Computer Engineering Commons^™

Ez-Translate, Mason D. Beattie

Honors Theses

This report describes the EZ-Translate Software that was designed and developed by Mason Beattie for the CSCI495-D1 Honors Capstone Project and Course at Coastal Carolina University. This project is built from Java and is designed for the Windows 10 operating system. While running it displays or hides a translation menu when the designated key binds are pressed. Translations supported include select phrases from English, German, and Russian. The application also provides localization support for these three languages. The overall goal of this project to provide translation services while within another application was successfully achieved. The application utilizes an open-source Java …

Hardware And Software (Ksu), Rebecca Rutherfoord, Dawn Tatum, Susan Vandeven, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li

Computer Science and Information Technology Grants Collections

This Grants Collection for Hardware and Software was created under a Round Eleven ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Evergreen: A Senior Project, Ashley Grover

Computer Engineering

No abstract provided.

Is Tech M&A Value-Additive?, Ani Deshmukh

Undergraduate Economic Review

Given rising M&A deal volume across all high-tech subsectors, the ability to measure post-acquisition performance becomes critical. Despite this growth, the relevant academic literature is severely lacking (Kohers and Kohers 2000). Using an event-study approach, I find that acquirers and targets both realize statistically significant day-0 abnormal returns (1.23% [p<0.1] and 8.1% [p<0.01], respectively). As positive stock returns signal positive growth prospects in a semi-strong efficient market, AR regressions found that firms' technological relatedness, deal financing, purchase price premiums, and the relative book to market ratio, explained most variance. Overall, high-tech transactions are value-additive for both targets and acquirers.