• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.4
• /
• pp.392-397
• /
• 2015

Society has been developed through analogue, digital, and smart era. Every technology is going through consistent changes and rapid developments. In this competitive society, R&D strategy establishment is significantly useful and helpful for improving technology competitiveness. A patent document includes technical and legal rights information such as title, abstract, description, claim, and patent classification code. From the patent document, a lot of people can understand and collect legal and technical information. This unique feature of patent can be quantitatively applied for technology analysis. This research paper proposes a methodology for extracting core technology and patents based on quantitative methods. Statistical analysis and social network analysis are applied to IPC codes in order to extract core technologies with active R&D and high centralities. Then, core patents are also extracted by analyzing citation and family information.

• The KIPS Transactions:PartC
• /
• v.15C no.5
• /
• pp.351-358
• /
• 2008

Recently, as network flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems(IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network environment. In this paper we propose a lightweight and fast detection mechanism for traffic flooding attacks. Firstly, we use SNMP MIB statistical data gathered from SNMP agents, instead of raw packet data from network links. Secondly, we use a machine learning approach based on a Support Vector Machine(SVM) for attack classification. Using MIB and SVM, we achieved fast detection with high accuracy, the minimization of the system burden, and extendibility for system deployment. The proposed mechanism is constructed in a hierarchical structure, which first distinguishes attack traffic from normal traffic and then determines the type of attacks in detail. Using MIB data sets collected from real experiments involving a DDoS attack, we validate the possibility of our approaches. It is shown that network attacks are detected with high efficiency, and classified with low false alarms.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.12
• /
• pp.692-700
• /
• 2016

The study proposed a strategy for supporting North Korea's SOC construction in the future by reviewing domestic and foreign cases. According to the literatureanalysis, we developed a candidate list of technology for SOC of North Korea in terms of Construction Management / economy sectors. The category is North Korea SOC construction support, and the sub-category is North Korea SOC construction support program. The implementation procedures included the following six steps: Preparation, Support for Establishing Construction Industry Base, Support for Establishing Business Management Base, Support for HR Management Base, Business Model Establishment/Expansion, and Monitoring of Management Result. Lastly, we developed twenty-five candidates of detailed technology. In the future, it is necessary to decide a methodology for project implementation by each scenario after selecting a study area, and to develop a more specified scenario.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.2 no.3
• /
• pp.1-15
• /
• 1999

This study was carried out to find out the way to build a comprehensive wetland ecosystem database using the technique of remote sensing and geographic information system. A Landsat TM image taken in May 17, 1997 was used for the primary source for the image analysis. Field surveys were conducted March to September of 1998 to help image analysis and examine the results. An actual wetland vegetation map was created based on the field survey. A Landsat TM image was analyzed by unsupervised and supervised classification methods and finally categorized into such 5 classes as Phragmites australis community, mixed community, sand beach, Scirpus trigueter community and non-vegetation intertidal area. Wetland basemap was developed for the overall accuracy assesment in wetland mapping. Vegetation index map of wetland vegetation was developed using NDVI(normalized difference vegetation index). The map of wetland productivity was developed based on the productivity of Phragmites australis and the relationship to the proximity of adjacent water bodies. The map of potential vegetation succession map was also developed based on the experience and knowledge of the field biologists. Considering these results, it is possible to use the remote sensing and GIS techniques for producing wetland ecosystem database. This study indicated that these techniques are very effective for the development of the national wetland inventory in Korea.

• Journal of Korean Society of Forest Science
• /
• v.88 no.2
• /
• pp.157-168
• /
• 1999

This paper analyzed vegetation and land use classification, slope and permanent preservation and legal reserves on the farm Jangada and Jamaica-Mato Grosso do Sul, Brazil, using satellite image for assisting the planning of planting Eucalyptus spp. This part of the State of Mato Grosso do Sul represents an important geopolitcal area, since it is located on the borders of Bolivia and Paraguay. Also exportation of goods can be achieved through hydrovias extending to Buenos Aires, Argentina-through the Paraguay River. Also there are road and railroad connection which link the soutreastern part of Brazil to the Andean countries. The vegetation map from sheet SF 21-Campo Grande of the RADAMBRASIL Project was used as the basis for the preliminary interpretation of coverage, and complemented by a visit of the field. After the initial interpretation of the image, definition of classes of use and land occupation were made, and files of spectral signatures were created. On the farms Jamaica and Jangada Open Arboreal Savanna and Grass Savanna are the predominant physiognomies occupying 68% of total area. In spite of the results being satisfactory at the present moment, the development of this project should be revised and adjusted based on the evaluations already made, including a greater detailing of environmental components, principally with respect to soil and topography.

