• 정보보호학회논문지
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• 제24권4호
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• pp.721-737
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• 2014

주민등록번호 제도가 도입된 이래 주민등록번호는 효과적인 국가 개인식별체계의 역할을 해왔다. 하지만 정보화 사회의 도래로 주민등록번호를 포함한 개인정보가 대규모로 수집됨에 따라 개인정보 유출사고 등의 문제가 발생하고 있다. 주민등록번호는 모든 영역에서 개인과 일대일로 대응되는 강력한 개인식별값이자 본인확인 수단으로 유출될 경우 큰 피해로 이어질 위험이 있으나, 주민등록번호는 변경할 수 없다는 문제가 있어 이러한 피해를 경감할 수 있는 대책이 없는 실정이다. 우리나라의 경우 개인정보가 주민등록번호를 중심으로 하여 기록 및 관리되는 것이 일반이므로, 유출된 주민등록번호와 개인정보의 연결성을 끊음으로써 국민의 개인정보를 보호할 필요가 제기되고 있다. 본 연구에서는 주민등록번호의 종속성을 제거함으로써 주민등록번호 및 개인정보 유출에 대한 피해를 방지할 수 있는 독립적인 난수기반 개인식별번호 체계를 제안하고, 체계의 도입 시 발생할 수 있는 쟁점사항을 식별하고 해소방안을 제시한다.

• Smart Structures and Systems
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• 제15권1호
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.146-148
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• 2005

In this paper, we propose a genetically optimized identification of information granulation(IG)-based fuzzy model. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the genetic algorithms and the least square method. And also, we exploite consecutive identification of fuzzy model in case of identification of structure and parameters. Numerical example is included to evaluate the performance of the proposed model.

• 한국정보통신학회논문지
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• 제20권5호
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• pp.931-936
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• 2016

PS 알고리즘은 리더의 송신 전력을 점진적으로 증가시키면서 리더의 식별 영역 내에 있는 태그들을 그룹화 하여 식별하는 기법이다. 이 기법에서는 스캔 과정을 수행할 때마다 고정된 크기의 프레임을 사용한다. 이로 인하여 PS 알고리즘의 성능은 태그의 수와 프레임 크기에 따라 다양하게 나타나는 문제점이 있다. 본 논문에서는 매 스캔마다 태그의 수를 추정하여 최적의 프레임 크기를 할당하는 EPS 알고리즘을 제안하고, 이를 STAC 프로토콜에 적용한 STAC/EPS 알고리즘의 성능을 분석한다. 성능 분석의 결과, STAC/EPS 알고리즘의 평균 식별지연은 STAC 프로토콜에 비하여 45% 개선됨을 알 수 있었다. 또한 제안한 알고리즘은 전력 증가 값에 관계없이 항상 일정한 식별 지연을 얻을 수 있었다.

• Smart Structures and Systems
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• 제13권2호
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Smart Structures and Systems
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• 제8권4호
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• 한방재활의학과학회지
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• 제24권2호
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• pp.107-114
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• 2014

Objectives The purpose of this study is analyzing internal research trends of oriental obesity pattern identification in korean literature based on obesity pattern identification questionnaires, development and application of Pattern Identification System to help solve problems of future researches. Methods 6 Korean databases were searched for articles of oriental obesity pattern identification, irrespective of publication year and 13 studies were reviewed. An analytical method such as descriptive statistics and an actual number and percentage was used. Results We collected 13 studies. 4 studies were published in 2012 and 2008, the highest number of studies. 7 Clinical studies were the major research method. The Studies were classified according to the characteristics and design. 5 studies were about research of analysis and improvement of oriental obesity pattern identification questionnaire, the most number of studies. 4 studies were about research of observational studies in clinical on obesity pattern identification. 3 studies were about research of intervention studies in clinical on obesity pattern identification and 1 study was about clinical practice recommendation. Conclusions Establishment of obesity pattern identification system and its clinical application could lead to standardizing obesity pattern identification and clinical practice guideline. Applied on other diseases, obesity pattern identification system could also lead to improving treatment rate, contributing to the development of clinical practice guidelines and academic field of research.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1996년도 추계학술대회논문집
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2003년도 학술대회논문집
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• pp.355-359
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• 2003

In this paper, an identification method for a first order dead time process is proposed. This method used the genetic algorithm for parameter identification of process. The proposed method gives a better identification result than the existing methods under step testing. The effectiveness of the identification method has been demonstrated through a number of simulation examples.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.34-39
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• 2009

현금 인출기를 통해 돈을 인출할 때나 핸드폰의 잠금 설정을 할 때 사용하는 네 자리 숫자를 이용한 비밀 번호 또는 개인 식별번호 입력 방법은 일상생활에서 널리 사용되고 있다. 하지만 숫자를 직접 입력하는 현재의 방법은 shoulder surfing attack(SSA)에 안전하지 않다. 본 논문에서는 SSA에 안전하면서도 누구나 쉽게 사용할 수 있는 새로운 PIN(Personal Identification Number) 입력방법들을 제안하고, 이들 방법과 기존 방법의 안전성과 편의성을 비교한다.