• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.1 s.20
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• pp.1-7
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• 2004

RADARSAT is one of many possible data sources that can play an important role in marine surveillance including ship detection because radar sensors have the two primary advantages: all-weather and day or night imaging. However, atmospheric effects on SAR imaging can not be bypassed and any remote sensing image has various geometric distortions, In this study, radiometric and geometric calibrations for RADARSAT/SAT data are tried using SGX products georeferenced as level 1. Even comparison of the near vs. far range sections of the same images requires such calibration Radiometric calibration is performed by compensating for effects of local illuminated area and incidence angle on the local backscatter, Conversion method of the pixel DNs to beta nought and sigma nought is also investigated. Finally, automatic geometric calibration based on the 4 pixels from the header file is compared to a marine chart. The errors for latitude and longitude directions are 300m and 260m, respectively. It can be concluded that the error extent is acceptable for an application to open sea and can be calibrated using a ground control point.

• Korean Journal of Materials Research
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• v.32 no.8
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• pp.345-353
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• 2022

In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO₄ nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.04a
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• pp.135-138
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• 2010

IMO adopt the revision of SOLAS convention on requirement systems for ECDIS and considered an ECDIS as the major system for E-Navigation strategy on marine transportation safety and environment protection. ENC(Electronic Navigational Chart) as base map of ECDIS is considered as a principal information infrastructure that is essential for navigation tasks. But ENCs are not easy to utilize because they are encoded according to ISO/IEC 8211 file format, and ENCs is required to utilize in parts of Marine GIS and various marine application because they are used for navigational purpose mainly. Meanwhile Google earth is satellite map that Google company service, is utilized in all kinds of industry generally providing local information including satellite image, map, topography, 3D building information, etc. In this paper, we developed KML conversion technology for ENC application. details of development contents consist of ENC loading module and KML conversion module. Also, we applied this conversion technology to Korea ENC and evaluated the results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.597-606
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• 2020

Because the USV(Unmanned Surface Vehicle) is capable of remote control or autonomous navigation at sea, it can secure the superiority of combat power while minimizing human losses in a future combat environment. To plan the technology for the development of USV, the trend analysis of related technology and the selection of promising technology should be preceded, but there has been little research in this area. The purpose of this paper was to measure and evaluate the technology trends quantitatively. For this purpose, this study analyzed the technology trends and selected promising/declining technologies using topic modeling of papers and patent data. As a result of topic modeling, promising technologies include control and navigation, verification/validation, autonomous level, mission module, and application technology, and declining technologies include underwater communication and image processing technology. This study also identified new technology areas that were not included in the existing technology classification, e.g., technology related to research and development of USV, artificial intelligence, launch/recovery, and operation, such as cooperation with manned and unmanned systems. The technology trends and new technology areas identified through this study may be used to derive key technologies related to the development of the USV and establish appropriate R&D policies.

• Journal of Science and Technology Studies
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• v.14 no.2
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• pp.199-222
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• 2014

Functional Magnetic Resonance Angiography (fMRA) was a technoscientific innovation that allows scientists to directly view the changes made in the blood vessels of a brain. fMRA was first developed at Neuroscience Research Institute (NRI) in Korea. fMRA mainly utilizes 7 Tesla MRI technology, and NRI is equipped with the instrument. First article on fMRA was published in 2008, and two more papers in 2010 and 2012 consecutively had been published on the newly developed technique. However, fMRA is a competitive technology with existing fMRI. Both techniques capture microvascular changes in a brain, and by doing it, both techniques visualize the cognitive and affective changes. fMRI technology was introduced by Seiji Ogawa in the early 1990's and has been widely used since then. In contrast, fMRA was a newer technology and rather unknown. Developers of fMRA in NRI used series of signifiant-politics in order to make it better known to scientific community as well as public. By resetting the boundaries of existing concept of fMRI, they tried to lower the threshold of a new concept/technique. This case study shows how technoscientists use semiotic strategies governing new technology.

• The Korean Journal of Archival Studies
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• no.15
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• pp.219-262
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• 2007

Business organization have developed in close association with the society afterward. Moreover, under capitalism business archives, though they are created in private sector, have started to have public characteristics and be used in public domain beyond internal use in business organization. Records and Archives management at a corporate level increasingly become indispensible. Business organization can use archive management to improve job efficiency and customer service and to facilitate legal matters, marketing, advertising, property management, personnel management and publicity. Additionally, They can secure corporate identity and social reliability as well as transparency in management. This is turn helps secure corporate competitiveness to play as a medium for creating new profit, which will enhance corporate brands. The records and Archives management, which recently kicks off among business organization, are to collect scattered archives and seek systemic management through archives management systems. This study present ways to collect archives scattered before archives management systems were adopted according to archives management. As a prior investigation, the scope and characteristics of business archives are defined. Visit to business organization to collect data and interview with officials responsible were carried out as a preliminary investigation to conduce acquisition policy. Based on the results of the investigation, acquisition policy of Meritz was conducted. into internal and external collection activities, event collection activities. Value appraisal and display appraisal of archives were established as a appraisal policy for efficient management and utilization of collected business archives. This study takes the case of Metitz Fire & Marine Insurance Co, Ltd (Meritz) as a example to present ways to manage business archives specifically.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.41-50
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• 2021

This study investigated what the general public thinks about the shipping industry and how important it is. As a result of the study, more than half of the respondents answered that they knew a little about the shipping industry or that they were normally knew about the shipping industry. Regarding the necessity of budget input to prevent bankruptcy of national shipping companies, it was found that more than half of the respondents answered that it was necessary or moderate. Regarding the necessity of maintaining a national shipping companies, 53% of respondents said it was necessary, and 23% of respondetns said it was normal. However, when asked if they thought that maintaining a national shipping companies would benefit me and my family, 39% of respondetns answered "normal" and 28% of respondetns answered "mostly". As for the cause of Hanjin Shipping's bankruptcy, 49% of respondents said that the owners' family members were immoral and incompetent, and 17.4% of respondetns said that the shipping market conditions deteriorated. Regarding the necessity of fostering the shipping industry, foreign currency acquisition and service balance improvement through export of shipping services accounted for 43.5%, and smooth transportation of import and export cargo accounted for 36.5%. When asked what kind of damage I suffered from Hajin Shipping's bankruptcy, 54.6% answered other (not much), and 14.5% said inflation. Abouve these results, this study gave implication in terms of public promotion and transparent business management.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.97-107
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• 2024

Despite the rapid advancement in image recognition technology, achieving perfect digitization of tabular documents and handwritten documents still challenges. The purpose of this study is to improve the accuracy of digitizing the logbook by correcting errors by utilizing associated rules considered during logbook entries. Through this, it is expected to enhance the accuracy and reliability of data extracted from logbook through OCR programs. This model is to improve the accuracy of digitizing the logbook of the training ship "Saenuri" at the Mokpo Maritime University by correcting errors identified after Optical Character Recognition (OCR) program recognition. The model identified and corrected errors by utilizing associated rules considered during logbook entries. To evaluate the effect of model, the data before and after correction were divided by features, and comparisons were made between the same sailing number and the same feature. Using this model, approximately 10.6% of errors out of the total estimated error rate of about 11.8% were identified, and 56 out of 123 errors were corrected. A limitation of this study is that it only focuses on information from Dist.Run to Stand Course sections of the logbook, which contain navigational information. Future research will aim to correct more information from the logbook, including weather information, to overcome this limitation.