• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.400-420
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• 2012

This study explores the way to enhance research performance focusing basic and fundamental technology when researchers conduct international joint research with counterparts in foreign countries, funded under the National R&D programs. In order to retain validity and objectivity, mixed approaches including qualitative and quantitative are adapted at the first step. Through this step, main factors affecting the research performance can be addressed, such as the number of SCI papers published, conference attendance held both in domestic and foreign countries, researchers holding PhD involving in projects. Then, at the second step, DEA methodology is applied to explore the way to enhance research performance, based on the analysis at first step. The result at second step shows that the various ways can be drawn according to programs respectively and the general assumption of research funds and number of projects affecting positive outcome is not absolutely mentioned. Therefore, this study implies that input variables including research funds are not compatible with research performance in terms of international joint research and suggests further that the decisive outcome and management be reconsidered according to the programs respectively under the national R&D program.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.55-62
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• 2020

To estimate headwater stream temperature with seasonal variations, we analyzed precipitation, runoff and air temperature in experimental forest of Kangwon National University, Gangwon-do (2017~2018 years). The daily mean value of headwater stream temperature for spring was 6.9~17.7℃ and correlated with air temperature, that for summer and fall were 12.2~26.3℃ and 3.6~19.3℃, correlated with air temperature and runoff. Based on seasonal variations, we applied for stepwise multiple linear regression analyses to estimate headwater stream temperature with seasonal variations. The equations were headwater stream temperature(WT)_spring=(0.553×Air temperature)+(0.086×Runoff)+4.145 (R²=0.505; p<0.01), WT_summer=(0.756×Air temperature)+(-0.072×Runoff)+2.670 (R²=0.510; p<0.01), and WT_fall=(0.738×Air temperature)+(0.028×Precipitation)+2.660 (R²=0.844; p<0.01). The coefficient of determination (R²) was greater than when it was estimated by air temperature in all seasons and progressively increased from spring to winter. Therefore, we indicated difference on estimated magnitude of stepwise multiple linear regression, due to effects on headwater stream temperature of different environmental factors with seasonal variations. Furthermore, temporal factors with spatial characteristics (e.g., river versus headwater stream) could be recommended for estimating headwater stream temperature.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.222-222
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• 2022

최근 기후변화로 인해 지역 및 시기별로 강수량이 편중되면서 가뭄(0.72회/년) 등 물 관련 재해가 빈번하게 발생하고 있으며, 가뭄의 강도 또한 심화되는 추세이다. 본 연구대상 지역인 태안군과 괴산군의 경우 기후변화 시나리오(RCP 4.5)를 적용, 미래(~2100년) 기상조건에 대하여 기존 농업용 저수지의 용수공급능력을 평가한 결과, 가뭄대응(내한) 능력이 감소하는 것으로 분석되었다. 한편, 농업가뭄의 경우 주로 영농기에 발생하여 장마가 시작되면서 해소되었으나, 최근 기후변화로 인해 지속기간이 점차 증가하여 가뭄피해가 매년 반복되고 있다. 그러나, 현재까지 추진된 가뭄대책의 경우 관정개발, 저수지 준설 등 단기·사후처방 중심의 대책이 마련되어 지속적인 재해관리와 예방에 많은 어려움을 겪고 있다. 이에 본 연구에서는 지역 맞춤형 가뭄대응 종합대책을 마련하여 기후 변화대비 안정적인 영농기반을 구축하고자 하였다. 기존시설 개선, 수요관리 등 최근 정부정책 방향과 재원조달 방안을 고려, 법적근거(농어촌정비법 등)에 의한 실현 가능한 사업계획을 수립하는 한편, 다목적 농촌용수 개발, 용수이용체계 재편 등 사업유형을 구분한 후 단계별(장·단기) 가뭄대책을 마련하였다. 가뭄대책 수립 시 한국농어촌공사에서 개발한 '수리수문 설계 시스템(K-HAS)'을 이용하여 용수 수요량을 산정하였고, 기존 수리시설물별 물 수지 분석을 통해 여유수량이 확보된 수원을 최대한 활용코자 하였다. 저수지 개발 등 신규 수자원 확보가 용이한 내륙·산간지역의 경우 중·대규모 저수지(유효저수량 1백만m³, 유역면적 200ha이상) 개발계획을 수립하는 한편 지역특성(형상, 표고차 등), 개발여건 및 경제성 등을 고려하여, 적정 개발범위(수혜면적 20ha이상)을 설정하였다. 한편, 신규 수자원개발이 어려운 도서·해안지역의 경우 용수 재이용(회귀수 활용) 및 담수호 내 염해방지시설을 도입하는 등 지역 맞춤형 가뭄대책을 수립하였다. 본 연구에서 제시한 단계별(장·단기) 가뭄대책이 차질없이 시행될 경우 기후변화 대비 안정적인 농업용수공급이 가능하고, 상습가뭄 발생(물 부족) 지역에 대하여 효율적이고 합리적인 물(수요·공급)관리가 가능할 것으로 기대된다.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.165-198
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• 2013

