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Full-Text Articles in Computer Engineering

The Effects Of Latency On 3d Interactive Data Visualizations, Allen Korenevsky Jun 2016

The Effects Of Latency On 3d Interactive Data Visualizations, Allen Korenevsky

Master's Theses

Interactive data visualizations must respond fluidly to user input to be effective, or so we assume. In fact it is unknown exactly how fast a visualization must run to present every facet within a dataset. An engineering team with limited resources is left with intuition and estimates to determine if their application performs sufficiently well.

This thesis studies how latency affects users' comprehension of data visualizations, specifically 3D geospatial visualizations with large data sets. Subjects used a climate visualization showing temperatures spanning from the 19th to the 21st century to answer multiple choice questions. Metrics like their eye movements, time …


Polyfs Visualizer, Paul Martin Fallon Jun 2016

Polyfs Visualizer, Paul Martin Fallon

Master's Theses

One of the most important operating system topics, file systems, control how we store and access data and form a key point in a computer scientists understanding of the underlying mechanisms of a computer. However, file systems, with their abstract concepts and lack of concrete learning aids, is a confusing subjects for students. Historically at Cal Poly, the CPE 453 Introduction to Operating Systems has been on of the most failed classes in the computing majors, leading to the need for better teaching and learning tools. Tools allowing students to gain concrete examples of abstract concepts could be used to …


Comparative Study Of Dimension Reduction Approaches With Respect To Visualization In 3-Dimensional Space, Pooja Chenna May 2016

Comparative Study Of Dimension Reduction Approaches With Respect To Visualization In 3-Dimensional Space, Pooja Chenna

Master of Science in Computer Science Theses

In the present big data era, there is a need to process large amounts of unlabeled data and find some patterns in the data to use it further. If data has many dimensions, it is very hard to get any insight of it. It is possible to convert high-dimensional data to low-dimensional data using different techniques, this dimension reduction is important and makes tasks such as classification, visualization, communication and storage much easier. The loss of information should be less while mapping data from high-dimensional space to low-dimensional space. Dimension reduction has been a significant problem in many fields as …