• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.3
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• pp.146-151
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• 2018

In this study, we compared the threshold-voltage extraction methods of accumulation-type JLDG (junctionless double-gate) MOSFETs (metal-oxide semiconductor field-effect transistors). Threshold voltage is the most basic element of transistor design; therefore, accurate threshold-voltage extraction is the most important factor in integrated-circuit design. For this purpose, analytical potential distributions were obtained and diffusion-drift current equations for these potential distributions were used. There are the ${\phi}_{min}$ method, based on the physical concept; the linear extrapolation method; and the second and third derivative method from the $I_d-V_g$ relation. We observed that the threshold-voltages extracted using the maximum value of TD (third derivatives) and the ${\phi}_{min}$ method were the most reasonable in JLDG MOSFETs. In the case of 20 nm channel length or more, similar results were obtained for other methods, except for the linear extrapolation method. However, when the channel length is below 20 nm, only the ${\phi}_{min}$ method and the TD method reflected the short-channel effect.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.265-275
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• 2015

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.10
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• pp.1465-1469
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• 2001

A sensitive high-performance liquid chromatographic method was developed to determine the content of cholesterol in milk and dairy products. To optimize separation of cholesterol, mobile phases including acetonitrile:2-propanol (8:1, v/v), acetonitrile:methanol (3:1, v/v), and acetonitrile:methanoI:2-propanol (7:3: I, v/v/v) were compared. Acetonitrile/methanol/2-propanol was superior to the other mobile phase systems for separating cholesterol. Liquid-liquid extraction (LLE) of cholesterol was simplified using a non-polar solvent, hexane, to remove interfering compounds, and had an excellent recovery $(100{\pm}1.0%)$ of cholesterol. A solid phase extraction (SPE) method using Sep-pak $C_{18}$ was developed and compared with LLE. The SPE method was rapid and highly reproducible. Both extraction methods were useful when used in combination with saponification of esterified cholesterol to facilitate total cholesterol determination. The detection limit of cholesterol was $0.01{\mu}g$. The newly developed HPLC method was rapid, simple, and accurate, and has advantages over the many methods commonly used.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.131-139
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• 2013

Support vector machines(SVM) may perform poorly in the presence of noise variables; in addition, it is difficult to identify the importance of each variable in the resulting classifier. A feature selection can improve the interpretability and the accuracy of SVM. Most existing studies concern feature selection in the linear SVM through penalty functions yielding sparse solutions. Note that one usually adopts nonlinear kernels for the accuracy of classification in practice. Hence feature selection is still desirable for nonlinear SVMs. In this paper, we compare the performances of nonlinear feature selection methods such as component selection and smoothing operator(COSSO) and kernel iterative feature extraction(KNIFE) on simulated and real data sets.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.242-246
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• 2006

Background level of heavy metals In soils (316 points by 15 classifications of land use) was investigated by two test methods, 0.1N HCl(1N HCl for As) extraction and aqua regia extraction methods. The average concentrations of aqua regia extractable heavy metals in soil(n=316) was 6.24(As), 0.25(Cd), 37.99(Cr), 24.10(Cu), 0.04(Hg), 25.68(Pb), 22.59(Ni), 106.11(Zn) mg/kg, respectively. Also the average concentrations of 0.1N HCl extractable heavy metals was 0.06(As), 0.08(Cd), 0.27(Cr), 3.78(Cu), 4.02(Pb), 12.5(Zn), 0.58(Ni) mg/kg, respectively. The ratio of soluble contents and total contents were 2.6%(As), 32.7%(Cd), 0.7%(Cr), 15.7%(Cu), 15.7%(Pb), 2.6%(Ni), 11.8%(Zn), and the correlation coefficient of soluble contents and total contents were 0.26(As), 0.27(Cd), 0.22(Cr), 0.57(Cu), 0.42(Pb), 0.23(Ni), 0.72(Zn).

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.359-367
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• 2011

A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.42-48
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• 2000

In this paper, we propose the face image recognition algorithm using skin color information, face region features such as eye, nose, and mouse, etc., and geometrical features of chin line. In the proposed algorithm, we used the intensity as well as skin color information in the HSI color coordinate which is similar to human eye system. The experimental results of proposed method shows improved extraction quality of face and provides adaptive extraction methods for the races. And also, we used chin line information as well as geometrical features of face such as eye, nose, mouse information for the improvement of face recognition quality, Experimental results shows the more improved recognition as well as extraction quality than conventional methods.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.1 s.232
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• pp.123-130
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• 2005

A digital in-line holographic particle image velocimetry (HPIV) which can be applied to measure three-dimensional velocity fields of turbulent flows was developed. There are three different implementation methods of HPIV: traditional film-based HPIV, intermediate HPIV and digital HPIV. The traditional film-based HPIV and intermediate HPIV method is rather troublesome to do experiments and takes long calculation time, compared with the digital HPIV, Configuration of the digital in-line HPIV is simple and the data processing routine is similar to conventional 2D PIV methods. The digital HPIV velocity field measurement consists of four steps: recording, numerical reconstruction, particle extraction and velocity extraction. In the velocity extraction process, we improved PTV algorithm to extract the displacement of particle each placed in 3D space. The developed digital in-line HPIV system was applied to a vertical jet flow. The 3D velocity vectors measured by the digital HPIV method in the near field are in a good agreement with 2D PIV results.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.365-373
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• 1997

In this paper, a new method of the 3D(dimensional) image reconstruction is proposed to build up the 3D image from 2D images using digital image processing techniques and computer graphics. First, the new feature extraction algorithm that doesn't need various input parameters and is not affected by threshold is adopted This new algorithm extracts feature points by eliminating some undesirable points on the ground of the connectivity. Second, as the cast function to reconstruct surfaces using extracted feature points, the minimum distance measure between two plane images has been adopted According to this measure, the surface formation algorithm doesn't need complex calculation and takes the form of triangle or trapezoid To investigate usefulness, this approach has been applied to a head CT image and compared with other methods. Experimental comparisons show that the suggested algorithm yields better performance on feature extraction than others. In contrast with the other methods, the complex calculation for surface formation in the proposed algorithm is not necessary.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.43-49
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• 2016

This paper presents the design and implementation of virtual aquarium by generating 3D models of fishes that are colored by viewers in an aim to create interaction among viewers and aquarium. The virtual aquarium system is composed of multiple texture extraction modules, a single interface module and a single display module. The texture extraction module recognize the QR code on the canvas to get information of the predefined mapping table and then extract the texture data for the corresponding 3D model. The scanned image is segmented and warp transformed onto the texture image by using the mapping information. The extracted texture is transferred to the interface module to save on the server computer and the interface module sends the fish code and texture information to the display module. The display module generates a fish on the virtual aquarium by using predefined 3D model with the transmitted texture. The fishes on the virtual aquarium have three different swimming methods: self-swimming, autonomous swimming, and leader-following swimming. The three different swimming methods are discussed in this paper. The future study will be the implementation of virtual aquarium based on storytelling to further increase interactions with the viewer.