• Proceedings of the Korean Association for Survey Research Conference
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• 2003.06a
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• pp.140-160
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• 2003

The purpose of this study is to identify and evaluate the competitiveness of ports in ASEAN(Association of Southeast Asian Nations), which plays a leading role in basing the hub of international logistics strategies as a countermeasure in changes of international logistics environments. This region represents most severe competition among Mega hub ports in the world in terms of container cargo throughput at the onset of the 21st century. The research method in this study accounted for over lapping between attributes, and introduced the HFP method that can perform mathematical operations. The scope of this study was strictly confined to the ports of ASEAN, which cover the top 100 of 350 container ports that were presented in Containerization International Yearbook 2002 wi th reference to container throughput. The results of this study show Singapore in the number one position. Even compared with major ports in Korea (after getting comparative ratings and applying tile same data and evaluation structure), the number one position still goes to Singapore and then Busan(2) and Manila(2), followed by Port Klang(4), Tanjung Priok(5), Tanjung Perak(6), Bangkok(7), Inchon(8), Laem Chabang(9) and Penang(9). In terms of the main contributions of this study, it is the first empirical study to apply the combined at tributes of detailed and representative attributes into the advanced HFP model which was enhanced by the KJ method to evaluate the port competitiveness in ASEAN. Up-to-now, none have comprehensively conducted researches with sophisticated port methodology that has discussed a variety of changes in port development and terminal transfers of major shipping lines. Moreover, through the comparative evaluation among major ports in Korea and ASEAN, the presentation of comparative competitiveness for Korean ports is a great achievement in this study. In order to reinforce this study, it needs further compensative research, including cost factors which could not be applied to modeling the subject ports by lack of consistently qualified data in ASEAN.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.576-583
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• 2018

Silicon carbide is considered to be a potentially useful material for high-temperature electronic devices, as its band gap is larger than that of silicon and the p-type and/or n-type conduction can be controlled by impurity doping. Particularly, porous n-type SiC ceramics fabricated from ${\beta}-SiC$ powder have been found to show a high thermoelectric conversion efficiency in the temperature region of $800^{\circ}C$ to $1000^{\circ}C$. For the application of SiC thermoelectric semiconductors, their figure of merit is an essential parameter, and high temperature (above $800^{\circ}C$) electrodes constitute an essential element. Generally, ceramics are not wetted by most conventional braze metals,. but alloying them with reactive additives can change their interfacial chemistries and promote both wetting and bonding. If a liquid is to wet a solid surface, the energy of the liquid-solid interface must be less than that of the solid, in which case there will be a driving force for the liquid to spread over the solid surface and to enter the capillary gaps. Consequently, using Ag with a relatively low melting point, the junction of the porous SiC semiconductor-Ag and/or its alloy-SiC and/or alumina substrate was studied. Ag-20Ti-20Cu filler metal showed promise as the high temperature electrode for SiC semiconductors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.1-10
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• 2004

Quite many papers about moving objects database (MOD) have been Published. Most of them are concerning of improving efficiency of updating policy, but none of them talks about verification of system's requirements. No matter how efficient updating policy is employed, a system designer still has to verify if the MOD satisfies user's requirement at the beginning of system lifestyle. For example, if a MOD serves n moving objects, then the designer must verity if it can update information for n moving objects and provide new information to moving objects within specified time limit. For the purpose of requirement analysis of MODs, we build a Petri net model for MOD using Design/CPN, and then we show how to verify whether the MOD satisfies user's requirements by simulation. The contribution of this paper is providing a simulation model for requirement analysis of MOD for the first time. The model is expansion of our previous fuzzy-timing Petri net model. The distance-based updating policy, and distributed database management system are reflected in this model and system analysis for moving objects is considered. It is built in Design/CPN so that the simulation can be automatically performed. The application of our model is not limited to requirement analysis, it is useful to study other MOD design issues, such as the trade-offs between update cost and information accuracy, and between the tim interval needed for updating database and MOD system resources, etc.