• Journal of the Korean Applied Science and Technology
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• v.37 no.4
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• pp.996-1007
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• 2020

The purpose of this study was to investigate the general characteristics, working condition, discrimination experience and job engagement of office workers and to examine the effect of discrimination experience on job engagement. This study was the secondary analysis of date from the fifth Korean Working Conditions Survey and the subjects included 6,718 office workers. Collected data were analyzed using descriptive statistics, x²-test, t-test, and complex samples general linear model(CSGLM). As a result, job engagement was high when they never experienced discrimination. Based on the results of this study, in order to improve job engagement of office workers, manage to prevent discrimination in the workplace should be included.

• Plant Biotechnology Reports
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• v.3 no.1
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• pp.87-93
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• 2009

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves and fruits of five commercial strawberry cultivars were subjected to Fourier transform infrared (FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Fisher's linear discriminant function analysis. The dendrogram based on hierarchical clustering analysis of these spectral data separated the five commercial cultivars into two major groups with originality. The first group consisted of Korean cultivars including 'Maehyang', 'Seolhyang', and 'Gumhyang', whereas in the second group, 'Ryukbo' clustered with 'Janghee', both Japanese cultivars. The results from analysis of fruits were the same as of leaves. We therefore conclude that the hierarchical dendrogram based on PCA of FT-IR data from leaves represents the most probable chemotaxonomical relationship between cultivars, enabling discrimination of cultivars in a rapid and simple manner.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.167-175
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• 2016

The volatile component analysis of 82 commercialized liquors(44 samples of single malt whisky, 20 samples of blended whisky and 18 samples of brandy) was carried out by gas chromatography after liquid-liquid extraction with dichloromethane. Pattern recognition techniques such as principle component analysis(PCA), cluster analysis(CA), linear discriminant analysis(LDA) and partial least square discriminant analysis(PLSDA) were applied for the discrimination of different liquor categories. Classification rules were validated by considering sensitivity and specificity of each class. Both techniques, LDA and PLSDA, gave 100% sensitivity and specificity for all of the categories. These results suggested that the common characteristics and identities as typification of whiskies and brandys was founded by using multivariate data analysis method.

• Journal of electromagnetic engineering and science
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• v.4 no.3
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• pp.128-136
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• 2004

In this paper,. with the aim of achieving the expected performance improvement for a polarization diversity system, we analyzed two-branch polarization diversity at the receiving end of a mobile link which a transmitter emits circularly polarized wave. In this analysis, to calculate the correlation coefficient considered by XPD(cross polarization discrimination) between the two received signals, a simple theoretical model of circular polarization diversity is adopted. From the analysis results, it is clearly seen that the correlation coefficient of circular polarization diversity evaluated by the XPD is less than that of conventional linear polarization diversity. And also, we designed and implemented a circular polarization diversity system with micro-strip antenna. By using the circular polarization diversity system, we analyzed the measured data in indoor NLOS(Non-Line-Of-Sight) environments. From this analysis results, it is also clearly seen that the diversity effect of circular polarization diversity system shows better performance compared to the conventional linear diversity system by about 3 dB high.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.1-6
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• 2006

This study proposes a new approach which combines Data Envelopment Analysis(DEA) and the Analytic Hierarchy Process(AHP) techniques to effectively evaluate Decision Making Units(DMUs). While DEA evaluates a quantitative data set, employs linear programming to obtain input and output weights and ranks the performance of DMUs, AHP evaluates the qualitative data retrieved from expert opinions and other managerial information in specifying weights. The objective of this research is to design a decision support process for managers to incorporate positive aspects of DEA's absolute numerical evaluations and AHP's human preference structure values. It is believed that a pragmatic manager will be more receptive to the results that include subjective opinions incorporated into the evaluation of the efficiency of each DMU efficiency. The WPDEA method provides better discrimination than the DEA method by reducing the number of efficient units.

• Smart Structures and Systems
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• v.26 no.1
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• pp.23-33
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• 2020

Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.2
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• pp.23-31
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• 1990

Acoustic Emission(AE) signals obtained during fracture toughness test and fatigue test for nuclear pressure vessel material(SA 508 cl.3) and artificial AE signals from pencil break and ultrasonic pulser were classified using pattern recognition methods. Three different classifiers ; namely Minimum Distance Classifier, Linear Discriminant Classifier and Maximum Likelihood Classifier were used for pattern recognition. In this study, the performance of each classifier was compared. The discrimination of AE signals from cracking and crack surface rubbing was possible and the analysis for crack propagation was applicable by pattern recognition methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.86-94
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• 1996

The aims of this study were to describe the way in which sound durations are perceived, and to attempt to explain the hidden mechanisms of the duration perception in music performances. Three experiments were carried out to determine the difference limen for the perception of sound duration and to find the effects of frequency and intensity on duration discrimination. For short duration tones ranging from 25 to 100 msec, a linear improvement in discrimination judgements was found with increasing duration of signal. The JND was constant for durations between 100 msec and 2 sec. However, for extended stimulus durations (more than 2 sec) the JND was again linearly improved. Subjects were also presented with a pair of stimuli, composed of high and low frequency pure tones, and asked to discriminate differences in duration of the two tones and ignore differences in the frequency of the tones. It was found that subjects perceived the higher frequency to be longer in duration. When an experiment was carried out to investigate the effect of intensity on duration discrimination it was found that a 20 phon difference makes subjects perceive the louder stimulus as longer than the quieter stimulus. Finally, in a performance study, an analysis of musical performances revealed the effect of frequency. It was found that the musicians played the higher notes shorter than the lower notes. This agrees with what was previously found in the work on the perception of tones.

• Korean Journal of Computational Design and Engineering
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• v.19 no.1
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• pp.68-79
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• 2014

Human model simulation has been widely used in various industrial areas such as ergonomic design, product evaluation and characteristic analysis of work-related musculoskeletal disorders. However, the process of building digital human models and capturing their behaviors requires many costly and time-consuming fabrication iterations. To overcome the limitations of this expensive and time-consuming process, many studies have recently presented a markerless motion capture approach that reconstructs the time-varying skeletal motions from optical devices. However, the drawback of the markerless motion capture approach is that the phenomenon of occlusion of motion data occurs in real-time human simulation. In this study, we propose a systematic method of discriminating missing or inaccurate motion data due to motion occlusion and interpolating a sequence of motion frames captured by a markerless depth camera.