• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.74.1-74.1
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• 2015

'The one to one correspondence model' defines the relation between a dark matter halo (DM halo) and a galaxy. A basic assumption of this model is that a more massive DM subhalo hosts a brighter galaxy. In a more improved version of the model we may be able to assign a mock galaxy with a morphological type. In this study, we are building a mock galaxy catalog using massive halo merging trees from the Horizon Run 4. We test various merging models to calculate the merging time scale of a subhalo along its merging tree. And we obtain the halo mass functions for major subhalos and satellite subhalos, separately, and compare them with the observed luminosity functions of major galaxies and satellite galaxies from the SDSS group catalog. Furthermore, we are going to make a range of mock galaxy catalogs and investigate their properties, such as spatial distributions, environmental effects, and morphologies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.578-585
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• 2018

In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.

• Publications of The Korean Astronomical Society
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• v.9 no.1
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• pp.21-38
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• 1994

We have developed a cylindrical mixing layer model of a stellar jet including cooling effect in order to understand an optical emission mechanism along collimated high velocity stellar jets associated with young stellar objects. The cylindrical results have been calculated to be the same as the 2D ones presented by Canto & Raga(1991) because the entrainment efficiency in our cylindrical model has been obtained to be the same value as the 2D model has given. We have discussed the morphological and physical characteristics of the mixing layers by the cooling effect. As the jet Mach number increases, the initial temperature of the mixing layer goes high because the kinetic energy of the jet partly converts to the thermal energy of the mixing layer. The initial cooling of the mixing layer is very severe, changing its outer boundary radius. A subsequent change becomes adiabatic. The number of the Mach disks in the stellar jet and the total radiative luminosity of the mixing layer, based on our cylindrical calculation, have quite agreed with the observations.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.7-13
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• 1997

Morphological Analysis of Korean has known to be a very complicated problem. Especially, the degree of part-of-speech(POS) ambiguity is much higher than English. Many researchers have tried to use a hidden Markov model(HMM) to solve the POS tagging problem and showed arround 95% correctness ratio. However, the lack of lexical information involves a hidden Markov model for POS tagging in lots of difficulties in improving the performance. To alleviate the burden, this paper proposes a method for combining multiword units, which are types of lexical information, into a hidden Markov model for POS tagging. This paper also proposes a method for extracting multiword units from POS tagged corpus. In this paper, a multiword unit is defined as a unit which consists of more than one word. We found that these multiword units are the major source of POS tagging errors. Our experiment shows that the error reduction rate of the proposed method is about 13%.

• Advances in nano research
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• v.9 no.1
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• pp.59-67
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• 2020

Filter cake formation during rotary drilling operation is an unavoidable scenario, hence there is need for constant improvement in the approaches used in monitoring the cake thickness growth in order to prevent drill-string sticking. This study proposes an improved model that predicts the growth of mud cake thickness overtime with the consideration of the addition of nanoparticles in the formulated drilling fluid system. Ferric oxide, titanium dioxide and copper oxide nanoparticles were used in varying amounts (2 g, 4 g and 6 g), and filtration data were obtained from the HPHT filtration test. The filter cakes formed were further analyzed with scanning electron microscope to obtain the morphological characteristics. The data obtained was used to validate the new filtrate loss model. This model specifically presents the concept of time variation in filter cake formation as against the previous works of constant and definite time. Regression coefficient which is a statistical measure was used to validate the new model and the predicted results were compared with the API model. The new model showed R² values of 99.9%, and the predictions from the proposed filtration model can be said to be more closely related to the experimental data than that predicted from the API model from the SSE and RMSE results.

