• The Journal of Korean Medicine
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• v.35 no.4
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• pp.24-35
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• 2014

Objectives: Although the autonomic nervous system (ANS) is thought to play an important role in treatment of obesity, no study has been conducted to investigate acupuncture's effects on this aspect of the ANS. This study aimed to describe the effects of acupuncture in the ANS by means of heart rate variability (HRV) analysis. Methods: A total of 46 obese women aged from 21 to 54 with body mass index ranging from 25.1 to $39.3kg/m^2$ were recruited and randomized into both the real acupuncture group (n=23) and sham acupuncture group (n=23). A total of 3 instances of HRV analysis were conducted before, during, and after treatment. Statistically significant differences between time and groups were analyzed using repeated measure analysis of variance. Results: All parameters of time domain analysis and frequency domain analysis except for the square root of the mean squared differences of successive normal sinus intervals (RMSSD) and very low frequency (VLF) showed significant differences between times. The mean of all R-R intervals (mean RR) showed significant level of interaction between time and group. Between groups, time domain analysis of standard deviation of the normal-to-normal intervals (SDNN), RMSSD and frequency domain analysis of total power (TP) and high frequency (HF) showed significant differences. Conclusions: The real acupuncture group showed deactivation of parasympathetic function and relative increase of sympathetic activity in obese subjects. Further studies are necessary to uncover the mechanisms of acupuncture in obesity treatment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• The Journal of Korean Obstetrics and Gynecology
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• v.35 no.3
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• pp.122-136
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• 2022

Objectives: The aim of this study is to investigate Heart Rate Variability (HRV) characteristics of patients with primary dysmenorrhea at the menstrual phase. Methods: 7 databases (Pubmed, Cochrane library, CNKI, RISS, KISS, OASIS, ScienceON) were searched for eligible studies published before 2021 December. The studies comparing HRV between patients with primary dysmenorrhea and controls were included. A random-effects model was used to evaluate differences of HRV parameters between patients with primary dysmenorrhea and controls. Results: 4 articles were included in this review based on inclusion and exclusion criteria. SDNN (Standard deviation of NN intervals), RMSSD (Square root of the mean squared difference of successive NN intervals), mean PR (Mean of pulse rate), LF (Low frequency), HF (High frequency), was the most frequently used as HRV parameters. RMSSD was significantly lower in patients with primary dysmenorrhea than controls. There was no statistically significant difference of other HRV parameters between patients with primary dysmenorrhea and controls. Conclusions: This study suggests that parasympathetic activity and overall functions of autonomic nervous system might be decreased in patients with primary dysmenorrhea at the menstrual phase. In the future, well-designed clinical studies using HRV and additional meta-analysis should be conducted to obtain a wealth of information about HRV characteristics of patients with primary dysmenorrhea.

• Proceedings of the KSRS Conference
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• v.1
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• pp.146-149
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• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.429-436
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• 2009

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. When the control chart signals after the occurrence of a special cause, the special cause will be detected and eliminated from the process by the rectifying action. However, when the elimination of the special cause costs high or is not practically possible, an alternative action is to readjust the process with appropriately modified adjustment scheme. In this paper, we propose the readjustment procedure after having a true signal, and show that the use of the readjustment can reduce the deviation of a process from the target.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.268-273
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• 2000

Plasma models are crucial to equipment design and process optimization. A radial basis function network(RBFN) in con-junction with statistical experimental design has been used to model a process plasma. A 2$^4$ full factorial experiment was employed to characterized a hemispherical inductively coupled plasma(HICP) in characterizing HICP, the factors that were varied in the design include source power, pressure, position of shuck holder, and Cl$_2$ flow rate. Using a Langmuir probe, plasma attributes were collected, which include typical electron density, electron temperature. and plasma potential as well as their spatial uniformity. Root mean-squared prediction errors of RBEN are 0.409(10(sup)12/㎤), 0.277(eV), and 0.699(V), for electron density, electron temperature, and Plasma potential, respectively. For spatial uniformity data, they are 2.623(10(sup)12/㎤), 5.704(eV) and 3.481(V), for electron density, electron temperature, and plasma potential, respectively. Comparisons with generalized regression neural network(GRNN) revealed an improved prediction accuracy of RBFN as well as a comparable performance between GRNN and statistical response surface model. Both RBEN and GRNN, however, experienced difficulties in generalizing training data with smaller standard deviation.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.339-353
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• 2014

