• Journal of IKEEE
• /
• v.21 no.2
• /
• pp.105-114
• /
• 2017

This paper proposes a design method of an LCL-filter for grid-tied three-level inverter systems. The demand for three-phase PWM inverters in applications such as wind or solar power generation systems has been increase in recent years. To reduce harmonic components caused by switching operation, such inverters are connected to the grid via an LCL filter. Although there are research results for designing LCL-filter, the modulation method should be fully considered to make the filter perform desired cancellation ability with minimized size. This paper presents the design methodology for an LCL-filter that is optimized for SVM switching operations. The simulation and experimental results verify the validity of the LCL-filter designed with proposed method in this paper.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.10 no.1
• /
• pp.17-26
• /
• 1990

A solution strategy for geometric non-linear analysis for the plane frame structures subjected to conservative and non-conservative forces is presented. By making efficient combination of the load incremental method and the displacement incremental method, this strategy can find postbuckling configuration such as snap-through and turning-back phenomena which cannot be easily found by the conventional load and displacement incrementation scheme. In the case of the analysis of the framed structure subjected to circulatory non-conservative forces, the total tangent stiffness matrix becomes unsymmetric and when calculating the incremental load and unbalanced load vector components, the direction change of the non-conservative forces is considered. Several example problems to demonstrate the feasibility of the present strategy, over ranges of deformation that are well beyond those likly to occur in practical framed structures, are given and discussed.

• Analytical Science and Technology
• /
• v.33 no.2
• /
• pp.98-107
• /
• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.3
• /
• pp.79-84
• /
• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.243-251
• /
• 2022

In this paper, we propose a phenomenon that analyze the impact of market sentiment on China's real estate market through the perspective of behavioral economics. Previously, real estate market analyzation basically focus on some fundamental principles which include market price, monetary policies and income, etc. However, little research has explored market sentiment and its influence. By using principal components analysis (PCA), this study first creates buyer's sentiment and seller's sentiment to measure the heat of China's real estate market. Different from using traditional estimation method, the vector autoregressive model (VAR) is used to analyze how both sentiments affect real estate return. The overall results show that from unit root test and impulse response analyzation, the impact of seller's sentiment is positive to real estate market while buyer's sentiment is negative. At the same time, the higher seller's sentiment will have different influence on the housing market compared with the higher buyer's sentiment.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.1
• /
• pp.270-279
• /
• 1997

The conversion of printed maps into computerized databases is an enormous task. Thus the automation of the conversion process is essential. Efficient computer representation of printed maps and line drawings depends on codes assigned to characters, symbols, and vector representation of the graphics. In many cases, maps are constructed in a number of layers, where each layer is printed in a distinct color, and it represents a subset of the map information. In order to properly represent the character layer from color map images, an interactive clustering and character extraction technique is proposed. Character is usually separated from graphics by extracting and classifying connected components in the image. But this procedure fails, when characters touch or overlap lines-something that occurs often in land register maps. By vectorizing line segments, the touched characters and numbers are extracted. The algorithm proposed in this paper is intended to contribute towards the solution of the color image clustering and touched character problem.

• Journal of Microbiology and Biotechnology
• /
• v.10 no.1
• /
• pp.56-62
• /
• 2000

The hpa gene genetically linked to the ctxa2b gene was cloned into the pTED expression vector, and the constructed pTEDhpa/ctxa2b was transformed into Excherichia coli. The fusion protein, the adhesin fused to the cholera toxin subunit A2B (CTXA2B) subunit, was expressed to high levels as inclusion bodies in E. coli. The expressed protein was partially purified by washing the inclusion bodies with working solution containing 8M Urea and 0.1M DTT. Refolding of denatured fusion protein was carried out in the presence of glutathione redox buffer. The refolded fusion protein was purified by size exclusion chromatography. The expressed fusion protein was verified by SDS-PAGE, western blotting with antibodies to both antigenic components of adhesin and cholera toxin subunit B (CTXB), and its N-terminal amino acid sequence was analyzed. The orderly assembled fusion protein was confirmed by modified Gm1-ganglioside ELISA with Abs to adhesin. The results indicate that the purified fusion protein is an Adhesin/CTXA2B protein containing the H. pylori adhesin and $G_{m1}4-ganglioside binding activity of CTXB and the expressed fusion protein in E. coli could be easily purified by the refolding process, Its molecular weight was 168kDa as estimated by size exclusion chromatography. The Adhesin/CTXA2B protein may be used as a candidate antigen for oral immunization against H. pylori.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.10 no.4
• /
• pp.479-486
• /
• 1999

In this paper the system performance degradation resulting from nonlinear transmitter power amplifier which is essential to increase the efficiency is analyzed in a forward link CDMA system. The power amplifier is modeled by power series model which includes only odd-order terms. The effects of power amplifier's nonlinearity such as intersymbol interference, phase distortion on the RF system performance were visualized by examining the distorted time domain waveforms, signal vector constellation. And through the investigation of the power spectrum density of the transmitted signal, spectral regrowth or sideband regrowth which is result from amplitude distortion can be seen. All these characteristics result in BER performance degradation due to other user interferences and intersymbol interference. The analysis technique described here applies not only to power amplifier but also to any other nonlinear components such as mixers and switches. Also the effects of adjacent channel interference and supurious emission can be analysed between different systems.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.16 no.9
• /
• pp.1788-1795
• /
• 1992

Numerical simulations have been performed to investigate various spectral estimators used in LDV signal processing. In order to simulate a particle arrival time statistics known as the doubly stochastic poisson process, an autoregressive vector model was adopted to construct a primary velocity field. The conditional Poisson process with a random rate parameter was generated through the rescaling time process using the mean value function. The direct transform based on random sampling sequences and the standard periodogram using periodically resampled data by the sample and hold interpolation were applied to obtain power spectral density functions. For low turbulent intensity flows, the direct transform with a constant Poisson intensity is in good agreement with the theoretical spectrum. The periodogram using the sample and hold sequences is better than the direct transform in the view of the stability and the weighting of the velocity bias for high data density flows. The high Reynolds stress and high fluctuation of the transverse velocity component affects the velocity bias which increases the distortion of spectral components in the direct transform.

• Journal of Aerospace System Engineering
• /
• v.15 no.5
• /
• pp.72-80
• /
• 2021

Albatross uses dynamic soaring technique to obtain energy from horizontal winds and fly long distances without flapping. These dynamic soaring technique can be applied to manned/unmanned aircraft to reduce the components required for the aircraft and achieve light weight and small volume to effectively perform a given task. In this paper, to simulate the dynamic soaring technique of Albatross, we defined the optimization problem and set each boundary condition to derive the optimal flight trajectory and carry out simulations to follow it. In particular, to model dynamic soaring simulations more closely with reality, we proposed a horizontal wind model that changes every moment. This identifies and analyzes the effect of the time-variable horizontal wind model on the dynamic soaring mission of unmanned aircraft.