• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• 제22권1호
• /
• pp.29-62
• /
• 2018

We investigate a class of HIV infection models with two kinds of target cells: $CD4^+$ T cells and macrophages. We incorporate three distributed time delays into the models. Moreover, we consider the effect of humoral immunity on the dynamical behavior of the HIV. The viruses are produced from four types of infected cells: short-lived infected $CD4^+$T cells, long-lived chronically infected $CD4^+$T cells, short-lived infected macrophages and long-lived chronically infected macrophages. The drug efficacy is assumed to be different for the two types of target cells. The HIV-target incidence rate is given by bilinear and saturation functional response while, for the third model, both HIV-target incidence rate and neutralization rate of viruses are given by nonlinear general functions. We show that the solutions of the proposed models are nonnegative and ultimately bounded. We derive two threshold parameters which fully determine the positivity and stability of the three steady states of the models. Using Lyapunov functionals, we established the global stability of the steady states of the models. The theoretical results are confirmed by numerical simulations.

• Journal of the Korean Data and Information Science Society
• /
• 제14권4호
• /
• pp.845-852
• /
• 2003

Forecasting exchange rate movements is a challenging task since exchange rates impact world economy and determine value of international investments. In particular, Korean-U.S. exchange rate behavior is very important because of strong Korean and U.S. trading relationship. Neural networks models have been used for short-term prediction of exchange rate movements. Least squares support vector machine (LS-SVM) is used widely in real-world regression tasks. This paper describes the use of LS-SVM for short-term and long-term prediction of Korean-U.S. exchange rate.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2007년도 춘계학술대회A
• /
• pp.1749-1753
• /
• 2007

The reliability, that is Long-Term Quality, require an approaching different from Short-Term Quality which is used before. As the electronic components are able to be easily normalized on the reliability testing, various testing standards are used. In this study, we proposed two reliability simulator that is PoF(Physics of Failure)-based and failure rate models-based. PoF-based simulator is introduced based on CalceEP program that is created by University of Maryland. This simulator can be modified by user interface of properties and PoF models and operated on stand alone system. Failure rate models-based simulator introduced according to analyzing reliability prediction documents. Also, unified database including failure data models is built from existing MIL-HDBK-217F N2, PRISM, and Bellcore, and web-based simulator is developed. The developed reliability simulator will service of the PoF model, properties, failure rate model accumulated and its data by web and internet.

• 한국농공학회지
• /
• 제36권2호
• /
• pp.44-55
• /
• 1994

This paper describes the development of real-time irrigation reservoir operation models that adequately allocate available water resources for paddy rice irrigation. Water requirement deficiency index(WRDI) was proposed as a guide to evaluate the operational performance of release schemes by comparing accumulated differences between daily release requirements for irrigated areas and actual release amounts. Seven reservoir release rules were developed, which are constant release rate method (CRR), mean storage curve method(MSC), frequency analysis method of reservoir storage rate(FAS), storage requirement curve method(SRC), constant optimal storage rate method (COS), ten-day optimal storage rate method(TOS), and release optimization method(ROM). Long-term forecasting reservoir operation model(LFROM) was formulated to find an optimal release scheme which minimizes WRDIs with long-term weather generation. Rainfall sequences, rainfall amount, and evaporation amount throughout the growing season were to be forecasted and the results used as an input for the model. And short-term forecasting reservoir operation model(SFROM) was developed to find an optimal release scheme which minimizes WRDIs with short-term weather forecasts. The model uses rainfall sequences forecasted by the weather service, and uses rainfall and evaporation amounts generated according to rainfall sequences.

• 한국수자원학회논문집
• /
• 제55권8호
• /
• pp.565-575
• /
• 2022

최근의 수자원공학 분야는 4차산업혁명과 더불어 비약적으로 발전된 딥러닝 기술을 활용한 시계열 수위 및 유량의 예측에 대한 관심이 높아지고 있다. 또한 시계열 자료의 예측이 가능한 LSTM 모형과 GRU 모형을 활용하여 수위 및 유량 예측을 수행하고 있지만 시간 변동성이 매우 큰 하천에서의 유량 예측 정확도는 수위 예측 정확도에 비해 낮게 예측되는 경향이 있다. 본 연구에서는 유량변동이 크고 하구에서의 조석의 영향이 거의 없는 한강의 팔당대교 관측소를 선택하였다. 또한, LSTM 모형과 GRU 모형의 입력 및 예측 자료로 활용될 유량변동이 큰 시계열 자료를 선택하였고 총 자료의 길이는 비교적 짧은 2년 7개월의 수위 자료 및 유량 자료를 수집하였다. 시간변동성이 큰 시계열 수위를 2개의 모형에서 학습할 경우, 2개의 모형 모두에서 예측되는 수위 결과는 관측 수위와 비교하여 적정한 정확도가 확보되었으나 변동성이 큰 유량 자료를 2개의 모형에서 직접 학습시킬 경우, 예측되는 유량 자료의 정확도는 악화되었다. 따라서, 본 연구에서는 급변하는 유량을 정확히 예측하기 위하여 2개 모형으로 예측된 수위 자료를 수위-유량관계곡선의 입력자료로 활용하여 유량의 예측 정확도를 크게 향상시킬 수 있었다. 마지막으로 본 연구성과는 수문자료의 별도 가공없이 관측 길이가 상대적으로 충분히 길지 않고 유출량이 급변하는 도시하천에서의 홍수예경보 자료로 충분히 활용할 수 있을 것으로 기대된다.

