The speed and accuracy of conservation planning could be improved if maps indicating areas where grassed waterways should be placed to reduce erosion could be easily created. For five central Kentucky fields, elevation data were obtained with real time kinematic (RTK) global positioning system (GPS) and from US Geological Survey (USGS) digital elevation models (DEMs). Terrain attributes were calculated from these datasets which were used as predictor variables for neural network and logistic regression analyses. Grassed waterway prediction models were developed with these analyses. The type of activation function, type of standardization procedure, number of neurons, number of preliminary runs, and number of hidden layers had little impact on the results of the neural network analysis. Logistic regression and neural network analyses produced similar erosion prediction maps. The type of flow direction algorithm used to calculate terrain attributes did not change prediction maps substantially. Grassed waterways could be predicted in most cases with the RTK data but only in some cases with the USGS data. This modeling approach was robust and could aid conservation planners in identifying suitable areas for waterways more efficiently if accurate elevation data can be acquired.

This study, concentrating on the Ouachita Mountain Range in western-central Arkansas, extends prior work on treethrows and their influence on soil development in the region by supplying a method of determining hotspots of bedrock mining by treethrow. Binary logistic regression analysis was employed to determine the abiotic and biotic factors that are highly correlated with the rate of bedrock detachment found in uprooted rootwads from three study sites within the Ouachita National Forest. The produced logistic regression models suggest topographic factors, tree specific characteristics, as well as the local geology and soil characteristics all have a significant effect upon the probability of bedrock mining activity by treethrow throughout the Ouachita National Forest, Arkansas. This methodology has demonstrated that the forcing mechanism that causes the uprooting event intrinsically changes the relationship between the abiotic and biotic factors that control bedrock mining. Finally, the computed probabilities of bedrock being mined were geographically assigned to the appropriate environmental setting using a geographic information system to identify areas of highest odds of mining, hotspots, and lowest odds of mining highlighted.

Customer targeting is the key to the success of bank telemarketing. To compare the flexible discriminant analysis and the logistic regression in customer targeting, a survey dataset from a Portuguese bank was used. For the flexible discriminant analysis model, the backward elimination of explanatory variables was used with several rounds of manual re-defining of dummy variables. For the logistic regression model, the automatic stepwise selection was performed to decide which explanatory variables should be left in the final model. Ten-fold stratified cross validation was performed to estimate the model parameters and accuracies. Although employing different sets of explanatory variables, the flexible discriminant analysis model and the logistic regression model show equally satisfactory performances in customer classification based on the areas under the receiver operating characteristic curves. Focusing on the predicted “right” customers, the logistic regression model shows slightly better classification and higher overall correct prediction rate.

Objective: The purpose of this dissertation was to examine which student- and school-level factors differentiated (1) susceptible never smokers from non-susceptible never smokers, (2) experimental smokers from never smokers, and (3) current smokers from experimental smokers among a nationally representative sample of Canadian students in grade 9-12. Methods: Student-level data from Canada???s nationally representative 2008-2009 Youth Smoking Survey (2008 YSS) were linked with school-level data from the 2006 Census, and one built environment characteristic, and examined using multi-level logistic regression analyses. Results: Overall as hypothesized in these three studies, student-level and school-level characteristics were associated with smoking susceptibility among never smokers, experimental smoking and current smoking. The likelihood of susceptibility among never smokers (P=0.0002), experimental smoking (P<0.0001) and current smoking (P<0.001) significantly varied across schools. This study identified that attending a school in an urban (AOR=0.62; 95% CI 0.46-0.82) setting or in a high socioeconomic status (SES) neighbourhood (AOR=0.88; 95% CI 0.79-0.98) was inversely associated with odds of a student being an experimental smoker (versus a never smoker) when adjusting for student-level characteristics. The number of tobacco retailers located within a 1-km radius of each school was associated with the odds of a student being a current smoker (versus an experimental smoker) (AOR 1.03; 95% CI 1.01-1.05) and also associated with a student being a susceptible never smoker (versus a non-susceptible never smoker) (AOR 1.01; 95% CI 1.00-1.02) when adjusting for student-level characteristics. Additionally, several student-level intrapersonal and social context characteristics were associated with smoking susceptibility, experimental smoking and current smoking. Conclusions: This study showed that the characteristics of the school a student attends may increase their likelihood of a student being in any of the smoking stages that were examined. Additionally, several student-level factors were also associated with the three smoking stages. Understanding these factors will provide more insight to guide stakeholders interested in developing anti-tobacco strategies that are responsive to the risk and protective factors of adolescents in different smoking stages.

