• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1319-1325
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• 2021

It is important to remove fog for accurate object recognition and detection during preprocessing because images taken in foggy adverse weather suffer from poor quality of images due to scattering and absorption of light, resulting in poor performance of various vision-based applications. This paper proposes an end-to-end deep learning-based single image de-fogging method using U-Net architecture. The loss function used in the algorithm is a loss function based on Mahalanobis distance with fog features, which solves the problem of domain shifts, and demonstrates superior performance by comparing qualitative and quantitative numerical evaluations with conventional methods. We also design it to generate fog through the VGG19 loss function and use it as the next training dataset.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.233-239
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• 2022

Recently, research is being conducted on the rapid service provision and reliability of the instance-based rather than the existing IP-based structure. Research is mainly conducted through Block cloud, a platform that combines service-centric networking (SCN) and blockchain. In addition, the Internet of Things network has been proposed as a fog computing environment in the structure of the existing cloud computing. Fog computing is an environment suitable for real-time information processing. In this paper, we propose a new Internet network structure based on fog computing that requires real-time for rapid processing of IoT services. The proposed system applies IoTA, the third-generation blockchain based on DAG, to the block cloud. In addition, we want to propose a basic model of the object block chain and check the application services of electric vehicles.

• Journal of Navigation and Port Research
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• v.29 no.6 s.102
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• pp.583-588
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• 2005

It is known that the cold water appears and fog frequently forms in the southwest coastal waters of Korea in summer. The authors investigate and analyze the time and place of cold water existence, and also whether the cold water affects the occurrence of fog formation. As a result, cold water begins to appear around Daeheugsando at the early summer and cold water area gradually moves toward southwest of Jindo in end July${\~}$early August, then disappears in this area around mid-Oct. Fog mostly forms in April through August and most frequently occurs at Jindo where sea surface temperature shows lower than that at the adjacent area Accordingly it is taken that the cold water considerably contributes to form the dense and frequent fog around Jindo area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2355-2362
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• 2016

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior - dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.65-76
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• 2018

This study aims to evaluate the legibility distances of variable speed limit sign(VSL) for different sizes, luminances, and fog conditions through a field experiment. For this, extensive fog simulated environment has been constructed, and legibility distances are tested and recorded among test subjects for different luminances and sizes of VSL in control. Results showed that legibility distance increased as the size of VSL increased in the given illumination conditions, but it was not an exact linear trend. The size was also an important factor for determining legibility distance as the fog density increased, especially heavy fog conditions. In addition, the legibility distance also increased as the given illumination levels of VSL improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.576-578
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• 2015

This paper propose the help of the secure a clear view and safe navigation of the coastal ship through the sea-fog removal algorithm. Interest in marine accidents and vessel safety has increased in recent Sewol ferry event. According to statistics coastal ship cause of the marine accident when sea fog on the sea did not secure clear view the ship's occur several incidents of collisions between ships and can see that accounts for a high percentage. Algorithm for image exist sea fog is number of studies. but, such studies take up a lot of calculation quantity in the course of performing the algorithm. In this paper, we improve the computational speed of sea fog over the GPU-based technique was removed to suit real-time video. Furthermore, by using GPU, we succeeded in accelerating the simulation 250 times.

• Journal of Bio-Environment Control
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• v.11 no.2
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• pp.93-100
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• 2002

This study was carried out not only to develop CFD model for numerically simulating fog cooling system but also to verify the validity of the developed model by data measured in fag cooling greenhouse. In addition the developed model was applied to investigate the effects of spraying water temperature, spraying water amount, spraying interval and evaporation percentage on the performance of the fog cooling system. According to the simulation results, the temperature differences between the measured and predicted temperatures at each measurement point were $0.1~1.4^{\circ}C$ in case of no shading and $0.2~2.3^{\circ}C$ in close of shading. The humidity differences were 0.3~6.0% and 0.7~10.6%, respectively in the cases of no shading and shading. Because the predicted data showed a good agreement with the measured ones, the developed model is supposed to be able to predict the cooling effect of the fog cooling system. The performance of fog cooling system was greatly influenced by spraying water amount, spraying interval and evaporation percentage, but it was not influenced by spraying water temperature.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.92-106
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• 2017

The adverse weather is known as a factor that interrupts traffic flow and causes traffic accidents and traffic congestion by lowering visibility of drivers. Especially, in case of fog unlike any other weather conditions, traffic accidents lead to serious accidents and the fatality of the accidents is known to be high. This paper aims to analyze uninterrupted traffic flow characteristics under foggy conditions among adverse weathers. The traffic volumes and speeds under foggy and normal conditions were analyzed. Results indicated that fog with low visibility causes the most insignificant reduction in traffic volumes. On the other hand, the reduction in the speeds due to low visibility was evident. In addition, the relationship between flow, speed, and density in fog were analyzed. Analysis results showed that the fog with less than 200m visibility had clear impact on traffic flow.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.294-296
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• 2017

Cloud computing is a computing technique that uploads all the data from a cloud node to a cloud server and provides it to users as a service. This is difficult to provide services in real time depending on the network conditions. This is because it is necessary to download information to the remote site through the network, not the local area, and to download additional services to provide services in the cloud. So fog computing has been proposed as an alternative. In this paper, we propose an efficient data exchange technique between cloud, fog and user. The proposed fog provides services to users and collects and processes data. The cloud is responsible for the flow of data exchange and control between the fog. We propose a standard method for data exchange. The application for this is to process and service the information generated by the BAN (Body Area Network) in the fog, and the cloud serves as a mediator. This can resolve data heterogeneity between devices or services and provide efficient data movement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.