• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.76-86
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• 2020

Technology growth curve methodology is commonly used in technology forecasting. A technology growth curve represents the paths of product performance in relation to time or investment in R&D. It is a useful tool to compare the technological performances between Korea and advanced nations and to describe the inflection points, the limit of improvement of a technology and their technology innovation strategies, etc. However, the curve fitting to a set of survey data often leads to model mis-specification, biased parameter estimation and incorrect result since data through survey with experts frequently contain outlier in process of curve fitting due to the subjective response characteristics. This paper propose a method to eliminate of outlier from a technology growth curve using M-estimator. The experimental results prove the overall improvement in technology growth curves by several pilot tests using real-data in Defense Science and Technology Survey reports.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.6
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• pp.555-561
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• 2010

Predicted noise level has been used to assess the annoyance response since noise map was generalized and being the normal method to assess the environmental noise. Unfortunately using predicted noise level to derive the annoyance prediction curve caused some problems. The data have to be grouped manually to use the annoyance prediction curve. The aim of this paper is to propose the method to handle the predicted noise level and the survey data for annoyance prediction curve. This paper used the percentage of persons annoyed(%A) and the percentage of persons highly annoyed as the descriptor of noise annoyance in a population. The logistic regression method was used for deriving annoyance prediction curve. It is concluded that the method of dichotomizing data and logistic regression was suitable to handle the predicted noise level and survey data.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.5
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• pp.37-40
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• 1995

In this paper, we investigate the daily load curve and yearly lighting hours of general and industrial Korean lighting apparatus. The daily load curve of lighting apparatus shows the peak use at 8 p.m. in general and 10 a.m. in industrial building. The yearly lighting hours are 2,948 hours in general and 4,066 hors in industrial building.

• Korean Management Science Review
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• v.26 no.1
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• pp.7-20
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• 2009

The framework of "blue ocean strategy (Kim and Mauborgne, 2005)" applies to not only business firm level but also region or regional industry level. The paper suggests an approach of survey-based blue ocean strategy formulation. The result from survey on customer group and non-customer group gives information on positions of value curves for regions on strategy canvas and hints on how to reposition the focal region's value curve for both increases in value for customers and decreases in cost for local government, i.e., value innovation. In the context of rafting industry in Korea, this study shows the process how blue ocean strategy can be formulated with results from the survey on customers and business people in rafting industry. Relative positions of value curves on strategy canvas and importance scores for strategy elements provides the local government in region A with implications on which elements to raise or to reduce to create "blue ocean" in rafting industry under fierce inter-region competition.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.31.1-31.1
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• 2016

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this talk, we outline this project, and present a few scientific highlights, such as the early light curve of SN 2015F in NGC 2442.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.663-673
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• 2009

Driver's perceived curve radius is different from actual curve radius at curve sections. This is called visual distortion. It has effect on operation speed according to driver's perception and finally bad effect on safety at curve sections. At present, however, there is no research on quantitatively analysis of visual distortion and no criteria for curve section design considering the visual distortion. Therefore, this study focus on finding degree of visual distortion and suggesting design criteria by visual distortion analysis. The process of this study is as below; First, a calculaiton model of perceived curve radius was developed by survey using computer simulation. In this model, a dependent variable is perceived curve radius and an independent variable is geometric factors. Second, degree of visual distortion was calculated from ratio of perceived curve radius to actual curve radius. Finally, design criteria were suggested through influencing factor analysis of visual distortion at curve sections.

• Journal of the Korean Chemical Society
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• v.59 no.6
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• pp.508-519
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• 2015

In this study, the pre-service chemistry teachers’ understanding of potential energy curve was investigated. The subjects were 24 junior students and 26 senior students studying chemistry education in a college of education. A concept questionnaire consisted of thought experiments with different initial conditions was developed to survey the pre-service teachers’ conceptions of potential energy curve. The survey results showed that the pre-service chemistry teachers had difficulties to accept the negative values for potential energy and total energy. And they knew the mechanical energy conservation but they could not apply it properly to the thought experiment situations given in the questionnaire. Also they had the knowledge about the direction of force exerted between the two balls, but many of them believed that the balls would stop moving at the bottom of potential energy curve well. In addition, it was discovered that few pre-service teachers could relate the thought experiments to the chemical bonding, the liquefaction of gas, and the molecular vibration.

• Journal of Biosystems Engineering
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• v.29 no.5 s.106
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• pp.441-450
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• 2004

This study was performed to estimate mid and long term demands of a tractor, a rice transplanter, a combine and a grain dryer by using logistic curve function and Markov chain model. Field survey was done to decide some parameters far logistic curve function and Markov chain model. Ceiling values of tractor and combine fer logistic curve function analysis were 209,280 and 85,607 respectively. Based on logistic curve function analysis, total number of tractors increased slightly during the period analysed. New demand for combine was found to be zero. Markov chain analysis was carried out with 2 scenarios. With the scenario 1(rice price $10\%$ down and current supporting policy by government), new demand for tractor was decreased gradually up to 700 unit in the year 2012. For combine, new demand was zero. Regardless of scenarios, the replacement demand was increased slightly after 2003. After then, the replacement demand is decreased after the certain time. Two analysis of logistic owe function and Markov chain model showed the similar trend in increase and decrease for total number of tractors and combines. However, the difference in numbers of tractors and combines between the results from 2 analysis got bigger as the time passed.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.383-384
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• 2016

The Special Needs Education Assessment Tool (SNEAT) were verified of reliability and validity. However, the reliability and validity has been verified is only Okinawa Prefecture, the national data has not been analyzed. Therefore, this study aimed to verify the reliability and construct validity of SNEAT in Miyagi Prefecture as part of the national survey. SNEAT using 55 children collected from the classes on independent activities of daily living for children with disabilities in Miyagi Prefecture between November and December 2015. Survey data were collected in a longitudinal prospective cohort study. The reliability of SNEAT was verified via the internal consistency method; the coefficient of Cronbach's ${\alpha}$ were over 0.7. The validity of SNEAT was also verified via the latent growth curve model. SNEAT is valid based on its goodness-of-fit values obtained using the latent growth curve model, where the values of comparative fit index (0.997), tucker-lewis index (0.996) and root mean square error of approximation (0.025) were within the goodness-of-fit range. These results indicate that SNEAT has high reliability and construct validity.

• 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.