• Journal of the Korean Society of Safety
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• v.28 no.4
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• pp.26-32
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• 2013

A digital image correlation(DIC) method is a whole-field measurement technique that acquires surface displacements and strains from images information which characterized a random speckle as intensity grey levels. Recently years, this DIC method is being developed and used increasingly in various research. In this study, we tried to apply to aluminum alloy(Al 6061-T6) using DIC method and strain gauge. DIC results demonstrated the usefulness and ability to determine a strain. The test specimen used in this study was an aluminum alloy(Al 6061-T6, thickness 1 mm). For a strain measurement, a strain gauge was attached at the center of a specimen. A specimen was lightly sprayed with a white paint and a black dot pattern was sprayed on its fully dried white surface to obtain a random speckle. The experimental apparatus used to perform the tensile test consisted of universal dynamic tester(5 kN; T.O. Co.) under displacement speed of 0.5, 1.0 and 3.0 mm/min. A Model 5100 B Scanner(V. Co.) used to obtain a strain. A CCD camera connected to a PC uses to record the images of the specimen surface. After acquisition, the images were transferred to PC where the DIC software was implemented. An acquired image was evaluated by the DIC program. DIC method for displacement and strain was suggests and it results show a good consistent remarkably. DIC results demonstrated the usefulness and ability to determine surface strain was better than by using classical measurements. The strain field measurement using a DIC is so useful that it can be applied to map strain distributions at a full area. DIC method can evaluate a strain change so it can predict a location of fracture. The findings of the investigation suggest that the DIC method is an efficient and reliable tool for full-field monitoring and detailed damage characterization of materials.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.324-342
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• 2007

This study reports petrography and geochemical characteristics of the basalt lava flows in Seongsan-Ilchulbong area, the easternpart of Jeju island, Korea, to understand the evolutionary processes of magma. Basalt lavas are classified into the Pyoseon-ri basalt and the Seongsan-ri basalt. The Pyoseon-ri basalt is dark-gray colored with many vescicles, and mainly consists of olivine, feldspar and rarely of clinopyroxene as phenocrysts. The Seongsan-ri basalt is largely aphanitic basalt and bright-gray colored, divided into two lava-flow units: lower lava flow (B1) and upper lava flow (B2) by the intercalated yellowish lapillistone and paleosol. The lavas plotted into sub-alkaline tholeiitic basalt and alkaline basalt series. The tholeiitic basalts have characteristically higher $SiO_2,\;FeO^T$, and CaO contents, but lower $TiO_2,\;K_2O,\;P_2O_5$ and other incompatible elements compared to the alkali basalts. The tholeiitic basalts have higher $SiO_2$ to the same MgO contents than the alkalic basalts. The contents of Ni, Cr, and MgO show a strong positive correlation, which indicates that low-MgO phases like plagioclase and titanomagnetite were important during the differentiation of magma. The contents of incompatible elements against that of Th show a strong positive correlation. The chondrite-nomalized REE patterns of tholeiitic and alkalic basalts are subparallel each other. LREEs contents of the former are lower than, but HREEs contents are similar to the latter. They both are similar to their K/Ba ratios. The primitive-mantle normalized spider diagram demonstrates that the contents of Ba and Th of all basaltic magma are enriched, and yet Cr, Ni are depleted. The tholeiitic and alkalic basalts may be originated from a different degree of the partial melting of the same mantle material source, and one shows a higher degree of the partial melting than the other.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.1041-1050
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• 2001

Control of bone cement volume (PMMA) may be critical for preventing complications in vertebroplasty, the percutaneous injection of PMMA into vertebra. The purpose of this study was to predict the optimal volume of PMMA injection based on CT images. For this, correlation between PMMA volume and textural features of CT images was examined before and after surgery to evaluate the appropriate PMMA amount. The gray level run length analysis was used to determine the textural features of the trabecular bone. Extimation of PMMA volume was done using 3D visualization with semi-automatic segmentation on postoperative CT images. Then, finite element (FE) models were constructed based on the CT image data of patients and PMMA volume. Appropriate material properties for the trabecular bone were assigned by converting BMD to elastic modulus. Structural reinforcement due to the changes in PMMA volume and BMD was assessed in terms of axial displacement of the superior endplate. A strong correlation was found between the injected PMMA volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT images (r=0.90 and -0.90, respectively). FE results suggested that vertebroplasty could effectively reinforce the osteoporotic vertebra regardless of BMD or PMMA volume. Effectiveness of additional PMMA injection tended to decrease. For patients with BMD well lower than 50mg/ml, injection of up to 30% volume of the vertebral body is recommended. However, less than 30% is recommended otherwise to avoid any complications from excessive PMMA because the strength has already reached the normal level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.956-962
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• 2018

As the study of the object feature detection from image, we explain methods to identify the species of the tree in forest using the picture taken from dron. Generally there are three kinds of methods, which are GLCM (Gray Level Co-occurrence Matrix) and Gabor filters, in order to extract the object features. We proposed the object extraction method using the statistical properties of trees in this research because of the similarity of the leaves. After we extract the sample images from the original images, we detect the objects using cross correlation techniques between the original image and sample images. Through this experiment, we realized the mean value and standard deviation of the sample images is very important factor to identify the object. The analysis of the color component of the RGB model and HSV model is also used to identify the object.

