• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.3 s.26
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• pp.211-218
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• 2006

Recently, many ships such as fishing boats, cargo ships, high speed ferry boats are visiting Mokpo harbor. In particular, many marine accidents have been occurred at this area due to the narrow channel, a thick fog, the existing of the shallow waters etc. However there is no suitable ships' routeing system which takes account of today's traffic situations in this area. This study aims at the settling of hazardous factors to mitigate the danger to vessels in Mokpo harbor and to secure the safety of maritime environment.

• Nuclear Engineering and Technology
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• v.41 no.9
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• pp.1135-1142
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• 2009

The activities related to this paper are to investigate the influence of nodalisation on simulating atmospheric stratification in the THAI experiment TH13 (ISP-47) with the German containment code COCOSYS. This article focuses on different nodalisations of the vessel dome, where an atmospheric stratification occurred due to a high helium content. The volume of the dome was divided into several levels that were varied horizontally into different geometries. These geometries differ in the number of zones as well as in the existence of zones that enable the direct rise of an ascending steam plume into the vessel dome. Additionally, the vertical subdivision of the vessel dome was increased to simulate density gradients in a more detailed way. It was pointed out that the proper simulation of atmospheric stratifications and their dissolution depends on both a suitable horizontal as well as vertical nodalisation scheme. Besides, the treatment of fog droplets has an influence if their settlement is not simulated correctly. This report gives an overview of the gained experience and provides nodalisation requirements to simulate atmospheric stratifications and their proper dissolution.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.486-490
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• 2018

Radar Beacons are marine aids that helps the navigators avoid dangers such as dangerous rocks, heavy fog, nighttime, etc. when sailing. The existing antenna was researching on the development of the advanced radar Beacon (Enhanced Radar Beacon) for the improvement of the next generation racon with the AIS (Automatic Identification System) function.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.1
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• pp.16-23
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• 2019

Cooking oil in kitchen-fog is the most harmful factor to the health of a cook. The proposed filter is a tool that protects the cooked state, to prevent users from inhaling oil mist in the kitchen. Due to efficiency issues, existing filters are of the mesh type or baffle type. In this paper, CFD analysis is carried out to select a filter with low pressure loss and low efficiency, and to attach the sub-filter to improve efficiency. The results of the analysis on the collection efficiency and pressure loss of three sub-filters, i.e., circle type, droplet type, and cone type, showed that the collection efficiency was 64.09% and the pressure loss was 1.26 mmAq when the circle type sub-filter was applied. The position of the sub-filter showed the best efficiency and pressure loss when it was located at the bottom of the center of the gap of the main filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2255-2281
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• 2021

Channel characteristic-based physical layer authentication is one potential identity authentication scheme in wireless communication, such as used in a fog computing environment. While existing channel characteristic-based physical layer authentication schemes may be efficient when deployed in the conventional wireless network environment, they may be less efficient and practical for the industrial wireless communication environment due to the varying requirements. We observe that this is a topic that is understudied, and therefore in this paper, we review the constructions and performance of several commonly used test statistics and analyze their performance in typical industrial wireless networks using simulation experiments. The findings from the simulations show a number of limitations in existing channel characteristic-based physical layer authentication schemes. Therefore, we believe that it is a good idea to combine machine learning and multiple test statistics for identity authentication in future industrial wireless network deployment. Four machine learning methods prove that the scheme significantly improves the authentication accuracy and solves the challenge of choosing a threshold.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.33-43
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• 2022

This study presents a method to restore an optical satellite image with distortion and occlusion due to fog, haze, and clouds to one that minimizes degradation factors by referring to the same type of peripheral image. Specifically, the time and cost of re-photographing were reduced by partially occluding a region. To maintain the original image's pixel value as much as possible and to maintain restored and unrestored area continuity, a simulation restoration technique modified with the Cycle Generative Adversarial Network (CycleGAN) method was developed. The accuracy of the simulated image was analyzed by comparing CycleGAN and histogram matching, as well as the pixel value distribution, with the original image. The results show that for Site 1 (out of three sites), the root mean square error and R² of CycleGAN were 169.36 and 0.9917, respectively, showing lower errors than those for histogram matching (170.43 and 0.9896, respectively). Further, comparison of the mean and standard deviation values of images simulated by CycleGAN and histogram matching with the ground truth pixel values confirmed the CycleGAN methodology as being closer to the ground truth value. Even for the histogram distribution of the simulated images, CycleGAN was closer to the ground truth than histogram matching.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.80-88
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• 2022

A systematic experimental study is carried out for the fire fighting monitor nozzle of 65A diameter to design and manufacture a new nozzle with better water spray performance than available domestic nozzles. The nozzle inlet pressure, flow rate and reach for the discharged water from the nozzle are measured by utilizing the experimental facility consisting of two pumps and piping system with a flow meter and pressure gauges. It was found that the baffle position and baffle head chamfering were the most sensitive design factors to be remarkably changed in the flow rate of the discharged water. Also, It was confirmed that the baffle position and the water exit area had the significant effect on the change in reach distance. The results obtained from this study are expected to be used effectively to design new nozzles with excellent spray performances and also to validate numerical analysis results for evaluating the water spray performance of fire fighting monitor nozzles.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.300-306
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• 2022

Currently, Korea is building traffic infrastructure using Intelligent Transport Systems (ITS), but the pedestrian traffic accident rate is very high. The purpose of this paper is to prevent the risk of traffic accidents by jaywalking pedestrians. The development of this study aims to detect pedestrians who trespass using the public data set provided by the Artificial Intelligence Hub (AIHub). The data set uses training data: 673,150 pieces and validation data: 131,385 pieces, and the types include snow, rain, fog, etc., and there is a total of 7 types including passenger cars, small buses, large buses, trucks, large trailers, motorcycles, and pedestrians. has a class format of Learning is carried out using YOLOv5 as an implementation model, and as an object detection and edge detection method of an input image, a canny edge model is applied to classify and visualize human objects within the detected road boundary range. In this study, it was designed and implemented to detect pedestrians using the deep learning-based YOLOv5 model. As the final result, the mAP 0.5 showed a real-time detection rate of 61% and 114.9 fps at 338 epochs using the YOLOv5 model.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1266-1272
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• 2022

With the recent development of computer vision technology, image processing-based mechanical devices are being developed to realize autonomous driving. The camera-taken images of image processing-based machines are invisible due to scattering and absorption of light in foggy conditions. This lowers the object recognition rate and causes malfunction. The safety of the technology is very important because the malfunction of autonomous driving leads to human casualties. In order to increase the stability of the technology, it is necessary to apply an efficient haze removal algorithm to the camera. In the conventional haze removal method, since the haze removal operation is performed regardless of the haze concentration of the input image, excessive haze is removed and the quality of the resulting image is deteriorated. In this paper, we propose an automatic haze removal method that removes haze according to the haze density of the input image by applying Ngo's Haziness Degree Evaluator (HDE) to Kim's haze removal algorithm using Hazy Particle Map. The proposed haze removal method removes the haze according to the haze concentration of the input image, thereby preventing the quality degradation of the input image that does not require haze removal and solving the problem of excessive haze removal. The superiority of the proposed haze removal method is verified through qualitative and quantitative evaluation.