• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.1
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• pp.1-10
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• 1999

Landuse information is base data being applied as common database in the process of executing urban project service and is very available. But, the progress of business on landuse information building is deficient yet. In this study, we'd like to deal with landuse information projet that is the base of urban project, many landuse information building and the method of extraction of efficient second-information. Also, we built system to apply actively landuse information for urban projectors. And, we'd like to present the model on urban landuse classification system that wouldn't be standard yet by studying the method of urban landuse pattern using landuse in-formation being built. Also, we can evaluate if the model of urban landuse pattern comes up to present landuse. We can expect it is a base data by extracting unsuitable area from present landuse efficiently when we construct landuse project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.507-516
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• 2019

The investigation of land characteristics is an important task for the calculation of officially land prices and standard comparison table of land price. Therefore, it should be done objectively and consistently. However, the current investigation system is mainly done by researcher's subjective judgment. Therefore, the objectivity and consistency of this investigation is not guaranteed and questionable. In this study, we first defined the problem by analyzing the current land topography investigation method. In addition, in order to investigate the land topography, the geometry of the parcel is quantified by spatial information and applied to the decision tree based method(C4.5) to produce the final result. This study intended to extract the parcel characteristics data of the topographic by the use of spatial information and to apply the information to the C4.5, there by suggesting a method for addressing the problems. The findings showed approximately 93.5% between the results of topography classification estimated with rules learned by C4.5.

• Journal of Korean Library and Information Science Society
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• v.43 no.3
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• pp.143-163
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• 2012

In order to convert a thesaurus described by a person to ontology, the first step is to translate the thesaurus to the ontology by using SKOS, which is suitable for conversion to ontology and was chose an international standard by W3C. SKOS is suitable for converting thesaurus or subject headings or classification system to ontology, but we need a web language to describe an ontology as RDF/XML. RDF/XML is so difficult to read and write that we can need RDFa embedded in HTML document or Turtle, which is more easily describable and readable. Along with description using SKOS, this research has experimentally constructed the ontology by using ontology construction program $Prot{\acute{e}}g{\acute{e}}$ 4.2. In addition to basic concept relationships of thesaurus like equivalent relationship, hierarchical relationships, association relationships transitive hierarchical relationships are included suggested by SKOS in this research.

• Spatial Information Research
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• v.21 no.2
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• pp.35-43
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• 2013

The aim of this research is to analyze the priority to functions of the U-city Service Aid Organization(USAO), which is to support invigorating U-City industry. This research analyzes the relative importance and the priority about the functional area and components of UASO based on AHP. This research also performs a sensitivity analysis. The research result shows that relative importance of functional area is like following orders: 1) distribution of U-City service-related information, 2) quality certification of U-City-related products and services, 3) R&D of U-City technology, 4) standardization of U-City, 5) U-City human resource development. The relative importance order of functional components is 1) establishment of U-City information distribution organization, 2) construction and management of U-City information distribution network, 3) supporting U-City information distribution and price policy, 4) providing U-City information list for distribution, 5) preparation and application of quality certification standard of U-City products and services, 6) research on legal system of U-City items, targets, and procedures for quality certification, 7) research, analysis, and provision of U-City information distribution situation, 8) level examination of constructed infrastructures and services in U-City, 9) U-City core technology development and localization of technology, 10) standardization of collected U-City information, service classification, distribution system. This research result can be applied directly to design functions of USAO. The result also can be used for duty management, human resource planning, or resource allocation.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.