• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.633-658
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• 2021

Statistical engineering contains design of experiments, quality control/ management, and reliability engineering. Python is a free software environment for machine learning, data science, and graphics. Python package has many functions and libraries for statistical engineering. We can use Python package as a useful tool for statistical engineering. This paper shows applications of Python package for statistical engineering and suggests a total Python projects for statistical engineering.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.141-148
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• 2021

The mainstream tool for software education for elementary students is Educational Programming Language. It is essential for upper graders to advance from EPL to text based programming language. However, many students experience difficulty in adopting to this change since Python is run in English. Python is an actively used TPL. This study focuses on developing an education program to facilitate learning Python for Korean speaking students. We have extracted the necessary reserved words needed for data analysis in Python. Then we replaced the extracted words into Korean terms that could be understood in elementary level. The replaced terms were matched on one-to-one correspondence with reserved words used in Python. This devised program would assist students in experiencing data analysis with Python. We expect that this education program will be applied effectively as a basic resource to learn TPL.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.360-363
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• 2022

According to the 2018 Kaggle ML & DS Survey, among the proportions of frameworks for machine learning and data science, TensorFlow and Keras each account for 41.82%. It was found to be 34.09%, and in the case of development programming, it is confirmed that about 82% use Python. A significant number of machine learning and deep learning structures utilize the Keras framework and Python, but in the case of Python, distribution and execution are limited to the Python script environment due to the script language, so it is judged that it is difficult to operate in various environments. This paper implemented a machine learning and deep learning system using C# and Keras running in Visual Studio 2019. Using the Mnist dataset, 100 tests were performed in Python 3.8,2 and C# .NET 5.0 environments, and the minimum time for Python was 1.86 seconds, the maximum time was 2.38 seconds, and the average time was 1.98 seconds. Time 1.78 seconds, maximum time 2.11 seconds, average time 1.85 seconds, total time 37.02 seconds. As a result of the experiment, the performance of C# improved by about 6% compared to Python, and it is expected that the utilization will be high because executable files can be extracted.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.53-60
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• 2018

In this study we have developed a Python education program that can be applied to students who have studied block-based coding. We have developed a Python education program based on the extracted the learners' level of block-based coding by analyzing the programs and the textbooks. We extracted the grammar of the block-based coding and constructed the curriculum. Then, the Python education program was composed by 16 hours. After reviewing the appropriateness of the education program through expert validation, it was concluded that the developed Python education program is suitable for applying to learners of block-based coding. We expect that proposed program will be effectively applied as basic resources to learn script coding in class.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.69-72
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• 2009

Python은 통합 개발 환경이 구축되어 있지 않아 Python을 이용해 개발하는 경우 대부분 Vi 혹은 Emacs 같은 텍스트 편집기를 이용해 코딩을 하고 다시 터미널 혹은 콘솔로 나와 일일이 디버깅을 해야만 한다. 게다가 import 한 모듈의 API에 대해서 알고 싶으면 Python Interpreter에서 다시 봐야 하는 등 상당한 불편함이 있다. 이에 본 논문에서는 한 화면에서 편집, 컴파일, 수행결과 보기, 디버거 등을 수행할 수 있는 Python 통합 개발 환경을 구축하였다.

• Food Science and Preservation
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• v.30 no.5
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• pp.758-769
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• 2023

The main aim of this study was to determine python fat's several physicochemical properties, including dimensions, color, structure, acid value (AV), saponification value (SV), density, and recovery efficiency. The optimum yield obtained was approximately 80.40% at 180℃ for 60 min with an AV of 0.3366 and SV of 179.56 mg KOH/g. Fatty acids, comprising oleic acid (72.462%), palmitic acid (26.243%), linolenic acid (0.835%), and myristic acid (0.459%), were identified using gas chromatography-mass spectrometry (GC-MS). The python fat had a very weak antioxidant capacity and almost no antibacterial ability with gram-positive (Staphylococcus aureus - ATCC 25923 and Bacillus cereus - ATCC 10876) and gram-negative (Escherichia coli - ATCC 25922 and Salmonella enterica - ATCC 35664) bacteria (used the paper disc diffusion method for antibiotic susceptibility testing). Moreover, python fat is considered to be very resistant to high temperatures.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.473-476
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• 2005

본 논문에서는 Python 을 사용한 유전 알고리즘 구현을 다룬다. 유전 알고리즘은 생물의 진화과정에서 일어나는 자연선택과 같은 유전법칙을 모방한 확률적 탐색기법이다. 유전 알고리즘에서는 염색체를 하나의 리스트 혹은 문자열로써 다룬다. 리스트나 문자열 처리 위주인 유전 알고리즘의 경우, 기존의 C/C++/Java 보다 표현력이 풍부한 Python 으로 프로그래밍할 경우 별도의 라이브러리 없이 쉽게 구현이 가능하다. 본 논문에서는 Python 을 사용한 유전 알고리즘 구현 방법에 대해 소개하고, 추가적으로 높은 성능을 얻기 위한 방법들에 대해 논의한다.

• Journal of Korea Game Society
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• v.6 no.1
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• pp.29-36
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• 2006

This paper describes the implementation of Direct3D interface library for Python language. DirectX is the most popular library used for 3D games and 3D modelings. However, softwares which use the library can only be developed in the environments provided by Microsoft like Visual Studios and .NET framework. The interface module for Python, this paper presents, will extend the coverage of the useful library DirectX to a language which is not fully supported by Microsoft. The interface techniques described here can be a guide to develop interface modules for other languages too, which make their language more powerful and extensible. This paper describes the implementation techniques to develop the interface module for Python, advantages and disadvantages.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.243-250
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• 2021

With the increased development of 3D VR applications augmented by recent VR/AR/MR technologies and by the advance of 3D devices, interchangeability and portability of 3D data have become essential. 3D files should be processed in a standard data format for common usage between applications. Providing standardized libraries and data structures along with the standard file format means that a more efficient system organization is possible and unnecessary processing due to the usage of different file formats and data structures depending on the applications can be omitted. In order to provide the function of using a common data file and data structure, this research is intended to provide a programming binding tool for generating and storing standardized data so that various services can be developed by accessing the common 3D files. To achieve this, this paper defines a common data structure including classes and functions to access X3D files with a standardized scheme using the Python programming language. It describes the implementation of a Python language binding viewer, which is an X3D VR viewer for rendering standard X3D data files based on the language binding interface. The VR viewer includes Python based 3D scene libraries and a data structure for creation, modification, exchange, and transfer of X3D objects. In addition, the viewer displays X3D objects and processes events using the libraries and data structure.

• Genomics & Informatics
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• v.21 no.1
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• pp.14.1-14.4
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• 2023

OncoPrint, the plot to visualize an overview of genetic variants in sequencing data, has been widely used in the field of cancer genomics. However, still, there have been no Python libraries capable to generate OncoPrint yet, a big hassle to plot OncoPrints within Python-based genetic variants analysis pipelines. This paper introduces a new Python package PyOncoPrint, which can be easily used to plot OncoPrints in Python. The package is based on the existing widely used scientific plotting library Matplotlib, the resulting plots are easy to be adjusted for various needs.