• Journal of the Korea Convergence Society
• /
• v.13 no.4
• /
• pp.17-24
• /
• 2022

Bitcoin is a peer-to-peer cryptocurrency designed for electronic transactions that do not depend on the government or financial institutions. Since Bitcoin was first issued, a huge blockchain financial market has been created, and as a result, research to predict Bitcoin price data using machine learning has been increasing. However, the inefficient Hyper-parameter optimization process of machine learning research is interrupting the progress of the research. In this paper, we analyzes and presents the direction of Hyper-parameter optimization through experiments that compose the entire combination of the Timesteps, the number of LSTM units, and the Dropout ratio among the most representative Hyper-parameter and measure the predictive performance for each combination based on Bitcoin price prediction model using LSTM layer.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.105-112
• /
• 2022

The development and spread of IT-technologies has raised interest in teaching programming pupils. The article deals with problems related to programming and ways to overcome them. The importance of programming skills is emphasized, as this process promotes the formation of algorithmic thinking of pupils. The authors determined the level of pupils' interest to programing learning depending on the age. The analysis has showed that the natural interest of younger pupils in programming is decreasing over the years and in the most productive period of its study is minimized. It is revealed that senior school pupils are characterized by low level of interest in the study of programming; lack of motivation; the presence of psychological blocks on their own abilities in the context of programming; law level of computer science understanding. To overcome these problems, we conducted the second stage of the experiment, which was based on a change in the approach to programing learning, which involved pupils of non-specialized classes of senior school (experimental group). During the study of programming, special attention was paid to the motivational and psychological component, as well as the use of game technologies and teamwork of pupils. The results of the pedagogical experiment on studying the effectiveness of teaching programming for pupils of nonspecialized classes are presented. Improvement of the results provided the use of social and cognitive motives; application of verbal and non-verbal, external and internal means; communicative attacks; stimulation and psychological setting; game techniques, independent work and reflection, teamwork. The positive effect of the implemented methods is shown by the results verified by the methods of mathematical statistics in the experimental and control groups of pupils.

• International Journal of Computer Science & Network Security
• /
• v.22 no.7
• /
• pp.268-282
• /
• 2022

One of the most important technologies today is augmented reality technology, it allows users to experience the real world using virtual objects that are combined with the real world. This technology is interesting and has become applied in many sectors such as the shopping and medicine, also it has been included in the sector of education. In the field of education, AR technology has become widely used due to its effectiveness. It has many benefits, such as arousing students' interest in learning imaginative concepts that are difficult to understand. On the other hand, studies have proven that collaborative between students increases learning opportunities by exchanging information, and this is known as Collaborative Learning. The use of multimodal creates a distinctive and interesting experience, especially for students, as it increases the interaction of users with the technologies. The research aims at developing collaborative framework for developing achievement of 6th graders through designing a framework that integrated a collaborative framework with a multimodal input "hand-gesture and touch", considering the development of an effective, fun and easy to use framework with a multimodal interaction in AR technology that was applied to reformulate the genetics and traits lesson from the science textbook for the 6th grade, the first semester, the second lesson, in an interactive manner by creating a video based on the science teachers' consultations and a puzzle game in which the game images were inserted. As well, the framework adopted the cooperative between students to solve the questions. The finding showed a significant difference between post-test and pre-test of the experimental group on the mean scores of the science course at the level of remembering, understanding, and applying. Which indicates the success of the framework, in addition to the fact that 43 students preferred to use the framework over traditional education.

