• Resources Recycling
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• v.19 no.2
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• pp.63-72
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• 2010

The patents were searched to investigate the trend of recycling technologies about plastic waste. Database was collected from WIPS site and the range of the search was limited to patents opened in U.S.A (US), European Union (EU), Japan (JP) and Korea (KR) to september 2009. In this paper, 4,795 patents were selected by investigation abstracts and the trend of the recycling technologies relating to waste plastic were investigated through the analyzing by the years, countries, companies. The patents were occupied 65% by Japan and the most of the patents were about chemical recycling. In the case of Korea, material recycling was major in the patents of waste plastic recycling.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.57-68
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• 1999

In case of topographic information construction it is most important as basemap determines the success or failure of GIS It is argument that digitizing works of basemap are divided by NGIS and PBLIS. So, it have to accompany the combination and application of cadastral information for constructing a usful basemap. In this study, we generated ortho image map using 1:5,000 aerial-photography image, present the comparative analysis for the overlay accuracy and map revision of topographic and cadastral information using ortho image map to base map. So, we present application schemes for land use, environment, and city planning field as well as union database by overlaying of image map and cadastral information.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.21-28
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• 2019

Process mining is state-of-the-art technology in the workflow field. Recently, process mining becomes more important because of the fact that it shows the status of the actual behavior of the workflow model. However, as the process mining get focused and developed, the material of the process mining - workflow event log - also grows fast. Thus, the process mining algorithms cannot operate with some data because it is too large. To solve this problem, there should be a lightweight process mining algorithm, or the event log must be divided and processed partly. In this paper, we suggest a set of operations that control and edit XES based event logs for process mining. They are designed based on relational algebra, which is used in database management systems. We designed three operations for tailoring XES event logs. Select operation is an operation that gets specific attributes and excludes others. Thus, the output file has the same structure and contents of the original file, but each element has only the attributes user selected. Union operation makes two input XES files into one XES file. Two input files must be from the same process. As a result, the contents of the two files are integrated into one file. The final operation is a slice. It divides anXES file into several files by the number of traces. We will show the design methods and details below.

• Journal of Information Management
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• v.26 no.4
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• pp.100-115
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• 1995

This paper outlines recent conditions after the collapse of former Soviet Union and presents activities in eight major information-related organizations including International Center for Scientific and Technical Information, Russian State Central Scientific Medical Library. Russian National Public Library for Science and Technology, All-Russian Institute for Science and Technical Information, Natural Sciences Library of Russian Academy of Sciences, Scientific and Technical Information Center of Russia, Russian State Library and All-Russian Scientific and Research Institute of State Patent Examination. All of these organizations face economic difficulties brought about by financial crisis and inflation as well as shortage of the state budget. In addition, the domestic information processing technology using computers and computer networks is generally inferior to that of developed western countries due to lack of growth of information infrastructure in Russia.

• Journal of Korean Society of Archives and Records Management
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• v.2 no.2
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• pp.93-106
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• 2002

Finding aids are descriptive tools for archival materials in order to physically and intellectually understand and control archival collections. For electronic finding aids, encoded archival description has been developed as part of the Online Archive of California project for direct and comprehensive access to a variety of archival materials across the California state. The purpose of this article are: to understand a brief history of EAD development; to examine EAD encoding, format conversion, structure, and representation used in OAC; and to necessarily suggest that a customized EAD model should be developed for Korean contexts.

• The Korean Journal of Archival Studies
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• no.8
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• pp.181-211
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• 2003

The purpose of this study is to reveal the context within which EAD was developed, to review the elements and the structure of EAD 1.0 version and to introduce EAD as new standard for encoded archival finding aids in Korea. Encoded Archival Description(EAD) has been developed in 1993 in order to facilitate exchange of ISAD(G) descriptive information. EAD is currently administered and maintained jointly by the Society of American Archivists and the United States Library of Congress. While development was initiated in the United Stares, international interest and contribution are increasing. EAD is a encoding standard designed specifically for marking up information contained in archival finding aids. From its inception, EAD was based on SGML, and, with the release of EAD version 1.0 in 1998, it is also compliant with XML in order to facilitate easier internet access to SGML-encoded finding aids. EAD is the first tool to preserve the multilevel and hierarchical description manifest in finding aids by providing structures in which to describe entire record collections and increasingly smaller subcomponents thereof such as series, subseries, folders, and even items. Archival institutions can form a EAD consortium and also create a union database of EAD finding aids for the geographically dispersed collections. The EAD DTD provides a flexible way for archives to convert finding aids that exist in paper form into electronic documents or to create new finding aids in electronic form.

• Korean Journal of Clinical Pharmacy
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• v.32 no.3
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• pp.226-237
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• 2022

Background: Monoclonal antibodies for the treatment of patients with different types of cancer, such as cetuximab, have been widely used for the past 10 years in oncology. Although drug information package insert contains some representative adverse events which were observed in the clinical trials for drug approval, the overall adverse event patterns on the real-world cetuximab use were less investigated. Also, there have been no published papers that deal with the full spectrums of adverse drug events of cetuximab using national-wide drug safety surveillance systems. Methods: In this study, we detected new adverse event signals of cetuximab in the Korea Adverse Event Reporting System (KAERS) by utilizing proportional reporting ratios, reporting odds ratios, and information components indices. Results: The KAERS database included 869,819 spontaneous adverse event reports, among which 2,116 reports contained cetuximab. We compared the labels of cetuximab among the United States, European Union, Australia, Japan, and Korea to compare the current labeling information and newly detected signals of our study. Some of the signals including hyperkeratosis, tenesmus, folliculitis, esophagitis, neuralgia, disseminated intravascular coagulopathy, and skin/throat tightness were not labeled in the five countries. Conclusion: We identified new signals that were not known at the time of market approval.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.253-260
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• 2005

The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.