Park Wan-seo's novels deal with realistic topics of society, such as women's issues, the capitalist system, and the problems that come with old age. Assuch, her work is used as a tool to analyze social phenomena in various fields, such as women's studies, sociology, and literature. A characteristic style of Park Wan-seo's novels is that she bases them on her own experiences. However, among her novels, the novel Mimang is exceptional. The plot is based on stories that have been passed down from generation to generation. This is to show the spirit of the times through the unforgettable story of her hometown, Gaesong. Mimang is the story of a family chronology that spans four generations centered on Chun Cheu-Man and his family, who became powerful capitalists through the cultivation and commerce of ginseng cultivation. Set in the late 19th century until the end of the Korean War, the novel unravels the essence of the times symbolized by merchants of ginseng and Gaeseong, focusing on the actions of people living in a period of historical turbulence. Gaeseong is the mecca of Korean ginseng, and Gaeseong cannot be portrayed without the story of ginseng and its merchants. Therefore, Mimang, a fictionalized story based on real facts, contains valuable testimony of the history of ginseng, not only as historical values of modern history and personal customs but also as microhistory. In the novel, traces of the times of Gaeseong and the spirit of ginseng merchants, as shown in the Japanese sacking of ginseng during the colonial period, the resistance of ginseng merchants, and the conversion of ginseng capitalism to modern capitalism, are imprinted like fossils. What is especially meaningful is that the stories in the novel correspond to historical facts and constitute a chapter in the history of ginseng. The symbolism of ginseng in the novel can be explained in three main ways. First, it shows the essence of Korean ginseng. It reveals the soul of ginseng through the sincerity and rigor of ginseng farming, as well as the spirit and pride of ginseng. Second, it symbolizes the exploitation of ginseng in Japan as a national issue. The efforts of ginseng merchants to protect this and support the independence movement are presented as important themes to express nationalism. Third, it shows the modern capitalist progressiveness of Gaeseong ginseng merchants, who do not stay in landownership and commercial capital, but convert them to productive capital and contribute to society by modernizing them. The three symbolisms show the spirit of the times of the Gaeseong ginseng merchants, clearly revealing the meaningful relationship between the Korean people and ginseng.
Pacific island countries, including Kiribati, are suffering from a shortage of essential resources as well as a reduction in their living space due to sea level rise and coastal erosion from climate change, groundwater pollution and vegetation changes. Global activities to solve these problems are being progressed by the UN's efforts to implement SDGs. Pacific island countries can adapt to climate change by using abundant marine resources. In other words, seawater plants can assist in achieving SDGs #2, #6 and #7 based on SDGs #14 in these Pacific island countries. Under the auspice of Korea International Cooperation Agency (KOICA), Korea Research Institute of Ships and Ocean Engineering (KRISO) established the Sustainable Seawater Utilization Academy (SSUA) in 2016, and its 30 graduates formed the SSUA Kiribati Association in 2017. The Ministry of Oceans and Fisheries (MOF) of the Republic of Korea awarded ODA fund to the Association. By taking advantage of seawater resource and related plants, it was able to provide drinking water and vegetables to the local community from 2018 to 2020. Among the various fields of education and practice provided by SSUA, the Association hope to realize hydroponic cultivation and seawater desalination as a self-support project through a pilot project. To this end, more than 140 households are benefiting from 3-stage hydroponics, and a seawater desalination system in connection with solar power generation was installed for operation. The Association grows and supplies vegetable seedlings from the provided seedling cultivation equipment, and is preparing to convert to self-support business from next year. The satisfaction survey shows that Tarawa residents have a high degree of satisfaction with the technical support and its benefits. In the future, it is hoped that SSUA and regional associations will be distributed to neighboring island countries to support their SDGs implementations.
Journal of Korea Entertainment Industry Association
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v.14
no.8
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pp.407-426
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2020
The purpose of this study was to make convergent and combined analysis of the sport industry and exercise rehabilitation in the era of New Normal based on the Fourth Industrial Revolution and devise a comprehensive plan for future activation. For this purpose, literature review was performed mainly by analyzing the environment of the sport industry in the New Normal era based on the Fourth Industrial Revolution and by carrying out convergent and combined analysis of the sport industry to present a convergent and combined activation plan for exercise rehabilitation comprehensively as follows: First, it is necessary to make a strategy of promoting exercise rehabilitation in convergent and combined ways at the sport industry level. This means development of a convergent and combined exercise rehabilitation-tourism-ICT model as well as a convergent and combined exercise rehabilitation-ICT model through collaboration among ministries, including those of health and sports. Second, it is necessary to convert into a convergent and combined way of thinking and extend and reinforce educational competitiveness in the area of exercise rehabilitation. That is, it is necessary to refine the education and training systems for reinforcing personal ICT competence of exercise rehabilitation majors and relevant ones and provide convergent and combined business commencement education. Third, it is necessary to make different types of research and development by applying practical, convergent and combined skills based on the industrial field to exercise rehabilitation and relevant areas. Efforts should be made to overcome any risk in the era of New Normal and support business commencement with convergent and combined skills for exercise rehabilitation. Fourth, it is necessary to make mid- and long-term clusters where exercise rehabilitation and relevant businesses can be accumulated. This means building an industrial hub and complex for exercise rehabilitation and requires making an R&D-based cluster with industrial-academic-governmental collaboration, maximizing the synergy effects with local infrastructures, and fulfilling the function of realizing a spontaneous profit-generating structure.
