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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Ryan Ray Wantouw Oei Theo Justin Amantha Jennifer Marcellyn Cen Rhio Sutoyo Said Achmad Esther Widhi Andangsari Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Psychology Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

Millions are fighting to maintain mental well-being in our high-pressure world. Stress, isolation, and mental illnesses can all be relentless foes, and neglecting them can have a domino effect on physical health, leading to a decline in overall well-being. Technological advances, particularly spatial computing, offer promising solutions to this problem. spatial computing's main feature is the contextualization of digital information within users' physical environments. Past studies have shown that this feature can support mental health by enabling remote therapy delivery and providing immersive therapeutic environments anywhere, at any time. While most studies on spatial computing in mental health highlight its benefits, the potential drawbacks and societal integration challenges remain largely unexplored. This work is a systematic literature review aimed at identifying opportunities for integrating spatial computing into mental healthcare, as well as the challenges it could face upon entering society and any potentially negative impacts it may have. The findings demonstrate that spatial computing can improve mental well-being through enhanced accessibility and immersive experiences. However, integration challenges and potentially negative impacts of spatial computing were also concerning, such as high costs and the risk of addiction. Due to the lack of extensive studies on these aspects, the findings on integration challenges and potential negative impacts require further investigation. Future research and real-world applications of spatial computing are necessary to validate this study's findings and uncover any underlying effects.

关键词： Costs Addiction Medical treatment Mental health Real-time systems Mobile handsets spatial computing Monitoring Systematic literature review Guidelines

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Folding Reality: Learning spatial computing through VR Interactive Paper Folding Game

Folding Reality: Learning Spatial Computing through VR Inter...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Mengyao Guo Shunan Zhang Zhenran Xu Yuyang Jiang Yikun Fang Harbin Institute of Technology Shenzhen The Hong Kong University of Science and Technology Guangzhou Royal College of Art London

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

We introduce "Folding Reality" for conducting research on training spatial computing in virtual reality scenarios. It is designed for children and Large Multimodal Models (LMMs). We aim to understand how creativity emerges during the 2D to 3D folding process through interactive data gathered from children’s engagement with the game. We will then use this data to train LMMs, providing them an opportunity to enhance their spatial computing abilities through interactive paper folding. Our goal is to create a learning environment where both children and LMM can explore and understand spatial relationships, advancing research in this field.

关键词： Training Solid modeling Three-dimensional displays Computational modeling Conferences Virtual reality Games User interfaces spatial computing Creativity

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IRIS: A 8.55mJ/frame spatial computing SoC for Interactable Rendering and Surface-Aware Modeling with 3D Gaussian Splatting

IRIS: A 8.55mJ/frame Spatial Computing SoC for Interactable ...

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IEEE International Conference on Solid-State Circuits (ISSCC)

作者： Seokchan Song Seryeong Kim Wonhoon Park Jongjun Park Sanghyuk An Gwangtae Park Minseo Kim Hoi-Jun Yoo KAIST Daejeon Korea

