Construction of Virtual Turning Scene Based on Local Ray Tracing Algorithm

According to the features of the turning simulation, a simplified Whitted lighti ng model is proposed based on the analysis of Phong and other local illumination model. Moreover, in order to obtain the natural lighting effects, local ray tra cing algorithm is given to calculate the light intensity of every position durin g the course of the simulation. This method can calculate the refresh area befor e calculating the intersection line, simulate the machining environment accurate ly and reduce the calculating time. Finally, an example of the virtual cutting s cene is shown to demonstrate the effects of the global illumination model. If th e CUP is 1.3 G and the internal memory is 128 M, the refreshing time of virtual turning scene can be reduced by nine times.This study plays an important role in the enrichment of the virtual manufacturing theory and the promotion of the dev elopment of the advanced manufacturing technology.

A modeling method for virtual scene based on multi-view image sequence

Through the analysis and comparison of shortcomings and advantages of existing technologies on object modeling in 3D applications,we propose a new modeling method for virtual scene based on multi-view image sequence to model irregular objects efficiently in 3D application.In 3D scene,this method can get better visual effect by tracking the viewer's real-time perspective position and projecting the photos from different perspectives dynamically.The philosophy of design,the steps of development and some other relevant topics are discussed in details,and the validity of the algorithm is analyzed.The results demonstrate that this method represents more superiority on simulating irregular objects by applying it to the modeling of virtual museum.

Redirected jumping in virtual scenes with alleys

Background The redirected jumping(RDJ)technique is a new locomotion method that saves physical tracking area and enhances the body movement experience of users in virtual reality.In a previous study,the range of imperceptible manipulation gains in RDJ was discussed in an empty virtual environment(VE).Methods In this study,we conducted three tasks to investigate the influence of alley width on the detection threshold of jump redirection in a VE.Results The results demonstrated that the imperceptible distance gain range in RDJ was not associated with the width of the alleys.The imperceptible height and rotation gain ranges in RDJ are related to the width of the alleys.Conclusions We preliminarily summarized the relationship between the occlusion distance and manipulation range of the three gains in a complex environment.Simultaneously,the guiding principle for choosing three gains in RDJ according to the occlusion distance in a complex environment is provided.

Construction of Realistic Scene in Virtual Turning Based on Global Illumination Model and Chip Simulation

With the rapid development of manufacturing technology, the traditional simulation of machining can not meet the people’s need. Research on virtual machining environment is one of the key parts of virtual manufacturing technology. According to the features of virtual turning, this paper proposes a simplified Whitted lighting model based on analysis of Phong and other local illumination model. This model takes the material and roughness of workpiece into account to calculate the roughness coefficient D, geometric fading coefficient G and Fresenel transmission coefficient F’ so that the light intensity in the scene can be got more realisticly. Moreover, to obtain the natural lighting effects, based on the analysis of motion space of machine tools, local ray tracing algorithm is given to calculate the light intensity of every position during the course of simulation. This method can not only simulate the machining environment accurately, but also reduce the calculating time greatly. For example, if CPU is 1.3 G and internal memory is 128 M, the refresh time using the original algorithm is 0.1 second, while it becomes 0.01 seconds by local refreshing. Besides, to get more realistic machining scene, the paper deduce the transfer matrix from chip coordinate to feeding coordinate so that the chip model can be integrated into the whole machining scene. At last, a example of virtual cutting scene is shown to demonstrate the effects of global illumination model and helical chip simulation. The system can give the user high true sensation. The user can operate the machine tools through the controlling panel and watch the cutting process from different viewing angle. The data needed for construction of scene and chip simulation is obtained form the C616 lathe. This study plays important role in richening virtual manufacturing theory and promoting the development of advanced manufacturing technology.

Spatial Heterogeneity of Embedded Water Consumption from the Perspective of Virtual Water Surplus and Deficit in the Yellow River Basin,China

Virtual water trade(VWT)provides a new perspective for alleviating water crisis and has thus attracted widespread attention.However,the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study.In this study,for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model(MRIO),we proposed two new concepts,i.e.,virtual water surplus and virtual water deficit,and then used the Logarithmic Mean Divisia Index(LMDI)model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China.The results show that:1)in provincial regions along the Yellow River Basin,the less developed the economy was,the larger the contribution of the agricultural sector in virtual water trade,while the smaller the contribution of the industrial sector.2)Due to the large output of agricultural products,the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus,with a net outflow of virtual water of 2.7×10^(8) m^(3) and 0.9×10^(8) m^(3),respectively.3)provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China,and the decisive factor was the active degree of trade with the outside.This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin,which has farreaching practical signific-ance for alleviating water scarcity.

