Augmented reality meeting table: a novel multi-user interface for architectural design

Immersive virtual environments have received widespread attention as providing possible replacements for the media and systems that designers traditionally use, as well as, more generally, in providing support for collaborative work. Relatively little attention has been given to date however to the problem of how to merge immersive virtual environments into real world work settings, and so to add to the media at the disposal of the designer and the design team, rather than to replace it. In this paper we report on a research project in which optical see-through augmented reality displays have been developed together with prototype decision support software for architectural and urban design. We suggest that a critical characteristic of multi user augmented reality is its ability to generate visualisations from a first person perspective in which the scale of rendition of the design model follows many of the conventions that designers are used to. Different scales of model appear to allow designers to focus on different aspects of the design under consideration. Augmenting the scene with simulations of pedestrian movement appears to assist both in scale recognition, and in moving from a first person to a third person understanding of the design. This research project is funded by the European Commission IST program (IST-2000-28559)

Sensemaking on the Pragmatic Web: A Hypermedia Discourse Perspective

The complexity of the dilemmas we face on an organizational, societal and global scale forces us into sensemaking activity. We need tools for expressing and contesting perspectives flexible enough for real time use in meetings, structured enough to help manage longer term memory, and powerful enough to filter the complexity of extended deliberation and debate on an organizational or global scale. This has been the motivation for a programme of basic and applied action research into Hypermedia Discourse, which draws on research in hypertext, information visualization, argumentation, modelling, and meeting facilitation. This paper proposes that this strand of work shares a key principle behind the Pragmatic Web concept, namely, the need to take seriously diverse perspectives and the processes of meaning negotiation. Moreover, it is argued that the hypermedia discourse tools described instantiate this principle in practical tools which permit end-user control over modelling approaches in the absence of consensus

Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

a human in the loop cyber physical system for collaborative assembly in smart manufacturing

Abstract Industry 4.0 rose with the introduction of cyber-physical systems (CPS) and Internet of things (IoT) inside manufacturing systems. CPS represent self-controlled physical processes, having tight networking capabilities and efficient interfaces for human interaction. The interactive dimension of CPS reaches its maximum when defined in terms of natural human-machine interfaces (NHMI), i.e., those reducing the technological barriers required for the interaction. This paper presents a NHMI bringing the human decision-making capabilities inside the cybernetic control loop of a smart manufacturing assembly system. The interface allows to control, coordinate and cooperate with an industrial cobot during the task execution

Adaptive Graph Contrastive Learning for Recommendation

Graph neural networks (GNNs) have recently emerged as an effective collaborative filtering (CF) approaches for recommender systems. The key idea of GNN-based recommender systems is to recursively perform message passing along user-item interaction edges to refine encoded embeddings, relying on sufficient and high-quality training data. However, user behavior data in practical recommendation scenarios is often noisy and exhibits skewed distribution. To address these issues, some recommendation approaches, such as SGL, leverage self-supervised learning to improve user representations. These approaches conduct self-supervised learning through creating contrastive views, but they depend on the tedious trial-and-error selection of augmentation methods. In this paper, we propose a novel Adaptive Graph Contrastive Learning (AdaGCL) framework that conducts data augmentation with two adaptive contrastive view generators to better empower the CF paradigm. Specifically, we use two trainable view generators - a graph generative model and a graph denoising model - to create adaptive contrastive views. With two adaptive contrastive views, AdaGCL introduces additional high-quality training signals into the CF paradigm, helping to alleviate data sparsity and noise issues. Extensive experiments on three real-world datasets demonstrate the superiority of our model over various state-of-the-art recommendation methods. Our model implementation codes are available at the link https://github.com/HKUDS/AdaGCL