• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2942-2960
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• 2022

The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

• Journal of Internet of Things and Convergence
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• v.2 no.3
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• pp.1-6
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• 2016

This paper aims to present the physical computing learning model applicable in teaching the information and communication technology for technology and engineering education. This model is based on the physical computing and deals with the information creation and information transfer in one framework, thus provides students with the total understanding and practice opportunity about information and communication. The proposed learning models are classified into the client-server based model and the web based model. In the implemented learning model, the acquirement and control of information is performed by sketch on Arduino and the communication of information is performed by the Python socket on Raspberry Pi well known as an education platform. Our proposed learning model can be used for teaching students to understand the concept of Internet of Things (IoT), which provides us with world wide control and communication of information.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1500-1506
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• 2020

In this paper, we study a scheduling problem based on reinforcement learning for overlay device-to-device (D2D) communication networks. Even though various technologies for D2D communication networks using Q-learning, which is one of reinforcement learning models, have been studied, Q-learning causes a tremendous complexity as the number of states and actions increases. In order to solve this problem, D2D communication technologies based on Deep Q Network (DQN) have been studied. In this paper, we thus design a DQN model by considering the characteristics of wireless communication systems, and propose a distributed scheduling scheme based on the DQN model that can reduce feedback and signaling overhead. The proposed model trains all parameters in a centralized manner, and transfers the final trained parameters to all mobiles. All mobiles individually determine their actions by using the transferred parameters. We analyze the performance of the proposed scheme by computer simulation and compare it with optimal scheme, opportunistic selection scheme and full transmission scheme.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.345-353
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• 2011

Information and communication brings us some degree of convenient but also serious side effects. Especially, information and communication ethics is an important issue for elementary school children who are early stage in moral value. This paper proposes a triple-connected teaching and learning model. which can be applied to the elementary school children. in order to improve the educational level. The model is formed by selecting three discretionary teaching models, and applying independently them into the different classes with linking the contents for each class. A teacher can choose the teaching models based on what he wants to teach. Caring model, Home-Connected model and Simulation model were linked in our experiment. Experiments were conducted in the same condition but different learning models, Then, an educational effect was compared and analyzed in the educational level improvement point of view, between the Triple-connected teaching and learning model and the single teaching and learning model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.36-45
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• 2011

An agent in collaborative e-learning has independent function for learners in any circumstance, status and task by the reasonable and general means for social learning. In order to perform it well, communication among agents requires standardized and regular information technology method. This study suggests data model as a communication tool for various agents. Therefore this study shows various agents types for collaborative learning, designation of rule for data model that enable to communicate among agents and data element of agent communication data model. A multi-agent e-learning system using like this standardized data model should able to exchange the message that is needed for communication among agents who can take charge of their independent tasks. This study should contribute to perform collaborative e-learning successfully by the application of communication data model among agents for social learning.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.79-83
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• 2021

This paper proposes a novel image classification method based on few-shot learning, which is mainly used to solve model overfitting and non-convergence in image classification tasks of small datasets and improve the accuracy of classification. This method uses model structure optimization to extend the basic convolutional neural network (CNN) model and extracts more image features by adding convolutional layers, thereby improving the classification accuracy. We incorporated certain measures to improve the performance of the model. First, we used general methods such as setting a lower learning rate and shuffling to promote the rapid convergence of the model. Second, we used the data expansion technology to preprocess small datasets to increase the number of training data sets and suppress over-fitting. We applied the model to 10 monkey species and achieved outstanding performances. Experiments indicated that our proposed method achieved an accuracy of 87.92%, which is 26.1% higher than that of the traditional CNN method and 1.1% higher than that of the deep convolutional neural network ResNet50.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.111-123
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• 2020

The core competencies for the 21st century are creativity, critical thinking, collaboration, and communication. In recent classes where ICT (information, communication, and technology) is grafted, a lot of efforts are also being made to increase such competencies. According to a research work, ICT is most often used as a communication channel between teachers and students or as an online collaboration tool among students. However, ICT has only played a role as a guideline for instruction, but not included in the curriculum until now. The research on methods how to integrate technology into teaching and learning is in full swing due to the development of technology and the advent of Covid-19. In this paper, we propose a technology integration hierarchy model, namely K-TIHM that can be combined with STEAM education. Since only learning environments have been proposed in the existing research for technology-based STEAM education, our model proposes a series of technology integration hierarchy that can be applied by school age along with STEAM. Also, we analyze the differences in among the Korea's ICT education operation guidelines, the Korea's Software education guidelines, and ours. The proposed model can help developing the primary and secondary school curriculum integrated with technology.

• The Journal of Korean Institute for Practical Engineering Education
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• v.5 no.1
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• pp.28-33
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• 2013

In this paper, we proposed a smart learning model that reflects the environment of information and communication that rapidly changing with the advent of smart devices. There are varieties of screen size and performance of smart devices, but they can be classified smart phones, smart pads, personal computer(PC) and Smart TV. In this paper, we look for appropriate services model with method of interaction and educational content as per each device type, then present the development direction of smart learning that reflects the information communication environment and future smart learning service model according to the characteristics of each device.

• Journal of The Korean Association of Information Education
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• v.18 no.4
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• pp.625-632
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• 2014

Due to the development of information and communication technology smart devices and apps, SNS, mirroring communication is made with such a smart and education to reflect the change of emphasis on the recent variety of collaborative social interaction are emerging. In this study, smart training and LT cooperative learning model developed in conjunction with the 'Smart-based cooperative learning 'model applied in the third grade social studies class and Smart-based cooperative learning and cooperative learning common to kidney doctor communication skills of elementary school students the impact on the communication capacity compared respectively, were analyzed. As a result, the expression of the elementary school, listening and understanding, all the sub-areas of interaction, such as communication skills in social studies class kidneys were applied to Smart-based cooperative learning in elementary school than applying the general cooperative learning model. This is not said to improve the ability to interact with the Smart-based cooperative learning in speech and in writing and clearly express the thoughts and opinions of students and separates help you understand the meaning of the words and writings of other students for the purpose in social situations can.