• Research in Plant Disease
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• v.30 no.1
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• pp.99-102
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• 2024

Integrated pest management is essential for controlling plant diseases that reduce crop yields. Rapid diagnosis is crucial for effective management in the event of an outbreak to identify the cause and minimize damage. Diagnosis methods range from indirect visual observation, which can be subjective and inaccurate, to machine learning and deep learning predictions that may suffer from biased data. Direct molecular-based methods, while accurate, are complex and time-consuming. However, the development of large multimodal models, like GPT-4, combines image recognition with natural language processing for more accurate diagnostic information. This study introduces GPT-4-based system for diagnosing plant diseases utilizing a detailed knowledge base with 1,420 host plants, 2,462 pathogens, and 37,467 pesticide instances from the official plant disease and pesticide registries of Korea. The AI plant doctor offers interactive advice on diagnosis, control methods, and pesticide use for diseases in Korea and is accessible at https://pdoc.scnu.ac.kr/.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.127-144
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• 2020

This study aims to examine the relationship between perceived organizational support (POS), work engagement (WE), and turnover intention (TI) among employees of small and medium-sized enterprises (SMEs) characterized by whether or not to participate in the work-learning dual system (WLDS). Also, this study intends to explore the effectiveness of WLDS by examining significant differences between the two groups. To achieve the purpose of this study, we have conducted surveys between August and December in 2018. A total of 616 cases (321 cases from SMEs participating in WLDS and 295 cases from general SMEs) were finally selected and used for data analysis with structural equation modeling (SEM). Results of the study revealed that POS had a significant and positive effect on WE. Also, POS had a significant and negative effect on TI. In addition, the mediating effect of WE in the relationship between POS and TI was found to be statistically significant. Furthermore, the results revealed that the conditional indirect effect between POS and TI depending on participation in WLDS was statistically significant. However, the conditional direct effect between POS and TI due to WLDS participation was not statistically significant. Based on the results, academic and practical implications were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.90-99
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• 2021

This study was conducted to provide basic data for improving nursing management practice by comparing and analyzing the perceptions of nursing students and clinical instructors about the importance of the learning contents of nursing management and their practical experience. The final 343 copies were analyzed using the Mann-Whitney test and cross-analysis, targeting 4th-grade students and clinical instructors at three universities. Both nursing students and clinical instructors recognized 'communication', 'interpersonal relationship', 'responsibility', 'trust', and 'morality' as important factors in the evaluation items of practice. Among the top 10 most importantly recognized items among nursing-management practice learning content, six items ('infection control', 'nursing record management', 'patient nursing management', 'drug management', 'patient safety', and 'nursing malpractice') were matched in the two groups. Moreover, clinical instructors recognized that interpersonal relationships and relationship ethics were important, while nursing students chose legal responsibility. As a result of the practical experience analysis between the two groups, nursing students had high experience of indirect participation, but the clinical instructors had a high experience of direct instruction. A plan is needed to reduce the difference by establishing an organic partnership relationship between the university and practice institutions and increase the experience of direct practice of nursing students.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.11-16
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• 2022

As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.

• Communications of Mathematical Education
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• v.24 no.2
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• pp.345-363
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• 2010

The purpose of this study is to investigate and analyze informal knowledge of students who do not learn the conception of proportion and to identify how the informal knowledge can be used for teaching the conception of proportion in order to present an effective method of teaching the conception. For doing this, proportion was classified into direct and inverse proportion, and 'What are the informal knowledge of students?' were researched. The subjects of this study were 117 sixth-graders who did not have prior learning on direct and inverse proportion. A total eleven problems including seven for direct proportion and four for inverse proportion, all of them related to daily life. The result are as follows; Even though students didn't learn about proportion, they solve the problems of proportion using informal knowledge such as multiplicative reasoning, proportion reasoning, single-unit strategy etc. This result implies mathematics education emphasizes student's informal knowledge for improving their mathematical ability.