• Journal of Korean Society of Archives and Records Management
• /
• v.13 no.3
• /
• pp.7-39
• /
• 2013

Some records have to be classified not according to their business function but according to their case because of the characteristics of the organization's business. Examples of this are case files, criminal files, lawsuit files, personal files, medical files, and project files. The case files are made according to standard business processes. Case files are filled with records of a series of activities and these records, which are made while carrying out various functions, reenact the multilevel process of a case. This study organized the implications of managing case files by examining the composition of lawsuit records and deducting characteristics in management. To do this, first, this study analyzed the composition of the lawsuit records that Korea Legal Aid Corporation produced and managed. Second, this study confirmed how the characteristics of case files are reflected in the lawsuit records of Korea Legal Aid Corporation. Third and lastly, this study searched how the lawsuit files are managed and used through the example of Korea Legal Aid Corporation.

• Journal of the Korean Society for Library and Information Science
• /
• v.49 no.3
• /
• pp.57-79
• /
• 2015

This study investigates and classifies 61 pieces of hereditary Sasojeol versions in possession of 8 libraries in Korea and 3 libraries in the US and Japan and compares them with one another with the following results. Firstly, as a result of investigation of 61 pieces of Sasojeol, it was found out that the hereditary versions are classified into 5 kinds including Cheongjangkwan Sasojeol, Sashojyeol of Korean version, Hyunto Sasojeol and Sasojeoljijeol. The detailed investigation proves that Sasojeol and Sasojeonjijeol are imparted to the present most often, that Sashojyeol of Korean version is the traslated from printed version of Sasojeol, that Hyunto Sasojeol is the Korean editings of printed version of Sasojeonl, and the Sasojeoljijeol is the ummarized version of Cheongjangkwan Sasojeol. Secondly, the comparison of Cheongjangkwan Sasojeol possessed by major libraries proves that the version in National Library of Korea's and Jangseogak's possession are similar to each other by and large and that the comparison of Sasojeol possessed by each institution proves that the version in Kyonggi University's possession copied the former generally fine. Thirdly, the comparison of Sasojeoljijeol and Cheongjangkwan Sasojeol proves that Sasojeonjijeol is the summarized version of redrafted Cheongjangkwan Sasojeol and traces of 22 sentences being added to.

• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.3
• /
• pp.241-264
• /
• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Journal of Korean Society of Forest Science
• /
• v.112 no.3
• /
• pp.267-279
• /
• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.537-549
• /
• 2023

The distribution characteristics of tidal flat sediment components are used as an essential data for coastal environment analysis and environmental impact assessment. Therefore, a reliable classification map of surface sedimentary facies is essential. This study evaluated the applicability of regression kriging to generate a classification map of the sedimentary facies of tidal flats. For this aim, various factors such as the number of field survey data and remote sensing-based auxiliary data, the effect of regression models on regression kriging, and the comparison with other prediction methods (univariate kriging and regression analysis) on surface sedimentary facies classification were investigated. To evaluate the applicability of regression kriging, a case study using unmanned aerial vehicle (UAV) data was conducted on the Hwang-do tidal flat located at Anmyeon-do, Taean-gun, Korea. As a result of the case study, it was most important to secure an appropriate amount of field survey data and to use topographic elevation and channel density as auxiliary data to produce a reliable tidal flat surface sediment facies classification map. In addition, regression kriging, which can consider detailed characteristics of the sediment distributions using ultra-high resolution UAV data, had the best prediction performance compared to other prediction methods. It is expected that this result can be used as a guideline to produce the tidal flat surface sedimentary facies classification map.