This report is a research aid, which lists the DOD authorization bills (Table 1) and appropriations bills (Table 2). This report includes all the pertinent information on the passage of these bills through the legislative process: bill numbers, report numbers, dates reported and passed, recorded vote numbers and vote tallies, dates of passage of the conference reports with their numbers and votes, vetoes, substitutions, dates of final passage, and public law numbers. Table 3 shows real growth or decline in national defense funding for FY1940-FY2009. Table 4 gives a more detailed picture of both regular and supplemental defense appropriations from the 103rd Congress to the present (FY1993-FY2005). Table 5 shows the President’s DOD appropriations budget requests for FY1950-FY2005 vs. final amount enacted.

This report is a research aid, which lists the DOD authorization bills (Table 1) and appropriations bills (Table 2). This report includes all the pertinent information on the passage of these bills through the legislative process: bill numbers, report numbers, dates reported and passed, recorded vote numbers and vote tallies, dates of passage of the conference reports with their numbers and votes, vetoes, substitutions, dates of final passage, and public law numbers. Table 3 shows real growth or decline in national defense funding for FY1940-FY2009. Table 4 gives a more detailed picture of both regular and supplemental defense appropriations from the 103rd Congress to the present (FY1993-FY2005). Table 5 shows the President’s DOD appropriations budget requests for FY1950-FY2005 vs. final amount enacted.

Annual report detailing the effectiveness of Texas risk management during fiscal year 2006 including cost containment measures measures to reduce workers' compensation payments.

The goal of the data intensive LDRD was to investigate the fundamental research issues underlying the application of High Performance Computing (HPC) resources to the challenges of data intensive computing. We explored these issues through four targeted case studies derived from growing LLNL programs: high speed text processing, massive semantic graph analysis, streaming image feature extraction, and processing of streaming sensor data. The ultimate goal of this analysis was to provide scalable data management algorithms to support the development of a predictive knowledge capability consistent with the direction of Aurora.