Applications of Linear Programming to Coding Theory

Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.

From Token, to Pioneer, to Crusader: Survival Strategies for Faculty of Color in PWI's

As the only person of color in your workplace you may experience feelings of isolation and hopelessness. However, it is possible to survive this situation. To do so, you must go .through an empowering developmental process. You no longer have to be a Token. Learn how you can become a Pioneer and a Crusader for social justice.

Positively Impacting the Retention Rates and Performance for Students-of-Color

This session reports on a first-year program designed to assist students-of-color in adjusting to higher education. Session participants will have the opportunity to view the overall structure of the program, including training components, academic tracking methodology, assessment and technology, enhancement programs, and additional services that S.T.A.R.S. provides.

The Importance of Affirmative Action in the 21st Century: Building Transformational Alliances with Constituencies Across the Power Structure for Scholars, Students and Staff of Color at Predominantly European American Institutions.

The purpose of this session is to reject the notion that proactive Affirmative Action strategic plans are no longer needed at predominantly European American Institutions. Data reveal an inverse relationship between creating successful strategic plans for inclusion and negative reactions from the power structure.

The Shaping of a New Identity: Continuation of the Transformation Process of People of Color on White University College Campuses Into "White" People of Color

“Our study will show how the pyramidal structure as a permanent feature of every aspect of American society continues to function in the same manner at institutions of higher learning.”

"100 CHALLENGES FACING STUDENTS OF COLOR IN THE 21st CENTURY"

"It is particularly critical to assess the impact, given the empirical data available, on institutions in California, Texas, Florida and Washington which anti-affirmative action laws and court orders have been passed/handed down."

“FAILING TO FIT: STUDENT DEVELOPMENT THEORIES AND STUDENTS OF COLOR”

Theories proposed by Chickering, Astin, Helms, Gilligan, and Perry serve as a framework for under¬standing and explaining the development of college students.