This study is to evaluate the availability of cardiorespiratory fitness measurement by 20 m shuttle run test based upon energy contribution rates of elite athletes in different sports type. Sixty-seven elite athletes attending K national university participated in this study. They were divided by three groups based upon sports type, composed of Anaerobic Group (sprint, jumps, weightlifting, throw; n=35), Aerobic Group (medium-long distance; n=9), and Combat Sport Group (judo; n=23). 20 m shuttle run test was conducted by Leger et al.(1982) method and calculating acceleration using measured shuttle run repetitions was conducted by Brewer et al.(1988) method. To test the usefulness of VO2max, graded exercise treadmill test was conducted and standing long jump and 50 m run were measured as power fitness factors. Z-jump was used for measuring power, agility, and muscular endurance. Standing long jump and 50 m run of Anaerobic Group (AnG) was significantly higher than that of Aerobic Group (AeG) and Combat Sport Group (CG) (p<0.05). However, Z-jump of CG was significantly higher than that of AnG and AeG(p<.05). There was a higher correlation of 20 m shuttle run test and VO2max in AnG(r= 0.577, p<.0001) and CG(r= 0.760, p<.0001). Otherwise, there was a low correlation of 20 m shuttle run test and VO2max in AeG. There was no significant group difference to test the availability of 20 m shuttle run test and there was a reduced error when converting 20 m shuttle run results into VO2max. This study examined the usefulness of 20 m shuttle run test by converting 20 m shuttle run repetition results into VO2max calculation, which showed reduced error. Therefore, this study confirmed that it would be needed to convert 20 m shuttle run results into VO2max for universal and practical use in the field without dividing sports type.
In this paper, a control system for a complex microbial incubator was proposed. The proposed control system consists of a control unit, a communication unit, a power supply unit, and a control system of the complex microbial incubator. The controller of the complex microbial incubator is designed and manufactured to convert analog signals and digital signals, and control signals of sensors such as displays using LCD panels, water level sensors, temperature sensors, and pH concentration sensors. The water level sensor used is designed and manufactured to enable accurate water level measurement by using the IR laser method with excellent linearity in order to solve the problem that existing water level sensors are difficult to measure due to foreign substances such as bubbles. The temperature sensor is designed and used so that it has high accuracy and no cumulative resistance error by measuring using the thermal resistance principle. The communication unit consists of two LAN ports and one RS-232 port, and is designed and manufactured to transmit signals such as LCD panel, PCT panel, and load cell controller used in the complex microbial incubator to the control unit. The power supply unit is designed and manufactured to supply power by configuring it with three voltage supply terminals such as 24V, 12V and 5V so that the control unit and communication unit can operate smoothly. The control system of the complex microbial incubator uses PLC to control sensor values such as pH concentration sensor, temperature sensor, and water level sensor, and the operation of circulation pump, circulation valve, rotary pump, and inverter load cell used for cultivation. In order to evaluate the performance of the control system of the proposed complex microbial incubator, the result of the experiment conducted by the accredited certification body showed that the range of water level measurement sensitivity was -0.41mm~1.59mm, and the range of change in water temperature was ±0.41℃, which is currently commercially available. It was confirmed that the product operates with better performance than the performance of the products. Therefore, the effectiveness of the control system of the complex microbial incubator proposed in this paper was demonstrated.
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.2
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pp.80-98
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2023
This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.
Song-in Kim;Eunbee Cho;Kyohee Cho;Chang Kwon;Seok-hee Lim;Jong Won Kim;Myung Jun Chung;Su Jeong Kim;Sanghyun Lim
Microbiology and Biotechnology Letters
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v.51
no.4
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pp.465-473
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2023
In this study, we aimed to evaluate the bioconversion ability of single (Lactiplantibacillus plantarum CBT LP3, Lactococcus lactis subsp. lactis CBT SL6, Streptococcus thermophilus CBT ST3) and multi-strain probiotics to convert rutin to quercetin in roasted tartary buckwheat, and to assess their biological activities. To evaluate the bioconversion efficiency, each strain was cultured for 24 h in MRS media with 5% roasted tartary buckwheat 'Hwangguem-Miso' powder. After then, rutin and quercetin contents were determined by HPLC. Additionally, the biological activities were compared before and after bioconversion of an ingredient. Anti-oxidant effects were measured by DPPH and ABTS assays. Anti-inflammatory effects were determined by measuring NO production, and levels of iNOS, TNF-α, IL-6 and IL-4 using an LPS-induced Raw 264.7 cell model. The bioconversion rate under the combination of three species of probiotics significantly increased more than single species. Antioxidant efficacy results showed the highest activity when the combination of three species of probiotics cultured. The pro-inflammatory factors such as nitric oxide, iNOS, TNF-a, and IL-6 were significantly decreased when the three types of probiotics were combined than single strain was cultured. In addition, level in the anti-inflammatory factor IL-4 was increased. The multi-strain probiotics showed increased bioconversion efficiency, effects of anti-oxidant and anti-inflammatory compared to the single strain. These findings suggest that the fermentation of tartary buckwheat by probiotics may be a valuable candidate for developing functional foods with anti-oxidation and anti-inflammation.
