Virtual Objects Research Articles

A Simplified Theoretical Method for Estimating the Effect of Capsule Grouting Expansion Technology on Controlling Pile Deformation

Deep excavation and shield tunneling processes often induce significant deformation in adjacent existing pile foundations, posing risks to the safety of superstructures. To address this issue, capsule grouting expansion technology has emerged as an efficient and economical technology to actively control pile deformation during such construction activities. This technology has been applied in some engineering projects aimed at safeguarding nearby buildings or facilities. However, theoretical research on capsule grouting expansion technology is limited and lags behind its practical engineering application. This paper proposed a simplified theoretical approach for estimating the effect of capsule grouting expansion technology on the deformation of neighboring pile foundations. Initially, virtual image technology was employed to obtain an analytical solution for the lateral displacement of soil resulting from the expansion of a cylindrical cavity with infinite height. The pile was considered as an Euler–Bernoulli beam on a Winkler foundation, allowing for the calculation of the loading response of the existing pile foundation. Utilizing the two-stage method, the theoretical analytical method of the lateral deformation of the pile shaft caused by capsule expansion was obtained. The reliability of the proposed theoretical method was verified by comparing the measured and calculated results. Further investigation into the controlling effect of the capsule grouting expansion technology on the deformation of the pile foundation was conducted through parametric analyses. These analyses encompass capsule radius, the distance between the capsule and pile foundation, the depth of the capsule, the length of the capsule, and the pile base constraints.

Virtual Sound Image Reconstruction Method for Multi-objective Optimization of Folk Music Based on Evolutionary Algorithm

At present, the exchanges in various fields such as culture, economy, and politics are becoming more and more close in the world. From the perspective of the relationship between national music and cultural development, the development of national music has also received more and more attention, and it has become an inevitable trend in the development of today's era. The purpose of this paper was to perform virtual reconstruction of the sound image of folk music through multiple objective optimizations, and to model the virtual sound image of folk music as a multi-objective optimization problem. According to the research on sound image positioning, the relevant noise factors were removed, so as to achieve the playback of ethnic music that enhanced the surround effect and visual enjoyment. The evolutionary algorithm in this paper was mainly based on the multi-objective optimized sound image localization technology. For the music virtual sound image, an improved FCM algorithm and an evolutionary multi-objective optimization algorithm combining local and non-local information of the sound image were proposed, respectively. Through the analysis of the traditional sound image algorithm method, the accuracy of the sound image localization on the horizontal plane could be effectively improved. After the conversion, the audience could feel the better stereo image and surround feeling of the folk music. Through experimental analysis, it can be seen that the system can not only perform virtual conversion of audio-visual signals of different frequencies, but also provide data for different audio playback systems. The feature point registration error is low, and the reconstruction effect is good, especially the random delay processing in the range of 0∼20m, and the performance is better than the traditional method. Finally, virtual left and right surround sound image signals were obtained, which effectively improved the three-dimensional surround feeling of folk music.

Immersive VR experience based on virtual robots in decorative material environment design simulation

Virtual robot and immersive VR experiences provide consumers with new ways of perception in the design process of decorative material environments. This experiential process is virtual, intuitive, and entertaining, and is widely recognized by consumers.The purpose of this study is to improve the processing effect of virtual images of decorative materials by image denoising algorithm. In this paper, the image acquisition and modeling technology based on sensor network and image denoising algorithm are used to process the acquired image data, and the processed image is applied to the virtual system of decorative materials. Through the application of image denoising algorithm, the noise in the image is reduced, and the clarity and authenticity of the virtual image of decorative materials are improved. This makes it possible to select the best decoration scheme more accurately when comprehensive calculation is carried out from various aspects such as aesthetic and functional data, and provides a new feasibility and method for environmental design and decoration material selection. The research results demonstrate that the system can achieve virtual image processing in environmental decoration scene design, thereby improving the level of indoor environmental art design.

