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CSID Global Program 2018년
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Overview
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Overview 3 Different Programs Prep during the 1st semester
National University of Singapore Risk Management Solutions, Inc. Purdue University Prep during the 1st semester Work and learn in the U.S. or Singapore during the Summer break Follow up during the 2nd semester
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Procedure Preparation during the 1st semester
Obtain base knowledge Work and/or learn in the U.S. or Singapore during the Summer Follow up during the 2nd semester Complete the project Write papers and/or patents Requires a class registration
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Qualification and Requirements
전공 컴퓨터 정보통신 멀티미디어 *소프트웨어연계전공 English Motivation Responsibility
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Selection Available spots: 13 Drop out possibility > 0
준비 과정에서 성과 미흡 시 탈락 가능성 있음 English Resume Statement of Purpose – Korean Submit online
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Contact 김동호 융합소프트웨어교육원 신공학관 10122
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National University of Singapore
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NUS – ranked 15th in the world
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Project Description DASH-UAV: Dynamic HTTP Adaptive Streaming Over Unmanned Aerial Vehicle Networks UAVs (unmanned aerial vehicles) or drone-based networks equipped with high-end cameras have become increasingly popular among consumers, and are also receiving much attention from both industry and academia. UAVs have been used for many emerging applications such as remote sensing for mapping and surveillance, flight automation, computer vision, live-event broadcasts and augmented-reality games and opportunities to use UAVs for new applications are constantly emerging and evolving. Current UAVs users considered a fixed high bitrate (4K, 1080p) video streaming scheme (most of user select this configuration). However, in wireless shared network environment with mobility, the network resources (i.e., throughput) can vary widely and is almost impossible to estimate and also it is very hard to meet their video quality requirements, thus unsatisfactory viewer quality of experience (QoE) will be received. Recently, Dynamic HTTP adaptive streaming (DASH) is being adopted with increasing frequency and becoming the de-facto standard for video streaming. In DASH, the source video is segmented into short duration chunks of 2–10 seconds, each of which is encoded at several different bitrate levels and resolutions. Then the generated chunks are stored on a server from which the clients (e.g., UAV user in our case) fetch them. During playback each client uses its bitrate adaptation logic (ABR) to dynamically fetch the chunk encoded at the optimal bitrate level based on metrics such as the average throughput and the buffer occupancy. DASH works over the universally available HTTP and TCP protocols to deliver media chunks, which simplifies the traversal through middleboxes (e.g., NATs and firewalls) and allows the use of existing caching infrastructure (e.g., content delivery networks) to scale in a cost-effective manner. In this project the students will work on integrating DASH with UAV networks and also design new ABR schemes for such kind of networks.
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Project Description – Nut Shell
DASH-UAV: Dynamic HTTP Adaptive Streaming Over Unmanned Aerial Vehicle Networks UAV Popular in these days Fixed high bitrate is not plausible Unsatisfactory QoE DASH Dynamic HTTP Adaptive Streaming 2-10 sec chunks Several different bitrates ABR Bitrate Adaptation Logic Works on HTTP & TCP Integrate DASH with UAV networks Design new ABR schemes
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Project – Steps and Deliverables
Survey related work on DASH, UAV, HAS, adaptive streaming over wireless networks, various ABR schemes, video encoding/decoding methods, compression mechanisms. Deliver a survey report. Perform experiments in different wireless environments and bandwidth fluctuation profiles using UAVs with their traditional schemes. Integrate DASH in an UAV network, initially use existing ABR algorithms. Design a new solution and perform some simulation tests. Implement the new solution and perform experiments and an evaluation. Write a final project report. Optional: participate in the publication of a research paper based on the results.
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Project - Requirements
Knowledge in C, C++, Python, Javascript, Android, PHP, HTML and MATLAB. Some knowledge in computing hardware, especially, drones, Arduino and Raspberry PI.
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References [1] Stockhammer, T. (2011, February). Dynamic adaptive streaming over HTTP--: standards and design principles. In Proceedings of the second annual ACM conference on Multimedia systems (pp ). ACM. [2] Wang, X., Chowdhery, A., & Chiang, M. (2017). Networked Drone Cameras for Sports Streaming. In IEEE International Conference on Distributed Computing Systems (ICDCS). [3] Wang, X., Chowdhery, A., & Chiang, M. (2016, October). SkyEyes: adaptive video streaming from UAVs. In Proceedings of the 3rd Workshop on Hot Topics in Wireless (pp. 2-6). ACM. [4] Kacianka, S., & Hellwagner, H. (2015, March). Adaptive video streaming for UAV networks. In Proceedings of the 7th ACM International Workshop on Mobile Video (pp ). ACM. [5] Muzaffar, R. (2017). Routing and video streaming in drone networks (Doctoral dissertation, Queen Mary University of London).
