Spatial Awareness Research Articles

Translating Words to Worlds: Zero-Shot Synthesis of 3D Terrain from Textual Descriptions Using Large Language Models

The current research on text-guided 3D synthesis predominantly utilizes complex diffusion models, posing significant challenges in tasks like terrain generation. This study ventures into the direct synthesis of text-to-3D terrain in a zero-shot fashion, circumventing the need for diffusion models. By exploiting the large language model’s inherent spatial awareness, we innovatively formulate a method to update existing 3D models through text, thereby enhancing their accuracy. Specifically, we introduce a Gaussian–Voronoi map data structure that converts simplistic map summaries into detailed terrain heightmaps. Employing a chain-of-thought behavior tree approach, which combines action chains and thought trees, the model is guided to analyze a variety of textual inputs and extract relevant terrain data, effectively bridging the gap between textual descriptions and 3D models. Furthermore, we develop a text–terrain re-editing technique utilizing multiagent reasoning, allowing for the dynamic update of the terrain’s representational structure. Our experimental results indicate that this method proficiently interprets the spatial information embedded in the text and generates controllable 3D terrains with superior visual quality.

Roadside experiences of parents of children with developmental coordination disorder and/or attention deficit hyperactivity disorder

IntroductionPedestrians are a vulnerable group at the roadside and previous research has identified that children with DCD and ADHD are at a heightened risk of pedestrian injuries. Despite this, limited research has explored parental perspectives of the pedestrian risks faced by children with DCD and/or ADHD. Understanding parents’ perspectives provides a unique insight into the challenges children face every day and the concerns that parents perceive regarding their children’s safety as pedestrians. Therefore, the aim of this study was to explore parents’ perspectives of the pedestrian risks faced by their children with DCD and/or ADHD.MethodsSemi-structured interviews were conducted with 14 parents of primary school and early secondary school aged children with age range 7–17. The participants were divided into three groups based on their children’s conditions: DCD group (10–17 years, n = 3), ADHD group (7–13 years, n = 5), and co-occurring group (7–16 years, n = 6). All parents confirmed an existing diagnosis and completed the SNAP-IV and DCDQ as screening tools. The interviews explored parents’ perspectives regarding their children’s pedestrian behaviors, parents’ concerns and preventative measures taken to improve the pedestrian safety of their children with DCD and/or ADHD. Reflexive thematic analysis was undertaken to analyze the interviews, from which three themes were developed.ResultsThe first theme related to the challenges experienced by children at the roadside; parents emphasized the significance of structured and controlled pedestrian crossing sites, underlining their preference for designated crossings as safer options due to their heightened perceptions of risk associated with other road-crossing locations. The second theme: parental concerns and influences on children’s road safety referred to their children’s performance and safety at the roadside, leading to increased monitoring and a more protective approach to road crossing. The third theme: road safety education related to various strategies parents implemented to mitigate risks, while balancing independence and prioritizing their safety.DiscussionWhile there were commonalities in the challenges faced by children with DCD and/or ADHD at the roadside, there were also notable differences. Parents of children with DCD discussed challenges with spatial awareness and motor skills, whereas parents of children with ADHD discussed challenges with impulsivity and inattention. Parents of children with co-occurring DCD and ADHD described a complex interplay of these challenges. It is evident from the interviews that children with DCD and/or ADHD require a distinct approach to develop their pedestrian skills effectively and parents reported specific strategies they used to address the risks associated with their children’s roadside behavior. Promoting pedestrian safety for children with DCD and/or ADHD necessitates collaboration among parents, schools and local authorities to implement comprehensive measures ensuring their safety. These findings contribute to understanding parental experiences and needs, providing valuable guidance for targeted interventions and policies to enhance the road safety of children with DCD and/or ADHD.

