• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2321-2330
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• 2015

A variety of studies for indoor positioning are now being in progress due to the limit of GPS that becomes obsolete in the room. However, most of them are based on private wireless networks and the situation is difficult to commercialize them since they are expensive in terms of installation and maintenance costs, non-real-time, and not accurate. This paper applies the mark recognition algorithm used in existing augmented reality applications to the indoor vehicle positioning application. It installs floor marks on the ground, performs the perspective transformation on it and decodes the internal data of the mark and, as a result, it obtains an absolute coordinate. Through the geometric analysis, it obtains current position (relative coordinates) of a vehicle away from the mark and the heading direction of the vehicle. The experiment results show that when installing the marks every 5 meter, an error under about 30 cm occurred. In addition, it is also shown that the mark recognition rate is 43.2% of 20 frames per second at the vehicle speed of 20km/h. Thus, it is thought that this idea is commercially valuable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1950-1956
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• 2017

In food-printing field, precise positioning technique for a printing object is very important. In this paper, we propose cup positioning method for a latte-art printer through image processing. A camera sensor is installed on the upper side of the printer, and the image obtained from this is projected and converted into a top-view image. Then, the edge lines of the image is detected first, and then the coordinate of the center and the radius of the cup are detected through a Circular Hough transformation. The performance evaluation results show that the image processing time is 0.1 ~ 0.125 sec and the cup detection rate is 92.26%. This means that a cup is detected almost perfectly without affecting the whole latte-art printing time. The center point coordinates and radius values of cups detected by the proposed method show very small errors less than an average of 1.5 mm. Therefore, it seems that the problem of the printing position error is solved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.75-80
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• 2021

Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.219-225
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• 2021

As for the battery package method, a prismatic package method is preferred for stability reasons, but it is rapidly expanding due to the stability verification of a pouch type package. The pouch type using the lamination process has an advantage of high battery energy density because it can reduce space waste, but has a disadvantage of low productivity. Therefore, in this paper, by extracting edge detection algorithm precision, pattern algorithm precision, and motion controller recall rate by improving backlight lighting fixtures to minimize light diffusion, securing standards for stereo camera position relationship displacement monitoring, and securing standards for lens release monitoring. We propose to implement a system that ensures accuracy and reliability in positioning. As a result of the experiment, the proposed system shows an average error range of 0.032mm for edge detection, 0.02mm for pattern algorithm, and 0.014mm for motion controller, thus ensuring the accuracy and reliability of the positioning mechanism.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.533-539
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• 2020

Real-time service (RTS) provided by IGS provides correction for GNSS orbit and clock via internet, so it is widely used in fields that require real-time precise positioning. However, the RTS signal may be lost due to an unstable Internet environment. When signal disconnection occurs, signal prediction can be performed using polynomial models. However, the RTS changes rapidly after the GNSS navigation message issue of data (IOD) changes, so it is difficult to predict when signal loss occurs at that point. In this study, we proposed an algorithm to generate continuous RTS correction information by applying the difference in navigation trajectory according to IOD change. The use of this algorithm can improve the accuracy of RTS prediction at IOD changes. After performing optimization studies to improve RTS prediction performance, the predicted RTS trajectory information was applied to precision positioning (PPP). Compared to the conventional method, the position error is significantly reduced, and the error increase along with the signal loss interval increase is reduced.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.125-138
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• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.396-409
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• 2023

In the field of autonomous vehicles, where high accuracy and reliability are critical, various satellite navigation augmentation systems have been developed to improve system performance. These systems generate correction and integrity information based on measurements and navigation data collected from ground reference stations, enhancing user positioning accuracy. Thus, the performance of the system heavily relies on the deployment and spacing of reference stations. To construct an effective satellite navigation augmentation system, careful consideration must be given to the installation points of reference stations. This paper presents a user positioning performance modeling formula and proposes a method for selecting the installation points of new reference stations. The proposed method involves selecting a candidate group area that can optimize the user's positioning performance. By utilizing this method, the system's performance can be improved, ensuring high accuracy and reliability for autonomous vehicle applications.

• Smart Media Journal
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• v.12 no.4
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• pp.41-46
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• 2023

UWB is a type of technology used for indoor positioning and is characterized by higher accuracy than RSSI-based schemes. Mobile equipment operating based on ROS can monitor the environment around the equipment using lidar and cameras. When applying the loop closing technique to determine the starting position in this monitoring process, the existing method has a problem of low accuracy because the closing operation occurs only when there are feature points on the image. In this paper, to solve this problem, we designed a system that increases the accuracy of loop closing work by providing location information by mounting a UWB tag on a mobile device. In addition, the accuracy of the UWB-based indoor positioning system was evaluated through experiments, and it was verified that it could be used for loop closing techniques.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.418-426
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• 2022

Unlike OSR(observation space representation), the SSR(state space representation) augmentation system is suitable for a one-way broadcasting service because it provides the same corrections to all users in the service area. Due to this advantage, several GNSS(global navigation system) systems such as Galileo, BDS(beidou navigation satellite system), QZSS(quasi zenith satellite system) are establishing PPP (precise point positioning)/PPP-RTK precision positioning services based on SSR messages. Therefore, in this paper, we try to understand the trends of satellite-based PPP/PPP-RTK correction services by analyzing the system configurations, characteristics, and precise positioning performance of satellite-based SSR correction broadcasting services.

• Journal of radiological science and technology
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• v.46 no.6
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• pp.527-533
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• 2023

The purpose of this study is to evaluate the clinical risk of spinal radiosurgery by calculating the dose difference due to dose calculation algorithm and multi-leaf collimator positioning error. The images acquired by the CT simulator were recalculated by correcting the multi-leaf collimator position in the dose verification program created using MATLAB and applying stoichiometric calibration and Monte Carlo algorithm. With multi-leaf collimator positioning error, the clinical target volume (CTV) showed a dose difference of up to 13% in the dose delivered to the 95% volume, while the gross tumor volume (GTV) showed a dose difference of 9%. The average dose delivered to the total volume showed dose variation from -8.9% to 9% and -10.1% to 10.2% for GTV and CTV, respectively. The maximum dose delivered to the total volume of the spinal cord showed a dose difference from -14.2% to 19.6%, and the dose delivered to the 0.35 ㎤ volume showed a dose difference from -15.5% to 19.4%. In future research, automating the linkage between treatment planning systems and dose verification programs would be useful for spinal radiosurgery.