• Title/Summary/Keyword: synthetic estimator

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A Stereo Matching Algorithm with Projective Distortion of Variable Windows (가변 윈도우의 투영왜곡을 고려한 스테레오 정합 알고리듬)

  • Kim, Gyeong-Beom;Jeong, Seong-Jong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.3
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    • pp.461-469
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    • 2001
  • Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.

Comparison of Automatic Calibration for a Tank Model with Optimization Methods and Objective Functions

  • Kang, Min-Goo;Park, Seung-Woo;Park, Chang-Eun
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.7
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    • pp.1-13
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    • 2002
  • Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

A model-free soft classification with a functional predictor

  • Lee, Eugene;Shin, Seung Jun
    • Communications for Statistical Applications and Methods
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    • v.26 no.6
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    • pp.635-644
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    • 2019
  • Class probability is a fundamental target in classification that contains complete classification information. In this article, we propose a class probability estimation method when the predictor is functional. Motivated by Wang et al. (Biometrika, 95, 149-167, 2007), our estimator is obtained by training a sequence of functional weighted support vector machines (FWSVM) with different weights, which can be justified by the Fisher consistency of the hinge loss. The proposed method can be extended to multiclass classification via pairwise coupling proposed by Wu et al. (Journal of Machine Learning Research, 5, 975-1005, 2004). The use of FWSVM makes our method model-free as well as computationally efficient due to the piecewise linearity of the FWSVM solutions as functions of the weight. Numerical investigation to both synthetic and real data show the advantageous performance of the proposed method.

Anomaly Detection in Medical Wireless Sensor Networks

  • Salem, Osman;Liu, Yaning;Mehaoua, Ahmed
    • Journal of Computing Science and Engineering
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    • v.7 no.4
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    • pp.272-284
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    • 2013
  • In this paper, we propose a new framework for anomaly detection in medical wireless sensor networks, which are used for remote monitoring of patient vital signs. The proposed framework performs sequential data analysis on a mini gateway used as a base station to detect abnormal changes and to cope with unreliable measurements in collected data without prior knowledge of anomalous events or normal data patterns. The proposed approach is based on the Mahalanobis distance for spatial analysis, and a kernel density estimator for the identification of abnormal temporal patterns. Our main objective is to distinguish between faulty measurements and clinical emergencies in order to reduce false alarms triggered by faulty measurements or ill-behaved sensors. Our experimental results on both real and synthetic medical datasets show that the proposed approach can achieve good detection accuracy with a low false alarm rate (less than 5.5%).

Voltage and current synthetic flux estimator using all the speed range control of induction motors (전압.전류 합성자속 추정기를 이용한 유도전동기의 전 속도영역 제어)

  • Cho, Moon-Taek;Kim, Eun-Gi;Kim, Young-Chun;Joo, Hae-Jong;Lee, Euy-Soo;Song, Ho-Bin;Kim, Sang-Soo
    • Proceedings of the KAIS Fall Conference
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    • 2011.12b
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    • pp.551-553
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    • 2011
  • 본 논문에서는 유도전동기의 저속운전영역에서 고속운전영역에 이르기까지 모든 영역에 걸친 안정된 속도제어를 목적으로 전압 전류 모델 합성 자속 추정기를 구현하였다. 제시한 시스템의 유용성을 확인하기 위해 3.7[kW]용량의 농형 유도전동기에 적용하여 시뮬레이션의 편의를 위해 각각의 제어기를 Matlab/Simulink를 통해 모델링하여 검토하였으며, 실험을 통해 확인하였다.

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Time-varying Estimation of Vocal Track Parameters During the Speech Transition Regions (음성천이구간에서의 성도 파라메타 시변추정에 관한 연구)

  • Choi, Hong-Sub
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.2
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    • pp.101-106
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    • 1997
  • In this paper, sample selective RLS(SSRLS) method is proposed, which aims to eliminate the influence of pitch bias. Its basic concepts are as follows. First it extracts the open glottis interval by using the residual signals, then estimates the formant values from the selected speech samples excluding above open glottis interval. This method has some analogy with the SSLPS, the simulation is conducted upon the synthetic and real speech. From these results, we find more usefulness of the proposed method than the conventional ones.

