• 전자공학회논문지
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• 제52권6호
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• pp.107-116
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• 2015

고성능 컴퓨터와 디지털 카메라의 보급으로 컴퓨터를 이용한 객체 탐지 및 추적은 컴퓨터 비전의 다양한 응용분야에서 중요한 문제로 대두 되고 있다. 또한, 지능형 자동화 감시 장치, 영상 분석 장치, 자동화된 로봇 분야 등에서 그 필요성이 점점 부각 되고 있다. 객체 추적은 카메라를 이용하여 움직이는 객체의 위치를 찾는 처리 과정을 의미 하며, 강건한 객체 추적을 위해서는 객체의 스케일, 형태 변화, 회전에 강건하고 정확한 객체의 위치를 파악할 수 있어야한다. 본 논문에서는 랜덤 포레스트를 이용한 강건한 객체 추적에 대한 알고리즘을 제안하였다. 정확한 객체의 위치를 찾기 위해 지역 공분산과 ZNCC (Zeros Mean Normalized Cross Correlation)를 사용하여 객체를 검출하고 검출된 객체를 5개의 부분으로 나누어 랜덤 포레스트로 객체가 잘 검출 되었는지 검증 한다. 검증된 객체 중 모델을 선택하여 객체 검출이 잘못 되었다고 판단된 경우 입력 모델을 변경하여 정확한 객체를 찾도록 하였다. 제안된 알고리즘과 기존의 알고리즘들을 비교 하였을 때 비교적 정확한 객체의 위치를 잘 찾아 가는 것을 확인하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 1992년도 수공학연구발표회논문집
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.369-388
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• 2023

In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.606-608
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• 1998

Digital watermarking is the technique which embeds the invisible signal into multimedia data such as audio, video, images, for copyright protection, including owner identification and copy control information. In this paper, a new watermark detection algorithm by local masking cross covariance between watermarked signal and pseudo noise signal is proposed. The proposed algorithm enhances the detection probability for embedding information. Since reducing detection errors for the weak embedding signals, the algorithm improves the image quality and robusts against illegal attack to delete the embedding information and data compression applications such as JPEG and MPEGs.

• Wind and Structures
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• 제30권6호
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• pp.633-648
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• 2020

The objective of this work was to investigate the interference effects of two-parallel bridge decks on aerodynamic coefficients, vortex-induced vibration, flutter instability and flutter derivatives. The two bridges have significant difference in cross-sections, dynamic properties, and flutter speeds of each isolate bridge. The aerodynamic static tests and aeroelastic tests were performed in TU-AIT boundary layer wind tunnel in Thammasat University (Thailand) with sectional models in a 1:90 scale. Three configuration cases, including the new bridge stand-alone (case 1), the upstream new bridge and downstream existing bridge (case 2), and the downstream new bridge and the upstream existing bridge (case 3), were selected in this study. The covariance-driven stochastic subspace identification technique (SSI-COV) was applied to identify aerodynamic parameters (i.e., natural frequency, structural damping and state space matrix) of the decks. The results showed that, interference effects of two bridges decks on aerodynamic coefficients result in the slightly reduction of the drag coefficient of case 2 and 3 when compared with case 1. The two parallel configurations of the bridge result in vortex-induced vibrations (VIV) and significantly lower the flutter speed compared with the new bridge alone. The huge torsional motion from upstream new bridge (case 2) generated turbulent wakes flow and resulted in vertical aerodynamic damping H1^* of existing bridge becomes zero at wind speed of 72.01 m/s. In this case, the downstream existing bridge was subjected to galloping oscillation induced by the turbulent wake of upstream new bridge. The new bridge also results in significant reduction of the flutter speed of existing bridge from the 128.29 m/s flutter speed of the isolated existing bridge to the 75.35 m/s flutter speed of downstream existing bridge.

• 한국항해항만학회지
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• 제36권10호
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• pp.833-838
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• 2012

TDOA 기법은 위치추정 기법의 하나로 간단한 구조와 높은 정확도를 가지는 장점으로 인해 실내측위, 재머 위치추적, 인명구조 등에 자주 사용된다. 본 논문에서는 MPM(Matrix Pencil Method)를 이용한 고분해능 TDOA 추정 기법을 제안한다. 제안된 기법은 기존의 교차상관을 이용한 TDOA 기법에 비교하여 높은 정확도를 가지며 협대역 신호에 적용이 가능하다. 또한 잘 알려진 고분해능 기법 중 하나인 MUSIC(Multiple Signal Classification)에서 공분산 행렬을 사용하는 것과 달리 수집된 데이터를 바로 행렬로 만들어 사용하므로 복잡성이 낮은 특징이 있다. 제안된 기법의 성능을 검증하기 위해 소프트웨어 시뮬레이션 통해 추정 오차와 연산량 측면에서 MUSIC 기법과 비교하였다.

