• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.69-76
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• 2008

Most pressurized water reactors use Venturi flow meters to measure the feedwater flow rate. However, fouling phenomena, which allow corrosion products to accumulate and increase the differential pressure across the Venturi flow meter, can result in an overestimation of the flow rate. In this study, a soft-sensing model based on fuzzy support vector regression was developed to enable accurate on-line prediction of the feedwater flow rate. The available data was divided into two groups by fuzzy c means clustering in order to reduce the training time. The data for training the soft-sensing model was selected from each data group with the aid of a subtractive clustering scheme because informative data increases the learning effect. The proposed soft-sensing model was confirmed with the real plant data of Yonggwang Nuclear Power Plant Unit 3. The root mean square error and relative maximum error of the model were quite small. Hence, this model can be used to validate and monitor existing hardware feedwater flow meters.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.221-226
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• 2007

A robust position-sensing system is proposed in this paper for ubiquitous mobile robots which move indoor as well as outdoor. The Differential GPS (DGPS) which has position estimation error of less than 5 m is a general solution when the mobile robots are moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is selected as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position-sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified through the real experiments using a mobile robot prepared for this research and demonstrated.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.89-94
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• 2002

In this paper, a Exhaust Flow Controller (EFC) technology for uniform application of film coater and developer device is introduced that spread and remove photo resister at semiconductor manufacturing process. Because developed EFC device uses differential pressure sensing method as a differential flow meter and embodied smart A/D conversion by using a one chip microprocessor and devised by feedback Servo control, It has shown excellent performance and stability evaluation, as maximum 2000L/min flow, capability of installation to actual semiconductor equipment.

• Journal of Applied and Pure Mathematics
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• v.5 no.5_6
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.219-224
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• 2002

This paper aims to derive a mathematical model of the dynamics of handling tasks in robot finger which stable grasping and manipulates a rigid object with some dexterity. Firstly, a set of differential equation describing dynamics of the manipulators and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. Secondly, problems of controlling both the internal force and the rotation angle of the grasped object under the constraints of area-contacts of tight area-contacts are discussed. The effect of geometric constraints of area-contacts on motion of the overall system is analyzed and a method of computer simulation for overall system of differential-algebraic equations is presented. Thirdly, simulation results are shown and the effects of geometric constraints of area-contact is discussed. Finally, it is shown that even in the simplest case of dual single D.O.F manipulators there exists a sensory feedback from sensing data of the rotational angle of the object to command inputs to joint actuators and this feedback connection from sensing to action eventually realizes secure grasping of the object, provided that the object is of rectangular shape and motion is confined to a horizontal plane.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.910-916
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• 2015

A sensorless motor control scheme with conventional back-Electro Motive Force (EMF) sensing based on zero crossing point (ZCP) detection has been widely used in various applications. However, there are several problems with the conventional method for effectively driving sensorless brushless motors. For example, a phase mismatch of 30 degrees occurs between the ZCP and commutation time. Additionally, most of the motor speed/current controls are achieved based on a pulse width modulation (PWM) method, which generates significant noise that distracts the back-EMF sensing. Due to the PWM switching, the ZCP is not deterministic, and thus the efficiency of the motor is reduced because the phase transition points become uncertain. Moreover, the motor driving performance is degraded at a low speed range due to the effect of PWM noise. To solve these problems, an improved back-EMF detection method based on a differential line method is proposed in this paper. In addition, the proposed sensorless BLDC driver addresses the problems by using a variable voltage driver generated from a buck converter. The variable voltage driver does not generate the PWM switching noise. Consequently, the proposed sensorless motor driver improves 1) the signal-to-noise ratio of back-EMF, 2) the operation range of a BLDC motor, and 3) the torque characteristics. The proposed sensorless motor driver is verified through simulations and experiments.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.297-304
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• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.10-16
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• 2021

This paper proposes a model that considers the parity-time symmetric structure as a state detection circuit for sensor applications using a stretchable inductor. In particular, to obtain a more practical computer simulation result, the stretchable inductor model was applied to this study model by referring to previously reported experimental results. The resistance component and phase component were controlled through the negative differential resistance circuit used in this study. In addition, the imbalance of the circuit caused by a change in the characteristics of the stretchable inductor could be compensated for using a negative differential resistance circuit. In particular, an analysis of the frequency characteristics of the sensor driving circuit of the parity-time symmetric structure proposed in this study confirmed that the Q-factor could be increased up to 20 times compared to the conventional resonant circuit.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.165-177
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• 2008

Small baseline subset (SBAS) algorithm has been recently developed using an appropriate combination of differential interferograms, which are characterized by a small baseline in order to minimize the spatial decorrelation. This algorithm uses the singular value decomposition (SVD) to measure the time-series surface deformation from the differential interferograms which are not temporally connected. And it mitigates the atmospheric effect in the time-series surface deformation by using spatially low-pass and temporally high-pass filter. Nevertheless, it is not easy to correct the phase unwrapping error of each interferogram and to mitigate the time-varying noise component of the surface deformation from this algorithm due to the assumption of the linear surface deformation in the beginning of the observation. In this paper, we present an improved SBAS technique to complement these problems. Our improved SBAS algorithm uses an iterative approach to minimize the phase unwrapping error of each differential interferogram. This algorithm also uses finite difference method to suppress the time-varying noise component of the surface deformation. We tested our improved SBAS algorithm and evaluated its performance using 26 images of ERS-1/2 data and 21 images of RADARSAT-1 fine beam (F5) data at each different locations. Maximum deformation amount of 40cm in the radar line of sight (LOS) was estimated from ERS-l/2 datasets during about 13 years, whereas 3 cm deformation was estimated from RADARSAT-1 ones during about two years.