• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.99-101
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• 2015

Massive stars are some of the most influential objects in the Universe, shaping the evolution of galaxies, creating chemical elements and hence shaping the evolution of the Universe. However, the processes by which they form and how they shape their environment during their birth processes are not well understood. We use $NH_3$ data from "The $H_2O$ Southern Galactic Plane Survey" (HOPS) survey to define the positions of dense cores/clumps of gas in the southern Galactic plane that are likely to form stars. Then, using data from "The Millimetre Astronomy Legacy Team 90 GHz" (MALT90) survey, we search for the presence of infall and outflow associated with these cores. We subsequently use the "3D Molecular Line Radiative Transfer Code" (MOLLIE) to constrain properties of the infall and outflow, such as velocity and mass flow. The aim of the project is to determine how common infall and outflow are in star forming cores, and therefore to provide valuable constraints on the timescales and physical process involved in massive star formation. Preliminary results are presented here.

• Korean Journal of Materials Research
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• v.12 no.1
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• pp.21-26
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• 2002

In order to search new phosphors for plasma display panel(PDP), phosphate hosts which has a host excitation band at around 150nm were prepared and their luminescent properties were investigated. In the preparation of $YPO_4: Eu\; and\; (Y,Gd)PO_4: Eu$ phosphors, the effect of oxide and oxalate starting materials on prepared phosphors were compared in terms of relative emission intensities and particle characteristics. The results showed that oxalate starting materials gave better performance in emission intensities and smaller size and more round shape phosphors which would be more applicable for high resolution display. Additionally, Gd, V, Nb and Ta ions were doped to $YPO_4:Eu$ and the luminescent properties of the resulant solid solutions were investigated to find efficient sensitizer. Among these ions, Gd, V and Nb ions increased the emission intensities of parent phosphor to around 10%. While Nb ion gave the best result in emission intensities, CIE color coordinate were improved by doping V ion into $YPO_4:Eu$ phosphor to give x=0.6523, y=0.3406 compared to commercial sample.

• Journal of Biosystems Engineering
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• v.9 no.2
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• pp.89-96
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• 1984

This study was intended to search the thermal properties of rice which are necessary in preventing qualitative and quantitative losses in the drying and milling processes. First, the coefficient of cubical thermal expansion of brown rice was measured, which is required for analyzing the internal stress of rice, and then theoretical thermal and moisture stresses were calculated. The results are summarized as follows: 1. The coefficient of cubical thermal expansion of brown rice was about $2.81{\times}10^{-4}/^{\circ}C$ in the temperature range of $10^{\circ}C-60^{\circ}C$. 2. When the shape of brown rice was assumed to be a sphere or a cylinder, maximum thermal stress due to temperature change of $20^{\circ}C-60^{\circ}C$ was in the range of $25-100kg/cm^2$. And maximum moisture stress was in the range of $450-650kg/cm^2$ when the drying temperature was $35^{\circ}C$, initial and final moisture contents of brown rice were 20% and 14% (w.b.), and the moisture diffusion coefficient was assumed to be $6.79{\times}10^{-4}cm^2/hr$. 3. Consequently, it was concluded that crack formation in a rice kernel is mainly caused by moisture stress.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4933-4956
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• 2016

Use-After-Free (UAF) is a common lethal form of software vulnerability. By using tools such as Web Browser Fuzzing, a large amount of samples containing UAF vulnerabilities can be generated. To evaluate the threat level of vulnerability or to patch the vulnerabilities, automatic deduplication and exploitability determination should be carried out for these samples. There are some problems existing in current methods, including inadequate pertinence, lack of depth and precision of analysis, high time cost, and low accuracy. In this paper, in terms of key dangling pointer and crash context, we analyze four properties of similar samples of UAF vulnerability, explore the method of extracting and calculate clustering eigenvalues from these samples, perform clustering by fast search and find of density peaks on a large number of vulnerability samples. Samples were divided into different UAF vulnerability categories according to the clustering results, and the exploitability of these UAF vulnerabilities was determined by observing the shape of class cluster. Experimental results showed that the approach was applicable to the deduplication and exploitability determination of a large amount of UAF vulnerability samples, with high accuracy and low performance cost.

• International Journal of Air-Conditioning and Refrigeration
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• v.16 no.1
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• pp.1-8
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• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.57-65
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• 2019

In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.

• The Journal of Advanced Prosthodontics
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• v.14 no.3
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• pp.182-202
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• 2022

PURPOSE. The aim of this study is to summarize various biomechanical aspects in evaluating the long-term stability of dental implants based on finite element method (FEM). MATERIALS AND METHODS. A comprehensive search was performed among published studies over the last 20 years in three databases; PubMed, Scopus, and Google Scholar. The studies are arranged in a comparative table based on their publication date. Also, the variety of modeling is shown in the form of graphs and tables. Various aspects of the studies conducted were discussed here. RESULTS. By reviewing the titles and abstracts, 9 main categories were extracted and discussed as follows: implant materials, the focus of the study on bone or implant as well as the interface area, type of loading, element shape, parts of the model, boundary conditions, failure criteria, statistical analysis, and experimental tests performed to validate the results. It was found that most of the studied articles contain a model of the jaw bone (cortical and cancellous bone). The material properties were generally derived from the literature. Approximately 43% of the studies attempted to examine the implant and surrounding bone simultaneously. Almost 42% of the studies performed experimental tests to validate the modeling. CONCLUSION. Based on the results of the studies reviewed, there is no "optimal" design guideline, but more reliable design of implant is possible. This review study can be a starting point for more detailed investigations of dental implant longevity.

• Journal of IKEEE
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• v.25 no.4
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• pp.650-663
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• 2021

Subsurface topology estimation is an important factor in the geophysical survey. Electrical impedance tomography is one of the popular methods used for subsurface imaging. The EIT inverse problem is highly nonlinear and ill-posed; therefore, reconstructed conductivity distribution suffers from low spatial resolution. The subsurface region can be approximated as piece-wise separate regions with constant conductivity in each region; therefore, the conductivity estimation problem is transformed to estimate the shape and location of the layer boundary interface. Each layer interface boundary is treated as an open boundary that is described using front points. The subsurface domain contains multi-layers with very complex configurations, and, in such situations, conventional methods such as the modified Newton Raphson method fail to provide the desired solution. Therefore, in this work, we have implemented a 7-layer artificial neural network (ANN) as an inverse problem algorithm to estimate the front points that describe the multi-layer interface boundaries. An ANN model consisting of input, output, and five fully connected hidden layers are trained for interlayer boundary reconstruction using training data that consists of pairs of voltage measurements of the subsurface domain with three-layer configuration and the corresponding front points of interface boundaries. The results from the proposed ANN model are compared with the gravitational search algorithm (GSA) for interlayer boundary estimation, and the results show that ANN is successful in estimating the layer boundaries with good accuracy.