• Imaging Science in Dentistry
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• 제51권2호
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• pp.187-193
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• 2021

Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

• Asian-Australasian Journal of Animal Sciences
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• 제20권1호
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• pp.25-30
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• 2007

The capability of microsatellite markers for individual identification and their potential for breed assignment of individuals was evaluated in two Indian horse breeds. The strength of these individual assignment methods was also evaluated by increasing the number of loci in increments of five. The probability of identity of two random horses from the two breeds at all twenty five studied loci was as low as $1.08{\times}10^{-32}$ showing their suitability to distinguish between individual horses and their products. In the phylogenetic approach for individual assignment using Nei's genetic distances, 10.81% of horses associated with breed other than the major cluster of the source breed horses when all twenty five microsatellite loci were implemented. Similar results were obtained when the maximum likelihood approach for individual assignment was used. Based on these results it is proposed that, although microsatellite markers may prove very useful for individual identification, their utility for breed assignment of horses needs further evaluation.

• 한국음향학회지
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• 제31권3호
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• pp.188-196
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• 2012

본 논문에서는 커널 주성분 분석 (KPCA, kernel principal component analysis)으로 강화한 화자 특징을 이용하여 복수의 분류기를 학습하고 이를 앙상블 결합하는 화자 식별 방법을 제안한다. 이 때, 계산량과 메모리 요구량을 줄이기 위해 전체 화자 특징 벡터 중 일부를 랜덤 선택하여 커널 주성분 분석의 기저를 추정한다. 실험 결과, 제안한 방법이 그리디 커널 주성분 분석 (GKPCA, greedy kernel principal component analysis)보다 높은 화자 식별률을 보였다.

• 음성과학
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• 제9권3호
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• pp.3-16
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• 2002

We examined some problems in speaker identification procedures: transformation of acoustic parameters into auditory scales, invalid measurement values, and comparability of spectral energy values across the frequency range. To resolve those problems, we analyzed the acoustic spectral energy of three Korean numbers produced by ten female students from narrow-band spectrograms at 19 proportional time points of each voiced segment. Then, cells of the first five spectral matrices were averaged to form a matrix model for each speaker. The correlation coefficients and sum of the absolute amplitude difference in each pair of the spectral models of the ten subjects were obtained. Also, some individual matrix models were compared to those of the same subject or the other subject with a similar spectral model. Results showed that in numbers '2' and '9' subjects could not be clearly distinguished from the others but in number '4' it shed some possibility of setting threshold values for speaker identification if we employed the coefficients and the sum of absolute difference. Further studies would be desirable on various combinations of the range of long-term average spectra and the degree of signal pre-emphasis.

• ETRI Journal
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• 제30권5호
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• 한국항행학회논문지
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• 제19권6호
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• pp.636-642
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• 2015

본 논문에서는 계단응답으로부터 시 지연을 갖는 선형 연속시스템을 식별하기 위해 HS 최적화 알고리즘을 적용에 관하여 연구하였다. 인식 모델은 1차 시 지연 모델 (FOPDT)로써, FOPDT은 많은 화학 공정과 HAVC 공정에 실효성이 있으며 PID 튜닝에도 적합하다. 최근에 개발된 HS 알고리즘은 완벽한 하모니를 찾아가는 음악적 과정을 개념화 한 것이다. 수학을 기반으로 하는 전통적 기법과 달리 HS는 확률적인 방법을 사용하므로 미분과 같은 수학적 접근을 필요로 하지 않는다. 제시된 인식 방법의 효과를 입증하기 위해 많은 수치 예를 수행하여 결과를 제시하였다.

