• 한국전자통신학회논문지
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• 제6권6호
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• pp.973-980
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• 2011

본 논문에서는 기존의 문제점인 얼굴 움직임이 있을 시 시선 식별이 어려운 점과 사용자에 따른 교정작업이 필요하다는 점을 해결하고자 새로운 시선 식별 시스템을 제안한다. Kalman필터를 사용하여 현재 머리의 위치정보를 이용하여 미래위치를 추정하였고 얼굴의 진위 여부를 판단하기 위해서 얼굴의 특징요소를 구조적 정보와 비교적 처리시간이 빠른 수평, 수직 히스토그램 분석법을 이용하여 얼굴의 요소를 검출한다. 그리고 적외선 조명기를 구성하여 밝은 동공효과를 얻어 동공을 실시간으로 검출, 추적하였고 동공-글린트 벡터를 추출한다.

• 한국소음진동공학회논문집
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• 제18권8호
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• pp.816-822
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• 2008

This study presents the design modification for SCR muffler of a commercial vehicle. Its main objective is the reduction of radiated noise at SCR muffler. For this study, the research of five steps were achieved by experimental and CAE analysis. First step is the measurement of radiated noise using impact-acoustic test. Second step is the source identification using experimental modal analysis. The cause of radiated noise source is confirmed by the resonance of end plates at SCR muffler. Third step confirms the possibility of resonance avoidance using SDM analysis applied the mass control. Fourth step is the suggestion of design modification which is the change of mode shape by CAE analysis. Last step is the verification of design modification using SYSNOISE analysis. Finally, the prototype product applied the countermeasure of resonance evasion was manufactured and the reduction of radiated noise at SCR muffler was confirmed by pass-by noise test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• Journal of Applied Biological Chemistry
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• 제42권3호
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• pp.146-150
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• 1999

As a part of the integrated disease system in greenhouse, an antifungal fungus(AF1) was isolated from greenhouse soil. It exhibited strong inhibitory activites against Pythium ultimum, Phytophtora capsici, Rhizoctonia solani, Botrytis cinerea, and Fusarium oxysporum based on dual culture on 1/5 strength of potato dextrose agar between antagonistic fungus and several plant pathogens. The antagonistic fungus was identified as Chaetomium cochliodes, based on morphological characteristics; the body of the perithecium bears straight or slightly wavy, unbranched hairs, whilst the apex bears a group of spirally coiled hairs. To investigate antagonistic principles, antifungal compound was extracted and fractionated by different solvent systems. An antifungal compound was isolated as pure crystal from is culture filtrate using organic solvent extraction and column chromatography, followed by preparative thin layer chromatography. The chemical structure of the purified antifungal compound was identified as chaetoglobosin A based on the data obtained form $^1H-NMR$, $^{13}C-NMR$, DEPT 90, 135, $^1H-^1H$ COSY, $^1H-^{13}C$ COSY and EI/MS. $ED_{50}$ values of the chaetoglobosin A against P. ultimum, P. capsici, R. solani, B. cinerea and F. oxysporum were 1.98, 4.01, 4.16, 2.67 and 35.14 ppm, respectively.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.287-292
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• 2005

This paper presents a rational polynomial approximation method to estimate modal parameters of wind excited structures using incomplete noisy measurements of structural responses and partial measurements of wind velocities only. A stochastic model of the excitation wind force acting on the structure is estimated from partial measurements of wind velocities. Then the transfer functions of the structure are approximated as rational polynomial functions. From the poles and zeros of the estimated rational polynomial functions, the modal parameters, such as natural frequencies, damping ratios, and mode shapes are extracted. Since the frequency characteristics of wind forces acting on structures can be assumed as a smooth Gaussian process especially around the natural frequencies of the structures according to the central limit theorem (Brillinger, 1969; Yaglom, 1987), the estimated modal parameters are robust and reliable with respect to the assumed stochastic input models. To verify the proposed method, the modal parameters of a TV transmission tower excited by gust wind are estimated. Comparison study with the results of other researchers shows the efficacy of the suggested method.

