• 한국수자원학회논문집
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• 제40권12호
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• pp.957-968
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• 2007

수자원의 정량적인 계획과 관리를 위해서는 정확하고 신뢰성 높은 유량 자료가 필수적이다. 이에 따라 최근에 초음파유량계와 유속지수법 등의 실시간 유량 측정 방법이 도입되고 있다. 이러한 방법들은 단면의 일부분에서 측정한 유속을 이용하여 전체 단면의 유량을 산정하고 있으므로 하천 단면의 2차원적 유속분포에 대한 합리적이고 이론적인 기초가 필요하다. 본 연구에서는 Chiu(1987, 1988)가 제안한 2차원 유속분포식을 자연하천에 적용하고 ADCP 실측 자료를 이용하여 비교 분석함으로써 적용성을 분석하였다. 이를 위해 실측 자료로부터 최대유속과 평균유속을 계산한 후 매개변수 M을 산정하였다. 등유속선 형상 매개변수는 최소자승합 기준의 목적함수를 이용하여 추정하였다. 최적화된 매개변수를 적용하여 도출된 엔트로피 유속분포를 실측 유속분포와 비교한 결과, 대체로 잘 일치하는 것으로 나타났다. 상관도가 높게 나타나는 14개의 실측 자료를 이용하여 매개변수 h, $\beta_i$의 특성을 분석한 후 미측정 단면에 적용할 수 있도록 그 값을 추정하였다. 추정된 매개변수를 검증을 위한 자료에 적용한 결과 역시 실측 자료를 대체로 잘 재현하는 것으로 나타났다. 유량의 경우 최대 7% 의 오차로 실측 자료와 대체로 비슷하게 산정하였다. Chiu의 유속분포식에 관여하는 매개변수를 적절히 추정한다면 자연하천의 유속분포를 잘 모의할 수 있을 것으로 판단된다.

• 한국환경생태학회지
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• 제37권6호
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• pp.450-463
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• 2023

본 연구는 전문가 기반형 모델(Habitat Suitability Index)의 한계로 지적되는 주관적 기준, 통계분석의 부재 등과 통계기반형 모델(MaxEnt)의 한계로 지적되는 현장검증, 전문가 의견 반영 등의 극복을 위하여 각각의 모델을 개발하여 통합하는 방식으로 핵심서식지를 도출하였다. 핵심서식지 발굴을 위해 문헌분석 및 공간분석자료를 바탕으로 전문가 심층면담을 진행하였고, 전문가 자문과 GIS 도면 구축 가능성을 고려하여 모델을 개발하였다. 주요 환경변수는 식생대, 임상, 임분밀도, 연평균 강수량, 유효토심으로 선정되었다. 그 결과 현재 나도승마가 분포하고 있는 16지점 중 15지점이 핵심서식지로 나타났으며, 개발된 모델은 약 93.75%의 높은 정확도를 가지고 있는 것으로 나타났다. 하지만 전체 연구대상지의 약 27.8%가 핵심서식지로 나타남에 따라, 추후 서식변수 및 공간자료 정밀화를 통한 모델의 고도화가 필요할 것으로 판단된다. 따라서 높은 등급으로 확인된 서식지라도 대상종의 서식유무 파악을 위한 현장검증은 필수적으로 수행되어야 한다. 하지만, 이러한 한계에도 불구하고 HSI와 MaxEnt의 상호보완적 활용은 생물종의 분포와 서식지 이용 특성을 통하여 적합 서식지를 예측하고, 신규 서식지 발굴 및 대체서식지 선정 등 다양한 방면으로 활용 가능할 것으로 판단된다.

• 한국환경복원기술학회지
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• 제20권3호
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• pp.55-64
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• 2017

The problem of the population number of honeybees that is decreasing not only domestically but also globally, has a great influence on human beings and the entire ecosystem. The habitat of honeybees is recognized to be superior in urban environment rather than rural environment, and predicting for habitat assessment and conservation is necessary. Based on this, we targeted Cheonan City and neighboring administrative areas where the distribution of agricultural areas, urban areas, and forest areas is displayed equally. In order to predict the habitat preferred by honeybees, we apply the Maxent model what based on the presence information of the species. We also selected 10 environmental variables expected to influence honeybees habitat environment through literature survey. As a result of constructing the species distribution model using the Maxent model, 71.7% of the training data were shown on the AUC(Area Under Cover) basis, and it was be confirmed with an area of 20.73% in the whole target area, based on the 50% probability of presence of honeybees. It was confirmed that the contribution of the variable has influence on land covering, distance from the forest, altitude, aspect. Based on this, the possibility of honeybee's habitat characteristics were confirmed to be higher in wetland environment, in agricultural land, close to forest and lower elevation, southeast and west. The prediction of these habitat environments has significance as a lead research that presents the habitat of honeybees with high conservation value of ecosystems in terms of urban space, and it will be useful for future urban park planning and conservation area selection.

