4,253 research outputs found

    Visualization for the Physical Sciences

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    Developing a virtual physics world

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    In this article, the successful implementation of a development cycle for a physics teaching package based on game-like virtual reality software is reported. The cycle involved several iterations of evaluating students' use of the package followed by instructional and software development. The evaluation used a variety of techniques, including ethnographic observation, surveys, student focus groups and conventional assessment. The teaching package included a laboratory manual, instructional support materials and the Real Time Relativity software that simulates a world obeying special relativistic physics. Although the iterative development cycle was time consuming and costly, it gave rise to substantial improvements in the software user interface and in the students' learning experience

    Virtual Astronomy, Information Technology, and the New Scientific Methodology

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    All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common technological challenges. The Virtual Observatory concept is the astronomical community's response to these challenges: it aims to harness the progress in information technology in the service of astronomy, and at the same time provide a valuable testbed for information technology and applied computer science. Challenges broadly fall into two categories: data handling (or "data farming"), including issues such as archives, intelligent storage, databases, interoperability, fast networks, etc., and data mining, data understanding, and knowledge discovery, which include issues such as automated clustering and classification, multivariate correlation searches, pattern recognition, visualization in highly hyperdimensional parameter spaces, etc., as well as various applications of machine learning in these contexts. Such techniques are forming a methodological foundation for science with massive and complex data sets in general, and are likely to have a much broather impact on the modern society, commerce, information economy, security, etc. There is a powerful emerging synergy between the computationally enabled science and the science-driven computing, which will drive the progress in science, scholarship, and many other venues in the 21st century
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