• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.29-36
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• 1999

The objective of this study is to analyse the flow field in the branching duct by visualizing the flow phenomena using the PIV system. A bifurcation model is fabricated with transparent acrylic resin to visualize the whole flow field with the PIV system. Water was used as the working fluid and the conifer powder as the tracer particles. The single-frame and two-frame methods of the PIV system and 2-frame of the grey level correlation method are applied to obtain the velocity vectors from the images captured in the flow filed. The velocity distributions in a lid-driven cavity flow are compared with the so-called standard experimental data, which was obtained from by 4-frame method in order to validate experimental results of the PIV measurements. The flow patterns of a Newtonian fluid in a branching duct were successfully visualized by using the PIV system and the sub-pixel and the area interpolation method were used to obtain the final velocity vectors. The velocity vectors obtained from the PIV system are in good agreement with the numerical results of the 3-dimensional branch flow. The results of numerical analyses and the PIV experiments for the three-dimensional flows in the branch ing duct show the recirculation zone distal to the branching point and the sizes of the recirculation length and height of the tow different methods are in good agreement.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.45-56
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• 2007

Direct estimation of the pollutant load(PL) should be carried out by the data filling in the missing intervals using an appropriate method because it is impossible in which the flow discharge(water quantity) or water quality(WQ) time-series data set have the missing intervals. In this study, the several methods estimating the water quality in the missing periods are suggested and the WQ and pollutants load change patterns are compared and evaluated based on the reproducible degree of the available data change patterns. The most appropriate method is finally suggested and the contribution factor deciding the influence degree and the PL characteristics of the river estuary is also suggested. Based on the PL estimation results using the several methods, the interpolation method considering the fluctuation of the available WQ data is shown to be most efficient. The PL patterns of the Han river estuary is classified as the discharge-dominated type. The data filling process is inevitable and the WQ estimation using the efficient and effective method should be carried out in order to estimate reasonable PL.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.270-285
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• 2005

A joint design scheme is proposed to optimize the up/down scaler and the motion vector estimation module in the transcoder system. The proposed scheme first optimizes the resolution scaler for a fixed motion vector, and then a new motion vector is estimated for the fixed scaler. These two steps are iteratively repeated until they reach a local optimum solution. In the optimization of the scaler, we derive an adaptive version of a cubic convolution interpolator to enlarge or reduce digital images by arbitrary scaling factors. The adaptation is performed at each macroblock of an image. In order to estimate the optimal motion vector, a temporary motion vector is composed from the given motion vectors. Then the motion vector is refined over a narrow search range. It is well-known that this refinement scheme provides the comparable performance compared to the full search method. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional systems. We can also see that the algorithms exhibit significant improvement in the minimization of information loss compared with other techniques.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.68-76
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• 2006

A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.94-101
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• 2008

Warming trends during winter seasons in East Asian regions are expected to accelerate in the future according to the climate projection by the Inter-governmental Panel on Climate Change (IPCC). Warmer winters may affect short-term cold hardiness of deciduous fruit trees, and yet phenological observations are scant compared to long-term climate records in the regions. Dormancy depth, which can be estimated by daily temperature, is expected to serve as a reasonable proxy for physiological tolerance of flowering buds to low temperature in winter. In order to delineate the geographical pattern of short-term cold hardiness in grapevines, a selected dormancy depth model was parameterized for "Campbell Early", the major cultivar in South Korea. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HDDTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations and a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and site elevation). To generate relevant datasets for climatological normal years in the future, we combined a 25km-resolution, 2011-2100 temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 scenario) with the 1971-2000 HD-DTM. The dormancy depth model was run with the gridded datasets to estimate geographical pattern of change in the cold-hardiness period (the number of days between endo- and forced dormancy release) across South Korea for the normal years (1971-2000, 2011-2040, 2041-2070, and 2071-2100). Results showed that the cold-hardiness zone with 60 days or longer cold-tolerant period would diminish from 58% of the total land area of South Korea in 1971-2000 to 40% in 2011-2040, 14% in 2041-2070, and less than 3% in 2071-2100. This method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.61-69
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• 2020

This study examined the braking characteristics of a heavy haul freight train with P4a distribution valves applied to domestic high-speed freight trains. A freight train was composed of 50 cars, which is twice the normal operation. A braking test was performed to confirm the characteristics of the braking of a heavy haul. The brake cylinder pressures were measured for emergency and service braking on the 1st, 10th, 20th, 30th, and 50th cars. Because the brake signal is transmitted to the pressure through the braking tube connected to the end of the train, the rear vehicle is braking later than the vehicle ahead. Therefore, it is necessary to predict the brake pressures in all cars in a train to supplement the results of the limited tests and calculate the braking distance. The pressure in each car was determined using empirical models of linear interpolation, stepwise, and exponential models, which provided reliable information. The predictive results of the empirical models were compared with the measured results, and the exponential model was predicted relatively accurately. These results are expected to contribute to the safe operation of heavy haul freight trains and can be used to predict the braking distance and calculate the level of impact between vehicles during braking.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.26-35
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• 2003

For the recognizing system to be classified the same or different images in the nature the rotation, scale and transition invariant features is to be necessary. There are many investigations to get the feature for the recognition system and the log-polar transform which is to be get the invariant feature for the scale and rotation is used. In this paper, we suggested the character recognition methods which are used the centroid method and the log-polar transform with the interpolation to get invariant features for the character recognition system and obtained the results of the above 50% differential ratio for the character features. And we obtained the about 90% recognition ratio from the suggested character recognition system using the BPEJTC which is used the invariant feature from the Mellin transform method for the reference image. and can be recognized the scaled and rotated input character. Therefore, we suggested the image character recognition system using the Mellin transform method and the BPEJTC is possible to recognize with the invariant feature for rotation scale and transition.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.