Comparison of deviceless methods for distant object manipulation in mixed reality

Mixed Reality (MR) applications based on the current generation of Head-mounted displays (HMDs) support a deviceless manipulation of virtual objects based on finger tracking and control of the 3D transformation with gestures. However, when the object manipulation is performed at some distance, and when the transform includes scaling, it is not apparent how to remap the hand motions over the degrees of freedom of the object. The most popular software toolkits used for XR development provide specific solutions, but there are still usability issues and a need for clear guidelines for the interaction design.In this work, we compare three different solutions for the devices and remote translation, rotation, and scaling of virtual objects in a real environment in two user studies aimed at assessing the usability of the methods for different tasks. The tasks are a fast and rough docking of virtual cubes on a tangible shelf from varying distances and the accurate placement of cubes on the shelf in a fixed amount of time.The outcomes of these studies show that the usability of the manipulation methods is strongly affected by the use of separate or integrated control of the degrees of freedom, by the use of the hands in a symmetric or specialized way, by the visual feedback, and by the previous experience of the users and provides valuable guidelines for the design of interactive mixed environments.

StarGAN Model to Translate Interior Style Trained with Virtual Images

StarGAN Model to Translate Interior Style Trained with Virtual Images

A seismic ambient noise data classification method based on waveform and frequency-wavenumber analysis: Application to reliable geological interpretation adjacent to Well Songke-2, Northeast China

Passive seismic interferometry techniques enable the retrieval of virtual shot gathers at receiver locations. However, it is difficult to distinguish body waves from surface waves in seismic ambient noise data, which leads to failed dispersion measurements, artificial deep reflections, and misleading geologic interpretations. We develop a new method that uses the waveforms and their corresponding f- k spectra to identify body waves and surface waves. Our technique functions as a data classification procedure before wavefield retrieval and subsequent imaging. A field data example is conducted to test the feasibility of this technique. The field data results demonstrate that our technique can reconstruct satisfactory high signal-to-noise-ratio wavefields for reliable imaging and interpretation purposes. The method can also serve as a validation tool for identifying surface wave-related artificial events in the obtained virtual source reflection image. The marker boundaries of the Songliao Basin in Northeast China are interpreted in the obtained profile and are in agreement with the well-logging data. In addition, two normal faults are detected, which correspond to the extensional rift environment during the early Cretaceous.

Assessing the Stability of Photon-Counting CT: Insights from a Two-Year Longitudinal Study.

Among the advancements in computed tomography (CT) technology, photon-counting computed tomography (PCCT) stands out as a significant innovation, providing superior spectral imaging capabilities while simultaneously reducing radiation exposure. Its long-term stability is important for clinical care, especially longitudinal studies, but is currently unknown. This study sets out to comprehensively analyze the long-term stability of a first-generation clinical PCCT scanner. Over a two-year period, from November 2021 to November 2023, we conducted weekly identical experiments utilizing the same multi-energy CT protocol. These experiments included various tissue-mimicking inserts to rigorously assess the stability of Hounsfield Units (HU) and image noise in Virtual Monochromatic Images (VMIs) and iodine density maps. Throughout this period, notable software and hardware modifications were meticulously recorded. Each week, VMIs and iodine density maps were reconstructed and analyzed to evaluate quantitative stability over time. Spectral results consistently demonstrated the quantitative stability of PCCT. VMIs exhibited stable HU values, such as variation in relative error for VMI 70 keV measuring 0.11% and 0.30% for single-source and dual-source modes, respectively. Similarly, noise levels remained stable with slight fluctuations linked to software changes for VMI 40 and 70 keV that corresponded to changes of 8 and 1 HU, respectively. Furthermore, iodine density quantification maintained stability and showed significant improvement with software and hardware changes, especially in dual-source mode with nominal errors decreasing from 1.44 to 0.03 mg/mL. This study provides the first long-term reproducibility assessment of quantitative PCCT imaging, highlighting its potential for the clinical arena. This study indicates its long-term utility in diagnostic radiology, especially for longitudinal studies.

