Several variants of a first-order simplification rule for nonnormal form tableaux using syntactic constraints are presented. These can be used as a framework for porting methods like unit resolution or hyper tableaux to non-normal form free variable tableaux.

An alternative approach to the semantics of definite descriptions was proposed by Heim in her dissertation [1982]. Heim assigns to pragmatics a larger part of the task of specifying the meaning of definite descriptions than the neo-Russellians do. In Heim’s theory, definite and indefinite NPs are semantically equivalent, and both introduce free variables. The truth conditions proposed by Heim f...

We investigate the problem of estimating the density function of multivariate binary data. In particular, we focus on models for which computing the estimated probability of any data point is tractable. In such a setting, previous work has mostly concentrated on mixture modeling approaches. We argue that for the problem of tractable density estimation, the restricted Boltzmann machine (RBM) pro...

The paper describes an implementation of a generator of random instances of non-binary constraint satisfaction problems that meets a given set of specifications. This is a continuation of the work we started in [1]. 1 Description The program is designed to generate random instances of Constraint Satisfaction Problems (CSPs) that meet a set of specified parameters, such as the number of variable...

Traditional process monitoring methods, such as PCA, PLS, ICA, MD et al., are strongly dependent on continuous variables because most of them inevitably involve Euclidean or Mahalanobis distance. With industrial processes becoming more and complex integrated, binary also appear in besides variables, which makes challenging. The aforementioned traditional approaches incompetent to mine the infor...

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Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a novel image-encoded forecasting method that input and output binary digital two-dimensional (2D) images are transformed from decimal data. Omitting ...