• East Asian mathematical journal
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• v.39 no.2
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• pp.93-117
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• 2023

The aim of this study is to explore the pre-service math teachers' characteristics of education to develop their AI literacy and SW competency, and to derive some implications. We conducted a 14-hours AI and SW education program for pre-service teachers with theory and practice, and an analysis on class observation data, video frames of classes and interview, Python programming assignments and papers. The results of this case study for 3 pre-service teachers are as follows. First, two students understood artificial neural network and deep learning system accurately, furthermore, all students conducted a couple of explorations related with performance improvement of deep learning system with interest. Second, coding and exploration activities using Python improved students' computational thinking as well as SW competency, which help them give convergence education in the future. Third, they responded positively to the necessity of AI literacy and SW competency development, and to applying coding to math class. Lastly, it's necessary to endeavor to give a coding education to the student's eye level according to his or her prerequisite and to ease the burden of student's studying AI technology.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.155-160
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• 2022

In recent years, Unreal Engine has been increasingly included in the animation process produced in the studio. In this case, there will be more than one of main software, and it is very important to accurately transfer data between the software and Unreal Engine. In animation data, not only the animation data of the character but also the animation data of objects interacting with the character must be individually produced and transferred. Most of the objects that interact with the character have a condition of constraints with the part of character. In this paper, I tried to stipulate the production process for extracting animation data of constrained objects, and to analyze why users experience difficulties due to the complexity of the regulations in the process of executing them. And based on the flowchart prescribed for user convenience, I created a program using a Python script to prove the user's convenience. Finally, by comparing the results generated according to the manual flowchart with the results generated through the script command, it was found that the data were consistent.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.15-16
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• 2022

본 논문에서는 국내 합법 사행산업의 가장 큰 비중을 차지하는 경마에 대한 데이터 분석 모델을 제공하여 건전한 국민 여가 스포츠로 인식 개선을 제안한다. 고배당을 강조하는 경마 예측론이 성행하며 경마가 스포츠가 아닌 도박에 가깝다는 부정적 이미지를 개선하고자 부모마의 수득 상금을 이용한 순위 분석 모델을 제공한다. 현재 국내 경마 경기는 서울, 부산, 제주에서 개최되며, 이 중 서울 지역 경마 데이터를 분석 데이터로 하였다. 분석에 이용한 데이터는 2019년 3월부터 2022년 3월까지의 경주 성적, 경주마 정보, 부모마 수득상금을 이용하였다. 분석에는 선형 회귀 모형, 랜덤 포레스트 회귀 모형 (Breiman, 2001)을 이용하였다. 분석은 Python 을 이용하였으며, Python에서 제공하는 다양한 라이브러리를 이용하여 크롤링, 전처리, 분석하였다.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.53.3-53.3
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• 2021

Adaptive Optics (AO) was first studied in the field of astronomy, and its applications have been extended to the field of laser, microscopy, bio, medical, and free space laser communication. AO modelling and simulation are required throughout the system development process. It is necessary not only for proper design but also for performance verification after the final system is built. In KASI, we are trying to develop the AO Python Package for AO modelling and simulation. It includes modelling classes of atmosphere, telescope, Shack-Hartmann wavefront sensor, deformable mirror, which are the components for an AO system. It also includes the ability to simulate the entire AO system over time. It is being developed in the Super Eye Bridge project to develop a segmented mirror, an adaptive optics, and an emersion grating spectrograph, which are future telescope technologies. And it is planned to be used as a performance analysis system for several telescope projects in Korea.

• Journal of Astronomy and Space Sciences
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• v.38 no.3
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• pp.157-164
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• 2021

We describe a method for the in-orbit calibration of body-mounted magnetometers based on the CHAOS-7 geomagnetic field model. The code is designed to find the true calibration parameters autonomously by using only the onboard magnetometer data and the corresponding CHAOS outputs. As the model output and satellite data have different coordinate systems, they are first transformed to a Star Tracker Coordinate (STC). Then, non-linear optimization processes are run to minimize the differences between the CHAOS-7 model and satellite data in the STC. The process finally searches out a suite of calibration parameters that can maximize the model-data agreement. These parameters include the instrument gain, offset, axis orthogonality, and Euler rotation matrices between the magnetometer frame and the STC. To validate the performance of the Python code, we first produce pseudo satellite data by convoluting CHAOS-7 model outputs with a prescribed set of the 'true' calibration parameters. Then, we let the code autonomously undistort the pseudo satellite data through optimization processes, which ultimately track down the initially prescribed calibration parameters. The reconstructed parameters are in good agreement with the prescribed (true) ones, which demonstrates that the code can be used for actual instrument data calibration. This study is performed using Python 3.8.5, NumPy 1.19.2, SciPy 1.6, AstroPy 4.2, SpacePy 0.2.1, and ChaosmagPy 0.5 including the CHAOS-7.6 geomagnetic field model. This code will be utilized for processing NextSat-1 and Small scale magNetospheric and Ionospheric Plasma Experiment (SNIPE) data in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.145-150
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• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.127-134
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• 2018

In this paper, we have developed the Auto Lip-Sync Maya plug-in for extracting Korean phonemes from voice data and text information based on Korean and produce high quality 3D lip-sync animation using divided phonemes. In the developed system, phoneme separation was classified into 8 vowels and 13 consonants used in Korean, referring to 49 phonemes provided by Microsoft Speech API engine SAPI. In addition, the pronunciation of vowels and consonants has variety Mouth Shapes, but the same Viseme can be applied to some identical ones. Based on this, we have developed Auto Lip-sync Maya Plug-in based on Python to enable lip-sync animation to be implemented automatically at once.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.140-143
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• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.

• Journal of Engineering Education Research
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• v.24 no.5
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• pp.3-14
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• 2021

This study deals with the case of online-based project learning, which was designed for the purpose of university educational innovation and enhancing learners' competencies required by society, operated during the COVID-19 pandemic. The course was applied Python programming language, team-based project learning, and intensive course system, which is required by our society and companies in the era of the 4th industrial revolution. Also it was operated as a non-face-to-face online class, which would have been operated in an offline class if it had not been for Covid 19 pandemic, to explore the possibilities and educational effects of online learning. To do this, 32 university students participated in online-based project learning during 8 weeks, and then conducted a survey. The survey results were analyzed in terms of i) non-face-to-face online learning, ii) team-based project learning, and iii) application of the intensive course system. Results say that most of the learners were satisfied with the online learning, team-based project learning, and the intensive semester system applied in this course at a high level, and also they clearly presented the reasons. Thereby, it has been confirmed that the learners were already well aware of the pros and cons of each learning method. Based on these results, the implications were discussed.