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Item More than Money: Recruiting and Retaining Library IT Staff(Library and Information Technology Association, 2015-11-14) Crum, Janet; Dobbs, Aaron; Helman, William; Sattler, KellyPower Point presentation delivered to the 2015 LITA Forum providing an overview of preliminary survey results on the topic of recruitment and retention of library information technology staff in the United States and Canada. Survey data includes responses from staff in public, academic, school and library consortium settings.Item Piloting PDA with ebrary: Initiation, cataloging, and acquisition(2013-10-29) Gilbert, Mary; Davis, Rick; Blake, WhitneySummarizes the Albert S. Cook Library's experience with implementing and maintaining its first collection of electronic books (ebooks) under a patron-driven acquisition model. The vendor used for this pilot project was ebrary, Inc.Item Publishing Connect Event on Publishing Ethics(2011-10-18)Item Recruiting and Retaining Library IT People - What We Learned(2016-10-25) Dobbs, Aaron; Helman, William; Sattler, Kelly; White, ErinPower Point presentation delivered to the 2016 edUi Conference, a program of the Virginia Foundation for the Humanities, providing analysis of survey results on the topic of recruitment and retention of library information technology staff in the United States and Canada. Presentation focuses on the factors that influenced respondents decisions to accept, as well as to stay or leave, their current position. Session concludes with advice for hiring managers and supervisors on attracting and maintaining a diverse library IT workforce.Item Statistical Unigram Analysis for Source Code RepositoryXu, Weifeng; Xu, Dianxiang; Ariss, Omar El; Liu, Yunkai; Alatawi, Abdularaham; School of Criminal Justice; Computer ScienceUnigram is a fundamental element of n-gram in natural language processing. However, unigrams collected from a natural language corpus are unsuitable for solving problems in the domain of computer programming languages. In this paper, we analyze the properties of unigrams collected from an ultra-large source code repository. Specifically, we have collected 1.01 billion unigrams from 0.7 million open source projects hosted at GitHub.com. By analyzing these unigrams, we have discovered statistical patterns regarding (1) how developers name variables, methods, and classes, and (2) how developers choose abbreviations. Our study describes a probabilistic model for solving a well-known problem in source code analysis: how to expand a given abbreviation to its original indented word. It shows that the unigrams collected from source code repositories are essential resources to solving the domain specific problems.