• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.343-349
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• 2004

Electroglottograph(EGG) is a signal recorded from the vocal cord vibration by measuring electrical impedance across the vocal folds through the neck skin. The purpose of this study was to develop EGG system and to evaluate possibility for the application on speech analysis and laryngeal disease diagnosis. EGG system was composed of two pairs of ring electrodes, tuned amplifier, phase sensitive detector, low pass filter, and auto-gain controller. It was designed to extract electric impedance after detecting by amplitude modulation method with 2.7MHz carrier signal. Extracted signals were transmitted through line-in of PC sound card, sampled and quantized. Closed Quotient(CQ), Speed Quotient(SQ), Speed Index(SI), fundamental frequency of vocal cord vibration(F0), pitch variability of vocal fold vibration (Jitter), and peak-to-peak amplitude variability of vocal fold vibration(Shimmer) were analyzed as EGG parameters. Experimental results were as follows: the faster vocal fold vibration, the higher values in CQ parameter and the lower values in SQ and SI parameters. EGG and speech signals had the same fundamental frequency. CQ, SQ, and SI were significantly different between normal subjects and patients with laryngeal cancer. These results suggest that it is possible to implement portable EGG system to monitor the function of vocal cord and to test functional changes of the glottis.

• Korean Journal of Food Science and Technology
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• v.27 no.5
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• pp.703-707
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• 1995

Shelf-life dating of cooked and heat sterilized food was carried out with the use of principal component analysis (PCA). Changes in color, pH, acidity and sensory properties were measured and analyzed during storage at 20, 30 and $40^{\circ}C$. Acceptability of sample was decreased during storage, shelf-life of sample was determined 1.5, 3 and 3 months at 20, 30 and $40^{\circ}C$, respectively. Application of PCA to quality evaluation, principal component (PC) 1 dominated 49.6% of total variation and PC 2 expressed 28.8%. The rate of change of PC 1 to storage time was 1.3 with increasing temperature of $10^{\circ}C$, and close to shelf-life determined by accepability at 20 and $40^{\circ}C$. Therefore, PCA was applicable to evaluate the quality, predict the shelf-life and investigate the quality parameter of food during storage.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.1-9
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• 2020

In recent days, fuel cell has received attention from the world as an alternative power source to hydrocarbon used in automobile engines. With the industrial advances of fuel cell, There have been a lot of researches actively conducted to find a way of generating hydrogen. Among many hydrogen production methods, Solid Oxide Electrolysis Cell(SOEC) is not only a basic way but also environment-friendly method to produce hydrogen gas. Solid Oxide Electrolysis Cell has lower electrical energy demands and high thermal efficiency since it is possible to operate under high temperature and high pressure conditions. For these reasons, experimental researches as well as studies on numerical modeling for Solid Oxide Electrolysis Cell have been under way. However, studies on numerical modeling are relatively less enough than experimental accomplishments and have limited performance prediction, which mostly is considered as a result from inadequate effects of electrochemical properties by temperature and pressure. In this study, various experimental studies of commercial Membrane Electrode Assembly (MEA) composed of Ni-YSZ (40wt%, Ni-60 wt% YSZ)/8-YSZ (TOSOH, TZ8Y)/LSM (La_0.9Sr_0.1MnO₃) was utilized for improving effectiveness of SOEC model. After numerically analyzing effects of electrochemical properties according to operating temperature, causing the largest deviation between experiments and simulation are that Charge Transfer Coefficient (CTC), exchange current density, diffusion coefficient, electrical conductivity in SOEC. Analyzing temperature effect on parameter used in overpotential model is conducted for modeling of SOEC. cross-validation method is adopted for application of various MEA and evaluating feasibility of model. As a result, the study confirm that the numerical model of SOEC based on structured process of effectiveness evaluation makes performance prediction better.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.795-806
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• 1998

