• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.225-234
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• 2019

We explore the associations between the total sunspot area, solar north-south asymmetry, and Southern Oscillation Index and the physical characteristics of clouds by calculating normalized cross-correlations, motivated by the idea that the galactic cosmic ray influx modulated by solar activity may cause changes in cloud coverage, and in turn the Earth's climate. Unlike previous studies based on the relative difference, we have employed cloud data as a whole time-series without detrending. We found that the coverage of high-level and low-level cloud is at a maximum when the solar north-south asymmetry is close to the minimum, and one or two years after the solar north-south asymmetry is at a maximum, respectively. The global surface air temperature is at a maximum five years after the solar north-south asymmetry is at a maximum, and the optical depth is at a minimum when the solar north-south asymmetry is at a maximum. We also found that during the descending period of solar activity, the coverage of low-level cloud is at a maximum, and global surface air temperature and cloud optical depth are at a minimum, and that the total column water vapor is at a maximum one or two years after the solar maximum.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.21-28
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• 2007

We suggest a new spatial linear interpolation method to substitute linear interpolation method which widely used in transportation engineering to impute the missing daily traffic volume. We layout daily traffic volume which is time series data over the virtual lattice space to consider the spatial correlation. We used Moran Index to evaluate the spatial correlations among daily traffic volume in same week and same date traffic volume by week considering the circularity of daily traffic volume. For real application, we used daily traffic volume on November, 2004 provided by Korea Institute of Construction Technology(KICT) and transformed daily traffic volume to 4 times 7 virtual lattice space to reflect the spatial correlation. Finally we showed that the spatial linear interpolation method has good performance for missing data imputation based on MAPE, RMSE, and Theil's U criteria.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.142.1-142.1
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• 2012

During the photometric runs of the eclipsing binary V432 Per in 2006, we serendipitously discovered peculiar light variations of GSC 2855-0585 that imaged on the same target field. Its brightness decreased about 0.02 mag for about 0.15 days in all B, V, and R bands. The depth, duration, and box-shaped light curves are very similar to those of typical transiting exoplanets. We gathered the time-series data of GSC 2855-0585 from the SuperWASP public archive and detected the same light variations with a period of about 2.406 days. The period and transitlike features were confirmed by photometric follow-up observations at a predicted epoch in 2010 November. In order to estimate the mass of the companion that produced the light variations, we obtained 10 high-resolution spectra with different orbital phases in 2010 November and 2011 October-December. The radial velocities showed large variations of about 44 km/s. It indicates that the transitlike light variations do not originate from a transiting exoplanet, but from the single-lined spectroscopic eclipsing binary with a cool dwarf companion. Using the photometric and spectroscopic data, we estimated the physical parameters of the eclipsing binary GSC 2855-0585, such as orbital period, effective temperature, surface gravity, and mass.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.75-90
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• 2019

As the 24-hour society arrives, human activities in daytime and nighttime urban spaces are changing drastically, and the need for new urban management policies is steadily increasing. This study analyzes the types and characteristics of Seoul's human dynamics using location-based big data and the results are summarized as follows. First, the pattern of human dynamics in Seoul repeats itself every 7 days. Second, the types of human dynamics in Seoul can be classified into five types, and each of type has its own unique time-series and local characteristics. Third, the degree of match between human dynamics and zoning system in urban planning legislation was highest in 'Type 1' residence pattern and low in other types. The following implications can be drawn from these results. First, This paper examined the methodology of analyzing the regional characteristics of Seoul through the human dynamics and obtained meaningful results. Second, This paper can derive reliable and objective pattern analysis results using Big data that reflect the overall population characteristics. Third, the scale of night-time activity in the urban space of Seoul was understood, and its distribution, patterns and characteristics identified.

