• Journal of Korean Neurosurgical Society
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• 제29권2호
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• pp.240-248
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• 2000

Objective : Spontaneous intracranial hypotension is a rarely reported syndrome of spontaneous postural headache associated with low CSF pressure and has rarely been demonstrated radiographically or surgically. But recently, it is being recognized with increasing frequency. The purpose of this study was to characterize clinical and imaging features, etiologic factors, and outcome in the spontaneous intracranial hypotension. Patients and Methods : We reviewed our experience with documented cases of spontaneous intracranial hypotension in 5 consecutive patients with orthostatic headaches from April 1998 to April 1999. Results : The mean age was 41 years(from 35 to 49 years). All patients had postural headaches, which were completely alleviated by recumbency position. Nausea, neck pain, horizontal diplopia, photophobia, and blurred vision were noted in some of the patients. Brain MRI showed diffuse pachymeningeal gadolinium enhancement, subdural collections of fluid, and descent of the brain. The opening pressure from lumbar puncture was $4cmH_2O$ or less in three of five patients whereas the opening pressure was within normal range in two patients. All patients underwent radioisotope cisternography and computerized tomographic myelography. On radioisotope cisternography, CSF leakage was suspected at the level of cervical area(1 patient), upper thoracic area(2 patients), mid-thoracic area(1 patient). Computed tomography myelography revealed extraarachnoid accumulation of contrast media(compatible finding with CSF leakage) at the level of cervical or thoracic area. In all patients, the symptoms resolved in response to supportive measures or epidural blood patch(1 patient). Conclusion : Spontaneous spinal CSF leakage is increasingly recognized as a cause of spinal postural headache. Most CSF leaks are located at the cervicothoracic junction or in the thoracic spine and can be demonstrated by variable diagnostic method. The condition is usually self-limiting and its prognosis is typically good.

• 한국작물학회지
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• 제50권3호
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• pp.205-211
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• 2005

본 연구는 저온에 민감한 밀양 23호를 모본으로 내냉성이 강한 Stejaree45호를 부본으로 교잡하여 육성한 175 RILs를 이용하여 내냉성 관련 형질들의 변이분포, 유전 통계량 및 상관 관계를 분석하였다. 조사된 형질 중 수당영화수, 적고, 출수지연일수, 간장단축율 및 영화수감소율은 정규분포에 가까운 연속변이 분포곡선을 보였으며, 모든 형질에서 양친의 범위를 벗어나는 초월분리현상을 보였다. 임실감소율과 수량감소율은 모본인 밀양 23호 쪽으로 일정하게 치우친 경향으로 저온에 민감한 쪽으로, 출수지연일수와 간장단축율은 부본인 Stejaree45 쪽으로 치우친 경향으로 내냉성이 증가되는 쪽으로 작용가가 큰 유전자가 관여하는 것으로 추정되었다. 내냉성 관련 형질들의 상관관계 중 수량감소율과 상관이 인정되었던 형질은 출수지연일수, 간장단축율, 이삭추출도 및 임실감소율이었고, 조사된 형질중 유전력이 $60\%$이상으로 나타난 형질은 분얼기 적고, 임실감소율, 이삭추출도 였으며, 유전력이 $40\%$ 이하로 낮았던 형질은 간장단축율, 영화수감소율 및 수량감소율이었다. 175 RILs 중에서 내냉성 관련 형질의 내냉성 정도가 부본인 Stejaree45수준이거나 그 이상의 내냉성 형질을 가진 것은 86계통으로, 1개의 내냉성 형질은 56계통 $32.0\%$였고, 2개의 내냉성 형질은 25계통 $14.3\%$, 3개의 내냉성 형질은 4계통 $2.3\%$, 4개의 내냉성 형질은 1계통 밖에 없었으며, 그 이상의 내냉성 관련 형질을 가진 계통은 없었다.

