• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.33-41
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• 2013

Intelligent automobile technology and IT convergence, the development of new imaging technology media applications based on open source Android installed on tracked, wheeled smart phone application technology and the development of intelligent vehicles as a new paradigm a lot of research and development being made. Android-based intelligent automotive applications, technology, and evolved into the center of a set of various multimedia technologies move beyond the limits of the means of each of multimedia platforms, services and applications that have been developed in such a distributed environment, has been developed according to a variety of services through technology mobile terminal device technology is an absolute requirement. In this paper, SVC Codec, real-time video and graphics processing and SoC design intelligent vehicles middleware applications with monolithic system specification through Android-based design of intelligent vehicles dedicated middleware research experiments on open platforms, and provides various terminal services functions SoC based on a newly designed and standardized interface analysis techniques in this study were verified through experiments.

• Journal of the Korean Orthopaedic Association
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• v.53 no.6
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• pp.459-465
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• 2018

Of the many factors that affect the clinical outcomes of orthopedic surgery, the surgical procedure is the most important. Robotics have been developed to perform the surgical procedures more accurately and consistently. Robotic surgical procedures in the orthopedic field were developed 20 years ago. Some designs of surgical robots have disappeared due to practical problems and complications, and an another design of surgical robots is emerging. To date, the use of robot surgery in arthroplasty is still controversial in terms of the clinical outcomes, practicality, and cost-effectiveness, even though it has been reported to be effective in the alignment and positioning of components in the field of artificial joints. Early robotic surgery was based mainly on active robot surgery according to the scheduled operation without the intervention of the operator. Recently the semi-active system of robotic surgery has been introduced. In a semi-active system, the robot constrains the surgeon to a haptic boundary defined by the computer based on the 3-dimensional imaging preoperative plan, and the operator can change the preoperative plan through real-time feedback during operation.

• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.65-72
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• 2018

The uses of unmanned aerial vehicles (UAV) have been expanding in agriculture surveys, obtaining real time updates of dangerous facilities where human access is difficult, disaster monitoring, and 3D modeling. In reality, there is an upsurge in the application of UAVs in fields like, construction, infrastructure, imaging, surveying, surveillance and transportation. Especially, when the slope failure such as landslide occurs, the uses of UAVs are increasing. Since, the UAVs can fly in three dimensions, they are able to obtain spatial data in places where human access is nearly impossible. Despite of these advantages, however, the uses of UAVs are still limited during slope failure. In order to overcome these limitations, this study computes the soil volume change during slope failure through the computation technique using photogrammetric information obtained from UAV system. Through this study, it was found that photogrammetric information from UAV can be used to acquire information on amount of earthworks required for repair works when slope collapse occurs in mountainous areas, where human access in difficult.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.195-201
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• 2020

This study studied scoliosis, one of the most common modern diseases caused by lifestyle patterns of office workers sitting in front of computers all day and modern people who use smart phones frequently. Scoliosis is a typical complication that takes more than 80% of the nation's total population at least once. X-ray are used to test for these complications. X-ray, a non-destructive testing method that allows scoliosis to be easily performed and filmed in various areas such as the chest, abdomen and bone without contrast agents or other instruments. We uses NI DAQ to miniaturize digital X-ray imaging devices and image intensifier in self-shielding housing with Vision Assistant for drawing lines to the top and the bottom of the spine to acquire angles, i.e. curvature in real-time. In this way, the research was conducted to see scoliosis patients and their condition easily and to help rapid treatment for solving the problem of posture correction in modern people.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1519-1527
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• 2020

AGeneral radiation measuring devices have been developed in the form of spatial dose rate detection devices that measure dose rates to radioactive contaminant and 2D or 3D imaging devices for radioactive contamination information. Each of these radiation detection techniques has advantages. The advantages of both detection devices are necessary to minimize personal injury and rapid decontamination in the area of a radioactive accident. In this paper, we proposed a technique that can measure the dose rate and direction information about the radioactive pollutant source in real time using a detection sensor, a rotating body, and a directional shield for radioactive pollutant detection. The rotational-based detection device is configured to check the dose rate and direction using the location information of the rotator and measurement value. We proposed a measurement technique for vertical and horizontal directions through multiple holes. It was confirmed that the measurement error for direction information was less than 1% when detected in the horizontal direction.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.547-554
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• 2022

Recently, the field of telemedicine is growing rapidly due to the COVID-19 pandemic. However, the cost of telemedicine services is relatively high, since cloud computing, video conferencing, and cyber security should be considered. Therefore, in this paper, we design and implement a cost-effective P2P-based telemedicine system. It is implemented using the widely used the open source computing platform, Raspberry Pi, and P2P network that frees users from security problems such as the privacy leakage by the central server and DDoS attacks resulting from the server/client architecture and enables trustworthy identifying connection system using SSL protocol. Also it enables users to check the other party's status including body temperature in real time by installing a thermal imaging camera using Raspberry Pi. This allows several medical diagnoses that requires visual aids. The proposed telemedicine system will popularize telemedicine service and meet the ever-increasing demand for telemedicine.

