• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.294-297
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• 2024

Malware detection has become increasingly critical with the proliferation of end devices. To improve detection rates and efficiency, the research focus in malware detection has shifted towards leveraging machine learning and deep learning approaches. This shift is particularly relevant in the context of the widespread adoption of end devices, including smartphones, Internet of Things devices, and personal computers. Machine learning techniques are employed to train models on extensive datasets and evaluate various features, while deep learning algorithms have been extensively utilized to achieve these objectives. In this research, we introduce TabNet, a novel architecture designed for deep learning with tabular data, specifically tailored for enhancing malware detection techniques. Furthermore, the Synthetic Minority Over-Sampling Technique is utilized in this work to counteract the challenges posed by imbalanced datasets in machine learning. SMOTE efficiently balances class distributions, thereby improving model performance and classification accuracy. Our study demonstrates that SMOTE can effectively neutralize class imbalance bias, resulting in more dependable and precise machine learning models.

• The Journal of Korean Association of Computer Education
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• v.11 no.2
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• pp.79-87
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• 2008

The self-regulated learning was making an alternative idea to improve a learning effect of student who takes part in a study course. This research aimed the self- regulated learning of E-learning system. Also. in this system, the students were able to select the learning object according to the learning method for improving learning effect that students take part in study spontaneously. And the learning logic was implemented for development efficiency and operation by web service. Finally, the test result of study group who had the similar studying level displayed that the proposal method was better learning effect than exist one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.687-690
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• 2007

Opening and participation, blog that mean public ownership, 2.0 series with UCC etc.. etc. is popularized to supply spread of latest web 2.0 technologies. While e-Learning was speaker initiative, lean much to elder brother knowledge last month and real condition that participation of learners is inactive in this running race meantime, e-Learning 2.0 that apply web 2.0 know-hows is offering environment that can spring this boundary. Because e-Learning applies well web 2.0, necessity of development of this running race 2.0 systems is risen with participation of learners and public ownership. e-Learning 2.0 may improve each other efficiency of study epochally exchanging studying method or know-how, information, summary notebook etc. with participation and public ownership.

• The Journal of Korean Academic Society of Nursing Education
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• v.26 no.3
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• pp.238-247
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• 2020

Purpose: The purpose of this study was to identify the relationship between intrinsic motivation and learning outcomes of nursing college students who took the Fundamentals of nursing as a problem-based learning method. Methods: In this cross-sectional study, we identified the intrinsic motivations of 114 nursing students who completed problem-based learning using the Intrinsic Motivation Inventory. The t-test was conducted to identify differences according to intrinsic motivation, and correlation analysis was performed to confirm the relationship between intrinsic motivation and learning outcomes. Results: The group with higher intrinsic motivation showed higher scores in all domains of self-assessed learning outcomes than the lower group. It was the 'Relatedness with an instructor' that showed the highest correlation with the learning outcomes in the domains of intrinsic motivation. Conclusion: Problem-based learning is an effective learning method for cultivating the competencies needed for nurses. The intrinsic motivation of students is an important factor in the performance of problem-based learning. For the efficiency of problem-based learning, efforts should be made to develop and apply autonomy-supportive interventions that can enhance intrinsic motivation.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.

• Knowledge Management Research
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• v.17 no.3
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• pp.207-225
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• 2016

Recently, flipped learning is being highlighted especially at the college of engineering because of its self-directed learning which direction matches that of the engineering education system. Although many engineering professors have tended to apply the flipped learning to their classes, they experienced a number of significant problems and challenges in practical implementing. By using TRIZ method as a tool for creative problem solving, that have been developed and applied in many fields ranging from engineering as well as management, this study aims to solve the education dilemma between learning efficiency and learning effectiveness, create a new concept of the flipped learning based on the solutions, and then explore its educational feasibility for successfully adopting it to engineering courses. This study suggests an instructional design for implementing the flipped learning according to the characteristics of engineering classes and then designs a new model of the flipped learning according to that procedure. Also, based on the empirical results in applying a new flipped learning model to the applied mathematics, this paper proposes several guidelines for the successful application of flipped learning in the future.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.05a
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• pp.409-424
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• 2005

Today, many universities are confronted with the changing education paradigm such as e-Learning, Distance Education, Virtual University. This IT-based learning paradigm shift is certainly a new opportunity or a threat to our universities. The Local University Community e-Learning Centers that support the demand of e-Learning for their community are recommended. Tn order to operate these centers efficiently, the strategic roles of the e-Learning center should first be defined. To define the strategic roles, We classified the strategic roles of the e-Learning center into four dimensions, (1) to improve management efficiency, (2) to enhance educational service, (3) to acquire competitive advantages, (4) to build new education infrastructure, and each dimension has S or 6 measurement items. As result, to enhance the educational service was considered as the most significant factor among the four dimensions of strategic roles, and the infrastructure building was the next. Through the strategic roles definition and analysis of expected role ratings, we could have recommended the direction and operation policies of the e-Learning centers.

• Journal of Energy Engineering
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• v.27 no.2
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• pp.26-31
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• 2018

This paper introduces a study to improve the thermal efficiency of the district heating user control facility based on reinforcement learning. As an example, it is proposed a general method of constructing a deep Q learning network(DQN) using deep Q learning, which is a reinforcement learning algorithm that does not specify a model. In addition, it is also introduced the big data platform system and the integrated heat management system which are specialized in energy field applied in processing huge amount of data processing from IoT sensor installed in many thermal energy control facilities.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.71-80
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• 2010

The purpose of this research is to help IPTV (Internet Protocol Television) commercialization using newly produced educational contents in the area of entertainment and education which currently popular in the market. It is called, Stimulus $Tester^{TM}$, endow reaction time from the feedback of learning system, using a non-direct method, for example, a remote controller. Reaction time is the learning efficiency promotion mechanism that learner ascertain the learning condition of oneself by the time with solved questions from the solving the question in given time. Reaction time also play a key role that the learner may go through course which distribute the point to PC from Server. If this system is ready, we expect that the educational industry will gradually spread out. To verify the learning efficiency of this system, we concluded that the learning improvements, by an Internet-based and a paper-based test, of the increase by 51%, from 2.47min to 1.27min, during reaction of 7 days.