• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.405-408
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• 2002

LSP(Line Spectrum Pairs) Parameter is used for speech analysis in vocoders or recognizers since it has advantages of constant spectrum sensitivity. low spectrum distortion and easy linear interpolation. However the method of transforming LPC(Linear Predictive Coding) into LSP is so complex that it takes much time to compute. Among conventional methods, the real root method is considerably simpler than others, but nevertheless, it still suffers from its jndeterministic computation time because the root searching is processed sequentially in frequency region. We suggest a method of reducing the LSP transformation time using voice characteristics The proposed method is to apply search order and interval differently according to the distribution of LSP parameters. in comparison with the conventional real root method, the proposed method results in about 46.5% reduction. And, the total computation time is reduce to about 5% in the G.723.1 vocoder.

• 한국안전학회지
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• 제14권1호
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• pp.141-149
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• 1999

At present time, industrial accidents statistics are used as the basic data of the policy to prevent industrial accidents and the plan to applicate the industrial accident insurance. But this statistical data is not sufficient for the effective safety management because it is the expression of the itemized distribution and the frequency for the whole cases. This study tried to correlational analysis for each causes by defining investigational items as their accident parameters. The correlational analysis, between the unsafe action and status and their relational causes, was performed to analyze the occurrence causes of industrial accident. And to assume the severity of accident, the correlativity and independency between causes and direct causes which are defined hospital days subordinate parameter were analyzed. In addition, this study expressed numerically the effectiveness of subordinate parameters depended on the level of independent parameter by presenting the predictive model between dependent parameter and independent parameter, which have the categorical parameter, through the Logit analysis method.

• 음성과학
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• 제11권4호
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• pp.17-28
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• 2004

In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pairs (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods based on linear mapping functions according to different assumption of distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. We apply the proposed techniques to a predictive vector quantizer used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064dB.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 1994년도 교수 연수회(역학)
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• pp.158-163
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• 1994

Slightly elevated urinary albumin excretion rate (microalhuminuria) is a marker of early diabectic nephropathy, but it is unclear if the established definition of microalbuminuria ($20-200{\mu}g/min$) is correct for children and adolescents. We investigated th.: albumin excretion rate, albumin/creatinine ratio and urinary albumin concentration in 150 healthy schoolchildren and adolescents to (a) obtain a reterence value for albumin excretion rate, (b) relate albumin excretion to pubertal stages and (c) evaluate albumin/creatinine ratio and morning albumin concentration as screening methods for elevated albumin excretion rate. Albumin concentration was measured by immunoturbidimetry in timed overnight urine samples. The albumin excretion showed a skewed distribution (geometric mean $3.2{\mu}g/min$, 95 percentile ($15.1{\mu}g/min$). In girls. a peak in the albumin excretion rate was found at the pubertal stage 4 (Tanner) and in boys at stage 5. Albumin/creatinine ratio of 2.5 mg/mmol as a screening level for elevated albumin excretion ($15{\mu}g/min$) showed a high positive (0.88) and negative (0.99) predictive value.

• 전기학회논문지
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• 제57권8호
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• pp.1305-1310
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• 2008

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• East Asian Economic Review
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• 제24권2호
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• pp.165-184
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• 2020

Applying Ismailov and Rossi (2018), I newly construct the Korea FX uncertainty based on the density distribution of historical forecast errors. This uncertainty index properly captures the rare but significant events in the Korean currency market and provides information distinct from other uncertainty measures in recent studies. I show that 1) FX uncertainty arising from unexpected depreciation has a stronger impact on Korea-U.S. exchange rates and that 2) macro variables, such as capital flows or interest rate differentials, have predictive ability regarding Korea FX uncertainty for short horizons. These findings enable us to predict the events of sudden currency crashes and understand the Korea-U.S. exchange rate dynamics.

• 품질경영학회지
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• 제26권1호
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• pp.201-212
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• 1998

A methodology of the safety analysis on the fusion power plant is introduced. It starts with the understanding of the physics and engineering of the plant followed by the assessment of the tritium inventory and flow rate. We a, pp.y the probabilistic risk assessment. An event tree that explains the propagation of the accident is constructed and then it is translated in to an influence diagram, that is accident is constructed and then it is translated in to an influence diagram, that is statistically equivalent so far as the parameter updating is concerned. We follow the Bayesian a, pp.oach where model parameters are treated as random variables. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of time to next severe accident.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 추계학술대회 논문집
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• pp.71-72
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• 2015

본 논문에서는 LCL필터가 적용된 대용량 3-Level NPC AC/DC PWM 컨버터의 출력 DC 전압 동특성을 향상시킬 수 있는 방법으로 예측제어기법을 적용하였다. 예측제어를 위하여 LCL필터와 3-Level NPC 컨버터를 모델링하고, 시뮬레이션을 통하여 제안하는 방법의 제어성능을 검토하였다.

• Bulletin of the Korean Chemical Society
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• 제17권3호
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• pp.245-253
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• 1996

A topological theory has been introduced to explain and evaluate the fractional volumes of system materials, the change of the weight and concentration of monomer molecules, molecular weight distribution, and interaction functions of polymer-polymer and polymer-oligomer, etc. for dispersion polymerization. The previous theory of Lu et al. has offered only an incomplete simulation model for dispersion polymer systems, whereas our present one gives a general theoretical model applicable to all the polymerization systems. The theory of Lu et al. considered only the physical property term caused by interaction between matters of low molecular weight (i.e., diluent, monomer, and oligomer) and polymer particles without dealing with physical properties caused by the structure of polymer networks in polymer particles, while our theory deals with all physical effect possible, caused by the displacement of not only entangled points but also junction points in polymer particles. The theoretically predictive values show good agreement with the experimental data for dispersion polymerization systems.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.83-92
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• 2022

Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.