• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.60.1-60.1
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• 2020

We present optical variability of nearby luminous active galactic nucleus (AGN). We use the multi-epoch data of 46 AGNs obtained from 2015 to 2019 through SNU AGN Monitoring Project (SAMP), which was carried out for the reverberation mapping of luminous AGNs. We estimated variability amplitudes and time scales using the various types of analytic function, such as structure function and damped random work. We present the comparisons between physical properties of AGNs and optical variability in order to unveil the origin of the variability of AGNs.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.353-381
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• 2019

The general world model for homogeneous and isotropic universe has been proposed. For this purpose, we introduce a global and fiducial system of reference (world reference frame) constructed on a (4+1)-dimensional space-time, and assume that the universe is spatially a 3-dimensional hypersurface embedded in the 4-dimensional space. The simultaneity for the entire universe has been specified by the global time coordinate. We define the line element as the separation between two neighboring events on the expanding universe that are distinct in space and time, as viewed in the world reference frame. The information that determines the kinematics of the geometry of the universe such as size and expansion rate has been included in the new metric. The Einstein's field equations with the new metric imply that closed, flat, and open universes are filled with positive, zero, and negative energy, respectively. The curvature of the universe is determined by the sign of mean energy density. We have demonstrated that the flat universe is empty and stationary, equivalent to the Minkowski space-time, and that the universe with positive energy density is always spatially closed and finite. In the closed universe, the proper time of a comoving observer does not elapse uniformly as judged in the world reference frame, in which both cosmic expansion and time-varying light speeds cannot exceed the limiting speed of the special relativity. We have also reconstructed cosmic evolution histories of the closed world models that are consistent with recent astronomical observations, and derived useful formulas such as energy-momentum relation of particles, redshift, total energy in the universe, cosmic distance and time scales, and so forth. The notable feature of the spatially closed universe is that the universe started from a non-singular point in the sense that physical quantities have finite values at the initial time as judged in the world reference frame. It has also been shown that the inflation with positive acceleration at the earliest epoch is improbable.

• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.379-386
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• 2015

This work presents fuel-optimal altitude maintenance of Low-Earth-Orbit (LEO) spacecrafts experiencing non-negligible air drag and J2 perturbation. A pseudospectral (direct) method is first applied to roughly estimate an optimal fuel consumption strategy, which is employed as an initial guess to precisely determine itself. Based on the physical specifications of KOrea Multi-Purpose SATellite-2 (KOMPSAT-2), a Korean artificial satellite, numerical simulations show that a satellite ascends with full thrust at the early stage of the maneuver period and then descends with null thrust. While the thrust profile is presumably bang-off, it is difficult to precisely determine the switching time by using a pseudospectral method only. This is expected, since the optimal switching epoch does not coincide with one of the collocation points prescribed by the pseudospectral method, in general. As an attempt to precisely determine the switching time and the associated optimal thrust history, a shooting (indirect) method is then employed with the initial guess being obtained through the pseudospectral method. This hybrid process allows the determination of the optimal fuel consumption for LEO spacecrafts and their thrust profiles efficiently and precisely.

• Biomolecules & Therapeutics
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• v.8 no.1
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12B
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• pp.1063-1069
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• 2004

There are some problems with the methods of paging and routing cache(PRC) and quasi soft handoff that are proposed to improve the performance for the transmission of real time data. This paper proposed a reasonable solution of these problems by proposing a new method using a combined cache(CC) and applying a different handoff procedure according to each type of data. The combined cache dose not maintain the handoff state but the idlle/active state. The simulation results in a better performance than the above methods in terms of the control packet traffic load, initial recevied data packet traffic load and arrival tune of real time packet at the epoch of handoff.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.235-243
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• 2018

Conventional Real Time Kinematics (RTK) collect measurements in stationary state for several minutes to resolve the integer ambiguity in the carrier phase measurement or resolve the integer ambiguity on the move assuming low maneuvering movement. In this paper, an On The Move-RTK (OTM-RTK) technique that resolves the integer ambiguity on the move for fast and precise positioning of ground vehicles such as high maneuvering vehicles was proposed. The OTM-RTK estimates the precise amount of movement between epochs using the carrier phase measurements acquired on the move, and by using this, resolves the integer ambiguity within a short period of time by evaluating the integer ambiguity candidates for each epoch. This study analyzed the integer ambiguity resolution performance using field driving experiment data in order to verify the performance of the proposed method. The results of the experiment showed that the precise trajectory including the initial position bias can be obtained prior to resolving the integer ambiguity, and after resolving the integer ambiguity on the move, it was possible to obtain the bias-corrected precise position solution. It was confirmed that the integer ambiguity can be resolved by collecting measurements of about 10 epochs from the moving vehicle using a dual frequency receiver.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.532-541
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• 2021

Recently, research on the application of artificial intelligence in the chemical process has been increasing rapidly. However, overfitting is a significant problem that prevents the model from being generalized well to predict unseen data on test data, as well as observed training data. Cross validation is one of the ways to solve the overfitting problem. In this study, the time-series cross validation method was applied to optimize the number of batch and epoch in the hyperparameters of the prediction model for the 2,3-BDO distillation process, and it compared with K-fold cross validation generally used. As a result, the RMSE of the model with time-series cross validation was lower by 9.06%, and the MAPE was higher by 0.61% than the model with K-fold cross validation. Also, the calculation time was 198.29 sec less than the K-fold cross validation method.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.11-19
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• 2022

In this paper, we propose a GoogleNet transfer learning and CNN-LSTM combination method to improve the time-series prediction performance for crack detection using crack data captured inside the sewer pipes. LSTM can solve the long-term dependency problem of CNN, so spatial and temporal characteristics can be considered at the same time. The predictive performance of the proposed method is excellent in all test variables as a result of comparing the RMSE(Root Mean Square Error) for time series sections using the crack data inside the sewer pipe. In addition, as a result of examining the prediction performance at the time of data generation, the proposed method was verified that it is effective in predicting crack detection by comparing with the existing CNN-only model. If the proposed method and experimental results obtained through this study are utilized, it can be applied in various fields such as the environment and humanities where time series data occurs frequently as well as crack data of concrete structures.

• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.171-175
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• 2017

Recently, Training of the convolutional neural network (CNN) entails many iterative computations. Therefore, a method of accelerating the training speed through parallel processing using the hardware specifications of GPGPU is actively researched. In this paper, the operations of the feature extraction unit and the classification unit are divided into blocks and threads of GPGPU and processed in parallel. Convolution and Pooling operations of the feature extraction unit are processed in parallel at once without sequentially processing. As a result, proposed method improved the training time about 314%.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.454-470
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• 2003

In this paper, a preliminary study for development of a fault diagnosis is presented for monitoring and diagnosing faults in the agitator driving system of a high temperature reduction reactor. In order to identify a fault occurrence and classify the fault cause, vibration signals measured by accelerometers on the outer shroud of the agitator driving system are firstly decomposed by wavelet transform (WT) and the features corresponding to each fault type are extracted. For the diagnosis, the fuzzy ARTMAP is employed and thereby, based on the features extracted from the WT, the robust fault classifier can be implemented with a very short training time - a single training epoch and a single learning iteration is sufficient for training the fault classifier. The test results demonstrate satisfactory classification for the faults pre-categorized from considerations of possible occurrence during experiments on a small-scale reduction reactor.