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The human oral cavity is an important habitat of microbes in the human body. It includes the colonization of various microorganisms such as bacteria, archaea, fungi, protozoa and viruses. Although oral diseases have been studied for decades, we have limited understanding of the boundaries of a healthy oral ecosystem and ecological shift toward dysbiosis. Here, we analyzed salivary microbiomes from...
DoS, probing, phishing, website defacements etc. are the major problems being faced by the network users these days. It has led to exposing of the network resources to the attackers. Hence, it is really important to identify whether a connection is secured or not. This paper proposes an algorithm that discriminates the anomalous from normal connection. Solving DoS problem facilitates the user in faster...
A new synthesis scheme is proposed to effectively generate a random vector with prescribed joint density that induces a (latent) Gaussian tree structure. The quality of synthesis is measured by total variation distance between the synthesized and desired statistics. The proposed layered and successive encoding scheme relies on the learned structure of tree to use minimal number of common random variables...
The article is devoted to the construction of a mathematical model and the algorithm for reducing a set of staganalytical correlated methods taking into account the computational complexity of the problem. The basic steganographic methods for the images spatial domain are described. Known steganalytical algorithms for the spatial domain are reviewed. It is shown that a significant number of steganalytical...
To remove redundant variables and resolve the high correlation problem of soft sensor modelling, this paper proposed an efficient mutual information(MI) based partial least squares(PLS) method. First, we use MI criterion to sort the variables in a descending order according to their importance. Then the linearity between process variables and quality variables is tested through F test. If there is...
Distributed energy resources (DER) systems introduce uncertainties in the electrical grid that cannot be addressed by classical deterministic methods. Power system analytic tools, such as Load Flow (LF), should be revisited to address such uncertainties. Probabilistic Load Flow (PLF) provides a solution to this problem by handling these uncertainties as random variables. Among the existing sampling...
Probabilistic power flow (PPF) approach based on unscented transformation (UT) method, which is particular for a variety of interdependent uncertainty sources associated with AC/DC hybrid grid, is presented herein. The applied traditional UT method is inherent with capability to tackle correlated random variables, however, the accuracy is poor in case of asymmetric distributions. In order to address...
Interaction information is one of the multivariate generalizations of mutual information, which expresses the amount of information shared among a set of variables, beyond the information shared in any proper subset of those variables. Unlike (conditional) mutual information, which is always non-negative, interaction information can be negative. We utilize this property to find the direction of causal...
In this paper, we establish a new inequality tying together the effective length and the maximum correlation between the outputs of an arbitrary pair of Boolean functions which operate on two sequences of correlated random variables. We derive a new upper-bound on the correlation between the outputs of these functions. The upper-bound is useful in various disciplines which deal with common-information...
Maximal leakage from a random variable X to a random variable Y is defined as the multiplicative increase, upon observing Y, of the probability of correctly guessing a randomized function of X, maximized over all such functions [1]. Herein, this guessing framework is used to give operational definitions to common information leakage metrics, including Shannon capacity, maximal correlation, and local...
We investigate binary block-codes (BBC). A BBC is defined as a vector of Boolean functions. We consider BBCs which are generated randomly, and using single-letter distributions. We characterize the vector of dependency spectrums of these BBCs. We use this vector to upper-bound the correlation between the outputs of two distributed BBCs. Finally, the upper-bound is used to show that the large blocklength...
In this paper, we obtain the reverse hypercontractive region for the pair of variables (X, Y) where X is a uniformly distributed binary random variable and Y (a ternary random variable) is obtained by passing X through a symmetric binary erasure channel (BEC), for a non-trivial range of parameters. The technique used builds on two recent results: a) characterization of reverse hypercontractivity using...
The problem of modelling of casual perturbances influencing functioning of complex systems is considered. The approach for correction of the known models is proposed. This approach allow reducing their methodical error without distortion of the physical principles taken as a principle of the mathematical description of casual perturbances.
With increasing number of electric vehicles and electric vehicle charge stations, the question that if existing infrastructure of distribution system will meet new requirements has gained great importance. Mutable load profiles of distribution system and charge stations makes engineering analyses more sophisticated. In this study, some probabilistic analyses are carried out in a local distribution...
Efficient and accurate spectrum sensing is a necessary part in cognitive radio networks. A simple and efficient spectrum sensing technique is proposed to solve the bad performance of spectrum sensing in non synchronous OFDM signals with low SNR regimes. Through the decomposition of the traditional OFDM signal spectrum sensing technology based on cyclostationarity, the real part and the imaginary part...
This paper considers a network of agents generating correlated data according to a known kernel. The correlation structure might undergo a change at an unknown time instant, where the post-change kernel is not fully known. Moreover, due to the data processing and communication costs, only a subset of agents can be observed at any time instant. The objective is to detect the change-point with minimum...
We consider regression testing of safety-critical systems consisting of black-box components. This scenario is common for automotive electronic systems where testing time is expensive and should be reduced without uncontrolled reduction of reliability. This requires a methodology to select test cases from a larger test suite for which a defined quality level of the resulting regression test cycle...
Multiple-set canonical correlation analysis (mCCA) is a generalization of canonical correlation analysis (CCA) to three or more sets of variables. It aims to study the relationships between several sets of variables and it subsumes a number of interesting multivariate data analysis techniques as special cases. The quality and interpretability of the mCCA components are likely to be affected by the...
Characterising the capacity region for a network can be extremely difficult, especially when the sources are dependent. Most existing computable outer bounds are relaxations of the Linear Programming bound. One main challenge to extend linear program bounds to the case of correlated sources is the difficulty (or impossibility) of characterising arbitrary dependencies via entropy functions. This paper...
The construction of a channel code by using a source code with decoder side information is introduced. For the construction, any pair of encoder and decoder is available for a source code with decoder side information. A constrained-random-number generator, which generates random numbers satisfying a condition specified by a function and its value, is used to construct a stochastic channel encoder...
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