• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.746-749
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• 2002

This paper is introducing a radio control helicopter as a new platform of ground truth measurement. This helicopter is normally used for spraying an agricultural chemical. It can do pinpoint hovering and programing flight using DGPS etc., A spectrometer with dual port can measure ground surface and white reference plate at the same time. And it can also take digital images by digital camera. It is needed to collect ground reflectance information as satellite sensor footprint size for satellite data validation. Generally it is possible to get such ground reflectance by an airplane measurement. But it is high cost and not so easy to make a measurement by airplane. Developed validation system can provide such ground reflectance in low cost and easy.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.765-771
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• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• Wind and Structures
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• v.18 no.4
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• pp.375-389
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• 2014

The high-frequency force-balance (HFFB) technique and its subsequent improvements are reviewed in this paper, including a discussion about nonlinear mode shape corrections, multi-force balance measurements, and using HFFB model to identify aeroelastic parameters. To apply the HFFB technique in engineering practice, various validation studies have been conducted. This paper presents the results from an analytical validation study for a simple building with nonlinear mode shapes, three experimental validation studies for more complicated buildings, and a field measurement comparison for a super-tall building in Hong Kong. The results of these validations confirm that the improved HFFB technique is generally adequate for engineering applications. Some technical limitations of HFFB are also discussed in this paper, especially for higher-order mode response that could be considerable for super tall buildings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.2
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• pp.81-89
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• 2001

Space systems are operating in a changing and uncertain space environment and are desired to have autonomous capability for long periods of time without frequent telecommunications from the ground station At the same time. requirements for new set of projects/systems calling for ""autonomous"" operations for long unattended periods of time are emerging. Since, by the nature of space systems, it is desired that they perform their mission flawlessly and also it is of extreme importance to have fault-tolerant sensor/actuator sub-systems for the purpose of validating science measurement data for the mission success. Technology innovations attendant on autonomous data validation and health monitoring are articulated for a growing class of autonomous operations of space systems. The greatest need is on focus research effort to the development of a new class of fault-tolerant space systems such as attitude actuators and sensors as well as validation of measurement data from scientific instruments. The characterization for the next step in evolving the existing control processes to an autonomous posture is to embed intelligence into actively control. modify parameters and select sensor/actuator subsystems based on statistical parameters of the measurement errors in real-time. This research focuses on the identification/demonstration of critical technology innovations that will be applied to Autonomous Spacecraft Health Monitoring/Data Validation Control Systems (ASHMDVCS). Systems (ASHMDVCS).

• Journal of ILASS-Korea
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• v.18 no.3
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• pp.119-125
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• 2013

Digital holographic particle velocity measurement system can be a promising optical tool for the measurements of three dimensional particle velocities. In this research, validation experiments for the digital holographic particle velocity measurement system were conducted with measuring the velocities of glass beads on a rotating disk. Uncertainty analysis was performed to identify the sources of all relevant errors and to evaluate their magnitudes. The measurement results of particle velocities obtained with digital holographic method are compared reasonably well with the known values within acceptable range of errors. Moreover, digital holographic method showed better performance compared with that of optical holographic system.

• Journal of electromagnetic engineering and science
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• v.15 no.3
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• pp.181-184
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• 2015

Evaluation of radiating radiofrequency fields from hand-held and body-mounted wireless communication devices to human bodies are conducted by measuring the specific absorption rate (SAR). The uncertainty of system validation and probe calibration in SAR measurement depend on the variation of RF power used for the validation and calibration. RF input power for system validation or probe calibration is controlled manually during the test process of the existing systems in the laboratories. Consequently, a long time is required to reach the stable power needed for testing that will cause less uncertainty. The standard uncertainty due to this power drift is typically 2.89%, which can be obtained by applying IEC 62209 in a normal operating condition. The principle of the Automatic Input Power Level Control System (AIPLC), which controls the equipment by a program that maintains a stable input power level, is suggested in this paper. The power drift is reduced to less than ${\pm}1.16dB$ by AIPLC, which reduces the standard uncertainty of power drift to 0.67%.

• Journal of Environmental Impact Assessment
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• v.21 no.6
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• pp.893-901
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• 2012

Aircraft noise model such as FAA Integrated Noise Model(INM) has recently been used for forecasting the impact of noise in a residential area near an airport and quantifying the effect of various options for noise mitigation. The noise modeling should be reliable and precise in order to ensure the quality of the results provided. In this study, the validation of the noise levels simulated by the INM against measurement data recorded continuously at multiple monitoring sites was discussed. As a result of validation, the quality of the input data used as a fixed point profiles for the INM was enhanced. The noise contour maps were designed as a way to evaluate the aircraft noise of the vicinity of the airfield. The results of this study indicate that the validation of aircraft noise model by the measurement data would be required for the accurate assessment of the aircraft noise levels.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.612-614
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• 1999

In order to improve the operational reliability, it is necessary to validate the measured sensor data, isolate any failed sensor and recover the failed critical measurement. This paper describes the use of estimating equation to identify failed sensors and to recover the feedback signal for control purpose when the sensor measurement is determined to be erroneous Simulation results show that the proposed sensor validation scheme can adequately identify the failed sensor and provide reasonable estimates for control purposes.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.209-216
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• 2015

Quantile regression models with covariate measurement errors have received a great deal of attention in both the theoretical and the applied statistical literature. A lot of effort has been devoted to develop effective estimation methods for such quantile regression models. In this paper we propose the partially linear support vector orthogonal quantile regression model in the presence of covariate measurement errors. We also provide a generalized approximate cross-validation method for choosing the hyperparameters and the ratios of the error variances which affect the performance of the proposed model. The proposed model is evaluated through simulations.