• Journal of Veterinary Clinics
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• v.7 no.1
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• pp.429-438
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• 1990

The cytochemical characteristics of the hematopoietic cells in blood and bone marrow from 3 clinically healthy dogs were examined using a battery of cytochemical stains. Alkaline phosphotase activity was demonstrated in eosinophilic series and occassionally in progranulocytes. A variety of cells exhibited acid phosphatase activity, but tartrate-resistant acid phosphatase activity was seen only in eosinophilic series. Peroxidase activity was observed in myeloblasts to segmented cells of granulocytic series and in monocytes. ${\alpha}$-naphthyl acetate esterase activity was found in monocytes and occassionally in lymphocytes. Naphthyl-AS-D-chloroacetate esterase marked neutrophilic series from myeloblasts to segmented cells. ${\beta}$-Glucuronidase activity was detected in a variety of cells except the cells of erythrocytic series. Periodic acid Schiff stain-positive granules were demonstrated in the neutrophilic and eosinophilic series from myelocytes to segmented cells and in monocytes and occassionally in lymphocytes. Sudan black B stain-positive granules marked granulocytic series from myeloblasts to segmented tells and monocytes.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.5
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• pp.1191-1194
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• 2005

The aim of this study was to investigate the change of Heart Rate Variability(HRV) that mild cold stimulus on the forehead of healthy men induces. 34 healthy male subjects participated in the experiments. On the first test series, 15 subjects were applied to the mild cold stimulus by the devise for cold stimulation. In the second test series, 10 subjects With heat Syndrome and 5 subjects With cold Syndrome were applied to the mild cold Stimulus. Aa a additional test, 4 subjects with cold syndrome were applied to the warm stimulus in the last test series. We analyzed the HRV through measuring electrocardiogram.(ECG). The result of this study is comparatively clear. In the first test series, mild cold stimulus made parasympathetic nervous system be activated. In the second test series, mild cold stimulus made parasympathetic nervous system be activated both in subjects with heat syndrome and subjects with cold syndrome, and heat syndrome shows more active parasympathetic nervous system rather than cold syndrome subjects do. In the last test series, 2 subjects with cold syndrome respond the mild cold stimulus. That means warm stimulus of cold condition subjects made parasympathetic nervous system active in 2 of 4 subjects. We found out that mild cold stimulus on forehead makes parasympathetic nervous system be activated in healthy male, and it can be interpreted that mild cold stimulus make healthy human be relaxed. Also, subjects have different fondness of thermal stimulus according to their Cold or Heat condition Preferences. Last test series shows that we need to investigate effect of the warm stimulus heat syndrome subjects.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.433-441
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• 2006

Because of the low power and low rate of a sensor network, outlier is frequently occurred in the time series data of sensor network. In this paper, we suggest periodic pattern analysis that is applied to the time series data of sensor network and predict outlier that exist in the time series data of sensor network. A periodic pattern is minimum period of time in which trend of values in data is appeared continuous and repeated. In this paper, a quantization and smoothing is applied to the time series data in order to analyze the periodic pattern and the fluctuation of each adjacent value in the smoothed data is measured to be modified to a simple data. Then, the periodic pattern is abstracted from the modified simple data, and the time series data is restructured according to the periods to produce periodic pattern data. In the experiment, the machine learning is applied to the periodic pattern data to predict outlier to see the results. The characteristics of analysis of the periodic pattern in this paper is not analyzing the periods according to the size of value of data but to analyze time periods according to the fluctuation of the value of data. Therefore analysis of periodic pattern is robust to outlier. Also it is possible to express values of time attribute as values in time period by restructuring the time series data into periodic pattern. Thus, it is possible to use time attribute even in the general machine learning algorithm in which the time series data is not possible to be learned.

• Journal of Microbiology and Biotechnology
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• v.15 no.3
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• pp.461-465
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• 2005

Characteristics of biological $CO_2$ fixation by Chlorella sp. HA-1 were investigated in a semi-continuous and series reactor system using an internally illuminated photobioreactor to overcome shortcomings of physicochemical technologies such as adsorption and membrane separation. High $CO_2$ fixation rate was achieved in the semi-continuous reactor system, in which the dilution ratios of the culture medium were controlled. The average $CO_2$ fixation rate was maintained almost constantly when the dilution ratio increased by 0.1 increment from the initial value of 0.5. The total removal efficiency of $CO_2$ was enhanced by employing a series reactor system. The average $CO_2$ fixation rate increased until 4.013 g $CO_2\;day^{-1}$ in a series operation of four reactors, compared to 0.986 g $CO_2\;day^{-1}$ in a batch operation mode. The total $CO_2$ fixation rate was proportional to the number of reactors used in the series reactor system. In the series reactor system of semi-continuous operation, a large amount of $CO_2$ was removed continuously for 30 days. These results showed that the present reactor systems are efficient and economically feasible for a biological $CO_2$ fixation.

