• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.36-39
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• 2000

A small electrical potential difference which appears on any solid body when subjected to illumination by a modulated light beam generated by laser is called photocharge voltage(PCV)[1,2]. This voltage is proportional to the induced change in the surface electrical charge and is capacitatively measured on various materials such as conductors, semiconductors, ceramics, dielectrics and biological objects. The amplitude of the detected signal depends on the type of material under investigation, and on the surface properties of the sample. In photocharge voltage spectroscopy measurements[3], the sample is illuminated by both a steady state monochromatic bias light and the pulsed laser. The monochromatic light is used to created a variation in the steady state population of trap levels in the surface and space charge region of semiconductor samples which does result in a change in the measured voltage. Using this technique the spatial variation of PCV can be utilized to evalulate the surface conditions of the sample and the variation of the PCV due to the monochromatic bias light are utilized to charactrize the surface states. A qualitative analysis of the proposed measuremen is present along with experimental results performed on amorphous silicon samples. The deposition temperature was varied in order to obtain samples with different structural, optical and electronic properties and measurements are related to the defect density in amorphous thin film.

• Applied Science and Convergence Technology
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• v.24 no.1
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• pp.22-26
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• 2015

The optical properties of InP/GaP short-period superlattice (SPS) structures grown at various temperatures from $400^{\circ}C$ to $490^{\circ}C$ have been investigated by using temperature-dependent photoluminescence (PL) and emission wavelength-dependent time-resolved PL measurements. The PL peak energy for SPS samples decreases as the growth temperature increases. The decreased PL energy of ~10 meV for the sample grown at $425^{\circ}C$ compared to that for $400^{\circ}C$-grown sample is due to the CuPt-B type ordering, while the SPS samples grown at $460^{\circ}C$ and $490^{\circ}C$ exhibit the significant reduction of the PL peak energies due to the combined effects of the formation of lateral composition modulation (LCM) and CuPt-B type ordering. The SPS samples with LCM structure show the enhanced carrier lifetime due to the spatial separation of carriers. This study represents that the bandgap energy of InP/GaP SPS structures can be controlled by varying growth temperature, leading to LCM formation and CuPt-B type ordering.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.77-84
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• 2003

Recent advances in remote sensing techniques provide the potential for monitoring soil color as well as soil moisture conditions at the spatial and temporal scales required for detailed local modeling efforts. Soil moisture as well as soil color is a key feature used in the identification and classification of soils. Soil spectral reflectance has a direct relationship with soil color, as well as to other parameters such as soil moisture, soil texture. and organic matter. We evaluate the influence of seven soil properties, soil color and soil moisture, on soil spectral reflectance. This paper presents the results obtained from the ground-truth spectral reflectance measurements in the 300-1100 nm wavelength range for various land surfaces. The results suggest that the reflectance properties of soils are related to soil color, soil texture, and soil moisture. Increasing soil moisture content generally decreases soil reflectance which leads to parallel curves of soil reflectance spectra across the entire shortwave spectrum. We discuss the relationships between the soil reflectance and the Munsell Soil Color Charts which contain standard color chips with colors specified by designations for hue, value, and chroma.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.429-435
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• 2003

In this paper, we propose improved binary tree vector quantization with consideration of spatial sensitivity which is one of the human visual properties. We combine weights in consideration with the responsibility of human visual system according to changes of three primary color in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. Also we propose the novel quality measure of the quantization images that applies MTF(modulation transfer function) to luminance value of quantization error of color image. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get less quantized level images and can reduce the resource occupied by the quantized image.

• Journal of Broadcast Engineering
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• v.6 no.2
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• pp.160-168
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• 2001

In this paper, we propose a new practical motion model that can exploit the general properties of camera motion in constructing a panorama. accounting for panning. tilting, and evert the change in focal length of the camera. We also present an efficient algorithm to handle moving objects or noose in the scene based on outliers rejection. Spatial and temporal statistical properties of motion field are exploited to detect the outliers. The proposed algorithm removes moving objects or noise from the panoramic Image so that mode clear and complete view of the background Image can be obtained. This method does not require assumptions or a priors knowledge of the scene. The entire process is fully automatic as this method does not require any manual correction in the process of constructing a Panorama. The proposed algorithm is tested on the broadcasting images of soccer games. Oun simulation result shows that this method is superior to conventional image mosaicing algorithms.

