19 resultados para Spatiotemporal visualization

em Universidad Politécnica de Madrid


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Cultural content on the Web is available in various domains (cultural objects, datasets, geospatial data, moving images, scholarly texts and visual resources), concerns various topics, is written in different languages, targeted to both laymen and experts, and provided by different communities (libraries, archives museums and information industry) and individuals (Figure 1). The integration of information technologies and cultural heritage content on the Web is expected to have an impact on everyday life from the point of view of institutions, communities and individuals. In particular, collaborative environment scan recreate 3D navigable worlds that can offer new insights into our cultural heritage (Chan 2007). However, the main barrier is to find and relate cultural heritage information by end-users of cultural contents, as well as by organisations and communities managing and producing them. In this paper, we explore several visualisation techniques for supporting cultural interfaces, where the role of metadata is essential for supporting the search and communication among end-users (Figure 2). A conceptual framework was developed to integrate the data, purpose, technology, impact, and form components of a collaborative environment, Our preliminary results show that collaborative environments can help with cultural heritage information sharing and communication tasks because of the way in which they provide a visual context to end-users. They can be regarded as distributed virtual reality systems that offer graphically realised, potentially infinite, digital information landscapes. Moreover, collaborative environments also provide a new way of interaction between an end-user and a cultural heritage data set. Finally, the visualisation of metadata of a dataset plays an important role in helping end-users in their search for heritage contents on the Web.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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A number of data description languages initially designed as standards for trie WWW are currently being used to implement user interfaces to programs. This is done independently of whether such programs are executed in the same or a different host as trie one running the user interface itself. The advantage of this approach is that it provides a portable, standardized, and easy to use solution for the application programmer, and a familiar behavior for the user, typically well versed in the use of WWW browsers. Among the proposed standard description languages, VRML is a aimed at representing three dimensional scenes including hyperlink capabilities. VRML is already used as an import/export format in many 3-D packages and tools, and has been shown effective in displaying complex objects and scenarios. We propose and describe a Prolog library which allows parsing and checking VRML code, transforming it, and writing it out as VRML again. The library converts such code to an internal representation based on first order terms which can then be arbitrarily manipulated. We also present as an example application the use of this library to implement a novel 3-D visualization for examining and understanding certain aspects of the behavior of CLP(FD) programs.

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We address the design and implementation of visual paradigms for observing the execution of constraint logic programs, aiming at debugging, tuning and optimization, and teaching. We focus on the display of data in CLP executions, where representation for constrained variables and for the constrains themselves are seeked. Two tools, VIFID and TRIFID, exemplifying the devised depictions, have been implemented, and are used to showcase the usefulness of the visualizations developed.

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The control part of the execution of a constraint logic program can be conceptually shown as a search-tree, where nodes correspond to calis, and whose branches represent conjunctions and disjunctions. This tree represents the search space traversed by the program, and has also a direct relationship with the amount of work performed by the program. The nodes of the tree can be used to display information regarding the state and origin of instantiation of the variables involved in each cali. This depiction can also be used for the enumeration process. These are the features implemented in APT, a tool which runs constraint logic programs while depicting a (modified) search-tree, keeping at the same time information about the state of the variables at every moment in the execution. This information can be used to replay the execution at will, both forwards and backwards in time. These views can be abstracted when the size of the execution requires it. The search-tree view is used as a framework onto which constraint-level visualizations (such as those presented in the following chapter) can be attached.

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Visualization of program executions has been used in applications which include education and debugging. However, traditional visualization techniques often fall short of expectations or are altogether inadequate for new programming paradigms, such as Constraint Logic Programming (CLP), whose declarative and operational semantics differ in some crucial ways from those of other paradigms. In particular, traditional ideas regarding the behavior of data often cannot be lifted in a straightforward way to (C)LP from other families of programming languages. In this chapter we discuss techniques for visualizing data evolution in CLP. We briefly review some previously proposed visualization paradigms, and also propose a number of (to our knowledge) novel ones. The graphical representations have been chosen based on the perceived needs of a programmer trying to analyze the behavior and characteristics of an execution. In particular, we concéntrate on the representation of the run-time valúes of the variables, and the constraints among them. Given our interest in visualizing large executions, we also pay attention to abstraction techniques, i.e., techniques which are intended to help in reducing the complexity of the visual information.

