• 대한기계학회논문집A
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• 제26권12호
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• pp.2574-2580
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• 2002

In this paper, an experimental verification has been conducted for the frequency response function (FRF)-based structural damage identification method (SDIM) proposed for beam structures. The FRF-based SDIM requires the natural frequencies and mode shapes measured in the intact state and the FRF-data measured in the damaged state. Experiments are conducted for the cantilevered beam specimens with one slot and with three slots. It is shown that the proposed FRF-based SDIM provides damage identification results that agree quite well with true damage state.

• Genomics & Informatics
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• 제14권1호
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• pp.12-19
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• 2016

Neuropeptides produced from prohormones by selective action of endopeptidases are vital signaling molecules, playing a critical role in a variety of physiological processes, such as addiction, depression, pain, and circadian rhythms. Neuropeptides bind to post-synaptic receptors and elicit cellular effects like classical neurotransmitters. While each neuropeptide could have its own biological function, mass spectrometry (MS) allows for the identification of the precise molecular forms of each peptide without a priori knowledge of the peptide identity and for the quantitation of neuropeptides in different conditions of the samples. MS-based neuropeptidomics approaches have been applied to various animal models and conditions to characterize and quantify novel neuropeptides, as well as known neuropeptides, advancing our understanding of nervous system function over the past decade. Here, we will present an overview of neuropeptides and MS-based neuropeptidomic strategies for the identification and quantitation of neuropeptides.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• 산업기술연구
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• 제19권
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• pp.127-133
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• 1999

This paper is a research about system identification which optimizes uncertain geothechnical properties from the data measured during geotechnical design and construction. Various numerical optimization algorithms of Simplex method, Powell method, Rosenbrock method and Levenberg-Marquardt method were applied to the excavation problem to determine which method showed the best results with respect to robustness of success in finding an optimal solution to within a certain accuracy and number of function evaluations. From the results of numerical analysis, all of four algorithms are converged to exact solution after satisfying the allowed criteria, and Levenberg-Marquardt's algorithms was identified to be the most efficient method in number of function evaluations. System identification was applied to geotechnical engineering problems, possibly being occurred in field, to verify its applicability : estimation of settlement due to self-weight consolidation in dredged and filled soil. For self-weight consolidational settlement of a dredged soil, a program of evaluating the constitutive relationship of effective stress-void ratio-permeability was developed by using the technique of system identification. Thus, consolidational characteristics of a dredged soil, having a very high initial void ratio, can be evaluated.

• Structural Engineering and Mechanics
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• 제75권4호
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• pp.445-454
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• 2020

Structural damage identification (SDI) is a crucial step in structural health monitoring. However, some of the existing SDI methods cannot provide enough identification accuracy and efficiency in practice. A novel whale optimization algorithm (WOA) based method is proposed for SDI by weighting modal data and flexibility assurance criterion in this study. At first, the SDI problem is mathematically converted into a constrained optimization problem. Unlike traditional objective function defined using frequencies and mode shapes, a new objective function on the SDI problem is formulated by weighting both modal data and flexibility assurance criterion. Then, the WOA method, due to its good performance of fast convergence and global searching ability, is adopted to provide an accurate solution to the SDI problem, different predator mechanisms are formulated and their probability thresholds are selected. Finally, the performance of the proposed method is assessed by numerical simulations on a simply-supported beam and a 31-bar truss structures. For the given multiple structural damage conditions under environmental noises, the WOA-based SDI method can effectively locate structural damages and accurately estimate severities of damages. Compared with other optimization methods, such as particle swarm optimization and dragonfly algorithm, the proposed WOA-based method outperforms in accuracy and efficiency, which can provide a more effective and potential tool for the SDI problem.

• 동의생리병리학회지
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• 제27권5호
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• pp.553-562
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• 2013

This study was performed to develop cold-heat and deficiency-excess pattern identification for dementia, as well as for standard Korean medicine diagnosis and treatment. Five experts comprised of 4 neuropsychiatrists of Korean medicine and 1 statistician to develop cold-heat and deficiency-excess pattern identification for dementia. We searched studies about pattern identification and selected 507 articles using Oasis search terms provided by the KIOM. As a result, 10 pattern identification research study were recruited. Moreover, we analyzed neuropsychological assessments for dementia that evaluate Behavioral and Psychological Symptoms of Dementia (BPSD) and cognitive function using experts conferences and we selected neuropsychological instruments using pattern identification. Six cold patterns, six heat patterns, ten deficiency patterns, and four excess patterns were identified according to the cold-heat and deficiency-excess pattern identification of dementia. We selected the Caregiver-Administered Neuropsychiatric Inventory and the Korean Mini-Mental State Examination as neuropsychological assessments of dementia, which examine behavioral symptoms and cognitive function, suspectively. We formed positive and negative correlation between Korean medicine pattern identification and neuropsychological assessments for dementia. We developed and suggested a forecast module of pattern identification for dementia. But, it is necessary to perform additional clinical trials to verify its validity and accuracy.

• 대한의용생체공학회:의공학회지
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• 제14권4호
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• pp.387-396
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• 1993

In this paper, a laryngeal function identification system based-on the EGG signal is proposed as the decision basis whether the laryngeal function is normal or abnormal. The normal EGG signal is approved an autoregressive model which has the optimal order of 9. It can be analized by determining the transfer function. But it is not meaningful that the determi- nation is made using the transfer function of an autoregressive model on the abnormal EGG signal. The power spectral analysis was applied to discriminate the normal or abnormal cases. The SNR of the EGG signal was enhanced by the optimal position of electrodes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.26.5-26
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• 2001

This paper proposes a new approach to identifying the unknown parameters of continuous LTI systems. For parameter identification in continuous-time systems, the Linear Integral Filter (LIF) method generally has been used in the beginning. Especially, one of the most efficient LIF methods in the literature is to use a weighting function satisfying specific three constraints. In high order systems, even though the weighting function satisfies the three constraints, it is impossible to identify the exact parameters of the systems because of information loss arising from a great amount of magnitude differences among the weighting function and its high-order derivatives. This paper, using an LMI technique, shows the limitation in designing the weighting function of the existing methods, and ...

• 대한전기학회논문지:시스템및제어부문D
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• 제50권7호
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• 한국멀티미디어학회논문지
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• 제7권2호
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• pp.156-163
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• 2004

본 논문에서는 적응적 얼굴영역 검출과 얼굴 특징자 평가함수를 사용한 실시간 얼굴인식 알고리즘을 제안하였다. 제안한 알고리즘은 명암도 정보와 타원마스킹 기법뿐만 아니라 인종별 얼굴피부색을 사용하여 정확한 얼굴영역을 적응적으로 검출 가능하다. 또한 제안한 알고리즘은 얼굴 특징자 및 얼굴특징자간 기하학적 평가함수를 사용하여 얼굴 인식 효율을 개선하였다. 제안한 알고리즘은 생체인증 및 보안 시스템 분야에 사용 가능하다. 실험에서는 제안한 방법의 우수성을 입증하기 위해 실 영상을 사용하였으며 실험 결과 기존의 방법보다 얼굴 영역 검출뿐만 아니라 얼굴인식 성능을 개선하였다.