• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.248-255
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• 2003

This paper presents a fingerprint recognition algorithm using cross-correlation function. This algorithm consists of minutiae extraction, minutiae alignment and minutiae matching, where we propose a new minutiae alignment method. In our alignment method, the rotation angle between two fingerprints is obtained by using cross-correlation function of the minutia directions, thereafter the displacement is obtained from the rotated fingerprint. This alignment method is capable of finding rotation angle and displacement of two fingerprints without resorting to exhaustive search. Our fingerprint recognition algorithm has been tested on fingerprint images captured with inkless scanner. The experiment results show that 17.299% false rejection ratio(FRR) at 2.086% false acceptance ratio(FAR).

• Applied Chemistry for Engineering
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• v.34 no.4
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• pp.388-396
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• 2023

The evaluation of fire risk for combustible materials was carried out using Chung's equations-X, Chung's equations-XI, and Chung's equation-XII, which were newly established. The fire risk index-XII (FRI-XII) and fire risk rating (FRR) were calculated for specimens including camphor tree, cherry, rubber tree, and elm. The combustion characteristics were determined using a cone calorimeter according to ISO 5660-1. Chung's equations caculated the fire performance index-X (FPI-X) and fire growth index-X (FGI-X) values ranged from 89.34 to 1696.75 s² /kW and from 0.0006 to 0.0107 kW/s² , respectively. In addition, the fire performance index-XI (FPI-XI) and fire growth index-XI (FGI-XI) varied from 0.08 to 1.48 and from 0.67 to 11.89, respectively. The fire risk index-XII (FRI-XII), which is an indicator of fire risk, showed that camphor tree had a value of 148.63 (fire risk rating: G), indicating a very high fire risk. This suggests that combustible materials with a high concentration of volatile organic compounds have lower FPI-X and FPI-XI values, higher FGI-X and FGI-XI values, and consequently higher FRI-XII values, indicating an increased fire risk.

• Applied Chemistry for Engineering
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• v.34 no.2
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• pp.144-152
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• 2023

To evaluate the fire risk of combustible materials, Chung's equations VII, VIII, and IX were newly established. The fire risk index-IX (FRI-IX) and fire risk rating (FRR) were calculated. Ginkgo, dawn redwood, toona, lime, walnut, and polymethylmethacrylate (PMMA) were selected as test specimens. The combustion characteristics were evaluated using a cone calorimeter according to ISO 5660-1. After combustion, the fire performance index-VII (FPI-VII) of the specimens, varied between 15.15 and 182.53 s²/kW, as determined by Chung's equations, and the fire growth index-VII (FGI-VII) varied between 0.0023 and 0.0165 kW/s². The fire performance index-VIII (FPI-VIII) based on PMMA varied between 0.29 and 3.45, and the fire growth index-VIII (FGI-VIII) varied between 2.88 and 20.63. The FRI-IX, which is the fire risk rating, showed dawn redwood has a very high fire risk, with FRI-IX values of 71.14 (fire risk rating: G). Therefore, wood with a large amount of volatile organic compounds and a low bulk density showed a high value of FRI-IX by lowering FPI-VII and FPI-VIII and increasing FGI-VII and FGI-VIII.

• MALSORI
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• no.43
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• pp.45-55
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• 2002

High reliability of automatic speaker recognition regardless of voice conditions is necessary for forensic application. Audio recordings in real cases are not consistent in voice conditions, such as duration, time interval of recording, given text or conversational speech, transmission channel, etc. In this study the variation of verification error rate of ASR system with the voice conditions was investigated. As a result in order to decrease both false rejection rate and false acception rate, the various voices should be used for training and the duration of train voices should be longer than the test voices.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.433-436
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• 2001

본 논문에서는, 지문인식에 있어서 특징 추출알고리즘과 추출된 특징을 가지고, matching하는 알고리즘을 제안하였다. 지문인식에 필요한 특징추출 알고리즘들은 Gabor-filter라는 알고리즘에 기반을 두었으며, minutiae 와는 달리 특징추출에 있어서 전처리과정(smoothing, binarization, thining, restoration) 을 필요로 하지않는다. 또한, 지문의 matching에 있어서의 알고리즘은 fingercode들 간의 유사성에 기반을 두었다. 이를 통한 실 험결과로써, 인식의 정확성은 95.7(%), FAR(2.9%), FRR(1.4%)을 보여주었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.3.2-6
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• 2000