GBC-BCD: an improved bridge crack detection method based on bidirectional Laplacian pyramid structure with lightweight attention mechanism convolution

ABSTRACT As roads continue to expand globally, the construction of a larger number of bridges has significantly increased the burden on bridge maintenance. Traditional methods for bridge crack detection often suffer from low efficiency and accuracy. To address these issues, we propose an efficient one-stage bridge crack detection method called GBC-BCD based on the YOLOv8n framework. To improve the model’s performance, we introduce the Coordinated Attention mechanism to enhance spatial context awareness and the Bidirectional Feature Pyramid Network to strengthen the ability of feature fusion and multi-scale feature learning. At the same time, in order to make the model more efficient while improving its performance, we introduce the Ghost Module, which significantly reduces the size of the model and raises the speed of object detection. Moreover, we employ transfer learning to improve training efficiency and conserve computational resources for small datasets. Experiments show that our model has the characteristics of lightweight and high speed. Compared with famous lightweight object detection algorithms, the model size is at most reduced by 86.6%, and realises real-time (625 FPS) processing of images ( 640 × 640 ), an 8.3 times increment in speed.

The Spatial Awareness Behind the Naming of Social Groups and Geographical Areas in Mainland South Sulawesi

In the sociological paradigm of space, as a place whatever its form and name as long as it is inhabited or used as a base for human activity, it is not a passive natural entity but rather dynamic. This is made possible by the spatial dialectics and social reproduction that take place accompanying the development of a space along with the meaning of it which is always changing and dynamic. This paper examines spatial identity in naming social groups and geographical areas in Sulawesi using place identity theory, social identity theory, and identity process theory. This type of research is a literature review with a sociology of space approach that uses data and analysis descriptively from a number of relevant literature. The results showed that some social group names in Sulawesi are a representation of the geographical structure of a space, so that when mentioning the name of the group or its residential center, it will reflect its spatial identity. This fact is sociologically a spatial awareness that has been created in the long history of Sulawesi as well as can be categorized as local community intelligence

Basic Analysis of Physical Determinants Affecting the Distribution Density of Senior Citizen Centers around Small Apartment Complexes, Focusing on Administrative Districts in Busan

The role of senior citizen centers is becoming more important, with a greater emphasis placed on ensuring that these establishments facilitate leisure and communication for older adults. These developments are taking place as population aging has now become an irreversible global trend. However, there is still a lack of systematic research on predicting the distribution density of senior citizen centers based on physical factors in urban planning. Therefore, this study set each administrative district in Busan as a unit and investigated physical factors affecting the distribution density of senior citizen centers around small apartment complexes to validate their effectiveness. First, the spatial hierarchy of each administrative district in Busan was examined. The city was divided into administrative districts while focusing on the distribution density of senior citizen centers (the dependent variable) around small apartment complexes where older adults live (within a 500 m radius). The spatial accessibility of senior citizen centers and the number of apartments in each administrative district were set as independent variables. This selection was made to verify the effectiveness of the physical factors by conducting an independent sample t-test, normality test, Friedman test, and two-way ANOVA. The chief findings of this study are as follows. (1) The spatial awareness of each administrative district was low, and there were large disparities in the land development density relative to the spatial scale of the administrative districts. (2) Regarding the physical factors affecting the distribution density of senior citizen centers, the spatial accessibility of senior residences was more significant than the number of small apartment complexes nearby. (3) Personal and social factors may have indirectly influenced the distribution density of senior citizen centers more than physical factors, depending on the type of house in which the older adults live. The findings will provide a theoretical basis for determining the location and distribution density of senior citizen centers in urban planning considering physical factors, as well as serve as a reference for public policy decisions related to the allocation of such centers in the future.

