Flexible Natural Language Generation in Multiple Contexts

We present a practical approach to Natural Language Generation (NLG) for spoken dialogue systems. The approach is based on small template fragments (mini-templates). The system’s object architecture facilitates generation of phrases across pre-defined business domains and registers, as well as into different languages. The architecture simplifies NLG in well-understood application contexts, while providing the flexibility for a developer and for the system, to vary linguistic output according to dialogue context, including any intended affective impact. Mini-templates are used with a suite of domain term objects, resulting in an NLG system (MINTGEN – MINi-Template GENerator) whose extensibility and ease of maintenance is enhanced by the sparsity of information devoted to individual domains. The system also avoids the need for specialist linguistic competence on the part of the system maintainer.

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.

Caracterização da variabilidade morfoagronômica de maracujazeiro (Passiflora cincinnata Mast.) no semi-árido brasileiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Systemic leukopenia, evaluation of laminar leukocyte infiltration and laminar lesions in horses with naturally occurring colic syndrome

The present study was aimed at identifying laminar lesions and leukocyte infiltration in hoof laminar tissue of horses with colic syndrome and its correlation with the total leukocyte count before death. Six healthy horses were used as control group (CG), and eighteen horses with lethal gastrointestinal disease were divided into two groups: leukopenic group (LG) with seven leukopenic horses, and non-leukopenic group (NLG) with 11 horses with total leukocyte count within reference range for the species. Leukocyte infiltration was examined by immunohistochemistry. Laminar lesions were observed in both LG and NLG, with no differences in severity between them. LG showed increase of the leukocyte infiltration in the hoof laminar tissue, when compared to CG and NLG. Horses with severe colic syndrome (LG and NLG) developed intense laminar lesions without clinical signs of laminitis, with increased leukocyte infiltration. However, the LG demonstrated an even higher increase of leukocyte infiltration compared to both CG and NLG.

Lateral tires characterization: testing, analytical models and applications for aeronautic purpose

The lateral characteristics of tires in terms of lateral forces as a function of sideslip angle is a focal point in the prediction of ground loads and ground handling aircraft behavior. However, tests to validate such coefficients are not mandatory to obtain Aircraft Type Certification and so they are not available for ATR tires. Anyway, some analytical values are implemented in ATR calculation codes (Flight Qualities in-house numerical code and Loads in-house numerical code). Hence, the goal of my work is to further investigate and validate lateral tires characteristics by means of: exploitation and re-parameterization of existing test on NLG tires, implementation of easy-handle model based on DFDR parameters to compute sideslip angles, application of this model to compute lateral loads on existing flight tests and incident cases, analysis of results. The last part of this work is dedicated to the preliminary study of a methodology to perform a test to retrieve lateral tire loads during ground turning with minimum requirements in terms of aircraft test instrumentation. This represents the basis for future works.

Adaptación de una herramienta de Generación de Lenguaje Natural al idioma Español

En el presente Trabajo de Fin de Máster se ha realizado un análisis sobre las técnicas y herramientas de Generación de Lenguaje Natural (GLN), así como las modificaciones a la herramienta Simple NLG para generar expresiones en el idioma Español. Dicha extensión va a permitir ampliar el grupo de personas a las cuales se les transmite la información, ya que alrededor de 540 millones de personas hablan español. Keywords - Generación de Lenguaje Natural, técnicas de GLN, herramientas de GLN, Inteligencia Artificial, análisis, SimpleNLG.---ABSTRACT---In this Master's Thesis has been performed an analysis on techniques and tools for Natural Language Generation (NLG), also the Simple NLG tool has been modified in order to generate expressions in the Spanish language. This modification will allow transmitting the information to more people; around 540 million people speak Spanish. Keywords - Natural Language Generation, NLG tools, NLG techniques, Artificial Intelligence, analysis, SimpleNLG.

The role of automated feedback in training and retaining biological recorders for citizen science

© 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Acknowledgments The authors thank H. H. Nguyen for his early development work on the BeeWatch interface; E. O'Mahony, I. Pearce, and R. Comont for identifying numerous photographed bumblebees; B. Darvill, D. Ewing, and G. Perkins for enabling our partnership with the Bumblebee Conservation Trust; and S. Blake for his investments in developing the NLG feedback. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen's Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).

Using WYSIWYM to Create an Open-ended Interface for the Semantic Grid

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Neurospora crassa transcriptomics reveals oxidative stress and plasma membrane homeostasis biology genes as key targets in response to chitosan

Chitosan is a natural polymer with antimicrobial activity. Chitosan causes plasma membrane permeabilization and induction of intracellular reactive oxygen species (ROS) in Neurospora crassa. We have determined the transcriptional profile of N. crassa to chitosan and identified the main gene targets involved in the cellular response to this compound. Global network analyses showed membrane, transport and oxidoreductase activity as key nodes affected by chitosan. Activation of oxidative metabolism indicates the importance of ROS and cell energy together with plasma membrane homeostasis in N. crassa response to chitosan. Deletion strain analysis of chitosan susceptibility pointed NCU03639 encoding a class 3 lipase, involved in plasma membrane repair by lipid replacement, and NCU04537 a MFS monosaccharide transporter related to assimilation of simple sugars, as main gene targets of chitosan. NCU10521, a glutathione S-transferase-4 involved in the generation of reducing power for scavenging intracellular ROS is also a determinant chitosan gene target. Ca2+ increased tolerance to chitosan in N. crassa. Growth of NCU10610 (fig 1 domain) and SYT1 (a synaptotagmin) deletion strains was significantly increased by Ca2+ in the presence of chitosan. Both genes play a determinant role in N. crassa membrane homeostasis. Our results are of paramount importance for developing chitosan as an antifungal.

Natural Language Generation enhances human decision-making with uncertain information.

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different informa- tion presentations for uncertain data and, for the first time, measure their effects on human decision-making. We show that the use of Natural Language Genera- tion (NLG) improves decision-making un- der uncertainty, compared to state-of-the- art graphical-based representation meth- ods. In a task-based study with 442 adults, we found that presentations using NLG lead to 24% better decision-making on av- erage than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better re- sults when presented with NLG output (an 87% increase on average compared to graphical presentations).