title: Airport surface access strategies and targets

authors: Francis, Graham

subjects: airport

abstract: Airport surface access is increasingly seen as a major problem not only in the UK but worldwide given its impact in terms of both traffic congestion and environmental degradation. In 1998 the UK Government published a White Paper entitled ‘A New Deal for Transport’ (DETR, 1998) in which it introduced the idea of Airport Transport Forums to be established by UK airports in order to set targets for the reduction in the proportion of journeys to/from the airport made by car based modes. In this working paper the authors critically assess the targets developed for achieving the objective of a greater use of public transport in making journeys to airports. Evidence is presented as to how UK airports have developed targets in order to respond to the Government’s initiative.

text: Airport surface access strategies and targets Airport surface access is increasingly seen as a major problem not only in the UK but worldwide given its impact in terms of both traffic congestion and environmental degradation. In 1998 the UK Government published a White Paper entitled ‘A New Deal for Transport’ (DETR, 1998) in which it introduced the idea of Airport Transport Forums to be established by UK airports in order to set targets for the reduction in the proportion of journeys to/from the airport made by car based modes. In this working paper the authors critically assess the targets developed for achieving the objective of a greater use of public transport in making journeys to airports. Evidence is presented as to how UK airports have developed targets in order to respond to the Government’s initiative.

year: 2004-09

title: A new framework for yield curve, output and inflation relationships

authors: Krippner, Leo

subjects: yield curve

abstract: This article develops a theoretically-consistent and easy-to-apply framework for interpreting, investigating, and monitoring the relationships between the yield curve, output, and inflation. The framework predicts that steady-state inflation plus steady-state output growth should be cointegrated with the long-maturity level of the yield curve as estimated by a arbitrage-free version of the Nelson and Siegel (1987) model, while the shape of the yield curve model from that model should correspond to the profile (that is, the timing and magnitude) of expected future inflation and output growth. These predicted relationships are confirmed empirically using 51 years of United States data. The framework may be used for monitoring expectations of inflation and output growth implied by the yield curve. It should also provide a basis for using the yield curve to value and hedge derivatives on macroeconomic data.

text: A new framework for yield curve, output and inflation relationships This article develops a theoretically-consistent and easy-to-apply framework for interpreting, investigating, and monitoring the relationships between the yield curve, output, and inflation. The framework predicts that steady-state inflation plus steady-state output growth should be cointegrated with the long-maturity level of the yield curve as estimated by a arbitrage-free version of the Nelson and Siegel (1987) model, while the shape of the yield curve model from that model should correspond to the profile (that is, the timing and magnitude) of expected future inflation and output growth. These predicted relationships are confirmed empirically using 51 years of United States data. The framework may be used for monitoring expectations of inflation and output growth implied by the yield curve. It should also provide a basis for using the yield curve to value and hedge derivatives on macroeconomic data.

year: 2005-12

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