Repeated adhesion frequency assay is the only published method for measuring the kinetic rates of cell adhesion. Cell adhesion plays an important role in many physiological and pathological processes. Traditional analysis of adhesion frequency experiments assumes that the adhesion test cycles are independent Bernoulli trials. This assumption can often be violated in practice. Motivated by the a...

†Bernoulli News is the of󰅳icial newsletter of the Bernoulli Society, publishing news, calendars of events, and opinion pieces of interest to Bernoulli Societymembers, aswell as to theMathematical Statistics andProbability community at large. The views and opinions expressed in editorials and opinion pieces do not necessarily re󰅳lect the of󰅳icial views of the Bernoulli Society, unless explicitly...

The Naive Bayes classifier exists in different versions. One version, called multi-variate Bernoulli or binary independence model, uses binary word occurrence vectors, while the multinomial model uses word frequency counts. Many publications cite this difference as the main reason for the superior performance of the multinomial Naive Bayes classifier. We argue that this is not true. We show tha...

Sampling biases are often assumed to arise from the type of information that learners sample (Fiedler, 2008), the possibility of negative payoffs (Denrell, 2001), or the prevalence of small samples (Kareev et al., 2002). Here, we show that even in a natural sampling situation (repeated Bernoulli trials), in which a learner’s only decision is when to stop sampling, different sampling goals can h...

To enhance the information security in network communications, this paper suggests a new speech scrambling algorithm based on random permutation, chaotic mapping and pseudo random binary scrambling.Firstly random permutation algorithm is used to shuffle the rows of the original speech followed by shuffling the rows using chaotic Bernoulli mapping. This produces an intermediary scrambled speech....

Neutron stars in binary orbit emit gravitational waves and spiral slowly together. During this inspiral, they are expected to have very little vorticity. It is in fact a good approximation to treat the system as having zero vorticity, i.e., as irrotational. Because the orbital period is much shorter than the radiation reaction time scale, it is also an excellent approximation to treat the syste...

Abstract: In this paper, we present a performance analysis of a system with two multiplexers in tandem. Each multiplexer is fed by an external arrival process that consists of the superposition of the traffic generated by independent binary Markov sources. Further, the output of the first multiplexer is fed into the second multiplexer according to an independent Bernoulli process. The probabili...

We propose a class of continuous-time Markov counting processes for analyzing correlated binary data and establish a correspondence between these models and sums of exchangeable Bernoulli random variables. Our approach generalizes many previous models for correlated outcomes, admits easily interpretable parameterizations, allows different cluster sizes, and incorporates ascertainment bias in a ...

We fit a Bayesian generalized mixed-effects model for binary data. For patient i = 1, . . . ,n j in each hospital j = 1, . . . ,J, let Yi j be a Bernoulli random variable with mean pi j, which represents the in-hospital probability that the patient survived after STEMI. The pi j’s are modelled through a logit regression with covariates xi j := (1,xi j1,xi j2,xi j3) which represent age, Symptom ...

This paper considers the problem of robust H filter design in uncertain discrete-time singular systems with possible missing measurements due to unreliable network transmission channels. The stochastic variable satisfying Bernoulli random binary distribution is introduced to model the missing phenomena and the corresponding filtering error dynamics with delay is then induced. We provide a set o...