• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.756-759
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• 2005

Dynamic force microscopy utilizes the dynamic response of a resonating probe tip as it approaches and retracts from a sample to measure the topography and material properties of a nanostructure. We present recent ideas based on proper orthogonal decomposition (POD) and detailed experiments that yield new perspectives and insight into AFM. A dynamic cantilever model with Lennrad-Jones interaction Potential which includes attractive and repulsive van der Waals demonstrates the resonable tapping mode response in time and frequency.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.371-377
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• 2021

This research proposes the best combination of tropospheric delay models for Korean Positioning System (KPS). The overall results are based on real observation data of Japanese Quasi-Zenith satellite system (QZSS), whose constellation is similar to the proposed constellation of KPS. The tropospheric delay models are constructed as the combinations of three types of zenith path delay (ZPD) models and four types of mapping functions (MFs). Two sets of International GNSS Service (IGS) stations with the same receiver are considered. Comparison of observation residuals reveals that the ZPD models are more influential to the measurement model rather than MFs, and that the best tropospheric delay model is the combination of GPT3 with 5 degrees grid and Vienna Mapping Function 1 (VMF1). While the bias of observation residual depends on the receivers, it still remains to be further analyzed.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.2
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• pp.53-64
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• 2017

Purpose: To evaluate the usefulness of the $HexaPOD^{TM}$ evo RT system(6DoF couch) and the tendency of dose difference according to size of rotational direction error for volumetric rotational modulated radiotherapy(V-MAT) in patients with long target lengths. Therefore, it is suggested to recommend the need for rotational error correction. Materials and Methods: Ten patients with Esophagus cancer or Breast cancer including SCL treated with HexaPOD 6DoF(Six-Degree of Freedom) couch were included in this study. 6DoF couch was used to measure the difference in dose according to the rotation error in the directions of Rx(pitch), Ry(roll), and Rz(yaw). Each rotation error was applied. Positioning variation on x, y and z axis was verified and random variations were made by 6DoF couch with positioning variation. Modified DQA is conducted and point dose and gamma value are analyzed and compared. In addition, after applying the rotation error every $1^{\circ}$ to treatment plans of each target with a diameter of 3 cm, 5, 10, 15, and 20 cm respectively, gamma passing rate is being monitored by its aspect of change according to types and sizes of the target length and rotation error. Results: Mean error of the point dose and Gamma passing rate when the position variation was applied were $2.50{\pm}1.11%$ and $84.1{\pm}7.39%$ in the Rx direction, $2.36{\pm}1.16%$, and $81.0{\pm}8.49%$ in the Ry, $2.35{\pm}1.10%$ and $84.4{\pm}6.99%$ in the Rz direction, respectively. As a result of analysis on gamma passing rate according to types and sizes of the target length and rotation error, the gamma passing rate tended to decrease with increasing rotation error in the Rx and Rz directions except Ry direction. In particular, the lowest gamma passing rate (74.2 %) was in the case of $2.5^{\circ}$ rotation error in Rz direction of the target of 10 cm. Conclusion: The correction of the rotational error is needed for volumetric modulated radiotherapy of the treatment area with a long target length, and the use of 6DoF couch will improve the reproducibility of the patient position and the quality of the treatment.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.71-76
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• 2009

The research to predict the resistance performance of the ship using the CFD analysis is increasing. For the CFD numerical analysis the computational mesh, which is proper to computational model, has to be made before the analysis is begun. In the parametric study, even though the deformation of each case is not very sharp, the whole computational mesh should be regenerated according to the conventional way. Hence, lots of effort is needed to repeated mesh generation work. To solve these problems, the automatic mesh generation method using the macro function of commercial CAD program and mesh generation program is introduced in this study. First, in the CAD program, by using the macro function and putting the deformation rate of bow and stern in lengthwise, the repeated modeling work is performed automatically. Next, the generated geometries are read by the mesh generation program and the proper mesh for the geometry is created automatically also using the macro function. The hybrid mesh which has unstructured grid near the bow and stern and structured grid in the remaining part of domain is used. The verification of the developed method is done by applying the method to predict the resistance performance of the podded propulsion cruise ship of the Daewoo Shipbuilding & Marine Engineering (DSME) in the cases of different length of bow and stern and pod set in different position. The author believes that the introduced method can help to make the database to optimize the resistance performance of the ship in various cases can be constructed without difficulty.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1414-1424
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• 2021