Less Is More: Label Recommendation for Weakly Supervised Point Cloud Semantic Segmentation

Weak supervision has proven to be an effective strategy for reducing the burden of annotating semantic segmentation tasks in 3D space. However, unconstrained or heuristic weakly supervised annotation forms may lead to suboptimal label efficiency. To address this issue, we propose a novel label recommendation framework for weakly supervised point cloud semantic segmentation. Distinct from pre-training and active learning, the label recommendation framework consists of three stages: inductive bias learning, recommendations for points to be labeled, and point cloud semantic segmentation learning. In practice, we first introduce the point cloud upsampling task to induct inductive bias from structural information. During the recommendation stage, we present a cross-scene clustering strategy to generate centers of clustering as recommended points. Then we introduce a recommended point positions attention module LabelAttention to model the long-range dependency under sparse annotations. Additionally, we employ position encoding to enhance the spatial awareness of semantic features. Throughout the framework, the useful information obtained from inductive bias learning is propagated to subsequent semantic segmentation networks in the form of label positions. Experimental results demonstrate that our framework outperforms weakly supervised point cloud semantic segmentation methods and other methods for labeling efficiency on S3DIS and ScanNetV2, even at an extremely low label rate.

Dancing Presence and Awareness:

In this article, I argue that the dance practice of ‘Khaita – Joyful Dances’ has been intentionally designed as a mindfulness practice with the aim of fostering presence and awareness by the Dzogchen master Namkhai Norbu. The three Khaita principles of awareness (Dems, Gyu and Drig) revolve around aspects of proprioception, smooth movements, musicality, spatial and group awareness and guide dancers to the here and now. They demand non-judgmental, purposeful and non-reactive attention, hence mindfulness, that results in more mature states of awareness and presence

VR based gesture elicitation for user—Interfaces with low vision

<p>User interfaces (UI) and menus in virtual reality (VR), which frequently replicate traditional UI for computers and smartphones, are not created factoring for individuals with low eyesight as they demand accurate pointing and good vision to engage effectively. As an alternative method of user interaction with UI, using gestures can be recommended. Comparing gesture-based interaction with the conventional point-and-click technique for changing system settings like volume, brightness, and window manipulation in order to test this hypothesis is employed. Accessibility, spatial awareness, and precision for those with low vision while lowering cognitive load and enhancing immersion for all users can be improved by leveraging gestures. The objective of the research work is to explore the framework of Gesture Elicitation in VR environments for users with low vision. In this research work the usage of gestures as a more effective and immersive means of interacting with menus, which will not only enhance the experience of normal VR users but also drastically reduce the friction experienced by those with visual impairments is proposed. User studies demonstrate a noticeable improvement in the aforementioned areas, with faster work completion times, more immersion, and better user satisfaction.</p>

Virtual Reality‐Enabled Intuitive Magnetic Manipulation of Microrobots and Nanoparticles

Magnetic microrobots and nanoparticles offer unique capabilities for medical applications by granting unprecedented access to intricate and delicate anatomical structures. Nevertheless, an intuitive manipulation approach remains a challenge due to their small size and limited feedback. This study presents a new method for magnetic microrobot and nanoparticle control that employs virtual reality (VR), creating an immersive and realistic view of the bodily anatomy and the microrobot within. This study compares three manipulation modes: a traditional mode using 2D displays, VR mode using a VR headset and touch controllers, and VR autonomous programmed maneuvering. It is shown that VR‐assisted modes reduce the manipulation time by improving spatial awareness. Nanoparticles in a VR environment are also manipulated. The proposed method will find applications in terms of intuitive, immersive microrobots or magnetic nanoparticle control in complex biological environments, thus in many medical procedures and for drug and cell delivery. The immersive nature of this approach enhances the ability of the user to perceive and understand complex anatomical structures, facilitating better navigation within delicate environments; both dexterity and spatial awareness are improved. Thus, it is shown how microrobots and magnetic nanoparticles can be controlled using immersive simulations to improve both visualization and manipulation.

ResNet50-Boosted UNet for Improved Liver Segmentation Accuracy

Segmentation of the liver from abdominal CT images is difficult due to changes in form, density, and the presence of malignancies. This research describes a novel strategy to improve segmentation accuracy that uses UNet as a foundation architecture and ResNet50 as a backbone architecture. This integrated design automates feature selection and spatial awareness, overcoming limitations in previous models. Experimental evaluations using the LiTS dataset show higher performance. Specifically, using the LiTS dataset, our algorithm achieves a remarkable foreground accuracy of 99.81% in liver segmentation. These results outperform existing approaches, demonstrating UNet and ResNet50's potential as valuable tools for precise liver segmentation in clinical situations. The suggested system shows promise for application in diverse medical imaging tasks other than liver segmentation, demonstrating its versatility and effectiveness in enhancing machine-assisted medical diagnostics and decision-making processes.

