Supporting Big Data Research at Case Western Reserve University

This report is an investigation of the research practices of faculty and research staff who utilize or support data science or big data methodologies at Case Western Reserve University (CWRU). The study was conducted by librarians and library staff within the Kelvin Smith Library (KSL) in collaboration with staff within CWRU University Technology ([U]tech), and was part of national selection of parallel studies occurring at public and private academic institutions throughout North America

Introduction to TEI mark-up (Workshop)

Confronted with a plain text transcription, a computer will know little about either that text\u27s structure (e.g., where pages start and end, or the boundaries of paragraphs are) or about more nuanced content (e.g., who added the interlinear glosses to a manuscript, how abbreviations ought to be expanded, or sources of intertextual references). TEI-XML, generally called just TEI, is an XML-based language for modeling documents and text. Encoding in TEI is the process of adding code to transcribed text to add structure and content while making those texts accessible and manipulable via computer. TEI was originally designed to help scholars describe what they know about a source text in a way that is computationally tractable. Since then, the language has expanded to let scholars describe many more material and conceptual artifacts in a robust and systematic way. Using a few real-world examples, this informational [workshop] will provide a brief introduction to TEI mark-up and it\u27s value as a scholarly and pedagogical tool. About Presenter Lee Zickel Humanities and Social Sciences Technologist Research Computing and Cyberinfrastructure Information Technology Services Doctoral Candidate in Design and Innovation Weatherhead School of Business Management Case Western Reserve Universit

Introduction to TEI mark-up (Workshop)

Confronted with a plain text transcription, a computer will know little about either that text\u27s structure (e.g., where pages start and end, or the boundaries of paragraphs are) or about more nuanced content (e.g., who added the interlinear glosses to a manuscript, how abbreviations ought to be expanded, or sources of intertextual references). TEI-XML, generally called just TEI, is an XML-based language for modeling documents and text. Encoding in TEI is the process of adding code to transcribed text to add structure and content while making those texts accessible and manipulable via computer. TEI was originally designed to help scholars describe what they know about a source text in a way that is computationally tractable. Since then, the language has expanded to let scholars describe many more material and conceptual artifacts in a robust and systematic way. Using a few real-world examples, this informational [workshop] will provide a brief introduction to TEI mark-up and it\u27s value as a scholarly and pedagogical tool. About Presenter Lee Zickel Humanities and Social Sciences Technologist Research Computing and Cyberinfrastructure Information Technology Services Doctoral Candidate in Design and Innovation Weatherhead School of Business Management Case Western Reserve Universit

First Test Project

Testing the interface of OS

Autocorrelation standard deviation and root mean square frequency analysis of polymer electrolyte membrane fuel cell to monitor for hydrogen and air undersupply

Proton exchange membrane fuel cells are a promising energy conversion device which can help to solve urgent environmental and economic problems. Among the various types of fuel cells, the air breathing proton exchange membrane fuel cell, which minimizes the balance of plant, has drawn a lot of attention due to its superior energy density. In this study a compact, air breathing, proton exchange membrane fuel cell based on Nafion and a Pt/C membrane electrode assembly was designed. The fuel cell was tested using a Scribner Associates 850e fuel cell test station. Specifically, the hydrogen fuel and oxygen starvation of the fuel cell were accurately and systematically tested and analyzed using a frequency analysis method which can analyze the input and output frequency. The analysis of the frequency variation under a fuel starvation condition was done using RMSF (root mean square frequency) and ACSD (autocorrelation standard deviation). The study reveals two significant results: first, the fuel starvations show entirely different phenomenon in both RMSF and ACSD and second, the results of the Autocorrelation show clearer results for fuel starvation detection than the results with RMSF. © 2015 Elsevier B.V. All rights reserved.