Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

KAIST 전산학과 iDBLab 20140318 신입생 소개자료

2,654 views

Published on

Published in: Education
  • Be the first to comment

  • Be the first to like this

KAIST 전산학과 iDBLab 20140318 신입생 소개자료

  1. 1. Intelligent Database Systems Lab. 현 순 주 2014.03.18(Wed.)
  2. 2. Lab Members • Professor – Hyun, Soon Joo • sjhyun@kaist.ac.kr • #804, ITC Bldg. (N1) • Tel. 350-3563 (office) • Students – 3 Ph.D. students – 2 M.S. students – Office • #822, ITC Bldg. (N1) • Tel. 350-7763 • Homepage – http://idb.kaist.ac.kr 2 http://idb.kaist.ac.kr/members
  3. 3. Lab Annual Activity • Home-coming Day • Winter Workshop 3 http://idb.kaist.ac.kr/gallery
  4. 4. 1876 938946 2010 Telephone ENIAC ARPA Net RDB 71 Web ubiquitous computing 1945 stored- program computer transistor 47 5251 UNIVAC program 57 FORTRAN 69 Intel 4004 80 MS-DOS 81 IBM PC 94 95 smart- phone SNS MOSAICApple Windows95 Linux Future Internet Transaction ER Distributed Multidatabase NewDBs IMS IBM701 webclient-server ubiquitous NewDBs OODB Evolution of Computer Technology 4
  5. 5. Computing Paradigm text, multimedia giga, tera, peta information, knowledge wired, wireless system-centric, user-centric desk-top personal, potable, wearable server/client, p2p, m2m distributed, mobile static, dynamic any time anywhere 5
  6. 6. network userinformation paradigm communicationparadigm browsing display remote access archiving multiple access global, virtual, cyber distribution interoperation content manipulation, Interactive querying context -aware mobile wireless ubiquity p2p, m2m Change of User Paradigm 6
  7. 7. Research Interest (1/3) • Context-aware Computing in Ubiquitous Environment – High-level context • User activities • Social relationships – Low-level context • Environmental sensor data • System parameters • Application usage data • Social network data 7
  8. 8. Research Interest (2/3) • Social-aware Computing – Multi-dimensional context • Social / spatial / temporal semantics – User interest inference – Social interaction recommendation – Collaborative group identification 8 [Interaction Opportunity Discovery in Public Places]
  9. 9. Research Interest (3/3) • 전자신문, 세계 석학, 미래를 말하다(하) – 김종훈 Bell Lab. 사장 9
  10. 10. Research Interest(3/3) 10 Sensor Node Applications | habitat monitoring, disaster surveillance, military supports, patient monitoring, etc. Storage (Database) DBMS Sensor Database Query/ResultQuery/Result (Virtual) Storage Wireless Sensor Network
  11. 11. Research Interest(3/3) • 모바일 환경 응용분야: Urban Sensing – 일정한 노선을 경유하는 시내버스에 센서 에이전트 부착 – 도시의 교통정보, 대기오염도, 주변 상황에 대한 기본적인 정보를 센서를 통해 획득 – 센서의 값을 네트워크를 통해 중앙 모듈로 전송 11
  12. 12. Research Interest(3/3) • Sensor Network Query Processor and Language(SNQL) 12
  13. 13. Ongoing Projects • http://idb.kaist.ac.kr/?mid=project 13
  14. 14. 14

×