Grid-Based Visualization and its Medical Applications

2011 ◽  
pp. 25-57 ◽  
Author(s):  
Yingjun Qiu ◽  
Youbing Zhao ◽  
Jiaoying Shi
Keyword(s):  
Grid Computing ◽  
Large Scale ◽  
Interactive Visualization ◽  
Research Direction ◽  
Data Sets ◽  
Computing Technology ◽  
Visualization System ◽  
Huge Data ◽  
Visualization Systems ◽  
Grid Based

Traditional visualization approaches cannot handle new challenges in the visualization field such as visualizing huge data sets, communicating between existing visualization systems and providing interactive visualization services, widely. In this chapter, the authors introduce an emerging research direction in the visualization field, grid-based visualization, which aims to resolves the above problems by utilizing grid computing technology. However, current grid computing technology is almost batch job-oriented and does not support interactive visualization applications natively. In this chapter, the authors implement a grid-based visualization system (GVis) which utilizes large-scale computing resources to achieve large dataset visualization in real time and provides end users with reliable interactive visualization services, widely. In GVis system, current grid computing technology is extended to support interactive visualization applications.

On the Effectiveness of Hybrid Canopy with Hoeffding Adaptive Naive Bayes Trees

2017 ◽  
Vol 8 (2) ◽  
pp. 30-43
Author(s):  
Mrutyunjaya Panda
Keyword(s):  
Big Data ◽  
Clustering Analysis ◽  
Large Scale ◽  
Data Sets ◽  
Recent Past ◽  
Large Scale Data ◽  
Huge Data ◽  
With Memory ◽  
Memory Constraints ◽  
Scale Data

The Big Data, due to its complicated and diverse nature, poses a lot of challenges for extracting meaningful observations. This sought smart and efficient algorithms that can deal with computational complexity along with memory constraints out of their iterative behavior. This issue may be solved by using parallel computing techniques, where a single machine or a multiple machine can perform the work simultaneously, dividing the problem into sub problems and assigning some private memory to each sub problems. Clustering analysis are found to be useful in handling such a huge data in the recent past. Even though, there are many investigations in Big data analysis are on, still, to solve this issue, Canopy and K-Means++ clustering are used for processing the large-scale data in shorter amount of time with no memory constraints. In order to find the suitability of the approach, several data sets are considered ranging from small to very large ones having diverse filed of applications. The experimental results opine that the proposed approach is fast and accurate.

An Immersive and Interactive Visualization System for Large-Scale CFD

2003 ◽  
Author(s):  
Yuichi Matsuo
Keyword(s):  
Large Scale ◽  
Interactive Visualization ◽  
Cfd Simulations ◽  
Output Data ◽  
Visualization System ◽  
Aerospace Research ◽  
Projection Screen ◽  
Computational Fluid Dynamics Cfd ◽  
Collaboration And Communication ◽  
Rear Projection Screen

We have been long involved in large-scale computational fluid dynamics (CFD) simulations in aerospace research. These days, as the computer power grows, output data from the simulations becomes larger and larger, and we feel that the current visualization methodology has its limitation in understanding. Thus, with the target concepts of reality, collaboration, and communication, we has built an immersive and interactive visualization system with a large-sized wall-type display. The system, which has been in operation since April 2001, is driven by a SGI Onyx 3400 server with 32 CPUs, 64Gbytes memory, and 6 IR3 graphics pipelines, and comprises a 4.6×1.5-meter (15×5-foot) rear projection screen with 3 high-resolution CRT projectors, supporting stereoscopic viewing, easy color/luminosity matching, and accurate edge-blending. The system is mainly used for visualization of large-scale CFD simulations. This paper will describe the new visualization system introduced at the National Aerospace Laboratory of Japan, and the features of the system are discussed while illustrating some typical visualized examples.

scholarly journals Designing, Implementing And Evaluating A Cross-Modal Sensory Substitution System For The Effective Communication Of The Emotional And Informative Aspects Of Music

2021 ◽  
Author(s):  
Michael Pouris
Keyword(s):  
Large Data ◽  
Large Data Sets ◽  
Sensory Substitution ◽  
Data Sets ◽  
Combined System ◽  
Visualization System ◽  
Substitution System ◽  
Music Visualization ◽  
Visualization Systems ◽  
Visual Domain

Visualizations have existed for millennia as ways to communicate information. Visualizations are ubiquitous tools used every day to help navigate cities and aid in learning complex tasks. Tasks are made simpler when applying various visualization methods to large data sets to discover trends that are otherwise difficult to notice. More recently, music visualization systems have been created to convey music in the visual domain; however, they are not based on any psychological model of auditory and visual equivalents. This thesis discusses a music visualization system called MusicViz, which facilitates in the visual communication of the informative and entertainment aspect of music based on psychologically justified translation principals. MusicViz is combined with a vibro-feedback chair called the Emoti-Chair, which translates auditory music to vibrations along the user’s back. The combined system is coined VITA (Visually Immersive and Tactile Animation). A usability evaluation of the VITA showed it is an enjoyable experience.

