• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.257-262
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• 1996

When we are estimate the smoothing parameter in spline regression model, we deal the diagnostic of influence observations as posteriori analysis. When we use Generalized Maximum Likelihood Function as the estimation method of smoothing parameter, we propose the diagnostic measure for influencial observations in the obtained estimate, and we introduce the finding method of the proper smoothing parameter estimate.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.255-268
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• 1992

We propose an iterated interpolation approach for the estimation fo time series parameters in the presence of outliers. The proposed approach iterates the parameter estimation stage and the outlier detection stage until no further outliers are detected. For the detection of outliers, interpolation diagnostic is applied, where the atypical observations by the one-step-ahead predictor instead of downweighting is also proposed. The performance of the proposed estimation methods is compared with other robust estimation methods by simulation study. It is observed that the iterated interpolation approach performs reasonably well is general, especially for single AO case and large $\phi$ in absolute values.

• Journal of Korean Society of Water and Wastewater
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• v.10 no.2
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• pp.88-103
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• 1996

The objective of this study is to develop stochastic and deterministic models which could be used to synthesize water application time series. Adaptive models using mulitivariate ARIMA(Transfer Function Model) are developed for daily urban water use forecasting. The model considers several variables on which water demands is dependent. The dynamic response of water demands to several factors(e.g. weekday, average temperature, minimum temperature, maximum temperature, humidity, cloudiness, rainfall) are characterized in the model by transfer functions. Daily water use data of Kumi city in 1992 are employed for model parameter estimation. Meteorological data of Seonsan station are utilized to input variables because Kumi has no records about the meteorological factor data.To determine the main factors influencing water use, autocorrelogram and cross correlogram analysis are performed. Through the identification, parameter estimation, and diagnostic checking of tentative model, final transfer function models by each month are established. The simulation output by transfer function models are compared to a historical data and shows the good agreement.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.874-880
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• 1986

A new diagnastic method for detection and location of faults in a linear time-invariant system is proposed. The fault detection algorithm is formulated in a signal space, while the fault location algorithm with estimation is done in a parameter space. In a way different from the conventional approach, the method of fault location with estimation is studied to apply the new concept to establish the models with an unknown parameter under the assumption of 1-fold fault. According to computer simulation, the proposed diagnostic method is effective as an algorithm for fault diagnosis of industdrial process controllers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.367-370
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• 2001

This paper proposes a new deterioration diagnostic technique for power facilities by analyzing the pulse-height analysis of leakage current. Until now, various deterioration diagnostic techniques to prevent power system failures by deterioration of power facilities are suggested, and most of which measures leakage current amplitude only as a estimation parameter. In this experiment, it is known that the pulse heights of the leakage current are increased according to deterioration progress as well as there comes remarkable changes in pulse height distribution thereto. Therefore, the use of pulse height distribution in deterioration diagnostic technique makes more accurate diagnosis than the conventional method by using only leakage current value. From the application test, it is confirmed that the proposed technique has sufficient performance to diagnose deterioration of power facilities.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.40-51
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• 1991

The $C_B$ statistic, a generalization of Mallows's $C_L$ statistic, is developed to determine the shrinkage parameter. Since not all cases in a data set play an equal role in forming $C_B$, a subdivision of $C_B$ into individual components for each case is developed. This subdivision is useful both as an aid in understanding $C_B$ and as a diagnostic procedure.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1030-1041
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• 1999

This study examined those problems noticed under the Asymptotically Generalized Least Squares estimator in evaluating a structural model of physical health. The problems were highly correlated parameter estimates and high standard errors of some parameter estimates. Separate analyses of the endogenous part of the model and of the metric of a latent factor revealed a highly skewed and kurtotic measurement indicator as the focal point of the manifested problems. Since the sample sizes are far below that needed to produce adequate AGLS estimates in the given modeling conditions, the adequacy of the Maximum Likelihood estimator is further examined with the robust statistics and the bootstrap method. These methods demonstrated that the ML methods were unbiased and statistical decisions based upon the ML standard errors remained almost the same. Suggestions are made for future studies adopting structural equation modeling technique in terms of selecting of a reference indicator and adopting those statistics corrected for nonormality.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.673-681
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• 2005

As it is the most important to make sure security and reliability for nuclear Power Plant, it's considered the most crucial issues to develop a fault detective and diagnostic system in spite of multiple hardware redundancy in itself. To develop an algorithm for a fault diagnosis in the nuclear PWR steam generator, this paper proposes a method based on ART2(adaptive resonance theory 2) neural network that senses and classifies troubles occurred in the system. The fault diagnosis system consists of fault detective part to sense occurred troubles, parameter estimation part to identify changed system parameters and fault classification part to understand types of troubles occurred. The fault classification part Is composed of a fault classifier that uses ART2 neural network. The Performance of the proposed fault diagnosis a18orithm was corroborated by applying in the steam generator.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.198-204
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• 2008

Uroflowmetry is a non-invasive clinical test useful for screening benign prostatic hyperplasia(BPH) common in the aged men. The current standard way to obtain the urinary flow rate is to continuously acquire the urine weight signal proportional to volume over time. The present study proposed an alternative technique measuring pressure to overcome noise problems present in the standard weight measuring technique. Experiments were performed to simultaneously acquire both weight and pressure changes during urination of 9 normal men. Noise components were separated from volume signals converted from both weight and pressure signals based on the polynomial signal model. Signal-to-noise ratio was defined as the ratio of the energies between signal and noise components of the measured volume changes, which was 8.5 times larger in the pressure measuring technique, implying that cleaner signal could be obtained, more immune to noisy environments. When four important diagnostic parameters were estimated, excellent correlation coefficients higher than 0.99 were resulted with mean relative errors less than 5%. Therefore, the present pressure measurement seemed valid as an alternative technique for uroflowmetry.

• The Korean Journal of Nuclear Medicine
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• v.29 no.1
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• pp.48-53
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• 1995

This study investigates a simple mathematical model for the quantitative estimation of regional myocardial blood flow in experimental canine coronary artery thrombosis using Rb-82 dynamic myocardial positron emission tomography. The coronary thrombosis was induced using the new catheter technique by narrowing the lumen of coronary vessel gradually, which finally led to partial obstruction of coronary artery. Ten Rb-82 dynamic myocardial PET scans were performed sequentially for each experiment using our 5, 10 and 20 second acquisition protocol, respectively, and three regions of interest were drawn on the transaxial slices, one on left ventricular chamber for input function and the other two on normal and decreased perfusion segments for the flow estimation in those regions. Single compartment model has been applied to the measured sets of regional PET data, and the rate constants of influx to myocardial tissue were calculated for regional myocardial flow estimates with the three parameter fits of raw data by the Levenberg-Marquardt method. The results showed that, (1) single compartment model suggested by Kety-Schmidt could be used for the simple estimation of regional myocardial blood flow, (2) the calculated regional myocardial blood flow estimates were dependent on the selection of input function, which reflected partial volume effect and left ventricular wall motion, and (3) mathematically fitted input and tissue time activity curves were more suitable than the direct application of the measured data in terms of convergence.