Earticle

South Korea has about 5,500 unified control points now. In last 10 years, after years of observations, obtained about 20,000 GNSS observation files, tried to compare these new coordinates values with the old values of unified control points to analysis the changes in the earth’s crust. But because of the changes of the GNSS receivers, multi bands and types of it was used, and the mistakes from the observers, they can’t be processed in GAMIT/GLOBK, the most used GNSS data processing software. Coding several python scripts to revise these mass datas instead of manual sequential corrections.

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.

This study aimed to develop and validate an automated Python-based tool for extracting radiation dose information from radiation dose structured reports (RDSRs) generated during fluoroscopically guided procedures performed with mobile C-arms or angiography units. The tool extracts dose-related information from multiple PDF and Digital Imaging and Communications in Medicine (DICOM) RDSRs and exports the data into a Microsoft Excel or JavaScript Object Notation file. PDF parsing was performed using the "PyPDF2" library, and the extracted data organized into DataFrames using the "Pandas" library. DICOM RDSRs were processed using the "Pydicom" library, and data were extracted based on selected DICOM tags. Up to 34 parameters could be extracted, including "basic study information", "accumulated radiation dose indices", and exposure-related parameters during "fluoroscopy" and/or "DSA events". A dose alert feature was included to identify cases where dose indices exceeded "trigger levels" or diagnostic reference levels. The accuracy of this tool was evaluated manually by comparing the extracted data with the original RDSRs. The tool underwent internal validation only. For PDFs, common parsing errors included missing or split text, which were corrected through additional programming effort using regular expression (regex) patterns. After refinement, the tool achieved 100% accuracy for PDF and DICOM formats. The tool enables expedited dose monitoring, protocol analysis, and quality assurance, particularly in facilities without a dose management system. It is implemented as a lightweight script intended for users familiar with Python and command-line execution. This tool was validated on Siemens, Philips, and Ziehm systems and is adaptable to other manufacturers' PDFs and DICOM RDSRs (given a specified series description). Future updates can enable remote access to picture archiving and communication system servers, allowing more automated assessment of radiation dose data.

본 논문에서는 3D 애니메이션 도구인 마야를 이용하여 태양계를 모델링하고 각 행성의 움직임과 물리적인 속성들을 정밀하고 객관적으로 구현하여 태양계의 구조를 시각적으로 쉽게 이해할 수 있도록 시뮬레이터를 구현하였다. 메뉴를 이용한 마야의 모델링으로는 정밀한 물리적 속성 값을 표현하기 어려우므로 파이선 스크립트를 이용하여 각 행성의 특성을 표현하였다. 제안하는 시뮬레이터는 가상현실 분야나 학생들의 교육 자료로서 사용 가능하도록 모델링과 렌더링을 실사와 동일하게 구현하였다. 또한 마야 애니메이션에서의 메뉴를 이용한 모델링과 스크립트 언어인 파이선을 활용하여 누구라도 쉽게 실사 영상을 볼 수 있도록 하였다.

In this paper, we introduce a simulation tool for solar system using 3D animation tool MAYA. It accurately models solar system's astronomical features, such as each planet's orbital period, orbital speed, relative size, and texture, etc. This simulator visualize the solar system in 3D, which can be used to easily understands the system's positioning and astronomical movements. With a conventional Maya modeling process using menus and UI windows, it is difficult to assign correct physical attributes of planets. We use Python script to set up each planet's astronomical parameters. The proposed simulator is rendered as real as possible to be used for virtual reality and educational purpose.