• Korean Journal of Audiology
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• v.23 no.1
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• pp.39-48
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• 2019

Background and Objectives: The influence of visual stimulus on the auditory component in the perception of auditory-visual (AV) consonant-vowel syllables has been demonstrated in different languages. Inherent properties of unimodal stimuli are known to modulate AV integration. The present study investigated how the amount of McGurk effect (an outcome of AV integration) varies across three different consonant combinations in Kannada language. The importance of unimodal syllable identification on the amount of McGurk effect was also seen. Subjects and Methods: Twenty-eight individuals performed an AV identification task with ba/ga, pa/ka and ma/ṇa consonant combinations in AV congruent, AV incongruent (McGurk combination), audio alone and visual alone condition. Cluster analysis was performed using the identification scores for the incongruent stimuli, to classify the individuals into two groups; one with high and the other with low McGurk scores. The differences in the audio alone and visual alone scores between these groups were compared. Results: The results showed significantly higher McGurk scores for ma/ṇa compared to ba/ga and pa/ka combinations in both high and low McGurk score groups. No significant difference was noted between ba/ga and pa/ka combinations in either group. Identification of /ṇa/ presented in the visual alone condition correlated negatively with the higher McGurk scores. Conclusions: The results suggest that the final percept following the AV integration is not exclusively explained by the unimodal identification of the syllables. But there are other factors which may also contribute to making inferences about the final percept.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.139-150
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• 2001

An initial approach for the identification of physical causes underlying the spatial coherency of seismic ground motions it presented. The approach relies on the observation that amplitude and phase variability of seismic data recorded over extended areas around the amplitude and phase of a common, coherent component are correlated. It suffices then to examine the physical causes for the amplitude variability in the seismic motions, in order to recognize the causes for the phase variability and, consequently, the spatial coherency. In this study, the effect of randomness in the shear wave velocity at a site on the amplitude variability of the surface motions mi investigated by means of simulations. The amplitude variability of the simulated motions around the amplitude of the common component is contained within envelope functions, the shape of which suggests, on a preliminary basis, the trend of the decay of coherency with frequency.

• ETRI Journal
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• v.36 no.1
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• pp.175-178
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• 2014

We introduce the Energy-Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative-form separation and closed-form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second-order blind identification (SOBI) algorithm in terms of separation quality.

• Korean System Dynamics Review
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• v.5 no.2
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• pp.199-216
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• 2004

The present study is aimed at developing the optimal instruments for dispelling the uncertainty factors during the formulation of strategies for corporate development. The objective is the creation of a complete model of strategic analysis, which encompasses both the environment (internal and external) and the management rational component. This model -built on the analysis of three corporate cases - is concretized by a simulation for testing the strategy by the means of software which enables the users to cope with a dynamic and complex corporate environment. The research questions regard the development of a complete strategic analysis, which covers the entire decision-making process; the concrete assessment of the business strategy on the basis of quantitative data: the identification and enhancement of the critical variables of business administration, in such a complex and dynamic reality as the corporate environment.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.322-324
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• 2003

생체인식 기술은 현재까지 많은 발전을 거듭하고 있으며 국내에서도 연구는 물론 표준화작업 및 데이터 베이스 구축이 활발히 진행되고 있다. 생체인식은 신체의 여러 부분을 이용하는 방법과 습관에서 비롯된 특징을 이용하는 방법이 있는데, 본 연구에서는 이 중에서 개인의 필기습관 정보를 이용하여 인식하였다. 본 연구에서는 필기습관에 주목하여 서명하는 사람의 습관이 잘 드러나는 펜의 기울임과 눌림, 펜의 방위각도 둥의 성분이 표현되어지는 동적인 생채정보를 감지하고 특성을 추출할 수 있는 타블렛과 펜을 사용하여 서명정보를 추출한다. 이렇게 생성된 서명정보의 특징을 추출하기 위하여 패턴인식분야에 널리 활용하고 있는 주성분요소분석(PCA, Principal Component Analysis), 독립성분요소분석(ICA, Independent Component Analysis)기법에 적용하였다. 생성된 두 특징벡터 사이의 거리를 Euclidean Distance를 이용하여 구하고 Nearest Neighbor를 비교하여 인식률을 알아보고 교차인식(Cross Validation) 기법 중 하나인 Leave-One-Out 방법을 이용한 분류성능 측정을 통하여 데이터의 신뢰수준을 알아보았다.

• International Journal of Safety
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• v.11 no.2
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• pp.22-25
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• 2012

This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2003.04a
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• pp.105.1-105
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• 2003

This study was performed to develop the precise and rapid method to distinguish the blended sesame oil through the electronic nose analysis. The sesame oil was blended with corn oil at the ratio of 95:5, 90:10, 80:20(w/w), respectively. Samples were then analyzed by gas chromatography, SPME-GC/MS and the electronic nose composed of 12 metal oxide sensors. The sensetivities(delta Rgas/Rair) of sensors by electronic nose was carried out with principal component analysis(PCA). The proportion of first principal component showed 98.76%. In this study, the electronic nose analysis could be used as a competent method to classify for genuine sesame oil.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.139-141
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• 1993

A new scheme to measure the rotor time constant and to set the slip gain of a vector-controller is presented. The approach utilizes the phase difference between the torque producing component of the stator current and rotor current in the stationary frame. It is shown that the rotor time constant can be uniquely identified by detecting the corresponding phase difference. The simulation was carried out by considering the variation of other parameters and the torque producing component of the stator current frequency.