• 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.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.555-562
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• 2007

In this paper we present a system architecture for the distributed measurement system of instrumentation over the network. The proposed architecture allows remote control & monitoring of the instrument by using web browser.

• 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.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.162-164
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• 2019

본 논문에서는 물체인식 딥러닝 모델 생성에 필요한 라벨링(Labeling)과정에서 사용자가 다양한 기능을 활용하여 효과적인 학습 데이터를 구성할 수 있는 GUI 프로그램을 구현했다. 프로그램의 인터페이스는 파이썬 기반의 GUI 모듈인 Tkinter 를 활용하여, 실시간으로 이미지 데이터를 수집할 수 있는 크롤링(Crawling)기능과 미리 학습된 Retinanet 을 통해 이미지 데이터를 인식함으로써 자동으로 주석(Annotation) 과정을 수행할 수 있는 기능을 구성했다. 또한, 수집한 이미지 데이터를 다양한 효과와 노이즈, 변형 등으로 Augmentation 기능을 추가함으로써, 사용자가 모델을 학습하기 위한 데이터 전처리 단계를 하나의 GUI 프로그램에서 수행할 수 있도록 했다. 또한 사용자가 직접 학습한 모델을 추정 모델(Inference Model)로 변환하여 프로그램에 입력할 수 있도록 설계한다.

• Journal of The Korean Association of Information Education
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• v.23 no.4
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• pp.355-362
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• 2019

Elementary students are studying software training to teach coding education using text-based languages such as Python. In general, these higher-level languages support learning activities in combination with a kits for physical computing or various programming languages, in contrast to block-coding programming languages. In this study, we conducted a coding project based on computational thinking using the ARCS model to overcome the difficulties of text-based language. The results of the experiment show that students are generally confident and interested in programming. Especially, the understanding of repetition, function, and object was high in the change of computational thinking power, so this trend is believed to be due to the use of text-based languages and the Python module.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.163-172
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• 2021

To specify a formal semantics for a programming language is to do a significant part for design, standardization and translation of it. The Python is popular and powerful, it is necessary to do research for a formal semantics to specify a static and dynamic semantics for Python clearly in order to design a similar language and do an efficient translation. This paper presents the Action Equation 2.0 that specifies a formal semantics for Python to change and update Action Equation. To measure the execution time for Python programs, we implemented the semantic structure specified in Action Equation 2.0 in Java, and prove through simulation that Action Equation 2.0 is a real semantic structure that can be implemented. The specified Action Equation 2.0 is compared to other descriptions, in terms of readability, modularity, extensibility, and flexibility and then we verified that Action Equation 2.0 is superior to other formal semantics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.404-406
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• 2021

In this paper, we propose an app application for classifying Korean food images and providing information related to Korean food. App Application consists of Flask server, Database (Mysql), and Python deep learning modules. Using the VGG16 model, 150 images of Korean foods are classified. If there is an internet environment, anyone can easily get information about Korean food anytime, anywhere with a single photo.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.233-234
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• 2022

본 논문에서는 효율적인 AI 교육을 위한 데이터셋 아카이브와 데이터 활용을 위한 프로그래밍 플랫폼과의 연동 모듈을 제안한다. 데이터셋 아카이브는 공공데이터를 전처리하여 생성한 데이터를 모아 설계하며, 프로그래밍 플랫폼 코드비(CodeB)와 연동하여 데이터를 활용할 수 있도록 한다. 코드비(CodeB)는 파이썬 블록 프로그래밍 플랫폼으로 연동을 통해 데이터를 활용한 프로그래밍이 가능하다.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.111-120
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• 2024

Cloud coverage is a key factor in determining whether to proceed with observations. In the past, human judgment played an important role in weather evaluation for observations. However, the development of remote and robotic observation has diminished the role of human judgment. Moreover, it is not easy to evaluate weather conditions automatically because of the diverse cloud shapes and their rapid movement. In this paper, we present the development of a cloud monitoring program by applying a machine learning-based Python module "cloudynight" on all-sky camera images obtained at Miryang Arirang Astronomical Observatory (MAAO). The machine learning model was built by training 39,996 subregions divided from 1,212 images with altitude/azimuth angles and extracting 16 feature spaces. For our training model, the F1-score from the validation samples was 0.97, indicating good performance in identifying clouds in the all-sky image. As a result, this program calculates "Cloudiness" as the ratio of the number of total subregions to the number of subregions predicted to be covered by clouds. In the robotic observation, we set a policy that allows the telescope system to halt the observation when the "Cloudiness" exceeds 0.6 during the last 30 minutes. Following this policy, we found that there were no improper halts in the telescope system due to incorrect program decisions. We expect that robotic observation with the 0.7 m telescope at MAAO can be successfully operated using the cloud monitoring program.