• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.73-80
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• 2021

In this paper, we propose a packet processing method capable of handling large-capacity traffic over 20Gbps using multi-core and huge page memory approaches. As ICT technology advances, the global average monthly traffic is expected to reach 396 exabytes by 2022. With the increase in network traffic, cyber threats are also increasing, increasing the importance of traffic analysis. Traffic analyzed as an existing high-cost foreign product simply stores statistical data and visually shows it. Network administrators introduce and analyze many traffic analysis systems to analyze traffic in various sections, but they cannot check the aggregated traffic of the entire network. In addition, since most of the existing equipment is of the 10Gbps class, it cannot handle the increasing traffic every year at a fast speed. In this paper, as a method of processing large-capacity traffic over 20Gbps, the process of processing raw packets without copying from single-core and basic SMA memory approaches to high-performance packet reception, packet detection, and statistics using multi-core and NUMA memory approaches suggest When using the proposed method, it was confirmed that more than 50% of the traffic was processed compared to the existing equipment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Journal of the Korea Organic Resources Recycling Association
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• v.28 no.4
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• pp.23-33
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• 2020

Marine algae(Macro algae) are easily bio-degradable, and by-products are available as feed and fertilizer. The biomass of marine algae has higher CO2 absorption capacity than the wood system, and is highly valuable in use due to its fast growth speed and wide cultivation area without special cost for raw material production. In 2018, Marine algae production was 1,722,486ton, such as Saccharina japonica, Undaria pinnatifida and Porphyra tenera, the large amounts of by-products have been generated in the food processing facilities for commercialization. In this study, Saccharina japonica, Undaria pinnatifida were collected in the south coast region and Porphyra tenera was collected in the west coast region. The theoretical methane potential and biochemical methane potential(BMP) were analyzed, and Modified Gompertz model and Parallel first order kinetics model were adopted for the interpretation of the cumulative methane production curves. The theoretical methane potential of Saccharina japonica, Undaria pinnatifida and Porphyra tenera were 0.393, 0.373 and 0.435 N㎥/kg-VS, respectively. BMP obtained by the Modified gompertz model 0.226, 0.227, and 0.241 N㎥/kg-VS for Saccharina japonica, Undaria pinnatifida and Porphyra tenera, respectively. And BMP obtained by the Parallel first order kinetics model were 0.220, 0.243, and 0.240 N㎥/kg-VS for Saccharina japonica, Undaria pinnatifida and Porphyra tenera, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.141-148
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• 2021

This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.561-566
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• 2021

Schools are highly feared to spread widely in the event of an infectious disease, and systematic management and prompt response are needed as it can undermine students' health and learning rights. This study was conducted to identify the current status of infectious diseases common to elementary, middle and high school students and to provide basic data to protect students and faculty from the threat of infectious diseases and maintain normal school functions. Sejong City was selected for investigation. The three major infectious diseases are influenza, chickenpox and aquarium, all of which are classified as acute viral infectious diseases and have fast propagation speed and strong propagation power, which can have fatal consequences for students living in groups. The research data were analyzed using the 2019 infectious disease report data from the Education Ministry's Education Administration Information Network (NEIS), and the current status data reported by elementary, middle and high schools nationwide were analyzed. The research method was to compare the current status of infectious diseases across the country and Sejong City, compare the status of issuance by each school level, compare the status of infectious diseases by item, and analyze the status of infectious diseases by time. The results of the survey on the status of the three major infectious diseases are expected to be used as basic data for managing infectious diseases not only in Sejong City but also in the nation, so that they can be used to establish measures to manage student infectious diseases in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.25-36
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• 2021

Hydrogen in hydrogen-electric vehicles has a wide range of combustion and explosion ranges, and is a combustible gas with a very fast flame propagation speed, so it has the risk of leakage, diffusion, ignition, and explosion. The fuel tank has a Thermally active Pressure Relief Device (TPRD) to reduce the risk of explosion and other explosions, and in the event of an accident, hydrogen inside the tank is released outside before an explosion or fire occurs. However, if an accident occurs in a semi-closed space such as an underground parking lot, the flow of air flow is smaller than the open space, which can cause the concentration of hydrogen gas emitted from the TPRD to accumulate above the explosion limit. Therefore, in this study, the leakage rate and concentration of hydrogen over time were analyzed according to the diameter of the nozzle of the TPRD. The diameter of the nozzle was considered to be 1 mm, 2.5 mm and 5 mm, and ccording to the diameter of the nozzle, the concentration of hydrogen in the underground parking lot increases in a faster time with the diameter of the nozzle, and the maximum value is also analyzed to be larger with the diameter of the nozzle. In underground parking lots where air currents are stagnant, hydrogen concentrations above LFL (Lowe Flammability Limit) were analyzed to be distributed around the nozzle, and it was analyzed that they did not exceed UFL (Upper Flammability Limit).

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.437-444
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• 2021

To evaluate the usefulness of Volume Axial Mode by comparing analyzing the exposure dose of the patients and the quality of each images from CT images obtained from high pitch mode using the local phantom or volume axial mode to determine the usefulness of he volume axial mode in diagnosing the head and cervical disease in adults. High Pitch Mode, Helical Mode, and Volume axial Mode as adult phantom were tested according to 70 kVp, 80 kVp, and 100 kVp tube voltages during an adult frontal CT scans. The equipment used was GE's Revolution (GE Healthcare, Wisconsin USA) model and iMED X-ray Phantom. The exposure dose of phantom was compared using the images obtained from each protocol, and the image quality was compared by calculating SNR and CNR by setting ROI on each image. When examined using Volume Axial Mode, the exposure dose of phantom was measured 17.12% lower than Helical Mode, 5.35% lower than High Pitch Mode, and both SNR and CNR were improved. Volume Axial Mode is a useful test that reduces investigation time without table movement using high speed rotary scanner, and in which exposure dose is reduced and image quality is improved by acquiring images in a short time of 0.28 seconds of phantom than using High Pitch Mode and Helical Mode. In addition, the fast testing time of Volume Axial Mode can be seen as the biggest advantage CT scans of emergency patients or patients with physical discomfort.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.21-27
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• 2022

Traditional automobile or 2-wheeled robot have limitations on mobility because of their mechanical structure. As traditional automobile is being replaced by electric cars, robot technology is applied to the car industry. In robotics, many researchers worked on omnidirectional mobile robot and produced lots of noticeable results. However in many of the results, specialized wheels such as Mecanum wheels are required. That imposes restrictions on robot speed and outdoor driving. We proposed a 2-wheeled modular robot that has omnidirectional mobility without using specialized wheels. In this paper, we propose a 4-wheeled omnidirectional mobile robot that consists of those two modular robots. The proposed robot adopts electric brakes to combine wheel housings and the robot body or to separate wheel housings from the robot body. Two absolute-type encoders and four incremental encoders are used to control the position of the wheel housing and velocities of the wheels. The proposed robot has omnidirectional mobility and can move fast and outdoor with normal tire wheels. We implemented the proposed robot and the feasibility and stability of the robot is verified by two separate experiments.