• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.441-457
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• 2014

Observed from the recent performance evaluation of clustering schemes in wireless sensor networks, we found that most of them did not consider various sensor characteristics and its application environment. Without considering these, the performance evaluation results are difficult to be trusted because these networks are application-specific. In this paper, for the fair evaluation, we measured several clustering scheme's performance variations in accordance with sensor data pattern, number of sensors per node, density of points of interest (data density) and sensor coverage. According to the experiment result, we can conclude that clustering methods are easily influenced by POI variation. Network lifetime and data accuracy are also slightly influenced by sensor coverage and number of sensors. Therefore, in the case of the clustering scheme that did not consider various conditions, fair evaluation cannot be expected.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.209-216
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• 2010

Optical Temperature Distribution Sensor Measurement System uses fiber optic sensors itself for temperature measurement is a system which can be measured the Installed surrounding entire temperature as a thousand points by laying a single strand of fiber optic. If there are a lot of measuring points in the distribution Measurement, the cost of each measuring point can be reduced the cost level of existing sensors and at the same time this has the advantage of connecting all sensors as one or two strands of fiber. Generally Optical Fiber is used for communication but Optical Fiber itself can be used for sensor and it has the characteristic of sensor function which can be measured Temperature in the at least each one meter distance. By using these characteristics each sensor and the number of Connection Lines can be reduced. In this paper, we implement a real time temperature monitoring system, which is easy to manage and control for data storage, data management, data storage using a computer and which has the functions of monitoring and correction according to Real-time temperature changes using historical temperature data.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.285-294
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• 2006

A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigated three sensor models: collinearity model, direct linear transform (DLT) model and orbit-based model. We applied matching between GOES images and global coastline database and used successful results as control points. With control points we improved the initial image geolocation accuracy using the three models. We compared results from three sensor models. As a result, we showed that the orbit-based model is a suitable sensor model for precise geolocation of GOES-9 Images.

• Proceedings of the KSRS Conference
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• v.2
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• pp.578-581
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• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

• Progress in Superconductivity and Cryogenics
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• v.17 no.3
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• pp.28-32
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• 2015

Nowadays the magnetic field mapping is widely used in the design and analysis of the NMR/MRI magnet system, and the accuracy of mapping result has become more and more important. There are several factors affecting the accuracy of the mapping such as the mapping method, the precision of the sensor, the position of the measurement points, the calculation accuracy, and so on. In this paper the error due to the misalignment of the measurement points was discussed. The magnetic field in the central volume was mapped using an indirect method in an MRI magnet system and the magnetic field was fitted to a polynomial. Considering the misalignment between the original measurement points and the practical measurement points, there must be some errors in the mapping calculation and we called it positioning error. Several comparisons of the positioning error have been presented through the theoretical estimates and the exact magnetic field values. Finally, the allowable positioning errors were suggested to guarantee the accuracy of the magnetic field mapping within a certain degree for an example case.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.629-644
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• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.200-207
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• 2007

The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.5-41
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• 2002

This paper presents a feature extraction algorithm for vision-based micromanipulation. In order to guarantee of the accurate micromanipulation, most of micromanipulation systems use vision sensor. Vision data from an optical microscope or high magnification lens have vast information, however, characteristics of micro image such as emphasized contour, texture, and noise are make it difficult to apply macro image processing algorithms to micro image. Grasping points extraction is very important task in micromanipulation because inaccurate grasping points can cause breakdown of micro gripper or miss of micro objects. To solve those problems and extract grasping points for micromanipulation...

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.161-167
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• 2012

Portable devices such as smartphones with built-in wireless LAN to the prevalence of anyone using. But the wireless Internet connection and positioning services are limited to high-quality wireless service, they may not be available. Thus, wireless LAN infrared sensor in the same way as with angry alternative way wireless capabilities of the application automatically identify the location of the Sensor application as an alternative method is proposed. Thus, wireless LAN, such as infrared sensors and other alternzative methods of wireless features in a way where the application can recognize and automatically recognize the sensor application as an alternative method is proposed. Sensor is signals between wireless LAN and access points using the sensitivity, WLAN antenna with omni-directional signal output operation of the sensor is assumed to be recognize this by putting a direction to obtain through the proposed algorithm, Sensors such as photo-coupler without direct recognition sensor, wireless LAN and access points, the same function as the connection between the sensitivity to perform its function was to utilizing.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..