Virtual Painting Environment Design on the Intemet Based on VRML Scene

How to build a commercial decorative paintings sale web with the function of see placing effect was explained before you buy. Especially, the user could remotely choose a painting and virtually place it on a model room, or even his own real room picture. ASP（Active Server Pages） was used to connect VRML and the database, and JavaScript was used to make3D interaction. In addition, the layered images and transparent images were proposed to solve the occlusion between background picture and foreground picture.

Mental health in the virtual world:Challenges and opportunities in the metaverse era

Current rates of mental illness are worrisome.Mental illness mainly affects females and younger age groups.The use of the internet to deliver mental health care has been growing since 2020 and includes the implementation of novel mental health treatments using virtual reality,augmented reality,and artificial intelligence.A new three dimensional digital environment,known as the metaverse,has emerged as the next version of the Internet.Artificial intelligence,augmented reality,and virtual reality will create fully immersive,experiential,and interactive online environments in the metaverse.People will use a unique avatar to do anything they do in their“real”lives,including seeking and receiving mental health care.In this opinion review,we reflect on how the metaverse could reshape how we deliver mental health treatment,its opportunities,and its challenges.

Effects of virtual agents on interaction efficiency and environmental immersion in MR environments

Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.

Virtual reality tools for training in gastrointestinal endoscopy:A systematic review

BACKGROUND Virtual reality(VR)has emerged as an innovative technology in endoscopy training,providing a simulated environment that closely resembles real-life scenarios and offering trainees a valuable platform to acquire and enhance their endoscopic skills.This systematic review will critically evaluate the effectiveness and feasibility of VR-based training compared to traditional methods.AIM To evaluate the effectiveness and feasibility of VR-based training compared to traditional methods.By examining the current state of the field,this review seeks to identify gaps,challenges,and opportunities for further research and implementation of VR in endoscopic training.METHODS The study is a systematic review,following the guidelines for reporting systematic reviews set out by the PRISMA statement.A comprehensive search command was designed and implemented and run in September 2023 to identify relevant studies available,from electronic databases such as PubMed,Scopus,Cochrane,and Google Scholar.The results were systematically reviewed.RESULTS Sixteen articles were included in the final analysis.The total number of participants was 523.Five studies focused on both upper endoscopy and colonoscopy training,two on upper endoscopy training only,eight on colonoscopy training only,and one on sigmoidoscopy training only.Gastrointestinal Mentor virtual endoscopy simulator was commonly used.Fifteen reported positive results,indicating that VR-based training was feasible and acceptable for endoscopy learners.VR technology helped the trainees enhance their skills in manipulating the endoscope,reducing the procedure time or increasing the technical accuracy,in VR scenarios and real patients.Some studies show that the patient discomfort level decreased significantly.However,some studies show there were no significant differences in patient discomfort and pain scores between VR group and other groups.CONCLUSION VR training is effective for endoscopy training.There are several well-designed randomized controlled trials with large sample sizes,proving the potential of this innovative tool.Thus,VR should be more widely adopted in endoscopy training.Furthermore,combining VR training with conventional methods could be a promising approach that should be implemented in training.

Virtual reality for preoperative patient education: Impact on satisfaction, usability, and burnout from the perspective of new nurses

BACKGROUND Traditional paper-based preoperative patient education is a struggle for new nurses and requires extensive training.In this situation,virtual reality technology can help the new nurses.Despite its potential benefits,there are studies on patient satisfaction but there is limited information on the usability of virtual reality(VR)technology for new nurses in giving preoperative education to patients.AIM To investigate the impact on satisfaction,usability,and burnout of a system using VR technology in preoperative patient education.METHODS The study involved 20 nurses from the plastic surgery ward and 80 patients admitted between April and May 2019.Each nurse taught four patients:Two using traditional verbal education and two using virtual reality.The System Usability Scale,After-Scenario Questionnaire,and Maslach Burnout Inventory(MBI)were employed to evaluate the impact of these education methods.RESULTS The VR education groups showed a statistically higher satisfaction than the traditional verbal education groups.Among the three subscales of the MBI,emotional exhaustion and personal accomplishment improved statistically significantly.VR was also better in terms of usability.CONCLUSION This study suggests VR enhances usability and reduces burnout in nurses,but further research is needed to assess its impact on depersonalization and objective measures like stress and heart rate.

