'Temporal data' presentation slideshows

Temporal Databases

Temporal Databases. VALID-TIME TEMPORAL DATA MODEL TIME NORMALIZATION TEMPORAL QUERY LANGUAGE CONCEPTUAL DESIGN AND LOGICAL DESIGN. Dr. Dang Tran Khanh Head, Department of Information Systems Director, Advances in Security & Information Systems Lab

1.08k views • 90 slides

Temporal Data and The Relational Model

Temporal Data and The Relational Model. Based on the book of the same title, by C.J. Date, Hugh Darwen, and Nikos A. Lorentzos. Hugh Darwen hugh@dcs.warwick.ac.uk www.dcs.warwick.ac.uk/~hugh.

1.1k views • 84 slides

Temporal Databases

Temporal Databases. VALID-TIME TEMPORAL DATA MODEL TIME NORMALIZATION TEMPORAL QUERY LANGUAGE CONCEPTUAL DESIGN AND LOGICAL DESIGN. What is temporal DB?. Temporal databases , encompass all DB applications that require some aspect of time when organizing their information.

2.97k views • 67 slides

SLP Cyclone anti-cyclone asymmetry and time mean field

SLP Cyclone anti-cyclone asymmetry and time mean field. July 8, 2008. NCEP reanalysis 1948-2008, DJF No filtering. NH Time mean (raw) reflected about equator. Total wavenumber >=6. Normalized by STD^3. Skewness (contours) Time mean (colors. Example Fit. Histograms of extrema.

720 views • 51 slides

Lecture 24: Cross-correlation and spectral analysis

Lecture 24: Cross-correlation and spectral analysis. MP574. Correlation and Spectral Analysis. Application 4. Review of covariance. Autocorrelation (Autocovariance). Noise Power. Zero-Mean Gaussian Noise. Power Spectrum. E{P n ( k )} = s 2 = 1.12 = R n (0). Auto-correlation.

726 views • 50 slides

Sofia Event Center 21-22 ??????? 2013 ?.

569 views • 47 slides

Lecture 16 : Visualizations Summary

457 views • 37 slides

Spatial and temporal data management

Spatial and temporal data management. Nothing puzzles me more than time and space; and yet nothing troubles me less, as I never think about them Charles Lamb, 1810. Data management developments. Location-based services Time-varying data. MySQL spatial extensions.

483 views • 32 slides

Discovering Collaborative Patterns in eLearning from Meta-code Subsequence

Discovering Collaborative Patterns in eLearning from Meta-code Subsequence. Name: Yip Chi Kin Date: 15-01-2005. Motivation. ?Collaborative eLearning ?Machine Learning Assess ?Temporal Data Mining ?Generalization Usage. eLearning. ?Learning Style & Model ? Collaborative activity

432 views • 32 slides

Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived From Terra MODIS Land Products

Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived From Terra MODIS Land Products. Eric G. Moody 1,2 , Michael D. King 1 , Steven Platnick 1 , Alan H. Strahler 3 , Crystal Schaaf 3 , Feng Gao 3 1 NASA Goddard Space Flight Center 2 L3-Communications GSI

419 views • 31 slides

Human Action Recognition using Spatio-Temporal Classification

Human Action Recognition using Spatio-Temporal Classification. ??? Ching-Hsien Fang 98.10.14 func1115@csie.ncku.edu.tw. Outline. Introduction Flowchart Learning for Spatio-Temporal Classification 3.1 Spatial Subspace Creation using Locality Preserving Projection(LPP)

612 views • 31 slides

Preparing the Data

Preparing the Data. What is Data?. Attributes. Kumpulan obyek data dan atributnya Atribut adalah property atau karakteristik suatu obyek Contoh : warna mata , temperature, dll Atribut dikenal sebagai variable, field, ataupun karakteristik Kumpulan dari atribut menggambarkan obyek

447 views • 30 slides

Schema Mediated Exchange of Temporal XML Data

322 views • 26 slides

Temporal Databases

Temporal Databases. From Handbook of Temporal Reasoning in Artificial Intelligence By Jan Chomicki & David Toman. Presented by Leila Jalali CS224 presentation. Temporal databases. Some data may be inherently historical e.g., medical or judicial records

452 views • 23 slides

Temporal Data is Pervasive!

Workshop: Interactive Visual Exploration of Electronic Health Records David Wang, Catherine Plaisant, Ben Shneiderman University of Maryland College Park, MD 20742.

313 views • 20 slides

Managing and serving large volumes of gridded spatial environmental data

Managing and serving large volumes of gridded spatial environmental data. Adit Santokhee, Chunlei Liu, Jon Blower, Keith Haines Reading e-Science Centre University of Reading, United Kingdom. Ian Barrodale, E. Davies Barrodale Computing Services Ltd., Victoria, Canada.

352 views • 19 slides

The Future of Time in ArcGIS

The Future of Time in ArcGIS. Steve Kopp. Project Vision. Support time as a new element of feature, raster, and tabular data in ArcGIS. Provide new tools for the ingest, management, exploration, visualization, and analysis of temporal data. Existing ArcGIS support for Time.

277 views • 11 slides

The world of highly heterogeneous data management

The world of highly heterogeneous data management. Highly heterogeneous computing. Applications Desktop Server-based Web-based Mixed Ubiquitous computing Mass produced computers Layered persistence systems (e.g., disk arrays and solid state caches) Mass collection of sensor data

265 views • 11 slides

Manish Gupta (gmanish@microsoft)

2014 Yahoo! DAIS Research Excellence Award Competition. INFORMATION GAIN ANALYSIS (Market-1). INFORMATION GAIN ANALYSIS (Market-N). AUGMENTED FEATURIZER - CMFL (Market-1 ). AUGMENTED FEATURIZER - CMFL (Market-N ).

191 views • 1 slides

Introduction

106 views • 1 slides