• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.5
• /
• pp.521-530
• /
• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.133-143
• /
• 2023

In this study, we propose a big data set of strawberry pests collected directly for diagnosis model learning and an automatic pest diagnosis model architecture based on deep learning. First, a big data set related to strawberry pests, which did not exist anywhere before, was directly collected from the web. A total of more than 12,000 image data was directly collected and classified, and this data was used to train a deep learning model. Second, the deep-learning-based automatic pest diagnosis module is a module that classifies what kind of pest or disease corresponds to when a user inputs a desired picture. In particular, we propose a model architecture that can optimally classify pests based on a convolutional neural network among deep learning models. Through this, farmers can easily identify diseases and pests without professional knowledge, and can respond quickly accordingly.

• PNF and Movement
• /
• v.17 no.2
• /
• pp.223-236
• /
• 2019

Purpose: This research was to develop a module for problem-based learning(PBL) and to enhance the problem-solving abilities of physical therapy students in a neurological physical therapy course and to evaluate the effects of the module using quantitative and qualitative data. Methods: The PBL module was applied to 55 third-year physical therapy students who participated in a neurological physical therapy course at S university in Seoul. Anonymous self-report questionnaires and reflection journals were collected, and the data were analyzed. Results: The results of the analysis showed that the academic achievements of the students who participated in the first PBL class improved compared to the academic achievements of the students who had participated in the same class in the previous semester. Second, the students who participated in the PBL class evaluated the PBL as a very effective learning method for developing clinical practical ability. Third, the students of the PBL class showed increased cooperation and communication abilities between team members. Conclusion: The results of this study indicated that, if PBL class case studies and various types of teaching and learning methods appropriate for theoretical and practical fields are continuously studied, then it is expected that teaching models will be developed that can develop flexibility and creativity among preliminary physical therapists in a rapidly changing medical environment.

• Korean Journal of Cognitive Science
• /
• v.14 no.3
• /
• pp.13-21
• /
• 2003

This study presents a design of Teachable Agent(TA) and its theoretical background. TA is an intelligent agent to which students as tutors teach, pose questions, and provide feedbacks using a concept map. TA consists of four independent Modules, Teach Module, Q&A Module, Test Module, and Resource Module. In Teach Module, students teach TA by constructing concept map. In Q&A Module, both students and TA ask questions and answer questions each other through an interactive window. To assess TA's knowledge and provide feedback to students, Test Module consists of a set of predetermined questions which TA should pass. From Resource Module, students can search and look up important information to teach, ask questions, and provide feedbacks whenever they want. It is expected that TA should provide student tutors with an active role in learning and positive attitude toward the subject matter by enhancing their cognition as well as motivation.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.575-579
• /
• 2006

Intelligent Tutoring System is composed of tutoring module, student module and expert module. Among the modules, interface module is the most closely related to students and shares the biggest part of a learning system. Interface module is important for students both in e-learning system but also in intelligent tutoring system. But research on the improvement of interface hasn't been actively done. It studied the interface improvement that has very close relation to e-Learning students. It studied the main components of the existing interface and designed multimedia interface to correct the problems of previous researches. It also suggested the method to relate it to the intelligent tutoring system.

• Journal of the Korean earth science society
• /
• v.25 no.5
• /
• pp.293-302
• /
• 2004

The earthquake education is the area that students have few opportunities to experience directly in elementary school earth science course. Therefore, I have developed an animation module to make students learn about earthquake efficiently satisfying students's interests and characteristics. I have planned to get the effective learning result by teaching 35 elementary students, using the developed module designed for ICT teaching and learning. The result of this study is that the animation module class gives students opportunity and develop students' attitudes towards earth science.

• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.352-361
• /
• 2018

Purpose: The objective of this study was to develop a multilayer perceptron (MLP) model to estimate solar radiation using a solar module. Methods: Data for the short-circuit current of a solar module and other environmental parameters were collected for a year. For MLP learning, 14,400 combinations of input variables, learning rates, activation functions, numbers of layers, and numbers of neurons were trained. The best MLP model employed the batch backpropagation algorithm with all input variables and two hidden layers. Results: The root-mean-squared error (RMSE) of each learning cycle and its average over three repetitions were calculated. The average RMSE of the best artificial neural network model was $48.13W{\cdot}m^{-2}$. This result was better than that obtained for the regression model, for which the RMSE was $66.67W{\cdot}m^{-2}$. Conclusions: It is possible to utilize a solar module as a power source and a sensor to measure solar radiation for an agricultural sensor node.

• Journal of Korean Elementary Science Education
• /
• v.29 no.3
• /
• pp.326-340
• /
• 2010

TGT (teams-games-tournaments) cooperative learning is suggested as a method which enables both the individualized teaching-learning and the small group learning in students-centered open education. This study investigated the instructional effects of the pre-learning program applied by ICT-based TGT cooperative module for science museum excursion regarding of the earth and the moon on the science related attitude according to gender difference in elementary school science class. Three classes of third graders (N=87) at a elementary school were randomly assigned to the ICT-based TGT cooperative learning group, the ICT learning group, and traditional learning group. The students were taught about the planning of exploring the moon in the chapter of the earth and the moon, for 1 class hour. Prior to the instructions, the TOSRA(test of science related attitude) and achievement test were administered. Two-way ANCOVA results revealed that the scores of the ICT-based TGT cooperative learning group were significantly higher than the other learning groups for most of the TOSRA scales. However, there was a little significant difference among the three groups in the three distinct scales of TOSRA, Normality of Scientists, Leisure Interest in Science, and Career Interest in Science. Advantage/disadvantage and usefulness of ICT-based TGT cooperative learning were also discussed.

• Journal of the Korean earth science society
• /
• v.25 no.7
• /
• pp.595-603
• /
• 2004

This study investigated the effects of the application of a variety of ICT (Information communication Technology) cause the effects on self-directed learning characteristics, creativity and science achievement. In order to achieve the above aim, WBI (Web-Based Instructions), instructions using CD-ROM Titles and Instruction Module Using ICT for the unit were applied and analyzed which belongs to the area of 'the earth' in the subject 'science' for Elementary school students. Instructions using WBI materials, CD-ROM titles and Instruction Module Using ICT were found to be effective on 'science achievement', 'self-directed learning characteristics' and 'creativity'. They show meaningful effect on improving 'science achievement', 'self-directed learning characteristics' and 'creativity'. WBI proved more fruitful than instruction using CO-ROM titles, Instruction Module Using ICT on improving self-directed learning characteristics. Instruction Module Using ICT proved more fruitful than instruction using CD-ROM title, WBI on improving creativity.

• Journal of Information Technology Applications and Management
• /
• v.15 no.3
• /
• pp.153-167
• /
• 2008

This study examines the effect of sense of community on the relationship between learner satisfaction and influencing factors related to the online learning environment. Influencing factors related to the online learning environment are derived from previous literature and classified into two groups : social dimension (leader's enthusiasm, offline activities) and system dimension (usefulness, ease of use, enjoyability). Learner satisfaction is defined as the learners' perceived learning gains from taking an online class. Study participants included 250 university students from two different institutions. The participants were divided into 43 groups and asked to complete an online TOEIC preparation module using a commercial cooperative learning system over 4 weeks. Data were collected at three points for each participant, at the beginning, 3 weeks after, and at the end of the online module. Two system factors related to the online learning environment (ease of use, usefulness) directly influenced learner satisfaction, while social factors indirectly influenced learner satisfaction through the mediating role of sense of community.