We show that L(R) absoluteness for semi-proper forcings is equiconsistent with the existence of a remarkable cardinal, and hence by [6] with L(R) absoluteness for proper forcings. By [7], L(R) absoluteness for stationary set preserving forcings gives an inner model with a strong cardinal. By [3], the Bounded Semi-Proper Forcing Axiom (BSPFA) is equiconsistent with the Bounded Proper Forcing Axi...

This article presents the language LinF for L-System specification. L-Systems are formal string rewriting systems introduced in 1968 by the botanist Aristid Lindenmayer that are used to model fractal images. LinF allows the definition of three-dimensional fractals and stochastic fractals. Together with the LinF definition this paper presents the implementation of cFLC, an OpenGL-based system th...

The class of Church-Rosser congruential languages has been introduced by McNaughton, Narendran, and Otto in 1988. A language L is Church-Rosser congruential (belongs to CRCL), if there is a finite, confluent, and length-reducing semi-Thue system S such that L is a finite union of congruence classes modulo S. To date, it is still open whether every regular language is in CRCL. In this paper, we ...

One of the important and basic topics in the theory of classical point set topology and several branches of mathematics, which have been researched by many authors, is continuity of functions. This concept has been extended to the setting of I-continuity of functions. Janković and Hamlett [1, 2] introduced the notion of I-open sets in topological spaces. Abd El-Monsef et al. [3] further investi...

This paper describes a new approach to predicting the aspectual class of verbs in context, i.e., whether a verb is used in a stative or dynamic sense. We identify two challenging cases of this problem: when the verb is unseen in training data, and when the verb is ambiguous for aspectual class. A semi-supervised approach using linguistically-motivated features and a novel set of distributional ...

Syndromic Surveillance has been performed using machine learning and other statistical methods to detect disease outbreaks. These methods are largely dependent on the availability of historical data to train the machine learning-based surveillance system. However, relevant training data may differ from region to region due to geographical and seasonal trends, meaning that the syndromic surveill...