• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.295-296
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• 2021

In iris diagnostics, iris changes in its area on the iris map when abnormal changes in human tissues and organs occur in response to changes in color and iris structure. This makes it possible to determine the long-term condition in which an abnormal change has occurred, and to determine the presence or absence of a congenital illness. In this paper, we design a neural network algorithm that is displayed on the iris and classifies lesions by using a convolution neural network that has the advantage of advancing learning using images of various dip-running neural networks.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.386-393
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• 2008

This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.283-286
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• 2002

본 논문에서는 보다 효과적이고 강인한 워터마크 은닉을 위한 방법으로 웨이브릿 변환 영역에서 영상의 통계적 특성에 기초한 비정상상태(non-stationary)에서와 정상상태(stationary) 일반화 가우스(generalized Gaussian: GG)모델을 이용한 적응 워터마크 은닉 기술을 제안한다. 워터마크는 고주파 영역에서 연속 부대역 양자화(successive subband quantization: SSQ)를 이용하여 다해상도 영상의 웨이브릿 계수 중에서 시각적 중요 계수(perceptual significant coefficients: PSC)를 선택하여 삽입한다. 워터마크 은닉을 위한 지각 모델은 NVF(noise visibility function)함수에 의해 계산된다. 이것은 비정상상태와 정상상태의 통계적 특성을 이용하고, 국부영상 특성을 가진다. 은닉모델은 다해상도내의 각 부대역별 분산과 형상계수(shape parameter)를 사용한다. Stirmark benchmark test에 근거하여 여러 가능한 왜곡에 대한 실험에서 강인성과 비가시성에서의 우수함을 확인하였고, 비정상상태의 경우와 정상상태의 경우를 비교하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1063-1066
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• 2004

기존의 침입을 탐지하는 방법은 여러 가지가 있지만, 모든 침입을 다 탐지하지는 못하고 있다. 공격자는 알려지지 않은 취약점을 이용하거나 취득한 패스워드나 ID 계정을 이용하여 공격하고자 하는 시스템에 악의적인 행위를 한다. 이런 침입을 탐지하는 연구는 탐지엔진에 적용될 패턴구성 방법이 핵심이다. 본 논문에서는 기존의 사람이 패턴을 찾는 것을 자동화 시키고, 자동화된 패턴 구축 방법을 직접 시스템에 적용하여 침입을 탐지하는 방법을 제시하고자 한다. 그래서 알려지지 않은 침입을 탐지하기 위해 전문가 시스템을 이용하고 패턴을 지식 베이스화하는 작업과 그 지식을 추론할 수 있는 추론망을 추론망 자동 생성 기법으로 구성하여 비정상적인 침입을 탐지하는 방법을 본 논문에서 제시하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.629-636
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• 2010

This study is to investigate the aerodynamic effects of the Rotor-Fuselage Interactions in forward flight, and is conducted by using an improved time-marching free-wake panel method. To resolve the instability caused by the close proximity of the wake to the blade surface, the field velocity approach is added to the prior unsteady panel code. This modified method is applied to the ROBIN(ROtor Body Interaction) problem, which had been conducted experimentally in NASA. The calculated results, pressure distribution on fuselage surface and induced inflow ratio without and with the rotor, are compared with the experimental results. The developed code shows not only very accurate prediction of the aerodynamic characteristics for the rotor-fuselage interaction problem but also the rotor wake development.

