• Journal of IKEEE
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• v.25 no.2
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• pp.243-251
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• 2021

In this paper, we propose a measurement technique of indoor location based on markerless applicable to AR. The proposed technique has the following originality. The first is to extract feature points and use them to generate local patches to enable faster computation by learning and using only local patches that are more useful than the surroundings without learning the entire image. Second, learning is performed through deep learning using the convolution neural network structure to improve accuracy by reducing the error rate. Third, unlike the existing feature point matching technique, it enables indoor location measurement including left and right movement. Fourth, since the indoor location is newly measured every frame, errors occurring in the front side during movement are prevented from accumulating. Therefore, it has the advantage that the error between the final arrival point and the predicted indoor location does not increase even if the moving distance increases. As a result of the experiment conducted to evaluate the time required and accuracy of the measurement technique of indoor location based on markerless applicable to AR proposed in this paper, the difference between the actual indoor location and the measured indoor location is an average of 12.8cm and a maximum of 21.2cm. As measured, the indoor location measurement accuracy was better than that of the existing IEEE paper. In addition, it was determined that it was possible to measure the user's indoor location in real time by displaying the measured result at 20 frames per second.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.62-72
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• 2022

In this study, a miniaturized GPS band(L₁ : 1.575 GHz) antenna that can be mounted on a small drone is proposed. The miniaturization was designed by applying the perturbation method based on the λ/4 microstrip antenna and lengthening the current path at the edge of the patch. The miniaturized antenna was fabricatred such that it could be attached to the surface of styrofoam(ε_r=1.06, t=10 mm) having a size of 10 mm × 9 mm × 10 mm (0.05 λ × 0.05 λ × 0.05 λ). The thickness and length of the feeding line and the spacing between short stubs were adjusted for impedance matching. S₁₁ was found to be -18.8 dB at the center frequency of the fabricated antenna, 1.575 GHz. The radiation pattern measurement results show that the maximum gain of E_θ is 1.87 dBi in 0 directions in the xz-plane, and that E_θ is an omnidirectional characteristic with an average gain of -1.7 dBi in the yz-plane. It was found that the antenna can be used as an ultra-small microstrip antenna, which can be mounted on a small dron for GPS, and is capable of preserving a reduction ratio of 98.8% as compared to a λ/2 microstrip patch antenna.

• Radiation Oncology Journal
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• v.17 no.1
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• pp.84-88
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• 1999

Purpose :To develop a method for verifying a treatment setup in stereotactic radiotherapy by ma- tching portal images to DRRs. Materials and Methods : Four pairs of orthogonal portal images of one patient immobilized by a thermoplastic mask frame for fractionated stereotactic radiotherapy were compared with DRRs. Portal images are obtained in AP (anteriorfposterior) and lateral directions with a target localizer box containing fiducial markers attached to a stereotactic frame. DRRs superimposed over a planned iso-center and fiducial markers are printed out on transparent films. And then, they were overlaid over onhogonal penal images by matching anatomical structures. From three different kind of objects (isgcenter, fiducial markers, anatomical structure) on DRRs and portal images, the displacement error between anatomical structure and isocenters (overall setup error), the displacement error between anatomical structure and fiducial markers (irnrnobiliBation error), and the displacement error between fiducial markers and isocenters (localization error) were measured. Results : Localization error were 1.5$\pm$0.3 mm (AP), 0.9$\pm$0.3 mm (lateral), and immobilization errors were 1.9$\pm$0.5 mm (AP), 1.9$\pm$0.4 mm (lateral). In addition, overall setup errors were 1.0$\pm$0.9 mm (AP), 1.3$\pm$0.4 mm (lateral). From these orthogonal displacement errors, maximum 3D displacement errors($\sqrt{(\DeltaAP)^{2}+(\DeltaLat)^{2}$)) were found to be 1.7$\pm$0.4 mm for localization, 2.0$\pm$0.6 mm for immobilization, and 2.3$\pm$0.7 mm for overall treatment setup. Conclusion : By comparing orthogonal portal images with DRRs, we find out that it is possible to verify treatment setup directly in stereotactic radiotherapy.

• Progress in Medical Physics
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• v.22 no.3
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• pp.107-116
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• 2011

Respiratory gated radiation therapy and stereotactic body radiation therapy require identical tumor motions during each treatment with the motion detected in treatment planning CT. Therefore, this study developed a tumor motion monitoring and analysis system during the treatments employing RPM data, gated setup OBI images and a data analysis software. A respiratory training and guiding program which improves the regularity of breathing was used to patients. The breathing signal was obtained by RPM and the recorded data in the 4D console was read after treatment. The setup OBI images obtained gated at 0% and 50% of breathing phases were used to detect the tumor motion range in crenio-caudal direction. By matching the RPM data recorded at the OBI imaging time, a factor which converts the RPM motion to the tumor motion was computed. RPM data was entered to the institute developed data analysis software and the maximum, minimum, average of the breathing motion as well as the standard deviation of motion amplitude and period was computed. The computed result is exported in an excel file. The conversion factor was applied to the analyzed data to estimate the tumor motion. The accuracy of the developed method was tested by using a moving phantom, and the efficacy was evaluated for 10 stereotactic body radiation therapy patients. For the sine wave motion of the phantom with 4 sec of period and 2 cm of peak-to-peak amplitude, the measurement was slightly larger (4.052 sec) and the amplitude was smaller (1.952 cm). For patient treatment, one patient was evaluated not to qualified to SBRT due to the usability of the breathing, and in one patient case, the treatment was changed to respiratory gated treatment due the larger motion range of the tumor than treatment planed motion. The developed method and data analysis program was useful to estimate the tumor motion during treatment.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.