• Near Infrared Analysis
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• v.2 no.1
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• pp.37-42
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• 2001

Near infrared spectroscopy (NIRS) was applied to determination of the lipid content of the compost during the compost fermentation of tofu (soybean0curd) refuse. The absorption of lipid observed at 5 wavelengths, 1208, 1712, 1772, 2312 and 2352 nm on the second derivative spectra. To formulated a calibration equation, a multiple linear regression analysis was carried out between the near-infrared spectral data and on the lipid content in the calibration sample set (sample number, n=60) obtained using Soxhlet extraction method. The value of the multiple correlation coefficient (R) was 0.975 when using the wavelengths of 1208 and 1712 nm were used in the calibration equation. To validate the calibration equation obtained, the lipid content in the validation sample set (n=35) not used for formulating the calibration equation was calculated using the calibration equation, and compared with the value obtained using the Soxhlet extraction method. Good agreement was observed between the results of the Soxhlet extraction method and those values of the NIRS method. The simple correlation coefficient (r) and standard error of prediction (SEP) were 0.964 and 0.815 %, respectively. suitability of the lipid content as an indicator of the compost fermentation of tofu refuse was also studied. The decrease of the lipid content in the compost corresponded to the decrease of the total dry weight of the compost in the composter. The lipid content was a significant indicator of the compost fermentation. The NIRS method was applied to measure the time course of the lipid content in the compost fermentation and good results were obtained. The study indicates that NIRS is a useful method for process management of the compost fermentation of tofu refuse.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1254-1254
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• 2001

Near infrared spectroscopy (NIRS) was applied to determination of the lipid content of compost during compost fermentation of tofu(soybean-curd) refuse. The reflected rays in the wavelength range between 800 and 2500 nm were measured at 2 nm intervals. The absorption of lipid observed at 4 wavelengths, 1208, 1712, 2312 and 2352 nm on the second derivative spectra. To formulate a calibration equation, a multiple linear regression analysis was carried out between the near-infrared spectral data and on the lipid content in the calibration sample set (sample number, n=60) obtained using a Soxhlet extraction method. The calibration equation for prediction of lipid, the value of the multiple correlation coefficient (R) was 0.975 when using the wavelengths of 1208 and 1712nm. To validate the calibration equation obtained, the lipid content in the validation sample set (n=35) not used for formulating the calibration equation were calculated using the calibration equations, and compared with the values obtained using the Soxhlet extraction method. Good agreement were observed between the results of the Soxhlet extraction method and those values of the NIRS method. The simple correlation coefficient (r) and standard error of prediction (SEP) were 0.964 and 0.815 %, respectively. Then, the NIRS method was applied to a compost fermentation in which the time course the lipid content were measured and good results were obtained. The study indicates that NIRS is a useful method for process management of the compost fermentation of tofu refuse.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2372-2374
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• 2003

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1,2,3,4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.2
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• pp.111-119
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• 2013

This paper proposes one method on photometric stereo calibration using the constraint on light source directions in which the light sources have the unknown tilt and slant angles but the slant angles are the same. First, the constraint is analyzed based on the equation of linear ambiguity which leads to the conclusion that another constraint should be added to solve the calibration completely. Later, the combination of constraint on light source directions and the constraint that there exists at least six surface patches having known albedos is exploited to resolve the linear ambiguity up to an accurate and close-form solution. The effective performance of the proposed method is demonstrated through experiment results.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.371-374
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• 1997

Recently, the development of computer achieves a system which is similar to the mechanics of human visual system. The 3-dimensional measurement using monocular vision system must be achieved a camera calibration. So far, the camera calibration technique required reference target in a scene. But, these methods are inefficient because they have many calculation procedures and difficulties in analysis. Therefore, this paper proposes a native method that without reference target in a scene. We use the grid type frame with different line widths. This method uses vanishing point concept that possess a rotation parameter of the camera and perspective ration that perspect each line widths into a image. We confirmed accuracy of calibration parameter estimation through experiment on the algorithm with a grid paper with different line widths.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.592-594
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• 2004

Camera calibration is an important problem to determine the relationship between 3D real world and 2D camera image. The existing calibration methods can be classified into linear and non-linear models. The linear methods are simple and robust against noise, but the accuracy expectation is generally poor. In comparison, if the non-linearity, which is due mainly to lens distortion, is corrected, the accuracy can be better. However, as the optical features of lens are diverse, no non-linear method can be always effective for diverse vision systems. In this paper, we propose a new approach to correct the calibration error of a linear method using GMDH algorithm. The proposed technique is simple in concept and showed improved accuracy in various cases.

• Mass Spectrometry Letters
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• v.9 no.3
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• pp.77-80
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• 2018

The focus of this paper is to present techniques to overcome certain difficulties in quantitative analysis with a time-of-flight mass spectrometer (TOF-MS). The method is based on conventional solid-phase extraction, followed by reversed-phase ultra high performance liquid chromatography of the extract, and mass spectrometric analysis. The target compounds included atenolol, atrazine, caffeine, carbamazepine, diclofenac, estrone, ibuprofen, naproxen, simazine, sucralose, sulfamethoxazole, and triclosan. The matrix effects caused by high concentrations of organic compounds in wastewater are especially significant in electrospray ionization mass spectroscopy. Internal-standard calibration with isotopically labeled standards corrects the results for many matrix effects, but some peculiarities were observed. The problems encountered in quantitation of carbamazepine and triclosan, due to nonlinear calibration were solved by changing the internal standard and using a narrower mass window. With simazine, the use of a quadratic calibration curve was the best solution.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.9
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• pp.32-39
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• 2006

In this paper, an iterative subspace-based calibration algorithm for a CDMA-based antenna array in the presence of unknown gain and phase error is presented. The algorithm does not depend on the array geometry and does not require a prior knowledge of the Directions Of Arrival (DOA) of the signals. The method requires the code sequence of a reference user only. The proposed algorithm is based on the subspace method and root finding approach, and it provides estimates of the calibration vector, the DOA and the channel impulse response, by using the code sequence of a reference user. The performance of the proposed algorithm was investigated by means of computer simulations and was verified using field data measured through a custom-built W-CDMA test-bed. The data show that experimental results match well with the theoretical calibration algorithm. Also, teh study propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the requirement of initial guessing in the subspace-based approach.

• 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.

• Ocean Systems Engineering
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• v.1 no.3
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• pp.195-205
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• 2011

A method for calibrating a laser profiling system for seafloor micro-topography measurements is described. The system consists of a digital camera and an arrangement of six red lasers that are mounted as a unit on a remotely operated vehicle (ROV). The lasers project as parallel planes onto the seafloor, creating profiles of the local topography that are interpreted from the digital camera image. The goal of the calibration was to determine the plane equations for the six lasers relative to the camera. This was accomplished in two stages. First, distortions in the digital image were corrected using an interpolation method based on a virtual pinhole camera model. Then, the laser planes were determined according to their intersections with a calibration target. The position and orientation of the target were obtained by a registration process. The selection of the target shape and size was found to be critical to a successful calibration at sea, due to the limitations in the manoeuvrability of the ROV.