• Water Engineering Research
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• v.2 no.4
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• pp.219-229
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• 2001

Synthetic unit hydrograph equations for rainfall run-off characteristics analysis and estimation of design flood have long and quite frequently been presented, the Snyder and SCS synthetic unit hydrograph. The major inputs to the Snyder and SCS synthetic unit hydrograph are lag time and peak coefficient. In this study, the methods for estimating lag time and peak coefficient for small watersheds proposed by Zhao and McEnroe(1999) were applied to the Kum river basin in Korea. We investigated lag times of relatively small watersheds in the Kum river basin in Korea. For this investigation the recent rainfall and stream flow data for 10 relatively small watersheds with drainage areas ranging from 134 to 902 square kilometers were gathered and used. 250 flood flow events were identified along the way, and the lag time for the flood events was determined by using the rainfall and stream flow data. Lag time is closely related with the basin characteristics of a given drainage area such as channel length, channel slope, and drainage area. A regression analysis was conducted to relate lag time to the watershed characteristics. The resulting regression model is as shown below: ※ see full text (equations) In the model, Tlag is the lag time in hours, Lc is the length of the main river in kilometers and Se is the equivalent channel slope of the main channel. The coefficient of determinations (r$^2$)expressed in the regression equation is 0.846. The peak coefficient is not correlated significantly with any of the watershed characteristics. We recommend a peak coefficient of 0.60 as input to the Snyder unit-hydrograph model for the ungauged Kum river watersheds

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2094-2105
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• 1994

This paper contains a Hough transform based projection method derived from Radon transform for tracking dim unresolved(sub-pixel) moving targets that move along straight line parths across a time sequential image data. In contrast to several recently presented Hough transform methods using a compressed image referred to as the track map our proposed technique utilizing a set of projections taken along arbitrary orientations effectively increases the changes of target detection, and creates a robust track estimation environment by incorporating all the available knowledge obtained from the projections. Moreover, in order to quantitatively assess the estimation capability of the projection-based Hough transform algorithm, the analytical bounds on the Hough space parameter errors introduced by image space noise contamination are derived. The simulation yielded promising results of estimating the track parameters even under low signal to noise rations when our technique was tested against the time sequential sets of real infrared image data referred to as the HiCamps.

• Korean Journal of Microbiology
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• v.47 no.3
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• pp.263-267
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• 2011

Genomic fingerprinting methods are useful in determining relatedness among bacterial strains. However, random coincidences in sizes of two DNA fragments in two different fingerprints may occur, resulting in erroneous interpretation of relatedness between two bacterial genomes. In this study, I estimated the probability of occurrence of DNA bands of identical size in fingerprints of two unrelated genomes, so that the significance of fingerprint-based estimation of genome relatedness could be analyzed. The probability could be estimated as outputs of a function formulated with the three parameters: the numbers of observed fragments, all possible sizes of fragments and observed fragments common in a given pair of fingerprints. The parameter most instrumental to significance of relatedness estimation was the number of all possible sizes of fragments. To keep the number of coincidentally-common size of fragments below 10, about 200 fragments should be distinguishable in the fingerprints.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.101-106
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• 2020

In order to smoothly control the speed of the induction motor, it is necessary to obtain the required rotor speed information. In order to obtain the speed information, it must be obtained using a sensor, but it can also be obtained using an appropriate algorithm without using a sensor. In order to obtain speed information, a system was designed using a model reference adaptive system (MARS). Indirect vector control, one of the speed control methods of induction motors, was calculated from the motor current and rotor parameter values. The method of obtaining the position information of the magnetic flux by combining the slip frequency with the rotor speed was used. It is possible to simply perform instantaneous current control in a wide speed range without actual magnetic flux information, and has the advantage that the structure of the controller is simple. Therefore, in this paper, the control system was constructed based on the indirect vector control method, and the speed control system of the induction motor was developed by estimating the required rotor speed information as an intelligent algorithm developed without using it as a sensor.