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Estimation of Forest Volumes in the Ecosystem Region Using Spatial Statistical Techniques (공간통계기법을 이용한 생태계 관리지역의 산림축적 추정)

  • SEO, Hwan-Seok;PARK, Jeong-Mook;KIM, Eun-Sook;LEE, Jung-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.2
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    • pp.149-160
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    • 2015
  • This study aims to estimate the forest volumes of the upper region of Nam-Han River in ecosystem zoning by forest types and age classes, and to suggest the optimal estimation method through the comparison of the standard errors according to the spatial unit. In the estimation of forest volumes, we used both of direct estimation, which uses sample plots of the target area only, and synthetic estimation, which includes sample plots of the expanded areas as well as those of the target area. As for the spatial expansion, we applied four standards for synthetic estimator: Mountainous zone, Neighbor ecosystem region, Gangwon province, and Buffer zone. The results show that average forest volume per ha, calculated by direct estimation, was $143.5m^3/ha$, while that by synthetic estimation with each standard, was estimated at $146.9m^3/ha$ by Gangwon province, $144.8m^3/ha$ by Buffer zone, $139.8m^3/ha$ by Neighbor ecosystem region, and $138.6m^3/ha$ by Mountainous zone, respectively. The standard errors of direct estimation was $1.79m^3/ha$, while those of synthetic estimation showed not a great difference among the errors. Meanwhile, considering the standard errors by forest type, the lowest was ${\pm}2.3m^3/ha$ of broad-leaved forest, followed by ${\pm}3.3m^3/ha$ of mixed forest, and ${\pm}4.8m^3/ha$ of coniferous forest.

Application of In-direct Estimation for Small Area Statistics (소지역 통계분석기법의 활용-도소매업 및 서비스업 통계조사 사례연구-)

  • 김영원;성나영
    • Proceedings of the Korean Association for Survey Research Conference
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    • 2000.06a
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    • pp.57-73
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    • 2000
  • Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. In estimating means, totals, and other parameters for small areas of a finite population, samplie sizes for small areas are typically small because the overall sample size is usually determined to provide specific accuracy at a much higher level of aggregation than that of small area. The usual direct estimators that use the only information which is gotten from the sample in a given small area provide unreliable estimates. However, indirect estimators utilize the information from the areas related with a given small area, that is borrow strength from other related areas, and so give more accurate estimates than direct estimators. In this paper we investigate small area estimation methods such as synthetic, composite and empirical best linear unbiased prediction estimator, and apply them to real domestic data which is from the Survey of Hotels and Restaurants in In-Chon as of 1996 and then evaluate the performance of these methods by measuring average squared errors. This evaluation shows that indirect estimators, which are small area estimation methods, are more efficient direct estimator.

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Deep Learning-based Gaze Direction Vector Estimation Network Integrated with Eye Landmark Localization (딥 러닝 기반의 눈 랜드마크 위치 검출이 통합된 시선 방향 벡터 추정 네트워크)

  • Joo, Heeyoung;Ko, Min-Soo;Song, Hyok
    • Journal of Broadcast Engineering
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    • v.26 no.6
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    • pp.748-757
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    • 2021
  • In this paper, we propose a gaze estimation network in which eye landmark position detection and gaze direction vector estimation are integrated into one deep learning network. The proposed network uses the Stacked Hourglass Network as a backbone structure and is largely composed of three parts: a landmark detector, a feature map extractor, and a gaze direction estimator. The landmark detector estimates the coordinates of 50 eye landmarks, and the feature map extractor generates a feature map of the eye image for estimating the gaze direction. And the gaze direction estimator estimates the final gaze direction vector by combining each output result. The proposed network was trained using virtual synthetic eye images and landmark coordinate data generated through the UnityEyes dataset, and the MPIIGaze dataset consisting of real human eye images was used for performance evaluation. Through the experiment, the gaze estimation error showed a performance of 3.9, and the estimation speed of the network was 42 FPS (Frames per second).

Precise Orbit Determination of LEO Satellite Using Dual-Frequency GPS Data (이중 주파수 GPS 데이터를 이용한 저궤도 위성의 정밀궤도결정)

  • Hwang, Yoo-La;Lee, Byoung-Sun;Kim, Jae-Hoon;Yoon, Jae-Cheol
    • Journal of Astronomy and Space Sciences
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    • v.26 no.2
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    • pp.229-236
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    • 2009
  • KOorea Multi-purpose SATellite(KOMPSAT)-5 will be launched at 550km altitude in 2010. Accurate satellite position(20 cm) and velocity(0.03 cm/s) are required to treat highly precise Synthetic Aperture Radar(SAR) image processing. Ionosphere delay was eliminated using dual frequency GPS data and double differenced GPS measurement removed common clock errors of both GPS satellites and receiver. SAC-C carrier phase data with 0.1 Hz sampling rate was used to achieve precise orbit determination(POD) with ETRI GNSS Precise Orbit Determination(EGPOD) software, which was developed by ETRI. Dynamic model approach was used and satellite's position, velocity, and the coefficients of solar radiation pressure and drag were adjusted once per arc using Batch Least Square Estimator(BLSE) filter. Empirical accelerations for sinusoidal radial, along-track, and cross track terms were also estimated once per revolution for unmodeled dynamics. Additionally piece-wise constant acceleration for cross-track direction was estimated once per arc. The performance of POD was validated by comparing with JPL's Precise Orbit Ephemeris(POE).