• 재무관리연구
• /
• 제25권4호
• /
• pp.79-116
• /
• 2008

본 논문은 1980년 1월부터 2004년 9월까지 한국 거래소 시장수익률을 이용하여 RiskMetrics, GARCH, IGARCH, GJR, APARCH 등의 모형에 정규분포, 스튜던트 t분포, 왜도 스튜던트 t분포 등을 이용하여 어느 분포를 가진 모형이 보다 더 정확한 VaR을 추정할 수 있는지를 실증검증 하였다. 실증결과 표본 내 검증 시 모든 신뢰수준($90%{\sim}99.9%$)에서 롱 포지션 전략에서는 ${\lambda}=0.87$를 가진 IGARCH 모형 및 왜도 스튜던트 t분포가 가장 우월하며, 숏 포지션 전략에서는 GARCH 및 GJR 모형이 그리고 왜도 스튜던트 t분포가 가장 우월하였고, 99% 이상의 신뢰수준에서는 또한 ${\lambda}=0.87$를 가진 IGARCH 모형이 롱 및 숏 포지션 양 전략에서 우월하였다. 또한 분포의 경우 롱 포지션에서 왜도 스튜던트 t분포, 숏 포지션에서 스튜던트 t분포가 가장 우월하였다. 표본 외 검증에서도 동일한 결과를 제시하고 있다.

• 전자공학회논문지B
• /
• 제32B권12호
• /
• pp.1663-1669
• /
• 1995

This paper is a study on the recognition of Korean proverb using neural network and Markov model. The neural network uses, at the stage of training neurons, features such as the rate of zero crossing, short-term energy and PLP-Cepstrum, covering a time of 300ms long. Markov models were generated by the recognized phoneme strings. The recognition of words and proverbs using Markov models have been carried out. Experimental results show that phoneme and word recognition rates are 81. 2%, 94.0% respectively for Korean proverb recognition experiments.

• Journal of Biosystems Engineering
• /
• 제19권2호
• /
• pp.112-123
• /
• 1994

At present, no appropriate drying conditions can be found for the heated-air drying of mushroom in Korea. Usually, mushroom is being dried at the temperature range of 40 to $50^{\circ}C$ until the moisture content reaches 10~13% (wb). However, drying characteristics of the mushroom should be investigated for quality improvement and efficient drying operation of the mushroom. The results of this study may be summarized as follows ; 1. The effect of air temperature on the rate of drying was greater than that of relative humidity for drying of mushroom, and the rate of drying was increased with increase in the air temperature. 2. Drying rate for Shiitake mushroom showed falling-rate period of drying without constant-rate period of drying. Drying rate for Oyster mushroom showed a short constant-rate period at the initial stage of drying process, and followed by falling-rate period of drying. 3. Exponential and App.-Diffusion models were found to describe well the drying process of Shiitake mushroom. Exponential and Thompson models for Oyster mushroom in which Thompson model was the most suitable for Oyster mushroom. 4. The equilibrium moisture content of the mushroom decreased with decrease in the air temperature and increase in the relative humidity. In room condition($20^{\circ}C$, 54% RH), the calculated values of the equilibrium moisture content showed 11.17% for Shiitake mushroom and 13.19% for Oyster mushroom, respectively.

• Computers and Concrete
• /
• 제8권4호
• /
• pp.371-388
• /
• 2011

In this paper, time-continuous constitutive equations for strain rate-dependent materials are presented first, among which those for the overstress and the consistency viscoplastic models are considered. By allowing the stress states to be outside the yield surface, the overstress viscoplastic model directly defines the flow rule for viscoplastic strain rate. In comparison, a rate-dependent yield surface is defined in the consistency viscoplastic model, so that the standard Kuhn-Tucker loading/unloading condition still remains true for rate-dependent plasticity. Based on the formulation of the consistency viscoplasticity, a computational elasto-viscoplastic constitutive model is proposed for the short fiber-reinforced fresh cementitious paste for extrusion purpose. The proposed constitutive model adopts the von-Mises yield criterion, the associated flow rule and nonlinear strain rate-hardening law. It is found that the predicted flow stresses of the extrudable fresh cementitious paste agree well with experimental results. The rate-form constitutive equations are then integrated into an incremental formulation, which is implemented into a numerical framework based on ANSYS/LS-DYNA finite element code. Then, a series of upsetting and ram extrusion processes are simulated. It is found that the predicted forming load-time data are in good agreement with experimental results, suggesting that the proposed constitutive model could describe the elasto-viscoplastic behavior of the short fiber-reinforced extrudable fresh cementitious paste.

• 대한안전경영과학회지
• /
• 제13권1호
• /
• pp.195-202
• /
• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.