RUI: Dynamic Net Analyte Signal Modeling for Multivariate Calibration and Maintenance

RUI：用于多变量校准和维护的动态网络分析物信号建模

• 批准号: 1111053
• 负责人: John Kalivas
• 金额: $ 30.11万
• 依托单位: Idaho State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1111053&HistoricalAwards=false
• 关键词: RUI; Dynamic; Net; Analyte; Signal

With support from the Chemical Measurement and Imaging Program, and co-funding from the Office of Cyberinfrastructure "Venture Fund," Professor John Kalivas of Idaho State University is developing five pioneering calibration tools to advance chemical analysis. Calibration generally involves forming a mathematical relationship between chemical concentration and an instrumental response such as spectroscopic data. It is critical to numerous disciplines, including process analytical technology for the pharmaceutical and chemical industries, environmental and agriculture monitoring, and medical diagnostics. The Kalivas group seeks to design calibrations which eliminate chemical analysis interferences and offer less costly and more accurate and precise chemical analyses. Two statistical/analytical tools are used: Tikhonov regularization and net analyte signal. The improvements targeted by this project should benefit many disciplines by enabling better calibrations that are stable over extended periods of time.By participating in this research, undergraduate students learn state-of-the-art calibration and become proficient at performing collaborative scientific research. Education of undergraduates in these advanced methods prepares them for subsequent scientific professional pursuits. Another key impact of this project is development of classroom software tools for use in the curriculum at Idaho State University and other institutions. Additionally, disseminating the innovative calibration and curricular software through Professor Kalivas' web site allows newcomers and practitioners direct access, assuring software re-use. Co-funding from the OCI-Venture Fund specifically seeks to enhance such efforts in CI-reuse and long term software sustainability.

在化学测量和成像计划的支持下，以及网络基础设施办公室“风险基金”的共同资助下，爱达荷州立大学的约翰·卡利瓦斯教授正在开发五种开创性的校准工具来促进化学分析。校准通常涉及在化学浓度和仪器响应(如光谱数据)之间形成数学关系。它对许多学科至关重要，包括制药和化学工业的过程分析技术、环境和农业监测以及医疗诊断学。Kalivas小组寻求设计校准，消除化学分析干扰，并提供成本更低、更准确和更精确的化学分析。使用了两种统计/分析工具：Tikhonov正则化和净分析物信号。这个项目所针对的改进将使许多学科受益，因为它能够实现更好的校准，并在更长的时间内保持稳定。通过参与这项研究，本科生学习最先进的校准技术，并熟练地进行协作科学研究。对本科生进行这些先进方法的教育，为他们随后的科学职业追求做好准备。该项目的另一个关键影响是开发课堂软件工具，用于爱达荷州立大学和其他机构的课程。此外，通过卡利瓦斯教授的网站传播创新的校准和课程软件，允许新人和实践者直接访问，确保软件重复使用。保监处创投基金的共同资助特别致力于加强在CI-Reuse和长期软件可持续发展方面的努力。