• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.193-195
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• 2015

The Palomar Transient Factory is a project making use of a Schmidt 48 inch telescope located on the Palomar Mountain, which is surveying the sky with dynamical cadences. It was deployed in 2009 and the observed sky region is over 1200 square degrees. We have studied the long-term periodic variabilities of the known galactic cataclysmic variables (CVs). More than 20 of the sources had been found to have long term periodic signals, ranging from several tens of days to several hundreds of days. Some possible scenarios are proposed to explain the results, such as a magnetic field change of the companion star, precession of the accretion disk, triple systems and superoutburst cycles. Some preliminary discussion will be presented in this article.

• Advances in nano research
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• v.8 no.1
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• pp.25-36
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• 2020

Rotating systems concern with torsional vibration, and it should be considered in vibration analysis. To do this, the time-dependent torsional vibrations in a single-walled carbon nanotube (SWCNT) under the linear and harmonic external torque, are investigated in this paper. Eringen's nonlocal elasticity theory is considered to demonstrate the nonlocality and constitutive relations. Hamilton's principle is established to derive the governing equation of motion and consequently related boundary conditions. An analytical method, called the Galerkin method, is utilized to discretize the driven differential equations. Linear and harmonic torsional loads, along with determined amplitude, are applied to the SWCNT as the external torques. SWCNT is considered under the clamped-clamped end supports. In free vibration, analysis of small scale effect reveals the capability of natural frequencies in different modes, and this results desirably are in coincidence with another study. The forced torsional vibration in the time domain, especially for carbon nanotubes, has not been done before in the previous works. The previous forced studies were devoted to the transverse vibrations. It should be emphasized that the dynamical analysis of torsion is novel, workable, and at the beginning of the path. The variations of nonlocal parameter, CNT's thickness, and the influence of excitation frequency on time-dependent angular displacement and nondimensional angular displacement are investigated in the context.

• Journal of Astronomy and Space Sciences
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• v.39 no.4
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• pp.181-194
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• 2022

Korea Pathfinder Lunar Orbiter (KPLO), also known as Danuri, was successfully launched on 4 Aug. from Cape Canaveral Space Force Station using a Space-X Falcon-9 rocket. Flight dynamics (FD) operational readiness was one of the critical parts to be checked before the flight. To demonstrate FD software's readiness and enhance the operator's contingency response capabilities, KPLO FD specialists planned, organized, and conducted four simulations and two rehearsals before the KPLO launch. For the efficiency and integrity of FD simulation and rehearsal, different sets of blind test data were prepared, including the simulated tracking measurements that incorporated dynamical model errors, maneuver execution errors, and other errors associated with a tracking system. This paper presents the simulation and rehearsal results with lessons learned for the KPLO FD operational readiness checkout. As a result, every functionality of FD operation systems is firmly secured based on the operation procedure with an enhancement of contingency operational response capability. After conducting several simulations and rehearsals, KPLO FD specialists were much more confident in the flight teams' ability to overcome the challenges in a realistic flight and FD software's reliability in flying the KPLO. Moreover, the results of this work will provide numerous insights to the FD experts willing to prepare deep space flight operations.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

• Atmosphere
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• v.25 no.3
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• pp.529-541
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• 2015

Korea Institute of Atmospheric Prediction System (KIAPS) has been developing a global numerial prediction model and data assimilation system. We has implemented LETKF (Local Ensemble Transform Kalman Filter, Hunt et al., 2007) data assimilation system to NCAR CAM-SE (National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core, Dennis et al., 2012) that has cubed-sphere grid, known as the same grid system of KIAPS Integrated Model (KIM) now developing. In this study, we have assimilated Global Positioning System Radio Occultation (GPS-RO) bending angle measurements in addition to conventional data within ensemble-based data assimilation system. Before assimilating bending angle data, we performed a vertical unit conversion. The information of vertical localization for GPS-RO data is given by the unit of meter, but the vertical localization method in the LETKF system is based on pressure unit. Therefore, with a clever conversion of the vertical information, we have conducted experiments to search for the best vertical localization scale on GPS-RO data under the Observing System Simulation Experiments (OSSEs). As a result, we found the optimal setting of vertical localization for the GPS-RO bending angle data assimilation. We plan to apply the selected localization strategy to the LETKF system implemented to KIM which is expected to give better analysis of GPS-RO data assimilation due to much higher model top.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.315-330
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• 2017

Halo coronal mass ejections (CMEs) originating from solar activities give rise to geomagnetic storms when they reach the Earth. Variations in the geomagnetic field during a geomagnetic storm can damage satellites, communication systems, electrical power grids, and power systems, and induce currents. Therefore, automated techniques for detecting and analyzing halo CMEs have been eliciting increasing attention for the monitoring and prediction of the space weather environment. In this study, we developed an algorithm to sense and detect halo CMEs using large angle and spectrometric coronagraph (LASCO) C3 coronagraph images from the solar and heliospheric observatory (SOHO) satellite. In addition, we developed an image processing technique to derive the morphological and dynamical characteristics of halo CMEs, namely, the source location, width, actual CME speed, and arrival time at a 21.5 solar radius. The proposed halo CME automatic analysis model was validated using a model of the past three halo CME events. As a result, a solar event that occurred at 03:38 UT on Mar. 23, 2014 was predicted to arrive at Earth at 23:00 UT on Mar. 25, whereas the actual arrival time was at 04:30 UT on Mar. 26, which is a difference of 5 hr and 30 min. In addition, a solar event that occurred at 12:55 UT on Apr. 18, 2014 was estimated to arrive at Earth at 16:00 UT on Apr. 20, which is 4 hr ahead of the actual arrival time of 20:00 UT on the same day. However, the estimation error was reduced significantly compared to the ENLIL model. As a further study, the model will be applied to many more events for validation and testing, and after such tests are completed, on-line service will be provided at the Korean Space Weather Center to detect halo CMEs and derive the model parameters.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.51-57
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• 1999

In this paper, we deal with the problem of controlling an unknown nonlinear dynamical system, using wavelet network. Accurate control of the nonlinear systems depends critically on the accuracy and efficiency of the function approximator used to approximate the function. Thus, we use wavelet network which shows high capability of approximating the functions and includes the free-selection of basis functions for the control of the nonlinear system. We find the dilation and translation that are wavelet network parameters by analyzing the time-frequency characteristics of the controller's input to construct an initial adaptive wavelet network controller. Then, weights is adjusted by the adaptive law based on the Lyapunov stability theory. We apply this direct adaptive wavelet network controller to control the inverted pendulum system which is an nonlinear system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.435-442
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• 2007

To reduce damage from high concentration ozone in the air, we have researched how to predict high concentration ozone before it occurs. High concentration ozone is a rare event and its reaction mechanism has nonlinearities and complexities. In this paper, we have tried to apply and consider as many methods as we could. We clustered the data using the fuzzy c-mean method and took a rejection sampling to fill in the missing and abnormal data. Next, correlations of the input component and output ozone concentration were calculated to transform more correlated components by modified log transformation. Then, we made the prediction models using Dynamic Polynomial Neural Networks. To select the optimal model, we adopted a minimum bias criterion. Finally, to evaluate suggested models, we compared the two models. One model was trained and tested by the transformed data and the other was not. We concluded that the modified transformation effected good to ideal performance In some evaluations. In particular, the data were related to seasonal characteristics or its variation trends.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.68-76
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• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the ring connection neural network in which each neuron is only to its nearest neurons with binary synaptic weights of ±1, has been inconnected vestigated Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of n-neuron network to produce a limit cycle of n- or 2n-period are also given The results show that the estimated number of limit cycle is an exponential function of n. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.