• Journal of Microbiology and Biotechnology
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• v.8 no.5
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• pp.490-496
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• 1998

Random amplified polymorphic DNA (RAPD) markers were used to survey genetic variability among 34 Botrytis cinerea isolates from nine different host plants in Korea. For RAPD analysis, 115 arbitrary decamer primers were initially screened for polymorphic major DNA bands with 11 representative B. cinerea isolates. Eleven primers that initially detected polymorphisms were tested a second time with additional 23 isolates of B. cinerea as well as one isolate of Botrytis squamosa as an outgroup. The RAPD analyses revealed that all isolates except one showed different molecular phenotypes. Dendrograms obtained from dissimilarity matrices using the unweighted paired group method of arithmetic means (UPGMA) showed the 36.4% to 90.0% similarity among all B. cinerea isolates. The B. squamosa isolate showed the least similarity to all B. cinerea isolates. The cluster analyses indicated no correlation among all the characteristics examined including molecular phenotypes, host and geographic origins, year of isolation, or pathogenicity. The RAPD data suggest that a high level of genetic variation exists among Korean populations of B. cinerea and it seems to be caused by heterokaryosis among preexisting molecular phenotypes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.18-18
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• 1996

This paper reviews some of the most prominent and promising areas of chemical process control both in relations to batch and continuous processes. These areas include the modeling, optimization, control and monitoring of chemical processes and entire plants. Most of these areas explicitly utilize a model of the process. For this purpose the types of models used are examined in some detail. These types of models are categorized in knowledge-driven and datadriven classes. In the areas of modeling and optimization, attention is paid to batch reactors using the Tendency Modeling approach. These Tendency models consist of data- and knowledge-driven components and are often called Gray or Hybrid models. In the case of continuous processes, emphasis is placed in the closed-loop identification of a state space model and their use in Model Predictive Control nonlinear processes, such as the Fluidized Catalytic Cracking process. The effective monitoring of multivariate process is examined through the use of statistical charts obtained by the use of Principal Component Analysis (PMC). Static and dynamic charts account for the cross and auto-correlation of the substantial number of variables measured on-line. Centralized and de-centralized chart also aim in isolating the source of process disturbances so that they can be eliminated. Even though significant progress has been made during the last decade, the challenges for the next ten years are substantial. Present progress is strongly influenced by the economical benefits industry is deriving from the use of these advanced techniques. Future progress will be further catalyzed from the harmonious collaboration of University and Industrial researchers.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.922-930
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• 2004

An experimental investigation was performed to study on the generation of air bubble and air core with swirling flow in a horizontal cicular tube. To determine some characteristics of the flow, 2D PIV technique is employed for velocity measurement in water. The experimental rig is manufactured from an acryl tube. The test tube diameter of 80mm, and a length of 3000mm. The used algorithm is the gray leve cross-correlation method(Kimura et al. 1986). An Ar-ion laser is used and the light from the laser(500mW) passes through a probe to make two-dimensional light sheet. In order to make coded images of the tracer particles on one frame, an AOM(Acoustic-Optical Modulator) is used. The maximum axial velocities showed near the test tube wall at y/D =0.1 and y/D =0.9 along the test tube. The higher Reynolds number increase, the lower axial velocities are showed in the center of the test tube. The air bubbles are generated from Re =10,000 and developed into air core from the recirculating water pump rpm equal 30Hz. The pressure and temperature are measured across the test tube at X/D=3.33.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.487-494
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• 2013

Medical image watermarking has received extensive attention as wide security services in the healthcare information system. This paper proposes a blind medical image watermarking approach on the segmented gray-matter (GM) images by utilizing discrete wavelet transform (DWT) and discrete cosine transform (DCT) along with enhanced suppressed fuzzy C-means (EnSFCM) for the optimal selection of sub-blocks position to insert a watermark. Experimental results show that the proposed approach outperforms other methods in terms of peak signal to noise ratio (PSNR) and M-SVD. In addition, the proposed approach shows better robustness than other methods in normalized correlation (NC) values against several attacks, such as noise addition, filtering, JPEG compression, blurring, histogram equalization, and cropping.