• Korea Trade Review
• /
• v.46 no.2
• /
• pp.281-299
• /
• 2021

This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.96-109
• /
• 2011

Recently, the geographic information system(GIS) is generally used in various fields with the development of information and communication technology, with expansion of its applications and utilization scope. Especially, utilizing GIS is expected to have positive effects on the geography learning and more helpful for the geographic information observation compared to the picture or 2D based media. The effective visualization of complex geographic data does not only take realization of its visual information but also increases the human ability in analysis and understanding to use the geographic information. In this paper, we examine a method to develop the geography learning contents based on the technology with augmented reality and GIS, and then we have a case study for various kinds of visualization techniques and examples to use in geography learning situation. Moreover, we introduce an example of the manufacturing process from the existing GIS data to augmented reality based geography learning system. From the above, we show that the usefulness of our method is applicable for effective visualization of the three-dimensional geographic information in the geography learning environment.

• Hwankyungkyoyuk
• /
• v.11 no.2
• /
• pp.224-237
• /
• 1998

The purpose of this study that was based on the theory review about the practical use necessity of school landscape was to survey on the awareness of elementary school teachers about the applications of school landscape for environmental education. This study was carried out through the review of literature, the questionnaire to 132 elementary school teachers in Seongnam City. The findings derived from this study were as follows : First, School landscape is an important field as environmental education resource for the improvement of school environmental education. Especially, for the improvement of environmental sensitivity through field-experience learning, the practical applications of elementary school landscape is very important and urgent in aspects of environmental education theory, accessibility, and convenience. Second, Most of responded teachers give an affirmative answer about the field-experience learning for school environmental education and the necessity of practical use of school landscape for field-experience learning. Several the improvement to use elementary school landscape for environmental education being suggested by teachers are the increase of financial support, the magnification of school area, and the school landscape planning and design in consideration of environmental education by landscape architect expert. Third, Above half of teachers don't agree to use the roof garden for environmental education because of the safety of students and the school building construction. Fourth, Teachers are more satisfied with the status of school landscape maintenance than the practical usability of school landscape in aspect of environmental education and the facilities in school landscape. Teachers think that the most important functions and roles of school landscape is psychological factor.

• Journal of The Korean Association of Information Education
• /
• v.7 no.3
• /
• pp.331-339
• /
• 2003

This study is the content about the development of ICT(Information and Communication Technology) teaching-learning model to support the korean language learning. Firstly, we proposed 3 types on developing models for ICT teaching-learning in korean language learning, we developed 4 ICT teaching-learning models based on analysing the curriculum of korean language course and studying the preceding works. Moreover we offered the strategies for applying ICT teaching-learning models with korean language learning. The developed 4 ICT teaching-learning models in this study are expected that ICT will use to design ICT teaching-learning model in another courses and teachers take advantage of the 4 models in korean lesson effectively.

• International Journal of Contents
• /
• v.4 no.4
• /
• pp.18-23
• /
• 2008

With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies has a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they are not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

• Journal of Medicine and Life Science
• /
• v.21 no.3
• /
• pp.53-61
• /
• 2024

With the rapid development of technology and societal change, a shift from traditional classroom instruction to more diverse educational methods in medical education is necessary. As an effective approach to providing flexibility and accessibility while maintaining the benefits of face-to-face interactions, blended learning, which integrates online and offline learning, has gained attention. This study examines the current status and best practices of the aforementioned blended learning, analyzes its application in domestic and international contexts, and derives effective instructional design strategies. A comprehensive review of previous research and empirical cases reveals a conceptual framework and core principles for designing such blended learning. Key considerations include strategic integration of online and offline activities, facilitation of self-directed learning and interaction, effective use of technology, and continuous quality improvement. Furthermore, we suggest contextually relevant strategies, such as designing curricula focused on clinical reasoning, providing iterative practice opportunities, enhancing reflection, and fostering future competencies. The case analysis establishes that blended learning is implemented in various forms across different medical schools and curricula. Common features include the linkage of online and offline learning, incorporation of learner-centered methods, and emphasis on practical competencies. However, the limited number of cases suggests that generalizations may be premature. Successful implementation requires multifaceted efforts, including gradual introduction, faculty support, flexible curricula, safety measures, and institutional support. Accumulating empirical research and evidence of their effectiveness can facilitate their wider dissemination. This study provides implications and future directions for innovative medical education using hybrid learning.

• The Journal of Korean Association of Computer Education
• /
• v.17 no.3
• /
• pp.65-74
• /
• 2014

The purposes of this study were to analyze the mobile learning usages of adult learners and how their perceptions of the mobile learning affects their learning achievements in a cyber-university. 1,118 online adult learners who enrolled in a cyber-university in Korea were involved in this study and the data for their demographic information, mobile learning usages, the perceptions of mobile learning(self-efficacy for mobile learning, perceived ease of use, perceived usefulness, and learning satisfaction) and the learning achievement were collected. The main findings of this study were as follows. First, the subjects in this study showed higher participation rates in the mobile learning with recently introduced mobile devices compared to the results of previous studies. They also showed the need of more learning materials and video streamed lectures. Second, the higher-aged subjects showed relatively higher levels of perception of mobile learning compared to the lower-aged group. Third, the effects of the subjects' perceptions of mobile learning to their learning achievement seem to be limited. It was recommended to enhance the quality of the mobile learning especially considering the relationships between the perceived usefulness and the learning achievement.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.2
• /
• pp.213-219
• /
• 2020

In this paper, we propose a classification analysis method for diagnosing and predicting problematic smartphone use in order to provide policy data on problematic smartphone use, which is getting worse year after year. Attempts have been made to identify key variables that affect the study. For this purpose, the classification rates of Decision Tree, Random Forest, and Support Vector Machine among machine learning analysis methods, which are artificial intelligence methods, were compared. The data were from 25,465 people who responded to the '2018 Problematic Smartphone Use Survey' provided by the Korea Information Society Agency and analyzed using the R statistical package (ver. 3.6.2). As a result, the three classification techniques showed similar classification rates, and there was no problem of overfitting the model. The classification rate of the Support Vector Machine was the highest among the three classification methods, followed by Decision Tree and Random Forest. The top three variables affecting the classification rate among smartphone use types were Life Service type, Information Seeking type, and Leisure Activity Seeking type.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.712-715
• /
• 1997

In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

• Journal of Electrical Engineering and Technology
• /
• v.10 no.2
• /
• pp.659-669
• /
• 2015

Face Recognition assumes much significance in the context of security based application. Normally, high resolution images offer more details about the image and recognizing a face from a reasonably high resolution image would be easier when compared to recognizing images from very low resolution images. This paper addresses the problem of recognizing faces from a very low resolution image whose size is as low as $8{\times}8$. With the use of CCTV(Closed Circuit Television) and with other surveillance camera-based application for security purposes, the need to overcome the shortcomings with very low resolution images has been on the rise. The present day face recognition algorithms could not provide adequate performance when employed to recognize images from VLR images. Existing methods use super-resolution (SR) methods and Relation Based Super Resolution methods to construct from very low resolution images. This paper uses a learning based super resolution method to extract and construct images from very low resolution images. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.