• The Korean Journal of Franchise Management
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• v.10 no.2
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• pp.33-47
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• 2019

Purpose - The purpose of this study is to classify and analyze existing studies from various angles through systematic literature review of how human resources development has been researched in the domestic franchise business. These studies are intended to suggest the direction in which human resource development research should be conducted in the future in the franchise business. Research design, data, and methodology - This study is based on systematic literature review methodology. It has gone through the process of subject language setting, literature search routing, search term selection, literature selection, literature classification and literature analysis. The systematic literature review identified 59 peer-reviewed dissertations and scientific journal publications on the subject of HRD in Korea franchise business. Result - This study analyzed by research methods, research industries, research population and dependent variable using the systematic review process. The literature studied in the 2000s mainly led to research on education and training of franchise employees in beauty franchise business. In the literature studied since 2010, human resources development was mainly studied in the supervisor in the restaurant franchise business, and in the study of competence rather than education and training. According to the research methods, statistical methods were mostly relatively simple, such as t-test or one-way distribution analysis until the 2000s, and after 2010, in-depth and structural studies using multiple return analysis, structural method analysis, path analysis, multi-dimensional scale analysis, AHP, etc were conducted. When classified by study dependant, early research until the 2000s focused on the study of education and training, which is an independent variable, on the satisfaction of education programs, job satisfaction, and immersion. On the other hand, studies conducted since 2010 have produced more complex results using various medium variants, and those related to management performance and relationship performance have been mainly studied, rather than the satisfaction of the education itself. Conclusions - While the domestic franchise business is expanding in terms of quantity, such as the number of franchises and franchises, the development in terms of quality for the joint growth of franchises and franchisees is still lacking. In order for the franchisee to continue to grow with each other, the franchisee must identify and develop their current performance or expected capabilities through capacity modeling at various targets and levels.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.393-413
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• 2021

Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.

• Structural Engineering and Mechanics
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• v.78 no.1
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• pp.41-52
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• 2021

Inelastic static pushover analysis has been used in the academic-research widely for seismic analysis of structures. Nowadays, the variety pushover analysis methods have been developed, including Modal pushover, Adaptive pushover, and Cyclic pushover, in which some weaknesses of the conventional pushover method have been rectified. In the conventional pushover analysis method, the effects of cumulative growth of cracks are not considered on the reduction of strength and stiffness of RC members that occur during earthquake or cyclic loading. Therefore, the Cyclic Pushover Analysis Method (CPA) has been proposed. This method is a powerful technique for seismic evaluation of regular reinforced concrete buildings in which the first mode of them is dominant. Since the bridges have different structures than buildings, their results cannot necessarily be attributed to bridges, and more research is needed. In this study, a cyclic pushover analysis with four loading protocols (suggested by valid references) by the Opensees software was conducted for seismic evaluation of two regular reinforce concrete bridges. The modeling method was validated with the comparison of the analytical and experimental results under both cyclic and dynamic loading. The failure mode of the piers was considered in two-mode of flexural failure and also a flexural-shear failure. Along with the cyclic analysis, conventional analysis has been studied. Also, the nonlinear incremental dynamic analysis (IDA) method has been used to examine and compare the results of pushover analyses. The time history of 20 far-field earthquake records was used to conduct IDA. After analysis, the base shear vs. displacement in the middle of the deck was drawn. The obtained results show that the cyclic pushover analysis method is able to evaluate an accurate seismic behavior of the reinforced concrete piers of the bridges. Based on the results, the cyclic pushover has proper convergence with IDA. Its accuracy was much higher than the conventional pushover, in which the bridge piers failed in flexural-shear mode. But, in the flexural failure mode, the results of each two pushover methods were close approximately. Besides, the cyclic pushover method with ACI loading protocol, and ATC-24 loading protocol, can provided more accurate results for evaluating the seismic investigation of the bridges, specially if the bridge piers are failed in flexural-shear failure mode.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.549-566
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• 2022

