This research is an ethnographic study of literacy as a socially constructed process, literacy viewed as a part of the acquisition and transmission of culture. The focal population was a group of low SES high school students, most of whom were African American, and their children (ages 7 weeks to 4 years), several of whom were enrolled in a day care center housed within the large, urban high school their parents attended in a midwestern U.S. city. The research was an attempt to understand the kinds of literacy, specifically the types and amounts of reading and writing, that were a part of the home and school lives of the student/parents, and their parents, and a part of the home and day care lives of their children.
Many people envision the cloud as a service that “just works”. What most do not realize though, is that the “cloud” is in fact a co-location center, a building housing a massive datacenter that is willing to provide its resources to companies for an annual cost. Someone needs to maintain these co-location centers, and when searching, recruiters often look for someone with experience. Acquiring enterprise level, hands-on experience for the job can be both quite expensive and hard to come across. VR Datacenter (VDC) plans to fix this. VDC is an application that leverages users’ consumer hardware to simulate an enterprise level environment. VDC aims to allow users to create assets that not only appear physically in the virtual reality environment, but also have functionality tied into a VMWare vSphere server environment. This includes controlling device connectivity, power, rackmount location (RU), readouts from the virtual machines (VMs), etc. VDC plans to better define the breadth of knowledge that an entry level IT administrator possesses.
Submitted to the Faculty of the Information Engineering Technology Program in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Information Engineering Technology
Submitted to the Faculty of the School of Information Technology Program in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Information Technology.
VonLehman Security Auditing is a service that aims to raise cyber security awareness and help local business better understand how to secure their systems. Approximately 60% of small business close within six months of being hacked. Technology is growing at speeds that many companies are not able to correctly implement and secure. VonLehman Security Auditing will review a company using a five-step approach. Educating users and testing various aspects of a company’s security is vital to securing their systems from malicious actors. The results of these tests will be compiled into a final risk assessment report which will recommend next steps and give the client a better understanding of their vulnerabilities.
Submitted to the Faculty of the Information Engineering Technology Program in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Information Engineering Technology
Classifier algorithms use the features (collectively known as Feature Vectors) of each item in a dataset to assess the classification to which that item belongs.
In this classifier approach, each item represents one document containing the application essay combined with unstructured language describing relevant activities of a single applicant. For privacy, the full text of this document is not provided. Instead, each document is represented only by its features. The feature vector for this classifier is based on the term frequency for each of the identified terms. E.G. Doc_A contains 0 occurrences of any terms identified as family medicine vocabulary, and 10 occurrences of terms from the the non-family-medicine vocabulary.
W2V takes terms from a large corpus of text and models them onto a vector space, based on word associations from your dataset. These Word Associations take into account each word's immediate context (its ten neighboring words).
Following the data modeling (large-scale unstructured text), The platform then generates a visualization of this vector space, which lets us perform analysis e.g. detect synonymous/synonym-ish words and highlight related words. At the heart of this project, is W2V's ability to identify key words that were more frequent - and more unique - to each group using results from 2 different W2V models – one for each group's application texts.
We coded these Key Terms into categories, then analyzed those categories for overarching themes.
A viscometer for liquids of low viscosity was built to be used at temperatures up to ca. 1000°C with the liquid maintained under a vacuum or inert gas atmosphere. The viscometer follows the method first suggested by Helmholz (8) and later successfully developed by Chiong and Andrade (4). In this method, the liquid is enclosed in a sphere; and the sphere is set in rotatory oscillation about a vertical axis. From measurements of the damping of the oscillations and the period and moment of inertia of the rotating pendulum, absolute values of the viscosity are calculated using the equations derived by Chiong and Andrade (4).
