• Water Engineering Research
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• v.5 no.4
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• pp.185-193
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• 2004

Estimates of annual actual evapotranspiration are needed in water balance studies, water resources management projects, and many different types of hydrologic studies. This study validated a set of 5 empirical equations of estimating annual actual evapotranspiration with climate data on 11 watersheds, and evaluated the further applicability of these forms in estimating annual runoff on watershed level. Five empirical equations generally overestimated annual evapotranspiration, with relative errors ranging $3.3\%$ to $47.2\%$. The results show that Schreiber formula can be applicable in determining annual evapotranspiration in sub-humid region that is classified by aridity index, while Zhang equation gave better results than the remaining methods in humid region. The mean differences for annual evapotranspiration bias over 11 watersheds are Zhang, Schreiber, Budyko, Pike, and Ol'dekop formula from lowest to highest. The empirical equations provide a practical tool to help water resources managers in estimating regional water resources on ungauged large watershed.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.1-9
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• 2014

This paper discusses the problem of estimation of finite population mean in double sampling for stratification. In fact, ratio and product type exponential estimators of population mean are proposed in double sampling for stratification. The biases and mean squared errors of proposed estimators are obtained upto the first degree of approximation. The proposed estimators have been compared with usual unbiased estimator, ratio and product estimators in double sampling for stratification. To judge the performance of the proposed estimators an empirical study has been carried out.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.352-357
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• 2004

This paper studies the errors that associated with particle velocity and intensity in a space. We theoretically derived their bias error and random error. The analysis shows that the more samples do not always guarantee the better results. The random error of the velocity and intensity are increased when we have many samples. The characteristics of the amplification of the random error are analyzed in terms of the sample spacing. The amplification was found to be related to the spatial differential of random noise. The numerical simulations are performed to verify theoretical results.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1045-1050
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• 2005

This paper describes a design experience of a low-cost 6 DOF spatial tracker system where relative low accuracy and relatively long ranges, wireless communication will be achieved by means of low cost accelerometers and gyros with contemporary microprocessor. However, there are two key problems; one is the bias drift problem and the other is that single or double integration of acceleration signal suffers not only from noise but also from nonlinear effects caused by gravity. To be specific, beginning and stopping of hand motions needs to be accurately detected to initiate and terminate integration process to get position and pose of the hand from accelerometer and gyro signals, since errors due to noise and/or hand-shaking motions accumulated by integration processes. Several experimental results are shown to validate our proposed algorithms.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.447-463
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• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.323-330
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• 1989

Large bias errors which occur during a numerical evaluation of the Rayleigh's integral is not due to the replicated source problem but due to the coincidence of singularities of the Green's function and the sampling points in Fourier domain. We found that there is no replicated source problem in evaluating the Rayleigh's integral numerically by the reason of the periodic assumption of the input sequence in Dn or by the periodic sampling of the Green's function in the Fourier domain. The wrap around error is not due to an overlap of the individual adjacent sources but berallse of the undersampling of the Green's function in the frequency domain. The replicated and overlApped one is inverse Fourier transformed Green's function rather than the source function.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.527-530
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• 1996

The Kalman filter has been used as a self-localization method for the mobile robot. To satisfy the assumptions inherent in the Kalman filter, we should calibrate the sensors of the robot before use of them. However, it is generally hard to find exact sensor parameters, and the parameters may change during the robot task as the environment varies. Thus we need to perform on-line sensor calibration, by which we can obtain more credible location of the mobile robot. In this paper, we present an on-line sensor calibration scheme which estimates the unknown sensor bias and the current position of the robot. To this end, first we find out the calibration errors of the sensor from redundant sensory data using the parity vector and recursive minimum variance estimation. Then we calculate the current position of the robot by weighted least square estimation without internal encoder data. The performance of the proposed method is evaluated through computer simulation.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.518-521
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• 1998

This paper describes a 3.3V-65MHz 12BIT CMOS current-mode DAC designed with a 8 MSB current matirx stage and a 4 LSB binary weighting stage. The linearity errors caused by a voltage drop of the ground line and a threshold voltage mismatch of transistors have been reduced by the symmetrical routing method with ground line and the tree structure bias circuit, respectively. In order to realize a low glitch energy, a cascode current switch ahs been employed. The simulation results of the designed DAC show a coversion rate of 65MHz, a powr dissipation of 71.7mW, a DNL of .+-.0.2LSB and an INL of .+-.0.8LSB with a single powr supply of 3.3V for a CMOS 0.6.mu.m n-well technology.

• Genomics & Informatics
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• v.11 no.3
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• pp.121-128
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• 2013

The introduction of metagenomics into the field of virology has facilitated the exploration of viral communities in various natural habitats. Understanding the viral ecology of a variety of sample types throughout the biosphere is important per se, but it also has potential applications in clinical and diagnostic virology. However, the procedures used by viral metagenomics may produce technical errors, such as amplification bias, while public viral databases are very limited, which may hamper the determination of the viral diversity in samples. This review considers the current state of viral metagenomics, based on examples from Korean viral metagenomic studies-i.e., rice paddy soil, fermented foods, human gut, seawater, and the near-surface atmosphere. Viral metagenomics has become widespread due to various methodological developments, and much attention has been focused on studies that consider the intrinsic role of viruses that interact with their hosts.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1279-1286
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• 1999

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.