• Journal of The Korean Association For Science Education
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• v.43 no.1
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• pp.37-47
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• 2023

The purpose of this study is to analyze the influence and structural relationship of variables related to science teaching professionalism. These variables set up learning organizational culture as exogenous variables and science epistemological beliefs and science teaching efficacy as endogenous variables. For this study, a survey was conducted with 499 elementary science teachers from Seoul and Gyeonggi province participating. The results of this study are as follows: Science epistemological beliefs and science teaching efficacy were found to directly affect science teaching professionalism. In addition, learning organizational culture perceived by the teachers did not show significant effects on the science teaching professionalism, but it was found that it has direct significant effects on science epistemological beliefs and science teaching efficacy. Based on the results of this study, which examines the structural relationship between learning organizational culture, science epistemological beliefs, science teaching efficacy and science teaching professionalism. we deem that it is necessary to consider internal factors of teachers as well as ways to improve learning organizational culture.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.175-186
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• 2014

The purpose of this study is to demonstrate the effectiveness of core competency courses by scrutinizing H Corporation case. The primary data survey was taken from direct and indirect participants of H Corporation core competency courses. The findings from the study are as follow. Firstly, before-and-after average differences were significant in inspecting core competency courses. Secondly, participants' own expected core competency was comparatively lower than how observers evaluated the participants. Thirdly, Core competency courses directly and indirectly influenced on the business performance. Therefore, the conclusions of the study are firstly, core competency courses may work effectively for the goal of the company in changing employees' organizational behavior. Secondly, for the better result of the core competency courses, customized and integrated learning transfer model for the particular company should be designed from the beginning of the education.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.77-97
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• 2017

A recent sharp increase of the biomedical literature causes researchers to struggle to grasp the current research trends and conduct creative studies based on the previous results. In order to alleviate their difficulties in keeping up with the latest scholarly trends, numerous attempts have been made to develop specialized analytic services that can provide direct, intuitive and formalized scholarly information by using various text mining technologies such as information extraction and event detection. This paper introduces and evaluates total 8 Convolutional Neural Network (CNN) models for extracting biomedical events from academic abstracts by applying various feature utilization approaches. Also, this paper conducts performance comparison evaluation for the proposed models. As a result of the comparison, we confirmed that the Entity-Type-Fully-Connected model, one of the introduced models in the paper, showed the most promising performance (72.09% in F-score) in the event classification task while it achieved a relatively low but comparable result (21.81%) in the entire event extraction process due to the imbalance problem of the training collections and event identify model's low performance.

• Journal of Computing Science and Engineering
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• v.7 no.2
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• pp.99-111
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• 2013

Approximating a divergence between two probability distributions from their samples is a fundamental challenge in statistics, information theory, and machine learning. A divergence approximator can be used for various purposes, such as two-sample homogeneity testing, change-point detection, and class-balance estimation. Furthermore, an approximator of a divergence between the joint distribution and the product of marginals can be used for independence testing, which has a wide range of applications, including feature selection and extraction, clustering, object matching, independent component analysis, and causal direction estimation. In this paper, we review recent advances in divergence approximation. Our emphasis is that directly approximating the divergence without estimating probability distributions is more sensible than a naive two-step approach of first estimating probability distributions and then approximating the divergence. Furthermore, despite the overwhelming popularity of the Kullback-Leibler divergence as a divergence measure, we argue that alternatives such as the Pearson divergence, the relative Pearson divergence, and the $L^2$-distance are more useful in practice because of their computationally efficient approximability, high numerical stability, and superior robustness against outliers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.530-536
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• 2017

The purpose of this study is to specify the procedures in problem design to employ BPBL and to design problems for learning subject content. The design of problems is crucial for the effectiveness of BPBL. Ineffective PBL problems could affect whether students acquire sufficient domain knowledge, activate appropriate prior knowledge, and properly direct their own learning. The procedures for designing good problems are composed of selection of educational content, figuring out the learner's characteristics, finding problems, setting roles and situations, and writing down problems. Using the procedures, we designed five integration problems covering the content of an Internet marketing subject. We can foster talent needed on a current industrial site with BPBL, not whole-class learning in a Mongolian engineering college. We made a plan for the Internet marketing subject based on BPBL in the Mongolian engineering college, and focused on the process of designing problems.