• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.134-135
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• 1993

The purpose of this research is development of EGG system for quantitative assessment of laryngeal function using speech and electroglotto-graphic data. The designed EGG system is 4-electrodes system which excitation current source is supplied from 1st to 4th electrode. The output signal.: from 2nd and 3rd electrodes, which are motivated by frequency of excitation current source, are air-pressure waveforms from vocal folds. After demodulation process, we obtain pitch signals of the modulated waveforms by excitation current source through differentiator which cuts off frequency below 0.1Hz. Software processing methods were used as conventional pitch extraction methods, but the proposed system is designed to analog hardware in order to eliminate interferences from low formant frequency of speech. We will construct the discriminating database between pathological subjects and control groups on each case. Using the proposed 3 channel EGG system and LMS algorithm, it will be detected that the distinctive characteristics of laryngeal function of voiced region and other regions by EGG signals and LPC spectra.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1058-1062
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• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.

• Human Ecology Research
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• v.57 no.1
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• pp.109-125
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• 2019

Few studies have utilized observational methods in the field of couple research even though using self-report questionnaires is prone to the subjective biases of the reporter. This study validates the Marital Interaction Coding System-Global (MICS-G), a global version of the well-established microanalytic observational coding system, Marital Interaction Coding System (MICS). Participants in the study consisted of 30 married couples with varied levels of marital adjustment who visited one of the Healthy Family and Multicultural Family Support Centers in Seoul, either for couple therapy or the "Marriage Checkup"program. Ten-minute problem-solving discussions were rated by two undergraduate student raters who were trained for 10 hours. Interobserver agreement based on percentage agreement and intraclass correlation coefficients showed a high level of agreement between raters in establishing interrater reliability. Convergent validity was established by: correlations among marital adjustment, psychological aggression, mental health, and MICS-G categories of conflicts, validation, invalidation, facilitation, and withdrawal. MICS-G categories also were successful in discriminating between distressed and nondistressed couples, which provides evidence of discriminant validity for MICS-G. This study showed that MICS-G is a promising method for researchers to observe couple interactions in a more cost-effective way. Methodological issues and practical applications are also discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.5
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• pp.131-139
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• 2007

Vulnerability analysis helps to remove discriminating vulnerabilities that exist in various equipment that composes operating information system. It is possible to explain representation and exclusion method about vulnerabilities of each equipment by vulnerability analysis. But it is difficult to display the weakness of whole information system. To do this, analyst synthesizes several information that achieved by vulnerability analysis. But the existing method does not provide fair evaluation because operators' personal opinion. In this paper, we explain about method that unites discriminatively vulnerable point and expresses whole weakness degree in numerical value by equipment, by system class, or by overall system.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.69-75
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• 2001

Intra-speaker variation, noise environments, and mismatch between training and test conditions are the major reasons for the speaker verification system unable to use it practically. In this study, we propose robust end-point detection algorithm, noise cancelling with the microphone property compensation technique, and inter-speaker discriminate technique by weighting cepstrum for robust speaker verification system. Simulation results show that the average speaker verification rate is improved in the rate of 17.65% with proposed end-point detection algorithm using LPC residue and is improved in the rate of 36.93% with proposed noise cancelling and microphone property compensation algorithm. The proposed weighting function for discriminating inter-speaker variations also improves the average speaker verification rate in the rate of 6.515%.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.1
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• pp.79-83
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• 1998

We analyzed dynamic-strain perturbations applied to a fiber Bragg grating. The fiber Mach-Zehnder interferometer was used, and by analyzing the interference signal wecould obtain the frequency and relative amplitude information of the dynamic-perturbation. The minimum detectable dynamic-strain using the system was ~9.5 nstrain RMS/.root.(Hz) at 500 Hz. Also we proposed and demonstrated a new method which uses a temperature-discriminating dual-trating sensor head. With the method, we could measure the dynamic -strain as well as static-static-strain even for the case in which the optical pathe difference modulation was applied.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.549-554
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• 2012

Noncontactable joystick for a low speed electric vehicle(LSEV) is developed. The joystick is proposed to replaced the steering wheel in a conventional LSEV. The main advantages of the proposed joystick are a durable and a stable in structure, simple and easy to control through discriminating the driving and braking area. To reduce error and stability in the joystick control, input and output signal of the joystick are manipulated by data averaging and differntiation. With this algorithm, the driving resolution and capability are improved. To verify the proposed algorithm, a simple prototype model which has two electric motors for propulsion and steering are used. Test results show that the prototype joystick control system is applicable to an LSEV dirve.

• Journal of Computing Science and Engineering
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• v.10 no.4
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• pp.128-136
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• 2016

It is impossible for any human being to analyze the more than 500 million tweets that are generated per day. Lexical ambiguities on Twitter make it difficult to retrieve the desired data and relevant topics. Most of the solutions for the word sense disambiguation problem rely on knowledge base systems. Unfortunately, it is expensive and time-consuming to manually create a knowledge base system, resulting in a knowledge acquisition bottleneck. To solve the knowledge-acquisition bottleneck, a topic signature is used to disambiguate words. In this paper, we evaluate the effectiveness of various features of newspapers on the topic signature extraction for word sense discrimination in tweets. Based on our results, topic signatures obtained from a snippet feature exhibit higher accuracy in discriminating company names than those from the article body. We conclude that topic signatures extracted from news articles improve the accuracy of word sense discrimination in the automated analysis of tweets.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.49-56
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• 2018

Virtual object weight perception is an important topic, as it heightens the believability of object manipulation in immersive virtual environments. Although weight perception can be achieved using haptic interfaces, their technical complexity makes them difficult to apply in immersive virtual environments. In this study, we present a visual pseudo-haptic feedback system that simulates and depicts the weights of virtual objects, the effect of which is weight perception. The proposed method recognizes grasping and manipulating hand motions using computer vision-based tracking methods, visualizing a Force Arrow to indicate the current lifting forces and its difference from the standard lifting force. With the proposed Force Arrow method, a user can more accurately perceive the logical and unidirectional weight and therefore control the force used to lift a virtual object. In this paper, we investigate the potential of the proposed method in discriminating between different weights of virtual objects.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.130-139
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• 1994

Video compression algorithms are based on removing spatial and/or temproal redundancy inherent in image sequences by predictive(DPCM) encoding, transform encoding, or a combination of predictive and transform encoding. In this paper, each 8$\times$8 DCT coefficient of DFD(displaced frame difference) is adaptively quantized by one of the four quantizers depending on total distortion level, which is determined by characteristics of HVS(human visual system) and buffer status. Therefore, the number of possible quantizer selection vectors(patterns) is 4$^{64}$. If this vectors are coded, toomany bits are required. Thus, the quantizer selection vectors are limited to 2048 for Y and 512 for each U, V by the proposed method using SWAD(sum of weighted absolute difference) for discriminating vectors. The computer simulation results, using the codebook vectors which are made by the proposed method, show that the subjective and objective image quality (PSNR) are goor with the limited bit allocation. (17Mbps)