A Laboratory for Scientific Visualization and Experimental Machine Learning

科学可视化和实验机器学习实验室

• 批准号: 9115268
• 负责人: Patrick Mantey
• 金额: $ 119.97万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-03-01 至 1997-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9115268&HistoricalAwards=false
• 关键词: Laboratory; Scientific; Visualization; Experimental; Machine

This infrastructure award is for the development of a visualization and machine learning laboratory. The laboratory consists of powerful graphics workstations, a parallel processor, a large file server, a fiber optics high speed data network, and support personnel to maintain the laboratory. The research supported by this equipment includes: statistical data analysis, pattern recognition, and machine learning; visualization of sample volume data; interactive steering of simulations; high speed switching;concurrent systems; and applications of electronic libraries. A major bottleneck to the utilization of scientific information is the massive amount of data now collected. Scientific visualization is the term that covers an emerging collection of new techniques for transforming multidimensional numeric data into understandable graphic images. These images can then be manipulated and explored by scientists and engineers who, sitting at their workstations, create models and draw inferences from them. Machine learning includes a wide variety of techniques from the fields of pattern recognition, signal processing, statistical decision and control theory, and artificial intelligence that allow the machine itself to participate in the process of creating models and drawing inferences from data. It is anticipated that a new synergy between machine learning and scientific visualization will arise from this award and that substantial collaborations with scientists outside of the computer science department will occur.

这个基础设施奖是为了开发一个 可视化和机器学习实验室。 实验室 由强大的图形工作站，并行处理器， 大型文件服务器，光纤高速数据网络， 和支持人员来维护实验室。 研究 该设备支持的内容包括：统计数据分析， 模式识别和机器学习;可视化 样本体积数据;模拟的交互式操纵;高 速度切换;并发系统;以及 电子图书馆 利用科学技术的一个主要瓶颈是 信息是现在收集的大量数据。 科学可视化是一个术语，涵盖了一个新兴的 转换多维数据的新技术的集合 数字数据转换成可理解的图形图像。 这些图像 科学家和工程师们就可以操纵和探索 他们坐在工作台上， 从他们的推论。机器学习包括各种各样的 来自模式识别、信号 处理，统计决策和控制理论，以及 人工智能让机器本身 参与创建模型和绘图的过程 从数据推断。 预计新的协同作用 机器学习和科学可视化之间的联系 从这个奖项和实质性的合作， 计算机科学系以外的科学家将出现。