assess participation, feasibility, and acceptability of a virtual, individual, brief, nonevaluative opt-out approach to accessing mental health support for residents and fellows. Methods From 2021 to 2023, all GME programs at one large institution were invited to participate. During orientation, incoming trainees from programs that had communicated interest were prescheduled for optional 20-minute, virtual "meet and greet" sessions with a counselor from the hospital's Employee Assistance Program. Nonformal feedback was gathered using an anonymous 6-question survey. Results Three hundred thirty-four residents and fellows from 12 of 74 (16%) participating GME programs were prescheduled for opt-out sessions over 3 academic years. Of the 334, 182 (54%) attended the sessions, 116 (35%) subsequently reached out to start counseling, and 108 (32%) responded to the survey. Each year, approximately 7 counselor hours were needed for the opt-out sessions per week over an 8-week period, which was feasible and added no extra cost. In the follow-up survey shared with all participants, 59 of 81 (73%) respondents reported that the sessions helped to reduce barriers to seeking mental health care. Conclusions During orientation, one-half of invited GME trainees participated in a virtual, individual, brief, nonevaluative meet and greet session with a counselor using an opt-out approach, and one-third subsequently requested counseling. Survey feedback was encouraging, and this approach can serve to help normalize culture surrounding accessing mental health services.

A real-time eye movement-based computer interface for people with disabilities

It is costly to develop systems that enable individuals exposed to Amyotrophic Lateral Sclerosis and similar diseases that directly affect the neuromotor ability to communicate with the outside world. In this study, a budget friendly, high-accuracy, software-based, gaze-controlled, real-time virtual keyboard approach that can enable these people to communicate effectively is proposed. The proposed application requires only a computer and a webcam and has a user-friendly interface that meets the basic daily needs of individuals with disabilities. Since the proposed system does not require an extra action such as blinking, it makes it possible to use computers in advanced stage patients who cannot blink their eyes. The application which uses a deep learning-based facial landmark detector, determines the letters the user focuses on the screen and converts thoughts into text. The part of the screen that the user focuses on is determined with a new selection approach inspired by the K-Nearest Neighbors algorithm. This approach, which does not require blinking, offers high speed and accuracy. In the tests, a typing speed of 23.33 characters per minute is achieved with an accuracy rate of 95.12%. It is anticipated that the study will increase computer accessibility for disabled individuals with limited mobility and contribute to the development of real-time eye tracking systems.

A Resource Allocation Algorithm for Cloud-Network Collaborative Satellite Networks with Differentiated QoS Requirements

With the continuous advancement of cloud computing and satellite communication technology, the cloud-network-integrated satellite network has emerged as a novel network architecture. This architecture harnesses the benefits of cloud computing and satellite communication to achieve global coverage, high reliability, and flexible information services. However, as business types and user demands grow, addressing differentiated Quality of Service (QoS) requirements has become a crucial challenge for cloud-network-integrated satellite networks. Effective resource allocation algorithms are essential to meet these differentiated QoS requirements. Currently, research on resource allocation algorithms for differentiated QoS requirements in cloud-network-integrated satellite networks is still in its early stages. While some research results have been achieved, there persist issues such as high algorithm complexity, limited practicality, and a lack of effective evaluation and adjustment mechanisms. The first part of this study examines the state of research on network virtual mapping methods that are currently in use. A reinforcement-learning-based virtual network mapping approach that considers quality of service is then suggested. This algorithm aims to improve user QoS and request acceptance ratio by introducing QoS satisfaction parameters. With the same computational complexity, QoS is significantly improved. Additionally, there has been a noticeable improvement in the request acceptance ratio and resource utilization efficiency. The proposed algorithm solves existing challenges and takes a step towards more practical and efficient resource allocation in cloud-network-integrated satellite networks. Experiments have proven the practicality of the proposed virtual network embedding algorithm of Satellite Network (SN-VNE) based on Reinforcement Learning (RL) in meeting QoS and improving utilization of limited heterogeneous resources. We contrast the performance of the SN-VNE algorithm with DDRL-VNE, CDRL, and DSCD-VNE. Our algorithm improve the acceptance ratio of VNEs, long-term average revenue and delay by an average of 7.9%, 15.87%, and 63.21%, respectively.

