Kyung-Joon Cha

Computerized analysis of fetal heart rate parameters by gestational age

Objective: The aim of this study is to define the reference ranges for fetal heart rate (FHR) parameters according to gestational age, by determining the relationship between the FHR and gestational age using a computerized FHR analysis system. Methods: Using our own software developed by Hanyang University Hospital in Korea, non‐stress tests were performed for 20 min. FHR parameters for 6455 subjects were analyzed for various gestational groups; <25 weeks, 25–28 weeks, 29–32 weeks, 33–36 weeks, 37–40 weeks, and >40 weeks. Results. The FHR parameters were related to gestational age. The mean baseline FHR, signal loss, and fetal movements decreased significantly with gestation (P<0.0001). The variability and accelerations of FHR were highest for the 37–40 weeks gestational group (P<0.05). Conclusions: The results showed that overall, the differences in the FHR parameters between gestational groups were statistically significant, and the gestational age of the fetus should be considered when interpreting FHR patterns.

Kriging interpolation methods in geostatistics and DACE model

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

Fetal heart rate after vibroacoustic stimulation.

To define reference ranges for fetal heart rate (FHR) parameters after vibroacoustic stimulation (VAS) according to gestational age by determining the relationship between FHR and gestational age using a computerized analysis system.

Estimating time to full uterine cervical dilation using genetic algorithm

The objectives of this study were to provide new parameters to better understand labor curves, and to provide a model to predict the time to full cervical dilation (CD). We studied labor curves using the retrospective records of 594 nulliparas, including at term, spontaneous labor onset, and singleton vertex deliveries of normal birth weight infants. We redefined the parameters of Friedmans labor curve, and applied a three‐parameter model to the labor curve with a logistic model using the genetic algorithm and the Newton–Raphson method to predict the time necessary to reach full CD. The genetic algorithm is more effective than the Newton–Raphson method for modeling labor progress, as demonstrated by its higher accuracy in predicting the time to reach full CD. In addition, we predicted the time (11.4 hours) to reach full CD using the logistic labor curve using the mean parameters (the power of CD = 0.97 cm/hours, a midpoint of the active phase = 7.60 hours, and the initial CD = 2.11 cm). Our new parameters and model can predict the time to reach full CD, which can aid in the forecasting of prolonged labor and the timing of interventions, with the end goal being normal vaginal birth.

The Optimal Design for Noise Reduction of the Intake System in Automobile Using Kriging Model

Recently, the regulations of the government and the concerns of people have rise to the interest in noise pollution levels as compared to other vehicles. In this area, many researchers have studied to reduce this noise in the field of automotive engineering. This paper proposes an optimal design scheme to reduce the noise of the intake system by adapting Kriging with two meta-heuristic techniques. For this, as a measuring tool for the performance of the intake system, the performance prediction software, was used. Then, the length and radius of each component of the current intake system are selected as input variables and the orthogonal arrays is adapted as a space-filling design. With these simulated data, we can estimate a correlation parameter in Kriging by solving the nonlinear problem with a genetic algorithm and find an optimal level for the intake system by optimizing Kriging estimated with simulated annealing. We notice that this optimal design scheme gives noticeable results and is a preferable way to analyze the intake system. Therefore, an optimal design for the intake system is proposed by reducing the noise of its system.

Recovery of signal loss adopting the residual bootstrap method in fetal heart rate dynamics

Abstract Fetal heart rate (FHR) data obtained from a non-stress test (NST) can be presented in a type of time series, which is accompanied by signal loss due to physical and biological causes. To recover or estimate FHR data, which is subjected to a high rate of signal loss, time series models [second-order autoregressive (AR(2)), first-order autoregressive conditional heteroscedasticity (ARCH(1)) and empirical mode decomposition and vector autoregressive (EMD-VAR)] and the residual bootstrap method were applied. The ARCH(1) model with the residual bootstrap technique was the most accurate [root mean square error (RMSE), 2.065] as it reflects the nonlinearity of the FHR data [mean absolute error (MAE) for approximate entropy (ApEn), 0.081]. As a result, the goal of predicting fetal health and identifying a high-risk pregnancy could be achieved. These trials may be effectively used to save the time and cost of repeating the NST when the fetal diagnosis is impossible owing to a large amount of signal loss.

A Study on the Nonlinearity of Chaotic Signal by Bispectral Analysis

During thirty years, deterministic chaos has moved center stage in many areas of applied mathematics. One important stimulus for this, particularly in the early 1970s, was work on nonlinear aspects of the dynamics of plant and animal populations. There are many situations, at least to a crude first approximation, by a simple first-order difference equation. Past studies have shown that such equations, even though simple and deterministic, can exhibit a surprising array of dynamical behavior, from stable points, to a bifurcating hierarchy of stable cycles, to apparently random fluctuations. But higher-order spectral analyses of such behavior are usually not considered. Higher-order spectra of a signal contain important information that is not present in its power spectrum. So, if we find the spectral pattern and get information from it, it will be able to be used effectively in so many fields. Hence, this paper uses auto bicoherence and bicoherence residue which are sort of bispectrum. Applying these to behavior of logistic difference equation, which is typical chaotic signal, the phenomenon of phase coupling and the appearance of frequency band can be analyzed. Such information means that bispectral analysis is useful to detect nonlinearity of signal.

Kriging Optimal Design of an Intake System with Meta-Heuristic Methods for Reducing Noise

Abstract Recently, government regulations and public concern have increased interest in noise pollution levels. Therefore, many researchers have studied to reduce this noise in the field of automotive engineering. The current paper proposes an optimal design scheme to reduce the noise of the intake system by adapting Kriging with two meta-heuristic techniques. This was achieved by using performance prediction software (developed by one of the present authors and his co-workers) as a measuring tool for the performance of the intake system. The length and radius of each component of the current intake system were then selected as input variables and the L18 table of orthogonal arrays was adapted as a space-filling design. With these simulated data, a correlation parameter can be estimated in Kriging by solving the non-linear problem with a genetic algorithm to find an optimal level for the intake system by optimizing Kriging estimated through simulated annealing. This optimal design scheme gives significant results and is a preferable way to analyse the intake system. Therefore, an optimal design for the intake system is proposed for reducing the noise of its system.

The Optimal Design for Noise Reduction of the Intake System in Automobile Using DACE Model

We propose an optimal design to improve the capacity by reducing the noise of the intake system. The length and radius of each component of the current Intake system are selected as control factors. We accept the output from computer simulator with orthogonal arrays. Then, the Kriging estimates are computed. From this, we exploit the optimal design of the intake system by adapting simulated annealing. From the results of this optimal design, we conclude that Kriging method with the orthogonal arrays is the efficient method for Design and Analysis of Computer Experiments and we propose the useful results for the low noise intake system.

The Estimation of Theoretical Semivariogram Adapting Genetic Algorithm for Kriging

In order to use Kriging, one has to estimate three parameters(nugget, sill and range) of semivariogram, which shows the relationship in the given two sites. A visual fit of the semivariogram parameters to a few standard models is widely used. But, it does not give the suitable results and not provide the automated process of Kriging. The gradient based nonlinear least squares is another choices to estimate three parameters, but it has some problems such as initial value problem. In this paper, we suggest the genetic algorithm as a compatible alternative method to solve the above mentioned problem. Finally, we estimate three parameters of semivariogram of rain-fall by adapting the genetic algorithm, compute Kriging estimate and conclude its effectiveness and compatibility.