ISBN: (数字)9798331541019

ISBN: (纸本)9798331541026

Interactive spatial computing (ISC) enables immersive mixed reality (MR) applications, which demand a real-time and user-interactive 3D graphics system [1]–[3]. This requires real-time surface-aware modeling (SAM) to transfer a physical object to the virtual world, and interactive photorealistic rendering (IPR) is required to present the deformed virtual 3D object, as shown in Fig. 2.7.1 [4]–[5]. Neural Radiance Field (NeRF) accelerators [7]–[8] are unable to realize ISC since they cannot support surface extraction and deformation [9].30 Gaussian Splatting (3DGS) with free-deforming algorithms [10]–[11] enables high-quality rendering for deformed objects, but its realization on a high-power-consumption (>5W) edge GPU [12] requires >20minutes for SAM and >400ms for IPR due to its massive external memory access (EMA) and huge computational requirements. In general, there are three hardware challenges to realize a mobile 3DGS accelerator. First, the parameters of 3DGS (>50MB for over 500K Gaussians) far exceed the L2 cache size of an edge GPU (4MB on the Jetson Orin Nano [12]), while being stored in an unordered manner incurs frequent irregular DRAM accesses [14], [19]. Its EMA occupies 81.3% of the system energy consumption, even after parameter pruning schemes are applied [16]. Thus, the Single-Embedding-Multi-MLP (SEMM)-Compressed 3DGS based on a state-of-the-art MLP-based compression approach [15] is adopted, but EMA still constitutes 52.8% of system energy. Second, spatial computing requires to accelerate IPR within a 15ms latency to provide real-time user interaction [23]. However, the three sequential stages of IPR - deform, reflect, and render - require 2.33x more processing time compared to non-interactive rendering on previous 3DGS hardware [13]. Third, backpropagation (BP) consumes -55.8% of the computations in SAM due to FP16 high-precision calculation and limited reusability.

关键词： Solid modeling Three-dimensional displays Computational modeling Graphics processing units Intellectual property Rendering (computer graphics) Neural radiance field Real-time systems Hardware spatial computing

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spatial computing Opportunities in Biomedical Decision Support: The Atlas-EHR Vision

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ACM TRANSACTIONS ON spatial ALGORITHMS AND SYSTEMS 2024年第3期10卷 1-36页

作者： Farhadloo, Majid Sharma, Arun Shekhar, Shashi Markovic, Svetomir Univ Minnesota Twin Cities Comp Sci Minneapolis MN 55455 USA Mayo Clin Oncol Rochester MN USA

We consider the problem of reducing the time that healthcare professionals need to understand the patient's medical history through the next generation of biomedical decision support. This problem is societally important because it has the potential to improve healthcare quality and patient outcomes. However, navigating electronic health records (EHR) is challenging due to high patient-doctor ratios, potentially long medical histories, urgency of treatment for some medical conditions, and patient variability. The current EHR systems provide only a longitudinal view of patient medical history, which is time-consuming to browse, and doctors often need to engage nurses, residents, and others for initial analysis. To overcome this limitation, we envision an alternative spatial representation of patient histories (e.g., electronic health records) and other biomedical data in the form of Atlas-EHR. Just like Google Maps, which allows a global, national, regional, and local view, Atlas-EHR can start with an overview of the patient's anatomy and history before drilling down to spatially anatomical subsystems, their individual components, or subcomponents. Atlas-EHR presents a compelling opportunity for spatial computing since healthcare is almost a fifth of the US economy. However, traditional spatial computing designed for geographic use cases (e.g., navigation, land survey, and mapping) faces many hurdles in the biomedical domain. This article presents several open research questions under this theme in five broad areas of spatial computing.

关键词： Atlas-EHR biomedical decision support inner space spatial computing vision

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spatial computing: Defining the Vision for the Future

Spatial Computing: Defining the Vision for the Future

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ACM CHI Conference on Human Factors in computing Sytems (CHI)

作者： Xu, Jiangnan Papangelis, Konstantinos Tigwell, Garreth W. LaLone, Nicolas Zhou, Pengyuan Saker, Michael Chamberlain, Alan Dunham, John Luna, Sanzida Mojib Schwartz, David Rochester Inst Technol Niant xRIT Geo Games & Media Res Lab Rochester NY 14623 USA Rochester Inst Technol Sch Informat Rochester NY USA Rochester Inst Technol Sch Interact Games & Media Rochester NY USA Univ Sci & Technol China Hefei Anhui Peoples R China City Univ London London England Univ Nottingham Nottingham England Rochester Inst Technol Rochester NY USA

ISBN: (纸本)9798400703317

spatial computing integrates technologies like Mixed Reality, Artificial Intelligence, and the Global Positioning System, enabling immersive, natural, and intelligent multi-modal interactions in physical and virtual spaces. With the huge potential to benefit users in multiple scenarios (e.g., gaming, education, design, and healthcare), spatial computing is growing at an incredible rate, with different attempts to define and capitalize on the growth in both industry and academia. Beyond the location, shape, and relationship of geographic objects, spatial computing delves into the social, emotional, and cognitive dimensions of shared spaces. However, the human-computer interaction research on spatial computing faces a notable gap, particularly in user experience areas like collaboration, trust, ethics, and accessibility. Addressing this gap, this Special Interest Group (SIG) seeks to unite experts from academia and industry to explore current and future trends in spatial computing.

