This thesis examines the evolution of Internet based knowledge networks (e-knowledge networks) in the domain of sustainable development. The objective of this thesis is to use an engineering systems approach to understand knowledge networks, identify the barriers to their sustainability…

The first two chapters of this thesis investigate a possibly fundamental aspect of technological progress. If knowledge accumulates as technology progresses, then successive generations of innovators may face an increasing educational burden, forcing them to spend longer periods in education…

Policies to avert the threat of dangerous climate change focus on stabilizing atmospheric carbon dioxide concentrations by drastically reducing anthropogenic emissions of carbon. Such reductions require limiting the use of fossil fuels-which supply the bulk of energy to economic activity,…

by Leslie Prince Rudolph., Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999., Includes bibliographical references (leaves 70-72).

by Roshanak Gilani., Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2001., Includes bibliographical references (p. 71-73).

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1990., Includes bibliographical references (leaves 231-234).

by Vuong P. Nguyen., Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997., Includes bibliographical references (leaves 67-68).

An Electronic Government Procurement (e-GP) project, as most of complex software systems development and implantation, requires sophisticated and strong managerial concepts and skills. So, an effective and consistent managerial framework is needed.
Traditional project management models, that propose a series…

I propose a common framework that combines three different paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way to model many machine learning and machine perception problems. Therein, one provides domain specific…