1,717 research outputs found

    The Impact of a Supernova Explosion in a Very Massive Binary

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    We consider the effect of a supernova (SN) explosion in a very massive binary that is expected to form in a portion of Population III stars with the mass higher than 100MM_\odot. In a Population III binary system, a more massive star can result in the formation of a BH and a surrounding accretion disc. Such BH accretion could be a significant source of the cosmic reionization in the early universe. However, a less massive companion star evolves belatedly and eventually undergoes a SN explosion, so that the accretion disc around a BH might be blown off in a lifetime of companion star. In this paper, we explore the dynamical impact of a SN explosion on an accretion disc around a massive BH, and elucidate whether the BH accretion disc is totally demolished or not. For the purpose, we perform three-dimensional hydrodynamic simulations of a very massive binary system, where we assume a BH of 103M10^3 M_{\odot} that results from a direct collapse of a very massive star and a companion star of 100M100 M_{\odot} that undergoes a SN explosion. We calculate the remaining mass of a BH accretion disc as a function of time. As a result, it is found that a significant portion of gas disc can survive through three-dimensional geometrical effects even after the SN explosion of a companion star. Even if the SN explosion energy is higher by two orders of magnitude than the binding energy of gas disc, about a half of disc can be left over. The results imply that the Population III BH accretion disc can be a long-lived luminous source, and therefore could be an important ionizing source in the early universe.Comment: 12 pages, 9 figures, accepted for publication in MNRAS, for high resolution figures, see http://www.rccp.tsukuba.ac.jp/Astro/Members/junichi/sus2008.pd

    pyParaOcean: A System for Visual Analysis of Ocean Data

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    Visual analysis is well adopted within the field of oceanography for the analysis of model simulations, detection of different phenomena and events, and tracking of dynamic processes. With increasing data sizes and the availability of multivariate dynamic data, there is a growing need for scalable and extensible tools for visualization and interactive exploration. We describe pyParaOcean, a visualization system that supports several tasks routinely used in the visual analysis of ocean data. The system is available as a plugin to Paraview and is hence able to leverage its distributed computing capabilities and its rich set of generic analysis and visualization functionalities. pyParaOcean provides modules to support different visual analysis tasks specific to ocean data, such as eddy identification and salinity movement tracking. These modules are available as Paraview filters and this seamless integration results in a system that is easy to install and use. A case study on the Bay of Bengal illustrates the utility of the system for the study of ocean phenomena and processes.Comment: 8 pages, EnvirVis202

    How to Read a Visualization Research Paper: Extracting the Essentials

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    Introduction. Women's sexual pain disorders include dyspareunia and vaginismus and there is need for state-of-the-art information in this area. Aim. To update the scientific evidence published in 2004, from the 2nd International Consultation on Sexual Medicine pertaining to the diagnosis and treatment of women's sexual pain disorders. Methods. An expert committee, invited from six countries by the 3rd International Consultation, was comprised of eight researchers and clinicians from biological and social science disciplines, for the purpose of reviewing and grading the scientific evidence on nosology, etiology, diagnosis, and treatment of women's sexual pain disorders. Main Outcome Measure. Expert opinion was based on grading of evidence-based medical literature, extensive internal committee discussion, public presentation, and debate. Results. A comprehensive assessment of medical, sexual, and psychosocial history is recommended for diagnosis and management. Indications for general and focused pelvic genital examination are identified. Evidence-based recommendations for assessment of women's sexual pain disorders are reviewed. An evidence-based approach to management of these disorders is provided. Conclusions. Continued efforts are warranted to conduct research and scientific reporting on the optimal assessment and management of women's sexual pain disorders, including multidisciplinary approaches. van Lankveld JJDM, Granot M, Weijmar Schultz WCM, Binik YM, Wesselmann U, Pukall CF, Bohm-Starke N, and Achtrari C. Women's sexual pain disorders. J Sex Med 2010;7:615-631

    ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

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    Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms

    How to Read a Visualization Research Paper: Extracting the Essentials

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    EXTRACTING FLOW FEATURES USING BAG-OF-FEATURES AND SUPERVISED LEARNING TECHNIQUES

