• Journal of Applied Reliability
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• v.16 no.1
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.

• Journal of the East Asian Society of Dietary Life
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• v.8 no.1
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• pp.20-27
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• 1998

This study estimate the amount of snack intake of 290 children from ages 3 to 6 living in Seoul, to provide some basic information for a nutrition education program for the promotion of health. Average height and weight of the children were 110.5cm and 19.7kg, respectively. Their body mass indes was 16.2kg/$m^2$ and obesity indesx was 6.5% Calorie intake from snacks was 294kcal, and protein, fat, carbohydrate were 11.3g, 9.3g and 40.6g, respectively. The 117(40.3%) boys prefered boiled-eggs and 112(38.6%) girls prefered fruits. The 133(45.9%) mothers of the children were in their thirties, and 123(42.4%) of them had a college degree. One hundred and thirty one(45.2%) mothers were house keepers, and they had been givins snacks to their children 1 or 2 times daily(245, 84.5%) The daily snack budget was 1,500 won(109, 37.6%). The person who served the snack was a mother(141, 48.6%). As a result, snack intake of pre-school children showed very good but partially showed a potential problem. We hope that the results of this study can be helpful for the nutrition education program for the health and nutrition of pre-school children.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.49-56
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• 2011

Estimating optimum hardware capacity of an e-learning system is very important process to grasp reasonable size of designing technique architecture and budget during step of ISP(information strategic planning) and development. It hugely influences cost and quality of the whole project. While investment on information system hardware has been continuously increased, there was no certified hardware capacity estimating method in e-learning system development. A guideline for hardware sizing of information systems was established by Telecommunication Technology Association in 2008. However, the guideline is not appropriate for estimating optimum hardware capacity of an e-learning system because it was designed to provide general standards for estimating hardware capacity of various types of projects. The purpose of this paper is to provide a methodology for estimating optimum hardware capacity in e-learning system development. To develop the methodology, this study, first of all, analyzes two e-learning development projects, in which the guideline was applied to estimate optimum hardware capacity. Then, this study finds out several key factors influencing on hardware capacity. Finally, this study suggests a methodology for estimating optimum hardware capacity of an e-learning system, in which weights for the factors are determined through AHP analysis.

• Journal of Environmental Health Sciences
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• v.26 no.4
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• pp.97-104
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• 2000

The purpose of this is made an examination of phosphorus loading model for eutrophication response in the Yongsan lake. For the model, we measured the total amount of nutrients derived from the Yongsan river watershed, inflow rate to the Yongsan lake, water quality, and water budget from January to December in 1999. The total amount of precipitation in the Yongsan river watershed was 4,951.7$\times$10$^{6}$ ㎥/y and inflow amount was 2,569.7$\times$10$^{6}$ ㎥/y, therefore the outflow rate of the Yongsan river watershed was 51.9%. The develop loading of total nitrogen was 86,928.1kg/d and that of total phosphorus was 22,007.6kg/d at the Yongsan river watershed, But, as the inflow loading of total nitrogen was 33,962kg/d and the inflow loading of total phosphorus was 2,218kg/d to the Yongsan lake. so each infolw rate was 39.0% and 10.1%. The hydraulic residence time was 34days, total phosphorus loading [L(P)] on the surface area was 23.398g/㎥/y, the hydraulic load( $Q_{s}$) of inflow water was 74.269m/y, the reserve rate of phosphorus in the lake was 0.359, and the settinh velocity of phosphorus was 0.114m/d at the Yongsan lake. Mathematical model of phosphorus loading to estimate the responses of eutrophication at the Yongsan lake is [ $P_{j}$] = 0.838 [L(P)/Q.(1+√ $T_{w}$)$^{-1}$ ] . ] . .

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.172-183
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• 2014

This paper measures and compares the efficiency of national health technology R&D programs focused on translational research program increasing importance using data envelopment analysis (DEA). Three input variables and three output variables are selected for DEA. Inputs are funds, researchers, and project period and outputs are SCI (E) papers, applied and granted patents, and impact factor. This study uses a three-stage approach. In the first stage, output-based DEA model is applied to evaluate the efficiency of decision making unit (DMU). In the second stage, based on efficiency scores of target diseases high-efficiency group and low-efficiency group are classified. And then strategic portfolio matrix of translational research program is composed of four dimensions combining research types. Mann-Whitney U test is then run to compare average efficiency scores among four groups. In the final stage, Tobit regression model is used to estimate factors likely to influence the efficiency. The results are expected to provide policy implications for effectively establishing investment strategy and managing performance of R&D program.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.251-258
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• 2016