• Fisheries and Aquatic Sciences
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• v.26 no.3
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• pp.188-203
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• 2023

Lysozymes are well-known antibacterial enzymes that mainly target the peptidoglycan layer of the bacterial cell wall. Animal lysozymes are mainly categorized as g-type, c-type, and i-type based on protein sequence and structural differences. In this study, c-type (AcLysC) and g-like-type (AcLysG-like) lysozymes from Amphiprion clarkii were characterized in silico via expressional and functional approaches. According to in silico analysis, open reading frames of AcLysC and AcLysG-like were 429 bp and 570 bp, respectively, encoding the corresponding polypeptide chains with 142 and 189 amino acids. Elevated expression levels of AcLysC and AcLysG-like were observed in the liver and the heart tissues, respectively, as evidenced by quantitative real-time polymerase chain reaction assays. AcLysC and AcLysG-like transcript levels were upregulated in gills, head kidney, and blood cells following experimental immune stimulation. Recombinant AcLysC exhibited potent lytic activity against Vibrio anguillarum, whereas recombinant AcLysG-like showed remarkable antibacterial activity against Vibrio harveyi and Streptococcus parauberis, which was further evidenced by scanning electron microscopic imaging of destructed bacterial cell walls. The findings of this study collectively suggest the potential roles of AcLysC and AcLysG-like in host immune defense.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.41.2-41.2
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• 2021

In this study, we generate He I 1083 nm images from Solar Dynamic Observatory (SDO)/Atmospheric Imaging Assembly (AIA) images using a novel deep learning method (pix2pixHD) based on conditional Generative Adversarial Networks (cGAN). He I 1083 nm images from National Solar Observatory (NSO)/Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used as target data. We make three models: single input SDO/AIA 19.3 nm image for Model I, single input 30.4 nm image for Model II, and double input (19.3 and 30.4 nm) images for Model III. We use data from 2010 October to 2015 July except for June and December for training and the remaining one for test. Major results of our study are as follows. First, the models successfully generate He I 1083 nm images with high correlations. Second, the model with two input images shows better results than those with one input image in terms of metrics such as correlation coefficient (CC) and root mean squared error (RMSE). CC and RMSE between real and AI-generated ones for the model III with 4 by 4 binnings are 0.84 and 11.80, respectively. Third, AI-generated images show well observational features such as active regions, filaments, and coronal holes. This work is meaningful in that our model can produce He I 1083 nm images with higher cadence without data gaps, which would be useful for studying the time evolution of chromosphere and coronal holes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.120-122
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• 2021

Currently, as demand for cars at home and abroad increases, the number of vehicles is decreasing and the number of vehicles is increasing. This is the main cause of the traffic jam. To solve this problem, it operates a high-ocompancy vehicle (HOV) lane, a multi-passenger vehicle, but many people ignore the conditions of use and use it illegally. Since the police visually judge and crack down on such illegal activities, the accuracy of the crackdown is low and inefficient. In this paper, we propose a system design that enables more efficient detection using imaging techniques using computer vision to solve such problems. By improving the existing vehicle detection method that was studied, the trigger was set in the image so that the detection object can be selected and the image analysis can be conducted intensively on the target. Using the YOLO model, a deep learning object recognition model, we propose a method to utilize the shift amount of the center point rather than judging by the bounding box in the image to obtain real-time object detection and accurate signals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.474-477
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• 2021

Recently, in order to prevent the proliferation of COVID-19, which began in earnest in 2020, an increasing number of places have been measuring the temperature and required to wear a mask. However, as wearing a mask and checking the temperature are typically measured directly by a person or by a single individual positioned in front of the machine, standards may vary based on the person's manual measurement method, wasting workforce. While standing in front of a device often measures the maximum temperature of the face, the standard of fever is also unclear. Both approaches can create bottleneck situations when checking large numbers of people. Furthermore, it is unable to conduct periodic measurements and tracking because the measuring machines are generally put only at the entrance. Thus, this study suggests a method for preventing the spread of infectious diseases by automatically identifying and displaying unmasked people and those with fever in real-time using a general camera, a thermal imaging camera, and an artificial intelligence algorithm.