• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.5
• /
• pp.151-168
• /
• 2022

Nowadays companies are required to achieve social goals beyond maximizing shareholder profits. Accordingly, it is important to pursue both the economic and social goals of a company at the same time. Thus the importance of hybrid organizations is increasing theoretically and practically. In particular, since hybrid organizations essentially have the complexity of pursuing both economic and social purposes, the institutional demands of various stakeholders surrounding hybrid organizations are also conflicting. Several previous studies have considered how hybrid organizations respond to these conflicting institutional demands, but most studies are limited to studying at a specific point in time. As a result, there was a limit to analyzing the dynamics in response to conflicting institutional demands as the hybrid organization expanded its business. This study predicted that the hybrid organization would take selective coupling with conflicting institutional demands and that the process of responding to institutional demands would change according to the organization's growth. In this study, we had a case study about Noul and Enuma, social ventures that operate relatively advanced business models with outstanding results in innovation and technology. As a result, social ventures show a selective coupling for conflicting institutional demands, and the selective coupling process changes as their business model are advanced. Specifically, in the early stages of the business, it appears to respond to economic and social demands at the same time with a single business model. When the business is advanced, two or more business models are operated, some of which respond to economic needs and some of which respond to social needs. In the early stages of business, social ventures respond to economic and social demands with a single business model to gain legitimacy and survive in the institutional demands. But when they enter the business growth period, they try to separate business models which respond to economic and social values because they pursue sustainable growth and challenge large-scale missions. Overall, this study attempted to contribute to an in-depth understanding of hybrid organizations by identifying that the method of responding to conflicting institutional demands varies depending on the growth process of social ventures.

• Korean Journal of Ecology and Environment
• /
• v.57 no.2
• /
• pp.102-110
• /
• 2024

This study presents a fine scale distribution of the endangered species, Odontobutis obscura, through field surveys and literature reviews. Using the mark-recapture method, the population size in major habitats was determined. Field surveys conducted on 18 streams in Geoje Island revealed that the O. obscura was only found in the main streams and tributaries of the Sanyang, Gucheon, and Buchun Streams, which are part of the Sanyang Stream watershed. The O. obscura exhibited relative abundances ranging from 0.5% to 35.3% at different locations, with certain spots showing higher relative abundances (18.8% to 35.3%), indicating major habitat areas. A review of six literature studies confirmed the presence of the O. obscura, although there were differences in occurrence status depending on the purpose, scope, and duration of the studies. Combining the results of field and literature surveys, it was found that the O. obscura inhabits the main and tributary streams of the Sanyang, Gucheon, and Buchun Streams, from the upper to lower reaches. Currently, the O. obscura population in the Sanyang Stream watershed maintains a stable habitat, but its limited distribution range suggests potential issues such as genetic diversity deficiency in the long term. The population size of the O. obscura was confirmed at two specific locations, with densities of 0.5 to 1.5 individuals per m². The average movement distance from the release point was 13.1 m, indicating the limited mobility characteristic of ambush predators. Understanding the distribution and population size of endangered species is the first step towards their conservation and protection. Based on this information, further research could significantly contribute to the conservation of the O. obscura.

• Korean Journal of Remote Sensing
• /
• v.40 no.4
• /
• pp.387-396
• /
• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of Animal Science and Technology
• /
• v.48 no.6
• /
• pp.933-942
• /
• 2006

