• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.9-13
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• 2015

Energy storage systems (ESS) can be used to provide frequency regulation services in a power system to replace traditional frequency regulation power plants. Battery ESS, in particular, can provide "fast-responding frequency regulation," wherein the facility can respond immediately and accurately to the frequency regulation signal sent by the system operator. This paper presents the development and the trial run results of a frequency regulation control system that uses large-scale ESS for use in a large power system. The control system was developed initially for the 4 MW ESS demonstration facility in Jocheon Jeju Island, and was further developed for use in the 28 MW ESS facility at the Seo-Anseong substation and the 24 MW ESS facility at the Shin-Yongin substation to provide frequency regulation services within mainland Korea. The ESS facility in Seo-Anseong substation responds to a sudden drop in frequency via governor-free control, while the ESS facility in Shin-Yongin responds via automatic generator control (AGC).

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.365-372
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• 2022

The accurate object recognition is important for the precise and accurate manipulation. To enhance the recognition performance, we can use various types of sensors. In general, acquired data from sensors have a high sampling rate. So, in the past, the RNN-based model is commonly used to handle and analyze the time-series sensor data. However, the RNN-based model has limitations of excessive parameters. CNN-based model also can be used to analyze time-series input data. However, CNN-based model also has limitations of the small receptive field in early layers. For this reason, when we use a CNN-based model, model architecture should be deeper and heavier to extract useful global features. Thus, traditional methods like RN N -based and CN N -based model needs huge amount of learning parameters. Recently studied result shows that Fast Fourier Convolution (FFC) can overcome the limitations of traditional methods. This operator can extract global features from the first hidden layer, so it can be effectively used for feature extracting of sensor data that have a high sampling rate. In this paper, we propose the algorithm to recognize objects using tactile sensor data and the FFC model. The data was acquired from 11 types of objects to verify our posed model. We collected pressure, current, position data when the gripper grasps the objects by random force. As a result, the accuracy is enhanced from 84.66% to 91.43% when we use the proposed FFC-based model instead of the traditional model.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.14 no.4
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• pp.201-210
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• 2010

We propose a new robust and accurate method for the numerical solution of medical image segmentation. The modified Allen-Cahn equation is used to model the boundaries of the image regions. Its numerical algorithm is based on operator splitting techniques. In the first step of the splitting scheme, we implicitly solve the heat equation with the variable diffusive coefficient and a source term. Then, in the second step, using a closed-form solution for the nonlinear equation, we get an analytic solution. We overcome the time step constraint associated with most numerical implementations of geometric active contours. We demonstrate performance of the proposed image segmentation algorithm on several artificial as well as real image examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• Journal of the Korea Computer Industry Society
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• v.8 no.3
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• pp.155-166
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• 2007

In this paper, captured face-image was pre-processing, segmentation, and extracting features from thinning by differential operator and minute-delineation. A straight line in slope-intercept form was transformed at the $r-\theta$ domain using Hough Transform, instead of Housdorff distance are extract feature as length, rotation, displacement of lines from thinning line components by differentiation. This research proposed a new approach compare with Hough Transformation and Housdorff Distance for face recognition so that Hough transform is simple and fast processing of face recognition than processing by Housdorff Distance. Rcognition accuracy rate is that Housdorff method is higher than Hough transformation's method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.14 no.1
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• pp.35-42
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• 2010

A goal of Magnetic Resonance Imaging is reproducing a spatial map of the effective spin density from the measured Fourier coefficients of a specimen. The imaging procedure can be done by inverse Fourier transformation or backward fast Fourier transformation if the data are sampled on a regular grid in frequency space; however, it is still a challenging question how to reconstruct an image from a finite set of Fourier data on irregular points in k-space. In this paper, we describe some mathematical and numerical properties of imaging techniques from non-uniform MR data using the pseudo-inverse or the diagonal-inverse weight matrix. This note is written as an easy guide to readers interested in the non-uniform MRI techniques and it basically follows the ideas given in the paper by Greengard-Lee-Inati [10, 11].

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.60-63
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• 2004

An innovative in-core neutron flux mapping system has been developed and applied successfully for service in a commercial pressurized water reactor. With the benefit of double indexing path selector (Dip $s^{ⓡ}$) mechanism, the reliability of the detector drive system has been improved five times higher than that of conventional systems, and the problems caused by the serious friction generated between the detector cable and guide tubing has been solved completely because the Dip $s^{ⓡ}$ architecture allows the detector guide tubings to have larger curvature and shorter length in nature. The simple and fast maintenance is particularly emphasized in the detector drive system to secure minimum radiation exposure to the maintenance personnel by optimizing the number of components and providing easy access to the components. The programmable logic controller based digital controller with Window $s^{ⓡ}$ based operator s console provides fully automated and user friendly operation and maintenance support means.

• Nuclear Engineering and Technology
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• v.2 no.4
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• pp.249-254
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• 1970

A time-energy transient characteristics of pulsed neutron transport problem with an inelastic kernel in the fast domain is solved exactly with a continuous energy transfer operator. A discrete time eigenvalue is found which is asymptotically dominant. The complete solution consists of three parts: a time-energy separable mode which is asymptotically dominant and a non-separable mode which is made up by two parts； a pure energy slowing-down transient and a mixture of time and energy transient which is negligible asymptotically.

• ETRI Journal
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• v.33 no.1
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• pp.39-49
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• 2011

A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2442-2447
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• 2015

Because an electric railway vehicle is a large scale moving load, it can cause various kinds of power quality problems in the railroad power system. The power quality impacts are considered as the strong instantaneous stresses to the related power systems and can cause an accelerating aging and a malfunction of the power supplying components. Therefore, it is necessary to detect the small and intermittent symptoms mixed in the voltage waveform. However, they cannot be detected by the triggering functions of the existing power analyzers installed in the railway systems. This paper will examine the drawback of some fast detection tools and propose an advanced detecting and analyzing method based on a combined TEO and STFT algorithm.