Deterministic Dynamic Quorum for Replication of FilesDETERMINISTIC DYNAMIC QUORUM FOR REPLICATION OF FILES ....etc

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ABSTRACT :
Heterogeneous types of gene expressions may provide a better insight into the biological role of gene interaction with the environment, disease development and drug effect at the molecular level. In this paper for both exploring and prediction
purposes a Time Lagged Recurrent Neural Network with trajectory learning is proposed for identifying and classifying the gene functional patterns from the heterogeneous nonlinear time series microarray experiments. The pr ....etc

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In third generation WCDMA systems, shared channels allow many users to jointly utilize a single Orthogonal Variable Spreading Factor (OVSF) code. In this paper, we propose a Scheduling Algorithm with Dynamic Priority Assignment (DPA) which is designed for the Downlink-Shared channel (DSCH) of 3G WCDMA systems and operates within a cross layer framework. The DPA scheduler has low computational complexity and is able to provide QoS differentiation among traffic flows based on their delay sensitivity. Through the cross layer framework, DPA takes i ....etc

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Myself BLACK,doing my Engineering final year in PSP college.For my final year project i am working Medical image processing field.Now i want ideas regarding the article Non local means speckle filtering of ultrasound images using Bayesian framework.I have attached the abstract of the project.

Abstract”In image processing, restoration is expected to improve
the qualitative inspection of the image and the performance
of quantitative image analysis techniques. In this paper, an adaptation
of the nonlocal (NL)-means filter is propos ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion.

A number of current applications using Bayesian networks are examined. The paper concludes with a brief ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion. A number of current applications using Bayesian networks are examined. The paper concludes with a brief des ....etc

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Abstract—Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization for ....etc

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Sparse Bayesian Learning Of Filters For Efficient Image Expansion

– Image Processing- Dotnet

We propose a framework for expanding a given image using an interpolator that is trained in advance with training data, based on sparse Bayesian estimation for determining the optimal and compact support for efficient image expansion. Experiments on test data show that learned interpolators are compact yet superior to classical ones. ....etc

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DYNAMIC SEARCH ALGORITHM IN UNSTRUCTURED PEER-TO-PEER NETWORKS--PARALLEL AND DISTRIBUTED SYSTEMS

Designing efficient search algorithms is a key challenge in unstructured peer-to-peer networks. Flooding and random walk (RW) are two typical search algorithms. Flooding searches aggressively and covers the most nodes. However, it generates a large amount of query messages and, thus, does not scale. On the contrary, RW searches conservatively. It only generates a fixed amount of query messages at each hop but would take longer search time. We pr ....etc

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