Using Eye-Tracking for Adaptive Human-Machine Interfaces for Pilots: A Literature Review and Sample Cases

This paper explores the potential of eye-tracking technology in adaptive human-machine interfaces for pilots in aviation. We argue that an interface able to adjust its layout and elements based on pilots’ real-time eye-tracking data can prevent errors and enhance their performance. The study presents a literature review on the use of eye-tracking for various pilot cases, including flight simulator games, drone pilots, and cockpit pilots. Results in most cases showed that eye-tracking has been employed to improve interactions, enhance spatial awareness, guide pilots’ gaze to relevant areas, and provide insights into pilots’ information processing and task load. The paper discusses two sample cases demonstrating the potential of eye-tracking in adaptive human-machine interfaces. In the first case, during challenging drone simulations, eye-tracking identified areas where an adaptive human-machine interface could aid navigation and reduce cognitive load. In the second one, based on real drone flights, when signal loss incidents occurred, eye-tracking data showed that the interface should adapt to pilots’ needs by providing critical information to help them to improve situational awareness. The paper concludes that eye-tracking technology has significant potential in adaptive human-machine interfaces for aviation, emphasising the importance of refining these technologies to meet pilots’ specific needs and enhance flight safety.

Wayfinding in immersive virtual environments as social activity supported by virtual agents

Effective navigation and interaction within immersive virtual environments (IVEs) rely on thorough scene exploration. Therefore, wayfinding is essential, assisting users in comprehending their surroundings, planning routes, and making informed decisions. Based on real-life observations, wayfinding is, thereby, not only a cognitive process but also a social activity profoundly influenced by the presence and behaviors of others. In virtual environments, these “others” are virtual agents (VAs), defined as anthropomorphic computer-controlled characters, who enliven the environment and can serve as background characters or direct interaction partners. However, less research has been conducted to explore how to efficiently use VAs as social wayfinding support. In this paper, we aim to assess and contrast user experience, user comfort, and acquisition of scene knowledge through a between-subjects study involving n = 60 participants across three distinct wayfinding conditions in one slightly populated urban environment: (i) unsupported wayfinding, (ii) strong social wayfinding using a virtual supporter who incorporates guiding and accompanying elements while directly impacting the participants’ wayfinding decisions, and (iii) weak social wayfinding using flows of VAs that subtly influence the participants’ wayfinding decisions by their locomotion behavior. Our work is the first to compare the impact of VAs’ behavior in virtual reality on users’ scene exploration, including spatial awareness, scene comprehension, and comfort. The results show the general utility of social wayfinding support, while underscoring the superiority of the strong type. Nevertheless, further exploration of weak social wayfinding as a promising technique is needed. Thus, our work contributes to the enhancement of VAs as advanced user interfaces, increasing user acceptance and usability.

Character and Peacebuilding in Islamic Pedagogy, 'Tazkiyah' and 'Taaruf' Concepts as A Case Study

This study highlights how character and peacebuilding education is manifested within Islamic pedagogy. Islamic pedagogy promotes three crucial aspects to nurture character development: spirit, mind, and body. Its curriculum seeks to cultivate specific areas with the potential to create a healthy generation imbued with critical self-consciousness and critical other consciousness. This study examines two concepts deeply rooted in Islamic education philosophy, namely 'Tazkiyaah' and 'Taaruf', as critical elements shaping individual personality and broad cross-cultural relations. Islamic pedagogy is reenacting human character to contribute to designing a world that fits everyone, regardless of their differences. Islamic pedagogy is a teaching philosophy that focuses on the spirit, mind, body, and space. Spatial awareness is also needed for human beings; 'Taaruf' is the keyword in shaping this type of learning.