• 비파괴검사학회지
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• 제21권2호
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• pp.204-212
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• 2001

주파수 응답함수 (FRF)를 이용하여 평판 구조물에 존재하는 손상을 규명하기 위한 새로운 구조손상 규명기법을 소개하였다. 본 연구의 구조손상 규명기법은 손상된 평판의 운동방정식으로부터 유도되었으며 손상 분포함수를 이용하여 손상의 특성을 나타내었다. 본 연구의 구조손상 규명기법의 주요 특징은 다음과 같다. 첫째, 손상된 구조물에 대한 모드 데이터를 요구하지 않으며, 둘째, 가진 주파수와 측정점을 적절히 다수 선택함으로써 손살규명에 요구되는 관계식을 확보하는데 널다 유리하다. 몇몇 수치모의실험을 통하여 본 연구에서 제안한 구조손상 규명기법의 적용가능성을 검증하였다.

• Smart Structures and Systems
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• 제14권5호
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• pp.831-845
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• 2014

This paper proposed a discrete wavelet transform based method for time-varying physical parameter identification of shear type structures. The time-varying physical parameters are dispersed and expanded at multi-scale as profile and detail signal using discrete wavelet basis. To reduce the number of unknown quantity, the wavelet coefficients that reflect the detail signal are ignored by setting as zero value. Consequently, the time-varying parameter can be approximately estimated only using the scale coefficients that reflect the profile signal, and the identification task is transformed to an equivalent time-invariant scale coefficient estimation. The time-invariant scale coefficients can be simply estimated using regular least-squares methods, and then the original time-varying physical parameters can be reconstructed by using the identified time-invariant scale coefficients. To reduce the influence of the ill-posed problem of equation resolving caused by noise, the Tikhonov regularization method instead of regular least-squares method is used in the paper to estimate the scale coefficients. A two-story shear type frame structure with time-varying stiffness and damping are simulated to validate the effectiveness and accuracy of the proposed method. It is demonstrated that the identified time-varying stiffness is with a good accuracy, while the identified damping is sensitive to noise.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.55-59
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• 2007

국가 R&D정보에 필요한 모든 정보를 정보의 소유에 관계없이 범 부처적으로 공동 활용하고자 하는 필요성이 대두되고 있다. 그러나, 국가 R&D정보는 부처별 각 연구관리전문기관별로 별도로 관리하고 있으며 상호 연계를 위한 식별체계의 부재로 인해 유사 중복과제 검증, 정보의 추적관리 등 통합적인 정보관리가 어려운 실정이다. 전 부처의 국가 R&D정보를 통합 관리하고 공동활용하기 위해서는 모든 정보에 항구적으로 유일한 URN기반 식별체계의 부여가 필요하다. 본 논문에서는 식별체계를 부여하기 위해 필수적인 식별메타데이터의 개념과 각 연구관리전문기관별 국가 R&D 과제관리번호의 현황을 살펴보고, 범부처 과제고유번호 및 정보식별자 부여를 위한 국가 R&D정보의 식별메타데이터 요소를 제안하고자 한다.

• Structural Engineering and Mechanics
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• 제59권6호
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• pp.1037-1054
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• 2016

Structural parameter evaluation and external force estimation are two important parts of structural health monitoring. But the structural parameter identification with limited input information is still a challenging problem. A new simultaneous identification method in time domain is proposed in this study to identify the structural parameters and evaluate the external force. Each sampling point in the time history of external force is taken as the unknowns in force evaluation. To reduce the number of unknowns for force evaluation the time domain measurements are divided into several windows. In each time window the structural excitation is decomposed by orthogonal polynomials. The time-variant excitation can be represented approximately by the linear combination of these orthogonal bases. Structural parameters and the coefficients of decomposition are added to the state variable to be identified. The extended Kalman filter (EKF) is augmented and selected as the mathematical tool for the implementation of state variable evaluation. The proposed method is validated numerically with simulation studies of a time-invariant linear structure, a hysteretic nonlinear structure and a time-variant linear shear frame, respectively. Results from the simulation studies indicate that the proposed method is capable of identifying the dynamic load and structural parameters fairly accurately. This method could also identify the time-variant and nonlinear structural parameter even with contaminated incomplete measurement.