• 대한전기학회논문지:전력기술부문A
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• 제49권1호
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• pp.37-42
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• 2000

The radio noise produced by corona discharge in high voltage transmission lines is one of the most important line design considerations. Therefore it is necessary for transmission line designers to pre-evaluate radio noise using prediction formulas or field test results. In this paper, more accurate and useful formulas for predicting radio noise during fair and foul weathers in high voltage AC transmission lines were proposed through comparison with the existing formulas. Also it was verified by comparing with the long-term measured data from operating lines that the proposed formulas are more accurate. The proposed prediction formulas are developed by the applications of nonlinear least squares optimization method to radio noise database collected from lines throughout the world.

• Archives of Pharmacal Research
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• 제13권3호
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• pp.221-226
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• 1990

A physiological pharmacokinetic hybrid model was developed in order to predict the disposition kinetics of diphenylhydantoin (DPH) in the brain from the plasma conentration data of DPH. The model was constructed under the assumptions of well-stirred, plasma flow-limited and lienar tissue diposition kinetics of DPH. DPH was administered intravenously to the rats at a dose of 10 mg/kg together with/without sodium salicylate (SA;10 mg/kg) and the DPH concentrations in the plasma and brain were determined. Plasma protein binding of DPH concentrations in the plasma and brain were determined. Plasma protein binding of DPH was also determined using equilibrium dialysis technique. Then the model was tested for its predictability of DPH concentrations in the brian from the plasma data of DPH. It was found that the predicted values of DPH concentrations in the brian were in fair agreement with the experimental values in the rats of both treatments. The 2-fold increase in the brain concentration of DPH by SA-coadinistration was predicted well from the plasma concentration and plasma free fraction ($f_p$) data of DPH using the model. Therefore, the hybrid model was concluded to be very useful for the prediction of the concentrations of DPH in the brain from the plasma concentration data. Finally, DPH concentrations in the human brian was calculated using this model from plasma DPH data in the literature, yet the scale-up of this model to the human is not convinced.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(1)
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• pp.17-20
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• 2000

TCP is ill-suited to real-time multimedia applications. Its bursty transmission, and abrupt and frequent wide rate fluctuations cause high delay jitters and sudden quality degradation of multimedia applications. Deploying non congestion controlled traffic results in extreme unfairness towards competing TCP traffic. Therefore, they need to be enhanced with congestion control schemes that not only am at reducing loss ratios and improve bandwidth utilization but also are fair towards competing TCP connections. This paper proposes a differentiated rate adaptation algorithm based on loss and round trip time. Rate in a sender quickly responds to loss ratio and holds steady state. Additionally, this algorithm reduces loss ratio by loss prediction in a receiver.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2006년도 춘계학술발표대회
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• pp.1057-1060
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• 2006

본 논문에서는 OFDMA-TDD 환경에서 서비스 사용자들에게 QoS 를 보장해줄 수 있도록 예측 알고리즘을 이용하여 한정된 무선 자원을 효율적이고 공정하게 스케줄링 해주는 알고리즘을 연구하였다. 예측 알고리즘은 각 사용자의 이동 정보와 단말들의 변화해온 채널상태의 history data 를 이용하여 앞으로의 채널상태를 예측하고, 예측된 결과는 사용자의 이동 정보와 함께 무선 자원 스케줄링에 적용한다. 또한 이동단말과 고정단말이 공존하는 환경에서는 QoS 보장에 있어 공정하지 않음을 밝히고, 이와 같은 문제를 해결하는 방안을 제안하였으며, 실험결과를 PF 알고리즘과 비교하였다.

• 한국통신학회논문지
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• 제7권3호
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• pp.112-119
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• 1982

CCITT V.26에 의거한 4-위상 DPSK 2400bps 모뎀이 설계 구성되었다. 회로 전체가 집적회로소자를 이용해 구성되었으며 능동 여파기와 반도체 지연장치가 사용되었다. 동기신호의 재생에 있어서 새롭고 간단한 방법을 시도하여 그 타당성을 확인하였다. Gaussian 잡음에 대한 에러율은(error rate) 이론치와의 차이가 매우 근소함이 확인되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.909-910
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• 2007

The volatile organic compounds exposure is governed by the source distance and dispersion of the pollutant into air and groundwater. The purpose of this study was to validate suggested models for the prediction of concentration distributions. The study design was organized into different methods to simulate industry site. The distribution models generally showed a fair agreement with measured data. For graphical representation of concentration of volatile hydrocarbon, it has to obtain a continuous representation of the contamination of the site. Therefore, the used interpolative methods examined for this project are the IDW(inverse Distance Weighting) and kriging method. In the results, in summary, all two different methods can be used to quantify exposures at a particular source area, and thus provide, a solid foundation for making risk-based decisions. All the calculations can be performed using Excel's built-in functions, and the capabilities of geospatial analysis allow the results to be displayed visually. However, anyone who uses these methods should understand all of the assumptions and limitation.

• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.109-117
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• 2002

High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.

• Geomechanics and Engineering
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• 제13권5호
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• pp.743-756
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• 2017

Laboratory investigation reveals that rockfills exhibit significant stress-path-dependent behavior during shearing, therefore realistic prediction of deformation of rockfill structures requires suitable constitutive models to properly reproduce such behavior. This paper evaluates the capability of a strain hardening model proposed by the authors, by comparing simulation results with large-scale triaxial stress-path test results. Despite of its simplicity, the model can simulate essential aspects of the shear behavior of rockfills, including the non-linear stress-strain relationship, the stress-dependence of the stiffness, the non-linear strength behavior, and the shearing contraction and dilatancy. More importantly, the model is shown to predict the markedly different stress-strain and volumetric behavior along various loading paths with fair accuracy. All parameters required for the model can be derived entirely from the results of conventional large triaxial tests with constant confining pressures.

• Asian Pacific Journal of Cancer Prevention
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• 제15권16호
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• pp.6811-6817
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• 2014

Background: Breast cancer risk prediction models are widely used in clinical practice. They should be useful in identifying high risk women for screening in limited-resource countries. However, previous models showed poor performance in derived and validated settings. Therefore, we aimed to develop and validate a breast cancer risk prediction model for Thai women. Materials and Methods: This cross-sectional study consisted of derived and validation phases. Data collected at Ramathibodi and other two hospitals were used for deriving and externally validating models, respectively. Multiple logistic regression was applied to construct the model. Calibration and discrimination performances were assessed using the observed/expected ratio and concordance statistic (C-statistic), respectively. A bootstrap with 200 repetitions was applied for internal validation. Results: Age, menopausal status, body mass index, and use of oral contraceptives were significantly associated with breast cancer and were included in the model. Observed/expected ratio and C-statistic were 1.00 (95% CI: 0.82, 1.21) and 0.651 (95% CI: 0.595, 0.707), respectively. Internal validation showed good performance with a bias of 0.010 (95% CI: 0.002, 0.018) and C-statistic of 0.646(95% CI: 0.642, 0.650). The observed/expected ratio and C-statistic from external validation were 0.97 (95% CI: 0.68, 1.35) and 0.609 (95% CI: 0.511, 0.706), respectively. Risk scores were created and was stratified as low (0-0.86), low-intermediate (0.87-1.14), intermediate-high (1.15-1.52), and high-risk (1.53-3.40) groups. Conclusions: A Thai breast cancer risk prediction model was created with good calibration and fair discrimination performance. Risk stratification should aid to prioritize high risk women to receive an organized breast cancer screening program in Thailand and other limited-resource countries.

• 대한교통학회지
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• 제24권7호
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• pp.81-90
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• 2006

교통사고를 줄이기 위한 방안으로써 교통사고와 다양한 요인과의 관계를 규명하는 것이 시급한 현실의 과제일 것이다. 본 연구에서는 전북권의 교통사고가 가장 많고, 치사율이 가장 높은 국도 17호선(전주-남원)를 대상으로 교통사고의 원인이 되는 다양한 요인들이 교통사고에 어느 정도 영향을 미치고 있는지에 대하여 교통안전분야에서 자주 사용되어오던 다중회귀이론, 수량화이론을 적용하여 교통사고예측모델을 구축하였다. 또한 데이터의 불확실성 상태를 합리적으로 처리할 수 있는 퍼지 추론이론 및 인간의 신경계를 수학적으로 모형화하여 학습에 의한 예측에 있어 뛰어난 것으로 알려져 있는 신경망이론을 적용한 교통사고예측모델을 구축하였다 이를 통해, 퍼지추론이론 및 신경망 이론의 유효성을 입증하고 교통사고분석 분야의 적용 타당성을 확인하는데 초점을 맞추고 있다.