• Selected Papers of The Society of Naval Architects of Korea
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• v.1 no.1
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• pp.76-90
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• 1993

A new propeller series is developed using the newly developed blade section (KH 18 section) which has better cavitation characteristics and higher lift-drag ratio at wade angle-of-attack range than a conventional section. The radial patch distribution of the new series propellers is variable stance they were designed adaptively to a typical wake distribution. Basic geometric particulars of the series propellers. such as chord length, thickness, skew and rake distributions, are determined on the basis of recent full scale propeller geometric data. The series is developed for propellers having 4 blades, and blade area ratios of 0.3, 0.45, 0.6 and 0.75. Mean pitch ratios are varied as 0.5, 0.6, 0.7, 0.95 and 1.1 for each blade area ratio. The new propeller series consists of 20 propellers and is named as the KD(KRISO-DAEWOO)-propeller series. Propeller open-water tests are performed at the towing tank, and cavitation observation tests and fluctuating pressure tests are carried out at the cavitation tunnel of KRISO. $B_{p}-\delta$ curves, which can be used to select the optimum propeller diameter at the preliminary design stage, are derived from a regression analysis of the propeller open-water test results. The KD-cavitation chart is derived from the cavitation observation test results by choosing the local maximum lift coefficient and the local cavitation number as parameters. The cavity extent predicted by the KD-cavitation chart would be more accurate compared to that by an existing cavitation charts, such as the Burrll's cavitation chart, since the former is derived from the cavitation observation test results in a typical ship's wake, while the lather is derived from the test results in a uniform flow.

• Restorative Dentistry and Endodontics
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• v.22 no.2
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• pp.622-636
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• 1997

Glass ionomer cements, which had been developed in 1972, were widely used as an agent for cementation, base, pit and fissure sealant, and esthetic filling material with the advantages of excellent biocompatibility, anti-cariogenic fluoride release. Specimens were made to evaluate the color change of Glass ionomer cement with a newly developed improved Fuji II Le. Specimens for color change study with cement thickness of 1, 2, 3mm were made and those for the study of color shift pattern were made with the assumption that new mid-shade can be made by mixing of equal amount of both shades in 2mm thickness. After 24 hours in a $37^{\circ}C$ incubator, CIELAB color spaces were evaluated with a spectrophotometer. The results were as follows ; 1. All specimens discolored to dark and blue with an increased thickness in all shades (p<0.05). 2. There were significant $a^*$ space (red-green direction) changes in every A, B, C, D shade series except the relationship between 1mm and 2mm thickness groups in B shade series. But the changes were irregular, i.e., each shade series has its own pattern. 3. Each shade series showed its own specific color shift pattern in all $L^*$, $a^*$, $b^*$ spaces. 4. B shade series showed less amont of changes in ${\Delta}{\pm}E$ than those of A and C shade series (p<0.05), but there was no significant difference in ${\Delta}E$ within each shade series.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.405-415
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• 2000

Time series of wind-induced pressure on a structure are modeled using autoregressive moving average (ARMA) model. In an AR process, the current value of the time series is expressed in terms of a finite, linear combination of the previous values and a white noise. In a MA process, the value of the time series is linearly dependent on a finite number of the previous white noises. The ARMA process is a combination of the AR and MA processes. In this paper, the ARMA models with several different combinations of the AR and MA orders are fitted to the wind-induced pressure time series, and the procedure to select the most appropriate ARMA model to represent the data is described. The maximum likelihood method is used to estimate the model parameters, and the AICC model selection criterion is employed in the optimization of the model order, which is assumed to be a measure of the temporal complexity of the pressure time series. The goodness of fit of the model is examined using the LBP test. It is shown that AR processes adequately fit wind pressure time series.

• Journal of Environmental Science International
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• v.20 no.11
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• pp.1425-1435
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• 2011

Time-series change in Gyeongpo beach shoreline was illustrated using DGPS(Differential Global Positioning System, resolution < 0.6m) observation from April, 2009 to April, 2010. The shoreline was subdivided into 12 areas, and westward and eastward movement of shoreline position at each area was calculated. In general, the shoreline moved toward sea during summer, and it moved toward land during winter. The southern and northern part of the shoreline had different pattern in time-series. The shoreline in the southern part moved toward sea during summer and moved toward land during winter, but time-series pattern of the shoreline in the northern part was more complicated than that in the southern part. Pattern of time-series change in the northern part was made up of three different types; the first is that the shoreline moves continuously toward land, and the second thing is that the shoreline's movement is the opposite to the southern part, and the third thing is that the shoreline maintains a state of equilibrium without any great fluctuation. The total length of the shoreline was the largest during winter and the smallest during summer. In general, time-series change in the shoreline had positive(+) relationship with sea surface pressure and wind speed.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.25-33
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• 2009

Recently, the TS fuzzy models that include the linear equations in the consequent part are widely used for time series forecasting, and the prediction performance of them is somewhat dependent on the characteristics of time series such as stationariness. Thus, a new prediction method is suggested in this paper which is especially effective to nonstationary time series prediction. First, data preprocessing is introduced to extract the patterns and regularities of time series well, and then multiple model TS fuzzy predictors are constructed. Next, an appropriate model is chosen for each input data by an adaptive model selection mechanism based on rough sets, and the prediction is going. Finally, the error compensation procedure is added to improve the performance by decreasing the prediction error. Computer simulations are performed on typical cases to verify the effectiveness of the proposed method. It may be very useful for the prediction of time series with uncertainty and/or nonstationariness because it handles and reflects better the characteristics of data.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.67-79
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• 2011

The statistical process control (SPC) assumes that observations follow the particular statistical distribution and they are independent to each other. However, the time-series data do not always follow the particular distribution, and most of cases are autocorrelated, therefore, it has limit to adopt the general SPC in tim series process. In this study, we propose a MPBC (Model Parameter Based Control-chart) method for fault detection in time-series processes. The MPBC builds up the process as a time-series model, and it can determine the faults by detecting changes parameters in the model. The process we analyze in the study assumes that the data follow the ARMA (p,q) model. The MPBC estimates model parameters using RLS (Recursive Least Square), and $K^2$-control chart is used for detecting out-of control process. The results of simulations support the idea that our proposed method performs better in time-series process.