No description available.

根據金管會銀行局的統計資料顯示，台灣在2005年2月底信用卡流通卡數已高逹44,611仟張，是1992年底信用卡流通卡數的近30倍。雖然信用卡流通卡數持續增長，在1992年底時成長率高逹62.1%，之後在這十年間信用卡流通卡數成長率幾乎都有30%以上的成長率，1996年成長率為48.7%，此時正為產品生命周期中的成長期。觀察近二年信用卡流通卡數的成長率，2004年只有16.7%，今年(2005年)成長率卻下滑到1%左右，可見信用卡市場已從生命周期中的成長期逐漸邁向成熟期。銀行若想在競爭激烈的信用卡市場中搶得先機，進而獲取利潤，應進行所謂產品的製程創新，即如何在信用卡進入產品生命周期的成熟期中，加強信用風險控管以降低成本、提高消費性產品即信用卡的品質和附加價值，以及如何進一步鞏固現有的信用卡客戶。本研究擬將提供一個具體之模型，以供日後銀行預測信用卡持卡人違約或剪卡之用。 本論文擬使用國內某家銀行在2004年3月底於資料倉儲中的客戶資料，有效分析客戶數共計128萬多筆。首先，本文先將信用卡客戶依人口統計變數、信用卡持卡人與發卡機構往來狀況、信用卡持卡人之使用狀況、信用卡持卡人之消費行為以及信用卡客戶付款狀況，探討信用卡客戶的剪卡概況。接著建構一個logistic model來預測客戶的剪卡機率，再用quantile regression model 分別對高剪卡率及低剪卡率之信用卡客戶進行分析。本文的重要發現有： 1. 年齡、是否使用循環利息在不同分量下，對於剪卡率的影響皆為負向關係，而且隨著分量愈大，剪卡率下降的幅度也愈多。 2. 每月限額、半年內交易次數、預借現金次數在不同分量下，對於剪卡率的影響皆為負向關係，而且隨著分量愈大，剪卡率下降的幅也愈少。 3. 婚姻狀況、有效信用卡數在不同分量下，對於剪卡率的影響皆為正向關係，而且隨著分量愈大，剪卡率增加的幅度也愈大。 銀行可根據重要的發現結果來制定授信政策，例如在每月限額部份，對於高剪卡率的客戶而言，若提高此客戶的信用額度，將使其剪卡率下降幅度少於低剪卡率的客戶，因此，銀行可著重在鞏固低剪卡率的客戶，藉由調高其信用額度，增加這群客戶對銀行信用卡的品牌忠誠度。或者可加以參考客戶的其它持卡消費行為，使授信政策更為完全，而且又可以滿足現存客戶的需求。

Diss. Stockholm : Karol. inst., 2004.

Thesis (Ph. D.)--Florida State University, 2005. / Advisor: Dr. Fred W. Huffer, Florida State University, College of Arts and Sciences, Dept. of Statistics. Title and description from dissertation home page (viewed June 10, 2005). Document formatted into pages; contains xii, 130 pages. Includes bibliographical references.

Thesis (M.S.)--California Polytechnic State University, 2010. / Mode of access: Internet. Title from PDF title page; viewed on April 16, 2010. Major professor: Dr. Tali Freed. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Industrial Engineering." "April 2010." Includes bibliographical references (p. 71).

Thesis (M.S. in Contract Management)--Naval Postgraduate School, December 2004. / Thesis advisor(s): Jeffrey R. Cuskey. Includes bibliographical references (p. 53). Also available online.