14 research outputs found

    Automated Deployment of a Splash Application to the Distributed System via Splash Build Unit

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    ν•™μœ„λ…Όλ¬Έ(석사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : κ³΅κ³ΌλŒ€ν•™ 전기·정보곡학뢀, 2021.8. ν™μ„±μˆ˜.SplashλŠ” 점점 λ³΅μž‘ν•΄μ§€λŠ” 자율기기(autonomous machine)λ₯Ό μœ„ν•œ μ‘μš© ν”„λ‘œκ·Έλž¨ κ°œλ°œμ„ 효과적으둜 ν•  수 μžˆλŠ” ν”„λ‘œκ·Έλž˜λ° ν”„λ ˆμž„μ›Œν¬μ΄λ‹€. SplashλŠ” κ·Έλž˜ν”½ μ‚¬μš©μž μΈν„°νŽ˜μ΄μŠ€λ₯Ό μ΄μš©ν•œ ν”„λ‘œκ·Έλž˜λ° 좔상화λ₯Ό μ œκ³΅ν•  뿐만 μ•„λ‹ˆλΌ μ‹€μ‹œκ°„ μ œμ–΄ μ‹œμŠ€ν…œμ— ν•„μˆ˜μ μΈ μ‹€μ‹œκ°„ 슀트림 처리, μ„Όμ„œ 퓨전, λͺ¨λ“œ λ³€κ²½, μ˜ˆμ™Έ 처리 λ“±κ³Ό 같은 κΈ°λŠ₯듀을 μ œκ³΅ν•œλ‹€. SplashλŠ” ROS 2에 이미 μ‘΄μž¬ν•˜λŠ” κΈ°λŠ₯의 이점을 μ΄μš©ν•˜κΈ° μœ„ν•΄μ„œ ROS 2 기반으둜 κ°œλ°œλ˜μ—ˆλ‹€. λ”°λΌμ„œ, Splashλ₯Ό μ‚¬μš©ν•˜μ—¬ μž‘μ„±λœ μ‘μš©μ€ Splash λŸ°νƒ€μž„ λΌμ΄λΈŒλŸ¬λ¦¬μ™€ ROS 2 λŸ°νƒ€μž„ λΌμ΄λΈŒλŸ¬λ¦¬κ°€ μ„€μΉ˜λœ 단일 ν˜Ήμ€ λΆ„μ‚° μ»΄ν“¨νŒ… ν™˜κ²½μ—μ„œ κ΅¬λ™λœλ‹€. ν•˜μ§€λ§Œ λΆ„μ‚° μ»΄ν“¨νŒ… ν™˜κ²½μ—μ„œ Splash μ‘μš©μ„ μ‚¬μš©ν•˜κΈ° μœ„ν•΄μ„  각 λ¨Έμ‹ μ˜ ν™˜κ²½μ— 맞게 μ‘μš©κ³Ό λŸ°νƒ€μž„μ„ λΉŒλ“œ 및 μ„€μΉ˜ν•΄μ•Ό ν•˜κ³ , μ΄λŠ” μ†Œν”„νŠΈμ›¨μ–΄ μ—…λ°μ΄νŠΈ 및 μœ μ§€λ³΄μˆ˜λ₯Ό ν•˜λŠ”λ° μ‹œκ°„κ³Ό λΉ„μš©μ΄ 많이 듀도둝 ν•œλ‹€. 이런 λΆˆνŽΈν•¨μ€ λΆ„μ‚° μ»΄ν“¨νŒ… 머신에 ν™•μž₯μ„±(scalability), κ°€μš©μ„±(availability), 관리성(manageability)을 κ³ λ €ν•œ μ†Œν”„νŠΈμ›¨μ–΄ 배포(deployment)의 ν•„μš”μ„±μ„ μ œκΈ°ν•œλ‹€. λ³Έ λ…Όλ¬Έμ—μ„œλŠ” Splash μ‘μš© ν”„λ‘œκ·Έλž¨μ˜ μžλ™ν™” 배포 및 관리λ₯Ό μœ„ν•œ 도컀(Docker) 기반 Splash λΉŒλ“œ μœ λ‹›μ„ κ΅¬ν˜„ν•œλ‹€. Splash λΉŒλ“œ μœ λ‹›μ„ ν†΅ν•΄μ„œ κ°œλ°œμžλŠ” μ†Œν”„νŠΈμ›¨μ–΄ λΉŒλ“œ 및 배포 ν”„λ‘œμ„ΈμŠ€λ₯Ό μžλ™ν™”ν•˜κ³  ν”„λ‘œκ·Έλž¨μ˜ 병렬성(parallelism) 및 λ™μ‹œμ„±(concurrency)을 μ΅œμ ν™”ν•  수 μžˆλ‹€. Splash λΉŒλ“œ μœ λ‹›μ„ μ΄μš©ν•œ μ†Œν”„νŠΈμ›¨μ–΄ μžλ™ν™” 배포에 λŒ€ν•œ μœ μš©μ„±μ„ κ²€μ¦ν•˜κΈ° μœ„ν•΄μ„œ λΆ„μ‚° μ‹œμŠ€ν…œμ—μ„œ Splash λΉŒλ“œ μœ λ‹›μ„ μ΄μš©ν•˜μ—¬ λ”₯λŸ¬λ‹ 기반 자율 μ£Όν–‰ μ‘μš© ν”„λ‘œκ·Έλž¨μ˜ 예제λ₯Ό μ§„ν–‰ν•˜μ˜€λ‹€.Splash is a programming framework that can effectively support the application development of increasingly complex autonomous machines. Splash not only offers user-friendly programming abstraction like a graphic user interface, but also provides essential programming semantics for a real-time control system such as real-time stream processing, sensor fusion, mode change, exception handling, etc. Splash was developed based on ROS 2 to take advantages of using already existing features and packages. Splash applications are eligible to run on a single or distributed computing systems where Splash runtime library, ROS 2 runtime library and any other software that are necessary for the Splash applications are installed. Therefore, in order to run Splash application on a distributed computing system, it is required to build and install the applications, additional external libraries and corresponding runtime according to the environment of each machine. This particular process comes with cost and time issue of software update and maintenance. This inconvenience and burden raise the need for automated software deployment considering scalability, availability, and manageability in distributed computing systems. This thesis will introduce a Docker-based Splash build unit for automated deployment and management of Splash applications. Splash build unit allows developers to automate the software build and deployment process to distributed computing machines by using Docker containerization. It also allows developers to focus on optimizing parallelism and concurrency of programs. In order to demonstrate the effectiveness and utility of software deployment using Splash build unit, the case study of a LFA(Lane Following Assist) application with DNN-based lane detection and DNN-model training program was conducted using Splash build unit in a distributed system.제 1 μž₯ μ„œ λ‘  1 제 2 μž₯ λ°°κ²½ 지식 3 제 1 절 ROS 2 3 제 2 절 Splash 7 제 3 μž₯ 도컀 기반 λΉŒλ“œ μœ λ‹› 15 제 1 절 λΉŒλ“œ μœ λ‹› 15 제 2 절 도컀 기반 λΉŒλ“œ μœ λ‹› 및 κ΅¬ν˜„ 17 제 3 절 λΉŒλ“œ μœ λ‹› 배포 19 제 4 μž₯ Case Study 21 제 1 절 예제 ν™˜κ²½ 21 제 2 절 예제 ꡬ성 22 제 3 절 예제 κ²°κ³Ό 및 평가 24 제 5 μž₯ κ²° λ‘  26 μ°Έκ³ λ¬Έν—Œ 27 Abstract 29석

