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The design and production of complex engineered systems (CES) require analysis of massive amounts of detailed information, including data on products and materials, engineering designs, manufacturing specifications, supply chain and delivery data, and changing customer needs. Visual analytics promises to offer tools and methods that will help stakeholders interactively explore, discover, and make sense of the underlying data.
Dimensionality reduction (DR) is often used for exploring the evolution patterns of a collection of dynamic ego-networks. However, DR often lacks flexibility: as analysts' questions evolve during data exploration, the low-dimensional projection remains static, limiting the depth of exploration. To address the inflexibility of DR, we designed a data transformation pipeline which enables analysts to transform dynamic ego-networks into event sequences for steering MDS to create different scatterplots of dynamic ego-networks.
Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks.
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GVU News
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Constellations Center Commits to Teaching 200 Students Computer Science in 2018-19 Academic Year
Constellations Center attends CSforALL Summit and pledges to teach 200 students computer science in Atlanta Public Schools during the 2018-19 academic year. -
Georgia Tech Researchers Develop AI That Can Create Entirely New Games
Conceptual expansion takes in an arbitrary number of games and then outputs original games with unique mechanics and level designs. -
EarSketch Team Receives Grant to Add AI ‘Co-Creative’ To Platform
The AI assistant would not be a visual character, but would help students learn new techniques.
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