• 한국노년학
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• v.31 no.1
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• pp.33-47
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• 2011

The purpose of this study was to examine the moderating and mediating effects of social support and social activity on the relationship between depression and quality of life in elderly women living alone. Subjects were 129 elderly living alone at K city in C province, from June to July, 2010. The data was analyzed using the SPSS program for descriptive statistics, Pearson's correlation coefficient and stepwise multiple regression. The degree of depression of elderly living alone was above the average(2.65), and that of quality of life was average(2.80). The correlated factors of quality of life among elderly women living alone included depression(r=-.745, p=.004), social support(r=.544, p=.000), leisure activity(r=.480, p=.024), and economic activity(r=.711, p=.001). Social support was an important mediator between the depression and quality of life in elderly women living alone. The moderating effects of social support and social activity between depression and quality of life in elderly women living alone were not significant. This study suggests that social support considered in enhancing the quality of life programs designed for elderly living alone. Further research needs to be done to refine moderating and mediating effects of social support, social activity including leisure activity, economic activity and volunteer activity.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.117-129
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• 2023

Organizations must seek change in order to adapt to environmental changes and achieve better performance. However, despite this obvious statement, empirical analysis has been almost non-existent due to the difficulty of manipulating organizational performance or change. In this study, we overcame these limitations and analyzed the causes and effects of organizational change by assuming a professional sports team as a venture company, which is relatively easy to objectively measure and evaluate organizational change or performance. We systematically collected and preprocessed traditional and advanced metrics of National Basketball Association (NBA) statistics along with preprocessed trade data from eight years of regular seasons (2014~2015-2021~2022) to analyze our research model. Assessment of process macro model 7 derives the following empirical result. The results of the empirical analysis depict that NBA teams with low organizational performance in the previous season are more likely to make organizational changes through player trades to improve performance. Into the bargain player trades mediate the static relationship between the winning percentage in the previous season and the winning percentage in the current season. However, the indirect effect of a team's previous season's performance on player trades appears to vary depending on the current situations and context of each NBA team. Teams that made the playoffs in the previous season tend to make fewer trades than teams that did not and the previous season's performance is highly correlated with the current season's performance. On the other hand, teams that did not make the playoffs in the previous season tend to make a relatively larger amount of player trades in total, and the mediating effect of trades vanishes in this case. In other words, teams that did not make the playoffs in the previous season experience a larger change in performance due to trades than teams that made the playoffs, even if they achieved the same winning percentage. This empirical analysis of the inverse relationship between organizational change and the performance of professional sports teams has both theoretical and practical implications in the field of sports industry and management by analyzing the fundamentals of organizational change and the performance of professional sports teams.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.119-135
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• 2021

Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.8
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• pp.1210-1218
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• 2005

This study was to investigate the sanitary knowledge and its practice level of school foodservice employees in Jeonju area. A total of 508 questionnaires were usable; resulting in 79.0$\%$ response rate. Statistics data analysis was completed using the SPSS 10.0 program. The results of this study were summarized as follow : About 62$\%$ of school foodservice employees were 41 $\∼$50 years old and 84$\%$ of them had a irregular job and they had a sanitation training at least once a month. The school foodservice employees had more knowledge about 'personal hygiene' than that about 'equipment and facilities sanitation', 'foodborn disease and food microorganism' Their hygiene practice level were high for 'equipment and facilities sanitation' (4.90$\pm$0.25) and were lesser in the order from 'foodborn disease and food microorganism'(4.86$\pm$0.30), 'personal sanitation'(4.79$\pm$0.34) and the least for food processing hygiene (4.70$\pm$0.37). As a result of relationship between knowledge and hygiene practice level, knowledge of school foodservice employees was not influenced on tile hygiene practice level during their working.

• The korean journal of orthodontics
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• v.40 no.6
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• pp.398-410
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• 2010

Objective: The purpose of this study was to investigate the changes in dentofacial morphology of non-orthodontically treated female patients with TMJ disk displacement. Methods: The sample consisted of 25 Korean female patients with bilateral TMJ disk displacement who visited the Department of Orthodontics, Seoul National University Dental Hospital from 1996 to 2006. Disk displacements were diagnosed using the magnetic resonance imaging (MRI) of both TMJs. Baseline (T1) and follow-up (T2) lateral cephalograms were analyzed. The mean age of samples at T1 was $18.1{\pm}3.5$ years (range 14.2 - 25.8 years) and at T2, $21.1{\pm}3.5$ years (range 16.2 - 28.0 years). The mean observation period was $3.0{\pm}1.9$ years. Descriptive statistics for each variable were calculated at baseline (T1) and follow-up (T2) stages, and during the observation period (T2-T1). Results: Skeletal changes were found in 64% of the non-orthodontically treated female patients with TMJ disk displacement during the observation period. The L1 to Mandibular plane distance (mm) increased significantly by 0.8 mm (p < 0.01). But there were no significant differences in the other dental relationship variables (overjet, overbite, U1 to palatal plane) during the observation period. Most patients with skeletal changes showed a backward rotation of the mandible. The ratio of the rotation was a decrease of SNB by $0.43^{\circ}$ for every $1^{\circ}$ increase of FMA (Spearman rho = -0.660, P < 0.01). A few patients showed a distal shift of the mandible without rotation or significant changes in the vertical dimension. Conclusions: During observation periods without orthodontic treatment, non-growing patients with TMJ disk displacement showed dentoskeletal changes, mainly backward rotation of the mandible.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.125-137
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• 2018

