• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• 대한토목학회논문집
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• 제37권1호
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• pp.29-41
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• 2017

확률강수량 산정은 하천관리, 수공구조물 설계 및 위험도 분석에 있어 중요한 기초적인 자료 중 하나이다. 실무에서는 대표지속시간에 대해서 지점빈도해석을 통해 확률강수량을 추정하고 이를 지속시간에 대해서 회귀분석을 실시하여 IDF (intensity-duration-frequency) 곡선을 작성한다. 이들 IDF곡선을 활용하여 기타 지속시간에 대해서는 내삽 또는 외삽으로 보간 하여 확률강수량 추정이 이루어지고 있다. 우리나라의 경우 상대적으로 자료 연한이 짧은 점을 고려한다면, 보다 정확하고 신뢰성 있는 확률강수량 산정 기법의 필요성이 대두되고 있다. 이러한 이유로 본 연구에서는 Bayesian GLM 모형을 통하여 자료의 확률분포 매개변수의 Scaling 특성을 고려할 수 있는 지역빈도해석 모형을 개발하였다. 모형 적용결과 개별지점에서 효과적인 매개변수 추정뿐만 아니라, 유역전체의 특성을 대표하는 매개변수 추정이 가능하였다. 본 연구결과를 통해 도출된 IDF 곡선은 향후 다양한 수자원분야의 기초자료로 활용될 수 있을 것으로 기대되며, 미계측유역 또는 지속시간별 자료가 불충분한 지역에 대해서도 활용이 가능할 것으로 판단된다.

• 한국과학교육학회지
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• 제15권2호
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• pp.201-212
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• 1995

The purpose of this study was to analyze science teaching models: Cognitive Conflict Teaching Model(CCTM), Generative Learning Model(GLM), Learning Cycle Model(LCM), Hypothesis-Testing Model(HTM), and Discovery Teaching Model(DTM). Using literature review, the models were analyzed and compared in several aspects; philosophical and psychological bases, primary goals and assumptions, syntax, implementation environments, and probable effects. The major finding were as follows; 1. Science teaching models had been diverse features. In the comparisons of science teaching models, some differences and similarities were founded. These were different in the degree of similarity and emphasis. 2. CCTM and GLM resemble each other in philosophical and psychological bases, primary goals and main assumptions, implementation environments, and probable effects. 3. LCM and HTM showed similarities in philosophical bases, syntax, and implementation environments. But differences were founded in other aspects These results showed that the diverse features of science teaching models should be considered in choosing a model for science teaching.

• 한국환경과학회지
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• 제22권3호
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• pp.303-308
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• 2013

This paper proposed a new method for estimating missing values in time series rainfall data. The proposed method integrated the two most widely used estimation methods, general linear model(GLM) and ordinary kriging(OK), by taking a weighted average of covariance matrices derived from each of the two methods. The proposed method was cross-validated using daily rainfall data at thirteen rain gauges in the Hyeong-san River basin. The goodness-of-fit of the proposed method was higher than those of GLM and OK, which can be attributed to the weighting algorithm that was designed to minimize errors caused by violations of assumptions of the two existing methods. This result suggests that the proposed method is more accurate in missing values in time series rainfall data, especially in a region where the assumptions of existing methods are not met, i.e., rainfall varies by season and topography is heterogeneous.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• 한국보육지원학회지
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• 제12권3호
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• pp.197-210
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• 2016

The purpose of this study was to examine the effects of young children's stay hours on kindergartens or child care centers on their language, cognition, and social development with teacher-child interactions as a mediator. For this purpose, the data from the 2013 Panel Study on Korean Children were analyzed using the GLM and pattern analysis. The results of the GLM analysis were as follows. First, the main effects of the stay hours on child development were statistically significant Second, the main effects of the level of teacher-child interaction were also statistically significant on the results of child development. Third, the moderating effect of teacher-child interaction level between the stay hours and child development were also significant. The results showed that young children's stay hours effected their language, cognitive, and social development and teacher-child interactions mediated these effects.