A Practical Approach for Developing Shared Decision-Making Knowledge, Skills, and Capability for Busy Health Care Practitioners.

There has been substantial development of shared decision-making (SDM) methods and approaches in the past few decades, but despite this, building capability and scaling application of SDM in clinical practice remains a challenge. Here the authors describe the development and initial experience with a new virtual Practical Approach continuing education program for busy practicing clinicians who care for people with complex, chronic, and costly conditions who are frequently faced with preference-sensitive decisions. This program was designed to provide plain language training in SDM for real-world clinical practice using an easy 4-step approach that does not require prior training or formal education in SDM theory or methods. The authors describe the development of the Practical Approach program using established evidence-based principles. The program was piloted in 4 different settings across 2 chronic conditions. Qualitative interviews of program participants were conducted to observe SDM attitudes and observed performance in repeated case-based simulation role-play exercises to assess knowledge and skills performance. The authors observed improved and more realistic SDM attitudes in qualitative interviews with program participants after exposure to the program compared to baseline, and they similarly observed improved knowledge and skills demonstrated in sequential simulations conducted as participants were exposed to the program. Post-program focus groups revealed that participants perceived the program to be feasible, acceptable, and useful. Initial experience with the Practical Approach program suggests that it may beneficially affect basic SDM knowledge, skills, and attitudes in busy practicing clinicians who are novices in SDM. It also has demonstrated initial feasibility, utility, and acceptability.

Computer-Simulated Virtual Image Datasets to Train Machine Learning Models for Non-Invasive Fish Detection in Recirculating Aquaculture.

Artificial Intelligence (AI) and Machine Learning (ML) can assist producers to better manage recirculating aquaculture systems (RASs). ML is a data-intensive process, and model performance primarily depends on the quality of training data. Relatively higher fish density and water turbidity in intensive RAS culture produce major challenges in acquiring high-quality underwater image data. Additionally, the manual image annotation involved in model training can be subjective, time-consuming, and labor-intensive. Therefore, the presented study aimed to simulate fish schooling behavior for RAS conditions and investigate the feasibility of using computer-simulated virtual images to train a robust fish detection model. Additionally, to expedite the model training and automate the virtual image annotation, a process flow was developed. The 'virtual model' performances were compared with models trained on real-world images and combinations of real and virtual images. The results of the study indicate that the virtual model trained solely with computer-simulated images could not perform satisfactorily (mAP = 62.8%, F1 score = 0.61) to detect fish in a real RAS environment; however, replacing a small number of the virtual images with real images in the training dataset significantly improved the model's performance. The M6 mixed model trained with 630 virtual and 70 real images (virtual-to-real image ratio: 90:10) achieved mAP and F1 scores of 91.8% and 0.87, respectively. Furthermore, the training time cost for the M6 model was seven times shorter than that for the 'real model'. Overall, the virtual simulation approach exhibited great promise in rapidly training a reliable fish detection model for RAS operations.