CROS or hearing aid? Selecting the ideal solution for unilateral CI patients with limited aidable hearing in the contralateral ear.

A hearing aid or a contralateral routing of signal device are options for unilateral cochlear implant listeners with limited hearing in the unimplanted ear; however, it is uncertain which device provides greater benefit beyond unilateral listening alone. Eighteen unilateral cochlear implant listeners participated in this prospective, within-participants, repeated measures study. Participants were tested with the cochlear implant alone, cochlear implant + hearing aid, and cochlear implant + contralateral routing of signal device configurations with a one-month take-home period between each in-person visit. Audiograms, speech perception in noise, and lateralization were evaluated. Subjective feedback was obtained via questionnaires. Marked improvement in speech in noise and non-implanted ear lateralization accuracy were observed with the addition of a contralateral hearing aid. There were no significant differences in speech recognition between listening configurations. However, the chronic device use questionnaires and the final device selection showed a clear preference for the hearing aid in spatial awareness and communication domains. Individuals with limited hearing in their unimplanted ears demonstrate significant improvement with the addition of a contralateral device. Subjective questionnaires somewhat contrast with clinic-based outcome measures, highlighting the delicate decision-making process involved in clinically advising one device or another to maximize communication benefits.

Exploration of the Utilization of Foreign Museum Resources in Junior High School World History Contextual Teaching – A Case Study on the Meiji Restoration

Addressing common issues in junior high school world history learning, such as unfamiliar content and weak spatial awareness, effectively using foreign museum resources in teaching through contextual methods proves to be a successful strategy. When selecting contextual teaching resources, it is crucial to adhere to principles based on student needs, teaching content, and the correct value orientation. Implementation should be based on students' experiences to achieve significant teaching results.

Enhancing wayfinding and route learning: a human-centred study of the route-defining locations algorithm

ABSTRACT Navigation services play a crucial role in everyday wayfinding. One of their key features is the turn-by-turn guidance, enabling wayfinders to navigate efficiently between locations. However, over-reliance on turn-by-turn guidance can hinder wayfinders' ability to perceive their surroundings and develop spatial awareness, negatively impacting user experience. Previous research has addressed these issues by modifying instructions, user interaction, or both. However, the applicability of these methods beyond specific studies remains unclear. This paper presents a human-centred study by evaluating an algorithm that automatically generates navigation instructions. The instructions are generated by adding route-defining locations to ‘standard’ turn-by-turn instructions to enhance wayfinder's spatial knowledge acquisition, and improve user experience. Route-defining locations, identified using a previously proposed algorithm, serve as anchors for the wayfinder to form a spatial understanding of the environment. The study involved 36 participants divided into two groups: one received ‘standard’ turn-by-turn (TBT) instructions, while the other received instructions that included route-defining locations (RDL). Participants navigated in an unfamiliar virtual environment, and their wayfinding and route learning were compared between the two groups. Results show that RDL instructions led to better wayfinding and route learning performance compared to TBT instructions, suggesting the potential to improve navigation systems and user experiences.

A Virtual Reality Scene Taxonomy: Identifying and Designing Accessible Scene-Viewing Techniques

Virtual environments (VEs) afford similar interactions to those in physical environments: individuals can navigate and manipulate objects. Yet, a prerequisite for these interactions is being able to view the environment. Despite the existence of numerous scene-viewing techniques (i.e., interaction techniques that facilitate the visual perception of virtual scenes), there is no guidance to help designers choose which techniques to implement. We propose a scene taxonomy based on the visual structure and task within a VE by drawing on literature from cognitive psychology and computer vision, as well as virtual reality (VR) applications. We demonstrate how the taxonomy can be used by applying it to an accessibility problem, namely limited head mobility. We used the taxonomy to classify existing scene-viewing techniques and generate three new techniques that do not require head movement. In our evaluation of the techniques with 16 participants, we discovered that participants identified tradeoffs in design considerations such as accessibility, realism, and spatial awareness, that would influence whether they would use the new techniques. Our results demonstrate the potential of the scene taxonomy to help designers reason about the relationships between VR interactions, tasks, and environments.

