• International journal of advanced smart convergence
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• v.9 no.1
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• pp.177-184
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• 2020

In this paper, we studied to direction of arrival (DoA) estimation to use DoA and optimum weight algorithms in coherent interference channels. The DoA algorithm have been considerable attention in signal processing with coherent signals and a limited number of snapshots in a noise and an interference environment. This paper is a proposed method for the desired signal estimation using MUSIC algorithm and adaptive beamforming to compare classical subspace techniques. Also, the proposed method is combined the updated weight value with LCMV beamforming algorithm in adaptive antenna array system for direction of arrival estimation of desired signal. The proposed algorithm can be used with combination to MUSIC algorithm, linearly constrained minimum variance beamforming (LCMV) and the weight value method to accurately desired signal estimation. Through simulation, we compare the proposed method with classical direction of in order to desired signals estimation. We show that the propose method has achieved good resolution performance better that classical direction arrival estimation algorithm. The simulation results show the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.301-304
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• 2001

The analog multiplier is very useful building block in many circuits such as filter, frequency-shifter, and modulators. In recent year, The main design issue of circuit designer is low-voltage/low-power system design, because of all systems are recommended very integrated system and portable system In this paper, the proposed the four-quadrant analog multiplier is using the bulk-driven techniques. The bulk-driven technique is very useful technique in low-voltage system, compare with gate-driven technique. therefore the proposed analog multiplier is operated in 1V supply voltage. And the proposed analog multiplier is low power dissipation compare with the others. therefor the proposed analog multiplier is convenient in low-voltage/low-power in system.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1025-1028
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• 1999

After detecting the edge which is applying the morphological operators to the hybrid FCNN, we could analyze and compare. The hybrid FCNN is completely removed to the noise in the image, and worked in order to obtain the result image which is closest to the original image. Also, the morphological operator is applied to the image as the method in order to detect more good the edge than the conventional edge. FCNN which is the pipeline type is completely suitable to detecting the image processing as well as the hardware size. In this paper. we would make the structure elements of the morphological operator the variable template and the static template, and compare with the edge enhancement of two images. After being the result which is applying the variable template morphological operator and the static template morphological operator to the image, we could know that the edge images applying the variable template is superior in a edge enhancement side.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.13-16
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• 2000

This paper is to compare DTCNN(Discrete-time Cellular Neural Networks) applying the fuzzy morphology operators with the conventional FCNN(Fuzzy CNN) using the general morphology operators. These methods are to the image filtering, and are compared as MSE. Also the main goal of this paper is to compare the fuzzy morphology operators with the general morphology operators through image input. In a result of computer simulation, we could know that the error of DTCNN applying the fuzzy morphology operators is less about 6.1809 than FCNN using the general morphology operators in the image included 10% noise, also the error of the former is less about 5.5922 than the latter in the image included 20% noise. And the image of DTCNN applying the fuzzy morphology operators is superior to FCNN using the general morphology operators.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.639-646
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• 2006

A nonlinear finite element analysis is carried out to predict the ultimate internal pressure and failure mechanism of a 1/4 scale prestressed concrete containment vessel(PCCV) model using the commercial code ABAQUS. Therefore, this paper is mainly focused to compare the influence of concrete material model, tension stiffening parameter, uplift phenomenon and basemat. From the analysis results, nonlinear behavior of the PCCV showed a substantially different aspects in accordance with the nonlinear material model for the concrete as well as tension stiffening parameter. The boundary conditions beneath the basemat are considered to be a fixed condition and a nonlinear spring element to compare the influence of the uplift. The finite element analysis is considered with and without a basemat to find out the influence of the basemant itself. From the analysis results, the nonlinear behavior of the PCCV is entirely similar for the two cases.

• The Plant Pathology Journal
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• v.22 no.2
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• pp.164-167
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• 2006

An immunocapture reverse transcription-polymerase chain reaction (IC/RT-PCR) was developed for simultaneous detection of two pepper-infecting RNA viruses, Pepper mud mottle virus (PMMoV) and Tobacco mild green mosaic virus (TMGMV). The assay could be performed in a single tube for simultaneous and sensitive detection of these tobamoviruses. This detection system revealed thousand-fold increase in detection sensitivity compare to ELISA. This method could save time and reagent cost compare to common RT-PCR which needs several reactions and several procedures of viral RNA extractions for the same number of samples.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.769-780
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• 2005

Recently, the discretization algorithms for continuous data have been actively studied. But there are few articles to compare the efficiency of these algorithms. In this paper we introduce the principles of some binary discretization algorithms including C4.5, CART and QUEST and investigate the efficiency of these algorithms through numerical study. For various underlying distribution, we compare these algorithms in view of misclassification rate and MSE. Real data examples are also included.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.4
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• pp.240-245
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• 2006

Viterbi decoder is composed of BMU(Branch metric Unit), ACSU(Add Compare Select Unit), and SMU(Survivor path Memory Unit). For high speed viterbi decoders, ACSU is the main bottleneck due to the compare-select and feedback operation. Thus, many studies have been advanced to solve the problem. For example, M-step look ahead technique and Minimized method are typical high speed algorithms. In this paper, we designed a bit-level ACSU(K=3, R=1/2, 4bit soft decision) based on those algorithms and switched the matrix product order in the backward direction of Minimized method so as to apply Code-Optimized-Array in order to reduce the area complexity. For experimentation, we synthesized our design by using SYNOPSYS Design compiler, with TSMC 0.18 um library, and verified the timing by using CADENCE verilog-XL.

• Journal of Industrial Technology
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• v.35
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• pp.35-39
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• 2015

One of the purposes of the study was to investigate and compare the physical properties(depth of light cure, degree of conversion, water absorption) of 4 kinds of composit resins prepared in this lab; Bis-GMA based, Bis-EMA based, Bis-GMA/UDMA based, and Bis-EMA/UDMA based composit. Another aim was to compare the physical properties of the composit resins with those of the commercialized products(Charmfil flow(Denkist), Quadrant flow(CAVEX)) in market. All of the composit resins and the commercialized products showed almost same values of the physical properties. It was found that all of the composit resins prepared in this lab satisfied the physical properties specified in ISO 4049.

• Sleep Medicine and Psychophysiology
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• v.2 no.1
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• pp.31-43
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• 1995

Recently, the methods that measure and analyze brain electrical activity quantitatively have been available with the rapid development of computer technology. The quantitative electroencephalography(QEEG) is a method of computer-assisted analyzing brain electrical activity. The QEEG allows for a more sensitive, precise and reproducible examination of EEG data than that can be accomplished by conventional EEG. It is possible to compare various EEG parameters each other by using QEEG. Neurometrics, a kind of the quantitative EEG. is to compare EEG characteristics of the patient with normative data to determine in what way the patient's EEG deviates from normality and to discriminate among psychiatric disorders. Nowadays, QEEG is far superior to conventional EEG in its detection of abnormality and in its usefulness in psychiatric differential diagnosis. The abnormal findings of QEEG in various psychiatric disorders are also discussed.