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Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 42-45).

Thesis (M.S.)--Wisconsin. / Includes bibliographical references (leaves 36-37).

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Includes bibliographical references (leaves 44-47). Also available online (PDF file) by a subscription to the set or by purchasing the individual file.

The kinematic characteristics of 17 elite male cross-country skiers competing in the 50 km race of the 1992 Winter Olympic Games were determined. Each skier used the open field skating technique, one of four skating techniques used in free technique cross-country ski races. Skiers were filmed by the use of three video cameras, placed at a filming site on a flat portion of the racing course. Digitized data from the video were used to determine selected kinematic parameters which included: cycle velocity; cycle length; cycle rate; center of mass (CM) velocity vector angle; CM lateral displacement; CM lateral velocity; CM horizontal velocity; ski angles; ski edging angles; several types of pole angles; and hip, knee, and trunk angles. Temporal characteristics including strong side and weak side ski and pole phase times were also calculated. Cycle velocity and cycle length were found to be significantly related as were cycle velocity and the maximum strong side knee angle (r > .48, p < .05). Cycle velocity and the CM velocity vector angle were found to have only a moderate non-significant relationship as did cycle velocity and the strong and weak side ski angles. For those skiers using the open field skating technique, CM lateral motion (as measured by the CM velocity vector angle and the ski angles) did not seem to be a distinguishing factor between faster and slower skiers, as hypothesized. However, cycle length and the maximum strong side knee angle did seem to distinguish faster from slower skiers. Skiers who covered more distance throughout a cyde tended to have faster cycle velocities. Contributing to this increased distance could have been the thrust of the strong side ski. Skiers with the most strong side knee extension tended to ski the fastest. Thus, it seems that greater leg extension results in greater propulsive forces and greater velocity. / Graduation date: 1993

Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 62-65).

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Typescript. Chairperson, Graduate Committee: Daniel P. Heil. Includes bibliographical references (leaves 44-47).

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Includes bibliographical references (leaves 44-47).

Throughout history, military officers have relied on maps to provide spatial information and make informed battlefield and other problem-solving decisions. Today’s officers can put even more spatial information at a soldier’s fingertips if they are made aware of the power of geographic information systems and software. This paper makes the argument that an informal education and introduction to the uses of geographic information systems (GIS) during their participation in reserve officer training corps (ROTC) can help provide future officers with a basic understanding on how GIS can impact their ability to solve military relevant problems with these technologies and can aid in their decision making. This project created a web application using python and based on military mapping manuals and defense tools that allow a user to create a model of how quickly the user could be able to move over a given terrain. This web application was given to military officers in ROTC training at the University of Arizona prior to participation in a land navigation exercise to help them plan and prepare their path through the event. Students using the app prior to the exercise were able to see how the information provided by GIS can help them make decisions and times were compared between those that used the tool and those that did not. This tool, and the subsequent exercise provided increased awareness in military applications of GIS for those future military officers and helps inspire them to pursue more information on the technology.

This dissertation adds to the literature on least squares model averaging by studying and extending current least squares model averaging techniques. The first chapter reviews existing literature and discusses the contributions of this dissertation. The second chapter proposes a new estimator for least squares model averaging. A model average estimator is a weighted average of common estimates obtained from a set of models. I propose computing weights by minimizing a model average prediction criterion (MAPC). I prove that the MAPC estimator is asymptotically optimal in the sense of achieving the lowest possible mean squared error. For statistical inference, I derive asymptotic tests on the average coefficients for the "core" regressors. These regressors are of primary interest to researchers and are included in every approximation model. In Chapter Three, two empirical applications for the MAPC method are conducted. I revisit the economic growth models in Barro (1991) in the first application. My results provide significant evidence to support Barro's (1991) findings. In the second application, I revisit the work by Durlauf, Kourtellos and Tan (2008) (hereafter DKT). Many of my results are consistent with DKT's findings and some of my results provide an alternative explanation to those outlined by DKT. In the fourth chapter, I propose using the model averaging method to construct optimal instruments for IV estimation when there are many potential instrument sets. The empirical weights are computed by minimizing the model averaging IV (MAIV) criterion through convex optimization. I propose a new loss function to evaluate the performance of the estimator. I prove that the instrument set obtained by the MAIV estimator is asymptotically optimal in the sense of achieving the lowest possible value of the loss function. The fifth chapter develops a new forecast combination method based on MAPC. The empirical weights are obtained through a convex optimization of MAPC. I prove that with stationary observations, the MAPC estimator is asymptotically optimal for forecast combination in that it achieves the lowest possible one-step-ahead second-order mean squared forecast error (MSFE). I also show that MAPC is asymptotically equivalent to the in-sample mean squared error (MSE) and MSFE. / Thesis (Ph.D, Economics) -- Queen's University, 2013-07-17 15:46:54.442