Jeong-Wook Park

This paper presents a novel optimal neurocontroller that replaces the conventional controller (CONVC), which consists of the automatic voltage regulator and turbine governor, to control a synchronous generator in a power system using a multilayer perceptron neural network (MLPN) and a radial basis function neural network (RBFN). The heuristic dynamic programming (HDP) based on the adaptive critic design technique is used for the design of the neurocontroller. The performance of the MLPN-based HD

This paper compares the performances of a multilayer perceptron neural network (MLPN) and a radial basis function neural network (RBFN) for online identification of the nonlinear dynamics of a synchronous generator in a power system. The computational requirement to process the data during the online training, local convergence, and online global convergence properties are investigated by time-domain simulations. The performances of the identifiers as a global model, which are trained at differe

This paper compares the performances of a multilayer perceptron network (MLPN) and a radial basis function network (RBFN) for the online identification of the nonlinear dynamics of a synchronous generator. Deviations of signals from their steady state values are used. The computational complexity required to process the data for online training, generalization and online global minimum testing are investigated by time-domain simulations. The simulation results show that, compared to the MLPN, th

Abstract The authors consider time series observations with data irregularities such as censoring due to a detection limit. Practitioners commonly disregard censored data cases which often result in biased estimates. The authors present an attractive remedy for handling autocorrelated censored data based on a class of autoregressive and moving average (ARMA) models. In particular, they introduce an imputation method well suited for fitting ARMA models in the presence of censored data. They demon

The controllable capacitive reactance can be used as the input variable for the external controller of a series capacitive reactance compensator (SCRC) to improve the damping of low-frequency oscillations of the rotor angle and active power in a power system. Conventional linear PI controllers are tuned for best performance at one specific operating point of the nonlinear power system. At other operating point its performance degrades. Nonlinear optimal neuro-controllers are able to overcome thi

This paper compares two indirect adaptive neurocontrollers, namely a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) to control a synchronous generator. The different damping and transient performances of two neurocontrollers are compared with those of conventional linear controllers, and analyzed based on the Lyapunov direct method.

Here we describe the application of a recently developed high-resolution microcantilever biosensor resonating at the air-liquid interface for the continuous detection of antigen-antibody and enzyme-substrate interactions. The cantilever at the air-liquid interface demonstrated 50% higher quality factor and a 5.7-fold increase in signal-to-noise-ratio (SNR) compared with one immersed in the purified water. First, a label-free detection of a low molecular weight protein (insulin, 5.8 kDa) in physi

This paper proposes the new hybrid energy storage system with the superconducting magnetic energy storage (SMES) and a lead-acid battery. The SMES is the most effective energy storage device due to its high power density, fast response, and high efficiency. However, its energy density is not higher than that of other batteries. Therefore, the proposed hybrid energy storage system combines these two energy storage devices. The optimal sizes of the SMES and battery are determined by considering th

The fire growth rate index (FIGRA), which is the ratio of the maximum value of the heat release rate (Qmax) and the time (tmax) to reach the maximum heat release rate, is a general method to evaluate a material in the fire-retardant performance in fire technology. The object of this study aims to predict FIGRA of the polyethylene foam pipe insulation in accordance with the scale factor (Sf), the volume fraction of the pipe insulation (VF) and the ignition heat source (Qig). The compartments made

건축물의 초고층화, 복합화, 비정형 및 생산성 증대, 지속가능성 등의 해소방안으로 BIM(Building Information Modeling)에 대한 관심도가 증가되었고, 국내에서도 BIM에 대한 관심이 높아져 건설관련업계에는 하루가 다르게 BIM 확산이 진행되고 있다. 따라서, BIM의 정의와 특징을 파악하고 국내와 해외의 사례를 검토하여 BIM의 성공적인 도입 방안에 대한 내용을 본 논문에서 분석하고자 하며, 아울러, 국내 BIM적용 사례를 비교분석 함으로써 국내 BIM적용의 문제점과 해결 방안을 모색하고자 한다. When faced with new projects, such as high-rise, complex, free-formed, and sustainable buildings, numerous participants in the building Industry use Building Information Modeling (BIM) technology. In 2009,

To elucidate the oncogenic H-Ras network, we have established various stable and inducible oncogenic H-Ras-expressing NIH/3T3 mouse embryonic fibroblast cell clones, which express G12V H-Ras and G12R H-Ras proteins under the influence of a strong cytomegalovirus promoter and under the tight control of expression by an antibiotic, doxycycline, respectively. Here we provide a catalogue of proteome profiles in total cell lysates derived from oncogenic H-Ras-expressing NIH/3T3 cells. In this biologi

This paper presents a sensitivity analysis of neural network (NN) parameters to improve the performance of electricity price forecasting. The presented work is an extended version of previous works done by authors to integrate NN and similar days (SD) method for predicting electricity prices. Focus here is on sensitivity analysis of NN parameters while keeping the parameters same for SD to forecast day-ahead electricity prices in the PJM market. Sensitivity analysis of NN parameters include back