• Smart Media Journal
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• v.2 no.1
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• pp.27-30
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• 2013

In this paper, we research the hand tracking and calibration algorithm using the EPIC sensor. We analyze the characteristics of EPIC sensor to be more sensitive in the around E-filed, and then we implement the 2-dimensional axis-transformation using the difference of detected amplitude between EPIC sensors. In addition, we implement the calibration algorithm considering the characteristics of EPIC sensor, and then we apply the Kalman filter to efficiently track a target. Thus, we implement the environment of window applications for verification and analysis the implemented algorithm. In turn, we use the DAQ API to extract the analog data. The DAQ hardware has the function of measuring and generating an electrical signal. Moreover, we confirm the movement of mouse cursor by detecting the potential difference depending on the movement of the user's hands.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.7
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• pp.1288-1295
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• 2002

The column-type sensing element in building and mechanical construction parts was designed as three forces and three moments sensor by attaching strain gages approximately. Compared to conventional multi-component sensor, the designed sensor has high stiffness and low cost. The radius of the column was designed analytically and compared with finite element analysis. The interference errors between components were minimized by using addition and subtraction procedure of signals. The fabricated sensor was tested by using a deadweight force standard machine and a six-component force calibration machine. The calibration results showed that the 6-component forces and moments sensor had interference error less than 7.3 % between $F_x$ and $M_x$ components, and 5.0 % in case of other components.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1368-1371
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• 1996

This paper presents an automatic calibration technique for piezoelectric low pressure transducer, which is useful to measure a pressure within 500 psi. This system with automatic calibration function and error correction algorithm generates standard dynamic pressure for the calibration of sensor. With the compensation for the offset voltage and the pressure error, the accuracy and the usefulness of the proposed scheme is validated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.1012-1016
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• 1996

This paper presents an automatic calibration technique for piezoelectic low pressure transducer, which is useful to measure a pressure within 500 psi. This system with automatic calibration function and error correction algorithm generates standard dynamic pressure for the calibration of sensor. With the compensation for the offset voltage and the pressure error, the accuracy and the usefulness of the proposed scheme is validated.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1679-1683
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• 1997

In this paper a linear Kalman filter for calibration of gimballed inertial navigation system(GINS) is designed and its performace is analyzed through the simulation with a real navigation data. Simulation results show that the proposed Kalman filter gives a good performance to calibrate the sensor errors.

• Journal of Biosystems Engineering
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• v.33 no.4
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.483-488
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• 2003

Calibration and gauge factor readjustment process made for the health monitoring system installed in the railway bridges is reviewed and some findings are explained in this study: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in details. Based on the regression results, new gauge factors are obtained from regression equation and another verification is made by performing another calibration again with new factors. From the second calibration, it was found that the suggested regression curves and their factors are appropriate and much better results are expected. Future work will be concentrated on the long-term analysis of the measurement data and on the database structures so that the assessment of the structure such as damage detection and remaining life estimation is possible.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.187-190
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• 1998

The values of physical components of the plants and controllers as well as the relevant environmental conditions change in time, thus the output performance can be deteriorated during the operating span of the system. Naturally the duty of calibration or the prevention of performance deterioration due to excessive component sensitivity should be provided to the control system. The proposed controller, whenever necessary, measures the open-loop and close-loop characteristics, and then calculates the offset and sensor gain correction values based on the prepared standard measurements It is applied to the control of a flexible link system with the gain and offset calibration problems in the light sensor module for position to show the applicability. In this paper, we propose a digital controller which has the capability of calibration gain and offset adjustment using fuzzy methods.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.3 s.357
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• pp.65-71
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• 2007

We propose a pixel-level automatic calibration circuit scheme that initializes a capacitive fingerprint sensor LSI to eliminate the influence of the surface condition and environment, which is degraded by dirt during long-time use, process variation and ambient temperature. The sample chip is fabricated on $0.35{\mu}m$ standard CMOS process. The calibration is executed by optimizing the reference voltage in each pixel to make the sensor signals of all pixels the same. The calibration control circuit is composed of the sensing circuit and charge pumping circuit, and calibrates all pixels in a short time. 16-level gray scale fingerprint images can be captured to increase the accuracy of identification. This confirms that the scheme is effective for capturing consistent clear images during long-time use.