• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.197-205
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• 2013

Real time transient stability assessment mainly depends on real-time prediction. Unfortunately, conventional techniques based on offline analysis are too slow and unreliable in complex power systems. Hence, fast and reliable stability prediction methods and simple stability criterions must be developed for real time purposes. In this paper, two new methods for real time determining critical clearing time based on clustering identification are proposed. This article is covering three main sections: (i) clustering generators and recognizing critical group; (ii) replacing the multi-machine system by a two-machine dynamic equivalent and eventually, to a one-machine-infinite-bus system; (iii) presenting a new method to predict post-fault trajectory and two simple algorithms for calculating critical clearing time, respectively established upon two different transient stability criterions. The performance is expected to figure out critical clearing time within 100ms-150ms and with an acceptable accuracy.

• ETRI Journal
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• v.33 no.2
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• pp.176-183
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• 2011

This paper presents a new analytical approach and experimental verification for the improvement of noise performance in phased-array receivers. For analysis purposes, a multi-channel array system is converted into an equivalent single-channel system, such that the two presents the identical signal and noise powers at the output, respectively. We define an effective gain, noise figure, and signal-to-noise ratio in the equivalent system. Through the proposed approach, the noise performance of the array receiver is analyzed in a general and straightforward manner and then compared to that of each individual array channel. In addition, the phase noise of the array system is analyzed in a rigorous manner, showing its effective reduction by a factor of the array size. The predicted improvement of the noise performance is experimentally confirmed with a CMOS integrated phased-array receiver.

• The Journal of Information Systems
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• v.14 no.3
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• pp.53-58
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• 2005

In this study, we will employ a multi-agent for the search and extraction of data in a distributed environment. We will use an Integrator Agent in the proposed model on the Hierarchical Clustering and Association Rule Discovery(HCARD). The HCARD will address the inadequacy of other data mining tools in processing performance and efficiency when use for knowledge discovery. The Integrator Agent was developed based on CORBA architecture for search and extraction of data from heterogeneous servers in the distributed environment. Our experiment shows that the HCARD generated essential association rules which can be practically explained for decision making purposes. Shorter processing time had been noted in computing for clusters using the HCARD and implying ideal processing period than computing the rules without HCARD.

• Journal of the Korean Society of Safety
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• v.18 no.3
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• pp.94-100
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• 2003

Gel-like compounds containing flammable solvents were prepared to use fur cleaning agents in field of innovative industries and general purposes. And experiments were conducted to improve the defects of liquified flammable solvents from the view point of safety and health hazards. Flammable solvents used in this study were several single component flammable solvents(turpentine oil, N-methyl-2-pyrrolidone(NMP), d-limonene) and multi component flammable solvent(gasoline and ethanol). For gelation of flammable solvents, commercially Known as Aerosil(equation omitted) 200 fumed silica and triethanolamine(TEA) were used as gelation agent dispersant. The analyses on properties of gel-like compounds was studied by gelation and viscosity test pH test, volatility test and differential scanning calorimetry(DSC) measurement. The experimental results indicate that gel-like compounds containing flammable solvents have pH stability, high viscosity, volatile organic compounds(VOC) control by the decrease of volatility and odor component generation, fluidity control etc. From the experimental values, it can be predicted that the safety in the working place is improved by manufacturing flammable solvents into gel-like compounds.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.721-726
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• 2005

In this study, researchers classifying the artificial flaws in semiconductor. packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method for entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1807-1820
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• 2008

The station area development planed to improve the old and narrowed station and to enhance the train passenger's convenience through private capital attraction in the past. But it has been faced with difficulty for the creative of transfer demand. Because of lean upon building facilities were caused by shortage of business profitability as to development of the upside a railway line, and lack of public utilities. The station area development requires that it's trend to large scale development of station areas, korail's direct development, deputation of specialty company to development, collaboration between local government and korail in development, diversification of process & installed facility, building multi-transfer center and one-stop transfer system. This trend caused by low profitability in development of the upside a railway line. The purposes of study are to make the system and law reflected to the property of station area development, investment in kind of needed land, and change railroad areas to high-rise and complex development, and make a forum between government and korail, etc.

• International Journal of Contents
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• v.14 no.4
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• pp.57-64
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• 2018

Among many UNESCO world heritage sites in Korea, "Historic Village: Hahoe" is adjacent to Nakdong River and it is imperative to monitor the water level near the village in a bid to forecast floods and prevent disasters resulting from floods.. In this paper, we propose a recurrent neural network with multiple hidden layers to predict the water level near the village. For training purposes on the proposed model, we adopt the sixth-order error function to improve learning for rare events as well as to prevent overspecialization to abundant events. Multiple hidden layers with recurrent and crosstalk links are helpful in acquiring the time dynamics of the relationship between rainfalls and water levels. In addition, we chose hidden nodes with linear rectifier activation functions for training on multiple hidden layers. Through simulations, we verified that the proposed model precisely predicts the water level with high peaks during the rainy season and attains better performance than the conventional multi-layer perceptron.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.145-161
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• 2021

Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.119-132
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• 2021

To accommodate various mobile communication frequency bands, the study of metamaterial antennas have begun since the mid-2000s to solve the Trilemma problem between antenna gain-occupied bandwidth-size. As an adaptive reconfiguration function is required in a multi-array antenna system since 4G, the metamaterial array antenna using low-power variable elements has been used to change the basic structure of the antenna. Recently, reconfigurable intelligent surface (RIS), which is made of metasurface with reconfigurability, has been studied to effectively cope with the randomly varying radio channels and be used for various purposes such as reflection/transmission/modulation. As a result of RIS-related patent information analysis in this study, it was confirmed that most of the patents are metamaterial antennas and metamaterial array antennas, but the metasurface antenna technology was in the early stages. Particularly, as the intelligent metasurface antenna is in a more initial stage, the investment to R&D of RIS is urgent to secure patent competitiveness in B5G and 6G.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.341-352
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• 2023

This paper reviews the potentials of a rotary chemical vapor deposition (RCVD) process for nanomaterial synthesis and coating on powder-based materials. The rotary reactor offers a significant improvement over traditional CVD methods having horizontal and fixed reaction chambers. The RCVD system yields enhanced productivity and surface coating uniformity of nanoparticles applied in various purposes, such as efficient heat dissipation, surface hardness enhancement, and enhanced energy storage performances. The effectiveness of the RCVD system would open up new possibilities in various applications because uniform coating on powder-based materials with massive productivity is inevitable to develop multi-functional materials with high reliability.