• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.37-42
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• 2016

In this paper, in today's highly complex video and broadcast operations, broadcasters are constantly challenged to reliably deliver low-latency, high-quality video to multiscreen audiences on-air and online. The Adaptive Bit Rate (ABR) protocols enable internet video to a wide range of multiscreen devices. However, video quality is often marginal and would prove unacceptable for valued linear broadcast content delivered to the Big Screen today. The Media information processing technology advances in ABR enables service providers to take control and offer quality managed linear video services to ALL screens in the home, including the Big Screen, with a single unified IP Video infrastructure. The New Multiscreen-Assisted ABR (MSA-ABR) delivery management system proposed using Cloud based multicast-assisted ABR for a broadcast facility that performs routing of contribution content and online publishing services within a virtual, centralized cloud infrastructure.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.221-222
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• 2023

본 연구에서는 주피터 노트북에서 자동 평가 시스템을 활용하기 위한 방안으로 자동 평가 시스템의 문제를 저장하고 제시하는 방안에 대해서 연구하였다. 자동 평가 시스템은 학습자가 직접 프로그래밍을 하고 바로 피드백을 받을 수 있는 장점이 있다. 주피터 노트북에서 자동 평가 시스템을 제공하는 nbgrader와 코들의 장점을 바탕으로 문제 제시 방안은 다음과 같다. 문제는 HTML 태그를 이용해 서식 있는 형태로 서버에 저장한다. 주피터 노트북에서 IPython.display 모듈의 display와 HTML 명령어를 사용하여 문제를 출력하면 코드셀 출력창에 서식 있는 HTML 문서를 출력하여 학습자에게 가독성 있게 문제를 제시할 수 있다.

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.437-443
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• 2024

Adhering to coding style guidelines is crucial for both companies and developers as it improves code readability and reduces the costs associated with testing and maintenance. However, teaching coding style in programming courses poses challenges. Setting up an environment for learning coding styles is hard, and there are no predefined coding style rules for beginners. From the learners' perspective, since adherence to coding styles does not affect their grades, they do not feel a strong need to learn them. This paper introduces a coding style checking system for an online evaluation system. The proposed system is implemented to check and evaluate coding styles in C, Java, and Python. Additionally, we applied 234 out of the 1,023 rules provided by the language-specific tools, which is 23.08%, allowing for the application of coding style rules according to the course progression. Moreover, we motivated learners to improve their coding style by adding quality scores to their basic scores. After introducing the coding style education system, the number of students scoring over 25 points on their initial submissions increased by 149.47%, from 18 students in the first week to 44 students in the sixth week. Learners used the coding style checking system to learn how to apply coding style rules and subsequently implemented their code in adherence to the specified coding styles.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.203-211
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• 2024

Utilizing programming languages for data visualization can enhance the efficiency and effectiveness in handling data volume, processing time, and flexibility. However, practice is required to become proficient in programming. Therefore public data-based the problem bank was developed to practice data visualization in a programming automatic assessment system. Public data were collected based on topics suggested in the curriculum and were preprocessed to make it suitable for users to visualize. The problem bank was associated with the mathematics curriculum to learn various data visualization methods. The developed problems were reviewed to expert and pilot testing, which validated the level of the questions and the potential of integrating data visualization in math education. However, feedback indicated a lack of student interest in the topics, leading us to develop additional questions using student-center data. The developed problem bank is expected to be used when students who have learned Python in primary school information gifted or middle school or higher learn data visualization.