A straightforward method for optimal determining of a high frequency inductor's parasitic capacitance is presented. The proposed estimation method is based on measuring the inductor's impedance samples over a limited frequency range bordering on the resonance point considering k-dB deviation from the maximum impedance. An optimized solution to k could be obtained by minimizing the root mean squared error between the measured and the estimated impedance values. The model used to provide the estimations is a parallel RLC circuit valid at resonance frequency which will be transferred to the real model considering the mentioned interval of frequencies. A straightforward algorithm is suggested and programmed using MATLAB which does not require a wide knowledge of design parameters and could be implemented using a spectrum analyzer. The inputs are the measured impedance samples as a function of frequency along with the diameter of the conductors. The suggested algorithm practically provides the estimated parameters of a real inductance model at different frequencies, with or without design information. The suggested work is different from designing a high frequency inductor; it is rather concentration of determining the parameters of an available real inductor that could be easily done by a recipe provided to a technician.

• Journal of Ocean Engineering and Technology
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• v.27 no.4
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• pp.83-89
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• 2013

A numerical scheme based on a mode superposition method is presented for the dynamic response analysis of a top-tensioned riser (TTR) under sheared current loads. The natural frequencies and mode shapes of the TTR have been calculated analytically for a beam with a slowly varying tension and pinned-pinned boundary conditions at the top and bottom ends. The lift coefficients and corresponding amplitudes used to estimate the vortex-induced modal force and damping for each mode were predicted via iterative calculations based on the input and output power balancing concept. Here, the power-in regions were controlled by the normal distribution function, for which the center was coincident with the lock -in location by local vortex-shedding, and the range was defined by the constant standard deviation for the reduced velocity by the local current speed. Finally, dynamic responses such as root-mean-squared displacement and stress were calculated using the mode superposition technique. In order to verify the presented scheme, a numerical calculation was performed for a TTR under an arbitrary linearly sheared current and linearly varying tension. A comparison with the results of the existing software showed that the presented scheme could give reliable and feasible solutions. Case studies were performed to investigate the effects of various current loads and tensions.

• Atmosphere
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• v.21 no.3
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• pp.311-317
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• 2011

Aerosol optical properties from the radiation measurements by SKYNET PREDE skyradiometers, POM-01 and POM-02 were compared during the inter-calibration campaign at Seoul in February 2009. The monochromatic solar flux at the top of the atmosphere ($F_0$) gave a relative standard deviation (RSD) of 9-10% for both instruments. This comparatively high value of RSD was probably because $F_0$ was determined at short time intervals, in the morning and afternoon, using the measurements made in the polluted environment of Seoul. Although POM-02 was more effective in tracking the solar radiation, aerosol optical depths (AODs) from the two instruments were very similar after the cloud screening procedure. The squared correlation coefficients ($R^2$) of single scattering albedo (SSA) and real and imaginary refractive indices between the two instruments was around 0.5 but increased to 0.7-0.8 when only using AOD greater than 0.4. Nevertheless, mean values of the Angstrom exponent, SSA, and the imaginary refractive index of POM-02 were higher than those of POM-01.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1073-1078
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• 2014

In this paper, an effective repeat-back jamming (RBJ) mitigation scheme known assuccessive repeat-back jamming cancellation (SRC) is proposed for the utilization of the successive interference cancellation (SIC) algorithm which is used to mitigate the near-far effect and the multiple-access interference for code division multiple-access communication systems. The proposed scheme uses a combined pseudo-random noise (C-PRN) signal from the estimated major parameters of RBJ signals. To evaluate the performance of the proposed scheme, the root mean squared (RMS) code tracking errors are shown according to the standard deviation of the parameter estimation errors of an RBJ signal, and using the well-known major parameters estimation schemes with a C-PRN signal through Monte-Carlo simulation.