This experiment was carried out to investigate effects of honeybee venom treatment on the humoral immune response in pigs. Corresponding author : S. K. Cho, Dept. of Animal Sci. Chung-Buk National University, Kaesin-dong, Cheongju, 361-763, Korea. phone : 043-261-2551. E-mail : deercho@chungbuk.ac.kr To investigate effects of natural honeybee venom on the concentration of immunoglobulin G, A, and M, 20 piglets(LY×D) from 3 sows were allocated into two groups bee venom-treated group(10 piglets) and non-treated control(10 piglets). Natural honeybee venom was treated at 0, 3, 6 days after birth and the acupoints were Hai-men(ST-25), Du-kou(CV-8) and Jiao-chao(GV-1) points at 0, 3 days after birth and the regions of castration and tail amputation point at 6 days. Control group was injected 1㎖ of saline to the same site. Concentrations of IgG, A, and M were measured with immunoturbidimetric method at 0, 3, 7, 14, and 21 days after treatment. To investigate the effect of bee venom on the production of antibodies against hog cholera and atrophic rhinitis vaccines that were used as indicator antigens, 40 piglets(LYxD) from 5 sows were grouped as bee venom-treated group (20 piglets) and control group(20 piglets). Natural honeybee venom was treated at 0, 3days(castration, tail amputation) and 21days after birth. The acupoints were Hai-men(ST-25), Du-kou(CV-8) and Jiao-chao (GV-1) points at 0 day, the regions of castration and tail ampution at 3 days and Jiao-chao(GV-1) and Bai-hui(GV-20) points at 21days after birth(weaning). Control group was injected 1ml of saline to the same site. Atrophic rhinitis vaccine was injected twice at 24 and 44 days after birth and hog cholera vaccine was also injected twice at 44 and 64 days after birth. Antibody titers against Bordetella bronchiseptica and hog cholera virus were measured by using tube agglutination and ELISA tests at 24, 34, 44, 54 and 74 days after birth. Concentrations of IgG of treated group were 339.52, 366.48, 296.52, 242.06 and 219.06mg/dl at 0, 3, 7, 14 and 21 days after birth, respectively. In contrast, concentrations of IgG in control group were respectively 347.10, 334.14, 243.28, 205.18 and 191.58mg/dl during same periods with treated group. Concentrations of IgG at 0 day was not significantly different between the treated group and control group but treated group were significantly increased by 10.28% at 3 days after birth (P<0.02), 21.88% at 7 days after birth(P<0.01), 18.0% at 14 days after birth(P<0.07) and 14.3% at 21 days after birth(P<0.01). Concentrations of IgA and Ig M were not significantly different. Antibody titers against hog cholera virus were significantly increased by 57.0% at 24 days after birth(P<0.03), 74.6% at 34 days after birth (P<0.006), 48.6% at 44 days after birth(P<0.017), 45.0% at 54 days after birth(P<0.16) and 44.4% at 74 days after birth (P<0.006) in bee venom treated group in comparison with control group. Antibody titers against the Bordetella bronchiseptica was significantly increased in Beevenom treated group as 9.1% (P<0.32) at 24days, 39.7% (P<0.002) at 34days, 31.9% (P<0.02) at 44days, 33.4% (P<0.01) at 54days and 57.3% (P<0.007) at 74 days after birth when compared with those of control group pigs. Collecting together, the results in this study showed that immune responses were increased by treatment of natural honeybee venom to pigs. These results suggested that the treatment of bee venom could be used effectively for the increase of productivity in livestock industry.

