• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.517-528
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• 2018

We provide R scripts to detect outliers in multivariate data and visualization. Detecting outliers is provided using three approaches 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) density-based approach methods. We use the following techniques to visualize detected potential outliers 1) multidimensional scaling (MDS) and minimal spanning tree (MST) with k-means clustering, 2) MDS with fviz cluster, 3) principal component analysis (PCA) with fviz cluster. For real data sets, we use MLB pitching data including Ryu, Hyun-jin in 2013 and 2014. The developed R scripts can be downloaded at "http://www.knou.ac.kr/~sskim/ddpoutlier.html" (R scripts and also R package can be downloaded here).

• Journal of applied mathematics & informatics
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• v.36 no.5_6
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• pp.359-368
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• 2018

In this paper, we investigate quasi-cyclic codes over the ring $R={\mathbb{F}}_2+v{\mathbb{F}}_2$, where $v^2=v$. We investigate the structure of generators for one-generator quasi-cyclic codes over R and their minimal spanning sets. Moreover, we find the rank and a lower bound on minimum distances of free quasi-cyclic codes over R. Further, we find a relationship between cyclic codes over a different ring and quasi-cyclic codes of index 2 over R.

• Journal of the Korean Mathematical Society
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• v.41 no.6
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• pp.1087-1099
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• 2004

We study the metrical and topological pressure for flows without fixed points on a compact metric space, and get the results as follows: (1) The metrical pressure with respect to an ergodic measure can be defined by (t, $\varepsilon$)-spanning sets. (2) The topological pressure is the supremum of metrical pressures with respect to all ergodic measures. (3) The properties that the topological pressure is zero, nonzero, finite or infinite respectively are invariant under weak equivalence.

• Computers and Concrete
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• v.12 no.2
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• pp.187-209
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• 2013

This paper presents a study on the prediction of transfer length of 13 mm seven-wire prestressing steel strand in pretensioned prestressed concrete members with rectangular cross-section including several material properties and design and manufacture parameters. To this end, a carefully selected database consisting of 207 different cases coming from 18 different sources spanning a variety of practical transfer length prediction situations was compiled. 16 single input features and 5 combined input features are analyzed. A widely used feedforward neural regression model was considered as a representative of several machine learning methods that have already been used in the engineering field. Classical multiple linear regression was also considered in order to comparatively assess performance and robustness in this context. The results show that the implemented model has good prediction and generalization capacity when it is used on large input data sets of practical interest from the engineering point of view. In particular, a neural model is proposed -using only 4 hidden units and 10 input variables-which significantly reduces in 30% and 60% the errors in transfer length prediction when using standard linear regression or fixed formulas, respectively.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.399-403
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• 1998

Absorption coefficient per mass unit of particles, specific absorption coefficient, is one of main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll (a$^*_{ph}$) and suspended sediment (SS) were analyzed by "wet filter technique" and "Kishino method" for data sets observed in the Yellow and Mediterranean Seas. A new data-recovering method for the filter technique was also developed using spectrum slopes. This method recovered the baseline of spectrum that was often missed in the Kishino method. High a$^*_{ph}$($\lambda$) values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, spanning over the range of 0.02 to 0.12 $m^2$/mg, at the chlorophyll maximum absorption wavelength 440nm. The empirical relationship between a$^*_{ph}$ and chlorophyll concentration was found to fit a power function, which was slightly different from that proposed by Bricaud et ai. (1995). Absorption specific coefficients for suspended sediment (a$^*_{SS}$) didn't show any relationship with concentrations of suspended sediment. However, the average value of a$^*_{SS}$ at 440nm was close to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The more-pronounced variability of a$^*_{SS}$ than a$^*_{ph}$ perhaps can explain more wide range of size-distribution for SS, which were determined by their specific gravity and agitation of water mass in the sea surface.

• Journal of The Korean Astronomical Society
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• v.48 no.6
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• pp.325-331
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• 2015

We study an association between the duration of solar activity and characteristics of the latitude distribution of sunspots by means of center-of-latitude (COL) of sunspots observed during the period from 1878 to 2008 spanning solar cycles 12 to 23. We first calculate COL by taking the area-weighted mean latitude of sunspots for each calendar month to determine the latitudinal distribution of COL of sunspots appearing in the long and short cycles separately. The data set for the long solar cycles consists of the solar cycles 12, 13, 14, 20, and 23. The short solar cycles include the solar cycles 15, 16, 17, 18, 19, 21, and 22. We then fit a double Gaussian function to compare properties of the latitudinal distribution resulting from the two data sets. Our main findings are as follows: (1) The main component of the double Gaussian function does not show any significant change in the central position and in the full-width-at-half-maximum (FWHM), except in the amplitude. They are all centered at ~ 11° with FWHM of ~ 5°. (2) The secondary component of the double Gaussian function at higher latitudes seems to differ in that even though their width remains fixed at ~ 4°, their central position peaks at ~ 22.1° for the short cycles and at ~ 20.7° for the long cycles with quite small errors. (3) No significant correlation could be established between the duration of an individual cycle and the parameters of the double Gaussian. Finally, we conclude by briefly discussing the implications of these findings on the issue of the cycle 4 concerning a lost cycle.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.196-198
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• 2003

