• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.135-144
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• 2022

Electromagnetic topology (EMT) technique is a method to analyze each component of the electromagnetic propagation environment and combine them in the form of a network in order to effectively model the complex propagation environment. In a typical commercial communication channel model, since the propagation environment is complex and difficult to predict, a probabilistic propagation channel model that utilizes an average solution, although with low accuracy, is used. However, modeling techniques using EMT technique are considered for application of propagation and coupling analysis of threat electromagnetic waves such as electromagnetic pulses, radio wave models used in electronic warfare, local communication channel models used in 5G and 6G communications that require relatively high accuracy electromagnetic wave propagation characteristics. This paper describes the effective implementation method, algorithm, and program implementation of the electromagnetic topology (EMT) method analyzed in the frequency domain. Also, a method of deriving a response in the time domain to an arbitrary applied signal source with respect to the EMT analysis result in the frequency domain will be discussed.

• Journal of Microbiology and Biotechnology
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• v.18 no.1
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• pp.15-22
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• 2008

Four series (S, M, R, and W) of Alternaria longipes isolates were obtained based on consecutive selection with Dimethachlon (Dim) and ultraviolet irradiation. These isolates were then characterized according to their tolerance to Dim, sensitivity to osmotic stress, and phenotypic properties. All the selected Dim-resistant isolates showed a higher osmosensitivity than the parental strains, and the last generation was more resistant than the first generation in the M, R, and W series. In addition, the changes in the Dim resistance and osmotic sensitivity were not found to be directly correlated, and no distinct morphologic characteristics were found among the resistant and sensitive isolates, with the exception of the resistant isolate K-11. Thus, to investigate the molecular basis of the fungicide resistance, a group III two-component histidine kinase (HK) gene, AlHK1, was cloned from nineteen A. longipes isolates. AlHK1p was found to be comprised of a six 92-amino-acid repeat domain (AARD), HK domain, and response regulator domain, similar to the Os-1p from Neurospora crassa. A comparison of the nucleotide sequences of the AlHK1 gene from the Dim-sensitive and -resistant isolates revealed that all the resistant isolates contained a single-point mutation in the AARD of AlHK1p, with the exception of isolate K-11, where the AlHK1p contained a deletion of 107 amino acids. Moreover, the AlHK1p mutations in the isolates of each respective series involved the same amino acid substitution at the same site, although the resistance levels differed significantly in each series. Therefore, these findings suggested that a mutation in the AARD of AlHK1p was not the sole factor responsible for A. longipes resistance to dicarboximide fungicides.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.193-195
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• 2003

The analysis of EEG data is an important task in the domain of Brain Computer Interface (BCI). In general, this task is extremely difficult because EEG data is very noisy and contains many artifacts and consists of mixtures of several brain waves. The P300 component of the evoked potential is a relatively evident signal which has a large positive wave that occurs around 300 msec after a task-relevant stimulus. Thus automatic detection of P300 is useful in BCI. To this end, in this paper we employ a method of reference-based independent component analysis (ICA) which overcomes the ordering ambiguity in the conventional ICA. We show here. that ICA incorporating with prior knowledge is useful in the task of automatic P300 detection.

• Journal of Microbiology and Biotechnology
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• v.19 no.2
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• pp.140-146
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• 2009

MAPSI(Management and Analysis for Polyketide Synthase Type I) has been developed to offer computational analysis methods to detect type I PKS(polyketide synthase) gene clusters in genome sequences. MAPSI provides a genome analysis component, which detects PKS gene clusters by identifying domains in proteins of a genome. MAPSI also contains databases on polyketides and genome annotation data, as well as analytic components such as new PKS assembly and domain analysis. The polyketide data and analysis component are accessible through Web interfaces and are displayed with diverse information. MAPSI, which was developed to aid researchers studying type I polyketides, provides diverse components to access and analyze polyketide information and should become a very powerful computational tool for polyketide research. The system can be extended through further studies of factors related to the biological activities of polyketides.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.143-151
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• 2016

This paper presents new prediction methods to improve compression performance of the so-called near-lossless RGB-domain image coder, which is designed to effectively decrease the memory bandwidth of a system-on-chip (SoC) for image processing. First, variable block size (VBS)-based intra prediction is employed to eliminate spatial redundancy for the green (G) component of an input image on a pixel-line basis. Second, inter-color prediction (ICP) using spectral correlation is performed to predict the R and B components from the previously reconstructed G-component image. Experimental results show that the proposed algorithm improves coding efficiency by up to 30% compared with an existing algorithm for natural images, and improves coding efficiency with low computational cost by about 50% for computer graphics (CG) images.

• MALSORI
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• no.53
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• pp.93-102
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• 2005

The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis. According to experimental results, the proposed temporal filtering method has shown slightly better performance than the previous ones.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.9
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• pp.934-943
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• 1990

There are no turn-on losses in the series Resonant Converter which operates above the resonance frequency, and the commutation stress on the switched component is low. For a given Series Resonant Converter with specified load resistance, the output voltage is a function of the operation frequency. This paper describes the static and dynamic characteristic analysis of the Series Resonant DC to DC Converter, which is operating above the resonant frequency, with frequency control. For the analysis method, state plane technique is adopted, and the circuit operation is defined from normalized switching frequency, Fsn. Under this condition, circuit performance is analyzed ideally. The validity of the proposed analysis is verified by comparing with experimental results, the stability of the converter is confirmed against small variations around the operating point by conventional frequency domain analysis, and the stress quantity added to switch component is shown.

• Speech Sciences
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• v.10 no.4
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• pp.107-115
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• 2003

In this paper we tried to classify the pathological voice signal with severe noise component based on two different parameters, the spectral slope and the ratio of energies in the harmonic and noise components (HNR), The spectral slope is obtained by using a curve fitting method and the HNR is computed in cepstrum quefrency domain. Speech data from normal peoples and patients are collected, diagnosed and divided into three different classes (normal, relatively less noisy and severely noisy data), The mean values and the standard deviations of the spectral slope and the HNR are computed and compared with in the three kinds of data to characterize and classify the severely noisy pathological voice signals from others.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.52-55
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• 1996

Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Between these reasons, the distortion of edge is dominant reason which is occured by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To correct and generalize distortion phenomenon is imprrtant. Thus we must fix the discrimination criteria which is collected by image recognition of precise focus. The edge of image means discontinuous point of intensity, and the component of edge is discribed as high frequency component at special domain specturm of image. The good condition of focus means there are much high frequency energy in image. The method of discribing high frequency energy is gradient operater which determines the condition of focus.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.102-108
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• 2005

CIELAB coordinate is represented by one lightness component and two chromaticity components and similar to human visual system. Visual devices such as computer monitor display images using RGB coordinate. We propose a technique for inserting the watermark of visually recognizable mark into the middle frequency domain of image. RGB coordinate image is transformed into CIELAB coordinate, which include the characteristics of Human vision and then a* component is transformed into DFT(Discrete Fourier transform) transform.