Thesis (M.P.H.)--University of Michigan, 1947.

Thesis (M.S.P.H.)--University of Michigan, 1939.

Thesis (M.S.P.H.)--University of Michigan, 1939.

Thesis (M.P.H.)--University of Michigan, 1947.

Thesis (Ed.D.)--Teachers College, Columbia University. / Typescript. Sponsor: Karl W. Bigelow. Dissertation Committee: Ethel M. Feagley, Maurice F. Tauber. Type C project. Includes bibliographical references (leaves 231-237).

Thesis (M.A.)--University of Wisconsin--Madison, 1966. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

"The purpose of this study is to survey the need for key punch operators in state government agencies and the adequacy of facilities in the Tallahassee, Florida area for training potential employees in this field. This study has attempted to determine the responsibility which business educators in the Tallahassee area have in providing trained personnel for automatic data-processing departments in state agencies. An effort was made to determine whether key-punch training and training for operators of other data-processing machines can best be given in business departments of schools in the Tallahassee area, in on-the-job training programs within the various state agencies, in offices of manufacturers of automatic data-processing equipment, or in cooperative programs"--Introduction. / Typescript. / "January, 1969." / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Arts." / Advisor: Frank Dame, Professor Directing Study. / Includes bibliographical references (leaves 85-89).

No description available.

This study presents a history of the development and implementation of a punched card registration system in North Texas State College. The study also covers planning stages of registration materials, and a description of the various stages and processes involved in a typical semester from pre-registration preparations through posting the student's grades to the permanent record. To help fill the need for ready reference to methods used in various institutions across the nation, this study will present a history of the development and implementation of a punched card registration system in North Texas State College, with emphasis placed upon those areas of probable major interest to other colleges faced with a similar problem. The study will cover planning stages of registration materials, and will then present a a description of the various stages and processes involved in a typical semester from pre-registration preparations through posting the student's grades to the permanent record.

Dissertation submitted in compliance with the requirements for Masters Degree in Technology in the Department of Electrical Engineering (Light Current, Technikon Natal, 2000. / The computational analysis of eukaryotic promoters are among the most important and complex research domains that may contribute to complete gene identification. The current methods for promoter recognition are not sufficiently developed. Eukaryotic promoters contain a number of short motifs that may be used in promoter recognition. Having good computational models for these motifs can be crucial for increased efficiency of promoter recognition programs. This study proposes a combined statistical and LVQ neural network system as a computational model of the TAT A box motif of eukaryotic promoters. The methodology used is universal and applicable to any short functional motif in DNA. The statistical analysis of the core TAT A motif hexamer and its neighboring haxamers show strong regularities that can be used in motif recognition. Moreover, the positional distribution of the TAT A motif in terms of its distance from the transcription start site is very regular and is used in the statistical modeling. Furthermore, the matching score of the position weight matrix for the motif was used as a part of the model. Based on these statistical properties. a novel LV Q classifier for TAT A motif recognition is developed. The characteristics of the method are that the genetic algorithm was used for finding good initial weights of the LV Q system, while fine tuning of two LVQ networks was done by the lvq? algorithm. The final computational model is developed for a recognition level of 67.8o/c correct recognition on the test set with less than 1% false recognition. This model is evaluated in the task of promoter recognition on an independent test set. The results in promoter recognition outperform three other promoter recognition programs. It is shown that the recognition of promoters based on the recognition of the TAT A motifs using this new model is superior to the recognition based on the currently used position weight matrix description of this motif. / M