• Journal of Animal Environmental Science
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• v.9 no.1
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• pp.9-18
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• 2003

Most of broiler houses in Korea have the trouble of environmental control such as suitability, stability, and uniformity of internal climate, resulting in serious stress on chickens. Accordingly, it is very urgent to develop optimum designs of naturally and mechanically ventilated broiler houses for Korean climate. In this study, the internal climates such as air temperature, humidity, dust, ammonia gas, and air velocity were measured at a naturally ventilated broiler house. The data were collected during summer season including local weather data. It was found that the difference between measured and optimum air temperatures was $14.0^{\circ}C$ in maximum during the summer time. The daily maximum range of internal averaged air temperature was found $10.5^{\circ}C$ while the uniformity was $5.2^{\circ}C$ in maximum. The maximum, average, and minimum internal averaged relative humidity were 89.3%, 73.7%, and 49.2%, respectively while locally measured were 95.1% and 47.2%, respectively in maximum and minimum. Considering Temperature-humidity index, during summer season, over 97% of totally rearing period was shown that counter plan is needed for thermal stress while it was very dangerous situation for 22% of the rearing period. The ammonia gas and dust concentrations were seriously affected by the broilers activity, growth level, and relative humidity.

• Korean Journal of Ecology and Environment
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• v.42 no.1
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• pp.1-8
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• 2009

This study used a mesocosm which presumes movement of the nutrient (especially $PO_{4^-}P$) in the wetland. After setting up the mesocosm inside the wetland and adding the $PO_{4^-}P$, observed the movement of the $PO_{4^-}P$ every hour. We analyzed the variables which had the possibility of affecting $PO_{4^-}P$ concentration in the wetland-flora, absorbing rate of algae, settling rate, release rate. Immediately after adding $PO_{4^-}P$, the concentration of the TP in water column at each mesocosm was 0.48, 12.4, 20.4, $23.6\;mg\;L^{-1}$, after 21 days they were 0.6, 1.92, 6.97 and $6.94\;mg\;L^{-1}$ respectively. The concentration of the TP in water column at the mesocosm decreased on average 73.7%. The concentration of the $PO_{4^-}P$ inside reed, algae and sediment in the mesocosm was increased from $0.73mg\;gDW^{-1}$, $3.81mg\;gDW^{-1}$, $466.1mg\;kg^{-1}$ to $0.83mg\;gDW^{-1}$, $4.57mg\;gDW^{-1}$ and $813.3mg\;kg^{-1}$ respectively. Algae is more sensitive than reeds in absorption of the nutrient. TP removal by settling was highest. Budgeting of TP indicated that P moved from particulates in the water column to sediment and algae. Immediately after adding $PO_{4^-}P$, water column (24.2%) and sediment (49.0%) dominated TP storage, with algae (10.3%) and reed (16.4%) holding smaller proportions of TP. After 21 days, Sediment (59.0%) and algae (17.9%) dominated TP storage, with water column (7.1%) and reed (15.8%) holding smaller proportions of TP. Estimation of phosphate movement using mesocosms is an appropriate method because wetlands have many controlling factors. Analysed data can be compared to background data for wetland construction and management.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Korean Journal of Weed Science
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• v.2 no.2
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• pp.75-113
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• 1982

Studies were carried out 1) to define the shape and size of sampling quadrat and its number of observations for weed experiments, 2) to characterize the growth and community of major summer weeds under upland condition and 3) to investigate the factors influencing competition between weeds and soybeans under weed-free and weedy conditions in early and late season cultures. No significant difference was noted among different shapes of quadrat (regular, rectangular, band, and circular) in the sampling efficiency of weeds. The results also suggested that the minimum size of quadrat was 0.25$m^2$ and the minimum number of replication was 2 times per plot. The major dominant weeds were about 10 species in the experimental field and the total number of weeds was in the range of 70 - 1,600 plants per $m^2$. Among the weeds Digitaria sanguinalis and Portulaca oleracea were the most dominant species. Growth amount and reproduction capability were also measured by weed species. Five different weed communities were identified in the field. The degree of dispersion by weed species and association among weeds were investigated. Intra-(within soybeans) and inter-specific (between soybeans and weeds) competition were studied in early and late season cultures of soybeans. The average yield of soybeans per plant was significantly decreased in both season cultures due to intra-specific competition as the planting density of soybeans increased, On the other hand, the average yield of soybeans per l0a was proportionally increased to the increase of planting density and the rate of its increase was more significant under weedy than weed-free condition. Most of the agronomic characteristics of soybeans were affected by weeds and its degree was greater in sparse planting than in dense planting and in early season than in late-season culture. Digitaria sanguinalis was the most competitive to soybeans in early season and both of Digitaria sanguinalis and Portulaca oleracea affected primarily the growth of soybeans in late season with about the same competitiveness. The occurrence of weeds was significantly decreased in early season and slightly decreased in late-season by dense planting of soybeans. The total growth amount of weeds was also considerably decreased by increase of soybean planting density both in early- and late-season cultures. The occurrence of Digitaria sanguinalis which was the most dominant in both seasons, and its growth amount was significantly decreased as the planting density of soybean was increased. On the other hand, the occurrence of Portulaca oleracea which was only dominant in late-season culture did not show significant response to the planting density of soybeans.