Visualization of Quick sort

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It demonstrates two comparison sorting algorithms: Bubble sort and Quick sort.
Comparison sorting algorithms are only allowed to ‘see’ the data through a sequence of pair-wise comparisons, therefore they are applicable to any type of comparable objects: numbers, strings, colored balls, etc

Bubble sort is very simple but has poor performance. A comparison sorting algorithm’s performance is usually measured by the number of comparisons it makes. Bubble sort performs on the order of n^2 comparisons to sort n elements.

Quick sort is only slightly more complicated but usually performs much better (as demonstrated in the video). It performs on average an order of n log(n) comparisons to sort n elements. This is much lower than n^2 for large values of n. However, if the algorithm makes some ‘unlucky’ choices it might require n^2 comparisons after all.

Other algorithms exist that guarantee the number of comparisons will not exceed n log(n), however, in practice Quick sort usually out-performs all other comparison sorting algorithms due to its simplicity.

If other operations other than pair-wise comparisons are allowed, then a broader range of algorithms can be used. Some of them can perform much faster than Quick sort, but they are limited to a particular type of elements, e.g., numbers is a certain range.

Duration : 0:2:56

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Lev Manovich. Data Visualization. 2009. 1/3 Lev Manovich speaking at the European Graduate School in Saas-Fee, Switzerland on data visualization, information design, visual analeptics, software studies, the internet, creativity, and media theory. Public open lecture for the students and faculty of the European Graduate School EGS Media and Communication Studies department program Saas-Fee Switzerland. Lev Manovich 2009
Lev Manovich is one of the most significant voices in internet criticism today. Working as an artist and net theorist as well as a professor in the Visual Arts Department at the University of California at San Diego, he also directs the Software Studies Initiative at the California Institute for Telecommunications and Information Technology. As well, he is a visiting research professor at both Goldsmiths College, London, and De Montfort College as well as the College of Fine Arts at the University of New South Wales in Sydney.
Manovichs most well known book, The Language of New Media, has influenced scores of students, artists and activists since it was published in 2001. In The Language of New Media, Manovich offer a detailed and rigorous theory of new media. Placing new media within the histories of visual and media culture, Manovich examines its reliance on the conventional apparatuses of old media. Manovich uses film theory, art history, literary theory and computer science to develop new theoretical constructs such as cultural interface and spatial montage. Lev Manovichs latest book, Software Takes Command, was released in 2008 under a Creative Commons license and will be available from MIT Press in 2010. Software Takes Command deals with the rise of software as the dominant force in society and culture. Manovich proposes a new system of study—the system of software studies—to investigate both the role software has in forming society, and the cultural, social and economic forces that shape software itself.
Lev Manovichs creative projects include Soft Cinema (2002-03) which is a dynamic computer-driven media installation. The viewer is presented with an infinite number of narrative films constructed at random using custom software. The computer selects clips of both audio and visual works from a database to create and original and unique random narrative. At UCSD, Manovich founded the Software Studies Initiative which seeks to create effective tools for the study of software society. Viewing software as a layer which permeates contemporary society, the Software Studies Initiative seeks to understand contemporary techniques of control, communication, decision making, memory, vision and writing.
Lev Manovichs books include The Engineering of Vision (1993), The Language of New Media (2001), and Software Takes Command (2008) which available for download through a Creative Commons license. Lev Manovich currently blogs at databeautiful.

Duration : 0:10:27

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About Dundas Data Visualization

Since 1992, Dundas has provided software components and consulting services to developers and other clients in more than 50 countries. Over the years, the company has achieved remarkable success, reflected in its numerous industry awards and by its long list of Fortune 500 customers. Learn how Dundas Chart, Gauge, Map and Calendar can enhance a variety of digital dashboard and other applications – via several industry-leading platforms.

Duration : 0:1:22

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How To Install Panopticon EX Server Data Visualization Software (1280×1024)

This tutorial explains how to install the Server component of Panopticon EX data visualization software.

Panopticon EX data visualization software incorporates a wide range of information visualizations, including our well-known Treemaps and Heatmaps as well as Scatter Plots, Horizon Graphs, Stack Graphs and a range of other great visualizations designed for fast comprehension and interpretation. The software includes our amazing StreamCube™ OLAP data model for on-the-fly data aggregations and slicing and dicing.

Duration : 0:4:58

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STOC (Stock Ticker Orbital Comparison) data visualization

STOC (Stock Ticker Orbital Comparison) is an interactive data visualization, using the metaphor of a planetary system, which maps parameters of stocks in the S&P500 to animated visual outputs. World Premiere at the SIGGRAPH 2009 Information Aesthetics Showcase in New Orleans, LA.
Credit to Adam Fielding’s “Traveling Light” for the demo video music, licensed CC-NC-BY.


University of Advancing Technology
James Grant
Todd Spencer

1. Introduction
Existing methods for displaying large amounts of stock market data do not easily allow comparison between companies, as the data is often presented in tabular format. Some solutions implement a price-over-time graph, with the option of layering on additional stocks or market indices for comparison. STOC, however, seeks to allow immediate comparison of hundreds or thousands of stocks, by mapping various stock-specific parameters to easily observable visual outputs. This visualization is particularly suited for comparisons between items, as one is able to immediately identify the largest, or reddest, or quickest item in the group.

2. Data Mapping
The program uses mapping functions to adjust the raw data within ranges usable for visualization purposes. The data is mapped between inputs and outputs as follows:
– volume of trading = planet orbital distance
– comparison to S&P 500 = planet speed
– percent change from prior close = planet color
– market capitalization = planet size
– P/E ratio = planet atmosphere width and color
– moving average = planet opacity
– dividend yield = planet moon size

The program also produces an average of all these numbers to define the general performance of the S&P 500. This is represented by a large center circle, or sun. After discussing how to best display the data, we determined that the color of the sun would be an average of the change percentage, and the volume is a scaled visualization of the total volume of trading on the S&P. This was done to allow the viewer to tell at a quick glance some basic information about the markets performance, and how much trading has occurred. The sun remains stationary, and there is no averaging of the dividend yields.

3. Interaction
The entire system can be manipulated in several ways. The user is able to zoom in and out of a section to see more detail, or expand and contract each of the relative orbital radii, maintaining their relationship but allowing the user to give more or less separation to them in order to better compare stocks. It also gives the user the ability to right click on a stock to display the name of the stock, and press the space bar to get a print out of all the raw data that has been collected. The speed of the system can also be scaled via keyboard, and by pressing the space bar the system can be paused at any time. An individual stock can be selected and highlighted by typing the company name.

4. Goals and future developments
Ideally, this application is something that could be set up in an area and let run to allow a person to simply glance at it to gauge the markets condition. In this way a person could always have an eye on the stock market without having to stare at line and bar graphs.
For future development, we plan on expanding the usability of the application with several additions:
– iPhone and Android apps
– Web-viewable visualization and interaction
– Scan through daily archived closing data points
– Additional data sets visualized with same orbital metaphor

Duration : 0:1:25

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