Thesis (Th. M.)--Calvin Theological Seminary, 2005. / Abstract. "April 2005." Includes bibliographical references (leaves 134-138).

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

Thesis (Th. M.)--Calvin Theological Seminary, 2005. / Abstract. "April 2005." Includes bibliographical references (leaves 134-138).

Thesis (M.A.)--Grace Theological Seminary, 1990. / Abstract. Includes bibliographical references (leaves 90-92).

Please read the abstract in the 00front part of this document / Dissertation (MA (Information Science))--University of Pretoria, 2006. / Information Science / unrestricted

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.

The associated particle technique was employed to produce a collimated beam of 4.3 MeV neutrons from the reaction D(d,n)3He. A rotating target assembly permitted the use of thin deuterated polyethylene deuterium targets. The use of a position sensitive detector in the associated particle technique was demonstrated. Data was accumulated by an on-line computer system. The differential scattering cross section for 4.3 MeV neutrons was measured for scattering samples of uranium, bismuth, and lead over the angular range of 5° to 15°. The data were corrected for the effects of finite angular resolution, neutron multiple scattering, air scattering, and neutron inelortic scattering. The experimental scattering cross sections were in agreement with those calculated on the basis of a nuclear optical model interaction plus an electromagnetic Schwinger interaction. No evidence was found to substantiate anamalous cross sections at small angles. / Science, Faculty of / Physics and Astronomy, Department of / Graduate

PVC are extensively applied in many fields, such as cables, pipes, vehicles, shoes, toys and infusion bags. Generally, plasticizers are blended with PVC to improve the ability of process in industrial production; however, the toxic plasticizers will gradually migrate to the surface of products and such a leakage results in brittleness of plasticized PVC and environmental pollution. In other words, humans are frequently exposed to the potential risks. According to previous researches, cross-linked PVC was proved that it was able to hinder the migration of plasticizer. Thus, in this research, we selected some commercially used cross-linking agents and employed six different tests based on mechanical, tribological and microscopy analysis in order to seek the best solution against plasticizer migration. Thus, we expected to develop a cross-linked flexible PVC which performed improved long-term performance and extended lifetime.

In the last centuries, transition metal chemistry beсome one оf the mоst іmportant tооls for synthesis of valuable organic compounds and different chemical transformations. In particular, transition metal catalysis are capable of forming novel cross coupling bonds. In this background, photocatalysis was developed later to create new chemical transformations by the irradiation with visible light. In this regard, the combination of transition metal catalysis and photochemistry is a breakthrough in catalysis that has provided impossible transformations in organochemistry. One of the widely available reactants in synthesis are alkyl chlorides. However, it is hard to activate chemically stable C(sp3 )-Cl bond at room temperature. In this study, we overcome this limitation by excited-state palladium catalysis under mild conditions. The reaction goes through the hybrid alkyl-Pd radical as a key intermediate. The procedure provides the synthesis of oxindole and isoquinolinedione derivatives mainly from alkyl chlorides via annulation overcoming its chemical limitations. This work will focus on the generation of alkyl radicals from unactivated C(sp3 )-Cl using simple palladium catalysis

Cross-validation is a widely used technique in statistics and machine learning for predictive performance assessment and model selection. It involves dividing the available data into multiple sets, training the model on some of the data and testing it on the rest, and repeating this process multiple times. The goal of cross-validation is to assess the model’s predictive performance on unseen data. Two standard methods for cross-validation are leave-one-out cross-validation and K-fold cross-validation. However, these methods may not be suitable for structured models with many potential prediction tasks, as they do not take into account the structure of the data. As a solution, leave-group-out cross-validation is an extension of cross-validation that allows the left-out groups to make training sets and testing points to adapt to different prediction tasks. In this dissertation, we propose an automatic group construction procedure for leave-group-out cross-validation to estimate the predictive performance of the model when the prediction task is not specified. We also propose an efficient approximation of leave-group-out cross-validation for latent Gaussian models. Both of these procedures are implemented in the R-INLA software. We demonstrate the usefulness of our proposed leave-group-out cross-validation method through its application in the joint modeling of survival data and longitudinal data. The example shows the effectiveness of this method in real-world scenarios.