Delaware State University Applied Mathematics Research Center (AMRC) was initially funded by the Department of Defense (DoD) in 2003. AMRC is designed to create a research environment where multidisciplinary groups work together to solve applied mathematics problems in military and other areas. The research center consists of faculty of Mathematics, Computer Science, Electrical Engineering, and Biotechnology, research associates, visiting professors and an administrative assistant.
The major goals are:
- to establish a permanent research base at Delaware State University which produces new knowledge and quality, publishable, peer-reviewed research relevant to DoD research goals
- to enhance participation and substantial involvement of minority graduate (M.S. and Ph.D.) and undergraduate students and faculty in Science and Mathematics research
- to provide additional training in mathematics and sciences to minority female high school students by involving them a summer program (GEMS), and therefore to prepare more minority students (especially women) in sciences and mathematics
- to foster long-term research collaboration among scientists with Army Research Laboratories, and other national government and academic institutions; and 5) to ensure long term sufficient research funding
MAIN RESEARCH AREAS
Ground Penetrating Radar Imaging
continuing to investigate our current research targets;
developing algorithms for 3-D GPR imaging; and
processing real land mine GPR data with new algorithms.
The NURBS methods of Computer geometric design in automatic representing 3D objects
NURBS is the most popular and widely used method and tool in the field of computer geometric design in representing and manipulating 3D objects. The objectives of the project are to study the following problems in reconstruction of smooth surfaces, which are:
- producing polygonal model from scattered and unstructured 3D data, and/or even from 2D data;
- mesh quadrilaterization of the polygonal model; and
- the representation of the parametric surfaces on each quadrilateral patch, and the construction of NURBS surface model.
Signal Processing in Data Mining
The ultimate goal of the proposed research is to provide advances in technology towards successful development, testing, refinement and application of intelligent, self-adaptive software systems. The approaches integrate computer vision systems, soft computing and evolutionary computational paradigms, complex adaptive software structures and robust machine learning algorithms. In addition, we aim towards practical design, development, prototyping and evaluation of a knowledge-based software system that will integrate theoretical aspects of the proposed techniques into user-friendly application equipped by advanced user interface and enhanced data base management capabilities.
The research focuses on nucleotide sequence and chromatin structure requirements for integration. We will also deal with the scientific, social, and ethical issues related to the field of Biotechnology, present the elements of biostatics and numerical methods needed for quantitative data analysis and interpretation, and provide practical experience with the use of software and databases in the investigation of problems critical to biotechnology and molecular biology to our undergraduate students.
Other Research Areas
Inverse Ill-Posed Problems, Numerical Analysis, Partial Differential Equations, Integral Equations, Wavelets and Image Analysis, Scientific Computation, and Mathematical Physics.