• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.111-123
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• 2019

In this paper, software activity, software activity instance, and the quality of the activity instance are defined as the 'activity which is performed on the software product by a person or a group of persons,' the 'distinctive and individual performance of software activity,' and the 'performer's evaluation on how good or bad his/her own activity instance is,' respectively. The representative values of the instance quality population associated with a product and its sub-population are defined as the (software) activity quality and activity quality characteristic of the product, respectively. The activity quality model in this paper classifies activity quality characteristics according to the classification hierarchy of software activity by the goal. In the model, a quality characteristic can have two types of sub-characteristics : Special sub-characteristic and component sub-characteristic, where the former is its super-characteristic too simultaneously and the latter is not its super-characteristic but a part of its super-characteristic. The activity quality model is parsimonious, coherent, and easy to understand and use. The activity quality model can serve as a corner stone on which a software quality body of knowledge, which constituted with a set of models parsimonious, coherent, and easy to understand and use and the theories explaining the cause-and-relationships among the models, can be built. The body of knowledge can be called the (grand) activity-centric quality model of software.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.265-273
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• 2004

We got the growth distance curve by spline smoothing method with observed marketing data and the growth velocity curve by the derivation of the growth distance curve. Using this growth velocity curve, we defined the several characteristic points which describe the variation of marketing data. In this paper, to specify several patterns of marketing data, we suggested characteristic function by using these characteristic points. In addition, we applied characteristic function to the seventeen brands of electric home products data.

• Korean Journal of Child Studies
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• v.22 no.4
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• pp.189-199
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• 2001

The purpose of this study was to explore the relationship between caregivers' characteristic variables and quality of child care and to investigate the magnitude of the association between variables and quality of child care according to children's age. The following factors were suggested as the caregivers' characteristic variables: Total years of caregiving experience, educational level, job satisfaction, amounts of turnover, time for commuting, salary, pay step, years of work in charge of current children, perception on the recommended caregiver/child ratio. The results of the study were as follows : First, it was found that caregivers' salary, total years of caregiving experience, pay step, perception on the recommended caregiver/child ratio, age, and amounts of in-service program were significant among caregivers' variables. Second, when the caregivers' characteristic variables were examined in terms of children's age respectively, the effects of teacher-related variables to influence the child-care quality were significantly different according to children's age group.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.88-98
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• 1997

For quality improvement, it is important to reduce variations of the quality characteristic. That can be achieved by the a, pp.ication of parameter design methodology to make the performance of the quality characteristic robust over the variety of noise conditions. Taguchi has used the signal-to-noise ratios for that purpose. For the static target characteristic and the dynamic characteristic problem, we propose a reasonable generalized SN ratio and p-value plot for identifying dispersion factors. The orginal idea of the p-value plot in from the gamma-plot in Lunani, Nair & Wasserman(1995). The graphic advantage of the p-value polt for identifying dispersion factors is illustrated through constructed examples.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.94-110
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• 2002

This research focuses on internet advertisement success factors derived from the relevant researches and clarified the concept of user and information characteristics. The corresponding determinants are suggested such as organizational characteristics, user characteristics, and information characteristics. Success factor of internet advertisement is used by user attitude. We then examine the impact of corresponding determinants on the success factors. Hypotheses on their characteristics were tested for 174 persons. The results indicated that organizational characteristic, user characteristic and information characteristic was partly found as a positive impact on the internet advertisement success while quality of innovation and purchase promotion traits were not significant.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.20-32
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• 1995

This paper is concerned with the economic selection of both the lower limit and the process mean for a continuous production process. Consider a production process where items are produced continuously. All of the items are subject to acceptance inspection. The items for which the measured values of the quality characteristic are larger than the lower limit are accepted, and those smaller than the lower limit are rejected and excluded from shipment. The process mean may be set higher to reduce the costs incurred by imperfect quality. Using a higher process mean, however, results in a higher production cost when production cost is an increasing function of the quality characteristic. Assuming that the quality characteristic is normally distributed with known variability, cost models are constructed which involve production cost, cost incurred by imperfect quality, rejection cost, and inspection cost. Methods of finding optimal values of the lower limit and the process mean are presented and numerical examples are given.

• International Journal of Quality Innovation
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• v.2 no.1
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• pp.50-57
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• 2001

The economic design of specification limits must be determined on an economic basis where we minimize total loss to society, which consists of both the producer and the consumer. Economic specification limits have been developed based on the assumption that the quality characteristic is normally distributed. Unfortunately, the assumption is not to meet some practical cases. In this paper, some non-normal distributions are considered for quality characteristic with geometrical features. An economic model for selecting the optimum specification limits on the basis of minimizing total cost is introduced. A case study is presented to illustrate the application in practice.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.155-164
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• 2000

This paper considers the problem of determining the optimum proccss mean value of the quality characteristic of interest, and the screening limit for two correlated variables under single-stage screening. In the single-stage screening, inspection is performed on two correlated variables which are correlated with the quality characteristic of interest. Model is constructed which involves selling price, production, inspection, and penalty costs. Method for finding the optimum process mean and screening limit are presented when the quality characteristic of interest and the correlated variables are assumed to be jointly normally distributed. A numerical example is presented and numerical analysis is performed to compare the proposed screening based on two screening variables with screening based on one screening variable.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.161-175
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• 2000

The problem of jointly determining the optimum process mem and screening limits for each market is considered in situations where there are several markets with different price/cost structures. Two inspection procedures are considered; an inspection based on the quality characteristic of interest, and an inspection based on a surrogate variable which is highly correlated with the quality characteristic. The quality characteristic is assumed to be a normal distribution with unknown mean and known variance. A Taguchi's quadratic loss function is utilized for developing the economic model for determining the optimum process mean and screening limits. A numerical example is given.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.67-73
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• 2000

The water quality of inland stream is polluting with industrialization and urbanization, and with that water quality of lake also deteriorated, to manage water quality pollution problem of lake, new water quality management method is needed. As a pilot study of the method that manage water quality of lake using GSIS(Geo-Spatial Information System), we study the method which automatically extract the hydraulic characteristic informations of lake in GSIS environment. Also, as an example of practical use of the extracted hydraulic characteristic information of lake, we carry out the characteristic analysis of waterbody flow using finite different method. With the automation the extraction procedure of hydraulics characteristic information needed in characteristic analysis of waterbody flow, we carried out the analysis efficiently. Particularly, with the extraction of section information on lake not in layout form, in analyzable form, we make the analysis that section information of lake was indispenably required(e.g. stratification analysis) possible in GSIS environment.