970 resultados para University of Illinois (Urbana-Champaign campus). College of Commerce and Business Administration.
Resumo:
"(This is being submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics, June 1959.)"
Resumo:
"This copy is a Zerox photographic representation from the carbon copy of Miss Bevier's request."
Resumo:
Mode of access: Internet.
Resumo:
Mode of access: Internet.
Resumo:
"Proceedings provided through an educational grant from the Ralston Purina Company"
Resumo:
Papers from earlier conferences never published.
Resumo:
"Printed: January 1991."
Resumo:
"December 19, 2001."
Resumo:
"January 2002."
Resumo:
"Project IHR-517, Illinois Cooperative Highway Research Program."
Resumo:
Final report by University of Illinois at Urbana-Champaign, the Building Research Council [by] Kate Brown, Len Heumann, Karen Winter-Nelson. Prepared for the State of Illinois and the Illinois Housing Development Authority.
Resumo:
Mode of access: Internet.
Resumo:
Also contains brochures, directories, manuals, and programs from various College of Engineering student organizations such as the Society of Women Engineers and Tau Beta Pi.
Resumo:
This case study investigated the decision-making process of high-achieving high school students and their parents in selecting a college or university. The conceptual framework that guided this study included theoretical and empirical research framed around a three-phase model of college choice. Parental influence dominated the first phase of this model. The search phase, which was the second and the most crucial one, included financial considerations related to this decision, admissions considerations during the search phase, the psychology of decision making, and advertising strategies for teenagers. Once students completed the search phase they developed expectations of the institutions they considered prior to making the final decision. The study employed qualitative methods using individual interviews with students and their parents. ^ Six high-achieving high school seniors from a South Florida high school and their parents were selected to participate in this study. Of these students, four were female and two were male. Participants were individually interviewed on two separate occasions over a three-month period. Students and their parents were interviewed separately, with one exception, during the first set of interviews and together during the second. The data obtained from these interviews were transcribed and these transcripts were coded, categorized, analyzed, and sorted into major themes and submitted to interpretive analysis. ^ In-depth descriptions of participants' experiences during the decision-making process are described in the study. Financial factors—which included the cost of college, the socio-economic status of the family, and scholarship possibilities—drove the selection process for these students and their parents, most of whom reported their family incomes between the lower-middle to upper-middle class range. All of these students took advantage of the Bright Futures Scholarship Program, other scholarship opportunities, and the lower tuition costs of in-state public institutions. The effectiveness of recruitment techniques, such as brochures, campus visits, the development of college Web sites, and the overall impact of Internet resources, was assessed by the researcher. ^ As these students had progressed through the search phase, they developed perceptions of potential institutions as they were assisted by those around them. The value of familiarity with institutions and the use of heuristics were quite evident in the final analysis of this study, based on what the students communicated about how their knowledge of and comfort in these institutions affected their decisions. Parental influence played an important role in the selection process for the students in this study as the parents clearly directed the process, by the constant advice they gave their children and by the financial limitations they communicated to them. ^
Resumo:
The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.