• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.124-132
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• 2022

This study was aimed to visualize the spatial distribution of PM₁₀ data measured at non-uniformly distributed observation sites in South Korea. Different spatial interpolation methods were applied to irregularly distributed PM₁₀ observation data from January, 2019, when the concentration was the highest and in July, 2019, when the concentration was the lowest. Four interpolation methods with different parameters were used: Inverse Distance Weighted (IDW), Ordinary Kriging (OK), radial base function, and scattered interpolation. Six cases were cross-validated and the normalized root-mean-square error for each case was compared. The results showed that IDW using smoothing-related factors was the most appropriate method, while the OK method was least appropriate. Our results are expected to help users select the proper spatial interpolation method for PM₁₀ data analysis with comparative reliability and effectiveness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.492-505
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• 2022

This study is a study on the results of improving the logic to effectively transmit and decode compressed data in real time by improving the encoding and decoding performance of BL-beta codes that can be used for lossless real-time transmission of IoT sensing data. The encoding process of BL-beta code includes log function, exponential function, division and square root operation, etc., which have relatively high computational burden. To improve them, using bit operation, binary number pattern analysis, and initial value setting of Newton-Raphson method using bit pattern, a new regularity that can quickly encode and decode data into BL-beta code was discovered, and by applying this, the encoding speed of the algorithm was improved by an average of 24.8% and the decoding speed by an average of 5.3% compared to previous study.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.683-692
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• 2019

Objective: We aimed to evaluate correlations between computed tomography (CT) parameters and pulmonary function test (PFT) parameters according to disease severity in patients with chronic obstructive pulmonary disease (COPD), and to determine whether CT parameters can be used to predict PFT indices. Materials and Methods: A total of 370 patients with COPD were grouped based on disease severity according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) I-IV criteria. Emphysema index (EI), air-trapping index, and airway parameters such as the square root of wall area of a hypothetical airway with an internal perimeter of 10 mm (Pi10) were measured using automatic segmentation software. Clinical characteristics including PFT results and quantitative CT parameters according to GOLD criteria were compared using ANOVA. The correlations between CT parameters and PFT indices, including the ratio of forced expiratory volume in one second to forced vital capacity (FEV1/FVC) and FEV₁, were assessed. To evaluate whether CT parameters can be used to predict PFT indices, multiple linear regression analyses were performed for all patients, Group 1 (GOLD I and II), and Group 2 (GOLD III and IV). Results: Pulmonary function deteriorated with increase in disease severity according to the GOLD criteria (p < 0.001). Parenchymal attenuation parameters were significantly worse in patients with higher GOLD stages (P < 0.001), and Pi10 was highest for patients with GOLD III (4.41 ± 0.94 mm). Airway parameters were nonlinearly correlated with PFT results, and Pi10 demonstrated mild correlation with FEV1/FVC in patients with GOLD II and III (r = 0.16, p = 0.06 and r = 0.21, p = 0.04, respectively). Parenchymal attenuation parameters, airway parameters, EI, and Pi10 were identified as predictors of FEV₁/FVC for the entire study sample and for Group 1 (R² = 0.38 and 0.22, respectively; p < 0.001). However, only parenchymal attenuation parameter, EI, was identified as a predictor of FEV₁/FVC for Group 2 (R² = 0.37, p < 0.001). Similar results were obtained for FEV₁. Conclusion: Airway and parenchymal attenuation parameters are independent predictors of pulmonary function in patients with mild COPD, whereas parenchymal attenuation parameters are dominant independent predictors of pulmonary function in patients with severe COPD.

• Journal of Food Hygiene and Safety
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• v.28 no.3
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• pp.217-221
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• 2013

This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at $4^{\circ}C$ (1440 h), $15^{\circ}C$ (288 h), $25^{\circ}C$ (72 h), and $30^{\circ}C$ (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (${\mu}_{max}$; ${\log}CFU{\cdot}g^{-1}{\cdot}h^{-1}$), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at $15^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. The ${\mu}_{max}$ values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.315-329
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• 2014

In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.