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Summer Workshop
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Time line 1학기 여름 2학기 원격 멘토링을 통한 프로젝트 시작 3주간 NUS summer workshop 참여
5주간 프로젝트 진행 2학기 원격 멘토링을 통한 프로젝트 완성 논문 완성
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RMS
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Exposure Management System
Joseph Kim senior director of model development …and your mentor 👨🏻🏫
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Founded at Stanford University in 1988
Risk. Managed. Founded at Stanford University in Solely focused on independent view of risk quantification and risk management Independent reinsurance industry Subsidiary of DMGT Provide catastrophe risk management and quantification solutions to the $1 trillion dollar global insurance industry
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Our Journey
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Our mission is to create a more resilient and sustainable global society through a better understanding of catastrophic events. We lead an industry that we helped pioneer Our work makes an impact on the world at large How we understand and manage risk affects us all RMS(One) A platform at the heart of the global risk market, transforming an industry to create a more resilient and sustainable global society
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The Project Universal (web and mobile) exposure management system that shows insight to big data collection Use company-provided advanced analytics and models Innovate to provide compelling UI and user experience
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Turn vast amount of complex data to…
The Project Turn vast amount of complex data to…
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The Project these…
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We are Seeking The talent
2 full-stack developers developing end-to-end Using React, React-Native, Redux/MobX or similar for front-end Using JVM (Java, Scala) or NodeJS based framework, and RDBMS (such as PostgreSQL) or HDFS-based NOSQL persistence layer 1 or 2 UI/UX developers passionate about making beautiful app using CSS, SCSS, React Tech stack Linux, MacOS Java, Java-based framework such as Spring JavaScript, JS-based open source such as React, Node
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Technical landscape Tech stack Linux, MacOS
Java, Java-based framework such as Spring Javascript, JS-based framework such as Node, React, React-Native CSS, SCSS Testing framework such as JUnit, Mocha, Enzyme Microsoft Azure, Heroku Git, Webpack Dev process Agile, continuous integration and deployment Agile development
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Core Internship Work Architecture and design
System and functional design of key components based on product design and scope Initial proof-of-concept Architecture and design documentation Development Incremental, steady, high-quality code contribution Peer code review Release every 2-weeks cycle Move fast, succeed fast, fail fast
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Success Criteria Production or production-ready product
Transparent, incremental, iterative improvement to the product Technical documentation
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Time line 1학기 여름 2학기 원격 멘토링을 통한 프로젝트 시작 실리콘밸리 RMS에서 8주간 프로젝트 진행
원격 멘토링을 통한 프로젝트 완성 인턴십 보고서 작성
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Purdue University
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Purdue University •개 교 : 1874년 •유 형 : 공립 종합대학
•소 재 지 : 미국 인디애나 주 West Lafayette (본교) •개 교 : 1874년 •유 형 : 공립 종합대학 •학 생 수 : 39,228명(2014)/•전임교원 : 3,075명 •대외평가 : 미 공과대 9위, 컴퓨터공학 11위(17년 US News) - 세계 74위, 미 26위(QS대학평가(17년), Computer Science)
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추진 방향 구분 캡스톤 디자인 프로젝트 전공이론 교육 세미나 및 영어교육 기본 프로그램 (8주)
美 현지학생, 현지 엔지니어와 같이 프로젝트를 진행하면서 선진화된 문제해결방법, 프로젝트 계획/관리 등을 학습 해외우수 대학이 갖는 인프라 및 기술적 강점을 적극적으로 활용함으로써 국내에서는 경험할 수 없는 다양한 기술 구현을 추진 구분 캡스톤 디자인 프로젝트 전공이론 교육 세미나 및 영어교육 기본 프로그램 (8주) •신상품 개발을 고려한 세분화된 주제를 학생들이 선택하여 팀 구성 후 프로젝트 수행 •프로토타입 개발 후 최종평가 실시 •학생들의 흥미와 관심, 프로젝트 주제 등 부합하는 전공과목 수강 •청강과목 : Computer Information & Technology, Computer Science Graphics Technology 등 수강 •대학인근 지역의 기업멘토를 활용한 기술 코칭 및 최신 ICT기술 트렌드 교육 •Lafayette Adult Resource Academy 영어ELS 및 TOEFL 수강(주4일)
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프로젝트 및 현지 프로그램 상세 프로젝트 전공과목 청강 : 현지 참여교수 개설과목 2과목 이상 청강 의무
SW개발 프로젝트 12개* 과제별 주요 내용 설명 SW분야 : AI, Mobile, Healthcare SW, VR, Safety and Security Robotics 참여기업 : Hewlett Packard Enterprise, Intel, Interactive Intelligence 등 8개 참여교수 : Eric Matson 교수 등 7명/현지학생 : 학부생, 석/박사 학생 등 14명 프로젝트 팀 구성 팀구성 : 수행과제별로 국내학생(4-5명), 지도교수(1명), 현지학생(1명), 기업멘토(1명) 등 7~8명으로 구성 예정 팀구성은 참여학생들의 영어성적, 관심 주제 등을 고려하여 현지지도가 구성 프로젝트 수행 : 팀별로 프로젝트 제안서, 추진계획, 주차별 수행 보고서, 최종결과보고서, 결과발표 PPT 등 전공과목 청강 : 현지 참여교수 개설과목 2과목 이상 청강 의무 전공과목 청강 : 퍼듀대에서 현지 상세자료 추후 안내 예정 영어수업 수강 : 프로젝트 수행을 위한 영어회화능력 향상 Lafayette Adult Resource Center : LARA(Morning 8:30-11:30, 11:30-1:00)
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Time line 1학기 영어 교육 준비 기간 여름 8주간 교육 및 프로젝트 수행 2학기 논문 완성
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Thank you!
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