• Journal of Information Processing Systems
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• 제13권2호
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• pp.305-320
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• 2017

The selection of subset size is of great importance to the accuracy of digital image correlation (DIC). In the traditional DIC, a constant subset size is used for computing the entire image, which overlooks the differences among local speckle patterns of the image. Besides, it is very laborious to find the optimal global subset size of a speckle image. In this paper, a self-adaptive and bidirectional dynamic subset selection (SBDSS) algorithm is proposed to make the subset sizes vary according to their local speckle patterns, which ensures that every subset size is suitable and optimal. The sum of subset intensity variation (${\eta}$) is defined as the assessment criterion to quantify the subset information. Both the threshold and initial guess of subset size in the SBDSS algorithm are self-adaptive to different images. To analyze the performance of the proposed algorithm, both numerical and laboratory experiments were performed. In the numerical experiments, images with different speckle distribution, different deformation and noise were calculated by both the traditional DIC and the proposed algorithm. The results demonstrate that the proposed algorithm achieves higher accuracy than the traditional DIC. Laboratory experiments performed on a substrate also demonstrate that the proposed algorithm is effective in selecting appropriate subset size for each point.

• International Journal of Precision Engineering and Manufacturing
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• 제1권1호
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• pp.62-70
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• 2000

The design of gear train is a kind of mixed problems which have to determine various types of design variables; i,e., continuous, discrete, and integer variables. Therefore, the most common practice of optimum design using the derivative of objective function has difficulty in solving those kinds of problems and the optimum solution also depends on initial guess because there are many sophisticated constrains. In this study, the Genetic Algorithm is introduced for the optimum design of gear trains to solve such problems and we propose a genetic algorithm based gear design system. This system is applied for the geometrical volume(size) minimization problem of the two-stage gear train and the simple planetary gear train to show that genetic algorithm is better than the conventional algorithm solving the problems that have continuous, discrete, and integer variables. In this system, each design factor such as strength, durability, interference, contact ratio, etc. is considered on the basis of AGMA standards to satisfy the required design specification and the performance with minimizing the geometrical volume(size) of gear trains

• Journal of Microbiology and Biotechnology
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• 제12권3호
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• pp.377-381
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• 2002

Recently, interests to remove nitrogen in the nitritation process have increased because of its economical advantages, since it could be a short-cut process to save both oxygen for nitrification and carbon for denitrification compared to a typical nitrification. However, the kinetics related with the nitritation process has not yet been fully understood. Furthermore, many useful models which have been successfully used for wastewater treatment processes cannot be used to estimate effluent nitrite concentration for evaluating performance of the nitritation process, since the process rate equations and population of microorganisms for nitrogen removal in these models have been set up only for the condition of full nitrification. Therefore, the present study was conducted to estimate an effluent nitrite concentration in the nitritation process with a concept of enzymatic inhibition kinetics based on long-term laboratory experiments. Using a nonlinear least squares regression method, kinetic parameters were accurately determined. By setting up a process rate equation along with a mass balance equation of the nitrite-oxidizing step, an effluent nitrite concentration in the nitritation process was then successfully estimated.

• 전기학회논문지
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• 제59권10호
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• pp.1874-1881
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• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1494-1499
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• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can be used to identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.290-293
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• 2007

The land surface temperature (LST) derived from the meteorological satellite can be used to investigate the urban heat island (UHI) and its temporal variations. In this study, we developed LST retrieval algorithm from MTSAT-1R by means of a statistical regression analysis from radiative transfer simulations using MODTRAN 4 for a wide range of atmospheric, satellite viewing angle (SVA) and lapse rate conditions. 535 sets of thermodynamic initial guess retrieval (TIGR) were used for the radiative transfer simulations. Sensitivity and intercomparison results showed that the algorithm, developed in this study, estimated the LST with a similar bias and root mean square errors to that of other algorithms. The magnitude, spatial extent, and seasonal and diurnal variations of the UBI of Korean peninsula were well demonstrated by the LST derived from MTSAT-1R data. In general, the temporal variations of UHI clearly depend on the weather conditions and geographic environment of urban.

• 로봇학회논문지
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• 제11권4호
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• pp.300-309
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• 2016

This paper proposes a method for motion estimation of consecutive cameras using 3-D straight lines. The motion estimation algorithm uses two non-parallel 3-D line correspondences to quickly establish an initial guess for the relative pose of adjacent frames, which requires less correspondences than that of current approaches requiring three correspondences when using 3-D points or 3-D planes. The estimated motion is further refined by a nonlinear optimization technique with inlier correspondences for higher accuracy. Since there is no dominant line representation in 3-D space, we simulate two line representations, which can be thought as mainly adopted methods in the field, and verify one as the best choice from the simulation results. We also propose a simple but effective 3-D line fitting algorithm considering the fact that the variance arises in the projective directions thus can be reduced to 2-D fitting problem. We provide experimental results of the proposed motion estimation system comparing with state-of-the-art algorithms using an open benchmark dataset.

• 한국항공우주학회지
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• 제44권7호
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• pp.620-628
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• 2016

호모토피 알고리즘은 비선형성이 강하거나 다수의 최적해가 존재하는 비선형 최적제어 문제에서 점진적으로 비선형 항으로 고려하게 해줌으로써 강건하게 전역의 최적해를 구할 수 있는 방법이다. 본 논문에서는 초기 추정치에 둔감한 SBS 알고리즘과 호모토피 알고리즘을 결합한 비선형 최적제어 알고리즘을 제시하였다. 이러한 접근방식은 저추력 궤적최적화 문제와 같이 비선형성이 강한 문제의 최적해를 구하는데 효과적이다. 또한, 비선형성이 강한 문제들은 종종 다수 국소 해가 존재하게 되는데, 이러한 경우에 SBS-호모토피 방법은 점진적으로 전역해를 찾는 것을 가능하게 한다.

• Bulletin of the Korean Chemical Society
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• 제24권3호
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• pp.279-284
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• 2003

The One Pass Method (OPM) previously presented for the identification of single input single output systems is used to estimate the parameters of a Decentralized Control System (DCS). The OPM is a linear and therefore a simple estimation method. All of the calculations are performed in one pass, and no initial parameter guess, iteration, or powerful search methods are required. These features are of interest especially when the parameters of multi input-output model are estimated. The benefits of the OPM are revealed by comparing its results against those of two recently published methods based on pulse testing. The comparison is performed using two databases from the literature. These databases include single and multi input-output process transfer functions and relevant disturbances. The closed loop responses of these processes are roughly captured by the previous methods, whereas the OPM gives much more accurate results. If the parameters of a DCS are estimated, the OPM yields the same results in multi or single structure implementation. This is a novel feature, which indicates that the OPM is a convenient and practice method for the parameter estimation of multivariable DCSs.

• 한국농공학회지
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• 제44권7호
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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.