• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.36-39
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• 1996

In chemical processes, measurement errors reduce the credibility of information and cause inconsistency in material and energy balances. Because multicomposition flows and temperature measurements make material and energy balances nonlinear equations, data reconciliation becomes a nonlinear constrained optimization problem. In multicomposition processes, if we follow general optimization procedure, the number of measurement variables is so large that data reconciliation requires much computation time. We propose the decomposition procedure to reduce the computation time without the decrease of accuracy of data reconciliation. Decomposition procedure finds global variables, that can reduce the nonlinearity of constraints, and divides two sub-optimization problems. Once we optimize the global variables at upper level, we can easily optimize the remain variables at tower level, We can obtain the short computational time and the same accuracy as SQP optimization method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2307-2310
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• 2003

In this paper, a method for face recognition based on the wavelet packet decomposition is proposed. In the proposed method, the input image is decomposed by the 2-level wavelet packet transformation and then the face areas are defined by the Integral Projection technique applied to each of the 1-level subband images, HL and LH. After the defined face areas are divided into three areas, called top, bottom, and border, the mean and the variance of the three areas of the approximation image are computed, and the variance of the single predetermined face area for the rest of 15 detail images, from which the feature vectors of statistical measure are extracted. In this paper we use the wavelet packet decomposition, a generalization of the classical wavelet decomposition, to obtain its richer signal analysis features such as discontinuity in higher derivatives, self-similarity, etc. And we have shown that even with very simple statistical features such as mean values and variance we can make an excellent basis for face classification, if an appropriate probability distance is used.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 추계학술대회 논문집
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• pp.375-378
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• 2008

This paper aims at identifying the factors that have influenced changes in the level of industrial $CO_2$ emissions. By means of complete decomposition method the observed changes are analyzed into five different factors: output level, energy intensity, energy mix and structural change and utility use. The application study refers to the manufacturing sectors in Korea. Moreover, this paper discusses the relationship between Korea's manufacturing $CO_2$ emission and economic growth (as measured by GDP), investigating whether economic growth is decoupling from $CO_2$ emission.

• 한국산업융합학회 논문집
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• 제3권4호
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• pp.369-378
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• 2000

Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

• Genomics & Informatics
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• 제17권2호
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• pp.18.1-18.10
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• 2019

Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.

• Journal of Forest and Environmental Science
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• 제29권1호
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• pp.38-48
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• 2013

Decomposition of plant material is an important component in the study of forest ecosystem because of its critical role in nutrient cycling. Different tree species has different nutrient release patterns, which are related to leaf litter quantitative traits and seasonal environmental factors. The quantitative traits of leaf litter are important predictors of decomposition and decomposition rates increase with greater nutrient availability in the forest ecosystems. At the ecosystem level, litter quantitative traits are most often related to the physical and chemical characteristics of the litter, for example, leaf toughness and leaf mass per unit area, and lignin content tannin and total phenolics. Thus, the analysis of litter quantitative traits and decomposition are highly important for the understanding of nutrient cycling in forest ecosystems. By studying the role of litter quantitative traits on decomposition and nutrient cycling in forest ecosystems will provide a valuable insight to how quantitative traits influence ecosystem nutrient dynamics. Such knowledge will contribute to future forest management and conservation practices.

• Bulletin of the Korean Chemical Society
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• 제30권12호
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• pp.2973-2978
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• 2009

The decomposition reaction mechanism of $CH_3CF_2O$ radical formed from hydroflurocarbon, $CH_3CHF_2$ (HFC-152a) in the atmosphere has been investigated using ab-initio quantum mechanical methods. The geometries of the reactant, products and transition states involved in the decomposition pathways have been optimized and characterized at DFT-B3LYP and MP2 levels of theories using 6-311++G(d,p) basis set. Calculations have been carried out to observe the effect of basis sets on the optimized geometries of species involved. Single point energy calculations have been performed at QCISD(T) and CCSD(T) level of theories. Out of the two prominent decomposition channels considered viz., C-C bond scission and F-elimination, C-C bond scission is found to be the dominant path involving a barrier height of 12.3 kcal/mol whereas the F-elimination path involves that of a 28.0 kcal/mol. Using transition-state theory, rate constant for the most dominant decomposition pathway viz., C-C bond scission is calculated at 298 K and found to be 1.3 ${\times}$ 10$^4s{-1}$. Transition states are searched on the potential energy surfaces involving both decomposition channels and each of the transition states are characterized. The existence of transition states on the corresponding potential energy surface are ascertained by performing Intrinsic Reaction Coordinate (IRC) calculation.

• Journal of Ecology and Environment
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• 제35권4호
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• pp.291-299
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• 2012

This experiment was conducted to investigate the effects of the addition of wintering waterfowl's feces prior to planting rice on nutrient dynamics, rice growth, and decomposition of rice straws in a controlled mesocosm. Waterfowl's feces and rice straws were placed on paddy soils in a mesocosm and the water level maintained at 5 cm. The amounts of supplied feces were 0 (control), 222, and 444 g/$m^2$. While the addition of feces showed no immediate effects, nutrients in the surface water increased in the month following treatment. Nutrients increased to a greater degree in the treatments with more feces added. Simultaneously, the decomposition of rice straws was promoted, indicating that more nutrients would be made available over time. The rice showed high productivity in the period during which nutrient level was increased, when rice needs more nutrients for the tillering stage. Therefore, the wintering waterfowl's feces could be associated with increased productivity during the growing season of rice through promoting nutrient supply and rapid decomposition of rice residue.

• International journal of advanced smart convergence
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• 제6권1호
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• pp.68-75
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• 2017

In this paper, a particular application of digital photos, remote sensing, remote shooting air moving, high-resolution and high compression of medical images required by remote shooting of JPEG2000 standard applied in the field of hardware design, production was implemented. JPEG2000 standard for image compression using the software implementation of the processing speed is very slow compared to conventional JPEG disadvantages, and also the standard of JPEG2000 DWT (Discrete wavelet transform) to improve the level of compression for image data if processing speed is a phenomenon that has degraded. In order to solve these JPEG2000 compression / decompression groups were designed and applied. In this paper, the optimal JPEG2000 compression / reservoir hardware by changing the level for still image compression, faster computation speed and quality has shown improvement.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2558-2561
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• 2008

In the present study, a parallel Taylor-Galerkin/level set based two-phase flow code was developed using finite element discretization and domain decomposition method based on MPI (Message Passing Interface). The proposed method can be utilized for the analysis of a large scale free surface problem in a complex geometry due to the feature of FEM and domain decomposition method. Four-step fractional step method was used for the solution of the incompressible Navier-Stokes equations and Taylor-Galerkin method was adopted for the discretization of hyperbolic type redistancing and advection equations. A Parallel ILU(0) type preconditioner was chosen to accelerate the convergence of a conjugate gradient type iterative solvers. From the present parallel numerical experiments, it has been shown that the proposed method is applicable to the simulation of large scale free surface flows.