• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.21-30
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• 2015

Information and knowledge society in the 21st century computer education is very important. Computer programming education in computer education is very important. There are very few teaching and learning model of computer programming education. In this paper, we develop a self-regulated learning model for students to be self-regulated learning. In this study, we propose self-regulated learning elements, a self-regulated learning steps and self-regulated learning modele. Self-regulated learning elements are task level, generalized level, and efficiency level. Self-regulated learning phases are problem understanding, design, and coding, testing, and maintenance. Self-regulated learning models are to copy, to modify, create, and to challenge. The results of this study are as follows. At Correlations between learning elements and achievement, generalized level, and efficiency level are higher than the task level. At Correlations between learning and achievement, Understanding and design stages are higher than the other stages. At Correlations between learning model and achievement, to transform, to create, and to challenge are higher than to copy.

• Knowledge Management Research
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• v.17 no.2
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• pp.205-229
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• 2016

Owing to the current economic downturn, one of the most important goals of the organizations who are actively involved in Information Technology Outsourcing (ITO) is the cost efficiency. We focus on supplier firm's domain understanding to make the cost efficiency; therefore, we examine how the disadvantages from lower domain knowledges affect outsourcing performance moderated by outsourcing ratio and knowledge change environments. That is, if clients can endure disadvantage from service providers' lower domain knowledge, they can achieve cost efficiency by choosing lower domain knowledge suppliers with less expensive cost. To examine performance gap depending on the environments, we applied 'A Learning Model of IT Outsourcing' which is suggested by previous literature. As a result, we suggest five strategies for clients to contract with suppliers which have lower domain knowledge: (1) Prepare the strategy to endure disadvantages from the early stage. (2) Make the strategy depending on outsourcing ratio. (3) Knowledge transfer between organizations is important. (4) Make a short-term contract if they do not have good environments for organizational learning. (5) Client's knowledge change environments are more important than those of supplier's. Finally, we offer various implications for clients and suppliers in IT outsourcing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.283-287
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• 2020

In this paper, we implemented a control for ventilation system based on IoT. It can on/off of system and monitoring current status through the smartphone app. We applied linear regression, one of machine learning algorithm. It autonomously collects data about temperature, humidity in home and works diagnosing system status. Using this proposed control method, the energy efficiency can be improved. It is expected to be used in energy efficiency and convenience.

• ETRI Journal
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• v.45 no.6
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• pp.963-973
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• 2023

Non-orthogonal multiple access (NOMA) is considered a key candidate technology for next-generation wireless communication systems due to its high spectral efficiency and massive connectivity. Incorporating the concepts of multiple-input-multiple-output (MIMO) into NOMA can further improve the system efficiency, but the hardware complexity increases. This study develops an energy-efficient (EE) subchannel assignment framework for MIMO-NOMA systems under the quality-of-service and interference constraints. This framework handles an energy-efficient co-training-based semi-supervised learning (EE-CSL) algorithm, which utilizes a small portion of existing labeled data generated by numerical iterative algorithms for training. To improve the learning performance of the proposed EE-CSL, initial assignment is performed by a many-to-one matching (MOM) algorithm. The MOM algorithm helps achieve a low complex solution. Simulation results illustrate that a lower computational complexity of the EE-CSL algorithm helps significantly minimize the energy consumption in a network. Furthermore, the sum rate of NOMA outperforms conventional orthogonal multiple access.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.224-230
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• 2022

The intent of this paper is to unveil the effectiveness of different learning environments (traditional, electronic, blended) in educational institutions through a set of dimensions: an introduction to traditional education and e-learning, the importance and objectives of e-learning, the difference between e-learning and traditional education and teachers' roles in e-learning, the challenges facing the use of e-learning. It also introduces blended learning, providing an account about its emergence, concept, importance, the difference between blended learning and e-learning, the advantages of blended learning, and the challenges confront using blended learning.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.309-316
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• 2021

The purpose of this study is to verify the effectiveness of community-based learning(CBL) on career decision-making self-efficiency of junior college students and explore the meaning. This study was conducted on 68 students and 10 departments participating in the CBL, which was supported by the D University Faculty Learning Development Center in Busan. First of all, does CBL affect the career decision-making self-efficiency for junior college students? Second, what is the meaning of CBL for career decisions for junior college students? The effectiveness of the CBL's before and after application surveys has shown statistically significant changes in the career decision-making self-efficiency. The meaning of CBL for learners' career decisions was derived from "improving understanding through on-site application of theory and creating confidence and commitment in their career paths by providing an opportunity to study." Through this, it can be seen that CBL is worth applying as a teaching method suitable for career guidance of junior college students.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.23-27
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• 2007

Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In time domain, a room impulse response is generally considered as the combination of three parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for the room impulse response. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the length or boundary of each model in the hybrid model. By the simulation with measured room impulse responses, it was examined that the performance of proposed model shows the best efficiency in views of both the parameter numbers and modeling error.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.361-367
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• 2008

Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In the time domain, room impulse responses are generally considered as combination of the three Parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for room impulse responses. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the boundary of each model in the hybrid model. By the simulation with measured room impulse responses, the performance of proposed model shows the best efficiency in views of computational burden and modeling error.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.192-194
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• 2006

In this paper, the situation of energy efficiency standards for motors and diffusion states are analyzed and a new methodology is proposed using diffusion models and learning curves. The existing diffusion models could not explain affects from new appliances' penetration during the diffusion. But a mixed diffusion model with learning curves or learning ratio is studied to explain this penetration.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.382-386
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• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.