Outstanding Chapter Website Award 2006
California Polytechnic State University-San Luis Obispo ACM Student Chapter
ACM Cal Poly, SLO website: http://acm.calpoly.edu
Webmaster: Manh Do (email@example.com)
The ACM website serves as a hub of communication for the club, connecting members with each other, the community, and some of the leading companies in our industry. Members can find in one place the newest club news, information about upcoming events, and research job opportunities in their field. The site also serves as a forum for visiting companies, allowing them to inform students about their newest promotions and presentations, as well as allowing them to post job openings. Finally it allows community members to spread information about upcoming community service opportunities, such as food drives and environmental cleanup days. To accomplish these tasks, the site has two main priorities: to always keep its information fresh, and to display it in an attractive and easy to navigate fashion.
To accomplish the second goal, of being attractive and easy to navigate, a combination of Flash and Photoshop were used to provide the graphics. In addition, the main page was designed to quickly display the most important information, saving the user the trouble of having to search for it. Finally to further extend its functionality, the webpage provides a list of useful links at the top of every page allowing members to quickly navigate to sites most frequently used by Cal Poly students.
Overall the site is simple to navigate on the user’s end, allowing them to easily get the information that they came for, and simple to update on the maintainer’s end, allowing them to quickly update data with minimal effort. This is achieved by a robust and flexible layer in between the two that transforms the plain text data files that the maintainer works with, into the graphical representation that the user sees.
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Written by leading domain experts for software engineers, ACM Case Studies provide an in-depth look at how software teams overcome specific challenges by implementing new technologies, adopting new practices, or a combination of both. Often through first-hand accounts, these pieces explore what the challenges were, the tools and techniques that were used to combat them, and the solution that was achieved.
ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.