scholarly journals Development of Interactive Visualization System for Unsteady Large-Scale Data Set

2004 ◽  
Vol 24 (Supplement1) ◽  
pp. 311-314
Author(s):  
Kenji ONO ◽  
Tsuyoshi TAMAKI ◽  
Hiroyuki YOSHIKAWA ◽  
Yasuo KATANO ◽  
Kwan-Liu Ma
Keyword(s):  
Large Scale ◽  
Interactive Visualization ◽  
Data Set ◽  
Visualization System ◽  
Large Scale Data ◽  
Scale Data

scholarly journals Designing, Implementing And Evaluating A Cross-Modal Sensory Substitution System For The Effective Communication Of The Emotional And Informative Aspects Of Music

2021 ◽  
Author(s):  
Michael Pouris
Keyword(s):  
Large Data ◽  
Large Data Sets ◽  
Sensory Substitution ◽  
Data Sets ◽  
Combined System ◽  
Visualization System ◽  
Substitution System ◽  
Music Visualization ◽  
Visualization Systems ◽  
Visual Domain

Visualizations have existed for millennia as ways to communicate information. Visualizations are ubiquitous tools used every day to help navigate cities and aid in learning complex tasks. Tasks are made simpler when applying various visualization methods to large data sets to discover trends that are otherwise difficult to notice. More recently, music visualization systems have been created to convey music in the visual domain; however, they are not based on any psychological model of auditory and visual equivalents. This thesis discusses a music visualization system called MusicViz, which facilitates in the visual communication of the informative and entertainment aspect of music based on psychologically justified translation principals. MusicViz is combined with a vibro-feedback chair called the Emoti-Chair, which translates auditory music to vibrations along the user’s back. The combined system is coined VITA (Visually Immersive and Tactile Animation). A usability evaluation of the VITA showed it is an enjoyable experience.

scholarly journals Ssecrett and NeuroTrace: Interactive Visualization and Analysis Tools for Large-Scale Neuroscience Data Sets

2010 ◽  
Vol 30 (3) ◽  
pp. 58-70 ◽  
Author(s):  
Won-Ki Jeong ◽  
Johanna Beyer ◽  
Markus Hadwiger ◽  
Rusty Blue ◽  
Charles Law ◽  
...  
Keyword(s):  
Large Scale ◽  
Interactive Visualization ◽  
Data Sets ◽  
Analysis Tools

scholarly journals A WEB-BASED PLATFORM FOR VISUALIZING SPATIOTEMPORAL DYNAMICS OF BIG TAXI DATA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1407-1412 ◽  
Author(s):  
H. Xiong ◽  
L. Chen ◽  
Z. Gui
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Trajectory Data ◽  
Visualization System ◽  
City Life ◽  
Interactive Animation ◽  
Dbscan Clustering ◽  
Main Work ◽  
Visualization Systems ◽  
Taxi Trajectory

With more and more vehicles equipped with Global Positioning System (GPS), access to large-scale taxi trajectory data has become increasingly easy. Taxis are valuable sensors and information associated with taxi trajectory can provide unprecedented insight into many aspects of city life. But analysing these data presents many challenges. Visualization of taxi data is an efficient way to represent its distributions and structures and reveal hidden patterns in the data. However, Most of the existing visualization systems have some shortcomings. On the one hand, the passenger loading status and speed information cannot be expressed. On the other hand, mono-visualization form limits the information presentation. In view of these problems, this paper designs and implements a visualization system in which we use colour and shape to indicate passenger loading status and speed information and integrate various forms of taxi visualization. The main work as follows: 1. Pre-processing and storing the taxi data into MongoDB database. 2. Visualization of hotspots for taxi pickup points. Through DBSCAN clustering algorithm, we cluster the extracted taxi passenger’s pickup locations to produce passenger hotspots. 3. Visualizing the dynamic of taxi moving trajectory using interactive animation. We use a thinning algorithm to reduce the amount of data and design a preloading strategyto load the data smoothly. Colour and shape are used to visualize the taxi trajectory data.

scholarly journals 1Click1View: Interactive Visualization Methodology for RNAi Cell-Based Microscopic Screening

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Lukasz Zwolinski ◽  
Marta Kozak ◽  
Karol Kozak
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Interactive Visualization ◽  
Image Data ◽  
Data Sets ◽  
Visualization Method ◽  
Multiple Cell ◽  
Visualization Tools ◽  
Screening Assays ◽  
Numeric Data

Technological advancements are constantly increasing the size and complexity of data resulting from large-scale RNA interference screens. This fact has led biologists to ask complex questions, which the existing, fully automated analyses are often not adequate to answer. We present a concept of 1Click1View (1C1V) as a methodology for interactive analytic software tools. 1C1V can be applied for two-dimensional visualization of image-based screening data sets from High Content Screening (HCS). Through an easy-to-use interface, one-click, one-view concept, and workflow based architecture, visualization method facilitates the linking of image data with numeric data. Such method utilizes state-of-the-art interactive visualization tools optimized for fast visualization of large scale image data sets. We demonstrate our method on an HCS dataset consisting of multiple cell features from two screening assays.

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