As an evolving successor to the mobile Internet, the extended reality (XR) devices can generate a fully digital immersive environment similar to the real world, integrating integrating virtual and ...real-world elements. However, in addition to the difficulties encountered in traditional communications, there emerge a range of new challenges such as ultra-massive access, real-time synchronization as well as unprecedented amount of multi-modal data transmission and processing. To address these challenges, semantic communications might be harnessed in support of XR applications, whereas it lacks a practical and effective performance metric. For broadening a new path for evaluating semantic communications, in this paper, we construct a multi-user uplink non-orthogonal multiple access (NOMA) system to analyze its transmission performance by harnessing a novel metric called age of incorrect information (AoII). First, we derive the average semantic similarity of all the users based on DeepSC and obtain the closed-form expressions for the packets' age of information (AoI) relying on queue theory. Besides, we formulate a non-convex optimization problem for the proposed AoII which combines both error-and AoI-based performance under the constraints of semantic rate, transmit power and status update rate. Finally, in order to solve the problem, we apply an exact linear search based algorithm for finding the optimal policy. Simulation results show that the AoII metric can beneficially evaluate both the error- and AoI-based transmission performance simultaneously.
In this paper a novel joint sensing, communication, and artificial intelligence (AI) framework is proposed so as to optimize extended reality (XR) experiences over terahertz (THz) wireless systems. ...Within this framework, active reconfigurable intelligent surfaces (RISs) are incorporated as as pivotal elements, serving as enhanced base stations in the THz band to enhance Line-of-Sight (LoS) communication. The proposed framework consists of three main components. First , a tensor decomposition framework is proposed to extract unique sensing parameters for XR users and their environment by exploiting the THz channel sparsity. Essentially, THz band's quasi-opticality is exploited and the sensing parameters are extracted from the uplink communication signal, thereby allowing for the use of the same waveform, spectrum, and hardware for both communication and sensing functionalities . Then, the Cramer-Rao lower bound is derived to assess the accuracy of the estimated sensing parameters. Second , a non-autoregressive multi-resolution generative artificial intelligence (AI) framework integrated with an adversarial transformer is proposed to predict missing and future sensing information. The proposed framework offers robust and comprehensive historical sensing information and anticipatory forecasts of future environmental changes, which are generalizable to fluctuations in both known and unforeseen user behaviors and environmental conditions . Third , a multi-agent deep recurrent hysteretic Q-neural network is developed to control the handover policy of RIS subarrays, leveraging the informative nature of sensing information to minimize handover cost, maximize the individual quality of personal experiences (QoPEs), and improve the robustness and resilience of THz links. Simulation results show a high generalizability of the proposed unsupervised generative AI framework to fluctuations in user behavior and velocity, leading to a 61% improvement in instantaneous reliability compared to schemes with known channel state information.
Virtual reality (VR) is rapidly developed and bringing advancement in various related technologies through the virtual world. It has high potential and plays an important role in education and ...training fields. Mixed reality (MR) is a type of hybrid system that involves both physical and virtual elements. While VR/MR has proved to be an effective way to improve the learning attitude and effectiveness for secondary students, however, not much work has been conducted on university students to compare the MR experience and traditional teaching approaches in learning design subjects. In this project, we investigated the effectiveness of students in learning design subjects with the support of MR. The effectiveness was measured based on their creativity and systematic approaches in design. Pretests and posttests were conducted to measure the learning effects. We also compared the learning effectiveness of a student’s study with the MR and traditional teaching materials. Nonparametric analyses were conducted to investigate whether the improvements were significant. Experimental results showed that after studying with the support of the MR technology, the students’ abilities in geometric analysis (mean difference = 4.36,
p
< 0.01) and creativity (mean difference = 1.59,
p
< 0.05) were significantly improved. The students’ ability in model visualization was also significantly better than the control group (mean difference = 3.08,
p
< 0.05). It indicated that the results were positive by using the MR to support their study. The MR was also better than using traditional teaching notes in various measured effects.
Recent advances in extended reality (XR) technologies have enabled new and increasingly realistic empathy tools and experiences. In XR, all interactions take place in different spatial contexts, all ...with different features, affordances, and constraints. We present a systematic literature survey of recent work on empathy in XR. As a result, we contribute a research roadmap with three future opportunities and six open questions in XR-enabled empathy research across both physical and virtual spaces.
X-ray reflection (XR) and surface grazing incidence X-ray diffraction GIXD) techniques have traditionally been used to evaluate the structure of soft interfacial films. In recent years, the use of ...synchrotron radiation and two-dimensional detectors has enabled high resolution and high speed measurements of interfacial films, which makes it possible to evaluate more detailed and complex interfacial film structures and adsorption dynamics. In this review, we will provide an overview of recent progress in structural characterization of simple oil/water interfaces, interfacial films of biologically relevant materials, oil/water interfaces for extraction of rare metal ions, and adsorption of nanoparticles. Examples of the application of time-resolved XR methods and surface sensitive techniques such as GISAXS and surface X-ray fluorescence analysis will also be presented.