Pine forests are continuously declining due to competition with broadleaf trees, such as oaks, as a consequence of changes in the natural dynamics of forest ecosystem. This natural decline creates a risk of losing the various benefits pine trees have provided to people in the past. Therefore, it is necessary to prepare future forest management directions by considering the state of pine tree decline in each region. The goal of this study is to understand the characteristics of pine forest changes according to forest dynamics and to predict future regional changes. For this purpose, we evaluated the trend of change in pine forests and extracted various variables(topography, forest stand type, disturbance, and climate) that affect the change, using time-series National Forest Inventory (NFI) data. Also, using selected key variables, a model was developed to predict future changes in pine forests. As a results, it showed that the importance of pine trees in forests across the country has decreased overall over the past 10 years. Also, 75% of the sample points representing pine trees remained unchanged, while the remaining 25% had changed to mixed forests. It was found that these changes mainly occurred in areas with good moisture conditions or disturbance factors inside and outside the forest. In the next 10 years, approximately 14.2% of current pine forests was predicted to convert to mixed forests due to changes in natural forest dynamics. Regionally, the rate of pine forest change was highest in Jeju(42.8%) and Gyeonggi(26.9%) and lowest in Gyeongbuk(8.8%) and Gangwon(13.8%). It was predicted that pine forests would be at a high risk of decline in western areas of the Korean Peninsula, including Gyeonggi, Chungcheong, and Jeonnam. This results can be used to make a management plan for pine forests throughout the country.
Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in
. This model is composed of four paths such as dimensions of e-store personality${\rightarrow}$e-store identification, e-store identification${\rightarrow}$e-store loyalty, e-store identification ${\rightarrow}$e-store trust${\rightarrow}$e-store loyalty, and e-store identification${\rightarrow}$e-store engagement${\rightarrow}$e-store loyalty. II. Research Method Ladies under 30s were the respondents of this survey. Data were collected from January 20th to February 26th in 2010. A total of 200 questionnaires were distributed and 169 respondents were analysed finally to test hypotheses because 31 questionnaires had incorrect or missing responses. SPSS 12.0 and LISREL 7.0 program were used to test frequency, reliability, factor, and structural equation modeling analysis. III. Result and Conclusion According to results from factor analysis, eigen value was over 1.0 and items which were below 0.6 were deleted. Consequently, 9 factors(% of total variance is 72.011%) were searched. All Cronbach's ${\alpha}$ values are over the recommended level(${\alpha}$ > 0.7). The overall fit indices are acceptable such as ${\chi}^2$=2028.36(p=0.00), GFI=0.87, AGFI=0.82, CFI=0.81, IFI=0.92, RMR=0.075. All factor loadings were over the recommended level. As the result of discriminant validity check with chi-square difference test between paired constructs, each construct has good discriminant validity. The overall fit indices of final model are acceptable such as ${\chi}^2$=340.73(df=36, p=0.00), GFI=0.92, AGFI=0.81, CFI=0.91, IFI=0.91, RMR=0.085. As test results, 5 out of 6 hypotheses are supported because there are statistically significant casual relationships in structural equation model, shown in
. First of all, hypothesis 1 is partially supported because sub-hypothesis 1-1 and 1-2 are supported, whereas sub-hypothesis 1-3, 1-4, and 1-5 are rejected. Specifically, it reveals that warmth and sophistication dimensions in e-store personality have positive influence on e-store identification, however, activity, progressiveness, and strictness does not have any significant relationship on e-store identification. Secondly, hypothesis 2 was supported. Therefore, it can be said that e-store identification has a positive impact on e-store trust. Thirdly, hypothesis 3 is also supported. Hence, there is a positive relationship between e-store identification and e-store engagement. Fourthly, hypothesis 4 is supported too. e-store identification has a positive influence on e-store loyalty. Fifthly, hypothesis 5 is also accepted. This indicates that e-store trust is a precedent variable which positively affects e-store loyalty. Lastly, it reveals that e-store engagement has a positive impact on e-store loyalty. Therefore, hypothesis 6 is supported. The findings of the study imply that some dimensions of e-store personality have a positive influence on e-store identification, and that e-store identification has direct and indirect influence on e-store loyalty through e-store trust and e-store engagement positively. These results also suggest that the e-store identification in e-store personality is a precedent variable which positively affects e-store loyalty directly and indirectly through e-store trust and engagement as a mediating variable. Therefore, e-store marketers need to implement website strategy based on e-store personality, e-store identification, e-store trust, and e-store engagement to meet customers' psychological needs and enhance e-store loyalty. Finally, the limitations and future study directions based on this study are discussed.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used
. Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.
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