Virtual Education in Military Medical University: A Descriptive Study

Background: Evaluating the strengths and weaknesses of virtual education is essential today. Objectives: This study examines the satisfaction of professors and students with the learning management system and the quality of virtual education in a military university. Methods: This descriptive-correlational study was conducted between 2021 and 2022. The sample included 44 professors and 167 students from the Faculty of Nursing, Medicine, and Pharmacy at a university. Data were collected using a demographic form and three standardized questionnaires that assessed satisfaction with the quality of virtual education, system interface, evaluation of professors' performance, and professors' opinions about virtual teaching. The data were analyzed using SPSS software version 22, employing correlation tests, one-way analysis of variance, independent t-tests, and multivariate analysis. Results: The students' average age was 21.23 ± 2.78 years, and 81.8% of them were male. The overall satisfaction of students with the learning management system (LMS) had an average score of 497.21 ± 109.68. The professors' performance, as perceived by the students, had an average score of 43.18 ± 9.98. The quality of online education was rated at 58.81 ± 12.51, with 68% of students reporting a moderate level of satisfaction. Among the professors, 29.5% expressed dissatisfaction with the LMS system interface, while 81.8% were moderately satisfied with the virtual education approach. Conclusions: Given the significance of virtual education, it is imperative to devise solutions that enhance professor satisfaction, improve content quality, and optimize performance. These measures will contribute to the overall success and effectiveness of virtual education, benefiting both professors and students alike.

CEC02-04 The virtual human approach to animal-free chemical hazard and risk assessment in developmental toxicology

CEC02-04 The virtual human approach to animal-free chemical hazard and risk assessment in developmental toxicology

A virtual case competition approach to bridging business acumen and biomedical graduate training.

A virtual case competition approach to bridging business acumen and biomedical graduate training.

Development of a hybrid ANFIS method for optimising laser beam welding of dissimilar metals: a virtual prototype approach

Development of a hybrid ANFIS method for optimising laser beam welding of dissimilar metals: a virtual prototype approach

Examining the effect of locomotion techniques on virtual prototype assessment: Gaze analysis using a Head-Mounted Display

Improvements in the performance and graphical quality of Head-Mounted Displays (HMDs) have led to their increasing use in Virtual Reality (VR) for product presentation and virtual prototype (VP) evaluations. Various locomotion techniques in VR make it possible to move through a virtual scenario and approach the VP for evaluation purposes. The integration of eye-tracking devices into recent HMDs allows the trajectory and gaze behavior of observers to be reported during the evaluation, often more objectively than self-report questionnaires. However, very few studies have used physiological measures for the evaluation of products embedded in VR environments. Therefore, this paper offers a study in which 95 people evaluated three VPs of street furniture presented in their environment of use using Meta Quest Pro headset and explored through teleport and natural walking. The influence of the locomotion techniques on the ratings recorded using a semantic differential, sense of presence, cybersickness, and the role of eye-tracking in understanding gaze behavior while evaluating products' Areas of Interest (AOIs), are investigated. This study found no evidence that the way of approaching the product influences the evaluation of some of its features, overall product evaluation, confidence in responses, sense of presence, or cybersickness differently. On the other hand, this work evidences that the locomotion technique had an impact on how the user approached the products, which could significantly influence the viewing time of some AOIs. The study revealed that the most observed AOIs coincided with those parts closely related to important features, generally located at the top of the products, so paying special attention to these parts when designing and evaluating similar VPs is recommended.

VLR-BPP: An intelligent virtual location replacement based bilateral privacy-preserving architecture for edge cloud systems

Mobile Crowdsourcing (MCS) has emerged as a significant edge-cloud computing paradigm in which workers perceive data at the network edge and report it to cloud-based computing services for processing, enabling the construction of various applications. Consequently, it is imperative to achieve Bilateral Location Privacy-Preserving (BLPP) to protect the privacy of both Data Requester (DR) and workers, as disclosing location information entails many sensitive details that can result in losses for DR and workers alike. The Local Differential Privacy (LDP) approach is widely employed in Privacy-Preserving (PP) techniques due to its inherent advantages, wherein owners release data with added noise, allowing for proactive customization of privacy strength without relying on any third party. However, the current state of LDP methods presents a dilemma: when privacy protection is strong, introducing excessive location noise can lead to a decrease in the accuracy of task-worker matching, while a high rate of task-worker matching necessitates the compromise of privacy strength. In this paper, an intelligent Virtual Location Replacement based enhanced Bilateral Privacy-Preserving (VLR-BPP) architecture is proposed to improve privacy protection strength and matching accuracy in MCS simultaneously. Within the VLR-BPP architecture, a Bipartite-Graph-based Matrix Completion (BGMC) model is employed to establish the spatiotemporal correlations among data. Then, a Virtual Location Replacement (VLR) strategy is proposed to obfuscate the locations of tasks or workers to their highly correlated virtual location before publishing. Based on VLR, three preemptive location virtualization approaches are introduced: Only Task Location Virtual (OTLV), Only Workers Location Virtual (OWLV), and Both Task and Workers Location Virtual (BTWLV). For workers and DR, Randomized Response (RR) techniques and Random Matrix Multiplication Mechanism (RMM) are used to implement LDP independently. A greedy algorithm is adopted to recruit workers for tasks. In response to the data submitted by workers, BGMC imputation mechanism is utilized to enhance data quality. Finally, simulations based on real-world datasets demonstrate that the performance of our architecture surpasses existing state-of-the-art methods in privacy protection and data collection quality by 18.92∼38.17% and 15.49∼50.77%, respectively.

