PATAXÓ: A Framework to Allow Updates Through XML Views

XML has become an important medium for data exchange, and is frequently used as an interface to (i.e., a view of) a relational database. Although a lot of work has been done on querying relational databases through XML views, the problem of updating relational databases through XML views has not received much attention. In this work, we map XML views expressed using a subset of XQuery to a corresponding set of relational views. Thus, we transform the problem of updating relational databases through XML views into a classical problem of updating relational databases through relational views. We then show how updates on the XML view are mapped to updates on the corresponding relational views. Existing work on updating relational views can then be leveraged to determine whether or not the relational views are updatable with respect to the relational updates, and if so, to translate the updates to the underlying relational database

Algebraic incremental maintenance of XML views

International audienceMaterialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state of the art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments

Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates

Neural radiance field is an emerging rendering method that generates high-quality multi-view consistent images from a neural scene representation and volume rendering. Although neural radiance field-based techniques are robust for scene reconstruction, their ability to add or remove objects remains limited. This paper proposes a new language-driven approach for object manipulation with neural radiance fields through dataset updates. Specifically, to insert a new foreground object represented by a set of multi-view images into a background radiance field, we use a text-to-image diffusion model to learn and generate combined images that fuse the object of interest into the given background across views. These combined images are then used for refining the background radiance field so that we can render view-consistent images containing both the object and the background. To ensure view consistency, we propose a dataset updates strategy that prioritizes radiance field training with camera views close to the already-trained views prior to propagating the training to remaining views. We show that under the same dataset updates strategy, we can easily adapt our method for object insertion using data from text-to-3D models as well as object removal. Experimental results show that our method generates photorealistic images of the edited scenes, and outperforms state-of-the-art methods in 3D reconstruction and neural radiance field blending

Updatable Process Views for User-centered Adaption of Large Process Models

The increasing adoption of process-aware information systems (PAISs) has resulted in large process model collections. To support users having different perspectives on these processes and related data, a PAIS should provide personalized views on process models. Existing PAISs, however, do not provide mechanisms for creating or even changing such process views. Especially, changing process models is a frequent use case in PAISs due to changing needs or unplanned situations. While process views have been used as abstractions for visualizing large process models, no work exists on how to change process models based on respective views. This paper presents an approach for changing large process models through updates of corresponding process views, while ensuring up-to-dateness and consistency of all other process views on the process model changed. Respective update operations can be applied to a process view and corresponding changes be correctly propagated to the underlying process model. Furthermore, all other views related to this process model are then migrated to the new version of the process model as well. Overall, our view framework enables domain experts to evolve large process models over time based on appropriate model abstractions

Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views

Learning object-centric representations of multi-object scenes is a promising approach towards machine intelligence, facilitating high-level reasoning and control from visual sensory data. However, current approaches for unsupervised object-centric scene representation are incapable of aggregating information from multiple observations of a scene. As a result, these "single-view" methods form their representations of a 3D scene based only on a single 2D observation (view). Naturally, this leads to several inaccuracies, with these methods falling victim to single-view spatial ambiguities. To address this, we propose The Multi-View and Multi-Object Network (MulMON) -- a method for learning accurate, object-centric representations of multi-object scenes by leveraging multiple views. In order to sidestep the main technical difficulty of the multi-object-multi-view scenario -- maintaining object correspondences across views -- MulMON iteratively updates the latent object representations for a scene over multiple views. To ensure that these iterative updates do indeed aggregate spatial information to form a complete 3D scene understanding, MulMON is asked to predict the appearance of the scene from novel viewpoints during training. Through experiments, we show that MulMON better-resolves spatial ambiguities than single-view methods -- learning more accurate and disentangled object representations -- and also achieves new functionality in predicting object segmentations for novel viewpoints.Comment: Accepted at NeurIPS 2020 (Spotlight

Lossless Selection Views under Constraints

The problem of updating a database through a set of views consists in propagat-ing updates of the views to the base relations over which the view relations are defined, so that the changes to the database reflect exactly those to the views. This is a classical problem in database research, known as the view update prob

Younger adolescents’ perceptions of physical activity, exergaming, and virtual reality:qualitative intervention development study

Background. Novel strategies to promote physical activity (PA) in adolescence are required. The vEngage study aims to test whether a virtual reality (VR) exergaming intervention can engage younger adolescents (13-15 year old) with physical activity. Objective: This study aimed to gather adolescents’ views of using VR to encourage PA and identify the key features they would like to see in a VR exergaming intervention via interviews. Methods: Participants were recruited through two schools in London, UK. Semi-structured interviews were conducted with adolescents about their views on PA and what might work to increase PA, technology, knowledge and experience of VR, and desired features in a VR exergaming intervention. Data were analysed using Framework Analysis. Results: 31 13-15 year olds (58% female, 62% from non-white ethnicities) participated in this interview study. The vast majority had no awareness of government PA recommendations, but felt they should be more thoroughly informed. All participants were positive about the use of VR in PA promotion. Rewards, increasing challenges and a social/multiplayer aspect were identified by participants as crucial aspects to include in a VR exercise game. Barriers were related to cost of high-end systems. Being able to exercise at home was very appealing. VR exergaming was viewed as a way to overcome multiple perceived social and cultural barriers to PA, particularly for girls. Conclusions: Key elements that should be incorporated into a VR for health intervention were identified and described. These also included the use of rewards, novelty and enjoyment in immersive game play, multi-player options, real-world elements, as well as continual updates and new challenge levels. The use of VR to promote PA in adolescents is promising, but some barriers were raised

A Review of integrity constraint maintenance and view updating techniques

Two interrelated problems may arise when updating a database. On one hand, when an update is applied to the database, integrity constraints may become violated. In such case, the integrity constraint maintenance approach tries to obtain additional updates to keep integrity constraints satisfied. On the other hand, when updates of derived or view facts are requested, a view updating mechanism must be applied to translate the update request into correct updates of the underlying base facts. This survey reviews the research performed on integrity constraint maintenance and view updating. It is proposed a general framework to classify and to compare methods that tackle integrity constraint maintenance and/or view updating. Then, we analyze some of these methods in more detail to identify their actual contribution and the main limitations they may present.Postprint (published version

Efficient Bayesian-based Multi-View Deconvolution

Light sheet fluorescence microscopy is able to image large specimen with high resolution by imaging the sam- ples from multiple angles. Multi-view deconvolution can significantly improve the resolution and contrast of the images, but its application has been limited due to the large size of the datasets. Here we present a Bayesian- based derivation of multi-view deconvolution that drastically improves the convergence time and provide a fast implementation utilizing graphics hardware.Comment: 48 pages, 20 figures, 1 table, under review at Nature Method