Networks analysts often need to compare nodes in different parts of a network. When zoomed to fit a computer screen, the detailed structure and node labels of even a moderately-sized network (say, with 500 nodes) can ...
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ISBN:
(纸本)9780819494276
Networks analysts often need to compare nodes in different parts of a network. When zoomed to fit a computer screen, the detailed structure and node labels of even a moderately-sized network (say, with 500 nodes) can become invisible or difficult to read. Still, the coarse network structure typically remains visible, and helps orient an analyst's zooming, scrolling, and panning operations. These operations are very useful when studying details and reading node labels, but in the process of zooming in on one network region, an analyst may lose track of details elsewhere. To address such problems, we present in this paper multi-focus and multi-window techniques that improve interactive exploration of networks. Based on an analyst's selection of focus nodes, our techniques partition and selectively zoom in on network details, including node labels, close to the focus nodes. Detailed data associated with the zoomed-in nodes can thus be more easily accessed and inspected. The approach enables a user to simultaneously focus on and analyze multiple node neighborhoods while keeping the full network structure in view. We demonstrate our technique by showing how it supports interactive debugging of a Bayesian network model of an electrical power system. In addition, we show that it can simplify visual analysis of an electrical power network as well as a medical Bayesian network.
Taking 3D borehole data for research object, an algorithm flow of volume rendering based GPU is given. According to the limited and discrete characteristics of 3D borehole data, Kriging interpolation algorithm is used...
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Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling, result in jagged artifacts around features and losses of hi...
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Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling, result in jagged artifacts around features and losses of high-frequency components. Based on the example-based up scaling framework, this paper presents a new high-quality volume up scaling technique, predicting the high-frequency components by searching for the best matched patch in the input volume. As each slice can be taken as an image, the existing image up scaling technique based on the local self-similarity assumption can be directly applied to achieve slice up scaling. We further validate that the local self-similarity assumption is still valid for 3D volumes, and we extend this technique to 3D volume up scaling, i.e., isotropic volume up scaling. We compare our volume up scaling technique with traditional linear and cubic spline interpolations, and demonstrate that our method can generate a higher quality volume with better shape and details preserved. The proposed volume up scaling technique is well suitable for legacy low-resolution volumes to improve their visual qualities in visualization and analysis.
Conversion of unorganized point clouds to surface reconstructions is increasingly required in the mobile robotics perception processing pipeline, particularly with the rapid adoption of RGB-D (color and depth) image s...
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Today's politicians are confronted with new (digital) ways to tackle complex decision-making problems. In order to make the right decisions profound analysis of the problems and possible solutions has to be perfor...
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Data visualisation with high expressive power plays an important role in code comprehension. Recent visualization tools try to fulfil the expectations of the users and use various analogies. For example, in an archite...
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We deal in this paper with the problem of creating an interactive and visual map for a large collection of Open datasets. We first describe how to define a representation space for such data, using text mining techniq...
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We describe computer-assisted pronunciation training (CAPT) through the visualization of the articulatory gestures from learner's speech in this paper. Typical CAPT systems cannot indicate how the learner can corr...
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ISBN:
(纸本)9781479903566
We describe computer-assisted pronunciation training (CAPT) through the visualization of the articulatory gestures from learner's speech in this paper. Typical CAPT systems cannot indicate how the learner can correct his/her articulation. The proposed system enables the learner to study how to correct their pronunciation by comparing the wrongly pronounced gesture with a correctly pronounced gesture. In this system, a multi-layer neural network (MLN) is used to convert the learner's speech into the coordinates for a vocal tract using Magnetic Resonance imaging data. Then, an animation is generated using the values of the vocal tract coordinates. Moreover, we improved the animations by introducing an anchor-point for a phoneme to MLN training. The new system could even generate accurate CG animations from the English speech by Japanese people in the experiment.
A multi-GPU approach of MRISIMUL, a recently developed step-by-step comprehensive MR physics simulator of the Bloch equation, is presented in this study. The specific aim was to apply MRISIMUL on multi-GPU systems so ...
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ISBN:
(纸本)9781479931637
A multi-GPU approach of MRISIMUL, a recently developed step-by-step comprehensive MR physics simulator of the Bloch equation, is presented in this study. The specific aim was to apply MRISIMUL on multi-GPU systems so as to achieve even shorter execution times. We hypothesized that such a simulation platform could achieve a scalable performance with the increasing number of available GPU cards on single node, multi-GPU computer systems. A parallelization strategy was employed using the MATLAB single-program-multiple-data (spmd) statement and an almost linear speedup was observed with the increasing number of available GPU cards on two separate systems: a single computer of 2 quad-core processors and two Tesla C2070 GPU cards and a single computer of 2 hexa-core processors and four Tesla C2075 GPU cards.
This paper describes the use of gamification in a classroom for higher education, specifically for university students. Our goal is achieve a major increase in student motivation and engagement through various technol...
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ISBN:
(纸本)9781450323451
This paper describes the use of gamification in a classroom for higher education, specifically for university students. Our goal is achieve a major increase in student motivation and engagement through various technologies and learning methodologies based on game mechanics called gamification [1-2]. Gamification is used to engage students in the learning process [3] and stretch their retention of the knowledge and skills received beyond a single lecture [4]. This study adds Problem-Based Learning (PBL) and Quest-Based Learning (QBL) to students' collaborative work, and mixes teacher support with new, accessible technology, such as virtual environments and visualization 3D on the web thanks to webGL. Understanding the role of gamification in education means understanding under what circumstances game elements can drive a student's learning behavior so that he or she may achieve better results in the learning process.
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