• 대한전자공학회논문지TE
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• 제39권3호
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• pp.97-104
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• 2002

이 논문에서는 퍼지뉴럴 시스템을 위하여 measure of fuzziness에 의한 입력공간의 분할을 최적화하는 방법을 제안한다. 이에 따라 최적화된 퍼지 부공간에 대하여 퍼지 제어규칙을 자동으로 생성하는 방법을 제안한다. 또한 시계열 예측 문제에서 입력패턴의 간격을 조정하여 그 성능을 검증한다. 이 방법은 샤논 함수와 index of fuzziness를 이용하여 입력공간을 분할하고, 분할된 부 공간에 대해 입력 데이터와 부합할 수 있는 각각의 규칙에 등급을 정하여 불필요한 제어규칙을 제거하여 최적의 규칙베이스를 구성하도록 한다. 적용되는 퍼지 신경망의 기본적인 구조는 퍼지 제어기의 규칙베이스와 추론의 과정을 신경회로망을 이용하여 구현하며 퍼지 제어규칙의 매개변수들은 최대 급경사 강하법에 의해 적응되어진다. 제안된 알고리즘을 토대로 여덟 가지의 입력패턴에 대하여 추론한 결과 입력공간의 최적분할에 의하여 수렴과정에서 초기에 오차(RMSE)가 빠르게 수렴함을 알 수 있었다.

• Journal of Ecology and Environment
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• 제38권1호
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• pp.95-107
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• 2015

Because an ecological community consists of diverse species that vary nonlinearly with environmental variability, its dynamics are complex and difficult to analyze. To investigate temporal variations of benthic macroinvertebrate community, we used the community data that were collected at the sampling site in Baenae Stream near Busan, Korea, which is a clean stream with minimum pollution, from July 2006 to July 2013. First, we used a self-organizing map (SOM) to heuristically derive the states that characterizes the biotic condition of the benthic macroinvertebrate communities in forms of time series data. Next, we applied the hidden Markov model (HMM) to fine-tune the states objectively and to obtain the transition probabilities between the states and the emission probabilities that show the connection of the states with observable events such as the number of species, the diversity measured by Shannon entropy, and the biological water quality index (BMWP). While the number of species apparently addressed the state of the community, the diversity reflected the state changes after the HMM training along with seasonal variations in cyclic manners. The BMWP showed clear characterization of events that correspond to the different states based on the emission probabilities. The environmental factors such as temperature and precipitation also indicated the seasonal and cyclic changes according to the HMM. Though the usage of the HMM alone can guarantee the convergence of the training or the precision of the derived states based on field data in this study, the derivation of the states by the SOM that followed the fine-tuning by the HMM well elucidated the states of the community and could serve as an alternative reference system to reveal the ecological structures in stream communities.

• 대한의용생체공학회:의공학회지
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• 제40권2호
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• 한국운동역학회지
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• 제27권2호
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• pp.133-140
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• 2017

Objective: The purpose of this study was to determine the relationship between center of pressure (CoP) and local stability of the lower joints, which was calculated based on approximate entropy (ApEn) during walking in elderly women. Method: Eighteen elderly women were recruited (age: $66.4{\pm}1.2yrs$; mass: $55.4{\pm}8.3kg$; height: $1.56{\pm}0.04m$) for this study. Before collecting data, reflective marker triads composed of 3 non-collinear spheres were attached to the lateral surface of the thigh and shank near the mid-segment to measure motion of the thigh and shank segments. To measure foot motion, reflective markers were placed on the shoe at the heel, head of the fifth metatarsal, and lateral malleolus, and were also placed on the right anterior-superior iliac spine, left anterior-superior iliac spine, and sacrum to observe pelvic motion. During treadmill walking, kinematic data were recorded using 6 infrared cameras (Oqus 300, Qualisys, Sweden) with a 100 Hz sampling frequency and kinetic data were collected from a treadmill (Instrumented Treadmill, Bertec, USA) for 20 strides. From kinematic data, 3D angles of the lower extremity's joint were calculated using Cardan technique and then ApEn were computed for their angles to evaluate local stability. Range of CoP was determined from the kinetic data. Pearson product-moment and Spearman rank correlation coefficient were applied to find relationship between CoP and ApEn. The level of significance was determined at p<.05. Results: There was a negative linear correlation between CoP and ApEn of hip joint adduction-abduction motion (p<.05), but ApEn of other joint motion did not affect the CoP. Conclusion: It was conjectured that ApEn, local stability index, for adduction/abduction of the hip joint during walking could be useful as a fall predictor.

