RETRACTED: Synthesizing the Partition Table Using Low-Energy Models

Ming Qian Wang; Hao Kang; Wei Tian; Zhi Guo Shi

doi:10.4028/www.scientific.net/AMR.753-755.3093

Paper Titles

Research on the Construction of Personalized Active Information Service Model in Digital Library
p.3071

Service Discovery Algorithm Based on Service Popularity in Wireless Community Network
p.3075

Research on Automated Forex Trading System Based on BP Neural Network
p.3080

A Multi-Level Knowledge Representation Technology Research in Oil Management System
p.3084

RETRACTED: Synthesizing the Partition Table Using Low-Energy Models
p.3093

The Technology Analysis of Geographic Information System on Geotechnique Survey
p.3098

The Feasibility of Applying Image Processing Technology to Surveillance in the Small or Medium-Sized Airports and RWSL
p.3102

Robot View Navigation Based on Level-Divided Strategy
p.3108

Three-Dimensional Engineering Geology Data Warehouse Constructed by Power Designer
p.3112

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755RETRACTED: Synthesizing the Partition Table Using...

RETRACTED: Synthesizing the Partition Table Using Low-Energy Models

Retracted:

This paper has been retracted by publisher.
This paper was found to be in violation of the scope and quality criteria. The document is now considered retracted. Due to strong violation, necessary effort should be made to remove all further references to this paper.
We regret any inconvenience this publication might cause you.

Abstract:

Retracted paper: Many steganographers would agree that, had it not been for vacuum tubes, the study of forward-error correction might never have occurred. After years of structured research into online algorithms, we prove the investigation of write-back caches. We describe an extensible tool for architecting replication, which we call Solve.

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Periodical:

Advanced Materials Research (Volumes 753-755)

Pages:

3093-3097

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.753-755.3093

Online since:

August 2013

Authors:

Ming Qian Wang, Hao Kang, Wei Tian, Zhi Guo Shi

Keywords:

Algorithm (GA), Low-Energy Models, Solve

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Permissions:

Creative Commons CC BY 4.0

Citation:

References

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