• Bulletin of the Korean Chemical Society
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• v.31 no.7
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• pp.1902-1906
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• 2010

A microchip electrophoresis (ME) method was developed using a programmed field strength gradients (PFSG) for the single nucleotide polymorphism (SNP) based fast identification of cattle breeds. Four different Korean cattle (Hanwoo) and Holstein SNP markers amplified by allele-specific polymerase chain reaction were separated in a glass microchip filled with 0.5% poly(ethyleneoxide) ($M_r$ = 8 000 000) by PFSG as follows: 750 V/cm for 0 - 14 s, 166.7 V/cm for 14 - 31 s, 83.3 V/cm for 31 - 46 s, and 750 V/cm for 46 - 100 s. The cattle breeds were clearly distinguished within 45 s. The ME-PFSG method was 7 times and 5 times faster than the constant electric field ME method and the capillary electrophoresis- PFSG method, respectively, with a high resolving power ($R_s$ = 5.05 - 9.98). The proposed methodology could be a powerful tool for the fast and simultaneous determination of SNP markers for various cattle breeds with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1460-1478
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• 2020

This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.180-182
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• 2005

Fingerprint-based identification is known to be used for a very long time. Owing to their uniqueness and immutability, fingerprints are today the most widely used biometric features. Therefore, recognition using fingerprints is one of the safest methods as a way of personal identification. But fingerprint identification system has a critical weakness. Since the fingerprint identification time dramatically increase when we compare the unknown fingerprint's minutiae with fingerprint database's minutiae. In this paper, a ridge orientation extraction method using Index table is proposed to solve the problem. The goal of fast direction image extraction is to reduce the identification time and to improve the clarity of ridge and valley structures of input fingerprint image.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.574-581
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• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Networks(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Self-Organized Distributed Networks (SODN). The learning with the SODN is fast and precise. Such properties are caused from the local learning mechanism. Each local network learns only data in a subregion. This paper also discusses neural network as identifier of nonlinear dynamical systems. The structure of nonlinear system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems. (author). 13 refs., 7 figs., 2 tabs.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.134-136
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• 2003

This paper proposes an algorithm for fingerprint identification using phase only correlation. This algorithm uses the phase of fast Fourier transform and correlation function to calculate the similarity. The algorithm gives very clear result for identification because it shows only one conspicuous sharp peak for the same person's fingerprint. Further, it shows good results even for the finger print images which are printed not clearly and does not need to preprocess the images. It also shows good results for parallel displacement of fingerprint. The experiment result shows the effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.3
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• pp.403-411
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• 2008

In 2005, A. Saxena, B. Soh and S. Priymak [10] proposed a two-flow blind identification protocol. But it has a weakness of the active-intruder attack and uses the pairing operation that causes slow implementation in smart cards. In 2008, Y. W. Lee [9] made a method of the active-intruder attack on their identification scheme and proposed a new zero-knowledge blind identification protocol for smart cards. In this paper, we give more simple and fast protocols than above protocols such that the prover using computationally limited devices such as smart cards has no need of computing the bilinear pairings. Computing the bilinear pairings is needed only for the verifier and is secure assuming the hardness of the Discrete-Logarithm Problem (DLP).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1165-1168
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• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Network(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Radial Basis Function Networks(RBFN). The learning with RBFN is fast and precise. This paper discusses RBFN as identification procedure is based on a nonlinear dynamical systems. and A design method of model follow control system based on RBFN controller is developed. As a result of applying this method to inverted pendulum, the simulation has shown that RBFN can be used as identification and control of nonlinear dynamical systems effectively.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.59-65
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• 2004

Personal identification using fingerprints needs much calculational effort. Generally, there are various methods for fingerprint-based identification. In this paper, an identification method is proposed which is based on direction distribution of fingerprint ridges. An 8-directional Gabor filter bank is used for extracting the feature vector from the given fingerprint. Then, it is compared with those of registered fingerprints for matching. This method is simple and fast to implement because it uses the information of ridge directions only. An experiment on 532 fingerprints from NIST database and some other source shows its usefulness.