• Journal of Digital Contents Society
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• v.14 no.1
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• pp.117-124
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• 2013

This paper suggests the robust method of extraction for moving objects in illumination variation by using image sequence from an immovable camera. The most difficult part of the implication is the effect by illumination and noise. The object area is hardly estimated when the dusky area occurs in illumination variation by time change. This thesis describes the extraction of moving objects employed by Gaussian mixture model which is noise robust measure. Also, the report suggests the elimination method of illumination part in input image by the representative illumination image which is defined to minimize the illumination influence.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.54-59
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• 1999

In this paper, a generalized auto-regressive(AR) model is proposed for linear prediction based on adaptive spatio-temporal support region(ASTSR). The conventional AR model suffers from the drawback that the prediction error increases in the edge region because the rectangular support region of the edge does not satisfy the stationary assumption. Thus, the proposed approach puts an emphasis on the formulation of a spatio-temporally adaptive support region for the AR model, called ASTSR. The ASTSR consists of two parts: the adaptive spatial support region(ASSR) connected with edges and the adaptive temporal support region(ATSR) related to temporal discontinuities. The AR model based on ASTSR not only produces more accurate model parameters but also reduces the computational complexity in the motion picture restoration.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.6
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• pp.23-32
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• 2007

This study developed an analytical model for predicting nonlinear behavior of PT flat plate frames having slab-column connections with and without slab bottom reinforcement passing through the column. The developed model can predict the failure sequence until punching failure occurs. For verifying the analytical model, the test results of PT flat plate slab-column connections were compared with the results of the analysis. Moreover, the results of static pushover test and shaking table test of 2 story PT flat plate frame were compared with analysis results. For evaluating seismic performance of PT flat plate frame, this study conducted nonlinear response history analysis of the 2 story PT flat plate frame with and without slab bottom reinforcement passing through the column under 1940 El Centro ground motion scaled to have pseudo spectral acceleration of 0.3, 0.5, and 0.7g at the fundamental period of the frame. This study observed that as ground motion is more intense, seismic demands for the frame having the connections without slab bottom reinforcement passing through the column are larger than those without slab bottom reinforcement.

• Applied Chemistry for Engineering
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• v.7 no.2
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• pp.321-325
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• 1996

Quantum chemical calculations are used to characterize the decomposition of nitrogenmonoxide over $Cu^{n+}$-Y zeolite. The method of theoretical calculations, such as CNDO/2, have been applied to cluster models representing cation sites in zeolite to obtain total energies, LUMO energies, and Wiberg bond orders. The calculated total energies and bond orders of cluster models showed the reaction mechanism of NO decomposition over $Cu^{n+}$ site in zeolite framework. The suggested cluster models of varying Si/Al ratios studied with exchange cations in the $Cu^+$ and in the $Cu^{2+}$ states. And the calculated LUMO energies can predict L acidifies of cluster models. The results from these experiments showed the possibility of the mechanism of NO decomposition, progressing adsorption of NO, conversion to $N_2$ and $O_2$, desorption of $N_2$ and $O_2$ in sequence. The L acidity of $Cu^{2+}$ ion in cation site is more strong than $Cu^+$.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.61-75
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• 2008

A script language, which represents and controls avatar behaviors in a natural language style, is especially remarkable, because it can provide a fast and easy way to develop an animation scenario script. However, the studies that consider avatar behavior interactions with various virtual objects and intuitive interface techniques to design scenario script have been lack. Therefore, we proposed a context-based avatar-object behavior model and layered script language. The model defines context-based elements to solve ambiguity problems that occur in abstract behavior interface and it provides user interface to control avatar in the object-based approach. Also, the proposed avatar behavior script language consisted of a layered structure that represents domain user interface, motion sequence, and implement environment information at each level. Using the proposed methods, the user can conveniently and quickly design an avatar-object behavior scenario script.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.655-660
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• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

• 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.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.135-142
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• 2003

Robust extraction of 3D object's features, shape and global motion information from 2D image sequence is described. The object's 21 feature points on the pyramid type synthetic object are extracted automatically using color transform technique. The extracted features are used to recover the 3D shape and global motion of the object using stereo paraperspective camera model and sequential SVD(Singuiar Value Decomposition) factorization method. An inherent error of depth recovery due to the paraperspective camera model was removed by using the stereo image analysis. A 30 synthetic object with 21 features reflecting various position was designed and tested to show the performance of proposed algorithm by comparing the recovered shape and motion data with the measured values.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.65-71
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• 2012

In order to improve the structural safety and light-weight design of aircraft floats, natural frequency and static stress analysis are performed under water and ground landing conditions. A finite element mesh based on the design configuration of light aircraft floats is modeled, and simplified water and ground landing loads are applied to this model. The natural frequency and stress analysis of aluminum-alloy floats are carried out first. Then, the structural performance of the floats is re-analyzed in the case of laminated composites, and the numerical results are compared each other. It is concluded that, by tailoring the laminated composites with respect to stacking sequence and ply thickness, the structural safety of the light-weight floats can be improved.