• Journal of Chest Surgery
• /
• v.41 no.3
• /
• pp.320-328
• /
• 2008

Background: Numerous surgical devices for mitral repair have been used in the past with good results. In this study we describe a simple annuloplasty technique with using a new device ($Mitracon^{(R)}$). The aim of this study was to assess its efficacy and surgical results with using $Mitracon^{(R)}$. Material and Method: From May 2003 to October 2005, 46 patients (21 women and 25 men (mean age of $51.4{\pm}17.8$ years) with mitral regurgitation from various causes were treated with either the $Mitracon^{(R)}$ (the $Mitracon^{(R)}$ group) or the Capentier Edward rigid ring (the CE group). The median follow-up duration was 18.9 months. Result: The mean grade of mitral regurgitation before and immediately after surgery in the $Mitracon^{(R)}$ group and the CE group decreased from $3.2{\pm}0.8$ to $0.6{\pm}0.7$ and $3.4{\pm}0.7$ to $0.3{\pm}0.5$, respectively. There were no significant changes in the ejection fraction either between the two groups or before and immediately after surgery. No deaths were seen in either group. Early postoperative echocardiography of all 46 patients showed only trivial mitral regurgitation or none at all. Echocardiography at a median of 18.9 months also showed no progression in mitral regurgitation. The mean grade of mitral regurgitation in the $Mitracon^{(R)}$ group at this time point decreased from $3.2{\pm}0.8$ to $0.8{\pm}0.7$ (p<0.05). The CE group also showed a similar degree of decrease from $3.4{\pm}0.7$ to $0.3{\pm}0.6$ (p<0.05). The mitral valve area in the $Mitracon^{(R)}$ group at 1 year follow-up was $3.3{\pm}0.9cm^2$. The mitral valve area in the CE group was $2.7{\pm}0.6cm^2$. The mean mitral pressure gradient in the $Mitracon^{(R)}$ group at 1 year follow-up was $3.1{\pm}1.3$ mmHg. The mean pressure gradient in the CE group was $4.5{\pm}2.1$ mmHg, although any statistical significant difference for this between the groups was not reached. Conclusion: The present study showed the described technique to be safe and effective in the intermediate term. Because long term results are unavailable, a more extensive prospective randomized multicenter trial may be warranted to determine whether this procedure should be generally applied for repair of mitral valve disease.

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.45-69
• /
• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.33 no.10
• /
• pp.1634-1640
• /
• 2004

This study was designed to compare the nutritional intake and iron nutritional status between urban and rural middle school girls. Along with a questionnaire, blood samples were obtained from 311 middle school girls (urban 129 girls, rural 182 girls). Nutrient intakes were measured with a convenient method, and clinical symptoms relating anemia was investigated by 4-point Likert scale. For the nutrient intake, the total energy intake was 1722.2 kcal (82.0% of RDA) for the urban group and 1649.5 kcal (78.6% of RDA) for rural group. The rural group showed significantly lower level than the urban group in all nutrients except fat, carbohydrate and total energy intake. Regarding the food frequency, students from the rural group marked significantly lower intake of milk (p<0.00l), kimchi (p<0.05), fruit (p<0.05), tofu, bean (p<0.00l) than the urban group. For every clinical finding regarding anemia, the rural group marked higher value than the urban group but the difference was not significant. The hemoglobin concentration of urban group was 13.28 g/dL, and rural group showed 12.51 g/dL which was significantly lower than urban group (p<0.00l). The hematocrit rate was 37.82% for the urban group and 38.13% for the rural group and there was no significant difference between two groups. The red blood cell (RBC) count of the rural group was significantly lower than the urban group (p<0.00l). Evaluating with the iron deficiency standard which is less than 12 g/dL, the urban group was 6.2% and the rural group was 34.6% thus the deficiency rate was significantly higher in the rural group. This study showed that nutrient and iron status of the girls of rural group is not as good as the urban group. As middle school girls require high level of iron absorption due to blood loss which occurs during abrupt physical growth and menstruation, dietary counselling is required to enhance the iron status. When iron deficiency is serious, they need to take more positive action such as iron supplement in addition to food-iron fortification.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.59-83
• /
• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Tuberculosis and Respiratory Diseases
• /
• v.47 no.6
• /
• pp.775-785
• /
• 1999