Real-virtual Point Cloud Augmentation Method for Test and Evaluation of Autonomous Weapon Systems

Autonomous weapon systems act according to artificial intelligence-based judgement based on recognition through various sensors. Test and evaluation for various scenarios is required depending on the characteristics that artificial intelligence-based judgement is made. As a part of this approach, this paper proposed a LiDAR point cloud augmentation method for mixed-reality based test and evaluation. The augmentation process is achieved by mixing real and virtual LiDAR signals based on the virtual LiDAR synchronized with the pose of the autonomous weapon system. For realistic augmentation of test and evaluation purposes, appropriate intensity values were inserted when generating a point cloud of a virtual object and its validity was verified. In addition, when mixing the generated point cloud of the virtual object with the real point cloud, the proposed method enhances realism by considering the occlusion phenomenon caused by the insertion of the virtual object.

Photon-Counting Computed Tomography for Microstructural Imaging of Bone and Joints.

Recently, photon-counting computed tomography (PCCT) has been introduced in clinical research and diagnostics. This review describes the technological advances and provides an overview of recent applications with a focus on imaging of bone. PCCT is a full-body scanner with short scanning times that provides better spatial and spectral resolution than conventional energy-integrating-detector CT (EID-CT), along with an up to 50% reduced radiation dose. It can be used to quantify bone mineral density, to perform bone microstructural analyses and to assess cartilage quality with adequate precision and accuracy. Using a virtual monoenergetic image reconstruction, metal artefacts can be greatly reduced when imaging bone-implant interfaces. Current PCCT systems do not allow spectral imaging in ultra-high-resolution (UHR) mode. Given its improved resolution, reduced noise and spectral imaging capabilities PCCT has diagnostic capacities in both qualitative and quantitative imaging that outperform those of conventional CT. Clinical use in monitoring bone health has already been demonstrated. The full potential of PCCT systems will be unlocked when UHR spectral imaging becomes available.

Improving Teaching Using Artificial Intelligence and Augmented Reality

With the rapid advancements in technology, the educational landscape is witnessing significant transformations in pedagogy and classroom dynamics. Two prominent technologies, Artificial Intelligence (AI) and Augmented Reality (AR), are gaining prominence in the field of education, promising to revolutionize the way teaching and learning take place. This article explores the potential benefits, challenges, and practical applications of integrating AI and AR into the teaching process to enhance student engagement and learning outcomes. The integration of AI in education brings forth personalized learning experiences. AI-powered algorithms analyze vast amounts of student data, including learning patterns, strengths, and weaknesses, to create tailored learning paths. This individualized approach helps educators identify students' unique needs and provide targeted support, ensuring that no student is left behind. Moreover, AI-based chatbots and virtual teaching assistants are increasingly being used to address student queries promptly, providing real-time support and fostering a more interactive learning environment. AR, on the other hand, enables the overlay of virtual objects and information in the real-world environment.. Students can explore complex concepts through visualizations, simulations, and interactive demonstrations, facilitating a deeper understanding of abstract topics. AR also fosters collaboration and teamwork among students, promoting active learning and peer-to-peer knowledge sharing. Combining AI and AR technologies offers a powerful synergy in the educational realm. AI can analyze AR-generated data and adapt instructional strategies in real time, responding to individual students' progress. This synergy not only enhances learning outcomes but also empowers teachers with data-driven insights, enabling them to make informed decisions about their teaching methodologies. However, successfully implementing AI and AR in education comes with its challenges. Issues related to data privacy, ethical considerations, and the need for effective teacher training in utilizing these technologies require careful attention.

A dual-energy computed tomography-based radiomics nomogram for predicting time since stroke onset: a multicenter study.

