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In the present scenario, even well administered networks are susceptible to sophisticated cyber attacks. Such attack combines vulnerabilities existing on different systems/services and are potentially more harmful than single point attacks. One of the methods for analyzing such security vulnerabilities in an enterprise network is the use of attack graph. It(More)
Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality(More)
A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the(More)
A new approach for developing multimodel streamflow forecasts is presented. The methodology combines streamflow forecasts from individual models by evaluating their skill, represented by rank probability score (RPS), contingent on the predictor state. Using average RPS estimated over the chosen neighbors in the predictor state space, the methodology assigns(More)
Data processing and source identification using lower dimensional hidden structure plays an essential role in many fields of applications, including image processing, neural networks, genome studies, signal processing and other areas where large datasets are often encountered. One of the common methods for source separation using lower dimensional structure(More)
In mobile ad hoc network (MANET) nodes have a tendency to drop others’ packet to conserve its own energy. If most of the nodes in a network start to behave in this way, either a portion of the network would be isolated or total network functionality would be hampered. This behavior is known as selfishness. Therefore, selfishness mitigation and enforcing(More)
The estimation of probability density functions is one of the fundamental aspects of any statistical inference. Many data analyses are based on an assumed family of para-metric models, which are known to be unimodal (e.g., exponential family, etc.). Often a histogram suggests the unimodality of the underlying density function. Parametric assumptions,(More)
Hydrogen sulphide (H2S) is known to play a vital role in human physiology and pathology which stimulated interest in understanding complex behaviour of H2S. Discerning the pathways of H2S production and its mode of action is still a challenge owing to its volatile and reactive nature. Herein we report azide functionalized metal-organic framework (MOF) as a(More)
Chemical separation has great importance in industrial applications. Separation of xylene isomers still prevails to be one of the most important challenges in chemical industry, due to the large amount of commercial use of p-xylene in the production of beverage bottles, fibers and films. A novel Zn(II)-based dynamic coordination framework based on flexible(More)