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.     

Automating application software generation

Many approaches have been proposed to enhance software productivity and reliability. These approaches typically fall into three categories: the engineering approach, the formal approach and the knowledge-based approach. But the optimal gain in software productivity cannot be obtained if one relies on only one of these approaches. This paper describes the work in knowledge-based software engineering conducted by the authors for the past 10 years. The final goal of the research is to develop a paradigm for software engineering which integrates the three approaches mentioned above. A knowledge-based tool which can support the whole process of software development is provided in this paper.     

An analysis of shielding against DC magnetic fields generated by electric railways. Evaluation of effective permeability of fine structure

This paper describes an effective analysis of magnetic shielding based on homogenization. The analyses become time‐consuming if the problems include the magnetic substances having fine structure. The homogenization of the structure makes it possible to analyze effectively the magnetic fields. The authors introduce a method to estimate the effective permeability of the homogenized substance. This method can be applied to any periodic structure made of magnetic substance. The magnetic shielding effects by the structures against direct‐current (DC) fields generated by electric railways are analyzed by using the present method. As a result, it is found that the overhead way and the protective fence near the railway work as a magnetic shield, whose effects can be improved by appropriate arrangement of those constructions. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(4): 7–15, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20310     

Analysis of brushless three-phase synchronous generator without exciter

Recently, a demand for small-capacity generators has been increasing as electric sources in small ships and automobiles or as portable electric sources driven by engines. It is desired that the structure of small-capacity generators be simple and robust, and that the generators be highly reliable, easily maintained and controlled. This paper describes an analysis of the original brushless synchronous generator without exciter. The output voltage can be adjusted in the wide range by controlling the stator dc current. To analyze the characteristics of this generator, the finite element method is applied. It is found that the results of theoretical analysis agree well with the experimental results.     

Synthesis and characterization of poly(ethylene aspartate)-metal complexes

Poly(ethylene aspartate) [PEA] was synthesized by the melt condensation of D,L-aspartic acid and ethylene glycol. PEA containing pendent amino and carbonyl groups in its repeating chain was used as the polymeric ligand for complexation with transition metal ions, viz. Co(II), Ni(II), Cu(II), Mn(II), Zn(II), Cd(II), Ca(II), Mg(II), Pb(II) and Hg(II). Complexation was found to be most effective in DMSO. The resulting polyester-metal complexes were solid coloured materials which have been characterized by IR spectroscopy, elemental analysis and magnetic susceptibility measurements. The thermal stability of the polyester-metal complexes was investigated by thermogravimetric analysis (TGA). On the basis of the physico-chemical studies, an oxygen and nitrogen coordinated structure for the polyester-metal complexes is proposed.     

Selecting a waste management option using a life-cycle analysis approach

Solid-waste management, and in particular the disposal of used packaging, is currently the subject of much topical debate. This is driven by both consumer and legislative pressures. Consumers see used packaging as a highly visible element of municipal solid waste, complaining of excessive packaging and low levels of recycling. Legislators, perhaps in pandering to the views expressed by consumer bodies, have been active within the CEC and individual Member States by introducing (or proposing) legislation or similar regulatory tools and targets to facilitate a greater diversion of used packaging from disposal by landfill to alternative solid-waste management practices, in particular recycling, which are widely accepted to have a lower impact on the environment. In this paper the relative environmental profiles of pursuing alternative solid-waste management practices to disposal by landfill are explored, focusing not just on solid waste per se but also on associated considerations of energy consumption and emissions, which are invariably overlooked as factors contributing to the environmental impact of solid-waste management practices.     

Prediction of Final Product Properties After Cocurrent Spray Drying

The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.