两篇文章
1：Optimizing ontology and semantic search usinggenetic and greedy
algorithms approach
abstract：
The content is extracted by means of semantic relevancy.
The semantic relevancies relate the content of videos based on a
certain parameter. The parameter varies between system to system
(implementation). The parameter will improve the performance of
semantic relevancy and accuracy. This accuracy is obtained after
various random experiments. Here a method called concept, sub
concept graph method is used to implement the semantic relevancies.
A graph algorithm is constructed to improve the relevancies between
concepts. The ontology model is created based on the relationship
between the vertices. At first relationship between the parent and
child are calculated.
diagrammatic representations are done.
priority of web pages are done and based on the number of
relationships the value for the vertices are noted.
Then based on all the relationships the
Based on hit rates the priority of web pages are done and based on the
number of
relationships the value for the vertices are noted.
2： Optimization Of Vertical Links In A Three Dimensional NOC Based
Multicore Crypto Processor For Cloud Computing
abstract:
The applications of network on chip has become wide .However the
implementation of 3D NoC has
become a vital issue with the fabrication of TSV.Hence, this work focuses on
the means of reducing the number of
vertical links in the wake of reducing the TSV to have an improved yield and
reduction in link power consumption.
The optimum number of 3D routers for a given 3D mesh NoC is modeled as an
optimization problem .Then for
the optimum number of 3D routers, their best possible arrangements and
grouping has been extended as another
optimization problem considering throughput, latency as constraints and
solved using ACO and SA and results
have been compared. This has been applied for the design of a 3D NoC based
multicore crypto processor design for
cloud computing. It is found that there is improvement in the execution
times for the RC6 and AES algorithms for
varying key size with and without NoC , AES256 shows an improvement of 49%
with NoC and RC6128 is close
by 44.7% .The throughput improvement. is 52% for RC6 and Blowfish by 48%.
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