Aquatic Environmental Science
Students will practice the skills of an environmental scientist by investigating human impacts on rivers, streams and ponds, with focus on water chemistry, heavy metals in stream water and sediments, emerging contaminants in municipal wastewater effluents, and endocrine disruption. Field-based experiences will focus on local Boone area environmental problems that will serve as the basis for a variety of student-centered research projects. Biological topics will include aquatic population and biodiversity responses to toxins or disturbance, lab & field sampling and analytical methods, and statistical analysis of data. As a field course, students will visit sites in Boone and surrounding areas to take advantage of the large number of high quality and unique water resources. Therefore, appropriate "river shoes" (such as Keen, Teva, Chaco, etc.) and clothing that can get wet/muddy are needed. Students will also canoe sections of the New River and camp over a three-day period. Students will need to bring a sleeping bag and tent for this excursion (further information will be sent out once class assignments have been made about tents/equipment). Each student will develop a research hypothesis, collect necessary data to test this hypothesis, provide a written report of their project, and present their findings at the closing symposium.
Exploratory Data Analysis
In today's data driven society, it is a pre-requisite of those studying science and mathematics that they understand data collection, analysis and application. In this course, we will deeply examine the process by which we collect and manipulate data. Please note, this is not an introductory statistics course. Our focus will be on interpretation of data as opposed to development of statistical theory. We will explore applications of data within the context of topics including, but not limited to, statistical inference, game theory, voting theory, rank order data, data envelopment analysis as well as data applications within the social sciences. Students will explore techniques investigating both quantitative and qualitative data through experimental design and simulation. Students will work both individually and collaboratively to obtain a mastery of the topics presented. At the conclusion of the course students will either generate their own data or use available data sets to develop their own unique research project that includes producing a paper and preparing an oral presentation.
The first rockets ever built, the fire-arrows of the Chinese, were not very reliable. Many just exploded on launching! Today, rockets are much more reliable. They fly on precise courses and are capable of going fast enough to escape the gravitational pull of Earth. How is this done? We will investigate the fascinating scientific theories involved with rocketry, including physical principles such as Newton's Laws, the aerodynamic forces that operate on objects in flight (weight, lift, drag, and thrust), different propellants and various engineering concepts such as stability and optimal mass. Applying this knowledge will allow us to design, construct, and test various models to investigate the aerodynamic capabilities and challenges of rocketry. Students will complete investigations by designing, flying and refining actual model rockets. Finally, they will present their findings via a written descriptive research paper and oral presentation.
Visual & Image Processing
This course will integrate two areas of study in computer science. First, students will have the opportunity to learn about some digital image processing techniques. Explorations will include image acquisition and display, properties of the human visual system, sampling and quantization, color image representations, image enhancement, transformations, compression and restoration. Second, students will investigate the role of visualization in science, engineering, medicine, and education and will have opportunities to learn different visualization techniques that can be applied to solve problems. Emphasis will be on visualization of data, using available tools to build and understand computational models, and understanding/visualizing solutions to proposed problems. MATLAB, ImageJ, and Excel will be used extensively, but prior knowledge is not required. Students will have daily hands-on activities and will conduct an inquiry-based research project, produce a written paper and oral presentation.