• 한국터널지하공간학회 논문집
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• 제15권3호
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• pp.289-300
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• 2013

본 연구에서는 도로터널 화재해석에 적용하는 화재성장곡선을 적용하여 도로터널 화재시 열기류의 전파특성과 터널벽면에 미치는 열적특성을 수치 해석적으로 고찰하였다. 최대화재강도는 20, 100 MW로 하였으며, 터널내 풍속은 2.5 m/s로 유지하는 경우와 열부력에 의한 풍속으로 하는 경우에 대해서 터널연장 및 경사도에 따른 연기의 전파특성을 분석하고 열기류가 벽체에 미치는 영향을 평가하기 위해서 벽체표면온도와 벽체표면 열전달계수를 분석하였다. 터널내 열기류는 풍속을 2.5 m/s로 하는 경우에 벽체의 냉각효과에 의해서 일정거리 이후에는 급격하게 하강하여 하류까지 동일한 양상으로 흐르는 특성을 보이고 있으며, 벽체표면의 최대온도는 화재강도가 100 MW일 경우에 최대 $615^{\circ}C$까지 상승하고 있으며, 표면온도가 $380^{\circ}C$를 초과하는 면적은 아주 작은 것으로 나타나고 있다. 벽체의 표면열전달계수는 화재강도 및 터널내 풍속에 따라서 변하며 약 $13{\sim}23W/m^{\circ}C$의 범위에 있는 것으로 나타났다.

• 한국농공학회논문집
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• 제59권4호
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• pp.97-107
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• 2017

This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.

• 유통과학연구
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• 제12권2호
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• 지능정보연구
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• 제10권1호
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• pp.109-123
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• 2004

기업부도예측은 재무와 경영의사결정문제에서의 주된 인공신경망 응용분야라 할 수 있다. 일반적으로 인공신경망은 이 분야에서 매우 좋은 성과를 보이는 것으로 알려져 있지만 종종 잡음이 심한 데이터에 대해서는 일관성 있고 예측가능한 성과를 보이지 못하는 경우가 있다. 특히 학습용 자료가 매우 많아서 학습시간과 자료수집비용이 과대한 경우에는 적절한 자료의 축소가 되지 않고는 인공신경망을 학습시키는 것이 불가능한 경우도 있다. 사례선택기법은 자료의 차원을 축약시켜 주며 직접적으로 자료를 축소시켜 주는 방법이다. 사례기반 학습기법에서는 이미 몇 연구가 사례선택기법의 필요성을 주장한 바 있으나 인공신경망 모형에서 사례선택기법의 필요성을 주장한 연구는 거의 없다. 본 연구에서는 기업부도예측을 위한 인공신경망 모형에서 유전자 알고리즘을 이용한 사례선택기법을 제안한다. 본 연구에서 유전자 알고리즘은 다층 인공신경망에서의 계층별 연결강도를 최적화하고, 동시에 학습에 적합한 사례를 선택한다. 유전자 알고리즘에 의해 결정된 계층별 연결강도는 역전파오류 학습기법에서 종종 발생하는 국부 최적해에 수렴하는 현상을 최소화해 줄 것으로 기대되고, 선택된 학습용 사례는 학습시간의 단축과 예측성과를 향상시켜 줄 것으로 기대된다. 본 연구에서는 제안한 모형과 주요 데이터 마이닝 기법들의 성과를 비교 연구한다. 실험결과, 제안된 방법이 인공신경망에서의 사례선택기법으로 유용한 것으로 나타났다.

• 한국운동역학회지
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• 제18권4호
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• pp.67-76
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• 2008

