• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.22-32
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• 2008

To overcome the weakness of the image retrieval system using the existing Ontology and the distributed image based on the database having a simple structure, HERMES was suggested to ensure the self-control of various image suppliers and support the image retrieval based on semantic, the mentioned framework could not solve the problems which are not considered the deterioration in the capacity and scalability when many users connect to broker server simultaneously. In this paper the tables are written which in the case numerous users connect at the same time to the supply analogous level of services without the deterioration in the capacity installs Broker servers and then measures the performance time of each inner Broker Component through Monitoring System and saved and decides the ranking in saved data. As many Query performances are dispersed into several Servers User inputted from the users Interface with reference to Broker Ranking Table, Load Balancing system improving reliability in capacity is proposed. Through the experiment, the scheduling technique has proved that this schedule is faster than existing techniques.

• Journal of Animal Science and Technology
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• v.62 no.1
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• pp.64-73
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• 2020

Producing animal products from farm to table emits massive amounts of greenhouse gases (GHGs). Modified meal plans, mainly including vegetables and grains, have been recommended to reduce GHG emissions. However, these meal plans have not been developed with regard to the micronutrient content, but rather with regard to the energy requirements of grains and vegetables, which could result in a nutritional imbalance. For this reason, we investigated a common Korean suggested meal plan (SMP) from the National Institute of Agricultural Sciences, in which nutritional conditions were considered, and evaluated its GHG emissions using the Life Cycle Assessment Inventory Database and nutritional values. The SMP, which included meat, was based on the Korean Nutrition Society for adult men age 19 to 29, and was changed to a vegan meal plan (VMP). Animal-based protein sources were substituted for meat alternatives, such as beans and tofu, for which carbon footprint data was available. To compare the nutritional differences, the 9^th Korean Food Composition Tables I and II were consulted. To calculate GHG emissions, the carbon footprint data of the food was converted to a CO₂ equivalent (CO₂e) using a procedure from the Foundation of Agriculture Technology Commercialization and Transfer. It was found that GHG emissions per calorie were 18% lower for the VMP when compared to the SMP. However, if GHG emissions per total amino acids were evaluated, the VMP GHG emissions per total amino acids were 0.12 g CO₂e/mg, while the corresponding value for the SMP was 0.06 g CO₂e/mg. The Korean daily meat intake reported by the Korea Agricultural Statistics Service was 37.1% lower than in the SMP, but when converted to a protein intake the figure was 17.0% lower. It was found that each SMP resulted in more GHG emissions than the VMP, but when considered as GHG emissions per total amino acids, the opposite pattern was apparent. There is a need to conduct more detailed studies of the variation in GHG emissions with different meal plans, using the daily meat intake per person.

• Korean Journal of Environment and Ecology
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• v.31 no.5
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• pp.433-443
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• 2017

Securing the species compositional integrity (typicalness and representativeness) is the essential prerequisite for an integrated management of vegetation resources using the phytosociological $relev\acute{e}s$ and plant communities of the Z.-M. school. This study is intended to develop a tool for qualitative and quantitative evaluation of species compositional homotoneity of a set of $relev\acute{e}s$ per syntaxon. The new homotoneities, actual homotoneity ($H_{act}$), and optimal homotoneity ($H_{opt}$) taking into account the heterogeneous factors of $relev\acute{e}s$ are proposed. The correlations between the floristic variables such as the vegetation type, the new homotoneities, and the previously studied homogeneous measures (e.g. Pfeiffer's homogeneity, basic homotoneity-coefficient, corrected homotoneity-coefficient, and mean floristic similarity) are analyzed by using Spearman's rank correlation coefficient. $H_{act}$ and $H_{opt}$ are effective in determining the difference of inter-synthesized units and of inter-$relev\acute{e}s$, respectively. $H_{act}$ is the homotoneity that is the most independent of the number of $relev\acute{e}s$. On actual vegetation with long-term human impact in the Korean Peninsula, $H_{opt}$ has become an aid to the more precise understanding of $H_{act}$ as substantive homogeneousness of species composition of syntaxa. It is expected that $H_{act}$ and $H_{opt}$ can be used for the selection of a sort of homogeneous vegetation data to build a phytosociological $relev\acute{e}$-database with consistency and objectiveness for national vegetation resources.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.300-312
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• 2020

