• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.1
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• pp.98-104
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• 1999

To investigate the relationships between ocean environmental characteristics, the time-series data of temperature and salinity observed at a station near at Hanlim set net in 1995 and 1996 are analyzed, and the results are as follow ; 1. In hanlim set net, the diurnal range of temperature and salinity variation in summer is very large and the amplitude of short-period fluctuation of temperature and salinity is very large. That is, not only the water of the middle and bottom layers (low temperature and high salinity) but also the coalstal water (high temperature and low salinity) appears alternatively depending on the current direction 2. from the result of mooring for 22 days in Hanlim set net, the mean speed and direction of tidal current in neap tide were 9.1 cm/sec and south westward in ebb time, and 11.6 cm/sec and north or northeastward in flood time, respectively. The highest speed of the current was 15cm/sec in ebb time, and 22.6 cm/sec in flood time. The mean speed and direction of tidal current in spring tide were 10.4 cm/sec, and southwestward in ebb time, and 12.3 cm/sec, and north or northestward in flood time, respectively. The highest speed of the current was 19.4 cm/sec in ebb time, and 20 cm/sec in flood time respectively. The mean speed of the current in flood time was larger than that in ebb time. The velocity vector along the major axis of semidiurnal tide ($M_2$) component was 1.5 times larger than that of diurnal tide ($K_1$), The major directions of two compornants were northwestward and east-southeastward and residiual current were 3.25 cm/sec and northwestward-directed. Result of TGPS Buoy tracer for 3 days between Biyang-Do and Chgui-Do showed that the mean speed was 1.6 knot in ebb time and 1.3 knot in flood time. Direction of tidal was southwestward in ebb time and northeastward in flood time respectively. The maximum current speed was 4.8 knot in ebb time and 3.7 knot in flood time respectively. The mean speed and direction of tidal in of offshore were 1.7 knot and northwestward in flood time. The residual current appeared 0.3 knot northeastward.

• Journal of KIISE
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• v.42 no.3
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• pp.367-378
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• 2015

This study was directed at the design of a hybrid algorithm for competition relation extraction. Previous works on relation extraction have relied on various lexical and deep parsing indicators and mostly utilize only the machine learning method. We present a new algorithm integrating machine learning with various filtering methods. Some simple but useful features for competition relation extraction are also introduced, and an optimum feature set is proposed. The goal of this paper was to increase the precision of competition relation extraction by combining supervised learning with various filtering methods. Filtering methods were employed for classifying compete relation occurrence, using distance restriction for the filtering of feature pairs, and classifying whether or not the candidate entity pair is spam. For evaluation, a test set consisting of 2,565 sentences was examined. The proposed method was compared with the rule-based method and general relation extraction method. As a result, the rule-based method achieved positive precision of 0.812 and accuracy of 0.568, while the general relation extraction method achieved 0.612 and 0.563, respectively. The proposed system obtained positive precision of 0.922 and accuracy of 0.713. These results demonstrate that the developed method is effective for competition relation extraction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.4
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• pp.53-60
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• 1986

This study is directed to propose a probability based LRFD design code, which could possibly replace the traditional USD provisions of the current code, based on the AFOSM reliability theory. The uncertainties of resistances and load effects for each R.C. structural elements are evaluated and adopted considering our practice, and a set of rational target reliability indices are selected based on the calibration with the reliability of the current R.C. design code and by considering the desired hierarchy of safety level. Then, a set of common load factors are chosen from the results of load and resistance factors which are computed by AFOSM method using the Rackwitz-Fiessler's efficient practical algorithm which is to transform the non-normal variables into the equivalent normal variables. It may be asserted that the proposed LRFD code for the R.C. building structures may have to be incorporated into the current RC. design codes as a design provision corresponding to the USD provisions of the current R.C. design code.

• Journal of Elementary Mathematics Education in Korea
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• v.11 no.2
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• pp.177-197
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• 2007