The purpose of the study is to identify risk factors and analyze risk impacts to increase R&D outcome by taking into consideration the activities undertaken in each phase of New Product Development(NPD) process. The paper builds on survey research that has been developed new IT products within the past 5 years at SAMSUNG and LG subsidiaries in the Republic of Korea. This study identified risk factors in accordance with NPD process and evaluated the identified risk factors with survey questionnaires. To analyze the risk impacts were used to perform a logistic regression analysis based on R&D output. The impact of risk factors were higher for the low-output group. High-output group took a risk into consideration unique undertakings in project management and managed risk factors effectively in order to increase R&D output. Consequently, with the aim of improving output of R&D, a risk management is necessary to identify the risk factors for each phase of NPD and focus on managing risk factors with great effect.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.126-139
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• 2011

In the traditional four-step travel demand models, each step is sequentially conducted following the model estimation at the previous step. The accuracy of the following model is partly dependent on whether the model at the former stage was properly established or not. Therefore, trip generation, which is the first step in this conventional model, has great effects on the modeling process and forecasting results. Linear regression models for trip generation of Seoul Metropolitan Area might increase the forcasting errors, since a variety of land-use characteristics are not considered. Hence, in this study, zonal factors such as socioeconomic and land use variables are included to improve the elaboration of trip generation. Comparing the %RMSE with the existing models, which contain bigger errors in the zones highly based on the secondary and tertiary industries than residence-based, the trip generation models including those variables seem more appropriate overall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.595-601
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• 2011

There is currently applied to the unit cost per a distance (KRW/km) for estimating the conceptual cost of civil work on basic planning stage of high speed railroad. This unit cost is an arithmetic average value based on historical data, which could be in big error. It also is difficult to explain the deficiency comparing the estimated cost derived from next basic design stage. This study provides the conceptual estimation model using by the parametric method and regression analysis. Independent variables are the distance and the geological materials (earth, weathered rock, soft-rock, hard-rock), extracting from the actual data to 36 contracts. The deviation between the unit costs estimated using the developed model and the actual cost data is presented in the range from -0.4% to +31%. This range is acceptable compared the typical range "-30% to + 50%". This model will improve the accuracy of existing method and be expected to contribute to effective total cost management and the economic aspects, reduce the financial expenditure.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.859-866
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• 2001

Successful project planning relies on a good estimation of the effort required to complete a project, together with the schedule options that may be available. Despite the extensive research done developing new and better models, existing software effort estimation models are present only the total effort and effort (or manpower： people per unit time) function for the software life-cycle. Also, Putnam presents constant effort rate in each subcycles. However, the size of total efforts are variable according to the software projects under the influence of its size, complexity and operational environment. As a result, the allocated effort in subcycle also differ from project to project. This paper suggests the linear and polynomial effort estimation models in specifying, building and testing phase followed by the project total effort. These models are derived from 128 different projects. This result can be considered as a practical guideline in management of project schedule and effort allocation.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.