• Journal of The Geomorphological Association of Korea
• /
• v.28 no.1
• /
• pp.101-114
• /
• 2021

Junior Ranger is a self-directed interpretation program for young visitors at national parks in the United States. The success of this program can be largely attributed to the role of an activity book which is given an applicant free of charge at a visitor center. This study aims to analyze the main characteristics of activity books for 14 national parks' Junior Ranger and to draw some implications for Korean geomorphological education. Although the activity books are varied in size, volume and printing, all of them offer diverse activities which are composed of different contents related to park resources in four fields and are performed in different ways such as Q&A, picture and word game, and creative activity. The time-consuming activities including attendance at a ranger-led program prevent the participant from making a superficial visit to be a junior ranger. The implications of the study are as follows: Firstly, the geomorphological education for children is needed to be strongly based on field experience learning and to be more carried out using a way of game rather than conventional Q&A, suggesting that it encourages students not to lose their interest for learning. Secondly, it is also necessary for the learning contents to be focused on various resources related to landform as well as landform itself. In addition, a creative activity such as writing verse or drawing feeling should be more applied to the geomorphological education in order to enhance their effects on affective domain beyond cognitive one. It is likely to be an alternative approach to understand landform by internalizing a sense of landform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.133-136
• /
• 2018

Today, the environment in which type 1 Diabetes children learn how to cope with their Diabetes is very vulnerable. Therefore, it is necessary to create an environment that can respond to changes in blood sugar level of children. The purpose of this study is to suggest game-based educational content on how to deal with changes in blood sugar level through behavioral methods for children with type 1 Diabetes. The purpose of this study is to suggest education type game contents using hybrid method which enhances efficiency in learning children 's expert knowledge. Based on the results of the interviews conducted with diabetes specialists for this study, we suggested the contents of coping with blood sugar change composed of education contents required for the children. As a result of this study, it was found that the hybrid factor was useful in learning diabetes through games. These game contents are expected to provide an environment that children with diabetes can learn more efficiently.

• Advanced Industrial SCIence
• /
• v.2 no.3
• /
• pp.8-14
• /
• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.321-324
• /
• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement Beaming is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement loaming is different from supervised teaming in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement loaming algorithms like Q-learning do not require defining or loaming any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning(AMMQL) as an improvement of the existing Modular Q-Learning(MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.145-156
• /
• 2018

Unlike the past, when distributors distributed games through retail stores, they are now selling digital content, which is based on online distribution channels. This study analyzes the effects of eWOM (electronic Word of Mouth) on sales volume of game sold on Steam, an online digital content distribution channel. Recently, data mining techniques based on Big Data have been studied. In this study, emotion index of eWOM is derived by emotional analysis which is a text mining technique that can analyze the emotion of each review among factors of eWOM. Emotional analysis utilizes Naive Bayes and SVM classifier and calculates the emotion index through the SVM classifier with high accuracy. Regression analysis is performed on the dependent variable, sales variation, using the emotion index, the number of reviews of each game, the size of eWOM, and the user score of each game, which is a rating of eWOM. Regression analysis revealed that the size of the independent variable eWOM and the emotion index of the eWOM were influential on the dependent variable, sales variation. This study suggests the factors of eWOM that affect the sales volume when Korean game companies enter overseas markets based on steam.

• Journal of The Korean Association of Information Education
• /
• v.14 no.3
• /
• pp.395-404
• /
• 2010

One of the object on math education is low-level students. To improve this problem and to instruct efficiently I developed "let's play figures" instruction and learning system. This system reconstructed diagram part of math into 5steps to achieve the goal of tailored education to fit student's learning level. Based on this, the game can be used as the teaching method to enhance the student's interest and self-studying ability and also this system has been developed for the education connected to home.

• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.142-146
• /
• 2023

We present a method for generating 3D structures and rendering objects by combining VAE (Variational Autoencoder) and GAN (Generative Adversarial Network). This approach focuses on generating and rendering 3D models with improved quality using residual learning as the learning method for the encoder. We deep stack the encoder layers to accurately reflect the features of the image and apply residual blocks to solve the problems of deep layers to improve the encoder performance. This solves the problems of gradient vanishing and exploding, which are problems when constructing a deep neural network, and creates a 3D model of improved quality. To accurately extract image features, we construct deep layers of the encoder model and apply the residual function to learning to model with more detailed information. The generated model has more detailed voxels for more accurate representation, is rendered by adding materials and lighting, and is finally converted into a mesh model. 3D models have excellent visual quality and accuracy, making them useful in various fields such as virtual reality, game development, and metaverse.