On the Economics of Integrated Ticketing

In this paper we explore alternative pricing and regulatory strategies within a simple transport network with Cournot duopoly and differentiated demands. We show that whilst firms always prefer to offer integrated ticketing, a social planner will not. With integrated ticketing, the firms always prefer complete collusion but there is not a uniform ranking of some of the less collusive regimes. Society generally prefers the less collusive regimes to complete collusion but prefers some collusion to independent pricing

Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model

Unsupervised learning on imbalanced data is challenging because, when given imbalanced data, current model is often dominated by the major category and ignores the categories with small amount of data. We develop a latent variable model that can cope with imbalanced data by dividing the latent space into a shared space and a private space. Based on Gaussian Process Latent Variable Models, we propose a new kernel formulation that enables the separation of latent space and derives an efficient variational inference method. The performance of our model is demonstrated with an imbalanced medical image dataset.Comment: ICLR 2016 Worksho

How good are your testers? An assessment of testing ability

During our previous research conducted in the Sheffield Software Engineering Observatory [11], we found that test first programmers spent a higher percentage of their time testing than those testing after coding. However as the team allocation was based on subjects' academic records and their preference, it was unclear if they were simply better testers. Thus this paper proposes two questionnaires to assess the testing ability of subjects, in order to reveal the factors that contribute to the previous findings. Preliminary results show that the testing ability of subjects, as measured by the survey, varies based on their professional skill level

Roles and responsibilities in agile ICT for development

This paper examines the different roles in designing interactive software in a ICT for development context. Using experiences from a participatory action research project, in which we used agile methods to design and deploy an system to support ‘agricultural information flow’ for a co-operative of small farmers in rural India, we identify points of difference between the roles in standard descriptions of agile software methods and the roles as they emerged in our project. A key finding is the critical role played by a ‘Development Project Manager’ in facilitating dialogue, orchestrating the activities of other actors and in building the capabilities and confidence of all the participants in joint action

Adapting participatory and agile software methods to participatory rural development

This paper presents observations from a project that combines participatory rural development methods with participatory design techniques to support a farmers’ co-operative in Madhya Pradesh, India</p

Simple sequence repeats in zebra finch (Taeniopygia guttata) expressed sequence tags: a new resource for evolutionary genetic studies of passerines

Background Passerines (perching birds) are widely studied across many biological disciplines including ecology, population biology, neurobiology, behavioural ecology and evolutionary biology. However, understanding the molecular basis of relevant traits is hampered by the paucity of passerine genomics tools. Efforts to address this problem are underway, and the zebra finch (Taeniopygia guttata) will be the first passerine to have its genome sequenced. Here we describe a bioinformatic analysis of zebra finch expressed sequence tag (EST) Genbank entries. Results A total of 48,862 ESTs were downloaded from GenBank and assembled into contigs, representing an estimated 17,404 unique sequences. The unique sequence set contained 638 simple sequence repeats (SSRs) or microsatellites of length ≥20 bp and purity ≥90% and 144 simple sequence repeats of length ≥30 bp. A chromosomal location for the majority of SSRs was predicted by BLASTing against assembly 2.1 of the chicken genome sequence. The relative exonic location (5' untranslated region, coding region or 3' untranslated region) was predicted for 218 of the SSRs, by BLAST search against the ENSEMBL chicken peptide database. Ten loci were examined for polymorphism in two zebra finch populations and two populations of a distantly related passerine, the house sparrow Passer domesticus. Linkage was confirmed for four loci that were predicted to reside on the passerine homologue of chicken chromosome 7. Conclusion We show that SSRs are abundant within zebra finch ESTs, and that their genomic location can be predicted from sequence similarity with the assembled chicken genome sequence. We demonstrate that a useful proportion of zebra finch EST-SSRs are likely to be polymorphic, and that they can be used to build a linkage map. Finally, we show that many zebra finch EST-SSRs are likely to be useful in evolutionary genetic studies of other passerines

Managing structural uncertainty in health economic decision models: a discrepancy approach

Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for quantifying uncertainty due to inadequacies in model structure are less well developed. We introduce an example of a model that aims to predict the costs and health effects of a physical activity promoting intervention. Our goal is to develop a framework in which we can manage our uncertainty about the costs and health effects due to deficiencies in the model structure. We describe the concept of `model discrepancy': the difference between the model evaluated at its true inputs, and the true costs and health effects. We then propose a method for quantifying discrepancy based on decomposing the cost-effectiveness model into a series of sub-functions, and considering potential error at each sub-function. We use a variance based sensitivity analysis to locate important sources of discrepancy within the model in order to guide model refinement. The resulting improved model is judged to contain less structural error, and the distribution on the model output better reflects our true uncertainty about the costs and effects of the intervention

RankME: Reliable Human Ratings for Natural Language Generation

Human evaluation for natural language generation (NLG) often suffers from inconsistent user ratings. While previous research tends to attribute this problem to individual user preferences, we show that the quality of human judgements can also be improved by experimental design. We present a novel rank-based magnitude estimation method (RankME), which combines the use of continuous scales and relative assessments. We show that RankME significantly improves the reliability and consistency of human ratings compared to traditional evaluation methods. In addition, we show that it is possible to evaluate NLG systems according to multiple, distinct criteria, which is important for error analysis. Finally, we demonstrate that RankME, in combination with Bayesian estimation of system quality, is a cost-effective alternative for ranking multiple NLG systems.Comment: Accepted to NAACL 2018 (The 2018 Conference of the North American Chapter of the Association for Computational Linguistics