• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.697-715
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• 2004

Component-Based Development (CBD) is a reuse technology Providing enhancement in productivity through using the unit of component which is larger-grained than an object. However, reference model defining the elements and semantics of CBD component is standardized neither internationally nor in industrial. This yields interoperability and portability problem between CBD platforms, and presents burden of choosing appropriate model to developers. In this paper, we define meta-models for representative component reference models, and identify advantages, disadvantages, and features of each model through technical comparison of meta-models. Besides, through a proposal of essential component model containing common and essential elements that all component models must conform and a extended component model containing maximum elements and mechanisms, we can precisely assess candidate component models in practice.

• Journal of The Korean Astronomical Society
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• v.32 no.1
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• pp.17-39
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• 1999

We investigate dynamical evolution of globular clusters with multi-mass component under the Galactic tidal field. We compare the results with our previous work which considered the cases of single-mass component m the globular clusters. We find the followings: 1) The general evolutions are similar to the cases of single-mass component. 2) There is no evidence for dependence on the orbital phase of the cluster as in the case of single-mass component. 3) The escape rate in multi-mass models is larger than that in the single-mass models. 4) The mass-function depends on radius more sensitively in anisotropic models than in isotropic models.

• ETRI Journal
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• v.25 no.2
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• pp.121-132
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• 2003

To enhance the productivity of software development and accelerate time to market, software developers have recently paid more attention to a component-based development (CBD) approach due to the benefits of component reuse. Among CBD processes, the identification of reusable components is a key but difficult process. Currently, component identification depends mainly on the intuition and experience of domain experts. In addition, there are few systematic methods or tools for component identification that enable domain experts to identify reusable components. This paper presents a systematic method and its tool called a component identifier that identifies software components by using object-oriented domain information, namely, use case models, domain object models, and sequence diagrams. To illustrate our method, we use the component identifier to identify candidates of reusable components from the object-oriented domain models of a banking system. The component identifier enables domain experts to easily identify reusable components by assisting and automating identification processes in an earlier development phase.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.3
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.755-761
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• 2014

Heterogeneous components have different component models, which prevents such components from sharing the functionalities of other components based on the different models. As one of methods for linking heterogeneous components, this paper suggests a proxy component to construct a bridge between heterogeneous components of OPRoS (Open Platform for Robotic Service) and RTM (Robot Technology Middleware). The proxy component consists of two types of components called Adaptor and Interceptor, via which the heterogeneous components can exchange data and services easily. The proposed method enables adaptor and interceptor components to directly invoke the services of the latter and the former, respectively, in order to exchange data and services on a real-time basis. The proxy component can be implemented for OPRoS and RT (Robot Technology) component models to connect with RT and OPRoS ones, respectively. It is shown through a simple experiment that the proposed method works well for real-time control.

• Bulletin of the Korean Chemical Society
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• v.29 no.4
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• pp.833-841
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• 2008

Principal component-genetic algorithm-multiparameter linear regression (PC-GA-MLR) and principal component-genetic algorithm-artificial neural network (PC-GA-ANN) models were applied for prediction of melting point for 323 drug-like compounds. A large number of theoretical descriptors were calculated for each compound. The first 234 principal components (PC’s) were found to explain more than 99.9% of variances in the original data matrix. From the pool of these PC’s, the genetic algorithm was employed for selection of the best set of extracted PC’s for PC-MLR and PC-ANN models. The models were generated using fifteen PC’s as variables. For evaluation of the predictive power of the models, melting points of 64 compounds in the prediction set were calculated. Root-mean square errors (RMSE) for PC-GA-MLR and PC-GA-ANN models are 48.18 and $12.77{^{\circ}C}$, respectively. Comparison of the results obtained by the models reveals superiority of the PC-GA-ANN relative to the PC-GA-MLR and the recently proposed models (RMSE = $40.7{^{\circ}C}$). The improvements are due to the fact that the melting point of the compounds demonstrates non-linear correlations with the principal components.

• Journal of Pharmaceutical Investigation
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• v.37 no.6
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• pp.377-395
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• 2007

Near infrared(NIR) spectral data have been used for the noninvasive analysis of various biological samples. Nonetheless, absorption bands of NIR region are overlapped extensively. It is very difficult to select the proper wavelengths of spectral data, which give the best PCR(principal component regression) models for the analysis of constituents of biological samples. The NIR data were used after polynomial smoothing and differentiation of 1st order, using Savitzky-Golay filters. To find the best PCR models, all-possible combinations of available principal components from the given NIR spectral data were derived by in-house programs written in MATLAB codes. All of the extensively generated PCR models were compared in terms of SEC(standard error of calibration), $R^2$, SEP(standard error of prediction) and SECP(standard error of calibration and prediction) to find the best combination of principal components of the initial PCR models. The initial PCR models were found by SEC or Malinowski's indicator function and a priori selection of spectral points were examined in terms of correlation coefficients between NIR data at each wavelength and corresponding concentrations. For the test of the developed program, aqueous solutions of BSA(bovine serum albumin) and glucose were prepared and analyzed. As a result, the best PCR models were found using a priori selection of spectral points and the final model selection by SEP or SECP.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.143-144
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• 1996

Two-component models (normal star and degenerate star components) are the simplest realization of clusters with a mass spectrum because the high mass stars quickly evolve off leaving degenerate stars behind, while low mass stars survive for a long time as main-sequence stars. In the present study we examine the post-collapse evolution of globular clusters using two-component Fokker-Planck models that include three-body binary heating. We confirm that a simple parameter ${\epsilon}{\equiv} (E_{tot}/t_{rh})/(E_c/t_{rc})$ well describes the occurrence of gravothermal oscillations of two-component clusters. Also, we find that the degree of instability depends on the steepness of the mass function such that clusters with a steeper mass function are less exposed to instability.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.272-279
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• 2002

A common task in assembly modeling is the determination of the position and orientation of a set of components by solving the spatial relationships between them. Assembly models could be constructed at various levels of abstraction. They could be classified into component or geometry-level assembly models. The geometry-level assembly design approach using mating constraints such as against and fits is widely used in the commercial modelers, but it may be very tedious in some cases fur designer. In this paper, we propose a new method to construct an assembly model at the component-level by extracting joint mating features from the kinematics constraints specified between components. The assembly model constructed using the proposed method includes hierarchical and relational assembly models, component/sub-assembly positions and degrees of freedom information. The proposed method is more intuitive and natural way of assembly design and it guarantees the topological robustness of assembly modification such as component replacement and modification.

• Fire Science and Engineering
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• v.10 no.2
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• pp.28-39
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• 1996

A recently developed electro-thermal simulation methodology is used to analyze the behavior of a PWM(Pulse-Width-Modulated) voltage source inverter which uses IGBT(Insulated Gate Bipolar Transistor) as the switching devices. In the electro-thermal network simulation methdology, the simulator solves for the temperature distribution within the power semiconductor devices(IGBT electro-thermal model), control logic circuitry, the IGBT gate drivers, the thermal network component models for the power silicon chips, package, and heat sinks as well as the current and voltage within the electrical network. The thermal network describes the flow of heat form the chip surface through the package and heat sink and thus determines the evolution of the chip surface temperature used by the power semiconductor device models. The thermal component model for the device silicon chip, packages, and heat sink are developed by discretizing the nonlinear heat diffusion equation and are represented in component from so that the thermal component models for various package and heat sink can be readily connected to on another to form the thermal network.