Soil moisture is affected by regional climate, soil characteristics and land surface condition, etc,. Especially, the changes in land surface condition is more than other factors, which is mainly due to rapid urbanization and industrialization. This study is to evaluate how the change of land surface condition impacts on soil moisture field evolution using a simple model of soil moisture dynamics. For the quantification of soil moisture field, the first half of the paper is spared for the statistical characterization based on the first- and second-order statistics of Washita '92 and Monsoon '90 data. The second half is for evaluating the impact of land cover changes through simulation study using a model for soil moisture dynamics. The model parameters, the loss rate and the diffusion coefficient, have been estimated using the observed data statistics, where the changes of surface conditions are considered into the model by applying various parameter sets with different second-order statistics. This study is concentrated on evaluating the impact due to the changes of land surface condition variability. It is because we could easily quantify the impact of the changes of its areal mean based on the linear reservoir concept. As a result of the study, we found; (1)as the variability of land surface condition, increases, the soil moisture field dries up more easily, (2)as the variabilit y of the soil moisture field is the highest at the beginning of rainfall and decreases as time goes on to show the variability of land surface condition, (3)the diffusion effect due to surface runoff or water flow through the top soil layer is limited to a period of surface runoff and its overall impact is small compared to that of the loss rate field.

• Current Optics and Photonics
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• v.1 no.2
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• pp.107-112
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• 2017

An adaptive optics system can be simulated or analyzed to predict its closed-loop performance. However, this type of prediction based on various assumptions can occasionally produce outcomes which are far from actual experience. Thus, every adaptive optics system is desired to be tested in a closed loop on an optical test bench before its application to a telescope. In the close-loop test bench, we need an atmospheric simulator that simulates atmospheric disturbances, mostly in phase, in terms of spatial and temporal behavior. We report the development of an atmospheric turbulence simulator consisting of two point sources, a commercially available deformable mirror with a $12{\times}12$ actuator array, and two random phase plates. The simulator generates an atmospherically distorted single or binary star with varying stellar magnitudes and angular separations. We conduct a simulation of a binary star by optically combining two point sources mounted on independent precision stages. The light intensity of each source (an LED with a pin hole) is adjustable to the corresponding stellar magnitude, while its angular separation is precisely adjusted by moving the corresponding stage. First, the atmospheric phase disturbance at a single instance, i.e., a phase screen, is generated via a computer simulation based on the thin-layer Kolmogorov atmospheric model and its temporal evolution is predicted based on the frozen flow hypothesis. The deformable mirror is then continuously best-fitted to the time-sequenced phase screens based on the least square method. Similarly, we also implement another simulation by rotating two random phase plates which were manufactured to have atmospheric-disturbance-like residual aberrations. This later method is limited in its ability to simulate atmospheric disturbances, but it is easy and inexpensive to implement. With these two methods, individually or in unison, we can simulate typical atmospheric disturbances observed at the Bohyun Observatory in South Korea, which corresponds to an area from 7 to 15 cm with regard to the Fried parameter at a telescope pupil plane of 500 nm.

• Journal of Chest Surgery
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• v.30 no.11
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• pp.1055-1061
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• 1997

In the field of the experimental lung transplantation, we analyzed the CT findings of acute rejection, infection in the left single allotransplanted lung of adult mongrel dogs, and the CT findings were compared with the histological findings obtained by the lung biopsy Twenty two adult mongrel dogs were divided into two groups(Donor and recipient group). Donor lungs were flushed with LPDG(low pota,ilium dextral glucose) solution(n=4) or modified Euro-collins solution(n=7) and preserved over 20 hours with $10^{\circ}C(1$ case preservation for 4hours). After left single lung transplantation, the chest X-ray and sequential computed tomogram were performed with concomitant hemodynamic study and arterial blood gas analysis on immediate postoperative period, postoperative 3rd day and postoperative 7th day. Two of eleven transplanted lungs had acute rejection which was represented as moderate infiltration at immediate or 1st postoperative d y but became extensive infiltration at postoperative 3rd day on CT. There were showed one case of bronchopleural fistula, six cases of pneumonia and two cases of pulmonary infarction. In one rejection cases, the opacity of transplanted lung was improved by injection of methylprednisolone 500mg daily during 3 days. We concluded that CT was a useful noninvasive evaluation parameter after lung transplantation and the serial CT scan enabled early detection of acute rejection.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.441-446
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• 2020

In this paper, we propose the α-Feature Map Scaling (α-FMS) method which extends the FMS method that was designed to enhance the discriminative power of feature maps of deep neural networks in Speaker Verification (SV) systems. The FMS derives a scale vector from a feature map and then adds or multiplies them to the features, or sequentially apply both operations. However, the FMS method not only uses an identical scale vector for both addition and multiplication, but also has a limitation that it can only add a value between zero and one in case of addition. In this study, to overcome these limitations, we propose α-FMS to add a trainable parameter α to the feature map element-wise, and then multiply a scale vector. We compare the performance of the two methods: the one where α is a scalar, and the other where it is a vector. Both α-FMS methods are applied after each residual block of the deep neural network. The proposed system using the α-FMS methods are trained using the RawNet2 and tested using the VoxCeleb1 evaluation set. The result demonstrates an equal error rate of 2.47 % and 2.31 % for the two α-FMS methods respectively.

