Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

Modeling alternative zoning strategies in forest management

To satisfy public demands for environmental values, forest companies are facing the prospect of a reduction in wood supply and increases in costs. Some Canadian provincial governments have proposed intensifying silviculture in special zones dedicated to timber production as the means for pushing out the forest possibility frontiers. In this paper, we compare the traditional two‐zone land allocation framework which includes ecological reserves and integrated forest management zones with the triad — a three‐zone scheme which adds a zone dedicated to intensive timber production. We compare the solutions of the mixed‐integer linear programs formulated under both land‐allocation frameworks. We explore through sensitivity analysis the conditions under which the triad regime can offset the impact on timber production from increased environmental demands. We show that under the realistic conditions characteristic to Coastal British Columbia, higher environmental demands may be satisfied under the triad regime without increasing the financial burdens on the industry or reducing its wood supply. This occurs, however, only if regulatory constraints in timber production zone are flexible.     

EM procedures using mean field-like approximations for Markov model-based image segmentation

Image segmentation using Markov random fields involves parameter estimation in hidden Markov models for which the EM algorithm is widely used. In practice, difficulties arise due to the dependence structure in the models and approximations are required. Using ideas from the mean field approximation principle, we propose a class of EM-like algorithms in which the computation reduces to dealing with systems of independent variables. Within this class, the simulated field algorithm is a new stochastic algorithm which appears to be the most promising for its good performance and speed, on synthetic and real image experiments.     

舰载火箭武器系统随机响应分析

利用随机振动复模态分析，提出了一种求解时变线性系统，在确定性激励与随机激励共同作用下非平稳随机响应的计算方法，并以舰载火箭武器系统为研究对象，用该法探讨了海浪对舰面火箭发射初始扰动和系统振动特性的影响。     

迭代回归法计算T型电位滴定中试液含量

本文将迭代回归法计算Ｔ型电位滴定中，叙述了其原理及数学推导，并运算了一批实验数据，结果表明，该法准确度较高，且不需空白溶液校正。     

概率空间中的一个不等式

设｛Ｚ，（Ｗ）｝是定义在概率空间上的独立的随机变量序列，Ｚ（Ｗ）具有方差为期望Ｅ（Ｚｎ）＝０．本文证明了对任意算数序列｛ｂｎ｝及任意的存在充分大的整数Ｎ＞０使当Ｎ＇＞Ｎ″＞Ｎ时．有此不等式在随机级数研究中有重要作用．     

光敏丝室探测器PET的触发判选处理器

介绍了为光敏丝室探测器PET而设计的触发判选处理器（TRIG）的结构和原理，该处理器具有触发判选，计数率损失测量，随机符合事例率测量，探测器分区计数统计以及系统定标等多项功能，由于应用了EPLD技术和流水线作业等技术，实现了TRIG系统的高集成度和高性能 。     

预测井眼稳定性的力学化学耦合方法

在井眼力学稳定性评价的基础上，将硬脆性页岩水化后岩石强度等参数的变化规律用于页岩水化前后坍塌压力变化的对比分析，结果表明，地层坍塌压力当量密度随页岩水化程度的增加逐渐升高。给出了预测井眼稳定性的力学化学耦合方法，并将该方法应用于现场生产中，取得了较好的预测效果     

A comparison of backpropagation and general regression neural networks in quantative trace metal analysis using anodic stripping voltammetry and cybernetic instrumentation

A comparison is made between backpropagation and general regression neural networks for the prediction of parts per billion lead concentration when used to process data obtained from digested curry powder by the electrochemical analysis method of differential pulse, anodic stripping at a thin film mercury electrode (TFME). Two data sets are used, one requiring the net to classify an unknown analytical data vector into one of a number of previously learnt concentrations, and one requiring the net to predict the probable concentration of an unknown sample by interpolation of the already learnt concentrations. For both of these data sets the general regression neural network is shown to train faster and to provide results superior to those obtained by backpropagation.     

Harvesting small trees and forest residues

Eight countries collaborated and shared technical information on the harvesting of small trees and forest residues in a three year program. Proceedings and reports from workshops and reviews are summarized in a review of activities and harvesting systems of the participating countries. Four databases were developed for harvesting and transportation of these materials.