• Korean Journal of Ecology and Environment
• /
• v.57 no.1
• /
• pp.1-16
• /
• 2024

Most wetlands worldwide have suffered from extensive human exploitation. Unfortunately they have been less explored compared to river and lake ecosystems despite their ecological importance and economic values. This is the same case in Korea. This study was aimed to estimate the assemblage attributes and distribution characteristics of benthic macroinvertebrates for fifty wetlands distributed throughout subtropical Jeju Island in 2021. A total of 133 taxa were identified during survey periods belonging to 53 families, 19 orders, 5 classes and 3 phyla. Taxa richness ranged from 4 to 31 taxa per wetland with an average of 17.5 taxa. Taxa richness and abundance of predatory insect groups such as Odonata, Hemiptera and Coleoptera respectively accounted for 67.7% and 68.2% of the total. Among them Coleoptera were the most diverse and abundant. Taxa richness and abundance did not significantly differ from each wetland type classified in accordance with the National Wetland Classification System. There were three endangered species (Clithon retropictum, Lethocerus deyrolli and Cybister (Cybister) chinensis) and several restrictively distributed species only in Jeju Island. Cluster analysis based on the similarity in the benthic macroinvertebrate composition largely classified 50 wetlands into two major clusters: small wetlands located in lowland areas and medium-sized wetlands in middle mountainous regions. All cluster groups displayed significant differences in wetland area, long axis, percentage of fine particles and macrophyte composition ratio. Indicator Species Analysis selected 19 important indicators with the highest indicator value of Ceriagrion melanurum at 63%, followed by Noterus japonicus (59%) and Polypylis hemisphaerula (58%). Our results are expected to provide fundamental information on the biodiversity and habitat environments for benthic macroinvertebrates in wetland ecosystems, consequently helping to establish conservation and restoration plans for small wetlands relatively vulnerable to human disturbance.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.1
• /
• pp.9-18
• /
• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.19 no.4
• /
• pp.231-241
• /
• 2024

Discovering innovative startups that use public technologies from universities and government-funded research institutes is crucial for maintaining national competitiveness. Advancing public R&D technology, discovering entrepreneurs from research institutes, and fostering and investing in deep-tech startups are very important at the national level. However, there is a lack of research on activating startups using public technologies, and research analyzing each governance entity is needed to activate the innovation startup ecosystem. Therefore, this study conducted an empirical analysis of the priorities for revitalizing the innovation startup ecosystem among researchers, research institutes, innovative startups, and the government, which constitute the public technology governance. The results of this study revealed that the sustainability of innovative startups (0.308), government innovation startup activation (0.298), research institutions discovering and fostering startups (0.221), and researcher's characteristics (0.173) were the most significant factors in the public R&D technology innovation startup ecosystem. And the sub-factors of researcher's characteristics, seizing business opportunities (0.305) was most important, and creating a startup-friendly culture (0.293) was most important among the sub-factors of research institutions discovering and fostering startups. Investment funds and procurement (0.373) was the most critical sub-factor for the sustainability of innovative startups, while a dedicated fund for public technology (0.305) was the most important among the sub-factors of government schemes for promoting innovative startups. A total of 20 factors were analyzed sequentially according to their importance in the weights for evaluation factors and sub-factors. By sub-factor, investment and financing for innovative startups (0.115), dedicated government fund for public technology (0.091), securing high-quality human resources for innovative startups (0.078), improving government regulations and permits related to innovative technologies (0.074), and creating a startup-friendly culture in research institutions (0.065) were the most important. This result emphasizes the significance of securing competitiveness to become a sustainable public technology startup. In addition, based on entrepreneurship experience, 'dedicated funding for public technology' was most important for the group with startup experience, while the group with no experience needed more 'investment and funding'. Furthermore, By region, 'improving government regulations and permits' was the highest priority in the Seoul metropolitan area, while 'attracting investment and financing' was the most important in Daejeon. Therefore, the results of this research, it is important to give policy priority to innovative startup companies in order to activate the innovation startup ecosystem in the public technology sector. The political and practical implications were derived that long-term (10 years or more) investment and funding for deep tech companies and the establishment of public technology-only funds are the most urgent and important.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.38 no.6
• /
• pp.694-708
• /
• 2009

