• Communications for Statistical Applications and Methods
• /
• v.24 no.1
• /
• pp.97-113
• /
• 2017

This paper proposes a method for sufficient dimension reduction (SDR) of mixture data. We consider mixture data containing more than one component that have distinct central subspaces. We adopt an approach of a model-based sliced inverse regression (MSIR) to the mixture data in a simple and intuitive manner. We employed mixture probabilistic principal component analysis (MPPCA) to estimate each central subspaces and cluster the data points. The results from simulation studies and a real data set show that our method is satisfactory to catch appropriate central spaces and is also robust regardless of the number of slices chosen. Discussions about root selection, estimation accuracy, and classification with initial value issues of MPPCA and its related simulation results are also provided.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1449-1454
• /
• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.4
• /
• pp.58-66
• /
• 1998

In many situations, it is very important to identify a certain unkown system, it from its input-output data. For this purpose, several system modeling algorithms have been suggested heretofore, and studies regarding the fuzzy modeling based on its nonlinearity get underway as well. Generatlly, fuzzy models have the capability of dividing input space into several subspaces, compared to linear ones. But hitherto subggested fuzzy modeling algorithms do not take into consideration the correlations between components of sample input data and address them independently of each other, which results in ineffective partition of input space. Therefore, to solve this problem, this letter proposes a new fuzzy modeling algorithm which partitions the input space more efficiently that conventional methods by taking into consideration correlations between components of sample data. As a way to use correlation and divide the input space, the method of principal component is ued. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.

• Structural Engineering and Mechanics
• /
• v.18 no.5
• /
• pp.691-707
• /
• 2004

This paper presents the micro-mechanical modeling for predicting concrete behavior under compressive loading. The model is able to represent the heterogeneities in the microstructure up to three phases, i.e., aggregate particles, matrix and interfaces. The smeared crack concept based on non-linear fracture mechanics is implemented in order to formulate the constitutive relation for each component. The splitting tensile strength is considered as a fracture criterion for cracking in micro-level. The finite element method is employed to simulate the model based on plane stress condition by using quadratic triangular elements. The validation of the model is verified by comparing with the experimental results. The influence of tensile strength from both aggregate and matrix phases on the concrete compressive strength is demonstrated. In addition, a guideline on selecting appropriate tensile strength for each phase to obtain specified concrete compressive strength is also presented.

• Korean Journal of Computational Design and Engineering
• /
• v.3 no.1
• /
• pp.68-85
• /
• 1998

Solid modeling refers to techniques for unambiguous representations of three-dimensional objects. Feature recognition is a sub-discipline focusing on the design and implementation of algorithms for detecting manufacturing information such as holes, slots, etc. in a solid model. Automated feature recognition has been an active research area in stolid modeling for many years, and is considered to be a critical component for CAD/CAM integration. This paper gives a technical overview of the state of the art in feature recognition research. Rather than giving an exhaustive survey, I focus on the three currently dominant feature recognition technologies: graph-based algorithms, volumetric decomposition techniques, and hint-based geometric reasoning. For each approach, I present a detailed description of the algorithms being employed along with some assessments of the technology. I conclude by outlining important open research and development issues.

• Journal of information and communication convergence engineering
• /
• v.2 no.1
• /
• pp.40-45
• /
• 2004

This paper describes a modeling of service composition manager based on TINA (Telecommunication Information Networking Architecture). The Service composition function is mainly motivated by the desire to easily generate new service using existing services from retailers or $3^{rd}$-party service providers. The TINA-C specification for the service composition does not include the detailed composition procedure and its object models. In this paper, we propose a model of components for the service composition, which adapts a static composition feature in a single provider domain. To validate the proposed modeling, we implemented prototype service composition function, which combines two multimedia services; a VOD service and a VCS service. As a result, we obtain the specification of the detailed composition architecture between a retailer domain and a $3^{rd}$-party service provider domain.

• International Journal of Computer Science & Network Security
• /
• v.24 no.6
• /
• pp.180-186
• /
• 2024

A common language for modelling software requirements and design in recent years is Unified Modeling Language (UML). Essential principles and rules are provided by UML to help visualize and comprehend complex software systems. It has therefore been incorporated into the curriculum for software engineering courses at several institutions all around the world. However, it is commonly recognized that UML is challenging for beginners to understand, mostly owing to its complexity and ill-defined nature. It is unavoidable that we need to comprehend their preferences and issues considerably better than we do presently in order to approach the problem of teaching UML to beginner students in an acceptable manner. This paper offers a hint based approach that can be implemented along with an ordinary lab task. Some keywords are heighted to indicate class diagram component and make students to understand the textual descriptions. The experimental results indicate significant improvement in students learning skills. Furthermore, majority of students also positively responded to the survey conducted in the end experimental study.

• Journal of KIISE:Software and Applications
• /
• v.27 no.3
• /
• pp.227-240
• /
• 2000

The research of the variability gains more gravity in component-based software development, because it helps to extend the reusability of the component. A domain-specific component supports the more variability, the wider scope that the component can be applied to. However, the more variability included in a component, It makes the size of a component bigger, and the cost to construct the component is rises. As a result, this disturbs making an optimized system. In this paper, we classify the variability into 3 types, according to their features. And we propose some implementation techniques for each type based COM. Moreover, we also propose a process to analysis and design the variability with their artifacts, which includes some tasks from variability extraction to implementation of it. This proposed process can be applied as a part of the component developing process.

• The Journal of Society for e-Business Studies
• /
• v.10 no.3
• /
• pp.1-19
• /
• 2005

Ontology-based approaches for automated information integration are being widely investigated. The existing approaches explicitly represent the semantics of information sources in ontologies and let the computer system, through aligning or merging the source ontologies, provide a global view of information sources. The problem of aligning or merging different ontologies is a well known problem, and the inter-ontology mappings play an essential role in information integration. To enable simple and well-founded mappings , the ontologies of information sources should be modeled with the same world view and with the same manner of representation. This paper introduces an ontology modeling framework for component libraries, which is developed based on the Guarino's theory of upper ontology . This paper discusses the results of modeling ontologies of mold and die component libraries based on the framework. A Web-based implementation automatically merges the source ontologies.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.15 no.1
• /
• pp.45-54
• /
• 2011

A program aiming at predicting dynamic characteristics of a Liquid Rocket Engine(LRE) was developed and examined to trace entire LRE operation. In the startup period, transient characteristics of the propellant flows were predicted and validated with hydraulic tests data. An arrangement of each component for the pipelines was based on an operating circuit of open cycle LRE. The flow rate ratio for the gas generator and the main chamber was determined to mimic that of real open cycle LRE. Individual component modeling at its transient was completed and was integrated into the system prediction program. Essential parameters of the component dynamic characteristics were examined in an integrated fashion.