• Journal of The Korean Astronomical Society
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• v.49 no.5
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• pp.175-192
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• 2016

CCD photometric observations of the globular cluster (GC), M53 (NGC 5024), are performed using the 1.8 m telescope at the Bohyunsan Optical Astronomy Observatory in Korea on the same nights (2002 April and 2003 May) as the observations of the GC M92 (NGC 6341) reported by Cho and Lee using the same instrumental setup. The data for M53 is reduced using the same method as used for M92 by Cho and Lee, including preprocessing, point-spread function fitting photometry, and standardization etc. Therefore, M53 and M92 are on the same photometric system defined by Landolt, and the photometry of M53 and M92 is tied together as closely as possible. After complete photometric reduction, the V versus B − V , V versus V − I, and V versus B − I color-magnitude diagrams (CMDs) of M53 are produced to derive the relative ages of M53 and M92 and derive the various characteristics of its CMDs in future analysis. From the present analysis, the relative ages of M53 and M92 are derived using the Δ(B − V ) method reported by VandenBerg et al. The relative age of M53 is found to be 1.6 ± 0.85 Gyr younger than that of M92 if the absolute age of M92 is taken to be 14 Gyr. This relative age difference between M53 and M92 causes slight differences in the horizontal-branch morphology of these two GCs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1549-1557
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• 1999

In this paper, we propose a face recognition algorithm based on the differential image method-DCT This algorithm uses neural networks which is flexible for noise. Using the same condition (same luminous intensity and same distance from the fixed CCD camera to human face), we have captured two images. One doesn't contain human face. The other contains human face. Differential image method is used to separate the second image into face region and background region. After that, we have extracted square area from the face region, which is based on the edge distribution. This square region is used as the characteristics region of human face. It contains the eye bows, the eyes, the nose, and the mouth. After executing DCT for this square region, we have extracted the feature vectors. The feature vectors were normalized and used as the input vectors of the neural network. Simulation results show 100% recognition rate when face images were learned and 92.25% recognition rate when face images weren't learned for 30 persons.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.869-872
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• 2005

This research studied robust design of column part for LCD transfer system. $1^{st}$ DOE(Design of Experiment)was conducted to find out main effect factors. 36 experiments were performed and their results were shows that the geometric parameters(Low-length, Side-length, Upper-thickness, Middle-thickness)are more important than other factors. The main effect plots shows that the maximum deflection of column is minimized with increasing Low-length, Side-length, under-thickness and Middle-thickness. $2^{nd}$ DOE was conducted to obtain RMS(Response Surface Method)equation 25 experiments were conducted. The CCD(Central Composite Design)technique with four factors were used. The coefficient of determination $(R^2)$ for the calculated RSM equation was 0.986. Optimum design was conducted using the RSM equation Multi-island genetic algorithm was used to optimum design. Optimum value for Low-length. Side-length, Upper-thickness and Middle-thickness were 299.8mm, 180.3mm, 21.7mm, 21.9mm respectively. An approximate value of 5.054mm in deflection was expected to be a maximum under the optimum conditions. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the standard deviation of design parameter should be controlled within 2% of average design value.

• Earthquakes and Structures
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• v.17 no.5
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• pp.511-519
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• 2019

The concrete gravity dam is one of the most important parts of the nation's infrastructure. Besides the benefits, the dam also has some potentially catastrophic disasters related to the life of citizens directly. During the lifetime of service, some degradations in a dam may occur as consequences of operating conditions, environmental aspects and deterioration in materials from natural causes, especially from dynamic loads. Cumulative Absolute Velocity (CAV) plays a key role to assess the operational condition of a structure under seismic hazard. In previous researches, CAV is normally used in Nuclear Power Plant (NPP) fields, but there are no particular criteria or studies that have been made on dam structure. This paper presents a method to calculate the limitation of CAV for the Bohyeonsan Dam in Korea, where the critical Peak Ground Acceleration (PGA) is estimated from twelve sets of selected earthquakes based on High Confidence of Low Probability of Failure (HCLPF). HCLPF point denotes 5% damage probability with 95% confidence level in the fragility curve, and the corresponding PGA expresses the crucial acceleration of this dam. For determining the status of the dam, a 2D finite element model is simulated by ABAQUS. At first, the dam's parameters are optimized by the Minitab tool using the method of Central Composite Design (CCD) for increasing model reliability. Then the Response Surface Methodology (RSM) is used for updating the model and the optimization is implemented from the selected model parameters. Finally, the recorded response of the concrete gravity dam is compared against the results obtained from solving the numerical model for identifying the physical condition of the structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Computers and Concrete
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• v.30 no.6
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• pp.393-407
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• 2022