Credit unions organized and operated by the members of communities, work-places or groups are co-operative entities where customers act as owners not just transaction partners. The foregoing organizational characteristic of credit unions exerts beneficial effects on their customer relationship, and underscores the need for diversifying their relationship marketing strategies. This study sheds light on the structural relationship of credit unions in terms of principal variables of relationship marketing, i.e. relationship benefits, customer satisfaction and long-term relationship orientation. Specifically, we classify the relationship benefits into three sub-dimensions, i.e. confidence benefits, social benefits and special treatment benefits, and structuralize a causal model involving the customer satisfaction and long-term relationship orientation. From December 26, 2017 to January 26, 2018, A total of 360 questionnaires was collected. Of these, 346 were selected as the final samples, excluding 14, which are difficult to use in statistics. The reliability analysis, exploratory factor analysis, and regression analysis was performed by using the 'SPSS 24.0'. And confirmatory factor analysis, structural equation model analysis was performed by using 'AMOS 24.0'. The findings highlight the following. First, confidence benefits directly impact on the long-term relationship orientation, and indirectly influence the latter by the medium of customer satisfaction. Second, social benefits directly influence the long-term relationship orientation, without exerting any indirect effects on the latter via customer satisfaction. Third, special treatment benefits do not directly impact on the long-term relationship orientation but have indirect effects on the latter by the medium of customer satisfaction. Fourth, customer satisfaction has positive effects on the long-term relationship orientation. The findings suggest credit unions should establish a long-term relationship with their customers by providing them with confidence benefits to earn their trust and confidence, with social benefits to build a relationship of affinity and friendship, and with special treatment benefits to meet their needs in the long, not short and temporary, term.

• Journal of Oriental Neuropsychiatry
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• v.31 no.1
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• pp.1-12
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• 2020

Objectives: The purpose of this study was to evaluate the reliability and validity of the instrument on pattern identification for insomnia (PIT-Insomnia) and verify the correlation between PIT-Insomnia and psychological tests. Methods: Two evaluators examined the pattern identification of the participants who met insomnia disorder diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorder, Fifth Edition (DSM-5) and took the Insomnia Severity Index (ISI) score over 15 once manually and twice using the PIT-Insomnia to measure the inter-rater and test-retest reliability. We also conducted the following surveys: the Pittsburgh Sleep Quality Index (PSQI), the Korean version of Beck's depression inventory (K-BDI), the Korean version of the State-Trait Anxiety Inventory (STAI-K), the Korean Symptom checklist-95 (KSCL-95), and the EuroQol-5 dimension (EQ-5D), to measure concurrent validity and correlation between the PTI-Insomnia and psychological tests. Results: 1. The test-retest reliability analysis of the pattern identification results showed moderate agreement, and test-retest reliability analysis of each pattern identification score showed agreements from poor to moderate. 2. The inter-rater reliability analysis of the pattern identification results via manual showed slight agreement, when analysis was performed with calibration, the inter-rater reliability analysis of the pattern identification results via manual showed fair agreement. 3. The concordance analysis between results via manual and the PIT-Insomnia showed poor agreement, when the analysis was performed with calibration, concordance analysis showed fair agreement. 4. The concordance analysis between the PIT-Insomnia and the PSQI showed positive linear correlation. 5. The concordance analysis between the PIT-Insomnia and the PSQI, K-BDI, STAI-K, KSCL-95, and EQ-5D showed that non-interaction between the heart and kidney have positive linear correlation with the K-BDI, anxiety item of KSCL-95, dual deficiency of the heart-spleen have positive linear correlation with somatization item of KSCL-95, paranoia item of KSCL-95, heart deficiency with timidity have positive linear correlation with stress vulnerability item of KSCL-95, parania item of KSCL-95, phlegm-fire harassing the heart have positive linear correlation with K-BDI, paranoia item of KSCL-95, depressed liver qi transforming into fire have positive linear correlation with the anxiety item of KSCL-95, parania item of KSCL-95, all pattern identification have negative linear correlation with EQ-5D. Conclusions: The PIT-Insomnia has moderate agreement of reliability and reflects the severity of insomnia since it has some concurrent validity with the PSQI. There are some correlations between the PTI-Insomnia with specific psychological tests, so we could suggest it can be used appropriately in the clinical situation.