• 설비공학논문집
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• 제12권6호
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• pp.589-598
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• 2000

The vapor-liquid equilibrium and miscibility measurement apparatus was developed and used to obtain data for refrigerant/oil mixture. The vapor-liquid equilibrium and miscibility data for R-410a/POE32 and R-410A/POE46 oil mixtures are obtained over the temperature range from -20 to $60^{\circ}C\;with\;10^{\circ}C$ intervals and the oil concentration range from 0 to 90 wt%. Using the experimental data, an empirical model is developed to predict the temperature-pressure-concentration relations for R-410A/POE oil mixtures at equilibrium. In the R-410A/POE32 oil mixture, the average root-mean-square deviation between measured data and calculated results from the empirical model is 2.00% and in the R-410a/POE46 oil mixture, that is 3.69%. Flory-Huggins theory is also used to predict refrigerant/oil mixture behavior. Miscibility for R-410A/POE32 oil mixture was observed all over the experimental conditions. Immiscibility for R-410A/POE46 oil mixture was observed at the low oil concentrations(10~30 wt%).

• 디지털산업정보학회논문지
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• 제19권4호
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• pp.97-115
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• 2023

In South Korea, chronic kidney disease(CKD) impacts around 4.6 million adults, leading to a high reliance on hemodialysis. For effective dialysis, vascular access is crucial, with decisions about vascular surgeries often made during dialysis sessions. Anticipating these needs could improve dialysis quality and patient comfort. This study investigates the use of Artificial Intelligence(AI) to predict the timing of surgeries for dialysis vessels, an area not extensively researched. We've developed an AI algorithm using predictive maintenance methods, transitioning from machine learning to a more advanced deep learning approach with Long Short-Term Memory(LSTM) models. The algorithm processes variables such as venous pressure, blood flow, and patient age, demonstrating high effectiveness with metrics exceeding 0.91. By shortening the data collection intervals, a more refined model can be obtained. Implementing this AI in clinical practice could notably enhance patient experience and the quality of medical services in dialysis, marking a significant advancement in the treatment of CKD.

• 농업과학연구
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• 제43권5호
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• pp.715-722
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• 2016

Rapid determination of food quality is important in food distribution. In this study, the chemical properties of oats were analyzed using visible-near infrared (VIS-NIR) spectroscopy. The objective of this study was to develop and validate a predictive model of oat quality by VIS-NIR spectroscopy. A total of 200 oat samples were collected from domestic and import markets. Reflectance spectra, moisture, protein, fat, Fe, and K of oat samples were measured. Reflectance spectra were measured in the wavelength range of 400 - 2,500 nm at 2 nm intervals. The reflectance spectrum of an oat sample was measured after sample cell and reflectance plate spectrum measurement. Preprocessing methods such as normalization and $1^{st}$ and $2^{nd}$ derivations were used to minimize the spectroscopic noise. The partial-least-square (PLS) models were developed to predict chemical properties of oats using a commercial software package, Unscrambler. The PLS models showed the possibility to predict moisture, protein, and fat content of oat samples. The coefficient of determination ($R^2$) of moisture, protein, and fat was greater than 0.89. However, it was hard to predict Fe and K concentrations due to their low concentrations in the oat samples. The coefficient of determinations of Fe and K were 0.57 and 0.77, respectively. In future studies, the stability and practicability of these models should be improved by using a high accuracy spectrophotometer and by performing calibrations with a wider range of oat chemicals.

• 한국안광학회지
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• 제17권1호
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• pp.53-58
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• 2012

목적: 최적구면굴절상태에서 진용한 시력표로 측정한 logMAR 시력에 의한 난시예상량을 파악해 보고, 투영식 소수시력표와 비교해 보고자 하였다. 방법: 대학생 150명 300안을 대상으로 logMAR 시력과 소수시력을 측정하여 완전교정 때의 난시량과 비교하였다. 결과: 진용한 시력표가 투영식 시력표에 비해 시표 줄 간의 차이가 0.25 D이상으로 비교적 구별이 뚜렷하였다. 또한 난시량과의 상관성은 logMAR 시력이 r = 0.8578로 소수시력 r = -0.7199 보다 높았다. 결론: 최적구면굴절상태에서 logMAR 시력을 통하여 난시량을 예측할 수 있었고, 투영식 시력표 보다 진용한 시력표가 단계별 난시예상량을 예측하는 것이 쉬운 것으로 판단된다.

• 산업기술연구
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• 제17권
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• pp.219-225
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• 1997

The maturity concept was adopted to predict the strength of concrete, which was subjected to several temperature levels and variable curing conditions. Penetration test and compressive test were conducted to measure the initial and final setting time and the compressible strength of concrete specimen, respectively. Also, the temperature and time were measured at some time intervals for calculating the maturity. The initial and final setting were delayed as the w/c ratio increased and curing temperature decreased. The relationships at the relative strength and the equivalent age were proposed at different w/c ratio for the several temperature curing conditions, and these were applied for the variable curing conditions.

• 대한산업공학회지
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• 제20권4호
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• pp.135-149
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• 1994

Demand forecasting is to estimate the demand of customers for products and services. Since the future is uncertain in nature, it is too difficult for us to predict exactly what will happen. Therefore, when the forecasting is performed upon the uncertain future, it is realistic to estimate the value of demand as an interval or a fuzzy number instead of a crisp number. In this paper, we propose a demand forecasting method using the standard back-propagation algorithm and then we extend the method to the case of interval inputs. Next, we demonstrate that the proposed method using the interval neural networks can represent the fuzziness of forecasting values as intervals. Last, we propose a demand forecasting method using the transformed input variables that can be obtained by taking account of the degree of influence between an input and an output.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.309-311
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• 1996

In this paper, we propose two types of novel discrete time current control methods of modified fixed band hysteresis control and optimal control for Parallel Resonant DC Link Inverters(PRDCLI). Because zero bus voltage intervals are generated on the DC link of PRDCLI, we can obtain the information of counter electromotive force(emf) by a simple estimation strategy. The proposed current controllers predict the currents of the next resonant cycle using the obstained information of counter emf and the average values of DC link voltages. The computer simulation results for a simple equivalent circuit of induction motor show that the proposed control methods are more effective than conventional methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.221-227
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• 2007

This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.227-233
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• 2004

This paper presents our work on constructing a model that is intended to predict the probability of attrition at specified points in time among customers of an insurance company. There are some difficulties in building a data-based model because a data set may contain possibly censored observations. In an effort to avoid such kind of problem, we performed logistic regression over specified time intervals while using explanatory variables to construct the proposed model. Then, we developed a Cox-type regression model for estimating the probability of attrition over a specified period of time using time-dependent explanatory variables subject to changes in value over the course of the observations.