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Filtering by: Creator Van Dersal, Samuel Academic Affiliation Electrical Engineering and Computer Science Committee Member Bailey, Mike

The ChildsPlay Approach: Evaluating an Experimental Approach for Teaching Introductory CS at University

Creator:

Nelson, Aiden J.

Abstract:

University students first learning about computer science (CS) can be intimidated and frustrated by programming. In addition, the general-purpose programming languages chosen for introducing students to programming contain several features that have the potential to overwhelm and distract them from focused curriculum topics, which can lead to reduced retention of...

Resource Type:

Masters Thesis
Tensor Field Design and Analysis for Applications in Computer Graphics and Scientific Visualization

Creator:

Palacios, Jonathan

Abstract:

Many applications in computer graphics and geometry processing rely on the ability to locally orient 2D and 3D entities on a surface, or inside a volume, such as the sinusoidal kernels in Gabor noise, the color and geometry textures in pattern synthesis, and the finite elements in remeshing. In these...

Resource Type:

Dissertation

Full Text:

, first introduced by Van Wijk [77] in 1991, are space- filling, and usually interactive when accelerated
Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

Creator:

Wei, Qi

Abstract:

Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...

Resource Type:

Dissertation

ScholarsArchive@OSU

The ChildsPlay Approach: Evaluating an Experimental Approach for Teaching Introductory CS at University

Tensor Field Design and Analysis for Applications in Computer Graphics and Scientific Visualization

Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

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