Companies have developed a keen interest in bolstering their CSR activities. Especially in Japan, CSR is strongly associated with social contribution and $m{\acute{e}}c{\acute{e}}nat$ activities. On the other hand, the primary purpose of companies is to provide their products and services to consumers and thereby return value to their shareholders through sales and profits. It is, however, difficult to estimate directly the relationship between CSR and sales/profits. This study focuses particularly on CSR activities related to environmental and consumer issues and community involvement and development. It is also analyzed the relationship between the degree of CSR empathy and product purchase motivation. For accomplishment the purpose, a questionnaire is designed that elicits the respondent's degree of purchase intention and empathy toward CSR activities supported through sales. The object industry for questionnaires is TV maker. For results of the questionnaire, a covariance structure analysis is conducted to understand potential relationships among CSR activities, sales, and disposable budget. Through this study, it is able to clear the relationship between CSR activities and sales/profits. It is one of the advice to future prospect, strategy and CSR concept for the companies.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.123-128
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• 2012

For optimal reservoir operation and management, there are essential elements including water supply in agricultural reservoir and demand in irrigation district. To estimate agricultural water demand and supply, many factors such as weather, crops, soil, growing conditions cultivation method and the watershed/irrigation area should be considered, however, there are occurred water supply impossible duration under the influence of the variability and uncertainty of meteorological and hydrological phenomenon. Focusing on agricultural reservoir, amount and tendency of agricultural water supply and demand shows seasonally/regionally different patterns. Through the analysis of deviation and changes in the timing of the two elements, duration in excess of water supply can be identified quantitatively. Here, we introduce an approach to assessment of irrigation vulnerable duration for effective management of agricultural reservoir using time dependent change analysis of residual water supply and irrigation water requirements. Irrigation vulnerable duration has been determined through the comparison of water supply in agricultural reservoir and demand in irrigation district based on the water budget analysis, therefore can be used as an improved and basis data for the effective and intensive water management.

• Journal of Korean Society of Rural Planning
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• v.12 no.4 s.33
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• pp.23-32
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• 2006

Recently, Owing to booming of leisure activities and national enforcement of 5-day workweek system, Korean government has been promoting rural tourism policy of which operating project's title is Green Rural Experience Village, Rural Traditional Theme Village, etc. In this study, ken investigation result on Green Rural Experience Village sites, an estimation model of returns by green-tourism activities was developed. The model was constructed through factor analysis and regression analysis method. Regression model developed can estimate green-tourism revenue by investment budget, homepage preengagement sales, homepage visitors, capacity of eating and drinking facilities, capacity of lodging facilities. The model developed was applied in sample villages. With these results, estimation revenue was recorded average 138.3% of survey revenue, and statistical significance was good(correlation coefficient $R^2$ = 0.8255, level of significance : 0.000), and the range of relative error was recorded largely from -7.1% to 158.6%, and average relative error was 38.3% and good. And, the model developed in this study have the critical point in aspects of insufficient data, but the results will be used in green-tourism policies and projects, and revenue estimation about each village in the present and future is limited, but in province or the whole country the application is good.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1076-1080
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• 2003

$CO_2$ uptake of vegetation is one of the important variables in order to estimate photosynthetic activity, plant growth and carbon budget estimations. The objective of this research was to develop a new estimation method of $CO_2$ uptake of vegetation based on airborne hyperspectral remote sensing measurements in combination with a photosynthetic rate curve model. In this study, a compact airborne spectrographic imager (CASI) was used to obtain image over a field that had been set up to study the $CO_2$ uptake of corn on August 7, 2002. Also, a field survey was conducted concurrently with the CASI overpass. As a field survey, chlorophyll a content, photosynthetic rate curve, Leaf area, dry biomass and light condition were measured. The developed estimation method for $CO_2$ uptake consists of three major parts: a linear mixture model, an enhanced big leaf model and a photosynthetic rate curve model. The Accuracy of this scheme indicates that $CO_2$ uptake of vegetation could be estimated by using airborne hyperspectral remote sensing data in combination with a physiological model.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.11-24
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• 2006

Coastal sea surface temperature (CSST) and meteorological data from January through December 1995 are used to estimate the net surface heat flux and heat content for Sendai Bay. The average annual surface heat flux in the area north of the bay is estimated to be $+35Wm^{-2}$, whereas the southwestern area is estimated to be $+56Wm^{-2}$. Therefore, the net surface heat flux shows a net gain of heat over the whole bay. The largest heat gain occurs near Matsukawaura, where the strong Kuroshio/Oyashio interaction produces anomalously cold SST and wind is more moderate than in other regions of Sendai Bay over most of the year. The lowest heat gain occurs around Tashiro Island, where the temperature difference between air and sea surface is lower and wind is stronger. The heat budget shows that both surface forcing and horizontal advection are potentially important contributors to the seasonal evolution of CSST in the bay. From the A VHRR and SeaWiFS data, it is found that offshore conditions between the bay and Eno Island are different due to the presence of the Ojika Peninsula. It is also shown that the temporal behaviors of SSTs in the bay are closely connected with the air-sea heat flux and offshore conditions.