The principal objective of this study was to determine the effects of smoking & drinking on the diet, nutrient intake, and overall health. A sample of 262 youths, aged 16 to 18 year-old, was randomly selected from Seoul and its vicinity. The subjects participated by answering survey questions including general questions, questions regarding health, smoking & drinking habits, dietary habits, nutrient intake, physical characteristics, and smoking cessation plans. The average height, weight, and BMI of the subjects were $173.5{\pm}6.8\;cm$, $64.8{\pm}11.8\;kg$, and $21.4{\pm}3.7\;kg/m^2$, respectively. Among the subjects, 88% appeared to be interested in health and 43.5% of youth asserted that the best way to keep healthy was to engage in regular exercise. Among 63 smokers, 52 students (82.5%) used alcoholic beverages while 11 students (17.5%) did not use alcoholic beverages, meaning that smoking was a causative factor in drinking. 55.6% of youth reported beginning to smoke in middle school, and 38.1% of them asserted that curiosity was the motive for smoking. The youth reported that the craving for smoking was highest when hungry, and the best place to smoke was the restroom. 20 students (69.0%) answered that the only way to quit smoking was just to stop. 12 students (44.4%) reported that the main reason for failures in smoking cessation attempts was a lack of intention or willpower. 87.1% of all subjects answered that they were inclined to quit smoking, and 56.7% of them would be interested in attending a smoking cessation program if they had the opportunity. Among the smoking and drinking group, 50% of drinkers began to drink in high school, and the reason for drinking given was peer pressure-40% of drinkers answered that they wished to quit drinking. 34.4% of students appeared to have breakfast everyday, but 16.4% of students answered that they had quit eating breakfast. 52.5% of all students reported that the principal reason for overeating was the presence of one's favorite food, and the smoking and drinking group reported overeating more frequently than other groups (p<0.05). 72.6% of all subjects reported eating interim meals $1{\sim}2$ times daily, 36.4% of smokers ate carbonated beverages, 38.5% ate ice cream as a interim meal, and 38.5% of the drinking and smoking groups ate fruits, 26.9% of them ate fried foods, and some of them ate fast foods as a interim meal. Among smokers, the ratio of eating fat-rich foods, and meats such as kalbi and samgyupsal more than two times per week was higher, and 54.3% of smokers ate ice cream, cookies, and carbonated beverages more than two times per week (p<0.05). The total nutrient intake of the $15{\sim}19$-year youth group was much higher than the standard value. The energy intake of the smoking group and the drinking and smoking group was significantly higher than that of the normal group (p<0.05). Intakes of phosphorus (p<0.05), cholesterol (p<0.05), and sodium (p<0.05) were the highest among all groups. Accordingly, it is recommended that practical education programs be implemented to teach young students to resist peer pressures to smoke and drink. Additionally, education that acknowledges the importance of nutrition is necessary to avoid preferential eating and overeating due to smoking and drinking.such education can also teach students to eat a balanced diet and improve their physical development.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.59-77
• /
• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of Nutrition and Health
• /
• v.46 no.4
• /
• pp.346-356
• /
• 2013

This study investigated the daily physical activity level, energy expenditure, energy balance, and body composition and their relationship with university students. The participants were 130 male students ($19.5{\pm}0.5$ yrs) and 139 female students ($19.5{\pm}0.3$ yrs) at a university in Chungnam province. Physical activity level was evaluated by an equation based on 24 hr-activity record and dietary nutrient intake was evaluated using the food record method during a three-day period consisting of two week days and one weekend. Body composition was measured using Inbody 430 (Biospace Co., Cheonan, Korea). As a result, mean body mass index (BMI) of subjects indicated that they had normal weight, however mean body fat ratio was $19.1{\pm}5.4%$ for males and $28.4{\pm}5.0%$ for females, indicating that they had higher than normal weight. Daily mean physical activity level was 1.55 for males and 1.47 for females, which was regarded as 'low active', respectively. Females had more light activity than males (p<0.01). Daily mean energy expenditure was $2,803.5{\pm}788.9$ kcal/d for males and $1,915.4{\pm}510.2$ kcal/d for females (p<0.001). Daily mean dietary energy intake was $2,327.0{\pm}562.5$ kcal/d for males and $1,802.1{\pm}523.6/d$ for females (p<0.001), and daily mean energy balance was $-476.5{\pm}955.9$ kcal/d for males and $-113.3{\pm}728.1$ kcal/d for females (p<0.01). Daily mean dietary intake of protein, vitamins, and minerals, except Ca, satisfied recommended nutrient intake. Daily energy expenditure was positively related to body weight (p<0.01), BMI (p<0.01), and fat free mass ratio (p<0.05), but was negatively related to body fat ratio (p<0.01). In conclusion, subjects had a negative energy balance and low physical activity. They had a normal weight by BMI but had a more fat than normal weight by body fat ratio. This appears to be related to their low physical activity. Thus, nutrition education should be provided for university students in order to increase their physical activity for maintenance of normal weight by body composition and health promotion.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.12 no.4
• /
• pp.47-60
• /
• 2017

