• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.1
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• pp.12-21
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• 2004

The purposes of this research were (1) to identify service quality and apparel quality in apparel stores, (2) to examine the influence of service quality, product quality and price on customer satisfaction, (3) to examine the influence of service quality, product quality, price and customer satisfaction on repurchase intention that is important feature of store patronage. The data was collected from 435 female students, career women, and house wives using questionnaire and analyzed by frequency analysis, factor analysis, reliability analysis and regression. The results of this research were as follows: (1) Service quality in apparel stores was divided into six factors: facilities and policy/ salesperson VMD/ after service/ impression and atmosphere/ promotion. (2) Product quality was divided into four factors: objective feature/ expressive feature/ wearing sensation/ fitness. (3) Service quality, product quality, price influenced customer satisfaction. (4) Product quality, price and customer satisfaction influenced repurchase intention directly, but service quality influenced repurchase intention indirectly. (5) Service quality factors that influenced customer to have repurchase intention were facilities and policy, salesperson, and VMD. (6) Product quality factors that influenced customer to have repurchase intention were objective feature and wearing sensation.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.3
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• pp.55-63
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• 1991

Transforming small ultrasonic energy into large mechanical energy is the essential feature of ultrasonic vibration in various application fields. This energy amplification can be obtained by achieving resonance condition between booster or tool horn and transducer. When it has uniform section with small sectional area, one dimensional analysis provides good estimation of the natural frequency of the horn. But, for arbitrary shape of horn, one dimensional analysis can no longer be applied. At present, designing tool horn whose natural frequency is identical to that of transducer requires serveral stages of trial and error in actual manufacturing process. In this paper, frequency analysis program is developed to easily predict the natural frequency of ultrasonic vibration cutting tool with axisymmetry and 3- dimensional shape using finite element method.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.487-490
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• 1999

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based features. The color features are extracted from color histograms of the global image and the wavelet based features are extracted from the invariant moments of the high-pass band image through the spatial-frequency analysis of the wavelet transform. The proposed algorithm, called color and wavelet features based query(CWBQ), is composed of two-step query operations for efficient image retrieval: the coarse level filtering operation and the fine level matching operation. In the first filtering operation, the color histogram feature is used to filter out the dissimilar images quickly from a large image database. The second matching operation applies the wavelet based feature to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• Journal of the Semiconductor & Display Technology
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• v.6 no.2 s.19
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• pp.59-63
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• 2007

Radio Frequency Identification (RFID) is a common term for technologies using micro chips that are able to communicate over short-range radio and that can be used for identifying physical objects. RFID technology already has several application areas and more are being envisioned all the time. While it has the potential of becoming a really ubiquitous part of the information society over time, there are many security and privacy concerns related to RFID that need to be solved. This paper proposes a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. This method improved linear discriminant analysis has reduced the dimension of feature information which has large size of data. Therefore, face feature information can be stored in small memory field of RFID tag. The proposed algorithm in comparison with other previous methods shows better stability and elevated detection rate and also can be applied to the entrance control management system, digital identification card and others.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.5
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• pp.241-249
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• 2003

This paper describes a novel approach for performing eigenvalue analysis and frequency domain analysis of multi-machine power system. The salient feature of this approach is a direct approach for constructing the state matrix equations of linearized power systems about its operating point using modular technique. These state matrix equations are then used to obtain eigenvalues and mode shapes of the system, and frequency response, or Bode, plots of selected transfer functions. The proposed program provides a flexible tool for systematic analyses of tuning PSS's parameters. The paper also presents its application to the analyses of a single-machine infinite bus system and two-area system with 4 machines.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.692-702
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• 2006

In this study, a weighted fuzzy min-max (WFMM) neural network model for pattern classification is proposed. The model has a modified structure of FMM neural network in which the weight concept is added to represent the frequency factor of feature values in a learning data set. First we present in this paper a new activation function of the network which is defined as a hyperbox membership function. Then we introduce a new learning algorithm for the model that consists of three kinds of processes: hyperbox creation/expansion, hyperbox overlap test, and hyperbox contraction. A weight adaptation rule considering the frequency factors is defined for the learning process. Finally we describe a feature analysis technique using the proposed model. Four kinds of relevance factors among feature values, feature types, hyperboxes and patterns classes are proposed to analyze relative importance of each feature in a given problem. Two types of practical applications, Fisher's Iris data and Cleveland medical data, have been used for the experiments. Through the experimental results, the effectiveness of the proposed method is discussed.

• Earthquakes and Structures
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• v.4 no.2
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• pp.181-202
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• 2013

It is well known that the properties of the soil deposits, especially the damping, depend on both frequency and strain amplitude. Therefore it is important to consider both dependencies to calculate the soil response against earthquakes in order to estimate input motions to buildings. However, it has been difficult to calculate the seismic response of the soil considering both dependencies directly. The author has studied the time domain evaluation of the frequency dependent dynamic stiffness, and proposed a simple hysteretic damping model that satisfies the causality condition. In this paper, this model was applied to nonlinear analyses considering the effects of the strain amplitude dependency of the soil. The basic characteristics of the proposed method were studied using a two layered soil model. The response behavior was compared with the conventional model e.g. the Ramberg-Osgood model and the SHAKE model. The characteristics of the proposed model were studied with regard to the effects of element divisions and the frequency dependency that is a key feature of the model. The efficiency of the model was confirmed by these studies.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.151-156
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• 2015

In this paper, we have proposed personal multimodal biometric authentication system based on face detection, recognition and speaker verification for smart-phone environment. Proposed system detect the face with Modified Census Transform algorithm then find the eye position in the face by using gabor filter and k-means algorithm. Perform preprocessing on the detected face and eye position, then we recognize with Linear Discriminant Analysis algorithm. Afterward in speaker verification process, we extract the feature from the end point of the speech data and Mel Frequency Cepstral Coefficient. We verified the speaker through Dynamic Time Warping algorithm because the speech feature changes in real-time. The proposed multimodal biometric system is to fuse the face and speech feature (to optimize the internal operation by integer representation) for smart-phone based real-time face detection, recognition and speaker verification. As mentioned the multimodal biometric system could form the reliable system by estimating the reasonable performance.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.429-440
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• 2014

The iris recognition is a biometrics technology to extract and code an unique iris feature from human eye image. Also, it includes the technology to compare with other's various iris stored in the system. On the other hand, eyelashes in iris image are a external factor to affect to recognition rate of iris. If eyelashes are not removed exactly from iris area, there are two false recognitions that recognize eyelashes to iris features or iris features to eyelashes. Eventually, these false recognitions bring out a lot of loss in iris informations. In this paper, in order to solve that problems, we removed eyelashes by gabor filter that using for analysis of frequency feature and improve preservation rate of iris informations. By novel method to extract various features on iris area using angle, frequency, and gaussian parameter on gabor filter that is one of the filters for analysing frequency feature for an image, we could remove accurately eyelashes with various lengths and shapes. As the result, proposed method represents that improve about 4% than previous methods using GMM or histogram analysis in iris preservation rate.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.123-126
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• 2007

This paper suggests a method to improve the performance of the pathological/normal voice classification. The effectiveness of the mel frequency-based filter bank energies using the fisher discriminant ratio (FDR) is analyzed. And mel frequency cepstrum coefficients (MFCCs) and the feature vectors through the linear discriminant analysis (LDA) transformation of the filter bank energies (FBE) are implemented. This paper shows that the FBE LDA-based GMM is more distinct method for the pathological/normal voice classification than the MFCC-based GMM.