A virtual thermometer for ultrahigh-temperature-pressure experiments in a large-volume press

Ultrahigh-temperature-pressure experiments are crucial for understanding the physical and chemical properties of matter.The recent development of boron-doped diamond(BDD)heaters has made such melting experiments possible in large-volume presses.However,estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained,owing to the lack of a suitable thermometer.Here,we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K.The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes,the actual sizes of cell assemblies after compression,the effects of the electrode,thermocouple and anvil,and the heat dissipation by the pressure-transmitting medium.The virtual thermometer reproduces the power-temperature relationships of ultrahigh-temperature-pressure experiments below 2600 K at press loads of 2.8-7.9 MN(~19 to 28 GPa)within experimental uncertainties.The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power-temperature relationships below 2600 K.Furthermore,our model shows that the temperature distribution inside a BDD heater(19-26 K/mm along the radial direction and<83 K/mm along the longitudinal direction)is more homogeneous than those inside conventional heaters such as graphite or LaCrO_(3) heaters(100-200 K/mm).Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences.

Wear dependent virtual flow rate sensor for progressing cavity pumps with deformable stator

This contribution presents a novel wear dependent virtual flow rate sensor for single stage single lobe progressing cavity pumps. We study the wear-induced material loss of the pump components and the impact of this material loss on the volumetric efficiency. The results are combined with an established backflow model to implement a backflow calculation procedure that is adaptive to wear. We use a laboratory test setup with a highly abrasive fluid and operate a pump from new to worn condition to validate our approach. The obtained measurement data show that the presented virtual sensor is capable of calculating the flow rate of a pump being subject to wear during its regular operation.

Towards complex scenes: A deep learning-based camouflaged people detection method for snapshot multispectral images

Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.

Special Vehicle Target Detection and Tracking Based on Virtual Simulation Environment and YOLOv5-Block+DeepSort Algorithm

In the process of dense vehicles traveling fast,there will be mutual occlusion between vehicles,which will lead to the problem of deterioration of the tracking effect of different vehicles,so this paper proposes a research method of virtual simulation video vehicle target tracking based on you only look once(YOLO)v5s and deep simple online and realtime tracking(DeepSort).Given that the DeepSort algorithm is currently the most effective tracking method,this paper merges the YOLOv5 algorithm with the DeepSort algorithm.Then it adds the efficient channel attention networks(ECA-Net)focusing mechanism at the back for the cross-stage partial bottleneck with 3 convolutions(C3)modules about the YOLOv5 backbone network and before the up-sampling of the Neck feature pyramid.The YOLOv5 algorithm adopts expected intersection over union(EIOU)instead of complete intersection over union(CIOU)as the loss function of the target frame regression.The improved YOLOv5 algorithm is named YOLOv5-Block.The experimental results show that in the special vehicle target detection(TD)and tracking in the virtual simulation environment,The YOLOv5-Block algorithm has an average accuracy(AP)of 99.5%,which significantly improves the target recognition correctness for typical occlusion cases,and is 1.48 times better than the baseline algorithm.After the virtual simulation video sequence test,multiple objects tracking accuracy(MOTA)and various objects tracking precision(MOTP)improved by 10.7 and 1.75 percentage points,respectively,and the number of vehicle target identity document(ID)switches decreased.Compared with recent mainstream vehicle detection and tracking models,the YOLOv5-Block+Deepsort algorithm can accurately and continuously complete the detection and tracking tasks of special vehicle targets in different scenes.

Proposal for a realtime Einstein-synchronization-defined satellite virtual clock

Realization of high performance satellite onboard clock is vital for various positioning, navigation, and timing applications. For further improvement of the synchronization-based satellite time and frequency references, we propose a geosynchronous(GEO) satellite virtual clock concept based on ground–satellite synchronization and present a beacon transponder structure for its implementation(scheduled for launch in 2025), which does not require atomic clocks to be mounted on the satellite. Its high performance relies only on minor modifications to the existing transponder structure of GEO satellites. We carefully model the carrier phase link and analyze the factors causing link asymmetry within the special relativity. Considering that performance of such synchronization-based satellite clocks is primarily limited by the link's random phase noise, which cannot be adequately modeled, we design a closed-loop experiment based on commercial GEO satellites for pre-evaluation. This experiment aims at extracting the zero-means random part of the ground-satellite Ku-band carrier phase via a feedback loop. Ultimately, we obtain a 1σ value of 0.633 ps(two-way link), following the Gaussian distribution. From this result, we conclude that the proposed real-time Einstein-synchronization-defined satellite virtual clock can achieve picosecond-level replication of onboard time and frequency.

