Binary Decision Diagrams (Bryant, R. E., 1986, IEEE Trans. Comput. C-35) to represent relations and formulas. We then show how our new Mu-Calculus model checking algorithm can be used to derive efficient decision procedures for CTL model checking, satistiability of linear-time temporal logic formulas

Recent work in text classification has used two different first-order probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multi-variate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e

A number of authors have considered multivariate Gaussian models for marginal independence. In this paper we develop models for binary data with the same independence structure. The models can be parameterized based on Möbius inversion and maximum likelihood estimation can be performed using a

randomly constructed molecular automata is examined by modeling the gene as a binary (on-off) device and studying the behavior of large, randomly con-structed nets of these binary “genes”. The results suggest that, if each “gene ” is directly affected by two or three other “genes”, then such random nets

efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model. We focus primarily on the case in which the model is only allowed to translate with respect to the image. Then we consider how to extend the techniques to rigid motion

Recently, the IEEE has standardized the 802.11 protocol for Wireless Local Area Networks. The primary medium access control (MAC) technique of 802.11 is called distributed coordination function (DCF). DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary

Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co

the convergence the more exact the approximation. • If the hidden nodes are binary, then thresholding the loopy beliefs is guaranteed to give the most probable assignment, even though the numerical value of the beliefs may be incorrect. This result only holds for nodes in the loop. In the max-product (or "

Foreign aid flows have increased considerably during the last decades, targeting, apart from development objectives, goals related to democracy. In this paper we investigate whether aid has affected the political regime of recipient countries. To this end, we use annual data on Net Official Development Assistance covering 64 aid-recipients. Because of data limitations, we cover the 1967–2002 period. We find that aid flows decreased the likelihood of observing a democratic regime in a recipient country. This effect is sensitive to economic and social conditions. The negative relation between aid and democracy is moderated when aid flows are preceded by economic liberalization. Aid from the U.S. has a non-significant effect on the political regime of recipients. © 2011 Elsevier B.V. All rights reserved. JEL classification:

at two given time points may also depend on the history of the time dependent covariates of the individual. In this paper, we exploit a dynamic logistic model to analyse such history based binary data. A moment based generalized quasi-likelihood (GQL) approach is considered for optimal estimation