We extend our n-gram-based data-driven prediction approach from the Helping Our Own (HOO) 2011 Shared Task (Boyd and Meurers, 2011) to identify determiner and preposition errors in non-native English essays from the Cambridge Learner Corpus FCE Dataset (Yannakoudakis et al., 2011) as part of the HOO 2012 Shared Task. Our system focuses on three error categories: missing determiner, incorrect de...

In this paper we briefly summarize the contents of Manzonetto’s PhD thesis [35] which concerns denotational semantics and equational/order theories of the pure untyped λ-calculus. The main research achievements include: (i) a general construction of λ-models from reflexive objects in (possibly non-well-pointed) categories; (ii) a Stonestyle representation theorem for combinatory algebras; (iii)...

In this paper we briefly summarize the contents of Manzonetto’s PhD thesis [35] which concerns denotational semantics and equational/order theories of the pure untyped λ-calculus. The main research achievements include: (i) a general construction of λ-models from reflexive objects in (possibly non-well-pointed) categories; (ii) a Stonestyle representation theorem for combinatory algebras; (iii)...

We extend our n-gram-based data-driven prediction approach from the Helping Our Own (HOO) 2011 Shared Task (Boyd and Meurers, 2011) to identify determiner and preposition errors in non-native English essays from the Cambridge Learner Corpus FCE Dataset (Yannakoudakis et al., 2011) as part of the HOO 2012 Shared Task. Our system focuses on three error categories: missing determiner, incorrect de...

Introduction: Tuberculosis (TB) is an infectious and contagious disease caused by mycobacterium tuberculosis. Dentists are susceptible to TB. Thus,the aim of this study is to evaluate the knowledge and attitudes of dentists regarding TB. Materials and methods: This cross-sectional and descriptive-analytic study evaluated the knowledge of 120 dentists regarding TB. Using a questionnaire the q...

The prediction of three-dimensional protein structures from onedimensional amino acid sequence information is an important and interesting problem, as much can be learned about a protein’s function from the way that it is folded. There are many different ways to approach this problem, but they all tend to fall into three basic categories: homology modeling, fold recognition, and ab initio predi...

In this paper we describe the steps taken to build a machine learning classifier that successfully classifies legal questions into the most relevant practice area. We have created 16 different general categories that legal questions fall into. Categorizing legal questions into the correct practice area has many useful applications such as facilitating improved realtime feedback, information ret...

We study ideal cotorsion pairs associated to almost exact structures in extension closed subcategories of triangulated categories. This approach allows us extend the recent approximation theory developed by Fu, Herzog et al. for categories above mentioned context. In last part paper we apply order projective classes (in particular localization or smashing subcategories) compactly generated