The Business Case for Systems Engineering: Comparison of Defense Domain and Non-defense Projects

This report summarizes analysis of data collected from the 2011 Systems Engineering (SE) Effectiveness Survey performed by the National Defense Industrial Association Systems Engineering Division, the Institute of Electrical and Electronics Engineers Aerospace and Electronic Systems Society, and the Software Engineering Institute. This analysis examined the differences in the deployment and impact of SE activities between defense-domain projects and non-defense projects. The analysis found significant differences in both the deployment of SE in the two domains and the effectiveness of the SE. The report identifies specific process areas where effectiveness in one domain is noticeably higher than in the other. Further research to understand these differences will benefit both domains by enabling them to share best practice

The Business Case for Systems Engineering Study: Results of the Systems Engineering Effectiveness Survey

This report summarizes the results of a survey that had the goal of quantifying the connection between the application of systems engineering (SE) best practices to projects and programs and the performance of those projects and programs. The survey population consisted of projects and programs executed by system developers reached through the National Defense Industrial Association Systems Engineering Division (NDIA-SED), the Institute of Electrical and Electronics Engineers Aerospace and Electronic Systems Society (IEEE-AESS), and the International Council on Systems Engineering (INCOSE). Analysis of survey responses revealed strong statistical relationships between project performance and several categories of specific SE best practices. The survey results show notable differences in the relationship between SE best practices and performance between more challenging and less challenging projects. The statistical relationship with project performance is quite strong for survey data of this kind when both SE capability and project challenge are considered together

The Business Case for Systems Engineering Study: Detailed Response Data

This report contains detailed response data from The Effectiveness of Systems Engineering: A Survey. The survey had the goal of quantifying the connection between the application of systems engineering (SE) best practices to projects and programs and the performance of those projects and programs. The survey population consisted of projects and programs executed by system developers reached through the National Defense Industrial Association (NDIA) Systems Engineering Division, the Institute of Electrical and Electronics Engineers (IEEE) Aerospace and Electronic Systems Society, and the International Council on Systems Engineering (INCOSE). Analysis of survey responses revealed strong statistical relationships between project performance and several categories of SE best practices. The survey results show notable differences in the relationship between SE best practices and performance between more challenging and less challenging projects. The statistical relationship with project performance is quite strong for survey data of this kind when both SE capability and project challenge are considered together

Machine-Learning Based Smoke Detection

A machine learning based arrangement can be used to more accurately detect whether a smoke alarm should be sounded based on a determined rate of change in the measured amount of smoke. The machine learning model may be pre-trained based on training data then executed by a smoke detector to accurately distinguish between likely emergencies and nuisance conditions

Methodology for Process Improvement Through Basic Components and Focusing on the Resistance to Change.

This paper describes a multi-model methodology that implements a smooth and continuous process improvement, depending on the organization's business goals and allowing users to establish their improvement implementation pace. The methodology focuses on basic process components known as ‘best practices’. Besides, it covers following the topics: knowledge management and change management. The methodology description and the results of a case study on project management process are included

Beat Browser

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.Includes bibliographical references (p. 51-53).Beat Browser is a music browsing environment that delivers immediate audio feedback while browsing arbitrarily large music collections. The goal of Beat Browser is to give users a sense of exploring "live" and continuous audio while rapidly moving between sources by mouse. It appears their entire universe of music is playing all the time, whether they're there listening or not. Beat Browser's Universal Time Base architecture keeps a central clock running that manages the playback position of every piece of music launclied, orchestrating this perceptual illusion.by Jefferey D. Goldenson.S.M

Quantifying Uncertainty for Early Life Cycle Cost Estimates

Disclaimer: The views represented in this report are those of the authors and do not reflect the official policy position of the Navy, the Department of Defense, or the federal government.Excerpt from the Proceedings of the Tenth Annual Acquisition Research Symposium Cost EstimatingNaval Postgraduate School Acquisition Research ProgramPrepared for the Naval Postgraduate School, Monterey, CANaval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Subseasonal Clustering of Atmospheric rivers over the western United States

The serial occurrence of atmospheric rivers (ARs) along the US West Coast can lead to prolonged and exacerbated hydrologic impacts, threatening flood-control and water-supply infrastructure due to soil saturation and diminished recovery time between storms. Here a statistical approach for quantifying subseasonal temporal clustering among extreme events is applied to a 41-year (1979–2019) wintertime AR catalog across the western United States (US). Observed AR occurrence, compared against a randomly distributed AR timeseries with the same average event density, reveals temporal clustering at a greater-than-random rate across the western US with a distinct geographical pattern. Compared to the Pacific Northwest, significant AR clusters over the northern Coastal Range of California and Sierra Nevada are more frequent and occur over longer time periods. Clusters along the California Coastal Range typically persist for 2 weeks, are composed of 4–5 ARs per cluster, and account for over 85% of total AR occurrence. Across the northwest Coast-Cascade Ranges, clusters account for ∼50% of total AR occurrence, typically last 8–10 days, and contain 3–4 individual AR events. Based on precipitation data from a high-resolution dynamical downscaling of reanalysis, the fractions of total and extreme hourly precipitation attributable to AR clusters are largest along the northern California coast and in the Sierra Nevada. Interannual variability among clusters highlights their importance for determining whether a particular water year is anomalously wet or dry. The mechanisms behind this unusual clustering are unclear and require further research

A Survey of Systems Engineering Effectiveness - Initial Results

This survey quantifies the relationship between the application of Systems Engineering (SE) best practices to projects and programs, and the performance of those projects and programs. The survey population consisted of projects and programs executed by defense contractors who are members of the Systems Engineering Division (SED) of the National Defense Industrial Association (NDIA). The deployment of SE practices on a project or program was measured through the availability and characteristics of specific SE-related work products. Project Performance was measured through typically available project measures of cost performance, schedule performance, and scope performance. Additional project and program information such as project size, project domain, and other data was also collected to aid in characterizing the respondent's project. Analysis of the survey responses revealed moderately strong statistical relationships between Project Performance and several categorizations of specific of SE best practices. Notably stronger relationships are apparent by combining the effects of more than one the best practices categories. Of course, Systems Engineering Capability alone does not ensure outstanding Project Performance. The survey results show notable differences in the relationship between SE best practices and performance between more challenging as compared to less challenging projects. The statistical relationship between Project Performance and the combination of SE Capability and Project Challenge is quite strong for survey data of this type