In this paper, the importance of input factors of a DNN (Deep Neural Network) PM_2.5 forecasting model using LRP(Layer-wise Relevance Propagation) is analyzed, and forecasting performance is improved. Input factor importance analysis is performed by dividing the learning data into time and PM_2.5 concentration. As a result, in the low concentration patterns, the importance of weather factors such as temperature, atmospheric pressure, and solar radiation is high, and in the high concentration patterns, the importance of air quality factors such as PM_2.5, CO, and NO₂ is high. As a result of analysis by time, the importance of the measurement factors is high in the case of the forecast for the day, and the importance of the forecast factors increases in the forecast for tomorrow and the day after tomorrow. In addition, date, temperature, humidity, and atmospheric pressure all show high importance regardless of time and concentration. Based on the importance of these factors, the LRP_DNN prediction model is developed. As a result, the ACC(accuracy) and POD(probability of detection) are improved by up to 5%, and the FAR(false alarm rate) is improved by up to 9% compared to the previous DNN model.

• Wind and Structures
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• v.38 no.5
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• pp.381-398
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• 2024

This study presents a mode analysis of 3D turbulent velocity data around a square-section building model to identify the dynamic system for Kármán-type vortex shedding. Proper orthogonal decomposition (POD) was first performed to extract the significant 3D modes. Magnitude-squared coherence was then applied to detect the phase consistency between the modes, which were roughly divided into three groups. Group 1 (modes 1-4) depicted the main vortex shedding on the wake of the building, with mode 2 being controlled by the inflow fluctuation. Group 2 exhibited complex wake vortexes and single-sided vortex phenomena, while Group 3 exhibited more complicated phenomena, including flow separation. Subsequently, a third-order polynomial regression model was used to fit the dynamics system of modes 1, 3, and 4, which revealed average trend of the state trajectory. The two limit cycles of the regression model depicted the two rotation directions of Kármán-type vortex. Furthermore, two characteristic periods were identified from the trajectory generated by the regression model, which indicates fast and slow motions of the wake vortex. This study provides valuable insights into 3D mode morphology and dynamics of Kármán-type vortex shedding that helps to improve design and efficiency of structures in turbulent flow.

• Smart Structures and Systems
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• v.25 no.2
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• Journal of Pharmaceutical Investigation
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• v.40 no.1
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• pp.45-49
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• 2010

Unlike human, with some exceptions, animals do not heal with excessive scar. The lack of suitable animal model has hindered the development of effective scar therapy. We previously reported that partial thickness rabbit ear wound model resembles human wound heal process. This study was designed to prepare a hypertropic scar wound model which can be employed for testing anti-scar therapy. Four wounds were created down to the bare cartilage on the anterior side of each rabbit ear using 8-mm dermal biopsy punch and histology analysis at post operation day (POD) 5, 28 and 48 were performed. As the outcome of scar formation is largely determined by the early inflammatory response to the wounding and the degree and the duration of occlusion, cephalodin(50 mg/kg) was injected daily and medical occlusive dressings were applied. Five micro wound and scar sections were stained with hematoxylin and eosin for quantification of epidermal regeneration and scar hypertrophy. Sections were also stained using Masson's trichrome and Sirius red to evaluate collagen organization and rete ridge formation. Wound closure process was assessed to 7wks post wounding. Complete removal of the epidermis, dermis and perichondrial layer caused delayed epithelialization, which results in hypertropic scarring. The inability of the wounds to contract and the delay in epithelialization in rabbit ear was likely due to cartilage and it created scar elevation. The results suggest that full thickness surgical punch wound model in rabbit ear could be employed as a reliable and reproducible scar wound model for testing anti-scar therapy.

• Journal of Conservation Science
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• v.37 no.1
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• pp.13-24
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• 2021

Safflower, a natural dye representing red, is the dye that materials and dyeing method are recorded in the literature, including materials and dyeing. Although the safflower is the same, the ash used as a mordant is recorded differently in each literature, which greatly affects the aesthetic perspective in realizing the traditional safflower red. Therefore, the optimal conditions for realizing the traditional safflower red were sought. The experiment was conducted by pH investigation, dyeing and color analysis by dyeing solution water, concentration, and temperature by ash, and the unique color of red was confirmed. As a result of the test, the pH point of time when the uniq ue color was expressed was 11.53 as goosefoot ash (natural bedrock water), which was 1:100 for concentration and 70℃ for temperature, which was easier to extract red pigment than other ash, indicating that it is suitable for safflower dyeing. The analysis of the ash showed that K and Si play an important role in dyeing, especially Si, which is an element that inhibits carthamon. The color of red was similar to that of KS Standard vivid purplish red in the ash of the goosefoot, and the other ash was deep purplish pink. In the light of findings, it was possible to quantify the dyeing method through traditional materials and find the standard color of red color, and it is judged to be a basic data for studying the unique color of natural materials.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.527-544
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• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.