'Streaming data' diaporamas de présentation

Optimizing database access and diving into .Net SqlClient

Optimizing database access and diving into .Net SqlClient. Mladen Prajdi? SQL Server MVP mladenp@gmail.com @ MladenPrajdic. About me. Welcome to Slovenia The sunny side of Alps. Disclaimer I use SELECT * in demos only for brevity ?. Agenda.

592 views • 44 slides

Project Context

NDIIPP Project: Collection and Preservation of At-Risk Digital Geospatial Data Partners: NCSU Libraries Project Lead: Steve Morris NC Center for Geographic Information & Analysis Project Lead: Zsolt Nagy. Project Context. Partnership between university library (NCSU) and state agency (NCCGIA)

576 views • 43 slides

Technologies for Cluster Computing

Technologies for Cluster Computing. Oren Laadan Columbia University <orenl@cs.columbia.edu>. ECI, July 2005. Course Overview (contd). What is Cluster Computing ? Parallel computing, enabling technologies, definition of a cluster, taxonomy Middleware

630 views • 42 slides

COP5725 Advanced Database Systems

COP5725 Advanced Database Systems. MapReduce. Spring 2014. What is MapReduce?. Programming model expressing distributed computations at a massive scale

563 views • 41 slides

Monitoring Message Streams : Retrospective and Prospective Event Detection

Monitoring Message Streams : Retrospective and Prospective Event Detection. OBJECTIVE :. Monitor streams of textualized communication to detect pattern changes and "significant" events. Motivation: sniffing and monitoring email traffic. TECHNICAL PROBLEM :.

487 views • 37 slides

Privacy-Preserving IntelliDrive Data for Signalized Intersection Performance Measurement

Vehicle Index Estimation for Signalized Intersections Using Sample Travel Times Peng Hao , Zhanbo Sun, Xuegang (Jeff) Ban, Dong Guo , Qiang Ji Rensselaer Polytechnic Institute ISTTT 20, The Netherlands July 19, 2013.

405 views • 27 slides

Stream Clustering

Stream Clustering. CSE 902. Big Data. Stream analysis. Stream : Continuous flow of data Challenges Volume: Not possible to store all the data One-time access: Not possible to process the data using multiple passes

623 views • 25 slides

Future Opportunities for Lightning Data The Time is Right to Review Federal Agency Lightning Requirements

392 views • 24 slides

Ninja and the Post-PC Era

Ninja and the Post-PC Era. David Culler U.C. Berkeley Mar 12, 1999. http://ninja.cs.berkeley.edu http://postPC.cs.berkeley.edu. Natural Tides of Innovation. Innovation. ??. Integration. Personal Computer Workstation Server. Log R. Minicomputer. Mainframe. 2/99. Time.

436 views • 23 slides

Fair Use Agreement

Fair Use Agreement. This agreement covers the use of all slides on this CD-Rom, please read carefully. You may freely use these slides for teaching, if You send me an email telling me the class number/ university in advance.

377 views • 23 slides

DBMS Lab Projects

DBMS Lab Projects. Information System Design. Auction Portal. Items Bidders Bid Managers Lowest Bid Incremental Bidding. Resume Posting Service. Resume Posts Employers Managers Matching. Tourism Information System. Data Integration Location Aware Services Map Based Interface

333 views • 23 slides

Using GIS in Creating an End-to-End System for Publishing Environmental Observations Data

Using GIS in Creating an End-to-End System for Publishing Environmental Observations Data. Jeffery S. Horsburgh David G. Tarboton, David R. Maidment, Ilya Zaslavsky David Stevens, Amber Spackman. Support: EAR 0622374 CBET 0610075. Little Bear River WATERS Test Bed.

366 views • 22 slides

Ocean Observatories Initiative Cyberinfrastructure

Ocean Observatories Initiative. Ocean Observatories Initiative Cyberinfrastructure. Karen Stocks OOI CI Data Curator University of California, San Diego. OOI Science Mission. OOI science themes Ocean-atmosphere exchange Climate variability, ocean circulation, and ecosystems

337 views • 20 slides

Intro to Node.js Winnipeg.js

http:// winnipegjs.com For questions tweet @ winnpegjs Michael Yagudaev - @ yagudaev Peter Braun. Intro to Node.js Winnipeg.js. Introductions. Introduce yourself Your name What you do for a living? How does Javascript fit into your life? What do you expect to get from this group?.

248 views • 16 slides

Middies: Passive middleware abstractions for pervasive computing environments

Middies: Passive middleware abstractions for pervasive computing environments. Daniel Cutting, Adam Hudson, Aaron Quigley University of Sydney. Pervasive computing Middies Data distribution. Pervasive computing. Small mobile devices + large fixed servers

283 views • 15 slides

CompE 460 Real-Time and Embedded Systems

242 views • 13 slides

Imputation of Streaming Low-Rank Tensor Data

284 views • 11 slides

Extreme Scale Analytics on Spatio -Temporal Datasets

Extreme Scale Analytics on Spatio -Temporal Datasets. Joel Saltz Center for Comprehensive Informatics & Biomedical Informatics Department Emory University. Morphometric Image Analysis Pipeline. Preprocessing: normalization, tiling, etc. Segmentation: identify nuclei as objects

188 views • 10 slides

The NSF Perspective on HEC-FSIO (as seen from CNS)

Keith Marzullo DIrector , Division of Computer and Network Systems CISE Directorate National Science Foundation August 10, 2011. The NSF Perspective on HEC-FSIO (as seen from CNS). The Future of Computing.

190 views • 8 slides

Questions and Topics Review Nov. 22, 2011

Questions and Topics Review Nov. 22, 2011. Assume you have to do feature selection for a classification task. What are the characteristics of features (attributes) you might remove from the dataset prior to learning the classification algorithm ?

164 views • 5 slides