Goodness

And what does the Lord require of me? To love mercy, do justice, and walk humbly with God. -Micah 6:8 This quote from the Hebrew Bible has been one of my favorite quotes from sacred scripture in the Judea-Christian tradition for a very long time. It well summarizes how we should live. It well articulates how to live a good life. In this brief and simple statement in response to what God wants of us, it makes clear that there are three things that we should do throughout our lives if we want to follow the dictates of the God in the Jewish and Christian tradition. Even if one isn\u27t affiliated with the JudeaChristian traditions, it is still pretty good advice regarding how one should live

Explicit vs. Implicit L2 grammar knowledge in written error correction

Error correction is undoubtedly an important part of the process of drafting and producing written texts. The aim of the paper is to analyse the learners’ ability to correct grammatical errors in relation to the type of knowledge they employ in this task. Green and Hecht (1992), in an often quoted study, found a low correlation between L2 learners’ knowledge of explicit grammar rules and their ability to correct errors. They interpret this as suggesting that in error correction, learners rely primarily on their implicit knowledge. However, certain design features of their study might have caused the subjects to simply guess the correct forms, which, in turn, as DeKeyser (2003) suggests, may have led to the overestimation of implicit knowledge. This paper reports the results of an experiment where 150 Polish learners of English were administered a corpus-based error correction task, the design of which, however, differed from that of Green and Hecht (1992). These alterations resulted in finding a much closer link between the subjects’ knowledge of rules and their ability to correct grammatical errors

Qualitative Theory for Lensed QSOs

We show that some characteristics of multiply-imaged QSO systems are very model-independent and can be deduced accurately by simply scrutinizing the relative positions of images and galaxy-lens center. These include the time-ordering of the images, the orientation of the lens potential, and the rough morphology of any ring. Other features can differ considerably between specific models; H_0 is an example. Surprisingly, properties inherited from a circularly symmetric lens system are model-dependent, whereas features that arise from the breaking of circular symmetry are model-independent. We first develop these results from some abstract geometrical ideas, then illustrate them for some well-known systems (the quads Q2237+030, H1413+117, HST14113+5211, PG1115+080, MG0414+0534, B1608+656, B1422+231, and RXJ0911+0551, and the ten-image system B1933+507), and finally remark on two systems (B1359+154 and PMN J0134-0931) where the lens properties are more complex. We also introduce a Java applet which produces simple lens systems, and helps further illustrate the concepts.Comment: 26 pages, incl. 15 figs; accepted to AJ; java applet available at http://ankh-morpork.maths.qmw.ac.uk/~saha/astron/lens

3D cellular automata

A cellular automaton (CA) is a set of rules which determines the state of individual cells on a grid, based on neighbourhood relations. CAs have been used by researchers to model a wide range of systems from cell growth to cosmology to universal computation. However nearly all such models have been on one or two dimensional grids. This article provides a brief history of the development of CAs and then extends the models to three dimensions using open source software; Blender and Python. New 3D rules are examined and the development of 3D cell configurations explored and visualized

A Machine learning approach to POS tagging

We have applied inductive learning of statistical decision trees and relaxation labelling to the Natural Language Processing (NLP) task of morphosyntactic disambiguation (Part Of Speech Tagging). The learning process is supervised and obtains a language model oriented to resolve POS ambiguities. This model consists of a set of statistical decision trees expressing distribution of tags and words in some relevant contexts. The acquired language models are complete enough to be directly used as sets of POS disambiguation rules, and include more complex contextual information than simple collections of n-grams usually used in statistical taggers. We have implemented a quite simple and fast tagger that has been tested and evaluated on the Wall Street Journal (WSJ) corpus with a remarkable accuracy. However, better results can be obtained by translating the trees into rules to feed a flexible relaxation labelling based tagger. In this direction we describe a tagger which is able to use information of any kind (n-grams, automatically acquired constraints, linguistically motivated manually written constraints, etc.), and in particular to incorporate the machine learned decision trees. Simultaneously, we address the problem of tagging when only small training material is available, which is crucial in any process of constructing, from scratch, an annotated corpus. We show that quite high accuracy can be achieved with our system in this situation.Postprint (published version

Verbal chunk extraction in French using limited resources

A way of extracting French verbal chunks, inflected and infinitive, is explored and tested on effective corpus. Declarative morphological and local grammar rules specifying chunks and some simple contextual structures are used, relying on limited lexical information and some simple heuristic/statistic properties obtained from restricted corpora. The specific goals, the architecture and the formalism of the system, the linguistic information on which it relies and the obtained results on effective corpus are presented