Classes each Wednesday evening starting October 17.

This five week workshop prepares participants to take the computer-adaptive Graduate Records Examination. The purpose of the course is to improve students' performance on the GRE by:

• Providing students with successful test management techniques
• Familiarizing students with question types specific to the GRE
• Teaching the logical, rhetorical, and mathematical problem-solving techniques relevant to the GRE
• Teaching essential grammatical and mathematical concepts and techniques in application to real test problems
• Identifying the specific problems posed by the GRE, and analyzing common test-taking errors
• Improving performance and reducing test anxiety through practice testing

This workshop is taught by Dr. Anthony Poplawski, who has helped thousands of students perform better on their GRE examinations. While this workshop provides participants with very valuable information, techniques and strategies for maximizing their potential on the GRE, please note that it does not replace studying. In addition to taking this workshop we recommend that students dedicate significant time to studying for the examination in order to be truly prepared.

Please visit the Graduate Record Examination web site at www.gre.org to view information on the GRE exam.

TO REGISTER AND LEARN MORE ABOUT THE COURSE, PLEASE VISIT:

http://www.umbc.edu/testprep/gre.html

Take advantage of early bird discounts by registering before September 26, 2012!

Come to UMBC and prepare for the types of questions included in the Law School Admissions Test. Designed to improve performance on the competitive LSAT, this intensive course focuses on:

1. Test-taking techniques
2. Time-saving methods
3. Improving logical reasoning
4. Practicing with sample tests
5. Enhancing reading comprehension
6. Reducing test anxiety

Taught by Dr. Anthony Poplawski of Spiegelberg and Associates, UMBC’s Test Preparation Courses are acclaimed for their comprehensiveness, revealing the true character of the test, their focus on maximizing scores, their intellectual seriousness, and reducing the test candidate’s test anxiety. Instruction is at the highest professional level by experienced college faculty.

Please visit The Law School Admission Council at www.lsac.org to view information on the LSAT exam.

TO REGISTER AND LEARN MORE ABOUT THE COURSE, PLEASE VISIT:

http://www.umbc.edu/testprep

We are pleased to announce that we have seven candidates for Senator positions this election season! Elections begin today and will run through Wednesday, May 2, 2012.

I encourage each of you to participate by voting during the election timeframe. The PSS is an important part of UMBC shared governance and is a representative body for you.

In order to vote, please follow these instructions:

1. Log onto the PSS myumbc groups page (http://my.umbc.edu/groups/ pss/home) and look for the documents sections. Click on the link that reads "2012 Professional Staff Senate Candidates" to open documents about each candidate. I encourage you to review information about each candidate that includes information about their UMBC service and what they feel the PSS should address next year.

2. After you have reviewed the candidate data, scroll down on the page and click on the link that reads "Vote Here". This will take you to Blackboard where you will select Professional Staff Senate in your list of "My Organizations". Then, on the left hand side, you will see a link to "PSS Elections 2012-2013". Click on the link and begin the voting process.

3. You can vote for up to seven (7) senator candidates.

Thank you in advance for participating in the PSS 2012 Election! Feel free to contact me with any questions or concerns at 410-455-2037 or csauter@umbc.edu.

Carrie Sauter

Vice President, Professional Staff Senate

Student Events Board

Friday, May 4th, 2012

Hollywood Theaters

Buses start leaving the Commons Circle @ 11pm

Show starts @ 11:59pm

All Guests = $5.00

Analyzing Social Media Data
Morgan Madeira
Junior, Computer Science

Social media has increasingly become an outlet for expression for a large part of our society. Literature suggests that analyzing data from these sites can lead to improvements in areas such as health-care and search-ad targeting. Users of these sites often associate with many other users described as “friends,” even if they do not have a strong connection, or what would be described as friendship in daily life. It is valuable to determine the strength of relationships between users and to identify communities within social networks. These communities represent people with similar characteristics, which are used by applications to solve many real-world problems. For instance, it is useful to identify groups that are interested in a specific movie genre. Information about these groups can be used to target movie advertisements towards the people most interested in that genre. These types of problems have similar characteristics to identifying close friends. We have created a system to collect and analyze the data about user characteristics, while being respectful of privacy concerns. The system is composed of a front end Facebook application and a back end machine-learning based tool. The front end component gathers data about a user and their friends. The back end uses the collected data and machine-learning techniques to determine relationships between users.

To learn more about the project, check out an interview with Morgan.

Catch Morgan's poster presentation at URCAD this Wednesday, April 25 in the University Center Ballroom from 10:00 a.m. to 12:30 p.m.

Multiclass Datasets, Their Predictions, and Their Visualization
Wallace Brown and Alexander Morrow with Kevin Winner
Senior, Computer Science
Sophomore, Computer Science

Many datasets contain a wealth of information. For example, a person may be described by their race, age, gender, income, marital status, nationality, level of education, etc. By analyzing this data, we can form educated and accurate predictions about individuals. We can, for instance, determine that a person with a particular race, age, nationality, and income is likely to be a college undergraduate. Our goal is to develop ways to visualize these predictions and the uncertainty associated with the predictions. Displaying data in a scatterplot is a standard means of describing two-dimensional information. However, displaying high-dimensional data (i.e., data that includes many attributes, such as age, race, and income) is significantly more challenging.  We present a means of visualizing high-dimensional data sets and the predictive models derived from the data, using existing dimension reduction techniques and novel glyph-based displays.

To learn more about the project, check out an interview with Wallace and Alexander.

Catch Wallace and Alexander's presentation at URCAD this Wednesday, April 25 in the University Center 312 from 1:15 to 1:30 p.m.