• Proceedings of the Zoological Society Korea Conference
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• 1996.10a
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• pp.75.2-75
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• 1996

No Abstract, See Full Text

• Bulletin of the Korean Mathematical Society
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• v.30 no.2
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• pp.213-221
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• 1993

In this paper, we will show that the multiplicative group G in a finite ring R with identity 1 has a (B, N)-pair satisfying the following conditions; (1) G=BNB where B and N are subgroups of G. (2) B.cap.N is a normal subgroup of N and W = N/(B.cap.N), is generated by a set S = { $s_{1}$, $s_{2}$, .., $s_{k}$} where $s_{i}$.mem.N/(B.cap.N), $s_{i}$$^{2}$.iden.1 and $s_{i}$.neq.1. (3) For any s.mem.S and w.mem.W, we have sBw.contnd.BwB.cup.BswB. (4) We have sBs not .subeq. B for any s.mem.S. When G, B, N and S satisfy the above conditions, we say that the quadruple (G, B, N, S) is a Tits system. The group W is called the Weyl gorup of the Tits system.ystem.m.

• The Korean Journal of Ecology
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• v.17 no.2
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• pp.213-222
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• 1994

Songs recorded in Chirisam(1990~1993) and $Ull\v{u}ngdo$(1992~1993) areas were analyzed to investigate the features and variances in songs of Great tit, Parus major. Songs of Great tits were identified, most of which were repetitions of phrases composed of high-frequency note and low-frequency note. The CV range of the Chirisan Great tit group was wider than that of the $Ull\v{u}ngdo$ area. ANOVA analysis level was highly significant (p<0.0001) for Chirisan area and $Ull\v{u}ngdo$ area. Inter-regional variance level was significant (p<0.05) in the maximum of low-frequency.

• The Korean Journal of Ecology
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• v.17 no.3
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• pp.379-385
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• 1994

Sonograms of songs recorded in Kwangnung and Chejudo were analyzed to investigate the features and variances in the songs of Great tit, Parus major variety. Songs of Great tits were identified, most of which were repetitions of phrases compoed of high-frequency note and low-frequency note. Variances between the songs of the two areas in the minimum and maximum of low-frequency were significat. The CV range of the Great tit group in Chejudo was wider than that in Kwangnung. Interregional variance level was significant in the minimum (P<0.04) and maximum (P<0.0001) of low-frequency.

• The Korean Journal of Zoology
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• v.38 no.2
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• pp.230-237
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• 1995

Playback experiments were excecuted with seven threat Tit males inhabited in Gsngnae Myeon, Darak Ri, Chungbuk province to investigate the signal value of partial song (one unit phrase composed of two notes) as a species recognition releaser. Territorial males responded strongly to their own natural, synthetic and partial songs played in the field. However, thew showed weak or no responses to the playback songs of other species: Coal Tit (Porus ate4 and Yellow-throated Bunting (EmberiEa elegansl.6reat Tits distinguished conspecific partial songs readily from songs of other species. The results demonstrated that one unit phrase which is a basic arrangement of the Great Tit song, containes information on species recognition.

• KIEAE Journal
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• v.10 no.6
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• pp.3-10
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• 2010

The subject is to find green roofs' location as stepping stones in green-network in fine scale. The study site is Junggu, Seoul, which has core areas(Bukaksan and Namsan) and green areas(parks, etc.). Through literature review, the closer to core areas and green areas, target species reach green roof easier, and target species must be avifauna(flying species) and high class in food chain, because of possibility of reaching. So, Great Tits, inhabited in Namsan and urban bird, is target species. The location standard of green roofs, realized birds' reaching distance, consists of home range(horizontal range and vertical range) and roof-greening capable area. The green roofs' distribution of location was resulted through GIS analysis of feasible site finding, and classified with weight of score. In discussion, Namsan gives more effect to locate green roofs than Bukaksan does and selected buildings which are grouped in some parts need to be managed with group, green roof district.

• Proceedings of the Zoological Society Korea Conference
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• 1994.10a
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• pp.103.2-103
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• 1994

No Abstract, See Full Text

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.411-418
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• 2014

This study seeks to identify the effects of light pollution and environmental factors on Great Tits(Parus major) bird's chirping at dawn. For this research, the campus of Sanji University, Wonju, South Korea was selected as the area with light pollution and the western forest of the Chiaksan National Park was chosen as the natural area herein. The Recording period was between March 26th and May 30th, 2014. As a result of analyzing the chirping time according to light pollution, it was found that the light pollution area clearly showed earlier chirping time than the natural area (p<0.05). Great Tits(P. major) normally start their first chirping before sunrise and in most of the days under investigation of this research, those in Sanji University started to chirp earlier. This faster chirping time seems to improve the chance for the female birds to mate with immature males thus, baby birds hatch earlier than the appropriate breeding season and results in the lack of feed resources. The correlation between Great Tits'(P. major) dawn chirping and environmental factors were investigated herein including the time of sunrise, civil twilight, navigation twilight, astronomical twilight, average temperature, highest temperature, lowest temperature, time of moonrise and cloudiness. The first chirping time of wild birds in the day was found to have correlations with all of the environmental factors excluding the time of moonrise and cloudiness. Great Tits(P. major) started their first chirping before sunrise when the day started to break around civil twilight. Along with the earlier sunrise and higher air temperature, their dawn chirping time was also quickened. The time of moonrise and cloudiness did not show a correlation and further follow-up studies will be necessary in this regard.

• Korean Journal of Environment and Ecology
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• v.30 no.5
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• pp.829-836
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• 2016

This study was carried out on Kongju National University and its neighboring area, Mt. Gyeryong national park and Mt. Worak national park in the breeding season of long-tailed tits Aegithalos caudaatus from 2008 to 2012. The result of the inquiry, the nests were found in 15 species of trees, and this result shows me it's not choosy about them. But after having classified them according to the features and analyzed them, long-tailed tits preferred evergreen needleleaf tree and deciduous broad-leaf tree and deciduous bush, especially evergreen needleleaf tree. The concealment rate of long-tailed tits' nests was $11.61{\pm}4.79%]\;4.38{\pm}2.19%$(n=29) in Kongju National University and it's neighboring area, $6.06{\pm}2.31%$(n=43) in Mt. Gyeryong national park and $4.38{\pm}2.19%$(n=32) in Mt. Worak national park. By regional groups, the concealment rates of neighboring nests were almost same, but there are no differences among the areas. The average of the color codes was $26.52{\pm}16.14$(n=32) that those of the nest subtract from those of surroundings of the nest. The nests were procryptic according to their surroundings, and if their nest in a tree were evergreen needleleaf trees, they were made of moss. while if the trees of nest in a tree were yellow because of fungus, made of dried moss, they were yellow, too.

• 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.