본 연구는 인터스키 부정지 숏턴 동작에서 우수 집단과 비우수 집단 간 운동학적 변인의 차이를 3차원 영상 분석을 통해 보다 효과적인 부정지 숏턴 동작을 모색하고자 하였다. 연구 대상은 2007년 전국스키기술선수권대회 부정지 숏턴 경기에 참가한 선수 10명을 대상으로 DLT 방법을 이용한 3차원 영상분석을 통해 운동학적 변인을 분석하였으며, 그 결과 다음과 같은 결론을 얻었다. 총 소요시간 및 국면별 소요시간은 우수 집단이 비우수 집단보다 짧게 나타났다. 신체중심은 우수 집단이 비우수 집단보다 작은 좌우이동 폭과 큰 상하이동 폭을 나타내며, 직진성을 강화하는 활주를 하였으며, 그로 인하여 좌우속도를 제어하면서 빠른 전후속도를 나타냈다. 상하속도는 드롭 인 구간에서는 느리게 하면서 범프 업 구간에서 속도를 증가시킨 것으로 나타났다. 고관절각과 슬관절각은 우수 집단이 비우수집단보다 전체 이벤트에서 모두 작게 나타났으며, 동체 전경갈 신체 기울기각은 우수 집단이 비우수 집단보다 모두 크게 나타났다. 하퇴 전경각은 우수 집단이 비우수 집단보다 모글 중앙에서 크게 나타났으며, 동체 비틀기각은 우수 집단이 비우수 집단보다 드롭 인 구간에서 오른쪽 턴 방향으로, 범프 업 구간에서 왼쪽 턴 방향으로 크게 나타났다.

• 제어로봇시스템학회논문지
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• 제16권12호
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• 한국컴퓨터정보학회논문지
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• 제18권7호
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• pp.23-35
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• 2013

본 논문은 고장 분류 시스템을 위해 진동 신호로부터 특징 벡터를 자동적으로 추출하는 효과적인 기법을 제안한다. 기존의 멜-주파수 캡스트럼 계수는 진동신호의 노이즈에 민감하여 분류 정확도를 감소시키는 단점이 있다. 이러한 문제를 해결하기 위해 본 논문은 4단계 필터 뱅크로 구성된 스펙트럴 엔벨로프 캡스트럼 계수 분석을 제안하며, 4단계는 (1) 모든 진동 신호의 스펙트럴 엔벨로프를 기술하기 위한 선형 예측 코딩 알고리즘 사용 단계, (2) 일반적인 스펙트럴 모양을 얻기 위해 모든 엔벨로프의 평균화 단계, (3) 평균 엔벨로프와 그 주파수의 최대값을 찾기 위한 기울기 하강 방법 사용 단계, (4) 엔벨로프의 주파수 사이의 거리로부터 계산된 중앙값을 얻는데 사용되는 비 중첩 필터 뱅크 단계로 구성된다. 이4-단계필터뱅크는 특징벡터를 추출하기위해 캡스트럼 계수 계산에 사용된다. 마지막으로 유도전동기의 결함 형태를 구분하기 위해 이러한 특수 파라미터를 사용하는 다중 계층 서포트 벡터 머신을 사용한다. 모의실험 결과, 제안하는 방법은 약 99.65%의 분류 성능을 보이며, 동시에 기존 방법들보다 우수한 성능을 보인다.

• Journal of Acupuncture Research
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• 제18권1호
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• pp.40-49
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• 2001

Background and Purpose : There have been many studys about the relationship between the meridians and the acupoints of the twelve meridians, but no study about the extra points. To verify Dong-Shi acupoints, a kind of extra points, we studied the effects on the thermal changes of the ankle region following acupuncture on the Wu-Hu. Object and Methods : This study was researched into clinical statistics for 45 healthy normal students. The object was divided into two groups. One was the control group and the other was the acupuncture group. The acupuncture group was divided into two groups ; ACU-up : The class of ascent thermal change among acupuncture group. ACU-dn : The class of descent thermal change among acupuncture group. First, in the control group, we took a picture at the ankle region(BL60, BL62, GB40, ST41) without any stimulation with the Digital Infrared Thermal Imaging System and did after 10 minutes respectively. Second, in the acupuncture group, we took a picture without any stimulation and then acupuncture on Wu-Hu and took a picture after 10 minutes in the same way respectively. Results : 1. In the control group, average thermal change of BL60, BL62, GB40 and ST41 was decreased(about $0.2^{\circ}C$) after 10 minutes. 2. The skin temperature of all measured parts was significantly lower in the ACU-dn group after 10 minutes. 3. There were no significant differences of thermal change between the control and the acupuncture group, between the control and ACU-up group after 10 minutes. Conclusion : This result indicated that the acupuncture on the Wu-Hu was effective at the ankle region. And so the more study is needed continuously.