• Korean Journal of Environmental Biology
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• v.33 no.3
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• pp.345-351
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• 2015

This study was conducted to find out the methodology of carbon budget assessment among soil, atmosphere and plant. Soil respiration, net ecosystem productivity of herbs and net ecosystem productivity of woody plants have been measured in 30 years old pear orchard at Naju. Closed Dynamic Chamber (CDC) method was used to measure soil respiration and net ecosystem productivity of herbs. Net ecosystem productivity of woody plant (pear) was determined by eddy covariance method using the EddyPro (5.2.1) program. As for soil respiration, $429.1mgCO_2m^{-2}h^{-1}$ was released to atmosphere and sensitivity of soil temperature ($Q_{10}$) was 2.3. In case of herbs, respiration was superior to photosynthesis during measurement period. From 20 to 24 Jun 2015, the sum of absorbed and released $CO_2$ by herb's photosynthesis and respiration was $156.1mgCO_2m^{-2}h^{-1}$. Woody plants showed the $680.1mgCO_2m^{-2}h^{-1}$ of absorption by photosynthesis. In a farm scale, the sum of soil respiration, and net ecosystem productivity of herbs and woody plants was $0.04tonCO_2ha^{-1}$ during the measurement period, and it showed that pear orchard act as a $CO_2$ sink. This study using various approaches is expected to present a methodology for evaluating the carbon budget of perennial woody crop plantations.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.59-59
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• 2015

Cryptococcus neoformans causes life-threatening meningoencephalitis in humans, but the treatment of cryptococcosis remains challenging. To develop novel therapeutic targets and approaches, signaling cascades controlling pathogenicity of C. neoformans have been extensively studied but the underlying biological regulatory circuits remain elusive, particularly due to the presence of an evolutionarily divergent set of transcription factors (TFs) in this basidiomycetous fungus. In this study, we constructed a high-quality of 322 signature-tagged gene deletion strains for 155 putative TF genes, which were previously predicted using the DNA-binding domain TF database (http://www.transcriptionfactor.org/). We tested in vivo and in vitro phenotypic traits under 32 distinct growth conditions using 322 TF gene deletion strains. At least one phenotypic trait was exhibited by 145 out of 155 TF mutants (93%) and approximately 85% of the TFs (132/155) have been functionally characterized for the first time in this study. Through high-coverage phenome analysis, we discovered myriad novel TFs that play critical roles in growth, differentiation, virulence-factor (melanin, capsule, and urease) formation, stress responses, antifungal drug resistance, and virulence. Large-scale virulence and infectivity assays in insect (Galleria mellonella) and mouse host models identified 34 novel TFs that are critical for pathogenicity. The genotypic and phenotypic data for each TF are available in the C. neoformans TF phenome database (http://tf.cryptococcus.org). In conclusion, our phenome-based functional analysis of the C. neoformans TF mutant library provides key insights into transcriptional networks of basidiomycetous fungi and ubiquitous human fungal pathogens.

• Progress in Medical Physics
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• v.25 no.3
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• pp.176-184
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• 2014

In this study, we compared dose distributions from simultaneously integrated boost (SIB) method versus the RTOG 0631 protocol for spine radiosurgery. Spine radiosurgery plans were performed in five patients with localized spinal metastases from hepatocellular carcinoma. The computed tomography (CT) and T1- and T2-weighted magnetic resonance imaging (MRI) were fused for delineating of GTV and spinal cord. In SIB plan, the clinical target volume (CTV1) was included the whole compartments of the involved spine, while RTOG 0631 protocol defines the CTV2 as the involved vertebral body and both left and right pedicles. The CTV2 includes transverse process and posterior element according to the extent of GTV. The doses were prescribed 18 Gy to GTV and 10 Gy to CTV1 in SIB plan, while the prescription of RTOG 0631 protocol was applied 18 Gy to CTV2. The results of dose-volume histogram (DVH) showed that there were competitive in target coverage, while the doses of spinal cord and other normal organs were lower in SIB method than in RTOG 0631 protocol. The 85% irradiated volume of VB in RTOG 0631 protocol was similar to that in the SIB plan. However, the dose to normal organs in RTOG 0631 had a tendency to higher than that in SIB plan. The SIB plan might be an alternative method in case of predictive serious complications of surrounded normal organs. In conclusion, although both approaches of SIB or RTOG 0631 showed competitive planning results, tumor control probability (TCP) and normal tissue complication probability (NTCP) through diverse clinical researches should be analyzed in the future.

• Clinics in Shoulder and Elbow
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• v.16 no.1
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• pp.17-26
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• 2013

Purpose: A comparison of the radiographic and the clinical outcomes between two different surgical approaches-Deltoid splitting and Delto-pectoral interval-on the proximal humerus fractures treated by locking compressive plate (LCP), is done. Materials and Methods: Medical records and pre- and postoperative radiographs were reviewed retrospectively for 75 adult patients who underwent surgical fixations with locking compressive plates from May 2005 to December 2011. Patients were divided into two groups according to the surgical methods. Differences in the neck-shaft angle between immediate postoperative period and final follow-up were compared between the two groups. Differences in constant score and Korean shoulder score (KSS) between affected arms and contralateral arms at final follow-up were also compared. Results: The differences in the neck-shaft angle between immediate postoperative period and at final follow-up was 12.04 degrees on average in Deltoid splitting approach and 10.20 degrees in Delto-pectoral interval approach, which was not statistically significant. Differences in constant score/KSS between the affected arm and the contralateral arm were 13.78/22.74 points in deltoid-splitting approach on average and 19.41/31.13 points in Delto-pectoral interval approach, showing that deltoid-splitting approach is significantly superior. Conclusion: Deltoid-splitting approach showed better functional outcomes in the fracture reduction and internal fixation using LCP for the treatment of unstable proximal humerus fractures.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.221-237
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• 2011

