• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.716-721
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• 2010

In this work we address the use of support vector machine (SVM) in the multi-class gas classification system. The objective is to classify single gases and their mixture with a semiconductor-type electronic nose. The SVM has some typical multi-class classification models; One vs. One (OVO) and One vs. All (OVA). However, studies on those models show weaknesses on calculation time, decision time and the reject region. We propose a hierarchical clustering method (HCM) based on the SVM for real-time gas mixture classification. Experimental results show that the proposed method has better performance than the typical multi-class systems based on the SVM, and that the proposed method can classify single gases and their mixture easily and fast in the embedded system compared with BP-MLP and Fuzzy ARTMAP.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1104-1106
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• 1996

In this paper, a hierarchical fuzzy controller is proposed for the stabilization control of the inverted pendulum system. The design of controller for that system is difficult because of its complicated nonlinear mathematical model with unknown parameters. Conventional fuzzy control strategy based only on dynamics of pendulum made have failed to stabilize. However, proposed control strategies are to swing pendulum from natural stable up equilibrium point to an unstable equilibrium point and are to transport a cart from an arbitrary position toward a center of rail. Thus, the proposed fuzzy stabilization controller have a hierarchical fuzzy inference structure; that is, the lower level is for inference interface for the virtual equilibrium point and the higher level one for the position control of cart according to the firstly inferred virtual equilibrium point.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.57-69
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• 2001

This study propose a image processing system of unsupervised analysis. This system integrates low-level segmentation and high-level classification. The segmentation and classification are conducted respectively with and without spatial constraints on merging by a hierarchical clustering procedure. The clustering utilizes the local mutually closest neighbors and multi-window operation of a pyramid-like structure. The proposed system has been evaluated using simulated images and applied for the LANDSATETM+ image collected from Youngin-Nungpyung area on the Korean Peninsula.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.302-303
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• 2011

Smart WAMAC (Wide Area Monitoring And Control) System, which supplements control function with the function of WAMS(Wide Area Monitoring System), is an intelligent system not only monitoring the wide area but controlling the power equipment according to defined procedure. This paper presents WAMAC system architecture for hierarchical Infra and considerations to design and implement.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1743_1744
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• 2009

In this paper, we propose a double network control approach for linear systems. Generally, there are two network control system structures: the direct structure and the hierarchical structure. Here, the hierarchical structure consists of a main controller and a remote controller. The network delay of the structure only appears in the closed loop between the main controller and the remote system. However, the delay can exist between the remote controller and the actuator. Therefore, we design the double network system with delays between the main controller and the remote system, and the remote controller and the actuator. Finally, we carry out simulations on the linear system to illustrate the effectiveness of the proposed control method.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.103-118
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• 1995

This paper is concerned with developing flow control method for a dynamic multistage manufacturing system with interstage buffers and unreliable machines. For the effective control of proposed manufacturing system, the three-level hierarchical scheme is introduced. At the top level, we collect the system data and then, design the buffer sizes and hedging points. Short-term production rates are calculated at the middle level. At the bottom level, actual dispatching times are determined by Clear the Largest Buffer Level rule. The control method utilizes the material and the space in the buffers to alleviate the propagation of a failure to other machines in the system and keeps the production close to demand. Finally, a numerical example is provided to illustrate the mathematical control method developed and implemented in a dynamic manufacturing environment.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.763-768
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• 1994

A hierarchical Petri- net is utilized in supervising an automated vehicle system, The supervisory system is supported by computer networking in order to facilitate necessary processing, and consists of control flow level and computer allocation level so that a designer and an operator can easily build and/or access to each level. There are two modes of utilizing Petri net here in this paper. One is to employ it in designing the control system, in order to optimally allocate computers in every stage of processing. The other is for supervision of the system in operation, in order for the operator to be in a easy-to-comprehend environment of operation. The effect of these two modes of utilizing Petri net is examined.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• Tribology and Lubricants
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• v.26 no.2
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• pp.129-135
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• 2010

Geckos have a unique ability to cling to ceilings and walls utilizing dry adhesion. Their foot pads are covered by a large number of small hairs (setae) that contain many branches per seta with a lower level of spatulae. Their fibrillar structure is the primary source of high adhesion. In this study, we construct the adhesion design database for biomimetic adhesive system. A simple idealized fibrillar structure consisting of single array of beams is modeled. The fibers are assumed as oriented cylindrical cantilever beams with spherical tip. We consider three necessary conditions; buckling, fracture and sticking of fiber structure, which constrain the allowed geometry. The adhesion analysis is performed for the attachment system in contact with rough surfaces with different s values for different main design variables-fiber radius, aspect ratio and material elastic modulus and so on. The developed adhesion design databases are useful for understanding biological systems and for guiding of fabrication of the biomimetic attachment system.