• Nuclear Engineering and Technology
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• v.44 no.7
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• pp.791-798
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• 2012

Since standardized fracture test specimens cannot be easily extracted from in-service components, several alternative fracture toughness test methods have been proposed to characterize the deformation and fracture resistance of materials. One of the more promising alternatives is the local approach employing the SP(Small Punch) testing technique. However, this process has several limitations such as a lack of anisotropic yield potential and tediousness in the damage parameter calibration process. The present paper investigates estimation of ductile fracture resistance(J-R) curve by FE(Finite Element) analyses using an anisotropic damage model and enhanced calibration procedure. In this context, specific tensile tests to quantify plastic strain ratios were carried out and SP test data were obtained from the previous research. Also, damage parameters constituting the Gurson-Tvergaard-Needleman model in conjunction with Hill's 48 yield criterion were calibrated for a typical nuclear reactor material through a genetic algorithm. Finally, the J-R curve of a standard compact tension specimen was predicted by further detailed FE analyses employing the calibrated damage parameters. It showed a lower fracture resistance of the specimen material than that based on the isotropic yield criterion. Therefore, a more realistic J-R curve of a reactor material can be obtained effectively from the proposed methodology by taking into account a reduced load-carrying capacity due to anisotropy.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Journal of Korea Water Resources Association
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• v.37 no.11
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• pp.915-927
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• 2004

The purpose of this paper is to estimate the instream flow of the South Han River Basin to ensure an adequate supply of suitable quality of water for preservation and enhancement of aquatic ecosystems. Proposed methods is Physical Habitant Simulation System of Instream Flow Incremental Methodology. Accurate estimation on a water depth and a velocity distribution was acquired by applying a two dimensional hydrodynamic model for a simulation of a hydraulic parameter necessary for the habitat evaluation to be used in a physical habitat simulation system. The Habitat Suitability Criteria with the application of univariate curve on zacco platypus as a representative fish was able to be established by conducting a field investigation. The establishment of a hydrological materialistic balance between upper and lower streams was confirmed by conducting a simulation simultaneously together with a mainstream section, which was excluded from the considered sections for the inhabitation evaluation of fish.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.309-319
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• 2016

For binary classification models, we consider a risk score that is a function of linear scores and estimate the coefficients of the linear scores. There are two estimation methods: one is to obtain MLEs using logistic models and the other is to estimate by maximizing AUC. AUC approach estimates are better than MLEs when using logistic models under a general situation which does not support logistic assumptions. This paper considers imbalanced data that contains a smaller number of observations in the default class than those in the non-default for credit assessment models; consequently, the AUC approach is applied to imbalanced data. Various logit link functions are used as a link function to generate imbalanced data. It is found that predicted coefficients obtained by the AUC approach are equivalent to (or better) than those from logistic models for low default probability - imbalanced data.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1224-1234
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• 2019

Hybrid rotor position estimation methods that integrate a fundamental model and high frequency (HF) signal injection are widely used for the wide speed-range sensorless control of interior permanent-magnet synchronous machines (IPMSMs). However, the direct transition of two different schemes may lead to system fluctuations or system instability since two estimated rotor positions based on two different schemes are always unequal due to the effects of parameter variations, system delays and inverter nonlinearities. In order to avoid these problems, a seamless transition strategy to define and construct a virtual q-axis inductance is proposed in this paper. With the proposed seamless transition strategy, an estimated rotor position based on a fundamental model is forced to track that based on HF signal injection before the transition by adjusting the constructed virtual q-axis inductance. Meanwhile, considering that the virtual q-axis inductance changes with rotor position estimation errors, a new observer with a two-phase phase-locked loop (TP-PLL) is developed to accurately obtain the virtual q-axis inductance online. Furthermore, IPMSM sensorless control with maximum torque per ampere (MTPA) operations can be tracked automatically by selecting the proper virtual q-axis inductance. Finally, experimental results obtained from an IPMSM demonstrate the feasibility of the proposed seamless transition strategy.