• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.961-963
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• 1998

Power telecommunication networks, being used to support the operation and management of power utility services, exhibits different characteristics from those of public domain networks. KEPCO is planning to evolve its own power network infrastructure to exploit ATM (Asynchronous Transfer Mode) technology. The ATM network to be developed needs to effectively utilize existing network of KEPCO and to fully support new and emerging power-utility-services. This paper summarizes the features of power communication services and the characteristics of Power telecommunication networks, and reports our evolution methodology for KEPCO network.

• Korean System Dynamics Review
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• v.17 no.3
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• pp.31-50
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• 2016

This study examines the basic conditions of joint authorship research activities in the Korean System Dynamics Review and points out the structural co-author network characteristics among co-authored papers based on the social network analysis(SNA) techniques. In specific, this study identifies the cooperative relationship of research papers in the Korean System Dynamics Review, knowledge formation, and knowledge propagation paths. The study results imply that Korean System Dynamics Review has exhibited the typical 'Steven's power law,' which is repeatedly observed among complex systems, and that knowledge structure centered upon and propagated around couples of researchers. Additionally, the study results present that there have been active personal exchanges among major researchers. In contrast, personal contacts among research groups and within groups seem relatively weak.

• Journal of the Korean Society for Railway
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• v.6 no.2
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• pp.81-86
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• 2003

This study proposes the neural network simulator for the integrity evaluation of weld zone in railway rails. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The constructed neural network simulator agrees fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). The Proposed neural network simulator in this study can be used for the integrity evaluation of weld zone in railway rails.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.64-69
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• 2021

In this paper, a method for improving the defect classification performance in low contrast, ununiformity and featureless steel plate surfaces has been studied based on deep convolution neural network and transfer-learning neural network. The steel plate surface images have low contrast, ununiformity, and featureless, so that the contrast between defect and defect-free regions are not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. A classifier based on a deep convolution neural network is constructed to extract features automatically for effective classification of images with these characteristics. As results of the experiment, AlexNet-based transfer-learning classifier showed excellent classification performance of 99.43% with less than 160 seconds of training time. The proposed classification system showed excellent classification performance for low contrast, ununiformity, and featureless surface images.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1448-1453
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• 2004

The major parameters governing the fluid dynamical and thermo-dynamical behavior in the large pipeline network system are friction loss and the pipeline length. But in local pipeline networks and relatively short distance pipeline system, secondary loss and the considerations of the moving states of the fluid machine are also important. One of the major element in local pressure control system is pressure regulator. It causes the variations of the physical properties in that pipeline system. Especially, as there is not enough information to obtain reliable physical property values such as density, temperature etc. at the downstream of the pressure regulator, It is hard to calculate accurate solution in the pipeline network analysis. In this study, some numerical approaches to investigate the critical-flow-characteristics of the pressure regulator have been done and the detail examinations and considerations of the pressure regulator as a pipeline network elements according to the variations of the inlet-outlet pressure ratio have been carried. Finally the flow-flied distributions, relations and critical-flow-characteristics have been studied. in detail and the 1D analytic method to analyze critical pipe flow have been investigated

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1854-1862
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• 2001

In this paper, power flow characteristics of a hydromechanical transmission(HMT) are investigated using network analysis. The HMT used in this study consist of a hydrostatic unit(HSU), planetary gear sets, clutches and brakes providing forward 4 speeds and backward 2 speeds. Since the HMT power flows showing a closed loop and the HSU efficiency varies depending on the pressure and speed, a systematic approach is required to analyze the power transmission characteristics of the HMT. In order to analyze the closed loop power flow and the HSU power loss which changes depending on the pressure and speed, network model is constructed fur each speed range. In addition, an algorithm is proposed to calculate an accurate HSU loss corresponding to the experimental results. It is found from the network analysis that the torque and speed of each transmission element including the HSU can be obtained as well as direction of the power flow by the proposed algorithm. It is expected that the network analysis can be used in the design of relatively complicated transmission system such as HMT.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.519-524
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• 2001

In this paper, power flow characteristics of a hydromechanical transmission(HMT) are investigated using network analysis. The HMT used in this study consist of a hydrostatic unit(HSU), planetary gear sets, clutches and brakes providing forward 4 speeds and backward 2 speeds. Since the HMT power flows showing a closed loop and the HSU efficiency varies depending on the pressure and speed, a systematic approach is required to analyze the power transmission characteristics of the HMT. In order to analyze the closed loop power flow and the HSU power loss which changes depending on the pressure and speed, network model is constructed for each speed range. In addition, an algorithm is proposed to calculate an accurate HSU loss corresponding to the experimental results. It is found from the network analysis that the torque and speed of each transmission element including the HSU can be obtained as well as direction of the power flow by the proposed algorithm. It is expected that the network analysis can be used in the design of relatively complicated transmission system such as HMT.

• Journal of the Korean Society for Railway
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• v.7 no.3
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• pp.264-270
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• 2004

The hub-and-spoke strategy is widely used in the field of transportation. At the field of rail transportation, however, it is difficult that we find an application case of this strategy because of modal characteristics. According to the fast growth of containerization and the development of transshipment technology, presently, the hub-and-spoke strategy is introduced by operators on actual European rail freight transportation. However, it is hardly to find empirical studies evaluating the applicability of transportation strategy. In this context, this study analyzed the applicabilities of hub-and-spoke strategy in the actual network of European rail freight. For the application and evaluation of the characteristics of hub-and-spoke strategy, it utilized a service network design model for rail freight. Utilizing this model, it analyzed the efficiency of furnished rail freight services, the potential locations of hubs, the characteristics of O-D flows by the types of trains and service links, and the types of paths of O-D flows. Finally, it proposed some implications and the further study topics.

• Journal of Power Electronics
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• v.18 no.1
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• pp.289-299
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• 2018

Electric-field coupled power transfer (ECPT) systems employ a high frequency electric field as an energy medium to transfer power wirelessly. Existing ECPT systems have made great progress in terms of increasing the transfer distance. However, the topologies of these systems are complex, and the transfer characteristics are very sensitive to variations in the circuit parameters. This paper proposes an ECPT system with a double-sided LC network, which employs a parallel LC network on the primary side and a series LC network on the secondary side. With the same transfer distance and output power, the proposed system is simpler and less sensitive than existing systems. The expression of the optimal driving voltage for the coupling structure and the characteristics of the LC networks are also analyzed, including the transfer efficiency, parameter sensitivity and total harmonic distortion. Then, a design method for the system parameters is provided according to these characteristics. Simulations and experiments have been carried out to verify the system properties and the design method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.57-66
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• 2007

Scanning worms increase network traffic load because they randomly scan network addresses to find hosts that are susceptible to infection. Since propagation speed is faster than human reaction, scanning worms cause severe network congestion. So we need to build an early detection system which can automatically detect and quarantine such attacks. We propose algorithms to detect scanning worms using network traffic characteristics such as variance, variance to mean ratio(VMR) and correlation coefficient. The proposed algorithm have been verified by computer simulation. Compared to existing algorithm, the proposed algorithm not only reduced computational complexity but also improved detection accuracy.