• Progress in Medical Physics
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• v.9 no.1
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• pp.1-9
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• 1998

In order to provide complementary image data, CT(computed tomography), MR(magnetic resonance) and angiography have been used in the field of Stereotactic Radiosurgery(SRS) and neurosurgery. The aim of this work is to develop 3-D stereotactic localization system in order to determine the precise shape, size and location of the lesion in the brain in the field of Stereotactic Radiosurgery(SRS) and neurosurgery using multi-image modality and multi purpose QA phantom. In order to obtain accurate position of a target, Hitchcoke stereotactic frame and CT/angiography localizers were rigidly attached to the phantom with nine targets dispersed in 3-D space. The algorithms to obtain a 3-D stereotactic coordinates of the target have been developed using the images of the geometrical phantom which were taken by CT/angiography. Positions of targets computed by our algorithms were compared to the absolute position assigned in the phantom. Outlines of targets on each CT image were superimposed each other on angiography images. A spatial mean distance errors were 1.02${\pm}$0.17mm for CT with a 512${\times}$512 matrix and 2mm slice thickness, 0.41${\pm}$0.05mm for angiogra- phy localization. The resulting accuracy in the target localization suggests that the developed system has enough Qualification for Stereotactic Radiosurgery (SRS).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.41-47
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• 2005

Even more than 240 commercial geostationary communication satellites currently on orbit at the higher location than the GPS orbit altitude perform their own missions only by the support of the ground segment because of weak visibility from GPS. In addition, the orbit determination accuracy is very low without using two or more dedicated ground tracking antennas in intercontinental ground segment, since the satellite hardly moves with respect to the ground station. In this paper, we propose the GSPS(Geostationary Satellite Positioning System) in circular orbits of two sidereal days period higher than the geosynchronous orbit for orbit determination and autonomous satellite operation. The GSPS is conceived as a ranging system in that unknown positions of a geostationary satellite can be acquired from the known positions of the GSPS satellites. Each GSPS satellite transmits navigation data, clock data, correction data, and geostationary satellite command to control a geostationary satellite.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1498-1503
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• 2010

PC Skillreporting feedback during cardiopulmonary resuscitaion would improve the performance of chest compression and ventilation during cardiac arrest. BLS skills were measured using Laerdal Skillreporter manikin(Laerdal, Norway) connected to a Laerdal PC Skillreporting system. Ventilation volume, chest compression accuracy, velocity of compression, depth of compression, hand position and chest recoil were measured between the two groups. Ventilation volume was significantly higher in the experimental group than that of control group(p<0.002). Chest compression depth was significantly higher in experimental group than that of control group(p=0.000). The quality of CPR can be improved by the use of PC Skillreporting system.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.848-855
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• 2008

In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.599-603
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• 2003

This paper present an error compensation system and On-Machine Measurement(OMM) system for improving the machining accuracy of ultra-precision lathe. The Fast-Tool-Servo(FTS) driven by a piezoelectric actuator is applied for error compensation system. The controller is implemented on the 32bit DSP for feedback control of piezoelectric actuator. The control system is designed to compensates three kinds of machining errors such as the straightness error of X-axis slide, the thermal growth error of the spindle. and the squareness between spindle and X-axis slide. OMM is preposed to measure the finished profile of workpiece on the machine-tool using capacitive sensor with highly accurate ruby tip probe guided by air bearing. The data acquisition system is linked to the CNC controller to get the position of each axis in real-time. Through the experiments, it is founded that the thermal growth of spindle and tile squareness error between spindle and X-axis slide influenced to machining error more than straightness error of X-axis slide in small travel length. These errors were simulated as a sinusoidal signal which has very low frequency and the FTS could compensate the signal less than 30 m. The implemented OMM system has been tested by measuring flat surface of 50 mm diameter and shows measurement error less than 400 mm

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.70-76
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• 2009

We proposed the device to control a computer mouse with only head movements and eye blinks so that disabilities by car or other accidents can use a computer. The mouse position were estimated from a gyro-sensor which can measure head movements, and the mouse events such as click/double click were from opto sensors which can detect the eyes flicker, respectively. The sensor was mounted on the goggle in order not to disturb the visual field. There was no difference in movement speed between ours and a general mouse, but it required 3$\sim$4 more times in the result of the experiment to evaluate spatial movements and events detection of the proposed mouse because of the low accuracy. We could eliminate cumbersome work to periodically remove the accumulated error and intuitively control the mouse using non-linear relative point method with dead zones. Optical sensors are used in the event detection circuitry designed to remove the influence of the ambient light changes, therefore it was not affected in the change of external light source.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.463-468
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• 2010

An obstacle avoidance method for a mobile robot is proposed in this paper. Our research was focused on the obstacles that can be found indoors since a robot is usually used within a building. It is necessary that the robot maintain the desired direction after successfully avoiding the obstacles to achieve a good autonomous navigation performance for the specified project mission. Sensors such as laser, ultrasound, and PSD (Position Sensitive Detector) can be used to detect and analyze the obstacles. A PSD sensor was used to detect and measure the height and width of the obstacles on the floor. The PSD sensor was carefully calibrated before measuring the obstacles to achieve better accuracy. Data obtained from the repeated experiments were used to plot an error graph which was fitted to a polynomial curve. The polynomial equation was used to navigate the robot. We also obtained a direction-error model of the robot after avoiding the obstacles. The prototypes for the obstacle and direction-error were modeled using a neural network whose inputs are the obstacle height, robot speed, direction of the wheels, and the error in direction. A mobile robot operated by a notebook computer was setup and the proposed algorithm was used to navigate the robot and avoid the obstacles. The results showed that our algorithm performed very well during the experiments.

• 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.