• Journal of The Korean Astronomical Society
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• v.48 no.5
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• pp.237-255
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• 2015

The Interferometric Monitoring of Gamma–ray Bright Active galactic nuclei (iMOGABA) program provides not only simultaneous multifrequency observations of bright gamma–ray detected active galactic nuclei (AGN), but also covers the highest Very Large Baseline Interferometry (VLBI) frequencies ever being systematically monitored, up to 129 GHz. However, observation and imaging of weak sources at the highest observed frequencies is very challenging. In the second paper in this series, we evaluate the viability of the frequency phase transfer technique to iMOGABA in order to obtain larger coherence time at the higher frequencies of this program (86 and 129 GHz) and image additional sources that were not detected using standard techniques. We find that this method is applicable to the iMOGABA program even under non–optimal weather conditions.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.42-55
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• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.2
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• pp.227-242
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• 2019

This paper presents a method to predict ground types ahead of a tunnel face utilizing operational data of the earth pressure-balanced (EPB) shield tunnel boring machine (TBM) when running through soil ground. The time series analysis model which was applicable to predict the mixed ground composed of soils and rocks was modified to be applicable to soil tunnels. Using the modified model, the feasibility on the choice of the soil conditioning materials dependent upon soil types was studied. To do this, a self-organizing map (SOM) clustering was performed. Firstly, it was confirmed that the ground types should be classified based on the percentage of 35% passing through the #200 sieve. Then, the possibility of predicting the ground types by employing the modified model, in which the TBM operational data were analyzed, was studied. The efficacy of the modified model is demonstrated by its 98% accuracy in predicting ground types ten rings ahead of the tunnel face. Especially, the average prediction accuracy was approximately 93% in areas where ground type variations occur.

• Journal of Astronomy and Space Sciences
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• v.14 no.2
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• pp.286-296
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• 1997

Magnetohydrodynamic wave phenomena have been investigated in the deep plasmasphere by the electric field measurements in the EXOS-D(Akebono) satellite. EXOS-D has highly eccentric orbits(the perigee: 274km, the apogee: 10,500km), which allows relatively long observational time interval near the apogee region compared to other satellites which pass by the same region with less eccentric orbits. Case studies are performed on one month data of October in 1989 where the apogee is located near the equator and the magnetic local time is about 9:00-12:00 a.m. in the dayside plasmasphere. The observational region ranges from L=2 to L=3 and the magnetic latitude is restricted to less than 30 degrees. The power spectrum is examined for each 128 point series of 8-sec averaged data through a FFT, which covers f = 0~62.3 mHz frequency bands. The results are well consistent with field line resonances (FLRs) and cavity modes in the plasmasphere.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.115-124
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• 2010

Urban watershed can be found in the visible changes in technology, the most realistic satellite images is to use the data. Satellite image data on the indicators for progress on the nature of the change of land use is consistent and repetitive information, regular observation makes possible the detailed analysis of space-time. These remote sensing techniques and the type of course and, by using the time series history, the past, the dynamic model and the randomized prediction methodology for the conversion process if the city and river basin cooperation of the space changes effectively will be able to extrapolate. For each of the main changes in river flow, depending on the area of urbanization as determined according to reproduce the duration of the relationship between the urbanization of the area and runoff can be represented as a linear polynomial expression was, if a linear expression in the two fast slew rate of 0.858 to 0.861 showed up, and fast slew rate of 0.934 to 0.974 for the polynomial are reported. Change of land use changes in the watershed of the flow is one of the most affecting elements. Therefore, changes in land use of the correct classification of rivers is a more accurate calculation of the amount of the floodgate. In particular, using the Landsat images through the image of the land use category, land use past data and calculated using the Markov Chain model and predict the future land use plan in the water control project will be used for large likely.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.197-205
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• 2021

Recently, the retail industry has been increasingly demanding information technology convergence and utilization to respond to various external environmental threats such as COVID-19 and to be competitive using AI technologies, but there is a very lack of research and application services. This study is a CCTV video data-driven AI application case study, using CCTV image data collection in retail space, object detection and tracking AI model, time series database to store real-time tracked objects and tracking data, heatmap to analyze congestion and interest in retail space, social access zone.We present the orientation and verify its usability in the direction designed through practical implementation.