This dataset details the force-displacement response of porcine meniscus under tensile-fracture behavior. Samples are cut from the anterior, middle and posterior regions of the meniscus. Each specimen geometry dimension is included.
The Dataset contains raw data that indicates the start and stop time of water flowing at fixtures in the Marian Spencer Hall Cafeteria restroom during hours of operation. The data were collected as part of an effort to develop and test a novel method of measuring flow to calculate the probability that the fixture is busy (fixture p-value). The fixture p-value is one of the parameters necessary to predict peak demand in buildings for pipe sizing purposes.
There are two .csv files, a README file and a sample of the data collection template with contact information. The dataset also contains a MATLAB code written to accept data in the suggested format and estimate the fixture probability of use.
Aurek Chattopadhyay, Reagan Maddox, Glen Horton, Nan Niu, Ganesh Malla, Tanmay Bhowmik, Jianzhang Zhang, and Juha Savolainen, Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions (submitted to REFSQ 2023: https://2023.refsq.org)
Until recently, nationally representative survey data has been the primary source of information on the energy performance of buildings in the U.S., relative to their year of construction. The emergence of municipal energy benchmarking ordinances and public availability of benchmarking datasets now makes it possible to explore these relationships at the local level, and to link this data with information about a building’s historic designation status. This paper presents results from an initial statistical analysis examining the relationships between building energy use, year of construction, and historic designation status. First, municipal benchmarking data from six U.S. cities is used to examine local trends in the relationship between building age and energy performance. Second, an exploratory analysis of the energy performance of designated historic compared to non-historic buildings in New York City is presented. The methods described in this paper could be applied more widely to benchmarking datasets from other cities.