• Journal of Environmental Science International
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• v.23 no.8
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• pp.1419-1428
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• 2014

Electron beam-induced grafting polymerization was employed to prepare Acrylic acid-grafted bacterial cellulose (BC-g-AAc). BC-g-AAc as an adsorbent was applied to remove heavy metals (e.g., As, Pb, and Cd). This study examined followings; morphological change of surface, adsorptive behavior of BC-g-AAc, and interpretation of adsorptive kinetics. Specific surface areas of BC and BC-g-AAc were $0.9527m^2g^{-1}$ for BC and $0.2272m^2g^{-1}$ for BC-g-AAc, respectively as measured by BET nitrogen adsorption, revealing the morphological change of the surface of BC-g-AAc. Batch adsorption test was performed to investigate adsorptive behavior of BC-g-AAc in aqueous solution. The amounts of Pb and Cd adsorbed on BC-g-AAc were $69mg\;g^{-1}$ and $56mg\;g^{-1}$, respectively. However, As was not adsorbed on BC-g-AAc due to its neutral nature. Both the Benaissa model and the Kurniawan model were applied in the study to interpret adsorptive kinetics. From the value of correction coefficient ($R^2$), adsorptive kinetics of Pb and Cd were subjected to Kurniawan model referred to pseudo-second-order. Taken together, the results of this study show that BC-g-AAc has potential as a heavy metal (eg., Pb, Cd)-adsorbent made of an environmentally friendly material.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.152-161
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• 2017

Making precise 3D maps using Mobile Mapping System (MMS) sensors are essential for the development of self-driving cars. This paper conducts research on the extraction of 3D objects around the roads using the point cloud acquired by the MMS Light Detection and Ranging (LiDAR) sensor through the following steps. First, the digital surface model (DSM) is generated using MMS LiDAR data, and then the slope map is generated from the DSM. Next, the 3D objects around the roads are identified using the slope information. Finally, 97% of the 3D objects around the roads are extracted using the morphological filtering technique. This research contributes a plan for the application of automated driving technology by extracting the 3D objects around the roads using spatial information data acquired by the MMS sensor.

• Ecology and Resilient Infrastructure
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• v.1 no.2
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• pp.61-67
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• 2014

Dam construction changes flow regime and stream morphology in the downstream reach. These affect the ecosystem of downstream reach. This study provides the assessment of the impact of dam construction on the downstream fish habitat. For this, physical habitat simulations are carried out. The quasi-steady model is used for hydraulic simulation, The hydraulic model used in the present study is capable of simulating the morphological change due to sediment transport. The change of the fish habitat condition is investigated using the flow scenarios before and after the dam construction. Simulation results indicate that the habitat suitability decreases frequently due to hydropeaking after dam construction. In addition, erosion is expected to occur in a reach downstream of dam. This is a long term effect due to the shut-down of sediment supply from the upstream reach.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.179-199
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• 2019

In this paper, we propose optimal methodologies for classifying patent literature by examining various feature extraction methods, machine learning and deep learning models, and provide optimal performance through experiments. We compared the traditional BoW method and a distributed representation method (word embedding vector) as a feature extraction, and compared the morphological analysis and multi gram as the method of constructing the document collection. In addition, classification performance was verified using traditional machine learning model and deep learning model. Experimental results show that the best performance is achieved when we apply the deep learning model with distributed representation and morphological analysis based feature extraction. In Section, Class and Subclass classification experiments, We improved the performance by 5.71%, 18.84% and 21.53%, respectively, compared with traditional classification methods.

• Journal of the Korean Geotechnical Society
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• v.39 no.8
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• pp.17-28
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• 2023

Laboratory-scale hydraulic fracturing experiments were conducted on granite specimens at various viscosities and injection rates of the fracturing fluid. A series of cross-sectional computed tomography (CT) images of fractured specimens was obtained via a three-dimensional X-ray CT imaging method. Pixel-level fracture segmentation of the CT images was conducted using a convolutional neural network (CNN)-based Nested U-Net model structure. Compared with traditional image processing methods, the CNN-based model showed a better performance in the extraction of thin and complex fractures. These extracted fractures extracted were reconstructed in three dimensions and morphologically analyzed based on their fracture volume, aperture, tortuosity, and surface roughness. The fracture volume and aperture increased with the increase in viscosity of the fracturing fluid, while the tortuosity and roughness of the fracture surface decreased. The findings also confirmed the anisotropic tortuosity and roughness of the fracture surface. In this study, a CNN-based model was used to perform accurate fracture segmentation, and quantitative analysis of hydraulic stimulated fractures was conducted successfully.