• Journal of Magnetics
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• v.11 no.4
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• pp.182-188
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• 2006

The search for high-density recording materials has been one of most active and vigorous field in the field of magnetism. $FePt-L1_{0}$ nanoparticle has emerged as a potential candidate because of its high anisotropy. In this paper, we provide an overview of recent work at Argonne National Laboratory that contributes to the ongoing dialogue concerning the relation between structure and properties of the FePt nanoparticle system. In particular we discuss the ability to control structure and properties via dosing with Cr. Cr-dosed FePt films were grown via molecular beam epitaxy and annealed at $550^{\circ}C$ in an ultrahigh vacuum chamber, and were studied with the surface magneto-optic Kerr effect (SMOKE), scanning electron microscopy (SEM) and x-ray magnetic circular dichroism (XMCD). We found that small dosage of Cr helps to generate $L1_{0}$ phase FePt magnetic nanoparticles with small size, defined shape and regular spatial distribution on MgO (001) substrate. The nanostructures are ferromagnetic with high magnetic coercivity (${\sim}0.9T$) and magnetic easy axis in the desired out-of-plane orientation. We also show that controlling the lateral region where nanostructures exist is possible via artificial patterning with Cr.

• Journal of the Korean housing association
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• v.17 no.5
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• pp.107-116
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• 2006

This study was to figure out the design characteristics of court housing type for the purpose of searching for the possibility of applying it to the housing design in Korea. In spite of changes of housing design condition in Korea, especially steep increase in density, there have been changes only in the height of housing block, not in the housing types, layout, spatial organization and other design properties. Due to such a situation, housing in Korea has been criticised as too high, monotonous one - especially types of housing block tend to be fixed into a slab block and a point block. As one of the alternatives to respond to the criticism, this study focused on the positive aspects of the court housing type, and suggested the design direction throughout the analysis of 8 entries in the design competition of EunPyeong New Town, which attempted to overcome the negative problems - mainly the daylighting, orientation, and privacy - and tried to maximize the positive properties of this type of housing.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.53-62
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• 2004

A single layer latticed dome is one of the most efficient structures because of its low specivic gravity. For easily analyzing of a single layer latticed dome, joint system is assumed to be pin or rigid joint. However, its joint uses ball whose system has intermediate properties of pin and rigid joint. Therefore this study has a grasp of bending rigidity, stress and mechanical properties through experimental and analyzing method of the bolt inserted ball joint. To analyze the stress of bolt and sleeve, this study uses through 3D elastic contact and cubic element, and then the ball and the bolt are perfectly connected for easily analyzing Compared experimental results to F.E.M, each specimen has an error of less than 12 percent. In the results of stress distribution through F.E.M, stress occurs from bottom of bolt to top of sleeve, and most of tension appears on the bolt, also compression occurs from upper parts of the bolt to the sleeve. The assumption of bending stiffness in ball joint is well known that bolt resists only tension and upper sleeve resiss compression. The results of experiment and analysis have $7{\sim}56%$ error, assuring that upper part of bolt occurs of partial compression. In the result of modified assumption have $4{\sim}20%$ error.

• Steel and Composite Structures
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• v.24 no.5
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• pp.635-641
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• 2017

Safety service improvement and development of efficient maintenance strategies for corroded steel structures are undeniably essential. Therefore, understanding the influence of damage caused by corrosion on the remaining load-carrying capacities such as tensile strength is required. In this study, artificial neural network (ANN) approach is proposed in order to produce a simple, accurate, and inexpensive method developed by using tensile test results, material properties and finite element method (FEM) results to train the ANN model. Initially in reproducing corroded model process, FEM was used to obtain tensile strength of artificial corroded plates, for which surface is developed by a spatial autocorrelation model. By using the corroded surface data and material properties as input data, with tensile strength as the output data, the ANN model could be trained. The accuracy of the ANN result was then verified by using leave-one-out cross-validation (LOOCV). As a result, it was confirmed that the accuracy of the ANN approach and the final output equation was developed for predicting tensile strength without tensile test results and FEM in further work. Though previous studies have been conducted, the accuracy results are still lower than the proposed ANN approach. Hence, the proposed ANN model now enables us to have a simple, rapid, and inexpensive method to predict residual tensile strength more accurately due to corrosion in steel structures.