• Nuclear Engineering and Technology
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• 제46권3호
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• pp.313-342
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• 2014

A Nuclear Energy Agency (NEA), Organization for Economic Co-operation and Development (OECD) benchmark for Uncertainty Analysis in Modeling (UAM) is defined in order to facilitate the development and validation of available uncertainty analysis and sensitivity analysis methods for best-estimate Light water Reactor (LWR) design and safety calculations. The benchmark has been named the OECD/NEA UAM-LWR benchmark, and has been divided into three phases each of which focuses on a different portion of the uncertainty propagation in LWR multi-physics and multi-scale analysis. Several different reactor cases are modeled at various phases of a reactor calculation. This paper discusses Phase I, known as the "Neutronics Phase", which is devoted mostly to the propagation of nuclear data (cross-section) uncertainty throughout steady-state stand-alone neutronics core calculations. Three reactor systems (for which design, operation and measured data are available) are rigorously studied in this benchmark: Peach Bottom Unit 2 BWR, Three Mile Island Unit 1 PWR, and VVER-1000 Kozloduy-6/Kalinin-3. Additional measured data is analyzed such as the KRITZ LEU criticality experiments and the SNEAK-7A and 7B experiments of the Karlsruhe Fast Critical Facility. Analyzed results include the top five neutron-nuclide reactions, which contribute the most to the prediction uncertainty in keff, as well as the uncertainty in key parameters of neutronics analysis such as microscopic and macroscopic cross-sections, six-group decay constants, assembly discontinuity factors, and axial and radial core power distributions. Conclusions are drawn regarding where further studies should be done to reduce uncertainties in key nuclide reaction uncertainties (i.e.: $^{238}U$ radiative capture and inelastic scattering (n, n') as well as the average number of neutrons released per fission event of $^{239}Pu$).

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권12호
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• pp.1239-1246
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• 2003

대상 물체의 3차원 모델을 구축하기 위해서는 여러 시점에서 측정된 거리정보 데이타들을 하나의 좌표계로 통합하는 정합(registration) 과정이 필수적이다. 3차원 데이타의 정합을 위해 가장 널리 사용되는 ICP(Iterative Closest Point) 알고리즘은 거리정보 데이타 간에 겹치는 영역 또는 일치점 등에 대한 사전 정보가 필요하다. 본 논문에서는 임의의 시점에서 측정된 데이타를 반복적인 방법에 의해 자동으로 정합하는 개선된 ICP 방법이 제안된다. 3차원 데이타가 거리정보 영상으로 맺히는 관계를 나타내는 센서 사영조건(projection constraint), 데이타의 공분산(covariance) 행렬, 교차(cross) 사영 등을 이용하여 정합과정을 자동화하였으며, 유저의 개입이나 3차원 기계 보조 장치 등을 사용하는 별도의 초기값 측정 없이 3차원 모델을 정확하게 구성할 수 있다. 다양한 거리정보 데이타에 대한 실험을 통해 제안된 방법의 우수한 성능을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2763-2782
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• 2014

In this paper, a generalized likelihood ratio test (GLRT) is proposed for cyclostationary multi-antenna spectrum sensing in cognitive radio systems, which takes into account the cyclic autocorrelations obtained from all the receiver antennas and the cyclic cross-correlations obtained from all pairs of receiver antennas. The proposed GLRT employs a different hypotheses problem formulation and a different asymptotic covariance estimation method, which are proved to be more suitable for multi-antenna systems than those employed by the $Dandawat{\acute{e}}$-Giannakis algorithm. Moreover, we derive the asymptotic distributions of the proposed test statistics, and prove the constant false alarm rate property of the proposed algorithm. Extensive simulations are conducted, showing that the proposed GLRT can achieve better detection performance than the $Dandawat{\acute{e}}$-Giannakis algorithm and its extension for multi-antenna cases.

• Journal of Preventive Medicine and Public Health
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• 제47권1호
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• pp.64-71
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• 2014

Objectives: Physical activity behavior begins to decline during adolescence and continues to decrease throughout young adulthood. This study aims to explain factors that influence physical activity behavior in a sample of female adolescents using a health promotion model framework. Methods: This cross-sectional survey was used to explore physical activity behavior among a sample of female adolescents. Participants completed measures of physical activity, perceived self-efficacy, self-esteem, social support, perceived barriers, and perceived affect. Interactions among the variables were examined using path analysis within a covariance modeling framework. Results: The final model accounted for an $R^2$ value of 0.52 for physical activity and offered a good model-data fit. The results indicated that physical activity was predicted by self-esteem (${\beta}$=0.46, p<0.001), perceived self-efficacy (${\beta}$=0.40, p<0.001), social support (${\beta}$=0.24, p<0.001), perceived barriers (${\beta}$=-0.19, p<0.001), and perceived affect (${\beta}$=0.17, p<0.001). Conclusions: The findings of this study showed that the health promotion model was useful to predict physical activity behavior among the Iranian female adolescents. Information related to the predictors of physical activity behavior will help researchers plan more tailored culturally relevant health promotion interventions for this population.