This study aims to investigate the environmental equity of the accessibility to urban neighborhood parks in the city of Daegu. The spatial distribution of urban neighborhood parks was explored by spatial statistics and the spatial accessibility to them was then evaluated by both minimum distance and coverage approaches. Descriptive and inferential statistics such as proximity ratio, Mann Whitney U test, and logistic regression were used for comparing the socioeconomic characteristics over different accessibilities to the neighborhood parks and then testing the distributional inequity hypothesis. The results from the minimum distance method indicated that Dalseo-gu had the best accessibility to the neighborhood parks while Dong-gu had the worst accessibility. It was apparent with the coverage method that Dalseo-gu had the best accessibility whereas Dong-gu and Nam-gu had the worst accessibility to the neighborhood parks at 500m and 1,000m buffer distances. There existed the spatial pattern of environmental inequity in old towns with respect to population density and the percentage of people under the age of 18. The spatial pattern of environmental inequity in new towns was explored on the basis of the percentage of people over the age of 65, the percentage of people below the poverty level, and the percentage of free of charge rental housing. These results were closely related to the development process of urban parks in Daegu stimulated by the quantitative urban park policy, urban development process, and residential location pattern such as permanent rental housing and free of charge rental housing. This study further extends the existing research topics of environmental justice related to the distributional inequity of environmental disamenities and hazards by focusing on environmental amenities such as urban neighborhood parks. The results from this study can be used in making the decisions for urban park management and setting up urban park policy with considering the social geography of Daegu.

• Journal of the Korean Arthroscopy Society
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• v.5 no.2
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• pp.74-79
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• 2001

Purpose : The purpose of this study is to evaluate the clinical results after arthroscopic PCL reconstruction and to compare the clinical results after arthroscopic PCL reconstruction using BPTB(bone patellar tendon bone) autograft(Group I : 11 cases), Achilles tendon allograft(Group II : 7 cases) and BPTB allograft(Group 111.6 cases). Materials and Methods : We reviewed the result of 24 patients who had been managed with arthroscopic reconstruction using different graft materials such as BPTB autograft, Achilles tendon allograft and BPTB allograft. Twenty-four patients(average age, 37 years) with PCL rupture were retrospectively evaluated more than one year(average, 31 months) after having arthroscopic posterior cruciate ligament reconstruction. The clinical results were evaluated by IKDC ligament standard evaluation form, using $KT-2000^{TM}$ knee ligament arthrometer and also evaluated Lysholm knee scoring scale. Results : The final evaluation was nearly normal in 11 patients($45\%$ in Group I, $43\%$ in Group II, $50\%$ in Group III). The corrected posterior sagging was abnormal(side to side difference more than 6mm) in 8 patients($36\%$ in Group I, $29\%$ in Group II, $33\%$ in Group III). We could not find significant difference among three groups by IKDC scale. Conclusion : Comparing with other reports, our overall results were not satisfactory. And also, we could not find any remarkable difference among the three groups. Further research is necessary to evaluate new surgical approaches as well as improved techniques for capsular and collateral ligament injuries.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Korean Journal of Ecology and Environment
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• v.50 no.2
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• pp.238-253
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• 2017

The sewage and wastewater (SAW) are a well-known major source of eutrophication and greentide in freshwaters and also a potential source of thermal pollution; however, there were few approaches to thermal effluent of SAW in Korea. This study was performed to understand the behavioral dynamics of the thermal effluents and their effects on the water quality of the connected streams during winter season, considering domestic sewage, industrial wastewater and hot spring wastewater from December 2015 to February 2016. Sampling stations were selected the upstream, the outlet of SAW, and the downstream in each connected stream, and the water temperature change was monitored toward the downstream from the discharging point of SAW. The temperature effect and its range of SAW on the stream were dependent not only on the effluent temperature and quantity but also on the local air temperature, water temperature and stream discharge. The SAW effects on the stream water temperature were observed with temperature increase by $2.1{\sim}5.8^{\circ}C$ in the range of 1.0 to 5.5 km downstream. Temperature effect was the greatest in the hot spring wastewater despite of small amount of effluent. The SAW was not only related to temperature but also to the increase of organic matter and nutrients in the connected stream. The industrial wastewater effluent was discharged with high concentration of nitrogen, while the hot spring wastewater was high in both phosphorus and nitrogen. The difference between these cases was due to with and without chemical T-P treatment in the industrial and the hot spring wastewater, respectively. The chlorophyll-a content of the attached algae was high at the outlet of SAW and the downstream reach, mostly in eutrophic level. These ecological results were presumably due to the high water temperature and phosphorus concentration in the stream brought by the thermal effluents of SAW. These results suggest that high temperature of the SAW needs to be emphasized when evaluating its effects on the stream water quality (water temperature, fertility) through a systematized spatial and temporal investigation.