Application of AI and VR Synergistic Enhancement in Employment Skills Training: A Virtual Simulation Approach

In recent years, the rapid development of artificial intelligence (AI) and virtual reality (VR) technology has opened up new approaches in the field of education and training, especially employment skills training. This study explores the application of artificial intelligence and virtual reality collaborative enhancement technology in virtual simulation training of employment skills. It introduces a comprehensive theoretical framework, including data collection and processing, intelligent analysis using multimodal algorithms, collaborative security mechanisms for AI models, and AI-VR interaction optimization techniques. This study confirms the feasibility and validity of the framework through theoretical analysis, simulation experiments, and expert interviews. The results show that the proposed framework significantly improves the personalization and interactivity of training, ensures data privacy and system stability, and improves the efficiency of intelligent diagnosis. This study provides valuable theoretical support and innovative ideas for the deep integration of VR technology in educational training.

From physical feelings to empathy: An immersive virtual reality approach to facilitate physical empathy

Studies have suggested that virtual reality (VR) as an ‘empathy-making machine’ has the potential to trigger historical empathy. Different VR technologies offer different levels of immersion with different educational implications. Higher immersive VR technology has shown promise in enhancing learners’ empathy levels. However, how highly immersive VR promotes learners’ historical empathy in real-life classroom settings has not been explored. Hence, this study focuses on comparing two levels of immersive VR-supported learning for historical empathy acquisition among secondary learners. A total of 49 students were recruited. A quasi-experimental design was employed and the quantitative and qualitative data were analyzed to explore participants’ historical knowledge and empathy. The quantitative data show no significant difference between immersive virtual reality (IVR) approach-supported learning and flatscreen VR-supported learning. However, the qualitative analysis suggests that the students from the IVR group showed stronger ‘physical empathy’. Intriguingly, even though the tests did not demonstrate that the students learned more in IVR-supported learning, they self-reported that they learned better in IVR-supported learning. The paper identifies implications for the connection between ‘physical empathy’ and the level of immersive technology.

Risk-aware scheduling and dispatch of flexibility events in buildings

Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services. In this work, we leverage this flexibility to react to consumption requests related to maximizing self-consumption and reducing peak loads. We employ a data-driven virtual storage modeling approach for flexibility prediction in the form of flexibility envelopes for individual buildings. The risk-awareness of this prediction is inherited by the proposed scheduling algorithm. A Mixed-integer Linear Program (MILP) is formulated to schedule the activation of a pool of buildings in order to best respond to an external aggregated consumption request. This aggregated request is then dispatched to the active individual buildings, based on the previously determined schedule. The effectiveness of the approach is demonstrated by coordinating up to 500 simulated buildings using the Energym Python library and observing about 1.5 times peak power reduction in comparison with a baseline approach while maintaining comfort more robustly. We demonstrate the scalability of the approach by solving problems with 2000 buildings in about 21 s, with solving times being approximately linear in the number of considered assets.