• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.144-153
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• 2024

Recent research is increasingly focused on utilizing seismic waves for structure health monitoring (SHM). Specifically, seismic interferometry, a technique applied in geophysical surveys using ambient noise, is widely applied in SHM. This method involves analyzing the response of buildings to propagating seismic waves. This enables the estimation of changes in structural stiffness and the evaluation of the location and presence of damage. Analysis of seismic interferometry applied to SHM, along with case studies, indicates its highly effective application for assessing structural stability and monitoring building conditions. Seismic interferometry is thus recognized as an efficient approach for evaluating building integrity and damage detection in SHM and monitoring applications.

• Journal of Radiation Industry
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• v.18 no.2
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• pp.117-126
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• 2024

This study aims to identify high exposure tasks among the tasks performed in domestic nuclear power plants as a basis for developing training programs to improve the efficiency of workers' work. To this end, we first analyzed the exposure status of radiation work in domestic nuclear power plants. Radiation tasks in nuclear power plants were categorized, collective doses were investigated, and the collective doses were calculated based on the collective doses, and representative high exposure tasks were identified. We found that the collective and individual doses in domestic nuclear power plants are continuously decreasing, but there is an imbalance of exposure among workers. In terms of work classification, nuclear power plants are managed in 236 work codes based on light water reactors and 181 work codes based on heavy water reactors, depending on the work equipment and location. Among the total work codes, 23 codes have an annual average dose exceeding 10 μSv, and based on this, 10 representative high exposure tasks were derived. The representative high exposure tasks were selected as S/G nozzle dam work, S/G debris removal work, nuclear instrumentation system, S/G eddy current detection work, and insulation work. The results of this study are expected to serve as an important basis for reducing the exposure of workers in nuclear power plants and improving work efficiency.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.5
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• pp.535-543
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• 2024

Studies on estimating the underwater sound source localization using acoustic signal characteristics have mainly been conducted in shallow waters. Recently, technologies for stably and efficiently estimating the underwater sound sources localization using the underwater sound propagation characteristics of the Reliable Acoustic Path(RAP) in deep water areas are being studied. Underwater surveillance technology in deep sea areas is known to have the advantage of having low detection performance variability due to time-varying underwater environments and having a small shadow zone, making it easy to stably detect underwater sound sources and estimate location even from relatively long distance. In this study, we analyzed the sound propagation characteristics based on the actual marine environment in the deep sea of the Korean Peninsula and conducted a study to analyze the estimation performance of sound source depth using the broadband interference pattern of direct wave and sea surface reflected waves radiating from underwater sound sources.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.26 no.2
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• pp.216-222
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• 2024

Dissecting posterior inferior cerebellar artery (PICA) aneurysms are uncommon lesions. Their anatomy and the location of the dissection are variable, however, they usually occurs at the origin of the PICA. Dissecting PICA aneurysms generally have non-vascular morphology involving an entire segment of the artery and cannot be cut. Nevertheless, the detection of these vascular lesions has increased latterly, so it is necessary to recognize it and take the appropriate management modalities for these injuries. In this report, we describe a case of a 73-year-old male patient, who presented a history of severe headache, associated with neck stiffness, nausea, vomiting, dizziness, hypoactivity, mental confusion, and walking difficulty. Radiographic investigation with brain computed tomography (CT) showed mild bleeding in a pre-medullary and pre-pontine cistern, and cerebral angiogram showed a dissecting PICA aneurysm. Despite being a challenging treatment, microsurgery management was the chosen modality. It was performed an end-to-end anastomosis between the p2/p3 segments, showing to be effective with good clinical and radiographic outcomes. We discussed an unusual case, reviewing the current literature on clinical presentations, the angiographic characteristics of the dissecting aneurysms of PICA, and evaluating the clinical and angiographic results of patients undergoing microsurgical treatment.

• Journal of the Health Care and Life Science
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• v.9 no.2
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• pp.297-302
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• 2021

As the price of LiDAR developed for autonomous driving has dropped dramatically, LiDAR has begun to be applied in various fields. Typical examples are vacuum cleaner robots, autonomous delivery robots, and autonomous obstacle avoidance drones. LiDAR is becoming the only means of figuring out the location of an object in real time while compensating for the weakness that 2D or 3D cameras are vulnerable to lighting. In this paper, we propose a method to monitor the movement of a patient by installing a 2D lidar in a hospital room. When a patient who needs intensive monitoring due to psychologically unstable, suicidal intention, or psychotic findings is alone in the ward, 2D LiDAR monitors the patient's movement and sends an appropriate alarm to the management room to effectively monitor the patient. devised a way to do it.

• Journal of Web Engineering
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• v.21 no.3
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• pp.729-750
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• 2022

In general, the importance of 6DoF (degree of freedom) 3D (dimension) volumetric contents technology is emerging in 5G (generation) telepresence service, Web-based (WebGL) graphics, computer vision, robotics, and next-generation augmented reality. Since it is possible to acquire RGB images and depth images in real-time through depth sensors that use various depth acquisition methods such as time of flight (ToF) and lidar, many changes have been made in object detection, tracking, and recognition research. In this paper, we propose a method to improve the quality of 3D models for 5G telepresence by processing images acquired through depth and RGB cameras on a multi-view camera system. In this paper, the quality is improved in two major ways. The first concerns the shape of the 3D model. A method of removing noise outside the object by applying a mask obtained from a color image and a combined filtering operation to obtain the difference in depth information between pixels inside the object were proposed. Second, we propose an illumination compensation method for images acquired through a multi-view camera system for photo-realistic 3D model generation. It is assumed that the three-dimensional volumetric shooting is done indoors, and the location and intensity of illumination according to time are constant. Since the multi-view camera uses a total of 8 pairs and converges toward the center of space, the intensity and angle of light incident on each camera are different even if the illumination is constant. Therefore, all cameras take a color correction chart and use a color optimization function to obtain a color conversion matrix that defines the relationship between the eight acquired images. Using this, the image input from all cameras is corrected based on the color correction chart. It was confirmed that the quality of the 3D model could be improved by effectively removing noise due to the proposed method when acquiring images of a 3D volumetric object using eight cameras. It has been experimentally proven that the color difference between images is reduced.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.21-30
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• 2014

Lately, new influentials have secured a large number of volunteers on social networks due to vitalization of various social media. There has been considerable research on these influential people in social networks but the research has limitations on location information of Location Based Social Network Service(LBSNS). Therefore, the purpose of this study is to propose a spatial detection methodology and application plan for influentials who make comments about diverse social and cultural issues in LBSNS using spatial statistical analysis methods. Twitter was used to collect analysis object data and 168,040 Twitter messages were collected in Seoul over a month-long period. In addition, 'politics,' 'economy,' and 'IT' were set as categories and hot issue keywords as given categories. Therefore, it was possible to come up with an exposure index for searching influentials in respect to hot issue keywords, and exposure index by administrative units of Seoul was calculated through a spatial joint operation. Moreover, an influential index that considers the spatial dependence of the exposure index was drawn to extract information on the influential areas at the top 5% of the influential index and analyze the spatial distribution characteristics and spatial correlation. The experimental results demonstrated that spatial correlation coefficient was relatively high at more than 0.3 in same categories, and correlation coefficient between politics category and economy category was also more than 0.3. On the other hand, correlation coefficient between politics category and IT category was very low at 0.18, and between economy category and IT category was also very weak at 0.15. This study has a significance for materialization of influentials from spatial information perspective, and can be usefully utilized in the field of gCRM in the future.

• Atmosphere
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• v.20 no.4
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• pp.467-482
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• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.