'Visualizations' presentation slideshows

Transform

756 views • 57 slides

or Not 3D: When and Why Does it Work?

3D. or Not 3D: When and Why Does it Work?. Ben Shneiderman. Human-Computer Interaction Laboratory. & Department of Computer Science. University of Maryland. Web3D: Phoenix, February 26, 2002.

456 views • 45 slides

MPICL/ParaGraph Evaluation Report

MPICL/ParaGraph Evaluation Report . Adam Leko, Hans Sherburne UPC Group HCS Research Laboratory University of Florida. Color encoding key: Blue: Information Red: Negative note Green: Positive note. Basic Information. Name: MPICL/ParaGraph Developer:

518 views • 44 slides

CS639: Data Management for Data Science

CS639: Data Management for Data Science. Lecture 25: EDA Theodoros Rekatsinas. Data Visualizations Today. Data Visualizations Today. Standard Data Visualization Recipe: Load dataset into data viz tool Start with a desired hypothesis/pattern (explore combination of attributes)

364 views • 36 slides

Visualizing Software Architectures, Part 2

Visualizing Software Architectures, Part 2. Software Architecture Lecture 12. Objectives. Concepts What is visualization? Differences between modeling and visualization What kinds of visualizations do we use? Visualizations and views How can we characterize and evaluate visualizations?

433 views • 34 slides

Visualizing Software Architectures, Part 2

Visualizing Software Architectures, Part 2. Software Architecture Lecture 12. Objectives. Concepts What is visualization? Differences between modeling and visualization What kinds of visualizations do we use? Visualizations and views How can we characterize and evaluate visualizations?

485 views • 34 slides

Core Methods in Educational Data Mining

Core Methods in Educational Data Mining. HUDK4050 Fall 2015. Final Project Presentations Part 1 of 3. Final Projects. Presentations of ideas for how educational data mining can be used to positively impact the world

338 views • 33 slides

ion

3D tree visualizations. Pseudo 2D tree visualizations. Constituent ... John found the letter and Bill signed the letter. I gave a book to Mary and gave a letter to Sue. I gave a ...

530 views • 23 slides

CMC/CC A Information Visualization

CMC/CC A Information Visualization. Master IK, CIW, MMI L.M. Bosveld-de Smet Mon. 20/11/06; 16.00-18.00. Information visualization for the general public. IV is moving out of research laboratories IV is reaching users Examples: http://www.peets.com http://www3.cancer.gov/atlasplus

385 views • 23 slides

Visualizing Parallel Workspace Activities

342 views • 20 slides

The Influence of Visualization of Personal Networks in Qualitative Interviews with Respondents

The Influence of Visualization of Personal Networks in Qualitative Interviews with Respondents. Molina, J.L., McCarty, C., Aguilar, C., & Rota, L.

177 views • 17 slides

Visualization

320 views • 16 slides

Brain Compatible Learning

365 views • 14 slides

Interactive VisualiZations of statistics in RIP

Interactive VisualiZations of statistics in RIP. By : Tim de Boer and Kim Verkooij. Data VisualiZation. The set of techniques used to turn a set of data into visual insight. It aims to give the data a meaningful representation by exploiting

172 views • 11 slides

Seeing Through The Bottleneck

Conceptualize. Visualize. Vizen. Recognize. Optimize. Seeing Through The Bottleneck. The Vizen Trace Visualization Tool Matthew Pruitt, Jeremiah Barr Progress Report: Graduate Operating Systems. The Problem. The tool strace Copious amounts of data

195 views • 10 slides

Loud

Loud. Loud Fast Unstoppable. Fast. Maltese Detector. Unstoppable. Ma tese. Maltese Detector. 98% success. 1% false negative. Ma tese. DETECTED. Ma tese. P ( | ) = 0.5%. Can visualization help?.

202 views • 8 slides

How To Clean Your Computer

269 views • 7 slides

visualizing disease and injury rates

visualizing disease and injury rates. Ian Bolliger Institute for Health Metrics and Evaluation. Background. DisMod 3 model produces country-age-sex-year-specific prevalence, incidence, excess mortality Over 20,000 estimates per disease cause Models can be very sensitive to parameter choice

142 views • 5 slides

150 views • 4 slides

April 27, 2010

April 27, 2010. Daniel Stutzman - Reduction of Inductive Predicates for Shape Analysis of Circular Lists James Holley - User Interfaces and Visualizations for Development-Time Program Analysis Allison Thompson - Visualizing Type Error Messages Sidartha Gracias

126 views • 2 slides