975 research outputs found

    Cross-Platform Presentation of Interactive Volumetric Imagery

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    Volume data is useful across many disciplines, not just medicine. Thus, it is very important that researchers have a simple and lightweight method of sharing and reproducing such volumetric data. In this paper, we explore some of the challenges associated with volume rendering, both from a classical sense and from the context of Web3D technologies. We describe and evaluate the pro- posed X3D Volume Rendering Component and its associated styles for their suitability in the visualization of several types of image data. Additionally, we examine the ability for a minimal X3D node set to capture provenance and semantic information from outside ontologies in metadata and integrate it with the scene graph

    The Iray Light Transport Simulation and Rendering System

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    While ray tracing has become increasingly common and path tracing is well understood by now, a major challenge lies in crafting an easy-to-use and efficient system implementing these technologies. Following a purely physically-based paradigm while still allowing for artistic workflows, the Iray light transport simulation and rendering system allows for rendering complex scenes by the push of a button and thus makes accurate light transport simulation widely available. In this document we discuss the challenges and implementation choices that follow from our primary design decisions, demonstrating that such a rendering system can be made a practical, scalable, and efficient real-world application that has been adopted by various companies across many fields and is in use by many industry professionals today

    Automated Design of Dynamic Programming Schemes for RNA Folding with Pseudoknots

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    Despite being a textbook application of dynamic programming (DP) and routine task in RNA structure analysis, RNA secondary structure prediction remains challenging whenever pseudoknots come into play. To circumvent the NP-hardness of energy minimization in realistic energy models, specialized algorithms have been proposed for restricted conformation classes that capture the most frequently observed configurations. While these methods rely on hand-crafted DP schemes, we generalize and fully automatize the design of DP pseudoknot prediction algorithms. We formalize the problem of designing DP algorithms for an (infinite) class of conformations, modeled by (a finite number of) fatgraphs, and automatically build DP schemes minimizing their algorithmic complexity. We propose an algorithm for the problem, based on the tree-decomposition of a well-chosen representative structure, which we simplify and reinterpret as a DP scheme. The algorithm is fixed-parameter tractable for the tree-width tw of the fatgraph, and its output represents a ?(n^{tw+1}) algorithm for predicting the MFE folding of an RNA of length n. Our general framework supports general energy models, partition function computations, recursive substructures and partial folding, and could pave the way for algebraic dynamic programming beyond the context-free case

    Enriching MATLAB with aspect-oriented features for developing embedded systems

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    This article presents an approach to enrich the MATLAB language with aspect-oriented modularity features, enabling developers to experiment different implementation characteristics and to acquire runtime data and traces without polluting their base MATLAB code. We propose a language through which programmers configure the low-level data representation of variables and expressions. Examples include specifically-tailored fixed-point data representations leading to more efficient support for the underlying hardware, e.g., digital signal processors and application-specific architectures, without built-in floating point units. This approach assists developers in adding handlers and monitoring features in a non-invasive way as well as configuring MATLAB functions with optimized implementations. Different aspect modules can be used to retarget common MATLAB code bases for different purposes and implementations. We validate the proposed approach with a set of representative examples where we attain a simple way to explore a number of properties. Experiment results and collected aspect-oriented software metrics lend support to the claims on its usefulness.This work was partially supported by FCT (Portuguese Science Foundation) under the project AMADEUS (POCTI, PTDC/EIA/70271/2006)

    The Mental Database

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    This article uses database, evolution and physics considerations to suggest how the mind stores and processes its data. Its innovations in its approach lie in:- A) The comparison between the capabilities of the mind to those of a modern relational database while conserving phenomenality. The strong functional similarity of the two systems leads to the conclusion that the mind may be profitably described as being a mental database. The need for material/mental bridging and addressing indexes is discussed. B) The consideration of what neural correlates of consciousness (NCC) between sensorimotor data and instrumented observation one can hope to obtain using current biophysics. It is deduced that what is seen using the various brain scanning methods reflects only that part of current activity transactions (e.g. visualizing) which update and interrogate the mind, but not the contents of the integrated mental database which constitutes the mind itself. This approach yields reasons why there is much neural activity in an area to which a conscious function is ascribed (e.g. the amygdala is associated with fear), yet there is no visible part of its activity which can be clearly identified as phenomenal. The concept is then situated in a Penrosian expanded physical environment, requiring evolutionary continuity, modularity and phenomenality.Several novel Darwinian advantages arising from the approach are described

    Automatic light source placement for maximum visual information recovery

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    The definitive version is available at http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8659.2007.00944.x/abstractThe automatic selection of good viewing parameters is a very complex problem. In most cases, the notion of good strongly depends on the concrete application. Moreover, when an intuitive definition of good view is available, it is often difficult to establish a measure that brings it to the practice. Commonly, two kinds of viewing parameters must be set: camera parameters (position and orientation) and lighting parameters (number of light sources, its position and eventually the orientation of the spot). The first ones will determine how much of the geometry can be captured and the latter will influence on how much of it is revealed (i. e. illuminated) to the user. Unfortunately, ensuring that certain parts of a scene are lit does not make sure that the details will be communicated to the user, as the amount of illumination might be too small or too high. In this paper we define a metric to calculate the amount of information relative to an object that is effectively communicated to the user given a fixed camera position. This measure is based on an information-based concept, the Shannon entropy, and will be applied to the problem of automatic selection of light positions in order to adequately illuminate an object. In order to validate the results, we have carried out an experiment on users, this experiment helped us to explore other related measures.Preprin

    From here to human-level AI

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    AbstractHuman-level AI will be achieved, but new ideas are almost certainly needed, so a date cannot be reliably predicted—maybe five years, maybe five hundred years. I'd be inclined to bet on this 21st century.It is not surprising that human-level AI has proved difficult and progress has been slow—though there has been important progress. The slowness and the demand to exploit what has been discovered has led many to mistakenly redefine AI, sometimes in ways that preclude human-level AI—by relegating to humans parts of the task that human-level computer programs would have to do. In the terminology of this paper, it amounts to settling for a bounded informatic situation instead of the more general common sense informatic situation.Overcoming the “brittleness” of present AI systems and reaching human-level AI requires programs that deal with the common sense informatic situation—in which the phenomena to be taken into account in achieving a goal are not fixed in advance.We discuss reaching human-level AI, emphasizing logical AI and especially emphasizing representation problems of information and of reasoning. Ideas for reasoning in the common sense informatic situation include nonmonotonic reasoning, approximate concepts, formalized contexts and introspection

    CPL: A Core Language for Cloud Computing -- Technical Report

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    Running distributed applications in the cloud involves deployment. That is, distribution and configuration of application services and middleware infrastructure. The considerable complexity of these tasks resulted in the emergence of declarative JSON-based domain-specific deployment languages to develop deployment programs. However, existing deployment programs unsafely compose artifacts written in different languages, leading to bugs that are hard to detect before run time. Furthermore, deployment languages do not provide extension points for custom implementations of existing cloud services such as application-specific load balancing policies. To address these shortcomings, we propose CPL (Cloud Platform Language), a statically-typed core language for programming both distributed applications as well as their deployment on a cloud platform. In CPL, application services and deployment programs interact through statically typed, extensible interfaces, and an application can trigger further deployment at run time. We provide a formal semantics of CPL and demonstrate that it enables type-safe, composable and extensible libraries of service combinators, such as load balancing and fault tolerance.Comment: Technical report accompanying the MODULARITY '16 submissio
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