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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Power System Restoration (PSR) has been a subject of study for many years. In recent years many techniques were proposed to solve the limitations of predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance.

This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on Artificial Neural Networks (ANNs). This proposed scheme has been tested on a 162-bus transmission system and compa ....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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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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Definition
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, thr ....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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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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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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ABSTRACT
Location prediction serves to save capacity on the air interface of mobile radio networks. A selection of neural networks of the feed-forward and feedback type are examined to prove their suitability for this purpose. As first results preferable network structures, input vectors, learning parameters and the simulated prediction probabilities are presented. A comparison with conventional methods shows the advantages and disadvantages of the use of neural networks for motion prediction. The results show that t ....etc

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A high degree of security for normal operation of larger inter connected power system is required one of the requirements of reliable service in electrical power system is to maintain the synchronous machines running in parallel with adequate capacity to meat the low demand with the growing stress on present days power systems, the potential impact of faults and other disturbances on their security is increasing. Protective relays in the power system detect faults and trigger the opening of circuit to isolate the fault. The power system can be ....etc

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