A Survey of Crime Scene Investigation Image Retrieval Using Deep Learning

Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep learning,data-driven paradigm has become the mainstreammethod of CSI image feature extraction and representation,and in this process,datasets provideeffective support for CSI retrieval performance.However,there is a lack of systematic research onCSI image retrieval methods and datasets.Therefore,we present an overview of the existing worksabout one-class and multi-class CSI image retrieval based on deep learning.According to theresearch,based on their technical functionalities and implementation methods,CSI image retrievalis roughly classified into five categories:feature representation,metric learning,generative adversar-ial networks,autoencoder networks and attention networks.Furthermore,We analyzed the remain-ing challenges and discussed future work directions in this field.

An impact sensitivity assessment method of spacecraft based on virtual exterior wall

The impact sensitivity assessment of spacecraft is to obtain the probability of spacecraft encountering the OD/M(orbital debris or meteoroid),which is a prerequisite for survivability assessment of on-orbit spacecraft.An impact sensitivity assessment method of spacecraft based on virtual exterior wall was proposed to improve the computational efficiency.This method eliminates determination of the outermost surface elements of the spacecraft before generating the debris rays,which are assumed to originate from a non-concave virtual wall that completely wraps the spacecraft.The Dist Mesh method was adopted for the generating of the virtual wall to ensure its mesh quality.The influences of the sizes,mesh densities,shapes of the virtual wall on the efficiency and accuracy were considered to obtain the best combination of the size and mesh density of the wall and spacecraft.The results of this method were compared with those of S3DE(Survivability of Spacecraft in Space Debris Environment),BUMPER,MDPANTO,ESABASE2/Debris to verify the feasibility of the method.The PCHIP(Piecewise Cubic Hermite Interpolating Polynomial)was used to fit the size vs.flux relationship of the space debris to acquire the impact probability of OD/M with arbitrary size on the spacecraft.

Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive simulations.CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are imperative.Despite ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems.To address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD processes.The HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision events.Extensive experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex models.The optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual systems.These findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

Enhancing preoperative patient education through virtual reality:A leap forward in nursing practice

Integration of virtual reality(VR)technology into preoperative patient education has shown potential to improve nursing practice.The study by Kim et al examines the impact of VR on nurse satisfaction,usability,and burnout.A prospective study involving 20 nurses and 80 patients was conducted,comparing traditional paper-based education with VR-based education in the plastic surgery ward at Chungnam National University Hospital.Findings demonstrated that VR significantly enhanced satisfaction and usability among nurses,while also reducing emotional exhaustion,a critical factor in nurse burnout.Consistency in education quality was also improved,ensuring uniform patient care.These results underscore the importance of VR in reducing the stress of repetitive tasks,improving job satisfaction,and potentially enhancing nurse retention.Future research should explore the broader applications of VR in healthcare and address the logistical challenges of integrating this technology into routine clinical practice.The study by Kim et al highlights VR’s transformative potential in preoperative education for both patients and healthcare providers.

Breaking the optical efficiency limit of virtual reality with a nonreciprocal polarization rotator

A catadioptric lens structure,also known as pancake lens,has been widely used in virtual reality(VR)displays to reduce the formfactor.However,the utilization of a half mirror(HM)to fold the optical path thrice leads to a significant optical loss.The theoretical maximum optical efficiency is merely 25%.To transcend this optical efficiency constraint while retaining the foldable characteristic inherent to traditional pancake optics,in this paper,we propose a theoretically lossless folded optical system to replace the HM with a nonreciprocal polarization rotator.In our feasibility demonstration experiment,we used a commercial Faraday rotator(FR)and reflective polarizers to replace the lossy HM.The theoretically predicted 100%efficiency can be achieved approximately by using two high-extinction-ratio reflective polarizers.In addition,we evaluated the ghost images using a micro-OLED panel in our imaging system.Indeed,the ghost images can be suppressed to undetectable level if the optics are with antireflection coating.Our novel pancake optical system holds great potential for revolutionizing next-generation VR displays with lightweight,compact formfactor,and low power consumption.