As the recent cultural contents area start-ups are creating remarkable outcomes such as investment attraction together with the reinforced institutional supports from the government, this study aimed to reverify the significance of researches related to correlation analysis between service of Business Incubating Center of Small & Medium Business Administration operated with no separation of business type, and corporate performance, in the aspect of Business Incubating Center in cultural contents area, and also to suggest the importance of establishing the business incubating system in the systematic and rational cultural contents area through the differentiated business incubating service by verifying the significant effects of the business validity of items on corporate performance, and then discovering services suitable for business incubating in cultural contents area, targeting Gyeonggi-do cultural contents area Business Incubating Center recently showing the biggest growth. Especially, contrary to the existing researches, in order to verify the characteristics of Gyeonggi-do Cultural Contents Business Incubating Center, the personal support service and marketing support service were included. It also aimed to understand the effects of the business validity of start-up items on corporate performance. Summarizing the results of this study, contrary to the results of the existing researches saying that spatial & additional support service, management support service, technical support service, personal support service, and marketing support service had significant effects on corporate performance, among the support service of Gyeonggi-do cultural contents area Business Incubating Center, the spatial & additional support service, personal support service, and marketing support service had significantly positive(+) effects on corporate performance while the management support service and technical support service had no significant effects on it. Comparing with the results of the researches on the support service of Business Incubating Center(BI) of Small & Medium Business Administration, the effects of the management support service and technical support service of Gyeonggi-do cultural contents area Business Incubating Center on corporate financial/non-financial performance were not huge. Also, in the results of analyzing the business validity of star-up items, the spatial & additional support service, management support service, and technical support service did not have significant effects on the business validity of start-up items while the personal support service and marketing support service had significantly positive(+) effects on it. In case when selecting companies, Gyeonggi-do Business Incubating Center emphasized the business validity of start-up items. However, the support service provided after the selection did not have huge effects on the business validity of start-up items. Lastly, in the results of analyzing the effects of the business validity of start-up items in Gyeonggi-do cultural contents area on corporate performance, among the success factors of business start-up, the business validity of start-up items was an important element having effects on corporate performance(financial/non-financial) in the cultural contents area.

• Journal of Intelligence and Information Systems
• /
• v.20 no.3
• /
• pp.109-131
• /
• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.49-65
• /
• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Genetic Medicine
• /
• v.7 no.2
• /
• pp.125-132
• /
• 2010

Purpose: Preimplantation genetic diagnosis (PGD), also known as embryo screening, is a pre-pregnancy technique used to identify genetic defects in embryos created through in vitro fertilization. PGD is considered a means of prenatal diagnosis of genetic abnormalities. PGD is used when one or both genetic parents has a known genetic abnormality; testing is performed on an embryo to determine if it also carries the genetic abnormality. The main advantage of PGD is the avoidance of selective pregnancy termination as it imparts a high likelihood that the baby will be free of the disease under consideration. The application of PGD to genetic practices, reproductive medicine, and genetic counseling is becoming the key component of fertility practice because of the need to develop a custom PGD design for each couple. Materials and Methods: In this study, a survey on the contents of genetic counseling in PGD was carried out via direct contact or e-mail with the patients and specialists who had experienced PGD during the three months from February to April 2010. Results: A total of 91 persons including 60 patients, 49 of whom had a chromosomal disorder and 11 of whom had a single gene disorder, and 31 PGD specialists responded to the survey. Analysis of the survey results revealed that all respondents were well aware of the importance of genetic counseling in all steps of PGD including planning, operation, and follow-up. The patient group responded that the possibility of unexpected results (51.7%), genetic risk assessment and recurrence risk (46.7%), the reproduction options (46.7%), the procedure and limitation of PGD (43.3%) and the information of PGD technology (35.0%) should be included as a genetic counseling information. In detail, 51.7% of patients wanted to be counseled for the possibility of unexpected results and the recurrence risk, while 46.7% wanted to know their reproduction options (46.7%). Approximately 96.7% of specialists replied that a non-M.D. genetic counselor is necessary for effective and systematic genetic counseling in PGD because it is difficult for physicians to offer satisfying information to patients due to lack of counseling time and specific knowledge of the disorders. Conclusions: The information from the survey provides important insight into the overall present situation of genetic counseling for PGD in Korea. The survey results demonstrated that there is a general awareness that genetic counseling is essential for PGD, suggesting that appropriate genetic counseling may play a important role in the success of PGD. The establishment of genetic counseling guidelines for PGD may contribute to better planning and management strategies for PGD.