    ζ²™ζ±° 降伏 원리λ₯Ό μ΄μš©ν•œ μ΄μ˜¨ν™” 좩돌 λ°˜λ„μ²΄ μ†Œμž

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    Thesis(doctoral)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :전기곡학뢀,2006.Thesis(doctoral)-

    선체 κ΅¬μ‘°μ™€μ˜ 연관성을 κ³ λ €ν•œ μΎŒμ† λ°°κ΄€ λͺ¨λΈλ§ 방법

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :쑰선해양곡학과,2006.Maste

    κ·Ήλ―Έμ„Έ κ³΅μ •κΈ°μˆ μ˜ 개발과 30nm nMOSFETμ—μ˜ μ μš©μ— κ΄€ν•œ 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :전기·컴퓨터곡학뢀,2002.Maste

    λ‘œν„° μœ λ™ 및 μ†ŒμŒμ˜ Navier-Stokes 해석을 μœ„ν•œ λ³Όν…μŠ€νŠœλΈŒ λͺ¨λΈ 및 κ³΅κ°„μ£ΌνŒŒμˆ˜ ν™•μž₯ μœ ν•œμ²΄μ  기법 연ꡬ

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    Thesis(doctors) --μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :기계항곡곡학뢀,2008.8.Docto

    Prevalence of Gait Features in Healthy Adolescents and Adults

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    Forensic gait analysis is the identification of individuals by their gait style and walking characteristics. This study aimed to examine the prevalence of gait patterns in healthy adolescents and adults. Five hundred healthy participants (mean age, 36.9 years) were enrolled and divided into four age groups: 13-20, 21-35, 36-50, and β‰₯51 years. The gait of the participants was recorded in a gait analysis laboratory. Five specialists experienced in gait analysis selected several gait features. The prevalence of out-toe, in-toe, planovalgus, and turtleneck was 25.0%, 1.6%, 6.8%, and 4.2%, respectively. The prevalence of genu varum (10.4%) was higher than that of genu valgum (5.6%). Genu valgum and hindfoot valgus were more common in younger than in older subjects (P=0.018 and P=0.029, respectively). Genu varum was more prevalent in older subjects (P<0.001). The prevalence of out-toe was higher in males (P<0.001), whereas the in-toe and genu valgum were more common in females than in males (P=0.027 and P=0.038, respectively). We have documented the prevalence of several gait features in healthy adolescents and adults. These gait features can be used to enhance evidentiary competence in forensic gait analysis and thereby help improve the arrest rate of offenders.N
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