We aimed to develop and validate a radiomics nomogram based on dual-energy computed tomography (DECT) images and clinical features to classify the time since stroke (TSS), which could facilitate stroke decision-making. This retrospective three-center study consecutively included 488 stroke patients who underwent DECT between August 2016 and August 2022. The eligible patients were divided into training, test, and validation cohorts according to the center. The patients were classified into two groups based on an estimated TSS threshold of ≤ 4.5 h. Virtual images optimized the visibility of early ischemic lesions with more CT attenuation. A total of 535 radiomics features were extracted from polyenergetic, iodine concentration, virtual monoenergetic, and non-contrast images reconstructed using DECT. Demographic factors were assessed to build a clinical model. A radiomics nomogram was a tool that the Rad score and clinical factors to classify the TSS using multivariate logistic regression analysis. Predictive performance was evaluated using receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA) was used to compare the clinical utility and benefits of different models. Twelve features were used to build the radiomics model. The nomogram incorporating both clinical and radiomics features showed favorable predictive value for TSS. In the validation cohort, the nomogram showed a higher AUC than the radiomics-only and clinical-only models (AUC: 0.936 vs 0.905 vs 0.824). DCA demonstrated the clinical utility of the radiomics nomogram model. The DECT-based radiomics nomogram provides a promising approach to predicting the TSS of patients. The findings support the potential clinical use of DECT-based radiomics nomograms for predicting the TSS. Accurately determining the TSS onset is crucial in deciding a treatment approach. The radiomics-clinical nomogram showed the best performance for predicting the TSS. Using the developed model to identify patients at different times since stroke can facilitate individualized management.

Fine structural human phantom in dentistry and instance tooth segmentation

In this study, we present the development of a fine structural human phantom designed specifically for applications in dentistry. This research focused on assessing the viability of applying medical computer vision techniques to the task of segmenting individual teeth within a phantom. Using a virtual cone-beam computed tomography (CBCT) system, we generated over 170,000 training datasets. These datasets were produced by varying the elemental densities and tooth sizes within the human phantom, as well as varying the X-ray spectrum, noise intensity, and projection cutoff intensity in the virtual CBCT system. The deep-learning (DL) based tooth segmentation model was trained using the generated datasets. The results demonstrate an agreement with manual contouring when applied to clinical CBCT data. Specifically, the Dice similarity coefficient exceeded 0.87, indicating the robust performance of the developed segmentation model even when virtual imaging was used. The present results show the practical utility of virtual imaging techniques in dentistry and highlight the potential of medical computer vision for enhancing precision and efficiency in dental imaging processes.

The Eye Stays in the Picture: Virtual Images in Early Modern and Modern Optics

Abstract In optics, real images can be projected onto a screen, while virtual ones always remain behind mirrors. This apparently straightforward distinction is based on complex premises which emerged in the Early Modern period, and its development went hand in hand with a transformation of the notion of image, which became detached from sensual perception. In this article I will outline this historical process, and argue that the distinction between a real and virtual image still implies a reference to visual perception which makes it problematic, yet useful for didactic purposes.

Field curvature analysis and optimization method for near-eye display systems

Near-eye display (NED) systems with a large field of view (FOV) and a large pupil are often accompanied by field curvature. In such cases, there is often a significant deviation between the virtual image seen by the human eye and an ideal plane. Currently, there is a lack of precise methods for describing and controlling the shape of virtual images in visual space. In this paper, the system is modeled, and the curvature is controlled through optimization. Under limited conditions, the system’s field curvature is controlled to approach an ideal state. When the system’s field curvature cannot be completely corrected, a method for describing the virtual image surface is introduced. This method helps optical designers effectively predict the degree of curvature and the distance of the virtual image. The image quality of the system with a curved image is evaluated and optimized based on the focusing function of the human eye. Additionally, the field curvature and pupil swim are analyzed jointly. The effectiveness of the method is verified by designing two different types of NED systems.

Understanding, Virtually: How Does the Synthetic Cell Matter?