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Experiences in immersive 3D virtual reality (VR) are more presence‐inducing, and so it may be tempting to claim that content will be learned better in VR. This randomized control trial study on ...natural selection challenges that assumption. This study answers the question of whether learning STEM in an immersive 3D VR environment is always superior to learning via a 2D monitor (PC). This is a 2 × 2 × 3 design. The first factor is platform immersivity (low = 2D PC, or high = 3D VR), the second factor is level of embodiment (lower = watching playback video, or higher = using mouse/controller to agentically manipulate content), and the third factor is test time (pretest, posttest, and follow‐up). There was a significant main effect for embodiment, the high embodied and agentic groups learned the most. There was not a main effect for platform, because the participants in the low embodied VR group performed significantly worse than the three other groups. Although, the one high embodied, VR group learned and retained the most knowledge. A path‐analysis revealed that the effect of platform was significantly mediated by presence, agency, and engagement. The smaller learning gain in the low embodied VR condition suggests that participants come to the immersive VR experience with expectations about agency and control of the virtual content, and when those expectations were not met, the disconnect was deleterious for learning. More agentic and interactive control of manipulable virtual content is encouraged. Design is critical, and platform is not destiny.
Lay Description
What is already known about this topic?
VR has special affordances like presence and embodied content manipulation that can increase learning, if used correctly.
Compared to 2D desktop, being in 3D VR generally induces more presence and more engagement.
When students physically reenact, using gesture or embodied learning, greater learning gains are often seen.
What this paper adds?
The high embodied, active VR group learned the most and reported the most engagement.
Overall, being active and embodied resulted in more learning (regardless of the platform of desktop or VR).
Embedded and embodied kinesthetic in‐process assessments during gameplay are valid measures of comprehension.
The pathways leading to post‐play and 1 week follow‐up knowledge are complex.
Implications for practice and/or policy?
Designers should strive to create embodied and agentic tasks in educational VR games.
Watching a playback video on a 2D PC (desktop) platform can be appropriate for learning, but passive viewing videos in immersive VR can attenuate learning.
Designers should include more embedded, in‐process data gathering during educational gameplay.
Some guidelines are given for in‐process assessments, these assessments can lead to more dynamic, adaptive learning.
With increasing utilization of medical imaging in clinical practice and the growing dimensions of data volumes generated by various medical imaging modalities, the distribution, storage, and ...management of digital medical image data sets requires data compression. Over the past few decades, several image compression standards have been proposed by international standardization organizations. This paper discusses the current status of these image compression standards in medical imaging applications together with some of the legal and regulatory issues surrounding the use of compression in medical settings.
Cisplatin is a major cancer chemotherapeutic drug. It kills cancer cells by damaging their DNA, mainly in the form of Pt-d(GpG) diadducts. However, it also has serious side effects, including ...nephrotoxicity and hepatotoxicity that limit its usefulness. Chronotherapy is taking circadian time into account during therapy to improve the therapeutic index, by improving efficacy and/or limiting toxicity. To this end, we tested the impact of clock time on excision repair of cisplatin-induced DNA damage at single-nucleotide resolution across the genome in mouse kidney and liver. We found that genome repair is controlled by two circadian programs. Repair of the transcribed strand (TS) of active, circadian-controlled genes is dictated by each gene’s phase of transcription, which falls across the circadian cycle with prominent peaks at dawn and dusk. In contrast, repair of the nontranscribed strand (NTS) of all genes, repair of intergenic DNA, and global repair overall peaks at Zeitgeber time ZT08, as basal repair capacity, which is controlled by the circadian clock, peaks at this circadian time. Consequently, the TS and NTS of many genes are repaired out of phase. As most cancers are thought to have defective circadian rhythms, these results suggest that future research on timed dosage of cisplatin could potentially reduce damage to healthy tissue and improve its therapeutic index.
Artificial Intelligence (AI) covers a broad spectrum of computational problems and use cases. Many of those implicate profound and sometimes intricate questions of how humans interact or should ...interact with AIs. Moreover, many users or future users do have abstract ideas of what AI is, significantly depending on the specific embodiment of AI applications. Human-centered-design approaches would suggest evaluating the impact of different embodiments on human perception of and interaction with AI. An approach that is difficult to realize due to the sheer complexity of application fields and embodiments in reality. However, here XR opens new possibilities to research human-AI interactions. The article’s contribution is twofold: First, it provides a theoretical treatment and model of human-AI interaction based on an XR-AI continuum as a framework for and a perspective of different approaches of XR-AI combinations. It motivates XR-AI combinations as a method to learn about the effects of prospective human-AI interfaces and shows
why
the combination of XR and AI fruitfully contributes to a valid and systematic investigation of human-AI interactions and interfaces. Second, the article provides two exemplary experiments investigating the aforementioned approach for two distinct AI-systems. The first experiment reveals an interesting gender effect in human-robot interaction, while the second experiment reveals an Eliza effect of a recommender system. Here the article introduces two paradigmatic implementations of the proposed XR testbed for human-AI interactions and interfaces and shows
how
a valid and systematic investigation can be conducted. In sum, the article opens new perspectives on how XR benefits human-centered AI design and development.
We propose a novel representation of virtual humans for highly realistic real-time animation and rendering in 3D applications. We learn pose dependent appearance and geometry from highly accurate ...dynamic mesh sequences obtained from state-of-the-art multiview-video reconstruction. Learning pose-dependent appearance and geometry from mesh sequences poses significant challenges, as it requires the network to learn the intricate shape and articulated motion of a human body. However, statistical body models like SMPL provide valuable a-priori knowledge which we leverage in order to constrain the dimension of the search space, enabling more efficient and targeted learning and to define pose-dependency. Instead of directly learning absolute pose-dependent geometry, we learn the difference between the observed geometry and the fitted SMPL model. This allows us to encode both pose-dependent appearance and geometry in the consistent UV space of the SMPL model. This approach not only ensures a high level of realism but also facilitates streamlined processing and rendering of virtual humans in real-time scenarios.
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