• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.407-414
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• 2008

This study introduces an automatic image matching algorithm that can be applied for the scale different image pairs consisting of the satellite pushbroom images and the aerial frame images. The proposed method is based on several image processing techniques such as pre-processing, filtering, edge thinning, interest point extraction, and key-descriptor matching, in order to enhance the matching accuracy and the processing speed. The proposed method utilizes various characteristics, such as the different geometry of image acquisition and the different radiometric characteristics, of the multi-sensor images. In addition, the suggested method uses the sensor model to minimize search area and eliminate false-matching points automatically.

• Journal of Sensor Science and Technology
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• v.10 no.5
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• pp.286-291
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• 2001

We propose a new saliency map model for selecting an attended location in an arbitrary visual scene, which is one of the most important characteristics of human vision system. In selecting an attended location, an edge information can be considered as a feature basis to construct the saliency map. Edge filters are obtained from the independent component analysis(ICA) that is the best way to find independent edges in natural gray scenes. In order to reflect the non-uniform density in our retina, we use a multi-scaled pyramid input image instead of using an original input image. Computer simulation results show that the proposed saliency map model with multi-scale property successfully generates the plausible attended locations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2473-2492
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• 2012

Energy conservation is a vital issue in wireless sensor networks. Recently, employing mobile sinks for data gathering become a pervasive trend to deal with this problem. The sink can follow stochastic or pre-defined paths; however the controlled mobility pattern nowadays is taken more into consideration. In this method, the sink moves across the network autonomously and changes its position based on the energy factors. Although the sink mobility would reduce nodes' energy consumption and enhance the network lifetime, the overhead caused by topological changes could waste unnecessary power through the sensor field. In this paper, we proposed EEDARS, an energy-efficient dual-sink algorithm with role switching mechanism which utilizes both static and mobile sinks. The static sink is engaged to avoid any periodic flooding for sink localization, while the mobile sink adaptively moves towards the event region for data collection. Furthermore, a role switching mechanism is applied to the protocol in order to send the nearest sink to the recent event area, hence shorten the path. This algorithm could be employed in event-driven and multi-hop scenarios. Analytical model and extensive simulation results for EEDARS demonstrate a significant improvement on the network metrics especially the lifetime, the load and the end-to-end delay.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.232-239
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• 2008

The position sensors used in a magnetic bearing system are desirable to provide some degree of fault-tolerance as the rotor position is necessary for the feedback control to overcome the open-loop instability. In this paper, we propose an inductive position sensor that can cope with a partial fault in the sensor. The sensor has multiple poles which can be combined to sense the in-plane motion of the rotor. When a high-frequency voltage signal drives each pole of the sensor, the resulting current in the sensor coil contains information regarding the rotor position. The signal processing circuit of the sensor extracts this position information. In this paper, we used the magnetic circuit model of the sensor that shows the analytical relationship between the sensor output and the rotor motion. The multi-polar structure of the sensor makes it possible to introduce redundancy which can be exploited for fault-tolerant operation. The proposed sensor is applied to a magnetically levitated turbo-molecular vacuum pump. Experimental results validate the fault-tolerance algorithm.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.4
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• pp.83-90
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• 2017

Unmanned Aerial Vehicles(UAVs) require collision avoidance capabilities equivalent to the capabilities of manned aircraft to enter the airspace of manned aircraft. In the case of Visual Flight Rules of manned aircraft, collision avoidance is performed by 'See-and-Avoid' of pilots. To obtain those capabilities of UAVs named as 'Sense-and-Avoid', sensor-system-based intruder tracking and collision avoidance methods are required. In this study, a multi-sensor-based tracking, data fusion, and collision avoidance algorithm is designed by using a model-based design tool MATLAB/SIMULINK, and validations of the designed model and code using numerical simulations and processor-in-the-loop simulations are performed.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.21-27
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• 2003

The rational polynomial coefficients(RPC) model is a generalized sensor model that is used as an alternative for the physical sensor model for IKONOS-2 and QuickBird. As the number of sensors increases along with greater complexity, and as the need for standard sensor model has become important, the applicability of the RPC model is also increasing. The RPC model can be substituted for all sensor models, such as the projective camera the linear pushbroom sensor and the SAR This paper is aimed at generating a RPC model from the physical sensor model of the KOMPSAT-1(Korean Multi-Purpose Satellite) and aerial photography. The KOMPSAT-1 collects $510{\sim}730nm$ panchromatic images with a ground sample distance (GSD) of 6.6m and a swath width of 17 km by pushbroom scanning. We generated the RPC from a physical sensor model of KOMPSAT-1 and aerial photography. The iterative least square solution based on Levenberg-Marquardt algorithm is used to estimate the RPC. In addition, data normalization and regularization are applied to improve the accuracy and minimize noise. And the accuracy of the test was evaluated based on the 2-D image coordinates. From this test, we were able to find that the RPC model is suitable for both KOMPSAT-1 and aerial photography.

• International Journal of Aeronautical and Space Sciences
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• v.1 no.1
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• pp.70-80
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• 2000

The attitude knowledge error model is formulated for specifically KOMPSAT attitude determination system using the Lefferts/Markley/Shuster method, and the attitude determination(AD) error analysis is performed so as to investgate the on-board attitude determination capability of KOrea Multi-Purpose SATellite(KOMPSAT) using the covariance analysis method. Analysis results show there is almost no initial value effect on Attitude Determination (AD) error and the sensor noise effects on AD error are drastically decreased as is predicted because of the inherent characteristic of Kalman filter structure. However, it shows that the earth radiance effect of IR-sensor(earth sensor) and the bias effects of both IR-sensor and fine sun sensor are the dominant factors degrading AD error and gyro rate bias estimate error in AD system. Analysis results show that the attitude determination errors of roll, pitch and yaw axes are 0.056, 0.092 and 0.093 degrees, respectively. These numbers are smaller than the required values for the normal mission of KOMPSAT. Also, the selected on-orbit data of KOMPSAT is presented to demonstrate the designed AD system.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.276-278
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• 2009

In this paper, we propose the smart management technique of applications using fuzzy logic in wireless sensor networks. We consider the intelligent action compared to the classical action that can only be controlled by on and off. The vagueness depends on the places of the sensor nodes, human's character and emotion. In order to control them with the smartness, the proposed technique considers the better performance of applications in wireless sensor networks. We performed the simulations and implementations on sensor nodes and checked out our ideas. The simulation results show that the proposed technique is more reasonable than the classical approach.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.37-45
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• 2014

This paper reports the geolocation accuracy of KOMPSAT-3 imagery. KOMPSAT-3 was launched successfully on May 18, 2012 and has been released last March. In this paper, we have checked the geolocation accuracy of initial sensor model, precise sensor model and stereo-and multi-image model using four KOMPSAT-3 images covering the same area. The KOMPSAT-3 images without GCPs provided the geolocation accuracy of about 30m and the geocorrected KOMPSAT-3 images provided the geolocation accuracy of about 1m or less. KOMPSAT-3 stereo- and multi-images models yield threedimensional points with sub-meter accuracy in horizontal and vertical direction. Overall, KOMPSAT-3 showed much improved performance in terms of the geolocation accuracy over KOMPSAT-2. KOMPSAT-3 is expected to be able to replace foreign satellite data with sub-meter accuracy level for achieving accurate geometric information.