• Speech Sciences
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• v.7 no.3
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• pp.185-195
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• 2000

This paper seeks to compare the feature parameters used in speaker identification systems under noisy environments. The feature parameters compared are LP cepstrum (LPCC), Cepstral mean subtraction(CMS), Pole-filtered CMS(PFCMS), Adaptive component weighted cepstrum(ACW) and Postfilter cepstrum(PF). The GMM-based text independent speaker identification system is designed for this target. Some series of experiments show that the LPCC parameter is adequate for modelling the speaker in the matched environments between train and test stages. But in the mismatched training and testing conditions, modified parameters are preferable the LPCC. Especially CMS and PFCMS parameters are more effective for the microphone mismatching conditions while the ACW and PF parameters are good for more noisy mismatches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1021-1024
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• 1993

System identification is a major component for a control system. In biosystems, which is nonlinear and dynamic, precise identification would be very helpful for implementing a control system. It is difficult to precisely identify such non-linear systems. The measurable data on products from 2,3-butanediol fermentation could not be included in a process model based on kinetic approach. Meanwhile, a predictive capability is required in developing a control system. A neural network (NN) dynamic identifier with a by/(1＋ t ) transfer function was therefore designed being able to predict this fermentation. This modified inverse NN identifier differs from traditional models in which it is not only able to see but also able to predict the system. A moving window, with a dimension of 11 and a fixed data size of seven, was properly designed. One-step ahead identification/prediction by an 11-3-1 BPNN is demonstrated. Even under process fault, this neural network is still able to perform several-step ahead prediction.

• Bulletin of the Korean Chemical Society
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• v.20 no.9
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• pp.1021-1025
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• 1999

Near-infrared (NIR) spectroscopy has been successfully utilized for the rapid identification of six typical petroleum products such as light straight-run (LSR), naphtha, kerosine, light gas oil (LGO), gasoline, and diesel. The spectral features of each product were reasonably differentiated in the NIR region, and the spectral differences provided enough qualitative spectral information for discrimination. For discrimination, principal component analysis (PCA) combined with Mahalanobis distance was used to identify each petroleum product from NIR spectra. The results showed that each product was accurately identified with an accuracy over 95%. Most noticeably, LSR, kerosine, gasoline, and diesel samples were predicted with identification accuracy of 99%. The overall results ensure that a portable NIR instrument combined with a multivariate qualitative discrimination method can be efficiently utilized for rapid and simple identification of petroleum products. This is especially important when local at-site measurements are necessary, such as accidental petroleum leakage and regulation of illegal product blending.

• Journal of Distribution Science
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• v.19 no.11
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• pp.81-90
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• 2021

Purpose: The purpose of this research is that Metaverse platforms' UXBDI can be distinguished among Metaverse platform channel types. Metaverse platform represents a collective term signifying services that include augmented reality, lifelogging, mirror worlds, and virtual worlds. User Experience-Based Design Innovativeness (UXBDI) is characterized by novelty in product design and services that satisfy user experience. This study examined the effect of Metaverse platforms' UXBDI on user-Metaverse platform relationships. Research design, data and methodology: Metaverse platform users were selected as samples, and a marketing research institution known as a panel company conducted the survey. It used multiple regression to test the impact on platform identification and commitment based on a survey of 442 South Korean respondents. Results: The research confirmed that UXBDI sub-dimensional scales of attractiveness and interaction increased user-Metaverse platform identification and commitment. Also, a Metaverse platform identity increased user-Metaverse platform identification in virtual and mirror worlds. Conclusion: This study contributes to multiple academic fields. First, the UXBDI of Metaverse platforms appears to be a key component of ongoing user-Metaverse relationships. Second, UXBDI affects relationships differently based on the Metaverse platform type.

• MALSORI
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• no.54
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• pp.73-83
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• 2005

The goal of our research is to build a text-independent speaker identification system that can be used in any condition without any additional adaptation process. The performance of speaker recognition systems can be severely degraded in some unknown mismatched microphone and noise conditions. In this paper, we show that PCA(principal component analysis) can improve the performance in the situation. We also propose an augmented PCA process, which augments class discriminative information to the original feature vectors before PCA transformation and selects the best direction for each pair of highly confusable speakers. The proposed method reduced the relative recognition error by 21%.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.413-418
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• 2007

국내 외 많은 컨설팅 및 SI회사들이 나름대로의 SOA방법론을 개발 및 적응하고 있다. 하지만 각 회사의 방법론 마다, SOA 사상 관점에 따라 접근 방향이 상이하고, 수행 방법과 태스크 또한 실제 적응하기에는 상세성이 부족하다. 이 연구에서는 국내 외 SOA 방법론을 비교 분석하고, 실제 적응된 사례를 통하여 특정 도메인에 무관한 현업 사용자 위주의 서비스 식별이라는 명제를 반영한 유저인터페이스 기반의 서비스 분석 및 모델링 방법론을 제시한다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.278-281
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• 2011

The global coordinates generated from Isomap algorithm provide a simple way to analyze and manipulate high dimensional observations in terms of their intrinsic nonlinear degrees of freedom. Thus, Isomap can find globally meaningful coordinates and nonlinear structure of complex data sets, while neither principal component analysis (PCA) nor multidimensional scaling (MDS) are successful in many cases. It is demonstrated that the adapted Isomap algorithm successfully enhances the quality of pattern classification for damage identification in various numerical examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.761-770
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• 2001

As software industry is rapidly evolving, IT business enterprises have been meeting with cutthroat competition in developing software. As software reusability, time to market, and maintainability are considered as a competitive edge, software component techniques have lately attracted considerable attention. Currently, although there are some supporting tools for developing software components, they do not have tight connections among component developing processes such as component identification, component modeling, detailed design, code generation, deployment, and testing. And it is restrictive for users to construct various scales of components on component platform architecture. In this paper, we provide an implementation and a design of a supporting tool for constructing platform-independent software components, which covers all development lifecycles of components. In the phase of component modeling, platform independent, conceptual components are identified from domain model information in the view of system partitioning. Detailed design and implementation of a component are performed on the J2EE platform architecture. And the changes on the design model and source codes are consistently managed by using round-trip techniques.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.6
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• pp.34-41
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• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is de veloped. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, dlgital averaging filter is employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the pmpased method in the parameter identification system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement conf i i the validity of this technique.