ATM 네트워트 기술은 초고속 인터넷의 멀티미디어 서비스의 통합을 해결하기 위한 기술로 널리 사용되고 있다. ATM 망에서 UBR 서비스는 데이터 트래픽의 어플리케이션을 지원하기 위해 설계되었다. 그러나 UBR 서비스는 명백한 제어매커니즘이 없어 셀 폐기와 재전송의 위험이 크다. 본 논문에서는 UBR 스위치 버퍼 정책으로 EPD을 효과적으로 적용시키기위해 UBR 스위치 파리미터를 조정하고, TCP 종단시스템 정책으로 빠른 재전송과 회복 (FRR)을 도입하여 LAN과 WAN 환경에서 시뮬레이션을 통해 성능평가하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.169-172
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• 2003

본 논문에서는 기존의 분절 단위 비교방법에서 참조서명과 비교서명간에 분할점 개수와 위치에 대한 불일치 문제를 개선하기 위해 구간 분할 매칭 방법을 제안한다. 제안된 분할방법은 시간에 대한 x와 y좌표 상에서 서명마다 변하지 않는 특징점을 구간 분할점으로 선택하여 구간별로 매칭시킴으로서 분절의 안정적인 분할을 통해 인식률을 높이고자 한다. 실험 결과에서 진서명과 위조서명을 포함한 기타서명에 대해 FAR이 0.06%일 때 FRR 1.25%의 오류율을 확인하였으며 FAR이 0%일 때의 평균인식율이 98.7%를 보임으로써 제안한 서명 검증 기법이 우수함을 확인 할 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.215-222
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• 2005

In this paper, we propose a fingerprint verification algorithm for the embedded system based on the minutia extracted using the image quality, the minutia structure, and the Sequency and the orientation of ridges. After the pre- and the post-processing, the true minutia are selected, thus it shows high reliability in the fingerprint verification. In matching process, we consider the errors caused by shift, rotation, and pressure when acquiring the fingerprint image and reduce the matching time by applying a local matching instead of a full matching to select the reference pair. The proposed algorithm has been designed and verified in Arm920T environment and various techniques for the realtime process have been applied. Time taken from the fingerprint registration through out the matching is 0.541 second that is relevant for the realtime applications. The FRR (False Reject Rate) and FAR (False Accept Rate) show 0.079 and 0.00005 respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.67-73
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• 2005

Recently, the social requirement of personal identification techniques has been increasing. Fingerprint recognition is one of the biometries methods that has been widely used for this requirement. This paper proposes the fingerprint matching algorithm that uses the information of the ridge shapes of minutiae. In which, the data of the ridge shape are expressed in one-dimensional discrete-time signals. In our algorithm, we obtain one-dimensional discrete-time signals for ridge at every minutiae from input and registered fingerprints, and find pairs of minutia which have the similar ridge shape by comparing input fingerprint with registered fingerprint, thereafter we find candidates of rotation angle and moving displacement from the pairs of similar minutia, and obtain the final rotation angle and moving displacement value from those candidates set by using clustering method. After that, we align an input fingerprint by using obtained data, and calculate the matching rate by counting the number of corresponded pairs of minutia within the overlapped area of an input and registered fingerprints. As a result of experiment, false rejection rate(FRR) of $18.0\%$ at false acceptance rate(FAR) of $0.79\%$ is achieved.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.110-116
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• 2006

In this paper, we implement a speech recognition system to support ubiquitous sensor network application services such as switch control, authentication, etc. using wireless audio sensors. The proposed system is consist of the wireless audio sensor, the speech recognition algorithm using psychoacoustic model and LDPC(low density parity check) for correcting errors. The proposed speech recognition system is inserted in a HOST PC to use the sensor energy effectively mil to improve the accuracy of speech recognition, a FEC(Forward Error Correction) system is used. Also, we optimized the simulation coefficient and test environment to effectively remove the wireless channel noises and correcting wireless channel errors. As a result, when the distance between sensor and the source of voice is less then 1.0m FAR and FRR are 0.126% and 7.5% respectively.