• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.127-134
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• 2000

Distance education, which emerged under the influence of both the rapid development of hi-tech information technology and the constructivism theory of learning, enables learners to acquire knowledge and skills needed by monitoring their learning process for themselves. Emphasis on web-based distance education and contructivism as a basis of learner-centered education does not mean that those education systems are performed without teachers or in noninterference. This study proposes a model of distance education system in which learners are taught in various levels of learning with the help of teacher agents. In the model teacher agents produce the learners' respective learning model considering the information on individual learners and also control the progress to the next step of learning with the result of the evaluation of learning accomplishment. The model of distance education system suggested in this study is able to help solve the problem that the learning resources web-based distance education provides were used only as objects of web search and to supply a basis of realizing learner-centered education.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.145-160
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• 2012

The globe-trotting trend has been converted from tourism for the simple purposes of sightseeing and enjoyment to a form of learning and practicing the more specialized contents by directly participation. Traditional cultural resources have sufficient potential as culture and tourism assets that fit this kind of trend. Therefore, building proper tourist resources for their application has become a very urgent and important matter. To make masterpiece tourism packages through combined services of traditional cultural resources, it is necessary for operators to ponder diverse methods that can be used to develop various experience programs and conserve traditional cultural properties by continuously generating profits. The major results of this research are as follows. Firstly, this study proposes plans for unified tourist information and combined services of traditional cultural resources based on ubiquitous IT. Secondly, it is ascertained that the organization of combined operational consultative groups and the improvement of operator' capability are required to execute combined services of traditional cultural resources. Thirdly, we propose business plans to generate profits in both product aspect and network aspect.

• Journal of Energy Engineering
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• v.28 no.1
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• pp.45-48
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• 2019

Currently, the global atmosphere around the world is altering at a very rapid pace. Among those changes, some are beneficial, but most of the changes are lead to destruction to our planet. The area of environmental science is a significant resource for learning more about these changes. Due to the urbanization, the human population is increasing, natural resources becoming very limited. To solve the limited resources issues, recycling is absolutely an alternative source for the new demands and limitations. Recycling education is very important to raise awareness among students and their communities about the need for recycling and what materials are recyclable locally. In this paper, we reported the role of sustainability science and technology and the impact of recycling research education in the middle schools, both in developing countries and Asian countries and also we included the brief data of global recycling of waste.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.1
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• pp.49-65
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• 2022

This study examined e-resources usage among polytechnic students in Southwest Nigeria. A descriptive research design was adopted for this study and the population consisted of polytechnic students from The Polytechnic, Ibadan and Federal Polytechnic, Ede. There were 9671 students from both polytechnics. A multi-stage sampling technique was employed with a sample fraction of 5% was drawn from the total number of students in each faculty amounting to 381. A structured questionnaire was the major instrument used for data collection and the questionnaire was pre-tested using Cronbach-alpha to determine the reliability co-efficient. Data obtained was analyzed using SPSS. The study found that the students from both polytechnics are aware of the e-resources and that the e-resources were mainly used for research, class assignment and to update knowledge. The problem such as epileptic power supply, poor internet connection and so on was identified. The study concluded that polytechnic students could benefit immensely from the enormous usage of e-resources particularly for teaching, learning and research. Based on the findings, recommendations were made.

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.115-118
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• 2000

In order to control the flow of traffics in ATM networks and optimize the usage of network resources, an efficient control mechanism is necessary to cope with congestion and prevent the degradation of network performance caused by congestion. To effectively control traffic in UNI(User Network Interface) stage, we proposed algorithm of integrated model using on-line teaming neural network for CAC(Call Admission Control) and UPC(Usage Parameter Control). Simulation results will show that the proposed adaptive algorithm uses of network resources efficiently and satisfies QoS for the various kinds of traffics.

• KNOM Review
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• v.21 no.2
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• pp.1-9
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• 2018

Network virtualization refers to a technology creating independent virtual network environment on a physical network. Network virtualization technology can share the physical network resources to reduce the cost of establishing the network for each user and enables the network administrator to dynamically change the network configuration according to the purpose. Although the network management can be handled dynamically, the management is manual, and it does not maximize the profit of network virtualization. In this paper, we propose Machine-Learning technology to allow the network to learn by itself and manage its management dynamically. The proposed approach is to dynamically allocate appropriate resources by predicting resource demand of VNF in service function chaining, which is a core and essential problem in virtual network management. Our goal is to predict the resource demand of the VNF and dynamically allocate the appropriate resources to reduce the cost of network operation while preventing service interruption.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.43-54
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• 2024

Recently, there has been a lot of research on utilizing Language Models, and Large Language Models have achieved innovative results in various tasks. However, the practical application faces limitations due to the constrained resources and costs required to utilize Large Language Models. Consequently, there has been recent attention towards methods to effectively utilize models within given resources. Curriculum Learning, a methodology that categorizes training data according to difficulty and learns sequentially, has been attracting attention, but it has the limitation that the method of measuring difficulty is complex or not universal. Therefore, in this study, we propose a methodology based on data heterogeneity-based Curriculum Learning that measures the difficulty of data using reliable prior information and facilitates easy utilization across various tasks. To evaluate the performance of the proposed methodology, experiments were conducted using 5,000 specialized documents in the field of information communication technology and 4,917 documents in the field of healthcare. The results confirm that the proposed methodology outperforms traditional fine-tuning in terms of classification accuracy in both LoRA fine-tuning and full fine-tuning.

• Journal of Gifted/Talented Education
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• v.21 no.2
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• pp.357-372
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• 2011

Enhancing individual competitiveness as well as national competitiveness by fostering creative human resources are one of the important visions of the nation. Thus, fostering creative human resources should be important mission of the nation. The purpose of this study is to identify what type of creative human resources is possible, based on Korean culture and background. Qualitative research experts was given to six experts of academics, institutes, and industries in science, humanities, social science, and art. The result indicated that key words for fostering creative human resources in Korea are 'fusion' and 'integration', and the definition and factors of creative human resources as well as educational strategy to foster it depend upon them. How to foster creative human resources in life-long learning also discussed.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.