Virtually every digital signal processors(DSPs) support on-chip multi- memory banks that allow the processor to access multiple words of data from memory in a single instruction cycle. Also, all existing fixed-point DSPs have irregular architecture of heterogeneous register which contains multiple register files that are distributed and dedicated to different sets of instructions. Although there have been several studies conducted to efficiently assign data to multi-memory banks, most of them assumed processors with relatively simple, homogeneous general-purpose resisters. Therefore, several vendor-provided compilers fer DSPs were unable to efficiently assign data to multiple data memory banks. thereby often failing to generate highly optimized code fer their machines. This paper presents an algorithm that helps the compiler to efficiently assign data to multi- memory banks. Our algorithm differs from previous work in that it assigns variables to memory banks in separate, decoupled code generation phases, instead of a single, tightly-coupled phase. The experimental results have revealed that our decoupled algorithm greatly simplifies our code generation process; thus our compiler runs extremely fast, yet generates target code that is comparable In quality to the code generated by a coupled approach

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.78.1-78.1
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• 2019

Using a method to correct redshift space distortion (RSD) for individual galaxies, we mapped the real space distributions of galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7(DR7). We use an ensemble of mock catalogs to demonstrate the reliability of this extension, showing that it allows for an accurate recovery of the real-space correlation functions and galaxy biases. We also demonstrate that, using an iterative method applied to intermediate scale clustering data, we can obtain an unbiased estimate of the growth rate of structure $f\sigma_8$, which is related to the clustering amplitude of matter, to an accuracy of $\sim 10\%$. Applying this method to the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we construct a real-space galaxy catalog spanning the redshift range $0.01 \leq z \leq 0.2$, which contains 584,473 galaxies in the North Galactic Cap (NGC). Using this data we, infer $0.376 \pm 0.038$ at a median redshift z=0.1, which is consistent with the WMAP9 cosmology at $1\sigma$ level. By combining this measurement with the real-space clustering of galaxies and with galaxy-galaxy weak lensing measurements for the same sets of galaxies, we are able to break the degeneracy between $f$, $\sigma_8$ and $b$. From the SDSS DR7 data alone, we obtain the following cosmological constraints at redshift $z=0.1$ for galaxies.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• The Plant Pathology Journal
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• v.21 no.2
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• pp.167-171
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• 2005

We isolated the Cucumber green mottle mosaic virus(CGMMV) particles from watermelon leaves and designated as CGMMV-HY1 as a watermelon isolate and attempted to characterize the pathogenic isolate responsible for such an epidemic in watermelon and also to monitor dominant viral isolates in greenhouse. The watermelon plants infected with CGMMV generally showed mottle mosaic, mosaic, growth stunting, necrosis and deformed fruit. The reactions of indicator plants to CGMMV-HY1 were the local lesions on Nicotiana tabacum cv. White Burley, Nicotiana tabacum cv. Samsun, and Chenopodium amaranticola, and the mosaic symptoms only on Cucumis sativus, but the CGMMV-HY1 did not infect Nicotiana sylvesytis, Datura stramonium, Chenopodium quinoa, and Petunia hybrida. Purified virus particles were rod-shaped and about 300 nm long. The coat protein (CP) of purified CGMMV-HY1 was single band with molecular weight of about 16.5 kDa which was confirmed by western blot analysis probed with monoclonal antibody of CGMMV-HY1. The genomic and subgenomic RNAs of 6.4 kb and 0.75 kb were revealed by the electrophoresis on 1.2% formaldehydedenatured agarose gel. Viral and complementary CGMMV-specific primer sets were designed for spanning the genome using previously reported CGMMV sequences. A 464bp of CP gene of CGMMV-HY1 was amplified by RT-PCR and cloned into PGEM-T easy vector. The nucleotide sequence of CP gene of CGMMV-HY1 shared 98%, 99%, and 100% identities with that of CGMMV strains W, KOM, and KW respectively. Based on these results, we identified CGMMV-HY1 as a CGMMV isolate of watermelon, a member of Tobamovirus.