关键词： spatial computing Artificial Intelligent Mixed Reality Augmented Reality Location-based Media Human-Computer Interaction Special Interests Group

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spatial computing perspective on food energy and water nexus

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Journal of Environmental Studies and Sciences 2016年第1期6卷 62-76页

作者： Eftelioglu, Emre Jiang, Zhe Ali, Reem Shekhar, Shashi University of Minnesota Minneapolis MN United States

In the coming decades, the increasing world population is expected to grow the demand for food, energy, and water resources. In addition, these resources will be under stress due to the climate change and urbanization. Previously, more problems were caused by piecemeal approaches analyzing and planning those resources independent of each other. The goal of the food, energy, and water (FEW) nexus approach is to prevent such problems by understanding, appreciating, and visualizing the interconnections and interdependencies of FEW resources at local, regional, and global levels. The nexus approach seeks to use the FEW resources as an interrelated system of systems, but data and modeling constraints make it a challenging task. In addition, the lack of complete knowledge and observability of FEW interactions exacerbates the problem. Related work focused on physical science solutions (e.g., desalination, bio-pesticides). No doubt these are necessary and worthwhile for FEW resource security. Overlooked in these work is that spatial computing may help domain scientists achieve their goals for the FEW nexus. In this paper, we describe our vision of the spatial computing’s role in understanding the FEW nexus using a Nexus Dashboard analogy. From a spatial data lifecycle perspective, we provide more details on the spatial computing components behind the Nexus Dashboard vision. In each component, we list new technical challenges that are likely to drive future spatial computing research. © 2016, AESS.

关键词： Food, energy, and water nexus Precision agriculture spatial computing Sustainability System of systems

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spatial computing Through an HCI Lens - UX Evaluation Based on Situatedness 26th

Spatial Computing Through an HCI Lens - UX Evaluation Based ...

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26th International Conference on Human-Computer Interaction (HCII)

作者： Pott, Katja Agotai, Doris Univ Appl Sci & Arts Northwestern Switzerland FHN Inst Interact Technol IIT Windisch Switzerland

ISBN: (纸本)9783031619496;9783031619502

The field of spatial computing is attracting increasing attention. Despite this, aspects related to user experience and evaluation methods are not yet established. The current state of the art in UX and UX evaluation needs to be extended to include aspects that are usually not considered when interacting with mobile or desktop applications. In spatial computing, devices are aware of 3-dimensional physical space and enable human actions with spatial meaning. However, it is important that applications consider not only the user's environment from a spatial perspective, but also other relevant contextual aspects such as the emotions of a place, the surrounding community, and the broader goals of the activity. This approach provides a new perspective and is complementary to the current state of the art. This paper presents three examples of applications in spatial computing and demonstrates the potential aspects to be considered in the context of the experience and how the interaction could be evaluated, using an open-ended interpretive methodology. It explores methods and aspects relevant to spatial computing, highlighting opportunities and tools for evaluating the user experience. This encourages a more comprehensive approach and allows to analyse a situation holistically. The results indicate that while methods and considerations exist, there is currently no coherent methodology that integrates all relevant aspects. This finding may provide the basis for a new perspective on spatial computing and highlights the great potential of this technology to provide exceptional user experiences.

