• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.781-792
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• 2015

This study aims to develop a spring/fall motorcycle jacket for quick service transporter. Depending on the results of the previous research, this study produced the tested jacket which was improved in material, pattern, and design. For the tested jacket, 100% polyester fabric excellent in strength, durability and abrasion-resistance was selected as a major material, and Cordura was used as a partial material to improve the strength and abrasion-resistance of the sleeve side lines, elbow and shoulder areas. The retro-reflection material was applied partially in order to improve visibility of the jacket in the night or in a dark place. A total of 7 pockets were composed in the jacket for the sufficient storage spaces. The functional design elements such as the 2-way zipper and the placket at the center front, the action pleats at the upper part of back armholes, the pit-zip at armpit were applied. In addition, the sleeve pattern was bent with the shape of elbow curvature in time of driving and the back length of the jacket was lengthened 4cm. As a result of the appearance assessment, there was a significant difference from the existing jacket in all items but chest size, shoulder width, cuffs circumference, and jacket hemline circumference. In motion adaptability and field activity appropriateness assessments, the assessment grade for all items was found to be commonly higher than that of the existing jacket, and thus, the tested jacket was assessed to be suitable for a motorcycle jacket design for the quick service transporters.

• Fashion & Textile Research Journal
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• v.25 no.2
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• pp.139-152
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• 2023

Despite efforts to apply 3D print (3DP) technology in the field of fashion and endless discussions about the possibility of future development, in reality, it is difficult to utilize 3DP technology in fashion for reasons related to material, technology, and cost constraints. The purpose of this study was to supplement the limitations of 3DP technology in order to promote its utilization in fashion and simultaneously find a solution to achieve aesthetic satisfaction in the design method. Specifically, through the development of fashion products with a 3DP polymer-fabric structure to which the parametric design methodology has been applied, this study explored the possibility of practical application and proposes a new 3DP fashion design method. The 3DP polymer-fabric developed as a result of the research was stably adhered to the fabric. Additionally, the study confirmed the possibility of making 3DP clothes that are amenable to the wearer's activities, as it was verified that cutting and sewing tailored to the human body's curvature and structure can be performed. The design process using the 3DP polymer-fabric presented in this study is meaningful in that it suggests a solution to complement the limitations of modern technology in connection with designers' creativity. Moreover, the design process presented in this study is expected to contribute to the commercialization and generalization of 3DP by providing practical help to allow fashion experts to utilize 3DP technology.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.106-112
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• 1990

The progress of oxidation of a porous silicon layer(PSL) was studied by examining the temperature dependence of the oxidation and the infrared absorption spectra. Thick OPSL(oxidized porous silicon layer). which has the same properties as thermal $SiO_{2}$ of bulk silicon, is formed in a short time by two steps wet oxidation of PSL at $700^{\circ}C$, 1 hr and $1100^{\circ}C$, 1 hr. Etching rate, breakdown strength of the OPSL are strongly dependent on the oxidation temperature, oxidation atmosphere. And its breakdown field was ${1\MV/cm^-2}$ MV/cm The oxide film stress was determined through curvature measurement using a dial gauge. During oxidation at temperature above $1000^{\circ}C$ in dry $O_{2}$, stress on the order of ${10^9}\dyne/{cm^2}{-10^10}\dyne/{cm^2}$ are generated in the OPSL.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.68-77
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• 2012

The joint of existing steel grid composite deck is composed of lap splice of reinforcing bar with end hooks and field-placed concrete. In this study, bending tests of deck joint composed of concrete shear key and high tension bolts are carried out for the design variable, concrete shear key strengthened with steel plate or not, and test results are compared with flexural performance of the existing deck joint. Test results showed that the mechanical deck joint has about 30% ~ 60% more ultimate bending strength than the existing joint. According to analysis results of moment-curvature relationship, the initial bending stiffness of the existing deck joint is some higher than that of mechanical joint. But, after crack failure the structural performance of the existing deck joint is rapidly reduced. Furthermore, the deck joint with the strengthened shear key with steel plate has more bending moment capacity than the deck joint without strengthening. And strengthening of shear key has positive influence on the increase of bending stiffness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.9
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• pp.785-795
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• 1990

For the far field radiation pattern of a microstrip array antenna which is conformed to a cylindrical surface and forms an arc array, an approximate analysis method using FOURIER TRANSFORM is presented. In this method, the conformal array antenna is projected on the effective aperture plane and assumed to be an aperiodic array with nonlinear phase tilt. The effective aperture plane includes four end-points of each arc on the cylindrical surface. When the effective aperture ratio which is normalized to the planar type is from 1.0 to 0.9, it is confirmed that this approximate method is valid. To the array on the effective aperture plane, it is assumed that the phase tilt is due to the distance between aperture plne and curvature surface. Specially, when the radius of arc is more than 5 times to its length, the FOURIER TRANSFORM METHOD could be used with only varying scale factors. The results of calculating by approximate method are good agreement with the results of COORDINATE TRANSFORM METHOD and experimentally measured value in the range of -40dB. And, the difference of half power angle is less than 5 degrees when the effective aperture ratio moer than 0.9.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.515-523
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• 2012

In this paper, the resonance characteristics and radiation characteristics of a spherical patch on a dielectric sphere are analyzed. Resonance characteristics can be obtained from the resonant frequency and the quality factor. Radiation characteristics can be also analyzed from the E-field in the far region. In order to calculate these parameters, spectral domain analysis method is applied. Algebraic equation can be obtained in spectral domain through Vector Legendre transform pair and Galerkin's method. So, efficient calculation is possible numerically. It is investigated that radius, curvature of a spherical patch, and dielectric constant of a dielectric sphere have an effect on characteristics of a spherical patch.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.4
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• pp.86-93
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• 2010

The wear of railway track affects loss of rough ride, noise or vibration of train and traveling safety. Moreover as the track is worn away, this promotes destruction of structural mechanism of rail track which can bring about increasing of rail track maintenance cost drastically. For this reason, it is very important and interested research subject to design railway track structure and to analyse train movement mechanism based on systematic analysis of the reasons causing rail wear possible in real field. In this research, for the efficient maintenance, Life Cycle Performance of rail track and maintenance characteristics are computed considering some track components such as track type, contracting type, sleeper type and roadbed type. Time - Wear probabilistic distribution relationship as well as multiple regression analysis based on time, curvature and wear data are computed to predict the service life remainder of railway track and to be adapted to safety assessment.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.