The growing stocks of young forests that are less than10 years of age have been excluded from the Korean forest resource statistics, despite the existence of standing trees; however, sustainable forest management and carbon removals in the forestry section require complete information regarding forest resources. This study developed a method to estimate the growing stocks for young forests from National Forest Inventory (NFI) data. After reviewing previous research on growth characteristics for young forests, we conducted stem analysis of major species, and examined stand characteristics by site index, based on real yield tables. Our statistical analysis results showed that there were few standing trees with diameters at breast height (DBH) above 6 cm in young stands, and that it would have taken 12 years, on average, to reach 6 cm DBH. This suggests that mean tree height by diameter should be assessed at the root, in order to assess growing stocks for young stands through the NFI. Moreover, the database system should be improved to differentiate tree species, since diverse shrubs, including trees, have been surveyed.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.663-672
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• 2005

This Paper Proposes an approach that removes the redundancy of Path information and uses an inverted index, as an efficient way to store a large volume of XML documents and to retrieve wanted information from there. An XML document is decomposed into nodes based on its tree structure, and stored in relational tables according to the node type, with path information from the root to each node. The existing methods using path information store data for all element paths, which cause retrieval performance to be decreased with increased data volume. Our approach stores only data for leaf element path excluding internal element paths. As the inverted index is made by the leaf element path only, the number of posting lists by key words become smaller than those of the existing methods. For the storage and retrieval of U data, our approach doesn't require the XML schema information of XML documents and any extension of relational database. We demonstrate the better performance of on approach than the existing approaches within the scope of our experiment.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.154-166
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• 2009

Database query and reporting tools, OLAP tools and data mining tools are typical front-end tools in Business Intelligence environment which is able to support gathering, consolidating and analyzing data produced from business operation activities and provide access to the result to enterprise's users. Traditional reporting tools have an advantage of creating sophisticated dynamic reports including SQL query result sets, which look like documents produced by word processors, and publishing the reports to the Web environment, but data source for the tools is limited to RDBMS. On the other hand, OLAP tools and data mining tools have an advantage of providing powerful information analysis functions on each own way, but built-in visualization components for analysis results are limited to tables or some charts. Thus, this paper presents a system that integrates three typical front-end tools to complement one another for BI environment. Traditional reporting tools only have a query editor for generating SQL statements to bring data from RDBMS. However, the reporting tool presented by this paper can extract data also from OLAP and data mining servers, because editors for OLAP and data mining query requests are added into this tool. Traditional systems produce all documents in the server side. This structure enables reporting tools to avoid repetitive process to generate documents, when many clients intend to access the same dynamic document. But, because this system targets that a few users generate documents for data analysis, this tool generates documents at the client side. Therefore, the tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the report viewer in the client side. Also, this reporting tool has data structure for integrating data from three kinds of data sources into one document. Finally, most of traditional front-end tools for BI are dependent on data source architecture from specific vendor. To overcome the problem, this system uses XMLA that is a protocol based on web service to access to data sources for OLAP and data mining services from various vendors.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.4
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• pp.447-452
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• 2007

This study was peformed to estimate manganese intake and the major food source of manganese in Korean adults. The 354 subjects aged over 20 years were measured anthropometrics and dietary intake using 24-hour recall method. Daily intake and the major food sources of manganese were calculated using manganese database of food composition tables in Korea, USA and Japan. The average age, height, weight and BMI were 54.6years, 165.7cm, 67.2kg and $24.5kg/m^2$ for men and 53.8 years, 153.7cm, 59.1kg and $24.9kg/m^2$ for women, respectively. The daily energy and manganese intake of men were significantly higher than those of women (1740.9 kcal vs. 1432.6 kcal; p<0.001, 3.7mg vs. 3.2mg; p<0.01). However, daily manganese intake per 1000kcal between men and women was not significantly different (2.2mg/1000kcal vs. 2.3mg/1000kcal). Daily manganese intakes from each food group were 1.9mg from cereals, 0.5mg from vegetables, 0.4mg from pulses and 0.2mg from seasonings. The 20 major food sources of dietary manganese were rice, soybean, sorghum, Kimchi, tobu, wheat flour, red pepper powder, small red bean, glutinous millet, soybean paste, potato, Ramyeon, green pepper, noodle, buckwheat Naengmyeon, soybean sprout, laver, watermelon, perilla seeds powder and soy sauce. Manganese intake from these 20 foods was 74.0% of the total dietary manganese intake. In conclusion, daily manganese intake of the subject was 3.4mg (2.2mg/1000 kcal) and met adequate intake of manganese. The mai or food sources of manganese were cereals, pulses, and vegetables such as rice, soybean, sorghum, Kimchi and tobu.