• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.265-272
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• 2007

This proposed gamma (${\gamma}$) correction system is developed to reduce the difference between non-linear gamma curve produced by a typical formula and result produced by the proposed algorithm. In order to reduce the difference, the proposed system is using the Least Squares Polynomial which is calculating the best fitting polynomial through a set of points which is sampled. Each system is consisting of continuous several kinds of equations and having their own overlap sections to get more precise. Based on the algorithm verified by MATLAB, the proposed systems are implemented by using Verilog-HDL. This paper will compare the previous algorithm of gamma system such as Existing system with Seed Table with the latest that such as Proposed system. The former and the latter system have 1, 2 clock latency; each 1 result per clock. Because each of the error range (LSB) is $1{\sim}+1,\;0{\sim}+36$, we can how that Proposed system is improved. Under the condition of SAMSUNG STD90 0.35 worst case, each gate count is 2,063, 2,564 gates and each maximum data arrival time is 29.05[ns], 17.52[ns], respectively.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.189-207
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• 2010

Several ocean color algorithms have been developed for GOCI (Geostationary Ocean Color Imager) using in-situ bio-optical data sets. These data sets collected around the Korean Peninsula between 1998 and 2009 include chlorophyll-a concentration (Chl-a), suspended sediment concentration (SS), absorption coefficient of dissolved organic matter ($a_{dom}$), and remote sensing reflectance ($R_{rs}$) obtained from 1348 points. The GOCI Chl-a algorithm was developed using a 4-band remote sensing reflectance ratio that account for the influence of suspended sediment and dissolved organic matter. The GOCI Chl-a algorithm reproduced in-situ chlorophyll concentration better than the other algorithms. In the SeaWiFS images, this algorithm reduced an average error of 46 % in chlorophyll concentration retrieved by standard chlorophyll algorithms of SeaWiFS. For the GOCI SS algorithm, a single band was used (Ahn et al., 2001) instead of a band ratio that is commonly used in chlorophyll algorithms. The GOCI $a_{dom}$ algorithm was derived from the relationship between remote sensing reflectance band ratio ($R_{rs}(412)/R_{rs}(555)$) and $a_{dom}(\lambda)$). The GOCI Chl-a fluorescence and GOCI red tide algorithms were developed by Ahn and Shanmugam (2007) and Ahn and Shanmugam (2006), respectively. If the launch of GOCI in June 2010 is successful, then the developed algorithms will be analyzed in the GOCI CAL/VAL processes, and improved by incorporating more data sets of the ocean optical properties data that will be obtained from waters around the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.1-8
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• 1999

The estimation technique of surface water temperature by satellite remote sensing has been applied to ocean and large lakes using AVHRR. However, the spatial resolution AVHBR is not abquate for coastal region and small lakes. Landsat 5 TM has 120 m spatial resolution, which suits better. We carried out analysis of surface water temperature in Lake Sihwa and near coastal area using Landsat 5 TM. To relate digital number to the brightness temperature, we applied Empirical, NASA, RESTEC, Quadratic methods. Comparing calculated and observed value, we obtained as follows; NASA method, $R^2=0.9343$, RMSE(Root Mean Square Error)=3.5876$^{\circ}C$; RESTEC method, $R^2=0.8937$, RMSE=3.76$^{\circ}C$; Quadratic method, $R^2=0.8967$, RMSE=2.949$^{\circ}C$. Because Landsat TM has only one band for extracting surface temperature, it was difficult to correct for the atmospheric errors. For improving the accuracy of surface temperature detection using Landsat TM, there is a need for a method to decrease the effect of atmospheric contents.

• Geophysics and Geophysical Exploration
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• v.6 no.4
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• pp.171-179
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• 2003

In land and marine seismic survey, we generally set receivers with equal interval suppose that sampling interval Is too narrow. But the cost of seismic data acquisition and that of data processing are much higher, therefore we should design proper receiver interval. Spatial aliasing can be occurred on seismic data when sampling interval is too coarse. If we Process spatial aliasing data, we can not obtain a good imaging result. Trace interpolation is used to improve the quality of multichannel seismic data processing. In this study, we applied the Spitz algorithm which is widely used in seismic data processing. This algorithm works well regardless of dip information of the complex underground structure. Using prediction filter and original traces with linear event we interpolated in f-x domain. We confirm our algorithm by examining for some synthetic data and marine data. After interpolation, we could find that receiver intervals get more narrow and the number of receiver is increased. We also could see that continuity of traces is more linear than before Applying this interpolation algorithm on seismic data with spatial aliasing, we may obtain a better migration imaging.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.861-867
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• 2021