• Journal of Aerospace System Engineering
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• v.14 no.3
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• pp.17-23
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• 2020

In this paper, the efficient periodic unsteady flow analysis is developed by using a Chebyshev collocation operator applied to the time differential term of the governing equations. The partial implicit time integration method was also applied in the governing equation for a fluid, which means flux terms were implicitly processed for a time integration and the time derivative terms were applied explicitly in the form of the source term by applying the Chebyshev collocation operator. To verify this method, we applied the 1D unsteady Burgers equation and the 2D oscillating airfoil. The results were compared with the existing unsteady flow frequency analysis technique, the Harmonic Balance Method, and the experimental data. The Chebyshev collocation operator can manage time derivatives for periodic and non-periodic problems, so it can be applied to non-periodic problems later.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.7-13
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• 2020

This paper focuses on detecting abnormal patterns of respiration of humans. In this study, a contact-based device was used to acquire both normal and abnormal respiration signals. To this end, this paper reports the development of a monitoring system to investigate the respiratory status of humans in a normal environment. This work aims to classify the respiratory status, i.e., normal and abnormal status, quantitatively. The respiration signal is acquired using a contact-based medical device (BIOBPAC), and noise reduction is carried out before classifying the respiratory status. To reduce noise, a mixed filter that combines the Savitzky-Golay filter and Median filter is applied to the acquired respiration signals. The inter-class distance is maximized, and the intra-class distance is minimized. The proposed algorithm is straightforward and can be applied to a practical environment. In addition, the experimental results are provided to substantiate the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.266-274
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• 2003

This paper considers an incremental support vector learning for the abnormality detection problems. One of the most well-known support vector learning methods for abnormality detection is the so-called SVDD(support vector data description), which seeks the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to modify the SVDD into the direction of utilizing the relation between the optimal solution and incrementally given training data. After a thorough review about the original SVDD method, this paper establishes an incremental method for finding the optimal solution based on certain observations on the Lagrange dual problems. The applicability of the presented incremental method is illustrated via a design example.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.383-387
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• 2007

본 논문은 NAND 플래시 메모리를 기반으로 한 임베디드 시스템에서 예기치 않은 오류에 대해 데이터 일관성 지원하는 파일 시스템을 제안 한다. 플래시 메모리는 하드디스크에 비해 작고, 내구성, 저 전력, 읽기속도 등 많은 부분에서 장점을 지니고 있어 임베디드 기기에 유리하다. 하지만 제자리 덮어쓰기가 되지 않고 추가적인 연산을 통해 지움 연산을 해야 하는 단점이 있다. 본 논문에서는 이미지 로그를 사용하여 시스템의 비정상적인 종료를 판단하고 플래시 메모리의 외부 갱신 쓰기 특징을 이용하여 파일 연산 전후 메타데이터의 타입을 다르게 하여 추가적인 로그 쓰기 연산 없이 파일 연산 중 오류를 판단하고 이전의 데이터로 복구론 할 수 있는 파일 시스템을 제안 한다. 또한 빠른 마운트를 지원 하는 파일 시스템에 복구 기법을 추가하고 마운트 시간을 실험 하였다. 실험 결과 정상적인 종료 시 YAFFS에 비해 $76%{\sim}85%$ 마운트 시간을 감소 시켰고 비정상 적인 종료로 인해 오류 복구를 해야 할 때 마운트 시간은 YAFFS에 비해 $40%{\sim}60%$감소 시켰다. 그리고 파일에 대한 연산 시간도 YAFFS 와 차이가 없었다.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1233-1242
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• 2017

Various attempts have been made to prevent crime risk. One of the cases where outdoor pedestrians are attacked by criminals is the abnormal health condition. When a mental or mental condition that can not sustain normal walking due to drunkenness is exposed, the case of being a crime is revealed through crime case analysis. In this study, we propose a method for estimating the state of an individual that can be detected in outdoor activities. In order to avoid the inconvenience of installing a separate terminal for event information transmission of sensors and sensors, it is possible to estimate an abnormal state by using a 3-axis acceleration sensor built in a smart phone. The state of the user can be estimated by analyzing the momentum of the user and analyzing it with the passage of time. It is possible to distinguish the flow of time at regular intervals, to recognize the activity patterns in each time band, and to distinguish between normal and abnormal. In this study, we have evaluated the total amount of kinetic energy and kinetic energy in each direction of the acceleration sensor and the Fourier transformed value of the total energy amount to distinguish the abnormal state.