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Spatial judgments are important for many real-world tasks in engineering and scientific visualization. While existing research provides evidence that higher levels of display and interaction fidelity in virtual reality systems offer advantages for spatial understanding, few investigations have focused on small-scale spatial judgments or employed experimental tasks similar to those used in real-world applications. After an earlier study that considered a broad analysis of various spatial understanding tasks, we present the results of a follow-up study focusing on small-scale spatial judgments. In this research, we independently controlled field of regard, stereoscopy, and head-tracked rendering to study their effects on the performance of a task involving precise spatial inspections of complex 3D structures. Measuring time and errors, we asked participants to distinguish between structural gaps and intersections between components of 3D models designed to be similar to real underground cave systems. The overall results suggest that the addition of the higher fidelity system features support performance improvements in making small-scale spatial judgments. Through analyses of the effects of individual system components, the experiment shows that participants made significantly fewer errors with either an increased field of regard or with the addition of head-tracked rendering. The results also indicate that participants performed significantly faster when the system provided the combination of stereo and head-tracked rendering.
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http://dx.doi.org/10.1109/TVCG.2012.163 | DOI Listing |
Environ Monit Assess
September 2025
Department of Geosciences, University of Bremen, Bremen, Germany.
Surveillance monitoring of shallow groundwater revealed that redox conditions can vary on a small scale. Therefore, the aim of this study was to categorize redox conditions in the groundwater of Lower Saxony, Germany, and to analyze the spatial distribution and trends of parameters related to redox conditions during surveillance monitoring from 1957 to 2015 in Lower Saxony, Germany. Methodically, trends were considered by applying the Mann-Kendall test and redox conditions of groundwater were classified according to the scheme of Jurgens et al.
View Article and Find Full Text PDFAdv Healthc Mater
September 2025
School of Chemistry and Chemical Engineering, Guangdong Provincial Key Lab of Green Chemical Product Technology, South China University of Technology, Guangzhou, 510640, P. R. China.
Photonic crystal (PC) hydrogel-based sensors with visual signal outputs have attracted attention for wearable motion monitoring, but current devices suffer from low spatial resolution, small-scale design, and poor signal consistency. Herein, we present a combined and scalable PC sensing platform that includes a single-point sensor (100 × 400 mm) and an 8 × 8 multipixel array (100 × 100 mm) for dual-mode visual-electrical feedback. The array achieves 2D strain mapping on the arm with a spatial resolution of 0.
View Article and Find Full Text PDFChanges in population responses to climate are usually studied at broad spatial grains, such as across species ranges. Only a handful of studies have investigated how small-scale variation, for example driven by soil conditions and microtopography, can mediate the responses of population vital rates to climate. Here, we examine responses of vital rates to climate across five subpopulations occurring in coastal dune locations that range from the foredune to the backdune.
View Article and Find Full Text PDFLangmuir
September 2025
School of Mechanical Engineering, Inner Mongolia University of Science & Technology, Baotou 014010, China.
Diamond-like carbon (DLC) is famous for its extraordinary mechanical properties in tribology applications. Despite the growing interest and achievements in exploiting more advanced DLC, unveiling the deformation mechanisms, especially in the plastic regime, remains a great challenge. Here, molecular dynamics (MD) simulation, as an computational microscopy technique, was employed to probe the atomically structural and mechanical responses in DLC with a certain density to nanoindentation.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Computer Science, University of Tsukuba, Tsukuba, 3058577, Japan.
Deep learning has achieved significant success in pattern recognition, with convolutional neural networks (CNNs) serving as a foundational architecture for extracting spatial features from images. Quantum computing provides an alternative computational framework, a hybrid quantum-classical convolutional neural networks (QCCNNs) leverage high-dimensional Hilbert spaces and entanglement to surpass classical CNNs in image classification accuracy under comparable architectures. Despite performance improvements, QCCNNs typically use fixed quantum layers without incorporating trainable quantum parameters.
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