• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.1
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• pp.63-78
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• 2009

This paper presents the development of dynamically combined Typhoon generated surge-tide-wave numerical model which is applicable to shallow water. The newly developed model is based on both POM (Princeton Ocean Model) for the surge and tide and WAM (WAve Model) for wind-generated waves, but is modified to be applicable to shallow water. In this paper which is the first paper of the two in a sequence, we verified the accuracy and numerical stability of the hydrodynamic part of the model which is responsible for the simulation of Typhoon generated surge and tide. In order to improve the accuracy and numerical stability of the combined model, we modified algorithms responsible for turbulent modeling as well as vertical velocity computation routine of POM. Verification of the model performance had been conducted by comparing numerical simulation results with analytic solutions as well as data obtained from field measurement. The modified POM is shown to be more accurate and numerically stable compare to the existing POM.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1207-1214
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• 2014

The first frame of a GOP is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the encoding results of the intra frame affects the first frame as well as the following frames. Traditionally, the quantization parameter for an intra frame is determined only depending on the bpp not considering the characteristics of the intra frame. For accurate intra frame encoding, we should consider not only bpp but also the complexity of the video sequence and the output bandwidth. In this paper, we propose a real-time quantization model which is used to calculate the quantization parameter for an intra frame encoding based on the investigation on the characteristics of a GOP. It is shown by experimental results that the proposed quantization model captures the characteristics of an intra frame effectively and the proposed method for model parameters accurately estimates the real values.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.405-412
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• 2010

Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts. To overcome this problem, in this paper, we propose a new background generation method which incorporates spatial as well as temporal contexts of the image. This enabled us to obtain 'clean' background image with no moving objects. In our proposed method, first we divided the sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static, we used MRF framework to model them in temporal and spatial contexts. MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.3011-3016
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• 2015

Representing protein three-dimensional structure by concatenating a sequence of protein fragments gives an efficient application in analysis, modeling, search, and prediction of protein structures. This paper investigated the effective combination of distance measures, which can exploit large protein structure database, in order to construct a protein fragment library representing native protein structures accurately. Clustering method was used to construct a protein fragment library. Initial clustering stage used inter alpha-carbon distance having low time complexity, and cluster extension stage used the combination of inter alpha-carbon distance, Binet-Cauchy distance, and root mean square deviation. Protein fragment library was constructed by leveraging large protein structure database using the proposed combination of distance measures. This library gives low root mean square deviation in the experiments representing protein structures with protein fragments.

• Smart Structures and Systems
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• v.15 no.4
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.

• Computers and Concrete
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• v.12 no.2
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• pp.211-228
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• 2013

The structure analyzed in this paper has particular building style and special structural system. It is a rigid-connected twin-tower skyscraper with asymmetrical distribution of stiffness and masses in two towers. Because of the different stiffness between the north and the south towers, the torsion seismic vibration is significant. In this paper, in order to study the seismic response of the structure under both frequent low-intensity earthquakes as well as rare earthquakes at the levels of intensity 7, the analysis model is built and analyzed with NosaCAD. NosaCAD is an nonlinear structure analysis software based on second-development of AutoCAD with ObjectARX. It has convenient modeling function, high computational efficiency and diversity post-processing functions. The deformations, forces and damages of the structure are investigated based on the analysis. According to the analysis, there is no damage on the structure under frequent earthquakes, and the structure has sufficient capacity and ductility to resist rare earthquakes. Therefore the structure can reach the goal of no damage under frequent earthquakes and no collapse under rare earthquakes. The deformation of the structure is below the limit in Chinese code. The time sequence and distribution of damages on tubes are reasonable, which can dissipate some dynamic energy. At last, according to forces, load-carrying capacity and damage of elements, there are some suggestions on increasing the reinforcement in the core tube at base and in stiffened stories.

• Microbiology and Biotechnology Letters
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• v.34 no.2
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• pp.129-135
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• 2006

A gene encoding for a putative microsomal epoxide hydrolase (mEH) of a zebrafish, Danio rerio, was cloned and characterized. The putative mEH protein of D. rerio exhibited sequence similarity with mammalian mEH and some other bacterial EHs. A structural model for the putative mEH was constructed using homology modeling based on the crystallographic templates, 1 qo7 and 1 ehy. The catalytic triad consisting of $Asp^{233}$, $Glu^{413}$, and $His^{440}$ was identified, and the characteristic features such as two tyrosine residues and oxyanion hole were found to be highly conserved. Based on bioinformatic analysis together with EH activity assay, the putative protein was annotated as mEH of D. rerio. Enantiopure styrene oxide with enantiopurity of 99%ee and yield of 33.5% was obtained from racemic styrene oxide by the enantioselective hydrolysis activity of recombinant mEH of D. rerio for 45 min.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.156-167
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• 2007

In this paper, we develop the model based prediction algorithm for Variable-Bit-Rate(VBR) video traffic with regular Group of Picture(GOP) pattern. We use multiplicative ARIMA process called GOP ARIMA (ARIMA for Group Of Pictures) as a base stochastic model. Kalman Filter based prediction algorithm consists of two process: GOP ARIMA modeling and prediction. In performance study, we produce three video traces (news, drama, sports) and we compare the accuracy of three different prediction schemes: Kalman Filter based prediction, linear prediction, and double exponential smoothing. The proposed prediction algorithm yields superior prediction accuracy than the other two. We also show that confidence interval analysis can effectively detect scene changes of the sample video sequence. The Kalman filter based prediction algorithm proposed in this work makes significant contributions to various aspects of network traffic engineering and resource allocation.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.