• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.413-415
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• 2021

Piano is one of the most beloved instruments in the world and is used a lot for children to learn music because it is simple to play. As a result, various products for children, such as toy pianos, were released. However, there is a lack of piano skills for music education, such as how to play the piano or read the score. To solve this problem, in this paper, we propose a game-style educational piano using Arduino. It is expected to capture fun and education at a low price by scoring points by displaying the score on the LCD screen and pressing the keyboard according to the timing of playing the note.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.619-630
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• 2015

The purpose of this study is to provide basic information to develop a game strategy plan of a team in a future by identifying the patterns of attack and pass of national men's professional volleyball teams and extracting core key words related with volleyball game performance to evaluate game performance using 'social network analysis' and 'text mining'. As for the analysis result of 'social network analysis' with the whole data, group '0' (6 players) and group '1' (11 players) were partitioned. A point of view the degree centrality and betweenness centrality in 'social network analysis' results, we can know that the group '1' more active game performance than the group '0'. The significant result for two group (win and loss) obtained by 'text mining' according to two groups ('0' and '1') obtained by 'social network analysis' showed significant difference (p-value: 0.001). As for clustering of each network, group '0' had the tendency to score points through set player D and E. In group '1', the player K had the tendency to fail if he attack through 'dig'; players C and D have a good performance through 'set' play.

• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.15-24
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• 1997

In this paper we suggested a performance evaluation model for future weapon systems. Weapon Performance Index(WPI) model transform the characteristics of alternatives as indices. We can easily obtain WPIs of alternatives with the model. The highest WPI recommended as the best solution. The performance elements in hierachy for future weapon systems are determined by systems engineering procedure. Priorities in hierachy can be determined through survey of experts engineering procedure. Priorities in hierachy can be determined through survey of experts and statistical analysis. Utility function is formulated as a probability model and utility score is predicted on the basis of historical data about the same category of weapon systems in the world. WPI is calculate from sum of product of priorities and utility scores. The model can be applied to trade-off analysis, cost and effectiveness analysis, war game model.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.45-50
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• 2017

This paper proposes a novel resource allocation scheme which allows to guarantee the user-perceived service quality for various high-quality mobile multimedia service such as interactive game, tactile internet service, remote emergency medical service or remote disaster handling robot control to a certain level in the mobile networks. In our proposed scheme, Mean Opinion Score(MOS), which represents the degree of user satisfaction for perceived quality, is determined based on the delay limit allowable to each service. Moreover resources are allocated in consideration of this MOS. Simulation results show that our proposed scheme can decrease the outage probability in comparison with existing schemes Moreover it can increase the total throughput as well.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.61-62
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• 2015

본 논문에서는 XNA Framework 기반의 모바일 게임 Cops VS Gangster를 설계하고 구현한다. 이 모바일 게임은 단순 피하기 게임 장르로 배경은 도로, 아파트 단지 등 생활 주변과 유사하도록 구현하였으며, 경찰차( Cops)는 오토바이(Gangster)의 주행을 피하면서 전진한다. 경찰차가 라이프(Heart)와 접촉하면 점수(Score)를 획득하고, 오토바이와 접촉하면 게임이 종료된다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.17-24
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• 2019

In this paper, we propose a new model for predicting effective Win/Loss in professional baseball game in Korea using machine learning technique. we used basic baseball data and Sabermetrics data, which are highly correlated with score to predict and we used the deep learning technique to learn based on supervised learning. The Drop-Out algorithm and the ReLu activation function In the trained neural network, the expected odds was calculated using the predictions of the team's expected scores and expected loss. The team with the higher expected rate of victory was predicted as the winning team. In order to verify the effectiveness of the proposed model, we compared the actual percentage of win, pythagorean expectation, and win percentage of the proposed model.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.593-600
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• 2021

In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.769-782
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• 2022

A study on agricultural automation became more important. In Korea, sweet persimmon farmers spend a lot of time and effort on classifying profitable persimmons. In this paper, we propose and implement an efficient grading algorithm for persimmons before shipment. We gathered more than 1,750 images of persimmons, and the images were graded and labeled for classifications purpose. Our main algorithm is based on EfficientDet object detection model but we implemented more exquisite method for better classification performance. In order to improve the precision of classification, we adopted a machine learning algorithm, which was proposed by PyCaret machine learning workflow generation library. Finally we acquired an improved classification model with the accuracy score of 81%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.526-528
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• 2022

In this study, through the capstone design project, an IoT based piano training system was developed after identifying problems in piano learning. The piano training system recognizes sheet music through image processing technology and checks whether the correct keyboard is struck through FFT transformation during piano practicing. By providing a visual effect and score display function using a rhythm game, it was possible to arouse interest in boring piano practice and increase the effect of piano learning.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.369-377
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• 2013

The purpose of this study was to explore which factors mostly influenced players' tour results employing tour skill factors provided by LPGA. For this study, Top 10 LPGA players' stats during 9 years (2004 2012) were used. As matter of fact, 10 variables were used like average score, top 10 finish, average putt, average birdies, average eagles, driving distance, driving accuracy, greens in regulation, sand saves, putts per GIR. and prize money earning. Stepwise multiple regression was conducted using SPSS win 20.0. Results indicated that the most influential tour skill factor to 9 seasons' results was average score, second influential factor was average putt, and the third factor was driving distance, and then top 10 finish was the fourth. Also on a year on year basis, 2004 was average score, 2005 was GIR., 2006 was average eagles, 2007 was top 10 finish, 2008 was average score, 2009 was average putt, 2010 were average score, GIR. and putt per GIR, 2011 was average birdies and 2012 was putt per GIR.