This study discussed the climbing learning method which studied and practiced by Professor Saito Noboru. This is the learning method which is devised to know not only the relationship of the learning factors but the systemic or structural connection of whole studying contents- affects children's math learning ability through practical class to both the lower and the higher grades. To achieve the purpose of this study, these following issues were set; A. Develop the teaching and learning course of mathematics by applying the climbing learning method. B. Execute the mathematics lesson according to the climbing learning method and analyze the learning achievement. C. Analyze the difference between application of the climbing learning method and that of the learning method by student's level in mathematics. D. Analyze what the climbing learning method gives a shift of the recognition of learning mathematics. In order to accomplish these study issues, we analyzed the text book of math not only for children but also for teachers and developed the teaching and learning course applied the climbing learning method with advice of experts. It was chosen two different homogeneous groups each, third year for lower grade group and fifth year for higher grade group. It was done the experimental group lesson applying the climbing learning method and general lesson for the control group. After then, t-test against independent samples was done depending on the result of the student's assessment(T1, T2). These two groups' students were divided into smaller groups based on result of achievement level regardless of gender. These subgroups were confirmed the difference of learning ability between upper and lower level group. As regarding the result making out grades of faith and attitude for math, t-test was used on independent sample. At the same time, experimental groups were tested using learning attitude with the learning structure chart. Through this study the following results are obtained and the conclusion was drawn. Firstly, although applying the climbing learning method to the lesson does not have significant effect to the lower grade of elementary school student's achievement it has significant influence on the higher grade student's achievement. Second, as a result of analyzing the difference between the climbing learning method and the learning method by student's level in mathematics, it is of no beneficial effect to the lower grade both upper level and lower level. However, it has appreciable effect to the higher grade classes both upper level and low level. Especially, upper level students have higher effect than low level students. Third, climbing learning method does not affect to the faith and attitude of the lower grade students positively, but it has affirmative effect to the higher grade students'. As a result of the survey of the experimental groups which were applied to the climbing loaming method, the lesson by using the learning structure chart proved to be helpful to the both the lower and higher grade. The best advantage of using the learning structure chart, children say, is easily understood whole contents of studying and is useful for review. Furthermore, using the learning structure chart is more efficient compared with previous learning method and is given the successful result to self-directed learning. In conclusion, keeping up with the current of the thought of education, we suggest a scheme as a new teaching method from the constructive learning method which emphasize the self-directed learning.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.23-34
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• 2017

During Khmer Rouge Regime, Cambodian pop music was completely forgotten since 90% of artists were killed. After recovering from war since 1979, the music started to grow again in 1990. However, Cambodian popular music dynamic and flows are observably directed by the multifaceted socioeconomic, political and creative forces. The major problems are the plagiarism and piracy which have been prevailing for years in the industry. Recently, the consciousness of the need to preserve Khmer original songs from both fans and artist have been increased and become a new trend for Cambodia young population. Still, the music quality is in the limit state. To increase the mind-set, the feedbacks and inspiration are needed. The study suggested a music ranking website using sentiment analysis which data were collected from Production Companies Facebook Pages' posts and comments. The study proposed an algorithm which translates from Khmer to English, doing sentiment analysis and generate the ranking. The result showed 80% accuracy of translation and sentiment analysis on the proposed system. The songs that rank high in the system are the songs which are original and fit the occasion in Cambodia. With the proposed ranking algorithm, it would help to increase the competitive advantage of the musical productions as well as to encourage the producers to compose the new songs which fit the particular activities and event.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.463-476
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• 2017

Climate change is considered as the greatest threat to our future and descendants. The Korean government has set a target for 2030 to reduce emission of greenhouse gases (GHGs) by 37% from the business-as-usual levels which are projected to reach 851 million metric tons of $CO_2eq$ (Carbon dioxide equivalent). In Korea, GHGs emission from agriculture account for almost 3.1% of the total of anthropogenic GHGs. The GHGs emitted from agricultural land are largely classified into three types: carbon dioxide ($CO_2$), methane ($CH_4$), and nitrous oxide ($N_2O$). In Korea, rice paddies are one of the largest agricultural $CH_4$ sources. In order to analyze domestic research trends related to $CH_4$ emission from rice paddies, 93 academic publications including peer reviewed journals, books, working papers, reports, etc., published from 1995 to September 2017, were critically reviewed. The results were classified according to the research purposes. $CH_4$ characteristics and assessment were found to account for approximately 65.9% of the research trends, development of $CH_4$ emission factors for 9.5%, $CH_4$ emission reduction technology for 14.8%, and $CH_4$ emission modeling for 6.3%, etc. A number of research related to $CH_4$ emission characteristics and assessment have been studied in recent years, whereas further study on $CH_4$ emission factors are required to determine an accurate country-specific GHG emission from rice paddies. Future research should be directed toward both studies for reducing the release of $CH_4$ from rice paddies to the atmosphere and the understanding of the major controlling factors affecting $CH_4$ emission.

