论文标题
部分可观测时空混沌系统的无模型预测
Managing Controlled Unclassified Information in Research Institutions
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
In order to operate in a regulated world, researchers need to ensure compliance with ever-evolving landscape of information security regulations and best practices. This work explains the concept of Controlled Unclassified Information (CUI) and the challenges it brings to the research institutions. Survey from the user perceptions showed that most researchers and IT administrators lack a good understanding of CUI and how it is related to other regulations, such as HIPAA, ITAR, GLBA, and FERPA. A managed research ecosystem is introduced in this work. The workflow of this efficient and cost effective framework is elaborated to demonstrate how controlled research data are processed to be compliant with one of the highest level of cybersecurity in a campus environment. Issues beyond the framework itself is also discussed. The framework serves as a reference model for other institutions to support CUI research. The awareness and training program developed from this work will be shared with other institutions to build a bigger CUI ecosystem.
