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Title: historical background of highway speed sensing
Page Link: historical background of highway speed sensing -
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Created at: Friday 05th of October 2012 03:03:11 AM
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Title: Mobile Radio Systems Historical Milestones to 1995
Page Link: Mobile Radio Systems Historical Milestones to 1995 -
Posted By: seminar details
Created at: Friday 08th of June 2012 02:25:10 PM
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Mobile Radio Systems Historical Milestones to 1995




Early Milestones

1885: Heinrich Hertz—First radio
transmission across a laboratory using
coils and gaps
1897: Guglielmo Marconi—First radio
transmission using a pole on a mast
over 18 miles to a tugboat
1921 and 1923: One-way police radio in
Detroit and London, respectively


Mid-century Milestones

1927: First international spectrum
management conference (for carriers up to
1 ....etc

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Title: ppt on network security overcome password hacking through graphical password authentication
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Title: MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS
Page Link: MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS -
Posted By: devaraj.nb
Created at: Thursday 16th of June 2011 06:36:58 PM
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HI i would like to get a detailed explanation of this project how it will be done and if possible send me the data flow or class diagram of the whole project so tat i can get a clear idea of this project..


Please send me the above asked to [email protected] and please specify your number for i can call to clarify if any things i need.



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Title: A Review of Hidden Markov Models for Context-Based Classification Historical Note
Page Link: A Review of Hidden Markov Models for Context-Based Classification Historical Note -
Posted By: seminar class
Created at: Saturday 26th of February 2011 02:04:49 PM
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A Review of Hidden Markov Models for Context-Based Classification
Historical Note

• “Classification in Context” was well-studied in pattern recognition in the 60’s and 70’s
– e.g, recursive Markov-based algorithms were proposed, before hidden Markov algorithms and models were fully understood
• Applications in
– OCR for word-level recognition
– remote-sensing pixel classification
Context-Based Classification Problems
• Medical Diagnosis
– classification of a patient’s state over ....etc

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Title: MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS
Page Link: MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS -
Posted By: project topics
Created at: Thursday 28th of April 2011 09:01:39 PM
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Domain
KNOWLEDGE AND DATA ENGINEERING

Technology
JAVA

Abstract:
MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS

A P2P-based framework supporting the extraction of aggregates from historical multidimensional data is proposed, which provides efficient and robust query evaluation. When a data population is published, data are summarized in a synopsis, consisting of an index built on top of a set of subsynopses (storing compressed representations of distinct data portions). The index and the subsy ....etc

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Title: password for downloaded pdf hdfc historical bank statement
Page Link: password for downloaded pdf hdfc historical bank statement -
Posted By:
Created at: Wednesday 10th of July 2013 01:39:57 PM
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Title: managing multidimensional historical aggregate data in unstructured p2p networks
Page Link: managing multidimensional historical aggregate data in unstructured p2p networks -
Posted By: Geetanjali_Mohite
Created at: Thursday 18th of August 2011 02:36:38 PM
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Hello,
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Title: hdfc bank pdf statement password
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Created at: Saturday 06th of July 2013 05:21:26 PM
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Title: THREE-DIMENSIONAL SHAPE RECOVERY BASED ON SINGLE HISTORICAL IMAGE
Page Link: THREE-DIMENSIONAL SHAPE RECOVERY BASED ON SINGLE HISTORICAL IMAGE -
Posted By: seminarsense
Created at: Wednesday 17th of November 2010 12:00:26 AM
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INTRODUCTION
Image Reconstruction
As name implies it is the process of reconstructing the three dimensional
shape of a single frame image.
principle
The principle of 3D-reconstruction is that, the object's three dimensions
are acquired by the conversion from the shade of gray to the depth of the
information of the image.


The basic design concept
The object surface shadeof gray can be expressed as
E(x,y) = I(x,y)cos
Where
I(x,y) = Light intensity of the optical source.
 = Object surface re
ecti ....etc

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