• Korean Journal of Veterinary Research
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• v.40 no.2
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• pp.383-391
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• 2000

Milk urea nitrogen (MUN) determination is being used an indicator of the protein-energy balance in dairy herds. A faulty balance can be corrected to optimize milk production and animal health. This parameter is regarded as a potential tool to evaluate suboptimal feeding practices and reproductive disorders. Therefore, the purpose of this study was to investigate the response of milk composition by regular feeding analysis and to compared the relationship between MUN and milk protein(MP) and fertility at the insemination period in Holstein dairy cows. Total of 355 artificial insemination (AI) for 150 Holstein cows in the herd were used to examine the relationship between MUN and MP content and conception rate. The AI occured for the cows 50 to 150 day in milk, and MUN and MP concentration were determined using automated infrared procedures. The mean${\pm}$standard deviation of MUN and MP concentration in the herd were $15.6{\pm}2.1mg/dl$ and $3.23{\pm}0.38%$, respectively. MUN contents of bulk milk were increase by elevated crude protein intake. The conception rate was lower in the cows in which the level of MUN was lower than > 8.0mg/dl (10.0%) or > higher than 25mg/dl (15.4%) relative to the cows in MUN content of 12.0~17.9 mg/dl (36.7%) at the time of insemination. Also, lower MP than 3.0% or higher MP than 3.25% were associated with a lower conception rates. Consequently, MUN and MP analyses may be used serve as a monitoring tool of protein and energy nutritional balance to improve reproduction efficiency in Holstein dairy cows.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.121-131
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• 2007

Despite the close linkage in changes between the ecological and hydrological processes in forest ecosystems, an integrative approach has not been incorporated successfully. In this study, based on the vegetation and hydrologic data of the Gwangneung headwater catchment with the Geographic Information System, we attempted such an integrated approach by employing the Regional Hydro-Ecologic Simulation System (RHESSys). To accomplish this, we have (1) constructed the input data for RHESSys, (2) developed an integrated calibration system that enables to consider both ecological and hydrological processes simultaneously, and (3) performed sensitivity analysis to estimate the optimum parameters. Our sensitivity analyses on six soil parameters that affect streamflow patterns and peak flow show that the decay parameter of horizontal saturated hydraulic conductivity $(s_1)$ and porosity decay by depth (PD) had the highest sensitivity. The optimization of these two parameters to estimate the optimum streamflow variation resulted in a prediction accuracy of 0.75 in terms of Nash-Sutcliffe efficiency (NSec). These results provide an important basis for future evaluation and mapping of the watershed-scale soil moisture and evapotranspiration in forest ecosystems of Korea.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.517-526
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• 2019

The purpose of this study is to find the optimal method for clinical application by analyzing image quality and radiation output according to parameter combination when using the Automatic Exposure Control (AEC). The experimental method combines 70, 81 kVp with sensitivity S200, S400, S800 and S1000 of the Automatic Exposure Control for Entrance Surface Dose (ESD), current volume, Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Time-to-Radiation Dose Curve in abdomen and pelvis. And then, image quality and radiation output stability were evaluated. As a results, Entrance Surface Dose, current volume, Signal to Noise Ratio, Contrast to Noise Ratio decreased as the tube voltage and sensitivity were set higher. In addition, the higher tube voltage and sensitivity, the Time-to-Radiation Dose Curve showed a poor output stability. In conclusion, the higher the combination of tube voltage and sensitivity in the use of Automatic Exposure Control, the more problems can be seen in image quality and stability of the radiation output. Therefore, a relatively low combination of tube voltage and sensitivity showed that the image quality and radiation output stability could be optimized by minimizing the error range that would occur when the detector recognized a combination of parameters.