• Journal of Agricultural Extension & Community Development
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• v.7 no.1
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• pp.121-136
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• 2000

This study reports on a comparison between the Korean diffusion of agricultural innovation or extension service and the cooperative extension service in the United States of America. It focuses on relevant differences between the two systems and provides recommendation for improvement of the Korean system to insure success in important areas related to the diffusion of agricultural innovations. After a comparative study on diffusion of innovations it is clear that: in order to have a productive agriculture that makes effective and efficient use of natural resources and helps achieve sustainability goals, a mechanism that delivers knowledge to agricultural communities must be established and maintained. This mechanism is clearly an agricultural extension service that is cooperatively funded by federal, state and local governments and that insures participation of constituents in the process of establishing priorities and evaluating achievements. The success of US agriculture, the most productive in the world, is to a large degree to the Cooperative Extension Service. Based on the results of this study and the differences of the United States and Korea, the following recommendations should be emphasized for more effective communication for agricultural innovation and rural development in Korea: 1) In order to insure that extension educators are high caliber professional individuals, it is important to establish a system that nationally recognizes these individuals as such, and that provides a professional development path. 2) The results of the decision of transfer of extension educators to local governments has not yielded positive outcomes, especially in terms of professional status. It is clearly demonstrable that valuable professionals are leaving the service, that local governments do not have the will and resources to implement a successful extension program. 3) Because of the critical importance of diffusing innovations to agricultural producers in order to insure and quality and steady food supply, it is of critical importance that these issues be addressed before the extension service is further deteriorated. Given the cement situation, it is clear that the extension service should become nationally supported again in cooperation with local and state governments and that extension professionals be given appropriate rank at the national level, commesurate with their peers in research and teaching. 4) The common current committee practice of lengthy reporting and short discussion needs to be changed to one that results in char, brief and substantive action oriented goals. Joint participation by researchers, extension educators and farmers should be encouraged in planning, implementation and evaluation of communication for agricultural innovations. Roles and functions of committees for institutional cooperation, and or agricultural extension committees should be enlarged. 5) Extension educators should be encouraged to adopt new communication technologies to improve their diffusion of innovations methods. Agricultural institutions and organizations should be encouraged to adopt farmer-first and or client-oriented approach in agricultural extension and diffusion of agricultural technologies. The number, complexity and rapid change of information in agricultural extension require the development of a computer based information and report system to support agricultural extension. 6) To facilitate and expand the further development of communication for agricultural innovation and rural development, agricultural communication programs in universities especially in colleges of agriculture and life sciences. 7) To strengthening the sense of national and social responsibility communication for agricultural innovation and rural development among students in agricultural colleges and universities through participation in learning activities by proactive recruitment. 8) To establish and reinforce a policy that insures participation in communication for agricultural innovation and regal development activities. 9) To improve further development of communication for agricultural innovation and rural development in Korea, more research activities should be encouraged.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.127-139
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• 2024

This study investigates the impact of edutech characteristics and both tangible and intangible educational services on the intention to re-enroll, which is directly related to the management performance of private institutes. The study aims to propose strategies to improve re-enrollment intentions and management performance based on the findings. Private education has grown continuously, complementing the limitations of public education and increasing parental dependence. This study tested the hypothesis that edutech characteristics, intangible services, and tangible services, increasingly utilized with the development of information and communication technology, would influence re-enrollment intentions. It also examined whether rapport-building behavior with parents would have a moderating effect on this relationship. The hypothesis testing results showed that among the edutech characteristics, content, intangible services such as reliability and empathy, and tangible services such as tangibility and payment accessibility positively impacted re-enrollment intentions. The hypothesis that rapport-building behavior would moderate the relationship between educational services and re-enrollment intentions was supported for empathy in intangible services and tangibility in tangible services. Based on these findings, the study proposed three strategies to improve management performance of private institutes. First, in terms of improving and managing edutech characteristics, it suggested introducing and updating edutech content and ensuring operational stability. Second, for improving and managing intangible services, it recommended managing instructor recruitment and training to enhance quality and competence, maintaining professionalism through continuous education by credible institutions, and providing level-based education for students based on the qualitative improvement of educational programs. Third, to improve and manage tangible services, it suggested setting appropriate tuition fees, offering various payment methods (online, mobile, card, bank transfer) unrestricted by time and place, and equipping interiors and facilities that enable focused learning. Additionally, considering the moderating effect of rapport-building behavior, it emphasized that improvements and management requiring costs are necessary, but making parents feel a high level of tangibility through rapport-building is also important. Furthermore, given the increasing importance of edutech based on information and communication technology, the study highlighted the need for various support measures such as government technological support and venture certification system support for institutes with an entrepreneurial spirit aiming to introduce innovative technologies such as AI technology based on large language models and AR/VR-applied metaverse environments. This study is expected to help improve the management performance of private institutes by specifically suggesting items and methods for improvement and management in the educational field.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.312-323
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• 2022