• International Journal of Aeronautical and Space Sciences
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• 제1권2호
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• pp.68-74
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• 2000

A comparative wind tunnel testing of an airplane model was performed at the Korea Aerospace Research Institute Low Speed Wind tunnel(KARI LSWT). The model used for the comparative test was a seaplane model from the Glenn L. Martin Wind(GLM) Tunnel of University of Maryland, U.S.A. The 6-component external balance used in force and moment measurement is pyramidal type, which is a precision device that has strain gauge-type load cell inside of balance and the virtual center of the balance coincides with the tunnel centerline. Image method is adopted to eliminate the tare and interference of the model support, and to correct the flow angularity to the model also. Test results from KARI LSWT were compared with the results from GLM tunnel.

• Computers and Concrete
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• 제32권6호
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• pp.607-613
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• 2023

The objective of this work is to determine the compressive strength of geopolymer concrete utilizing four distinct machine learning approaches. These techniques are known as gradient boosting machine (GBM), generalized linear model (GLM), extremely randomized trees (XRT), and deep learning (DL). Experimentation is performed to collect the data that is then utilized for training the models. Compressive strength is the response variable, whereas curing days, curing temperature, silica fume, and nanosilica concentration are the different input parameters that are taken into consideration. Several kinds of errors, including root mean square error (RMSE), coefficient of correlation (CC), variance account for (VAF), RMSE to observation's standard deviation ratio (RSR), and Nash-Sutcliffe effectiveness (NSE), were computed to determine the effectiveness of each algorithm. It was observed that, among all the models that were investigated, the GBM is the surrogate model that can predict the compressive strength of the geopolymer concrete with the highest degree of precision.

• 수산해양기술연구
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• 제54권2호
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• pp.116-123
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• 2018

Pacific bluefin tuna (Thunnus orientalis) has been mostly caught by the Korean offshore large purse seine fishery in Korean waters. The annual catch of Pacific bluefin tuna caught by the offshore large purse seine fishery in Korean waters showed less than 1,000 mt until the 1990s except for 1997. The catch sharply increased to 2,401 mt in 2000 and recorded the highest of 2,601 mt in 2003, but the catch has generally decreased with a fluctuation thereafter. The main fishing ground of Pacific bluefin tuna of this fishery is formed around Jeju Island. However, it expanded to the Yellow Sea, the coastal of Busan, and the East Sea, which depends on the migration patterns of Pacific bluefin tuna by season. The CPUE standardization of Pacific bluefin tuna was conducted using Generalized Linear Model (GLM) to assess the proxy of the abundance index. The data used for the GLM were catch (weight), effort (number of hauls), catch ratio of Pacific bluefin tuna, moon phase by year, quarter and area. The standardized CPUE from 2004 to 2011, except for 2003 and 2010, showed a steady trend, and then increased until 2014. The CPUE in 2015 decreased, and in 2016 was higher than that in 2015. The result of GLM suggests that the effect of the catch ratio of Pacific bluefin tuna is the largest factor affecting the nominal CPUE.

• 한국식품과학회지
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• 제43권3호
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• pp.249-254
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• 2011

생강은 다양한 생리활성이 보고되고 있으나 자극적인 향미로 인하여 건강식품 소재로의 사용에는 제약을 받아왔다. 본 연구에서는 낙농제품 및 김치 유래 유산균으로 발효생강을 제조하고 요쿠르트에 첨가하여 관능적 특성에 미치는 영향을 조사하였다. 건 생강의 첨가는 플레인 요쿠르트의 맛과 전체적 선호도를 저하시켰으며, GSt, GLa, GLm(발효 생강)의 첨가도 저하시키는 경향을 나타낸 반면에 GLp 첨가구는 저하되지 않았다. 또한 모든 발효생강은 제조공정 중 생강의 특징적 향기성분이 감소하여 이들을 첨가한 요쿠루트의 향미에는 유의적인 영향을 주지 않았으므로 GLp 첨가는 건생강을 대신한 건강식품 소재로서 사용될 수 있을 것으로 기대된다. 한편 생강의 생리활성 성분의 하나인 6-gingerol은 모든 발효생강에서는 발효 전에 비하여 감소하고 6-shogaol은 증가하였으나, GLp 발효생강에서는 6-shogaol 이 거의 검출되지 않은 점이 특이하였다.