Background : Though surgery plays an important role in the management of patients with Mycobacterium tuberculosis infection, there is little information regarding the timing of resection. We tried to find out the ideal timing of operation. Method: A retrospective review was performed in 69 patients underwent pulmonary resection for pulmonary tuberculosis between January 1993 and December 1997. They were categorized into various groups according to the length of preoperative specific drug therapy. The rates of treatment failure, realpse and complication in each group were compared statistically by $x^2$-test. Results: Eighty one point two percent were men and 18.8 % women with a median age of 33 years(range, 16 to 63 years). The mean number of resistant drugs was 3.l(range, 0 to 9). Patients were treated preoperatively with multidrug regimens, which mean number of preoperative specific drugs was 4.6, in an effort to reduce the mycobacterial burden with the mean length of preoperative drug therapy, 5.0 months. Postoperative treatment was conducted for a mean period of 13.0 months with a mean number of postoperative specific drugs, 4.4. Postoperative treatment failures were confirmed in 8 among 69 patients(11.6%). 2 of these 8 patients were showed up in the preoperative 3 to 4 months medication group and each of the rest was occurred in the preoperative 2 to 3, 5 to 6, 6 to 7, 12 to 13, 17 to 18 months, less than one month medication group, respectively. 59 of 69 patients were available for evaluation of the relapse rate with the mean duration of the postoperative follow-up, 19.8 months. In 4 patients bacterial relapse was confirmed(6.8%). Each of these 4 was in the preoperative 1 to 2, 2 to 3, 3 to 4, 5 to 6 months medication group. Categorized into various groups according to the length of preoperative specific therapy, there were no statistical significances of the treatment failure rate, relapse rate and complication rate in the groups. There were seven treatment failures of 28 who were AFB culture positive until the time of operation(25%, p<0.01). Categorized the preoperative AFB culture positive group into various groups according to the length of preoperative drug therapy, there were no statistical significances, either. Conclusion: We believe that operation plays an important ancillary role in the treatment of pulmonary tuberculosis. Our results indicate that the timing of resection according to the length of preoperative drug therapy may not cause trouble.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.36 no.3
• /
• pp.115-127
• /
• 2018

This study was attempted to find out the value of cultural assets through the clear diagnosis and prescription of the dead and weakness factors of the Population of Retusa Fringe Trees in Pyeongji-ri, Jinan(Natural Monument No. 214), The results are as follows. First, Since the designation of 13 natural monuments in 1968, since 1973, many years have passed since then. In particular, despite the removal of some of the buried soil during the maintenance process, such as retreating from the fence of the primary school after 2010, Second, The first and third surviving tree of the designated trees also have many branches that are dead, the leaves are dull, and the amount of leaves is small. vitality of tree is 'extremely bad', and the first branch has already been faded by a large number of branches, and the amount of leaves is considerably low this year, so that only two flowers are bloomed. The second is also in a 'bad'state, with small leaves, low leaf density, and deformed water. The largest number 1 in the world is added to the concern that the s coverd oil is assumed to be paddy soils. Third, It is found that the composition ratio of silt is high because it is known as '[silty loam(SiL)]'. In addition, the pH of the northern soil at pH 1 was 6.6, which was significantly different from that of the other soil. In addition, the organic matter content was higher than the appropriate range, which is considered to reflect the result of continuous application for protection management. Fourth, It is considered that the root cause of failure and growth of Jinan pyeongji-ri Population of Retusa Fringe Trees group is chronic syndrome of serious menstrual deterioration due to covered soil. This can also be attributed to the newly planted succession and to some of the deaths. Fifthly, It is urgent to gradually remove the subsoil part, which is estimated to be the cause of the initial damage. Above all, it is almost impossible to remove the coverd soil after grasping the details of the soil, such as clayey soil, which is buried in the rootstock. After removal of the coverd soil, a pestle is installed to improve the respiration of the roots and the ground with Masato. And the dead 4th dead wood and the 5th and 6th dead wood are the best, and the lower layer vegetation is mown. The viable neck should be removed from the upper surface, and the bark defect should undergo surgery and induce the development of blindness by vestibule below the growth point. Sixth, The underground roots should be identified to prepare a method to improve the decompression of the root and the respiration of the soil. It is induced by the shortening of rotten roots by tracing the first half of the rootstock to induce the generation of new roots. Seventh, We try mulching to suppress weed occurrence, trampling pressure, and soil moisturizing effect. In addition, consideration should be given to the fertilization of the foliar fertilizer, the injection of the nutrients, and the soil management of the inorganic fertilizer for the continuous nutrition supply. Future monitoring and forecasting plans should be developed to check for changes continuously.