Recently, artificial intelligence (AI) technology has progressed rapidly, and industries using this technology are significantly increasing. Further, analysis research using text mining, which is an application of artificial intelligence, is being actively developed in the field of social science research. About 125 laws, including joint laws, have been enacted under the Ministry of Oceans and Fisheries in various sectors including marine environment, fisheries, ships, fishing villages, ports, etc. Research on the laws under the Ministry of Oceans and Fisheries has been progressively conducted, and is steadily increasing quantitatively. In this study, the domestic research trends were analyzed through text mining, targeting the research papers related to laws of the Ministry of Oceans and Fisheries. As part of this research method, first, topic modeling which is a type of text mining was performed to identify potential topics. Second, co-occurrence network analysis was performed, focusing on the keywords in the research papers dealing with specific laws to derive the key themes covered. Finally, author network analysis was performed to explore social networks among authors. The results showed that key topics have been changed by period, and subjects were explored by targeting Ship Safety Law, Marine Environment Management Law, Fisheries Law, etc. Furthermore, in this study, core researchers were selected based on author network analysis, and the tendency for joint research performed by authors was identified. Through this study, changes in the topics for research related to the laws of the Ministry of Oceans and Fisheries were identified up to date, and it is expected that future research topics will be further diversified, and there will be growth of quantitative and qualitative research in the field of oceans and fisheries.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.83-92
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• 2022

The 2020 summer extreme flood severely disturbed the riparian ecosystem of the Seomjin River. Some trees were killed by the flood impact, whereas others have recovered through epicormic regeneration after the disturbance. At the same time, several tree individuals newly germinated. This research aimed to explain the recovery of the riparian ecosystem by spatial proximity between each tree individual of different characteristics, such as "dead", "recovered", and "newly germinated". A spatial point pattern analysis based on K and g-functions revealed that the newly germinated trees and the existing trees were distributed in the spatially clumping patterns. However, further detailed analysis revealed that the new trees were statistically less attracted to the recovered trees than the dead trees, implying competitive interactions hidden in the facilitative interactions. Habitat amelioration by the existing trees positively affected the growth of the new trees, while "living" existing trees were competing with the new trees for resources. This research is expected to provide new knowledge in this era of rapid climate change, which likely induces stronger and more frequent natural disturbance than before. Environmental factors have been widely used for ecosystem modeling, but species interactions, represented by the relative spatial distribution of plant individuals, are also valuable factors explaining ecosystem dynamics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.269-285
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• 2021

As the systematic management of knowledge within an organization is recognized as a core factor for the continuous growth of an organization, organizations are increasing their interest in knowledge management. Knowledge management requires the active sharing of knowledge by insiders of the organization, but there are cases of failure due to the lack of participation of leaders and employees of the organization. The purpose of this study is to suggest a mechanism by which the authentic leadership of leaders in small and medium-sized enterprises(SME), which are relatively lacking in knowledge production capacity, leads to intention to share knowledge of employees. In addition, the study confirms that reciprocal feedback and task interdependence moderate the relationship between antecedent factors and intention to share knowledge. In this study, a research model was derived based on precedent research, and 272 samples were obtained by conducting a questionnaire survey on employees of SME that introduced a knowledge management policy. And, the study verified the hypothesis by applying structural equation modeling based on AMOS 22.0. The results of the study proved that authentic leadership has a positive effect on the intention to share knowledge through organization identification and organization commitment, and confirmed that reciprocal feedback and work interdependence moderate the relationship between knowledge sharing intentions and antecedent factors. This study suggests the mechanism by which the authentic behavior of the leaders of SMEs affects the knowledge sharing behavior of employees, and suggests that work cooperation strengthens the influence of the mechanism.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.115-121
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• 2023

The leopard plant has the characteristic of being used for ornamental purposes when there are yellow spots on the leaves, and is widely used as a bed plant for viewing flowers. To set several indicators to predict the growth of crops with ornamental value, and to quantitatively express the relationship between the indicators are necessary. In this study, we determine a model that estimates the leaf area and the number of flower of Farfugium japonicum Kitam. using leaf length and width, and conducting a regression analysis on some regression models. As an indicator for estimating the leaf area and the number of flower, the leaf length and width of F. japonicum were measured and applied to 8 regression models. As a result of regression analysis of 8 models that estimated leaf area and the number of flower, R² values of the linear models were all higher than 0.84 and 0.80. As a result of validation, using the most reliable model among the models for estimating the leaf area and the number of flowering, R² was 0.90 and 0.82, respectively. Using a model that estimates various indicators that can be used for quality evaluation from easy-to-measure morphological factors, the evaluation of ornamental plants will be facilitated.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.1-10
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• 2023

This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982-2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0-6 years) and number of cutting (NC, 2nd-5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.