Cybersecurity for Manufacturers: Securing the Digitized and Connected Factory

As manufacturing becomes increasingly digitized and data-driven, manufacturers will find themselves at serious risk. Although there has yet to be a major successful cyberattack on a U.S. manufacturing operation, threats continue to rise. The complexities of multi-organizational dependencies and data-management in modern supply chains mean that vulnerabilities are multiplying. There is widespread agreement among manufacturers, government agencies, cybersecurity firms, and leading academic computer science departments that U.S. industrial firms are doing too little to address these looming challenges. Unfortunately, manufacturers in general do not see themselves to be at particular risk. This lack of recognition of the threat may represent the greatest risk of cybersecurity failure for manufacturers. Public and private stakeholders must act before a significant attack on U.S. manufacturers provides a wake-up call. Cybersecurity for the manufacturing supply chain is a particularly serious need. Manufacturing supply chains are connected, integrated, and interdependent; security of the entire supply chain depends on security at the local factory level. Increasing digitization in manufacturing— especially with the rise of Digital Manufacturing, Smart Manufacturing, the Smart Factory, and Industry 4.0, combined with broader market trends such as the Internet of Things (IoT)— exponentially increases connectedness. At the same time, the diversity of manufacturers—from large, sophisticated corporations to small job shops—creates weakest-link vulnerabilities that can be addressed most effectively by public-private partnerships. Experts consulted in the development of this report called for more holistic thinking in industrial cybersecurity: improvements to technologies, management practices, workforce training, and learning processes that span units and supply chains. Solving the emerging security challenges will require commitment to continuous improvement, as well as investments in research and development (R&D) and threat-awareness initiatives. This holistic thinking should be applied across interoperating units and supply chains.National Science Foundation, Grant No. 1552534https://deepblue.lib.umich.edu/bitstream/2027.42/145442/1/MForesight_CybersecurityReport_Web.pd

Cluster of systemic lupus erythematosus (SLE) associated with an oil field waste site: a cross sectional study

BACKGROUND: This is a community comparison study that examines persons living in a subdivision exposed to petroleum products and mercury. METHODS: We compared their health status and questionnaire responses to those living in another community with no known exposures of this type. RESULTS: Pristane house dust among the exposed homes was higher than in the comparison communities. The exposed subdivision has higher ambient air mercury levels compared to the control community. The prevalence of rheumatic diseases (OR = 10.78; CI = 4.14, 28.12) and lupus (OR = 19.33; CI = 1.96, 190.72) was greater in the exposed population compared to the unexposed. A higher prevalence of neurological symptoms, respiratory symptoms and several cardiovascular problems including stroke (OR = 15.41; CI = 0.78, 304.68) and angina (OR = 5.72; CI = 1.68, 19.43) was seen. CONCLUSION: There were statistically significant differences in B cells, Natural Killer Cells, gamma glutamyl transferase, globulin and serum calcium levels between control and exposed subjects

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics on cluster computing platforms with access to local disks and is optimized for data-parallel tasks. We examine three widely-used and important matrix factorizations: NMF (for physical plausability), PCA (for its ubiquity) and CX (for data interpretability). We apply these methods to TB-sized problems in particle physics, climate modeling and bioimaging. The data matrices are tall-and-skinny which enable the algorithms to map conveniently into Spark's data-parallel model. We perform scaling experiments on up to 1600 Cray XC40 nodes, describe the sources of slowdowns, and provide tuning guidance to obtain high performance

Federal Reserve Bank of New York Meeting with AIG Notes

In this particular instance, AIG faced liquidity issues that threatened the company\u27s survival

Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture

A Distributed Engine Control Working Group (DECWG) consisting of the Department of Defense (DoD), the National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) and industry has been formed to examine the current and future requirements of propulsion engine systems. The scope of this study will include an assessment of the paradigm shift from centralized engine control architecture to an architecture based on distributed control utilizing open system standards. Included will be a description of the work begun in the 1990's, which continues today, followed by the identification of the remaining technical challenges which present barriers to on-engine distributed control

Estimate of Hanford Waste Rheology and Settling Behavior

The U.S. Department of Energy (DOE) Office of River Protection’s Waste Treatment and Immobilization Plant (WTP) will process and treat radioactive waste that is stored in tanks at the Hanford Site. Piping, pumps, and mixing vessels have been selected to transport, store, and mix the high-level waste slurries in the WTP. This report addresses the analyses performed by the Rheology Working Group (RWG) and Risk Assessment Working Group composed of Pacific Northwest National Laboratory (PNNL), Bechtel National Inc. (BNI), CH2M HILL, DOE Office of River Protection (ORP) and Yasuo Onishi Consulting, LLC staff on data obtained from documented Hanford waste analyses to determine a best-estimate of the rheology of the Hanford tank wastes and their settling behavior. The actual testing activities were performed and reported separately in referenced documentation. Because of this, many of the required topics below do not apply and are so noted

Eileen Rafferty and Dr Barry Newell

Mount Stromlo and Siding Spring Observatories - Star Plots, Photos from Telescope, Site - Mr. Graeme Blackman, Mr. Robbie Sybaczynsky, Don Carney, Patrick Barling, Simon Fantich, Governor Sinclair, Mrs. Sinclair, Prof. Freeman, Mrs. Eileen Rafferty, Prof. Don Mathewson, Prof. Alex Rodgers, Kim Sebo, Prof. Em. Olin Eggen, Peter Quinn, Stuart Ryder, Pat Barling, Stephanie Cote, Don Faulkner, John Dawe, Allan Barton, Scott Griffiths, Heather Griffiths, Dr. Barry Newell, Eileen Rafferty, Mr. Buchorn, Prof. Dan Mathewson & other