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Title: Monitoring High-Dimensional Data for Failure Detection and Localization in Large-Sca
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Posted By: crazy
Created at: Friday 06th of October 2017 03:05:10 PM
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Abstract
It is a major challenge to process high-dimensional measurements for failure detection and localization in large-scale computing systems. However, it is observed that in information systems, those measurements are usually located in a low-dimensional structure that is embedded in the high-dimensional space. From this perspective, a novel approach is proposed to model the geometry of underlying data generation and detect anomalies based on that model. We consider both linear and nonlinear data generation models. Two statistics, that ....etc

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Title: mining projected clusters in high dimensional spaces source
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Posted By: chaitra
Created at: Thursday 17th of August 2017 06:53:58 AM
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Title: High-Resolution Three-Dimensional Sensing of Fast Deforming Objects
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Posted By: samanvai
Created at: Thursday 17th of August 2017 06:31:34 AM
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High-Resolution Three-Dimensional Sensing of Fast Deforming Objects


Motivations

Considerable research on sensing 3D geometry of objects

Focused on rigid objects and static scenes

Moving and deforming objects found in many applications

Motivational Applications

Navigation in dynamic environments

Object recognition

Human tissue modeling for surgical simulation and planning

Robotic manipulation of fabric and rope

Limitations of Existing Methods ....etc

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Title: mining projected clusters in high dimensional spaces java source code
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Posted By: pradhyuman05
Created at: Thursday 17th of August 2017 07:58:22 AM
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Title: projected capacitive touch screen technology
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Posted By: thameem.ms
Created at: Thursday 17th of August 2017 08:32:07 AM
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please visit the following thread for more details on 'projected capacitive touch screen technology'.

http://seminarsprojects.net/Thread-touch-screen--9763?pid=14608#pid14608 ....etc

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Title: Online Index Recommendations For High-Dimensional Databases Using Query Workloads
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Posted By: abygeorge7
Created at: Thursday 17th of August 2017 08:23:01 AM
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Online Index Recommendations For High-Dimensional Databases Using Query Workloads

Scope of this Project:

Best application for this approach is to apply the more time consuming no-constraint analysis in order to determine an initial index set and then apply a lightweight and low control sensitivity analysis for the online query pattern change detection in order to avoid or make the user aware of situations where the index set is not at all effective for the new incoming queries.

Introduction

An increasing number of database applicati ....etc

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Title: design implementation and performance of a load balancer for sip server clusters ppt
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Posted By: bineet
Created at: Thursday 17th of August 2017 05:40:10 AM
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Title: high-dimensional databases
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Posted By: Nazeerthebest
Created at: Thursday 05th of October 2017 03:49:20 AM
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Please visit the below given thread for more details

http://seminarsprojects.net/Thread-online-index-recommendations-for-high-dimensional-databases-using-query-workloads ....etc

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Title: Online Index Recommendations for High-Dimensional Databases Using Query Workloads
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Posted By: midphoenix13
Created at: Thursday 17th of August 2017 05:54:30 AM
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following threads contain details 0n 'Online Index Recommendations for High-Dimensional Databases Using Query Workloads'

http://seminarsprojects.net/Thread-online-index-recommendations-for-high-dimensional-databases-using-query-workloads--4159?pid=34372
http://seminarsprojects.net/Thread-online-index-recommendations-for-high-dimensional-databases-using-query-workloads
http://seminarsprojects.net/Thread-online-index-recommendations-for-high-dimensional-databases-using-query-workloads--8974 ....etc

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Title: Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data
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Posted By: viswanath
Created at: Thursday 05th of October 2017 03:44:14 AM
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Abstract Discriminative patterns can provide valuable insights into data sets with class labels, that may not be available from the individual features or the predictive models built using them. Most existing approaches work efficiently for sparse or low-dimensional data sets. However, for dense and high-dimensional data sets, they have to use high thresholds to produce the complete results within limited time, and thus, may miss interesting low-support patterns. In this paper, we address the necessity of trading off the completeness of discri ....etc

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