• Journal of The Korean Association of Information Education
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• v.19 no.2
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• pp.215-224
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• 2015

For this, 410 development topics and contents were selected based on the analysis of contents related to mathematics and science, the pre-investigation and analysis of mathematics and science teachers in agricultural, mountain and fishing villages and the analysis of the 2009 revised curriculum. The validity verification of the selected subject list and implementation plan was implemented through the reviews by experts in each subject and the storyboard was designed by reflecting the examination opinion after the final revision. Development directions of the contents were set after analyzing the application result of contents from classroom for creativity and science and selected schools in agricultural, mountain and fishing villages for demonstration, and opened the platform after the revision and supplement of the expert. It is expected to elevate students' self-directed learning abilities in agricultural, mountain and fishing villages by developing and extending smart learning contents to use ICT in Mathematics and science education, which are high in urbanrural academic disparity.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.267-271
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• 2005

The goal of data mining is to extract new and useful knowledge from large scale datasets. As the amount of available data grows explosively, it became vitally important to develop faster data mining algorithms for various types of data. Recently, an interest in developing data mining algorithms that operate on graphs has been increased. Especially, mining frequent patterns from structured data such as graphs has been concerned by many research groups. A graph is a highly adaptable representation scheme that used in many domains including chemistry, bioinformatics and physics. For example, the chemical structure of a given substance can be modelled by an undirected labelled graph in which each node corresponds to an atom and each edge corresponds to a chemical bond between atoms. Internet can also be modelled as a directed graph in which each node corresponds to an web site and each edge corresponds to a hypertext link between web sites. Notably in bioinformatics area, various kinds of newly discovered data such as gene regulation networks or protein interaction networks could be modelled as graphs. There have been a number of attempts to find useful knowledge from these graph structured data. One of the most powerful analysis tool for graph structured data is frequent subgraph analysis. Recurring patterns in graph data can provide incomparable insights into that graph data. However, to find recurring subgraphs is extremely expensive in computational side. At the core of the problem, there are two computationally challenging problems. 1) Subgraph isomorphism and 2) Enumeration of subgraphs. Problems related to the former are subgraph isomorphism problem (Is graph A contains graph B?) and graph isomorphism problem(Are two graphs A and B the same or not?). Even these simplified versions of the subgraph mining problem are known to be NP-complete or Polymorphism-complete and no polynomial time algorithm has been existed so far. The later is also a difficult problem. We should generate all of 2$^n$ subgraphs if there is no constraint where n is the number of vertices of the input graph. In order to find frequent subgraphs from larger graph database, it is essential to give appropriate constraint to the subgraphs to find. Most of the current approaches are focus on the frequencies of a subgraph: the higher the frequency of a graph is, the more attentions should be given to that graph. Recently, several algorithms which use level by level approaches to find frequent subgraphs have been developed. Some of the recently emerging applications suggest that other constraints such as connectivity also could be useful in mining subgraphs : more strongly connected parts of a graph are more informative. If we restrict the set of subgraphs to mine to more strongly connected parts, its computational complexity could be decreased significantly. In this paper, we present an efficient algorithm to mine frequent subgraphs that are more strongly connected. Experimental study shows that the algorithm is scaling to larger graphs which have more than ten thousand vertices.

• Korean Security Journal
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• no.24
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• pp.125-146
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• 2010

The G20 summit is the premier forum for international economic cooperation and it will be held in Seoul in November 2010. However, protests are expected during the Seoul summit, as a part of the deepening global war against capitalism. The Korean Police need to deal with these protests effectively in order to provide security to the participating leaders and make the meeting run on wheel as planned. The current study attempts to analyze the death of Ian Tomlinson who died in the context of a heavily policed protest during 2009 G20 London summit. There are number of unique features regarding this incident, such as the public scrutiny of police conduct through video footage, the police use of excessive force, and the process to hold the police to account for misconduct. This incident caused serious damages to the public's faith in the British police. Based on the analysis, this study found that during the G20 London summit British police had the problems such as the lack of the clear standards on the use of force, improper training in the use of force, poor communications with the media and protesters, inappropriate use of the close containment tactic, and the failure to display police identification. Therefore, this study suggests the inducement of peaceful protests, the adoption of a set of standards on the use of force, public order training that is more directed and more relevant to the public order challenges facing the Korean police, improvement of the communication with the media and protesters, enhancement of individual officer's accountability as public order policing strategies for G20 Seoul summit meeting. However, the most fundamental principle is that Korean police must place a high value on tolerance and winning the consent of the public.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.101-126
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• 2016

This paper identifies core research topics and their relationships by deriving the research topic networks in the technology management field using co-word analysis. Contrary to the conventional approach in which undirected networks are constructed based on normalized co-occurrence frequency, this study analyzes directed networks of keywords by employing the confidence index of association rule mining for pairs of keywords. Author keywords included in 2,456 articles published in nine international journals of technology management in 2011~2014 are extracted and categorized into three types: THEME, METHOD, and FIELD. One-mode networks for each type of keywords are constructed to identify core research keywords and their interrelationships with each type. We then derive the two-mode networks composed of different two types of keywords, THEME-METHOD and THEME-FIELD, to explore which methods or fields are frequently employed or studied for each theme. The findings of this study are expected to be fruitfully referred for researchers in the field of technology management to grasp research trends and set the future research directions.