Investigating the Role of Geography Education in Natural Resource Management

Geography education plays a pivotal role in natural resource management by fostering an understanding of optimal conservation practices. Through comprehensive examination of regional environments and geography, we can gauge the impact of human activities on natural resources and propose sustainable solutions. By increasing environmental awareness, geography education elucidates the repercussions of activities such as deforestation, pollution, biodiversity loss, and climate change. This heightened awareness empowers us to refine policies and management practices, ensuring the judicious utilization and preservation of natural resources. This article underscores the paramount importance of geography education in natural resource preservation. Employing an applied and descriptive approach, the research methodology involves library studies. The findings highlight that geography education establishes vital links between individuals and their environment, facilitating informed resource management decisions. By analyzing regional geography and its influence on natural resources, optimal preservation strategies emerge. For instance, studying precipitation patterns enables efficient water management and drought mitigation. Ultimately, geography education equips us with the knowledge and tools to identify effective resource preservation methods, fostering sustainable utilization practices through enhanced environmental comprehension and spatial awareness.

The Reliability of the Senaptec Sensory Station for the Comprehensive Assessment of Sensorimotor Skills in College-Aged Individuals

ABSTRACT This study determined the test-retest reliability of 10 sensorimotor skills assessed by the Senaptec Sensory Station in a population of 100 (80 female, age = 21.6 ± 2.8 years) college-aged individuals (18–30 years). Separate intraclass correlation coefficients (ICCs) with a two-way mixed-effects model, absolute agreement, and 95% confidence intervals (CIs) were calculated. Additionally, the standard error of measurement and minimal detectable change values were determined to examine clinical applicability. Go/no-go, multiple-object tracking, eye-hand coordination, depth perception, and reaction time demonstrated good reliability (ICCs = 0.81–0.88). Target capture and perception span demonstrated moderate reliability (ICCs = 0.51–0.63). Visual clarity, contrast sensitivity, and near-far quickness demonstrated poor reliability (ICCs = 0.28–0.43). Assessments involving decision-making, anticipation, and spatial awareness demonstrated good reliability, while most assessments of visual skills demonstrated poor reliability. Overall, go/no-go, multiple-object tracking, eye-hand coordination, depth perception, and reaction time from the Senaptec Sensory Station are reliable and can be administered clinically in a healthy, college-aged population.

MSE-Net: A novel master–slave encoding network for remote sensing scene classification

Remote sensing scene (RSS) image classification plays a vital role in various fields such as urban planning and environmental protection. However, due to higher inter-class similarity and intra-class variability, achieving accurate classification for RSS images poses a considerable challenge for current convolutional neural networks (CNNs)-based and visual transformer (ViT)-based methods. To address these issues, this paper proposes a novel dual-encoding method named master–slave encoding network (MSE-Net) from two perspectives of feature extraction and fusion. The master encoder, based on ViT, extracts higher-level semantic features, while the slave encoder, based on CNN, captures relative lower-level spatial structure information. Secondly, to integrate feature information from the two encoders effectively, this paper further develop two fusion strategies. The first strategy involves the auxiliary enhancement units (AEUs), which eliminates semantic divergence between the two encoders, enhances spatial context awareness of the slave encoder and promotes effective feature learning. The interactive perception unit (IPU), as the second strategy, facilitates interaction and integration of the two encoders’ representations to extract more discriminative feature information. In addition, we conducted comparative experiments on four widely-used RSS datasets, including RSSCN7, SIRI-WHU, the aerial image dataset (AID) and NWPU-RESISC45 (NWPU45), to verify the effectiveness of MSE-Net. The experimental results demonstrate that MSE-Net achieved state-of-the-art (SOTA) performance across all the datasets.