• The Journal of Korean Physical Therapy
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• v.20 no.3
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• pp.9-18
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• 2008

Purpose: We determined the effect of global synkinesis(GS) on gait ability, muscle contraction, and central neuron action potentials in post-stroke hemiplegic subjects. Methods: Thirty hemiplegia patients were evaluated for walking ability, muscle contraction, central neuron action potential, and comparing differences between the H-GS(high-global synkinesis) group and L-GS(low-global synkinesis) group. To obtain the GS level, surface electromyography(EMG) data were digitized and processed to root mean square(RMS). Walking ability was tested with a modified motor assessment scale(MMAS), a 10 m walking test, timed up and go(TUG) test, and a Fugl-Meyer assessment(FMA). Muscle contraction ability was measured as maximal isometric contraction(MIC) peak, MIC slope, and MIC ramp up using mechanomyography(MMG). Central neuron action potential was measured as the H/Mmax ratio or V/Mmax ratio using EMG. The data were analyzed with t-tests to determine the statistical significance. Results: MMAS(p<0.01), 10 m walking velocity(p<0.01), TUG(p<0.01), FMA-HKA(Hip, Knee, Ankle)(p<0.05), FMA-coordination(p<0.05), MIC peak (p<0.05), MIC slope(p<0.01), and MIC ramp up(p<0.05) were significantly different between H-GS and L-GS, as was the V/Mmax ratio(p<0.05), but H/Mmax was not. Conclusion: Lower GS levels indicated better walking ability and motor function. Therefore, intervention programs should consider GS levels in gait training of chronic hemiplegia.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.2
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• pp.307-316
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• 1994

The rainfall forecasting model of the short term is improved at the point where meterological data is not gaged. In this study, the adopted model is based on the assumptions for simulation model of rainfall process, meteorological homogeneousness, prediction and estimation of meteorological data. A Kalman Filter technique is used for rainfall forecasting. In the existing models, the equation of the model is non-linear type with regard to rainfall rate, because hydrometer size distribution (HSD) depends on rainfall intensity. The equation is linearized about rainfall rate as HSD is formulated by the function of the water storage in the cloud. And meteorological input variables are predicted by emprical model. It is applied to the storm events over Taech'ong Dam area. The results show that root mean square error between the forecasted and the observed rainfall intensity is varing from 0.3 to 1.01 mm/hr. It is suggested that the assumptions of this study be reasonable and our model is useful for the short term rainfall forecasting at the ungaged point of the meteorological data.

• 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.

• Genomics & Informatics
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• v.13 no.1
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• pp.15-24
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• 2015

Fatty acid synthase (FASN, EC 2.3.1.85), is a multi-enzyme dimer complex that plays a critical role in lipogenesis. This lipogenic enzyme has gained importance beyond its physiological role due to its implications in several clinical conditions-cancers, obesity, and diabetes. This has made FASN an attractive pharmacological target. Here, we have attempted to predict the theoretical models for the human enoyl reductase (ER) and ${\beta}$-ketoacyl reductase (KR) domains based on the porcine FASN crystal structure, which was the structurally closest template available at the time of this study. Comparative modeling methods were used for studying the structure-function relationships. Different validation studies revealed the predicted structures to be highly plausible. The respective substrates of ER and KR domains-namely, trans-butenoyl and ${\beta}$-ketobutyryl-were computationally docked into active sites using Glide in order to understand the probable binding mode. The molecular dynamics simulations of the apo and holo states of ER and KR showed stable backbone root mean square deviation trajectories with minimal deviation. Ramachandran plot analysis showed 96.0% of residues in the most favorable region for ER and 90.3% for the KR domain, respectively. Thus, the predicted models yielded significant insights into the substrate binding modes of the ER and KR catalytic domains and will aid in identifying novel chemical inhibitors of human FASN that target these domains.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.