• 한국전기전자재료학회논문지
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• 제23권1호
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• pp.76-85
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• 2010

In general, anesthetic depth is evaluated by experience of anesthesiologist based on the changes of blood pressure and pulse rate. So it is difficult to guarantee the accuracy in evaluation of anesthetic depth. The efforts to develop the objective index for evaluation of anesthetic depth were continued but there was few progression in this area. Heart rate variability provides much information of autonomic activity of cardiovascular system and almost all anesthetics depress the autonomic activity. Novel monitoring system which can simply and exactly analyze the autonomic activity of cardiovascular system will provide important information for evaluation of anesthetic depth. We investigated the anesthetic depth as following 7 stages. These are pre-anesthesia, induction, skin incision, before extubation, after extubation, Post-anesthesia. In this study, temporal, frequency and chaos analysis method were used to analyze the HRV time series from electrocardiogram signal. There were NN10-NN50, mean, SDNN and RMS parameter in the temporal method. In the frequency method, there are LF and HF and LF/HF ratio, 1/f noise, alphal and alpha2 of DFA analysis parameter. In the chaos analysis, there are CD, entropy and LPE. Chaos analysis method was valuable to estimate the anesthetic depth compared with temporal and frequency method. Because human body was involved the choastic character.

• Journal of Ecology and Environment
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• 제34권2호
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• pp.203-214
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• 2011

The objectives of this research were to predict land-use/land-cover change at the Sakaerat Environmental Research Station (SERS) and to analyze its consequences on the distribution for Black-crested Bulbul (Pycnonotus melanicterus), which is a popular species for bird-watching activity. The Dyna-CLUE model was used to determine land-use allocation between 2008 and 2020 under two scenarios. Trend scenario was a continuation of recent land-use change (2002-2008), while the integrated land-use management scenario aimed to protect 45% of study area under intact forest, rehabilitated forest and reforestation for renewable energy. The maximum entropy model (Maxent), Geographic Information System (GIS) and FRAGSTATS package were used to predict bird occurrence and assess landscape fragmentation indices, respectively. The results revealed that parts of secondary growth, agriculture areas and dry dipterocarp forest close to road networks would be converted to other land use classes, especially eucalyptus plantation. Distance to dry evergreen forest, distance to secondary growth and distance to road were important factors for Black-crested Bulbul distribution because this species prefers to inhabit ecotones between dense forest and open woodland. The predicted for occurrence of Black-crested Bulbul in 2008 covers an area of 3,802 ha and relatively reduces to 3,342 ha in 2020 for trend scenario and to 3,627 ha for integrated-land use management scenario. However, intact habitats would be severely fragmented, which can be noticed by total habitat area, largest patch index and total core area indices, especially under the trend scenario. These consequences are likely to diminish the recreation and education values of the SERS to the public.

• 한국융합학회논문지
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• 제9권5호
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• pp.171-177
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• 2018

본 연구의 목적은 비관련다각화가 이익조정에 어떠한 영향을 미치는지를 살펴보고, 이러한 관계가 감사위원회의 효율성에 따라 달라지는지를 검증하는 것이다. 분석을 위한 표본자료는 2000년에서 2009년까지 한국거래소에 상장되어있는 제조기업 중 264개 기업, 1924개의 기업-연(firm-year)자료를 이용하였다. 분석결과는 다음과 같다. 첫째, 엔트로피지수로 측정한 비관련다각화는 이익조정에 양(+)의 영향을 미치는 것으로 나타났다. 둘째, 비관련다각화가 이익조정에 미치는 양(+)의 영향에 대한 감사위원회의 상호조절효과를 검증한 결과, 비관련다각화수준이 높은 기업에서 감사위원회의 설치 및 독립성이 높은 경우 이익조정이 감소하는 음(-)의 관련성이 있는 것으로 나타났다. 이러한 연구결과는 비관련다각화지수가 보다 높은 기업의 경우, 경영자를 감시하는 감사위원회의 효율성을 강화하는 것이 중요함을 시사한다.