Since SBRT takes up to 1 hour from 30 minutes to treatment fraction once or three to five times, there is a possibility of setup error during treatment. To reduce these set-up errors and give accurate doses, we intend to evaluate the usefulness of pre-treatment and post-treatment error values by imaging CBCT again to determine postural movement due to pre-treatment coordinate values using pre-treatment CBCT. On average, the range of systematic errors was 0.032 to 0.17 on the X and Y,Z axes, confirming that there was very little change in movement even after treatment. Tumor centripetal changes (±SD) due to respiratory tuning were 0.11 (±0.12) cm, 0.27 (±0.15) cm, and 0.21 cm (±0.31 cm) in the X, Y and Z directions. The tumor edges ±SD were 0.21 (±0.18) cm, 0.30 (±0.23) cm, and 0.19 cm (±0.26) cm in the X, Y and Z directions. The (±SD) of tumor-corrected displacements were 0.03 (±0.16) cm, 0.05 (±0.26) cm, and 0.02 (±0.23) cm in RL, AP, and SI directions, respectively. The range of the 3D vector value was 0.11 to 0-.18 cm on average when comparing pre-treatment and CBCT, and it was confirmed that the corrected set-up error was within 0.3 cm. Therefore, it was confirmed that there were some changes in values depending on some older patients, condition on the day of treatment, and body type, but they were within the significance range.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.701-714
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• 2018

The purpose of this study is to show the possibility of 3-dimensional modeling of open-pit limestone mine by using a rotary-wing unmanned aerial vehicle, a drone, and to estimate the amount of mining before and after mining of limestone by explosive blasting. Analysis of the image duplication of the mine has shown that it is possible to achieve high image quality. Analysis of each axis error at the shooting position after analyzing the distortions through camera calibration was shown the allowable range. As a result of estimating the amount of mining before and after explosive blasting, it was possible to estimate the amount of mining of a wide range quickly and accurately in a relatively short time. In conclusion, it is considered that the drone of a rotary-wing unmanned aerial vehicle can be usefully used for the monitoring of open-pit limestone mines and the estimation of the amount of mining. Furthermore, it is expected that this method will be utilized for periodic monitoring of construction sites and road slopes as well as open-pit mines in the future.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.73-83
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• 2020

Purpose: The purpose of this study is to confirm the matching of the electron density between tissue and gas due to variation of abdominal gas volume in MRgART (Magnetic Resonance-guided Adaptive Radiation Therapy) for pancreatic cancer patients, and to confirm the effect on the dose change and treatment time. Materials and Methods: We compared the PTV and OAR doses of the initial plan and the AGC(Abdominal gas correction) plans to one pancreatic cancer patient who treated with MRgART using the ViewRay MRIdian System (Viewray, USA) at this clinic. In the 4fx AGC plans, Beam ON(%) according to the patient's motion error was checked to confirm the effect of abdominal gas volume on treatment time. Results: Comparing the Initial plan with the average value of AGC plan, the dose difference was -7 to 0.1% in OAR and decreased by 0.16% on average, and in PTV, the dose decreased by 4.5% to 5.5% and decreased by 5.1% on average. In Adaptive treatment, as the abdominal gas volume increased, the Beam ON(%) decreased. Conclusion: Abdominal gas volume variation causes dose change due to inaccurate electron density matching between tissue and gas. In addition, if the abdominal gas volume increases, the Beam ON(%) decreases, and the treatment time may increase due to the motion error of the patient. Therefore, in MRgART, it is necessary to check the electron density matching and minimize the variability of the abdominal gas.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.269-282
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• 2021

As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1049-1057
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• 2020

This study aimed to develop a flow measurement method using drone in flood season. Measuring flow in all branches is difficult to conduct annually due to budget and labor limitation, safety and river works. Especially when heavy rain like storm comes, changes in stage-discharge relationship should be reviewed; however, it is usually impeded by the aforementioned issues. To solve the problem, it developed a simple measuring method with a minimum of labor and time. A numeric map and numeric orthophoto coordinate of South Korea are mostly based on Transverse Mercator Projection (TM) in accordance with rectangular coordinate system and use World Geodetic Reference System 1980 (GRS80) oval figure for conversion. Applying a concept of aerial photogrammetry, it located four visible Ground Control Points (GCP) near the river at Uijeongbu-si (Singok Bridge) and Yeongdong-gun (Youngdong 2nd Bridge) station and measured the coordinates using VRS DGPS. Hovering at a same level, drones took orthophoto of water surface at an interval of 3 seconds. It defined the pictures with GRS80 TM coordinate system, a rectangular coordinate system and then conducted an orthometric correction using GCP coordinates. According to X and Y coordinate analysis, it estimated the distance between the floating positions at 3 seconds-intervals and calculated the flow through the flow area according to the flow path. This study attested applicability of the flow measurement method using drone in flood season by applying the rectangular coordinate system based on the concept of aerial photogrammetry.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.119-125
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• 2022

With the recent increase in dementia patients due to aging, measures to prevent their wandering behavior and disappearance are urgently needed. To solve this problem, various authentication methods and location detection techniques have been introduced, but the security problem of personal authentication and a system that can check indoor and outdoor overall was lacking. In order to solve this problem, various authentication methods and location detection techniques have been introduced, but it was difficult to find a system that can check the security problem of personal authentication and indoor/outdoor overall. In this study, we intend to propose a system that can identify personal authentication, basic health status, and overall location indoors and outdoors by using wristband-type wearable devices in a private blockchain environment. In this system, personal authentication uses ECG, which is difficult to forge and highly personally identifiable, Bluetooth beacon that is easy to use with low power, non-contact and automatic transmission and reception indoors, and DGPS that corrects the pseudorange error of GPS satellites outdoors. It is intended to detect wandering behavior and abnormal signs by locating the patient. Through this, it is intended to contribute to the prompt response and prevention of disappearance in case of wandering behavior and abnormal symptoms of dementia patients living at home or in nursing homes.