Due to the enormous cement content, pozzolanic materials, and the use of different aggregates, sustainable controlled low-strength material (CLSM) has a higher material cost than conventional concrete and sustainable construction issues. However, by selecting appropriate materials and formulations, as well as cement and aggregate content, whitethorn costs can be reduced while having a positive environmental impact. This research explores the desire to optimize plastic properties and 28-day unconfined compressive strength (UCS) of CLSM containing powder content from unprocessed-fly ash (u-FA) and recycled fine aggregate (RFA). The mixtures' input parameters consist of water-to-cementitious material ratio (W/CM), fly ash-to-cementitious materials (FA/CM), and paste volume percentage (PV%), while flowability, bleeding, segregation index, and 28-day UCS were the desired responses. The central composite design (CCD) notion was used to produce twenty CLSM mixes and was experimentally validated using MATLAB by an Artificial Neural Network (ANN). Variance analysis (ANOVA) was used for the determination of statistical models. Results revealed that the plastic properties of CLSM improve with the FA/CM rise when the strength declines for 28 days-with an increase in FA/CM, the diameter of the flowability and bleeding decreased. Meanwhile, the u-FA's rise strengthens the CLSM's segregation resistance and raises its strength over 28 days. Using calcareous powder as a substitute for cement has a detrimental effect on bleeding, and 28-day UCS increases segregation resistance. The response surface method (RSM) can establish high correlations between responses and the constituent materials of sustainable CLSM, and the optimal values of variables can be measured to achieve the desired response properties.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.293-299
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• 2023

The Wide-Angle Polarimetric Camera (PolCam) is installed on the Korea's lunar orbiter, Danuri, which launched on August 5, 2022. The mission objectives of PolCam are to construct photometric maps at a wavelength of 336 nm and polarization maps at 461 and 748 nm, with a phase angle range of 0°-135° and a spatial resolution of less than 100 m. PolCam is an imager using the push-broom method and has two cameras, Cam 1 and Cam 2, with a viewing angle of 45° to the right and left of the spacecraft's direction of orbit. We conducted performance tests in a laboratory setting before installing PolCam's flight model on the spacecraft. We analyzed the CCD's dark current, flat-field frame, spot size, and light flux. The dark current was obtained during thermal / vacuum test with various temperatures and the flat-field frame data was also obtained with an integrating sphere and tungsten light bulb. We describe the calibration method and results in this study.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of Life Science
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• v.21 no.8
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• pp.1083-1093
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• 2011

A microorganism utilizing rice hulls as a substrate for the production of carboxymethylcellulase (CMCase) was isolated from seawater and identified as Bacillus lincheniformis by analyses of its 16S rDNA sequences. The optimal carbon and nitrogen sources for production of CMCase were found to be rice hulls and ammonium nitrate. The optimal conditions for cell growth and the production of CMCase by B. lincheniformis LBH-52 were investigated using the response surface method (RSM). The analysis of variance (ANOVA) of results from central composite design (CCD) indicated that a highly significant factor ("probe>F" less than 0.0001) for cell growth was rice hulls, whereas those for production of CMCase were rice hulls and initial pH of the medium. The optimal conditions of rice hulls, ammonium nitrate, initial pH, and temperature for cell growth extracted by Design Expert Software were 48.7 g/l, 1.8 g/l, 6.6, and 35.7$^{\circ}C$, respectively, whereas those for the production of CMCase were 43.2 g/l, 1.1 g/l, 6.8, and 35.7$^{\circ}C$. The maximal production of CMCase by B. lincheniformis LBH-52 from rice hulls under optimized conditions was 79.6 U/ml in a 7 l bioreactor. In this study, rice hulls and ammonium nitrate were developed to be substrates for the production of CMCase by a newly isolated marine microorganism, and the time for production of CMCase was reduced to 3 days using a bacterial strain with submerged fermentation.