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SUMMARY:3D Visualization Software: Introduction to Unreal Engine and C++
DESCRIPTION:This is part of a series of workshops covering 3D game engines and animation software for research and data visualization. Registration to previous parts of this series is not required. \nUnreal Engine is a popular game engine among professional industries and game studios. It is also increasingly used for “serious” applications that require interactive 3D graphics and visualizations. Today\, Unreal Engine is available for free for creators not producing paid-for products. \nIn this workshop\, we’ll introduce the Unreal Engine workspace from a beginner’s perspective\, and prepare a simple data visualization with the interface\, including an introduction to its C++ workflow. Users will gain a basic understanding of the software\, and will be prepared to continue advanced training or to build simple examples in the software. \nA basic familiarity with any programming language (C++ will be used during the session) is recommended to get the most out of the workshop. Prior experience with any other 3D workspace for games\, animation\, visualization or science is encouraged. To take part\, users will be responsible to use their own laptop with Unreal Engine (available for Windows\, Macintosh and Linux\, but Windows is recommended) pre-installed. At this time\, Unreal Engine 4 is planned to be used\, pre-registered attendees will received a confirmation email about the version before the event. \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/3d-visualization-software-introduction-to-unreal-engine-and-c/
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DTSTART;TZID=America/Detroit:20220127T140000
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SUMMARY:Reading and discussion group: Spatial Analysis in Social Science
DESCRIPTION:This reading group moderated by consultants from CSCAR will focus on spatial analysis especially as practiced in social sciences. We will meet for 1.5 to 2 hours every month on the fourth Thursday and discuss one or two chapters from relevant graduate level textbooks. We will focus on the concepts and applications but will also try to discuss the technical details. The format is open-ended\, and the key objective is to support learning at different knowledge and skill levels. If there is interest\, we will also cover software implementation of techniques in R or Python. We will select reading material that is available via U-M library or freely accessible online. \nReadings – For the first meeting scheduled on Jan 27th\, we will discuss the following chapters: \n(1) Chapter 2: Defining neighbors via a spatial weight matrix (from Spatial Analysis for Social Science by David Darmofal) \n(2) Chapter 3: Global and local indicators of spatial association (from Spatial Analysis using Big Data by Yoshiki Yamagata and Hajime Seya) \n(3) Chapter 3: Spatial autocorrelation and statistical inference (from Spatial Analysis for Social Science by David Darmofal) \nDigital versions of the above two books are available from the UM Library.
URL:https://micde.umich.edu/event/reading-and-discussion-group-spatial-analysis-in-social-science/
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