title: Electing a candidate: A speculative history of the bacterial phylum OP10

authors: Dunfield, Peter F.

subjects: 16s ribosomal-rna

abstract: In 1998, a cultivation-independent survey of the microbial community in Obsidian Pool, Yellowstone National Park, detected 12 new phyla within the Domain Bacteria. These were dubbed candidate divisions OP1 to OP12. Since that time the OP10 candidate division has been commonly detected in various environments, usually as part of the rare biosphere, but occasionally as a predominant community component. Based on 16S rRNA gene phylogeny, OP10 comprises at least 12 class-level subdivisions. However, despite this broad ecological and evolutionary diversity, all OP10 bacteria have eluded cultivation until recently. In 2011, two reference species of OP10 were taxonomically validated, removing the phylum from its candidate status. Construction of a highly resolved phylogeny based on 29 universally conserved genes verifies its standing as a unique bacterial phylum. In the following paper we summarize what is known and what is suspected about the newest described bacterial phylum, the Armatimonadetes.

text: Electing a candidate: A speculative history of the bacterial phylum OP10 In 1998, a cultivation-independent survey of the microbial community in Obsidian Pool, Yellowstone National Park, detected 12 new phyla within the Domain Bacteria. These were dubbed candidate divisions OP1 to OP12. Since that time the OP10 candidate division has been commonly detected in various environments, usually as part of the rare biosphere, but occasionally as a predominant community component. Based on 16S rRNA gene phylogeny, OP10 comprises at least 12 class-level subdivisions. However, despite this broad ecological and evolutionary diversity, all OP10 bacteria have eluded cultivation until recently. In 2011, two reference species of OP10 were taxonomically validated, removing the phylum from its candidate status. Construction of a highly resolved phylogeny based on 29 universally conserved genes verifies its standing as a unique bacterial phylum. In the following paper we summarize what is known and what is suspected about the newest described bacterial phylum, the Armatimonadetes.

year: 2012

title: Application of Swingler's Method for Analysis of Multicomponent Exponentials with Special Attention to Non-equispaced Data

authors: Hasan, Rahat

subjects: Science & Technology

abstract: Swingler enhanced the work of Gardner to provide an elegant deconvolution method by which multiple summed exponential components might be resolved within time-domain data. Nevertheless, the application of the method remains limited owing to subtle complications that discourage many users. We present a tutorial and extend the approach to handle nonequispaced data. Finally the method’s limits are identified in the case of closely-spaced exponential components with added input noise.

text: Application of Swingler's Method for Analysis of Multicomponent Exponentials with Special Attention to Non-equispaced Data Swingler enhanced the work of Gardner to provide an elegant deconvolution method by which multiple summed exponential components might be resolved within time-domain data. Nevertheless, the application of the method remains limited owing to subtle complications that discourage many users. We present a tutorial and extend the approach to handle nonequispaced data. Finally the method’s limits are identified in the case of closely-spaced exponential components with added input noise.

year: 2016

title: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language

authors: Cocks, John

subjects: Māori

abstract: This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

text: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

year: 2012