• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.357-365
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• 2011

The variation of the dissolved inorganic nutrients were investigated four times per year in the costal area of Gunsan, Yellow Sea from 2001 to 2010. Water samples were collected at 10 stations and phsico-chemical parameters were analyzed including water temperature, salinity, suspended solids, dissolved oxygen, chemical oxygen demand, chlorophyll a and dissolved inorganic nutrients. The average of dissolved inorganic nitrogen(DIN) for ten years at Gunsan area showed similar concentration between surface and bottom. The average of DIN at surface was 0.421mg/L (0.198~0.846mg/L) and bottom was 0.344mg/L(0.148~0.717mg/L). The highest value of annual average of DIN at surface was 0.846mg/L in 2002 and the lowest value was 0.198mg/L in 2010. The percentage of ammonia, nitrite and nitrate for the average DIN of 10 years showed 27%, 3% and 70% which showed most of DIN was nitrate. Dissolved inorganic phosphate(DIP) for ten years at Gunsan area showed similar concentration between surface and bottom and DIP was decreasing from 2003 to 2010. The average of DIP of 10 years was 0.024mg/L and annual average 0.021mg/L in 2008, 0.007mg/L in 2009 and 0.008mg/L in 2010 which showed decreasing pattern from 2007 to 2010. The average of DIN/DIP ratio from 2002 to 2010 was 6.0(3.2~10.1) at surface and 4.6(2.6~7.0) at bottom. The average value of dissolved inorganic silicate from 2004 to 2010 showed 0.372mg/L at surface layer and 0.352mg/L at bottom layer and was on decreased from 2006 to 2010. The Spearman's correlation analysis was carried out to knowrelation among the salinity and dissolved inorganic nutrients at the surface and bottom layer. The correlation factor of DIN was -0.72, DIP was -0.46 and dissolved inorganic silicate was -0.63 at surface layer and DIN was -0.70, DIP was -0.44 and dissolved inorganic silicate was -0.57 at bottom layer. The dissolved inorganic nutrients at the nearshore of Gunsan was affected from the freshwater discharge of Geum river. Especially, a lot of DIN flowed into the nearshore of Gunsan from Guem river. The concentration of dissolved inorganic nutrients at Gunsan showed high at station 1, 2 and 3 and there was a little concentration differences according to the cruise time. The concentration of dissolved inorganic nutrients showed high value at the station 1, 2, 3 which exist nearshore of Gunsan city and it means these stations mainly affected by Geum river and Gunsan city. The annual average of dissolved inorganic nutrients showed gradually decreased from 2003 to 2010 and we need more research on this conditions.

• Korean Journal of Environmental Agriculture
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• v.18 no.2
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• pp.126-134
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• 1999

To provide the basic information for the water improvement and control of water resource in Nakdong river districts, the physico-chemical characteristics of water in four main streams and three branch streams of the river were investigated through 36 times totally, one time per each month from January in 1995 to November in 1997. The pH values of each sites in main or branch stream of Nakdong river was pH $6.3{\sim}9.3$ range, pH range of Jukpo and Namji area at spring and fall was almost over pH 8.5, which was exceeded the water quality standard for agriculture. DO values of Nakdong river was almost $8.0{\sim}13mg/l$, except for Kangchang area in downstream of Kumho river. BOD values in Dasa area where was prior to mixing of Kumho river was $1.5{\sim}4.8mg/l$, which was under the water quality standard for agriculture(8mg/l), but BOD values followed mixing of Kumho river was over the permit standard of agricultural water as $3.8{\sim}8.9mg/l$ in Koryung, $3.4{\sim}8.4mg/l$ in Jukpo and $3.3{\sim}7.8mg/l$ in Namji according to time or season. Especially, BOD values at Gangchang area in Kumho river were $7.6{\sim}18.5mg/l$, which was over the water quality standard for agriculture and so Kumho river was a main pollutant: source of Nakdong river. COD values of main stream of Nakdong river was over the permit standard of agriculture(8mg/l) as $5.2{\sim}13.5mg/l$ in Koryvng, $5.0{\sim}12.7mg/l$ in Jukpo and $5.0{\sim}12.2mg/l$ in Namji according to time or season. And COD values was much high rather than BOD values and its gap of concentration was increased along with downstream. $NH_4-N$ of main stream of Nakdong river followed mixing of Kumho river($0.5{\sim}13.1mg/l$) was the highest affected in Koryung($0.18{\sim}5.0mg/l$) and detected much more in winter than in summer. T-N in Koryung($4.96{\sim}12.06mg/l$) followed mixing of Kumho river was significantly high rather than $2.86{\sim}4.86mg/l$ in Dasa, $4.20{\sim}8.20mg/l$ in Jukpo and $3.18{\sim}8.64mg/l$ in Namji, which was almost over the permit standard of agricultural water(1.0mg/l). T-P in Koryung($0.10{\sim}0.58mg/l$) also was significantly high rather than those $0.07{\sim}0.36mg/l$ in Jukpo and $0.08{\sim}0.4mg/l$ in Namji as over the standard of agricultural water(0.1mg/l). The concentration of T-N or T-P in Nakdong districts was trended of increasing in every year.

• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.110-119
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• 2003

Purpose: Radioiodine (I-131) therapy is an effective modality to reduce both recurrence and mortality rates in differentiated thyroid cancer. Whether higher doses shows higher therapeutic responses was still debatable. The purpose of this study was to validate curve-fitting (CF) method measuring maximum permissible dose (MPD) by a biological dosimetry using metaphase analysis of peripheral blood lymphocytes. Materials and Methods: Therapeutic effects of MPD was evaluated in 58 patients (49 females and 9 males, mean age $50{\pm}11$ years) of papillary thyroid cancer. Among them 43 patients were treated with ${\Leq}7.4GBq$, while 15 patients with ${\geq}9.25GBq$. The former was defined as low-dose group, and the latter high-dose group. Therapeutic response was defined as complete response when complete disappearance of lesions on follow-up I-131 scan and undetectable serum thyroglobulin levels were found. Statistical comparison between groups were done using chi-square test. P value less than 0.05 was regarded as statistically significant. Results: MPD measured by CF method using tracer and therapeutic doses were $13.3{\pm}1.9\;and\;13.8{\pm}2.1GBq$, respectively (p=0.20). They showed a significant correlation (r=0.8, p<0.0001). Exposed doses to blood measured by CF and biological methods were $1.54{\pm}0.03\;and\;1.78{\pm}0.03Gy$ (p=0.01). They also showed a significant correlation (r=0.86, p=0.01). High-dose group showed a significantly higher rate of complete response (12/15, 80%) as compared to the low-dose group (22/43, 51.2%) (p=0.05). While occurrence of side effects was not different between two groups (40% vs. 30.2%, p=0.46). Conclusion: Measurement of MPD using CF method is reliable, and the high-dose I-131 therapy using MPD gains significantly higher therapeutic effects as compared with low-dose therapy.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.272-279
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• 2012

In order to effectively treat livestock wastewater in constructed wetlands by natural purification method, removal velocities of pollutants under different injection methods in constructed wetlands were investigated. The removal velocities of chemical oxygen demand (COD), suspended solid (SS), T-N and T-P by continuous injection method were slightly rapid than those by intermittent injection method in full-scale livestock wastewater treatment plant. The removal velocity (K; $day^{-1}$) of COD by continuous injection method was $0.38\;d^{-1}$ for $1^{st}$ bed, $0.13\;d^{-1}$ for $2^{nd}$ bed, $0.17\;d^{-1}$ for $3^{rd}$ bed, $0.05\;d^{-1}$ for $4^{th}$ bed and $0.17\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of COD in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.210\;d^{-1}$, $0.086\;d^{-1}$, $0.222\;d^{-1}$, $0.053\;d^{-1}$ and $0.137\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of SS by continuous injection method was $0.750\;d^{-1}$ for $1^{st}$ bed, $0.108\;d^{-1}$ for $2^{nd}$ bed, $0.120\;d^{-1}$ for $3^{rd}$ bed, $0.086\;d^{-1}$ for $4^{th}$ bed and $0.292\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of SS in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.485\;d^{-1}$, $0.056\;d^{-1}$, $0.174\;d^{-1}$, $0.081\;d^{-1}$ and $0.227\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of T-N by continuous injection method was $0.361\;d^{-1}$ for $1^{st}$ bed, $0.121\;d^{-1}$ for $2^{nd}$ bed, $109\;d^{-1}$ for $3^{rd}$ bed, $0.047\;d^{-1}$ for $4^{th}$ bed and $0.155\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of T-N in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.235\;d^{-1}$, $0.071\;d^{-1}$, $0.171\;d^{-1}$, $0.058\;d^{-1}$ and $0.126\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of T-P by continuous injection method was $0.803\;d^{-1}$ for $1^{st}$ bed, $0.084\;d^{-1}$ for $2^{nd}$ bed, $0.076\;d^{-1}$ for $3^{rd}$ bed, $0.118\;d^{-1}$ for $4^{th}$ bed and $0.301\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of T-P in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.572\;d^{-1}$, $0.049\;d^{-1}$, $0.090\;d^{-1}$, $0.112\;d^{-1}$ and $0.222\;d^{-1}$, respectively.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.