• Smart Structures and Systems
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• 제25권3호
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• pp.265-277
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• 2020

Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.

• Journal of Applied Biological Chemistry
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• 제64권4호
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• pp.391-397
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• 2021

Four compounds were isolated from Salvia plebeia aerial parts. Silica gel open column chromatography with a gradient elution system was used to isolate and purify these compounds. Nuclear magnetic resonance spectroscopy and mass spectroscopy were used for structural elucidation and identification, while electronic circular dichroism was used to confirm the absolute configuration. The structures were determined to be 𝛽-sitosterol (1), (-)-1S,5S,8S,10R-1-acetoxy-8-hydroxy-2-oxoeudesman-3,7(11)-dien-8,12-olide (2), ursolic acid (3), and N-methylhydroxylamine (4). Compounds 2 and 4 were isolated for the first time from this plant. Compound 2 was quantitatively analyzed via HPLC/UV. The results showed that the methanol extract of S. plebeia had a higher content of compound 2 (1.20 mg/g) than the ethanol extract (0.55 mg/g). This study could be used as a preliminary step in conducting HPLC/UV analysis of sesquiterpenoids in S. plebeia extract to assess their bioavailability and potency.

• Structural Monitoring and Maintenance
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• 제6권2호
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• pp.161-171
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• 2019

There have been a few checking frameworks intended to ensure and improve the nature of their regular habitat. The greater part of these frameworks are constrained in their capacities. In this paper, the insightful checking framework intended for debacle help and administrations has been exhibited. The ideal administrations, necessities and coming about plan proposition have been indicated. This has prompted a framework that depends fundamentally on ecological examination so as to offer consideration and security administrations to give the self-governance of indigenous habitats. In this sense, ecological acknowledgment is considered, where, in light of past work, novel commitments have been made to help include based and PC vision situations. This epic PC vision procedure utilized as notice framework for avalanche identification depends on changes in the normal landscape. The multi-criteria basic leadership strategy is used to incorporate slope data and the level of variety of the highlights. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

• Structural Monitoring and Maintenance
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• 제7권4호
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• pp.319-344
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• 2020

Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.233-242
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• 2021

Various anatomical MRI imaging biomarkers for Alzheimer's Disease (AD) identification have been recognized so far. Cortical and subcortical volume, hippocampal, amygdala volume, and genetics patterns have been utilized successfully to diagnose AD patients from healthy. These fundamental sMRI bio-measures have been utilized frequently and independently. The entire possibility of anatomical MRI imaging measures for AD diagnosis might thus still to analyze fully. Thus, in this paper, we merge different structural MRI imaging biomarkers to intensify diagnostic classification and analysis of Alzheimer's. For 54 clinically pronounce Alzheimer's patients, 58 cognitively healthy controls, and 99 Mild Cognitive Impairment (MCI); we calculated 1. Cortical and subcortical features, 2. The hippocampal subfield, amygdala nuclei volume using Freesurfer (6.0.0) and 3. Genetics (APoE ε4) biomarkers were obtained from the ADNI database. These three measures were first applied separately and then combined to predict the AD. After feature combination, we utilize the sequential feature selection [SFS (wrapper)] method to select the top-ranked features vectors and feed them into the Multi-Kernel SVM for classification. This diagnostic classification algorithm yields 94.33% of accuracy, 95.40% of sensitivity, 96.50% of specificity with 94.30% of AUC for AD/HC; for AD/MCI propose method obtained 85.58% of accuracy, 95.73% of sensitivity, and 87.30% of specificity along with 91.48% of AUC. Similarly, for HC/MCI, we obtained 89.77% of accuracy, 96.15% of sensitivity, and 87.35% of specificity with 92.55% of AUC. We also presented the performance comparison of the proposed method with KNN classifiers.