Abstract This paper examines how scientific understanding is enhanced by virtual entities, focusing on the case of the synthetic cell. Comparing it to other virtual entities and environments in science, we argue that the synthetic cell has a virtual dimension, in that it is functionally similar to living cells, though it does not mimic any particular naturally evolved cell (nor is it constructed to do so). In being cell-like at most, the synthetic cell is akin to many other virtual objects as it is selective and only partially implemented. However, there is one important difference: it is constructed by using the same materials and, to some extent, the same kind of processes as its natural counterparts. In contrast to virtual reality, especially to that of digital entities and environments, the details of its implementation is what matters for the scientific understanding generated by the synthetic cell. We conclude by arguing for the close connection between the virtual and the artifactual.

Additive 3D printed optical waveguide for augmented reality

The mass production of augmented reality (AR) waveguides has been challenging due to the intricate nature of the fabrication technique and the high precision required for their optical characteristics. In this paper, we have presented a novel and low-cost approach for fabricating geometric optical waveguides designed for AR applications utilizing 3D printing techniques. To strike a balance between optical performance and fabrication feasibility, we have optimized the conventional geometric waveguide design to facilitate easier fabrication. It is worth noting that our proposed method does not require molding, dicing, or post-surface polishing after printing. A prototype based on this method has been successfully fabricated, showing the immersion between the virtual image and the real-world scene. The proposed method has great potential for adaptation to mass production in various AR applications.

Correlation between vertebral bone mineral density and multi-level virtual non-calcium imaging parameters from dual-layer spectral detector computed tomography

Correlation between vertebral bone mineral density and multi-level virtual non-calcium imaging parameters from dual-layer spectral detector computed tomography

The Ghost in the Machine: Metaphors of the ‘Virtual’ and the ‘Artificial’ in Post-WW2 Computer Science

Abstract Metaphors that compare the computer to a human brain are common in computer science and can be traced back to a fertile period of research that unfolded after the Second World War. To conceptualize the emerging “intelligent” properties of computing machines, researchers of the era created a series of virtual objects that served as interpretive devices for representing the immaterial functions of the computer. This paper analyses the use of the terms “artificial” and “virtual” in scientific papers, textbooks, and popular articles of the time, and examines how, together, they shaped models in computer science used to conceptualize computer processes.

The Use of Virtual Reflectance Transformation Imaging (V-RTI) in the Field of Cultural Heritage: Approaching the Materiality of an Ancient Egyptian Rock-Cut Chapel

The Use of Virtual Reflectance Transformation Imaging (V-RTI) in the Field of Cultural Heritage: Approaching the Materiality of an Ancient Egyptian Rock-Cut Chapel

Acoustic Assembly and Scanning of Superlens Arrays for High-Resolution and Large Field-of-View Bioimaging.

High-resolution and dynamic bioimaging is essential in life sciences and biomedical applications. In recent years, microspheres combined with optical microscopes have offered a low cost but promising solution for super-resolution imaging, by breaking the diffraction barrier. However, challenges still exist in precisely and parallelly superlens controlling using a noncontact manner, to meet the demands of large-area scanning imaging for desired targets. This study proposes an acoustic wavefield-based strategy for assembling and manipulating micrometer-scale superlens arrays, in addition to achieving on-demand scanning imaging through phase modulation. In experiments, acoustic pressure nodes are designed to be comparable in size to microspheres, allowing spatially dispersed microspheres to be arranged into arrays with one unit per node. Droplet microlenses with various diameters can be adapted in the array, allowing for a wide range of spacing periods by applying different frequencies. In addition, through the continuous phase shifting in the x and y directions, this acoustic superlens array achieves on-demand moving for the parallel high-resolution virtual image capturing and scanning of nanostructures and biological cell samples. As a comparison, this noncontact and cost-effective acoustic manner can obtain more than ∼100 times the acquisition efficiency of a single lens, holding promise in advancing super-resolution microscopy and subcellular-level bioimaging.