This study began with the hypothesis of whether "solar radiation" and "terrestrial radiation" can be replaced by "visible radiation" and "infrared radiation", respectively. To this end, we investigated the perceptions of high school students who completed the Earth Science I course through a questionnaire to reveal how they perceived each concept. We also analyzed the descriptions and illustrations of textbooks that may have affected their perceptions. All of the students who participated in the questionnaire recognized solar radiation as radiation emitted only in the visible light region. About 35% of the students recognized convection, conduction, and latent heat as energy transfer by radiation in the Earth's heat budget. By analyzing six types of Earth Science I textbooks in the 2015 revised curriculum, we observed that two types introduced the terms "shortwave radiation" and "longwave radiation" but had no explanation for them, while the other two described solar radiation as "radiation mainly in the visible light region" or "radiation in short wavelengths". Regarding solar and terrestrial radiation in the last two types, there was no explanation for the wavelength regions, or ambiguous terms such as "short wavelength" and "long wavelength" were used. In addition, the two textbooks contained some errors in the illustration of the energy budget. Considering that textbooks described solar and terrestrial radiation without defining the exact terms for shortwave and longwave radiation, learners are likely to recognize solar and terrestrial radiation as visible and infrared radiation, respectively. This finding implies that vague statements or errors in textbooks can cause or reproduce students' misconceptions. The discussion in this study is expected to be used as a helpful reference material for teaching and learning processes regarding the Earth's radiation equilibrium and heat budget, and thereby contribute to proposing reasonable description plans for future textbook writing.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.177-198
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• 2024

Article 22(1) of the Library Act, which was completely revised in December 2006, stipulated that regional representative libraries are statutory organizations, and Article 25(1) of the Library Act, which was revised again in late 2021, renamed them as metropolitan representative libraries and expanded their duties. The reason why cities and provinces are required to specify or establish and operate metropolitan representative libraries is that in addition to their role as public libraries for public information use, cultural activities, and lifelong learning as stipulated in Article 23 of the Act, they are also responsible for the legal works of metropolitan representative libraries as stipulated in Article 26, and lead the development of libraries and knowledge culture by serving as policy libraries, comprehensive knowledge information centers, support and cooperation centers, research centers, and joint preservation libraries for all public libraries in the city or province. Therefore, it is necessary to analyze and diagnose whether the metropolitan representative library has been faithfully fulfilling its legal works for the past 15 years(2009-2023), and whether it is properly providing the results of its statutory planning and implementation on its website to meet the digital and mobile era. Therefore, this study investigated and analyzed the performance of the metropolitan representative library for the last two years based on the current statutory tasks and evaluated the extent to which it provides them through its website, and suggested complementary measures to strengthen its web services. As a result, it was analyzed that the web services for legal works that the metropolitan representative library should perform are quite insufficient and inadequate, so it suggested complementary measures such as building a website for legal works on the homepage, enhancing accessibility and visibility through providing an independent website, providing various policy information and web services (portal search, inter-library loan, one-to-one consultation, joint DB construction, data transfer and preservation, etc.), and ensuring digital accessibility of knowledge information for the vulnerable.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.1
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• pp.161-174
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• 1997

Omega-3 fatty acids have been major research interests in medical and nutritional science relating to life sciences since after the epidemiologic data on Green3and Eskimos reported by several researchers clearly showed fewer per capita deaths from heart diseases and a lower incidence of adult diseases. Linolenic acid(LNA) is an essential fatty acid for human beings as well as linoleic acid(LA) due to the fact that vertebrates lack an enzyme required to incorporate a double bond beyond carbon 9 in the chain. In addition the ratio of omega-6 and 3 fatty acids seems to be important in terms of alleviation of heart diseases since LA and LNA competes for the metabolic pathways of eicosanoids synthesis. High consumption of omega-3 fatty acids in seafoods may control heart diseases by reducing blood cholesterol, triglyceride, VLDL, LDL and increasing HDL and by inhibiting plaque development through the formation of antiaggregatory substances like PGI$_2$, PGI$_3$ and TXA$_3$ metabolized from LNA. Omega 3 fatty acids also play an important role in neuronal developments and visual functioning, in turn influence learning behaviors. Current dietary sources of omega-3 fatty acids are limited mostly to seafoods, leafy vegetables, marine and some seed oils and the most appropriate way to provide omega-3 fatty acids is as a part of the normal dietary regimen. The efforts to enhance the intake of omega-3 fatty acids due to several beneficial effects have been made nowadays by way of food processing technology. Two different ways can be applied: one is add Purified and concentrated omega-3 fatty acids into foods and the other is to produce foods with high amounts of omega-3 fatty acids by raising animals with specially formulated feed best for the transfer of omega-3 fatty acids. Recently, items of manufactured and marketed omega-3 fatty acids fortified foodstuffs are pork, milk, cheese, egg, formula milk and ham. In domestic food market, many of them are distributed already, but problem is that nutritional informations on the amounts of omega-3 fatty acids are not presented on the labeling, which might cause distrust of consumers on those products, result in lower sales volumes. It would be very much wise if we consume natural products, result in lower sales volumes. It would be very much wise if we consume natural products high in omega-3 fatty acids to Promote health related to many types of adult diseases rather than processed foods fortified with omega-3 fatty acids.