Total Quality Management: Analysis, Evaluation and Implementation Within ACRV Project Teams

Total quality management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The Assured Crew Return Vehicle (ACRV) Project Office was identified as an excellent project in which to demonstrate the applications and benefits of TQM processes. As the ACRV Program moves through its various stages of development, it is vital that effectiveness and efficiency be maintained in order to provide the Space Station Freedom (SSF) crew an affordable, on-time assured return to Earth. A critical factor for the success of the ACRV is attaining the maximum benefit from the resources applied to the program. Through a series of four tutorials on various quality improvement techniques, and numerous one-on-one sessions during the SSF's 10-week term in the project office, results were obtained which are aiding the ACRV Office in implementing a disciplined, ongoing process for generating fundamental decisions and actions that shape and guide the organization. Significant advances were made in improving the processes for two particular groups - the correspondence distribution team and the WATER Test team. Numerous people from across JSC were a part of the various team activities including engineering, man systems, and safety. The work also included significant interaction with the support contractor to the ACRV Project. The results of the improvement activities can be used as models for other organizations desiring to operate under a system of continuous improvement. In particular, they have advanced the ACRV Project Teams further down the path of continuous improvement, in support of a working philosophy of TQM

Demography Is Not Destiny, Revisited

Looks at the impending demographic challenges of the aging American population. Considers the impact of factors in addition to anticipated changes in the size and age distribution, particularly those related to the economy and public policies

Demography Is Not Destiny

Examines demographic and economic trends, and other challenges and opportunities associated with the aging American population. Highlights the interactions that occur among public programs, private institutions, and individuals. Discusses policy options

A new approach to social assistance : Latin America's experience with conditional cash transfer programs

Conditional cash transfers are a departure from more traditional approaches to social assistance, that represents an innovative, and increasingly popular channel for the delivery of social services. Conditional cash transfers provide money to poor families, contingent upon certain behavior, usually investments in human capital, such as sending children to school, or bringing them to health centers on a regular basis. They seek both to address traditional short-term income support objectives, as well as to promote the longer-term accumulation of human capital, by serving as a demand-side complement to the supply of health, and education services. Evaluation results from a first generation of programs reveal that this innovative design has been quite successful in addressing many of the criticisms of social assistance, such as poor poverty targeting, disincentive effects, and limited welfare impacts. There is clear evidence of success from programs in Brazil, Colombia, Mexico and Nicaragua in increasing enrollment rates, improving preventive health care and raising household consumption. Despite this promising evidence, many questions remain unanswered about conditional cash transfer programs, including the replicability of their success under different conditions, their role within a broader social protection system, and their long-term effectiveness in preventing the inter- generational transmission of poverty. One of the main challenges facing policymakers today is how to build off of the established success of conditional cash transfer programs, to tackle the more difficult issues of improving the quality of health, and education services, and providing a more holistic approach to both social protection, and chronic poverty.Poverty Assessment,Poverty Impact Evaluation,Health Monitoring&Evaluation,Services&Transfers to Poor,Rural Poverty Reduction

Implementation of quality improvement techniques for management and technical processes in the ACRV project

Total Quality Management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The objective of the activities described in this paper was to implement effective improvement tools and techniques in order to build work processes which support good management and technical decisions and actions which are crucial to the success of the ACRV project. The objectives were met by applications in both the technical and management areas. The management applications involved initiating focused continuous improvement projects with widespread team membership. The technical applications involved applying proven statistical tools and techniques to the technical issues associated with the ACRV Project. Specific activities related to the objective included working with a support contractor team to improve support processes, examining processes involved in international activities, a series of tutorials presented to the New Initiatives Office and support contractors, a briefing to NIO managers, and work with the NIO Q+ Team. On the technical side, work included analyzing data from the large-scale W.A.T.E.R. test, landing mode trade analyses, and targeting probability calculations. The results of these efforts will help to develop a disciplined, ongoing process for producing fundamental decisions and actions that shape and guide the ACRV organization

A Primer on Causality in Data Science

Many questions in Data Science are fundamentally causal in that our objective is to learn the effect of some exposure, randomized or not, on an outcome interest. Even studies that are seemingly non-causal, such as those with the goal of prediction or prevalence estimation, have causal elements, including differential censoring or measurement. As a result, we, as Data Scientists, need to consider the underlying causal mechanisms that gave rise to the data, rather than simply the pattern or association observed in those data. In this work, we review the 'Causal Roadmap' of Petersen and van der Laan (2014) to provide an introduction to some key concepts in causal inference. Similar to other causal frameworks, the steps of the Roadmap include clearly stating the scientific question, defining of the causal model, translating the scientific question into a causal parameter, assessing the assumptions needed to express the causal parameter as a statistical estimand, implementation of statistical estimators including parametric and semi-parametric methods, and interpretation of our findings. We believe that using such a framework in Data Science will help to ensure that our statistical analyses are guided by the scientific question driving our research, while avoiding over-interpreting our results. We focus on the effect of an exposure occurring at a single time point and highlight the use of targeted maximum likelihood estimation (TMLE) with Super Learner.Comment: 26 pages (with references); 4 figure

MHD Disc Winds and Linewidth Distributions

We study AGN emission line profiles combining an improved version of the accretion disc-wind model of Murray & Chiang with the magneto-hydrodynamic model of Emmering et al. We show how the shape, broadening and shift of the C IV line depend not only on the viewing angle to the object but also on the wind launching angle, especially for small launching angles. We have compared the dispersions in our model C IV linewidth distributions to observational upper limit on that dispersion, considering both smooth and clumpy torus models. As the torus half-opening angle (measured from the polar axis) increases above about 18? degrees, increasingly larger wind launching angles are required to match the observational constraints. Above a half-opening angle of about 47? degrees, no wind launch angle (within the maximum allowed by the MHD solutions) can match the observations. Considering a model that replaces the torus by a warped disc yields the same constraints obtained with the two other models