• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1663-1672
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• 2021

There are various typing practice applications. In addition, research cases on learning applications that support typing practice have been reported. These services are usually provided in a way that utilizes their own built-in text. Learners collect various contents through web services and use them a lot for learning. Therefore, this paper proposes a learning application to increase the learning effect by collecting vast amounts of web content and applying it to typing practice. The proposed application is implemented using Tkinter, a GUI module of Python. BeautifulSoup module of Python is used to extract information from the web. In order to process the extracted data, the NLTK module, which is an English data preprocessor, and the KoNLPy module, which is a Korean language processing module, are used. The operation of the proposed function is verified in the implementation and experimental results.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.31-34
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• 2022

The concept of locating chromatic number of graph is a development of the concept of vertex coloring and partition dimension of graph. The locating-chromatic number of G, denoted by χ_L(G) is the smallest number such that G has a locating k-coloring. In this paper we will discussed about the procedure for determine the locating chromatic number of Origami graph using Python Programming.

• 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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• 2021.07a
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• pp.453-454
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• 2021

본 논문에서는 딥아이(DIY) 블록 프로그래밍과 라즈베리파이의 피지컬 컴퓨팅을 활용해 엑츄에이터와 센서를 제어하고 센서를 통해 수집한 데이터를 전처리해 인공지능에 활용함으로써 효율적인 인공지능 교육 방식을 제안한다. 해당 방식은 블록코딩 방식을 사용함으로써 문자코딩 대비 오타을 줄이고 문법 구애율을 낮춤으로써 프로그래밍 입문자의 구문적 어려움을 최소화하고 개념과 전략적 학습을 극대화한다. 블록프로그래밍 사용언어로 파이썬을 채택해 입문자의 편의를 도모하고 파일처리, 크롤링, csv데이터 추출을 통해 인공지능 교육에 활용한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.163-164
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• 2021

본 논문에서는 날씨와 상관관계를 갖는 교통사고에 대한 예측을 진행하는 Web Site 개발을 제안한다. 날씨에 영향을 받는 교통사고에 대한 일일 사망자 수, 교통사고 발생률의 각각의 예측값을 딥러닝 모델을 이용한다. 위의 모델을 작성하기 위하여 본 논문에서는 Anaconda 기반의 Jupyter Notebook에서 Python Tensorflow 모델을 작성하여 테스트하고, 만들어진 모델을 웹 사이트에서 불러오기 위해 Python 기반 Flask Web Framework를 통하여 웹 사이트를 개발한다. 개발된 웹 사이트는 사용자들은 Web Site에 날씨 정보를 입력하여 교통사고 발생률을 예측하고 볼 수 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.89-90
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• 2021

본 논문에서는 Python과 Selenium 라이브러리 기반의 재난 문자 크롤링 및 데이터 시각화 애플리케이션을 설계하고 구현한다. 이 애플리케이션의 특징은 웹상에서 재난 문자 데이터를 크롤링(Crawling)하여 그 빈도수에 따라 시각화하는 것이다. 이 애플리케이션을 활용하여 국민재난안전포털에 접속하여 재난 문자 데이터를 크롤링하고, 그 데이터를 Word Cloud를 활용하여 지역별 재난 문자 빈도수를 시각화한다. 지역별 재난 문자 빈도수를 한눈에 보기 쉽게 시각화함으로써 재난문자를 잘 확인하지 않는 사람들에게 해당 지역의 재난 정보를 쉽게 전달하는 기능을 제공한다.

• Genomics & Informatics
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• v.20 no.4
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• pp.49.1-49.7
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• 2022

Many packages for a meta-analysis of genome-wide association studies (GWAS) have been developed to discover genetic variants. Although variations across studies must be considered, there are not many currently-accessible packages that estimate between-study heterogeneity. Thus, we propose a python based application called Beta-Meta which can easily process a meta-analysis by automatically selecting between a fixed effects and a random effects model based on heterogeneity. Beta-Meta implements flexible input data manipulation to allow multiple meta-analyses of different genotype-phenotype associations in a single process. It provides a step-by-step meta-analysis of GWAS for each association in the following order: heterogeneity test, two different calculations of an effect size and a p-value based on heterogeneity, and the Benjamini-Hochberg p-value adjustment. These methods enable users to validate the results of individual studies with greater statistical power and better estimation precision. We elaborate on these and illustrate them with examples from several studies of infertility-related disorders.

• Genomics & Informatics
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• v.21 no.1
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• pp.15.1-15.4
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• 2023

Bioinformatics education can be defined as the teaching and learning of how to use software tools, along with mathematical and statistical analysis, to solve biological problems. Although many resources are available, most students still struggle to understand even the simplest sequence alignment algorithms. Applying visualizations to these topics benefits both lecturers and students. Unfortunately, educational software for visualizing step-by-step processes in the user experience of sequence alignment algorithms is rare. In this article, an educational visualization tool for biological sequence alignment is presented, and the source code is released in order to encourage the collaborative power of open-source software, with the expectation of further contributions from the community in the future. Two different modules are integrated to enable a student to investigate the characteristics of alignment algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.229-231
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• 2021

In this paper, we describe a hardware design of the SIMECK block cipher algorithm that can be implemented in lightweight hardware with appropriate security strength. To achieve fast encryption and decryption operations, it was designed using two-step method that reduces the number of operation rounds. The designed SIMECK cryptographic core was implemented in Arty S7-50 FPGA device and its hardware operation was verified with a GUI using Python.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.231-232
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• 2022

본 논문에서는 직업 교육 분야에 인공지능 융합 교육을 위한 파이썬 블록과 텍스트 동시 코딩 플랫폼을 설계하였다. 플랫폼에 코딩 언어로는 데이터 분석과 머신러닝의 다양한 라이브러리를 지원하고 있는 파이썬으로 하며, 직업 교육의 영역 전문가가 쉽게 직무 기능 파이썬 블록 모듈을 만들어 추가하고 커스터마이징을 할 수 있는 아키텍처를 갖고 있다. 제안한 플랫폼을 활용한 인공지능 융합 직업 분야로 바이오와 기계공학 분야의 블록 모듈을 추가하고 실습 예제를 만드는 과정을 보여 플랫폼의 유용성과 효율성을 보였다.