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    Measuring the similarity between two streamlines is fundamental to many important flow data analysis and visualization tasks such as feature detection, pattern querying and streamline clustering. This dissertation presents a novel streamline similarity measure inspired by the bag-of-features concept from computer vision. Different from other streamline similarity measures, the proposed one considers both the distribution of and the distances among features along a streamline. The proposed measure is tested in two common tasks in vector field exploration: streamline similarity query and streamline clustering. Compared with a recent streamline similarity measure, the proposed measure allows users to see the interesting features more clearly in a complicated vector field. In addition to focusing on similar streamlines through streamline similarity query or clustering, users sometimes want to group and see similar features from different streamlines. For example, it is useful to find all the spirals contained in different streamlines and present them to users. To this end, this dissertation proposes to segment each streamline into different features. This problem has not been studied extensively in flow visualization. For instance, many flow feature extraction techniques segment streamline based on simple heuristics such as accumulative curvature or arc length, and, as a result, the segments they found usually do not directly correspond to complete flow features. This dissertation proposes a machine learning-based streamline segmentation algorithm to segment each streamline into distinct features. It is shown that the proposed method can locate interesting features (e.g., a spiral in a streamline) more accurately than some other flow feature extraction methods. Since streamlines are space curves, the proposed method also serves as a general curve segmentation method and may be applied in other fields such as computer vision. Besides flow visualization, a pedagogical visualization tool DTEvisual for teaching access control is also discussed in this dissertation. Domain Type Enforcement (DTE) is a powerful abstraction for teaching students about modern models of access control in operating systems. With DTEvisual, students have an environment for visualizing a DTE-based policy using graphs, visually modifying the policy, and animating the common DTE queries in real time. A user study of DTEvisual suggests that the tool is helpful for students to understand DTE

    Adaptive remote visualization system with optimized network performance for large scale scientific data

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    This dissertation discusses algorithmic and implementation aspects of an automatically configurable remote visualization system, which optimally decomposes and adaptively maps the visualization pipeline to a wide-area network. The first node typically serves as a data server that generates or stores raw data sets and a remote client resides on the last node equipped with a display device ranging from a personal desktop to a powerwall. Intermediate nodes can be located anywhere on the network and often include workstations, clusters, or custom rendering engines. We employ a regression model-based network daemon to estimate the effective bandwidth and minimal delay of a transport path using active traffic measurement. Data processing time is predicted for various visualization algorithms using block partition and statistical technique. Based on the link measurements, node characteristics, and module properties, we strategically organize visualization pipeline modules such as filtering, geometry generation, rendering, and display into groups, and dynamically assign them to appropriate network nodes to achieve minimal total delay for post-processing or maximal frame rate for streaming applications. We propose polynomial-time algorithms using the dynamic programming method to compute the optimal solutions for the problems of pipeline decomposition and network mapping under different constraints. A parallel based remote visualization system, which comprises a logical group of autonomous nodes that cooperate to enable sharing, selection, and aggregation of various types of resources distributed over a network, is implemented and deployed at geographically distributed nodes for experimental testing. Our system is capable of handling a complete spectrum of remote visualization tasks expertly including post processing, computational steering and wireless sensor network monitoring. Visualization functionalities such as isosurface, ray casting, streamline, linear integral convolution (LIC) are supported in our system. The proposed decomposition and mapping scheme is generic and can be applied to other network-oriented computation applications whose computing components form a linear arrangement

    Reactant Jetting in Unstable Detonation

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    We note the common existence of a supersonic jet structure locally embedded within a surrounding transonic flow field in the hitherto unrelated phenomena of unstable gaseous detonation and hypervelocity blunt body shock wave interaction. Extending prior results that demonstrate the consequences of reduced endothermic reaction rate for the supersonic jet fluid in the blunt body case, we provide an explanation for observations of locally reduced OH PLIF signal in images of the keystone reaction zone structure of weakly unstable detonations. Modeling these flow features as exothermically reacting jets with similarly reduced reaction rates, we demonstrate a mechanism for jetting of bulk pockets of unreacted fluid with potentially differing kinetic pathways into the region behind the primary detonation front of strongly unstable mixtures. We examine the impact of mono-atomic and diatomic diluents on transverse structure. The results yield insight into the mechanisms of transition and characteristic features of both weakly and strongly unstable mixtures

    Streamlining Digital Modeling and Building Information Modelling (BIM) Uses for the Oil and Gas Projects

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    The oil and gas industry is a technology-driven industry. Over the last two decades, it has heavily made use of digital modeling and associated technologies (DMAT) to enhance its commercial capability. Meanwhile, the Building Information Modelling (BIM) has grown at an exponential rate in the built environment sector. It is not only a digital representation of physical and functional characteristics of a facility, but it has also made an impact on the management processes of building project lifecycle. It is apparent that there are many similarities between BIM and DMAT usability in the aspect of physical modeling and functionality. The aim of this study is to streamline the usage of both DMAT and BIM whilst discovering valuable practices for performance improvement in the oil and gas projects. To achieve this, 28 BIM guidelines, 83 DMAT academic publications and 101 DMAT vendor case studies were selected for review. The findings uncover (a) 38 BIM uses; (b) 32 DMAT uses and; (c) 36 both DMAT and BIM uses. The synergy between DMAT and BIM uses would render insightful references into managing efficient oil and gas’s projects. It also helps project stakeholders to recognise future investment or potential development areas of BIM and DMAT uses in their projects

    Advanced Mobile Robotics: Volume 3

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    Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective
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