• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.142-149
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• 2004

This paper presents a neural network controller of a grid-connected wind energy conversion system for extracting maximum power from wind and a power controller to transfer the maximum power extracted into a utility grid. It discusses the modeling and simulation of the wind energy conversion system with the controllers, which consists of an induction generator, a transformer, a link of a rectifier, and an inverter. The paper describes tile drive train model, induction generator model and grid-interface model for dynamics analysis. Maximum power extraction is achieved by controlling the pitch angle of the rotor blades by a neural network controller. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation. The simulation results performed on MATLAB show the variation of the generator torque, the generator rotor speed, the pitch angle, and real/reactive power injected into the grid, etc. Based on the simulation results, the effectiveness of the proposed controllers is verified.

• Journal of Power Electronics
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• v.13 no.4
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10A
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• pp.1717-1726
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• 2001

본 논문에서는 CORBA(Common Object Request Architecture)기반의 TINA(Telecommunications Information Networking Architecture) 분산체계에서 통신망 하부 장비들이 SNMP(Simple Network Management Protocol) 혹은 TMN(Telecommunications Management Network) 체계로 혼재되어 관리되는 네트워크의 NE(Network Element)들을 효율적으로 통합 관리할 수 있는 Generic Interface Adaptor(GIA)를 제안하고 이를 설계 및 구현하였다. GIA는 message mapping, protocol conversion 및 DBMS를 이용한 Object Abstract Translation(OAT)을 통해서 각 관리체계에 맞도록 관리정보를 변환시키며, 이를 통해 TINA EML(Element Management Layer) component와 SNMP NE agent 간의 상호연동을 가능하게 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1113-1122
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• 1999

In this paper, we propose MSS(Multicast Synchronization Server) and QCS(QoS Conversion Server) models that can support IP multicast and QoS(Quality of Service) over the ATM network more efficiently. In the MSS model, it is possible to establish shortcut VCs(Virtual Circuits) among all hosts in the ATM network and to transfer multicast data at high speed. Also the MSS model is more scalable, because the number of inter-cluster VCs needed in the MSS model is less than that of EARTH. In the QCS model, ATM switch is modified to support one QoS service and best effort service through the one point-to-multipoint VC at the same time so required network resources are reduced, and dedicated server is used for QoS conversion to accept heterogeneous receivers more efficiently. In this Paper, the proposed MSS model and QCS model have solved both efficiency problem and scalability problem. It is proved through the comparison of the VCs required in each model.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.77-85
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• 2003

The conversion into a new Local Area Network (LAN) environment without clear analysis of the problems with the conventional LAN environment nay bring about some improvement of performance, but in general, the result would not be as good as expected. Besides, in case new traffic or application programs are added In the near future, traffic overload similar to the past may incur. Therefore, the conversion into a new LAN environment should not only relieve the problems with the conventional environment but also be able to cope with future expansion of the network flexibly. In the present paper, in view of the above, the problems with protocols and traffic that may occur in the Bus-structured 10/100 Mbps shared Ethernet that has been widely used by many institutions are reviewed, and as a case study whether such conversion into a new LAN environment in order to increase the efficiency in the operation, management, and utilization of the network would be proper for the actual operational environment is implemented, and the results are analyzed.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.171-178
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• 2006

The seismological observation of Korea began in 1905, and has been run with continuous earthquake network of observation, expanding to the advanced country, but still has some problems in accuracy and speed for report. There are many problems to announce the early warning system for earthquakes and tsunami in the East Sea because most events in the East Sea occur outside the seismic network. Therefore multi-waveform data conversion and composition from the surrounding countries such as Korea, Japan and Far East Russia are requested in order to improve more accurate determination of the earthquake parameters. We used FESNET(Far East Seismic Network) technology to analyze the May 29 and June 1 Earthquakes, and the March 20, 2005 Fukuoka Earthquake in this research, using the data sets of KMA, Japan(JMA/MIED) and IRIS stations. It was found out that use of FESNET resulted in more better outputs than that of a single network, either KMA or JMA stations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.165-170
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• 2020

