Translating HOL to Dedukti

Dedukti is a logical framework based on the lambda-Pi-calculus modulo rewriting, which extends the lambda-Pi-calculus with rewrite rules. In this paper, we show how to translate the proofs of a family of HOL proof assistants to Dedukti. The translation preserves binding, typing, and reduction. We implemented this translation in an automated tool and used it to successfully translate the OpenTheory standard library.Comment: In Proceedings PxTP 2015, arXiv:1507.0837

Crisis Event Extraction Service (CREES) - Automatic Detection and Classification of Crisis-related Content on Social Media

Social media posts tend to provide valuable reports during crises. However, this information can be hidden in large amounts of unrelated documents. Providing tools that automatically identify relevant posts, event types (e.g., hurricane, floods, etc.) and information categories (e.g., reports on affected individuals, donations and volunteering, etc.) in social media posts is vital for their efficient handling and consumption. We introduce the Crisis Event Extraction Service (CREES), an open-source web API that automatically classifies posts during crisis situations. The API provides annotations for crisis-related documents, event types and information categories through an easily deployable and accessible web API that can be integrated into multiple platform and tools. The annotation service is backed by Convolutional Neural Networks (CNNs) and validated against traditional machine learning models. Results show that the CNN-based API results can be relied upon when dealing with specific crises with the benefits associated with the usage word embeddings

Exploring the International Student Experience: Providing Insight through a Mixed-Methods Approach

Southern Illinois University Edwardsville (SIUE) is a Master’s level institution in the Midwest with a roughly 14,000 FTE that has been experiencing a dramatic increase in the enrollment of international students, up 30% respectively from 2014 to 2015. With the growing numbers of international students on campus, librarians sought to understand these students better and to create targeted services to meet their information needs. The researchers utilized a mixed-methods approach to explore the international student experience on campus and in the library. The methods included in-depth interviews, photo diaries, and a survey. The presenter will provide an overview of the methods and analysis, share common themes uncovered in the data, and the ways in which the data has been used to create change

Community and Thread Methods for Identifying Best Answers in Online Question Answering Communities

Much research has recently investigated the measurement of quality answers in Question Answering (Q&A) communities in the form of automatic best answer identification. Previous approaches have focused on manual user annotations and diverse features based on intuition for identifying best answers and proved relatively successful despite considering best answer identification as a general classification problem. Best answer modelling is generally distanced from community studies about what users regard as important for identifying quality content. In particular, previous research tends to only focus on the automatic aspects of best answers identification model by applying generic learning algorithms. This thesis introduces the concepts of qualitative and structural design in order to investigate if features derived from community questionnaires can enrich the understanding of best answer identification in Q&A communities and if the thread-like structure of Q&A communities can be exploited for better results. Two different approaches for exploiting the thread structure of Q&A communities are proposed and two new, previously unstudied, features are introduced. First, a measure of question complexity is introduced as a proxy measure of answerer knowledge. Second, different models of contribution effort are proposed for representing the answering reactivity of contributors. The experiments are systematically conducted on datasets issued from three different communities that vary in size, content and structure. The results show that the newly proposed features allow for better understanding of what constitute best answers. The findings also reveal that the thread-wise algorithms and optimisation techniques created from the structural design methodology correlate with best answers. In general both structural and qualitative design appear to improve best answer identification meaning that structural and qualitative methods may improve unrelated classification tasks

Linking Focusing and Resolution with Selection

Focusing and selection are techniques that shrink the proof search space for respectively sequent calculi and resolution. To bring out a link between them, we generalize them both: we introduce a sequent calculus where each occurrence of an atom can have a positive or a negative polarity; and a resolution method where each literal, whatever its sign, can be selected in input clauses. We prove the equivalence between cut-free proofs in this sequent calculus and derivations of the empty clause in that resolution method. Such a generalization is not semi-complete in general, which allows us to consider complete instances that correspond to theories of any logical strength. We present three complete instances: first, our framework allows us to show that ordinary focusing corresponds to hyperresolution and semantic resolution; the second instance is deduction modulo theory; and a new setting, not captured by any existing framework, extends deduction modulo theory with rewriting rules having several left-hand sides, which restricts even more the proof search space

The Pine Vole - Monitoring and Research Efforts

The fruit industry is an important segment of New York\u27s agricultural economy generating over 100 million dollars of farm income annually. Of the 66,740 acres of apples in the state, four counties of the lower Hudson River Valley incorporate 20,680 acres or approximately 30% of New York\u27s apple acreage

Atmospheric Transport and Diffusion Modeling of Rocket Exhaust

Space launches at Vandenberg Air Force Base (VAFB) and the Cape Canaveral Air Station (CCAS) produce exhaust from the solid rocket boosters and liquid hypergolic fuels containing several toxic substances including hydrogen chloride and hydrazine. In order to estimate the health risk that would be imposed upon the public by proposed launches, range safety officials rely on the Rocket Exhaust Effluent Diffusion Model to predict where the exhaust chemicals will go after the launch and how strong the concentrations will be. The original REEDM program averaged the meteorological parameters (wind speed, wind direction, shear, etc.) across the entire mixing level and used these averages in its Gaussian calculations to predict instantaneous concentration, dose and time weighted average concentration. This thesis modified the model program to perform its meteorological parameter averaging using only those parameters which affected source material transport in diffusion, excluding from the averaging, those parameters which did not affect the calculation. The difference in before and after modification REEDM output was statistically, significantly different for maximum centerline instantaneous concentrations and maximum centerline doses. However, the magnitude of the difference may not be considered practically significant by launch safety officials