关键词： spatial computing Augmented Reality UX Evaluation 3D Interaction Perception

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spatial computing using Null Convention Logic

Spatial Computing using Null Convention Logic

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IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)

作者： Haque, Kashfia Jakob, Conrad Sovani, Renuka Beckett, Paul RMIT Univ Sch Elect & Comp Engn Melbourne Vic Australia Crunch DSP Pty Ltd Melbourne Vic Australia

ISBN: (纸本)9781467387866

We present the design and organization of an homogeneous asynchronous bit-level array based on Null Convention Logic. A bit element (bel) array represents a bit-level hybrid processor that exhibits both spatial and Temporal computing characteristics. The bit elements are organized in a 2D grid, with eight-way connectivity. Programs represented as Directed Acyclic Graphs can be mapped to the array either fully statically or with a small level of element reuse (dynamic mapping).

关键词： asynchronous computing spatial computing NCL

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spatial computing Meets Realistic Mobile Wireless Problems

Spatial Computing Meets Realistic Mobile Wireless Problems

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7th IEEE International Conference on Self-Adaptation and Self-Organizing Systems (SASO)

作者： Wiandt, Bernat Simon, Vilmos Kokuti, Andras Beal, Jacob Inter Univ Ctr Telecommun & Informat London England Budapest Univ Technol & Econ Budapest Hungary Raytheon BBN Technol Cambridge MA USA

ISBN: (纸本)9781479950874

Controlling and leveraging the vast and ever-growing number of wireless devices around us has become a serious problem. spatial computing offers a promising approach toward solving this problem, in the form of higher-level distributed programming abstractions. Many challenging mobile communications problems, however, can only be investigated using a realistic and detailed model of wireless communication. We thus demonstrate a new research platform, integrating the MIT Proto spatial computing suite with the OMNeT++ network simulator framework, which will enable investigation of spatial computing solutions to difficult mobile wireless problems.

关键词： mobile ad hoc self organizing spatial computing wireless communication CARRIER SYSTEM wireless device ad hoc wireless Mobile

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The foundation of self-developing blob machines for spatial computing

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PHYSICA D-NONLINEAR PHENOMENA 2008年第9期237卷 1282-1301页

作者： Gruau, Frederic Eisenbeis, Christine Maignan, Luidnel Inria Futurs Saclay Parc Orsay Univ F-91893 Orsay France Univ Paris 11 LRI F-91405 Orsay France Lab Informat Robot & Microelect Montpellier F-34000 Montpellier France Univ W England Bristol BS16 1QY Avon England

The current trend in electronics is to integrate more and more transistors on a chip and produce massive hardware resources. As a consequence, traditional computing models, which mainly compute in the temporal domain, do not work well anymore since it becomes increasingly difficult to orchestrate these massive-scale hardware resources in a centralized way. spatial computing is a unifying term that embodies many unconventional computing models and means computing on a relatively homogeneous physical medium made of hardware components, where the communication time is dependent on the Euclidean distance between the components (locality constraint). This constraint makes the programming for high performance significantly more complex compared to classical non-spatial hardware because performance now depends on where computation happens in space (mapping problem). Blob computing is a new approach that addresses this parallel computing challenge in a radically new and unconventional way: it decouples the mapping of computations onto the hardware from the software programming while still elegantly exploiting the space of the underlying hardware. Hardware mapping of computations is done by a physical force-based approach that simulates forces between threads of computation (automata). Attractive forces are used to keep automata that need to communicate with each other closer while repulsive forces are used for load balancing. The advantage of these primitives is that they are simple enough to be implemented on an arbitrary computing medium. They form the basis of a runtime system (RTS) that transforms an arbitrary computing medium into an easier-to-program virtual machine called the blob machine. The basic objects of the blob machine are those automata, and the instructions let automata create new automata in specific ways so as to maintain a hierarchical organization (which facilitates both the mapping and the programming). We detail the basic instructions of the blob mach

关键词： spatial computing distributed algorithm self-developing network computer architecture computer language

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