The spiking neural network operates in a different mechanism than the existing neural network. The existing neural network transfers the output value to the next neuron via an activation function that does not take into account the biological mechanism for the input value to the neuron that makes up the neural network. In addition, there have been good results using deep structures such as VGGNet, ResNet, SSD and YOLO. spiking neural networks, on the other hand, operate more like the biological mechanism of real neurons than the existing activation function, but studies of deep structures using spiking neurons have not been actively conducted compared to in-depth neural networks using conventional neurons. This paper proposes the method of loading an deep neural network model made from existing neurons into a conversion tool and converting it into a spiking deep neural network through the method of replacing an existing neuron with a spiking neuron.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.484.2-484.2
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• 2014

There are many efforts to improving the power conversion efficiencies (PCEs) of dye-sensitized solar cells (DSCs). Although DSCs have a low production cost, their low PCE and low thermal stability have limited commercial applications. This study describes the preparation of a novel multifunctional polymer gel electrolyte in which a cross-linking polymerization reaction is used to encapsulate $TiO_2$ nanoparticles toward improving the power conversion efficiency and long-term stability of a quasi-solid state DSC. A series of liquid junction dye-sensitized solar cells (DSCs) was fabricated based on polymer membrane encapsulated dye-sensitized $TiO_2$ nanoparticles, prepared using a surface-induced cross-linking polymerization reaction, to investigate the dependence of the solar cell performance on the encapsulating membrane layer thickness. The ion conductivity decreased as the membrane thickness increased; however, the long term-stability of the devices improved with increasing membrane thickness. Nanoparticles encapsulated in a thick membrane (ca. 37 nm), obtained using a 90 min polymerization time, exhibited excellent pore filling among $TiO_2$ particles. This nanoparticle layer was used to fabricate a thin-layered, quasi-solid state DSC. The thick membrane prevented short-circuit paths from forming between the counter and the $TiO_2$ electrode, thereby reducing the minimum necessary electrode separation distance. The quasi-solid state DSC yielded a high power conversion efficiency (7.6/8.1%) and excellent stability during heating at $65^{\circ}C$ over 30 days. These performance characteristics were superior to those obtained from a conventional DSC (7.5/3.5%) prepared using a $TiO_2$ active layer with the same thickness. The reduced electrode separation distance shortened the charge transport pathways, which compensated for the reduced ion conductivity in the polymer gel electrolyte. Excellent pore filling on the $TiO_2$ particles minimized the exposure of the dye to the liquid and reduced dye detachment.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.23-34
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• 1998

Travel time forecasting, especially public bus travel time forecasting in urban areas, is a difficult and complex problem which requires a prohibitively large computation time and years of experience. As the network of target area grows with addition of streets and lanes, computational burden of the forecasting systems exponentially increases. Even though the travel time between two neighboring intersections is known a priori, it is still difficult, if not impossible, to compute the travel time between every two intersections. For the reason, previous approaches frequently have oversimplified the transportation network to show feasibilities of the problem solving algorithms. In this paper, forecasting of the travel time between every two intersections is attempted based on travel time data between two neighboring intersections. The time stamps data of public buses which recorded arrival time at predetermined bus stops was extensively collected and forecast. At first, the time stamp data was categorized to eliminate white noise, uncontrollable in forecasting, based on wavelet conversion. Then, the radial basis neural networks was applied to remaining data, which showed relatively accurate results. The success of the attempt was confirmed by the drastically reduced relative error when the nodes between the target intersections increases. In general, as the number of the nodes between target intersections increases, the relative error shows the tendency of sharp increase. The experimental results of the novel approaches, based on wavelet conversion and neural network teaming mechanism, showed the forecasting methodology is very promising.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.67-76
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• 2010

Although both functional verification and performance evaluation are necessary for the development of effective and reliable communication systems, they have been often performed independently; by functional modeling with formal language tools and by performance modeling with professional network performance evaluation tools, respectively. Separate and repeated modeling of one system, however, would often result in cost increase and inconsistency between the models. This paper proposes an integrated model design approach in order to overcome this problem that evaluates the performance of a communication protocol designed in SDL with SDL-OPNET model conversion. The proposed technique generates OPNET skeleton code from Tau-generated C code of the SDL model by analyzing the relations between SDL and OPNET models. IEEE 802.2 LLC protocol was used as an example of model conversion to show the applicability and effectiveness of the proposed technique.