• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.491-500
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• 2021

In this study, we propose a method for detecting fall behavior using MS Kinect v2 RGBD Camera-based Human-Skeleton Keypoints and a 2-Stacked Bi-LSTM model. In previous studies, skeletal information was extracted from RGB images using a deep learning model such as OpenPose, and then recognition was performed using a recurrent neural network model such as LSTM and GRU. The proposed method receives skeletal information directly from the camera, extracts 2 time-series features of acceleration and distance, and then recognizes the fall behavior using the 2-Stacked Bi-LSTM model. The central joint was obtained for the major skeletons such as the shoulder, spine, and pelvis, and the movement acceleration and distance from the floor were proposed as features of the central joint. The extracted features were compared with models such as Stacked LSTM and Bi-LSTM, and improved detection performance compared to existing studies such as GRU and LSTM was demonstrated through experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.55-61
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• 2020

Getting on and off an elevator is one of the most important parts for multi-floor navigation of a mobile robot. In this study, we proposed the method for the pose recognition of elevator doors, safe path planning, and motion estimation of a robot using RGB-D sensors in order to safely get on and off the elevator. The accurate pose of the elevator doors is recognized using a particle filter algorithm. After the elevator door is open, the robot builds an occupancy grid map including the internal environments of the elevator to generate a safe path. The safe path prevents collision with obstacles in the elevator. While the robot gets on and off the elevator, the robot uses the optical flow algorithm of the floor image to detect the state that the robot cannot move due to an elevator door sill. The experimental results in various experiments show that the proposed method enables the robot to get on and off the elevator safely.

• Journal of The Korean Astronomical Society
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• v.50 no.3
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• pp.51-59
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• 2017

The presence of blue stragglers pose challenges to standard stellar evolution theory, in the sense that explaining their presence demands a complex interplay between stellar evolution and cluster dynamics. In the meantime, mass transfer in binary systems and stellar collisions are widely studied as a blue straggler formation channel. We explore properties of the Galactic open clusters where blue stragglers are found, in attempting to estimate the relative importance of these two favored processes, by comparing them with those resulting from open clusters in which blue stragglers are absent as of now. Unlike previous studies which require a sophisticated process in understanding the implication of the results, this approach is straightforward and has resulted in a supplementary supporting evidence for the current view on the blue straggler formation mechanism. Our main findings are as follows: (1) Open clusters in which blue stragglers are present have a broader distribution with respect to the Z-axis pointing towards the North Galactic Pole than those in which blue stragglers are absent. The probability that two distributions with respect to the Z-axis are drawn from the same distribution is 0.2%. (2) Average values of $log_10(t)$ of the clusters with blue stragglers and those without blue stragglers are $8.58{\pm}0.232$ and $7.52{\pm}0.285$, respectively. (3) The clusters with blue stragglers tend to be relatively redder than the others, and are distributed broader in colors. (4) The clusters with blue stragglers are likely brighter than those without blue stragglers. (5) Finally, blue stragglers seem to form in condensed clusters rather than simply dense clusters. Hence, we conclude that mass transfer in binaries seems to be a relatively important physical mechanism of the generation of blue stragglers in open clusters, provided they are sufficiently old.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.44-49
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• 2015

When the scene has less texture or when camera pose largely changes, the existing texture-based feature tracking methods are not reliable. Topology-based feature description methods, which use the geometric relationship between features such as LLAH, is a good alternative. However, they require feature detection methods with high performance. As a basic study on developing an effective feature detection method for topology-based feature description, this paper aims at examining their applicability to topology-based feature description by analyzing the repeatability of several feature detection methods that are included in the OpenCV library. Experimental results show that FAST outperforms the others.

• Bulletin of the Korean Chemical Society
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• v.30 no.8
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• pp.1783-1792
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• 2009

Although overlapping resonances have been studied extensively in conventional resonance theories, there have not been many studies on them in multichannel quantum defect theories (MQDT). In MQDT, overlapping resonances occur between the channels instead of states, which pose far greater difficulty. Their systematic treatment was obtained for cases involving degenerate closed channels by applying our previous theory, which decouples background scattering from the resonance scattering in the MQDT formulation. The use of mathematical theory on con-diagonalization and con-similarity was essential for handling the non-Hermitian symmetric complex matrix. Overlapping resonances in rare gas spectra of Ar, Kr and Xe were analyzed using this theory and the results were compared with the ones of the previous alternative parameterizations of MQDT which make the open-open part $K^{oo}$ and closed-closed part $K^{cc}$ of reactance submatrices zero. The comparison revealed that separation of background and resonance scatterings achieved in our formulation in a systematic way was not achieved in the representation of $K^{oo}\;=\;0\;and\;K^{cc}$ = 0 when overlapping resonances are present.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.79-86
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• 2019

This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.342-345
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• 2020

Some types of spinal dysraphism can be accompanied by extraspinal cysts, including myelomeningocele, myelocystocele, myelocele, meningocele, limited dorsal myeloschisis, lipomyelomeningocele, and terminal myelocystocele. Each disease is classified according to the developmental mechanism, embryologic process, site of occurrence, or internal structure of the extraspinal cyst. In most cystic spinal dysraphisms except meningocele, part of the spinal cord is attached to the cyst dome. Most open spinal dysraphisms pose a risk of infection and require urgent surgical intervention, but when the cyst is accompanied by closed spinal dysraphism, the timing of surgery may vary. However, if the extraspinal cyst grows, it aggravates tethering by pulling the tip of the cord, which is attached to the dome of the cyst. This causes neurological deficits, so urgent surgery is required to release the tethered cord.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.114-124
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• 2019

The Internet was designed for machines, not humans, and hence, nobody owns a digital identity. Instead, a digital identity is rented from a website and an application. This lack of unique and secure digital identities has resulted in confusion in the online/cyber world. Digital identities pose one of the oldest and most difficult problems with regard to the Internet. There is still no way to use digital credentials to prove, own, and control an online identity, namely a self-sovereign identity, in the same manner we do in the offline world, particularly without a trusted third party. This article discusses the current open standards for digital identities, proposes solutions pertaining to digital identities in the future, and introduces the concept of a blockchain-based self-sovereign digital identity without the need of trusted third parties.