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Visualization of program executions has been found useful in applications which include education and debugging. However, traditional visualization techniques often fall short of expectations or are altogether inadequate for new programming paradigms, such as Constraint Logic Programming (CLP), whose declarative and operational semantics differ in some crucial ways from those of other paradigms. In particular, traditional ideas regarding flow control and the behavior of data often cannot be lifted in a straightforward way to (C)LP from other families of programming languages. In this paper we discuss techniques for visualizing program execution and data evolution in CLP. We briefly review some previously proposed visualization paradigms, and also propose a number of (to our knowledge) novel ones. The graphical representations have been chosen based on the perceived needs of a programmer trying to analyze the behavior and characteristics of an execution. In particular, we concéntrate on the representation of the program execution behavior (control), the runtime valúes of the variables, and the runtime constraints. Given our interest in visualizing large executions, we also pay attention to abstraction techniques, Le., techniques which are intended to help in reducing the complexity of the visual information.

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The arrangement of atoms at the surface of a solid accounts for many of its properties: Hardness, chemical activity, corrosion, etc. are dictated by the precise surface structure. Hence, finding it, has a broad range of technical and industrial applications. The ability to solve this problem opens the possibility of designing by computer materials with properties tailored to specific applications. Since the search space grows exponentially with the number of atoms, its solution cannot be achieved for arbitrarily large structures. Presently, a trial and error procedure is used: an expert proposes an structure as a candidate solution and tries a local optimization procedure on it. The solution relaxes to the local minimum in the attractor basin corresponding to the initial point, that might be the one corresponding to the global minimum or not. This procedure is very time consuming and, for reasonably sized surfaces, can take many iterations and much effort from the expert. Here we report on a visualization environment designed to steer this process in an attempt to solve bigger structures and reduce the time needed. The idea is to use an immersive environment to interact with the computation. It has immediate feedback to assess the quality of the proposed structure in order to let the expert explore the space of candidate solutions. The visualization environment is also able to communicate with the de facto local solver used for this problem. The user is then able to send trial structures to the local minimizer and track its progress as they approach the minimum. This allows for simultaneous testing of candidate structures. The system has also proved very useful as an educational tool for the field.

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Algebraic topology (homology) is used to analyze the state of spiral defect chaos in both laboratory experiments and numerical simulations of Rayleigh-Bénard convection. The analysis reveals topological asymmetries that arise when non-Boussinesq effects are present. The asymmetries are found in different flow fields in the simulations and are robust to substantial alterations to flow visualization conditions in the experiment. However, the asymmetries are not observable using conventional statistical measures. These results suggest homology may provide a new and general approach for connecting spatiotemporal observations of chaotic or turbulent patterns to theoretical models.

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In this demo paper we describe an iOS-based application that allows visualizing live bus transport data in Madrid from static and streaming RDF endpoints, reusing the Web services provided by the bus transport authority in the city and wrapping them using SPARQLStream

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In recent years, the continuous incorporation of new technologies in the learning process has been an important factor in the educational process [1]. The Technical University of Madrid (UPM) promotes educational innovation processes and develops projects related to the improvement of the education quality. The experience that we present fits into the Educational Innovation Project (EIP) of the E.U. of Agricultural Engineering of Madrid. One of the main objectives of the EIP is to "Take advantage of the new opportunities offered by the Learning and Knowledge Technologies in order to enrich the educational processes and teaching management" [2].

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Electronic devices endowed with camera platforms require new and powerful machine vision applications, which commonly include moving object detection strategies. To obtain high-quality results, the most recent strategies estimate nonparametrically background and foreground models and combine them by means of a Bayesian classifier. However, typical classifiers are limited by the use of constant prior values and they do not allow the inclusion of additional spatiodependent prior information. In this Letter, we propose an alternative Bayesian classifier that, unlike those reported before, allows the use of additional prior information obtained from any source and depending on the spatial position of each pixel.

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We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways.

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In recent years, the continuous incorporation of new technologies in the learning process has been an important factor in the educational process (1). The Technical University of Madrid (UPM) promotes educational innovation processes and develops projects related to the improvement of the education quality. The experience that we present fits into the Educational Innovation Project (EIP) of the E.U. of Agricultural Engineering of Madrid. One of the main objectives of the EIP is to Take advantage of the new opportunities offered by the Learning and Knowledge Technologies in order to enrich the educational processes and teaching management (2).