Summer High School Internship Program -- 2013 Project List
The Summer High School Internship Program is a collaboration between the Sonoma County Office of Education and SSU School of Science and Technology. This year's projects are in the departments of Astronomy / NASA Outreach, Biology, Computer Science, Engineering Science, Kinesiology, Mathematics & Statistics, and Physics.
Project Title: Monitoring Active Galaxies with the GLAST Optical Robotic Telescope
Faculty Mentors: Dr. Lynn Cominsky, Department of Physics and Astronomy and NASA E/PO Group; Dr. Kevin McLin, NASA E/PO Group
The NASA Education and Public Outreach program at Sonoma State operates a small observatory located in the Pepperwood Preserve in northeast Sonoma County. The observatory houses the GLAST Optical Robotic Telescope (GORT), a Celestron 14-inch remote/robotic telescope. For nearly ten years, GORT has been used to make observations in support of NASA high energy astrophysics missions, including Swift, XMM-Newton and the Fermi Gamma-ray Space Telescope (formerly GLAST). With the launch of NASA’s NuSTAR mission in June 2012, we expect the work to increase. The primary task of the observatory is to monitor active galaxies for changes in brightness. We use it to do both routine monitoring, for which we have a catalog of approximately 28 objects, and partake in coordinated observing campaigns with other observatories, both on the ground and in space. This summer we might also try to find time to observe some of the recently discovered exoplanets of the Kepler telescope.
The intern working with us would learn how to make these observations and how to use computer software to reduce and analyze the acquired data. Included in their tasks would be learning how to accurately measure stellar brightnesses and the effects of the atmosphere on such measurements. They would also become acquainted with the nature of the objects we study and the general motions of objects in the sky.
Project Title: Determining the subcellular localization of peroxiredoxin 1 using fluorescence microscopy
Faculty Mentor: Dr. Joseph Lin, Department of Biology
For this project, we plan to investigate the localization of peroxiredoxin 1 (Prdx1) in B cells. B cells are important cells of the immune system that become activated when pathogens are recognized by the B cell receptor (BCR). Following engagement of the BCR, signaling events ultimately lead to the production of hydrogen peroxide (H2O2). H2O2 has long been known to have dramatic effects on cells. At high concentrations, the oxidative damage caused by H2O2 can ultimately lead to cell death; however, more recently, it has been demonstrated that at low concentrations, H2O2 plays an important role in normal cellular signaling. Indeed, many cells generate endogenous H2O2 following receptor stimulation supporting the notion that H2O2 generation and degradation is a carefully regulated mechanism cells use to modulate their signaling pathways. One of the enzymes responsible for the degradation of H2O2 to H2O is Prdx1. The purpose of this project is to investigate the subcellular localization of Prdx1 during B cell activation.
Project Title: Machine Learning Using EEG Data
Faculty Mentor: Dr. B. Ravikumar, Departments of Computer Science and Engineering Science
The goal of this project is to generate noninvasive neurological data and use it to correlate the EEG signal to motor action and/or thought patterns of the human brain. There has been extensive work during the past decade on the use of functional MRI (fMRI) and other noninvasive brain signals (e.g. PET scan) in trying to understand the regions of the brain activated in response to cognitive input data. Machine learning techniques have been used to correlate fMRI images to neural circuit activity in the human brain. The fMRI technology is very expensive, however, and elaborate experimental setup is needed to generate fMRI data. Further, only a certified professional is allowed to operate fMRI equipment and medical approval is needed before an individual can be used as a subject for fMRI studies. Some inexpensive alternative technologies are emerging (based on EEG) that can be used for applications similar to fMRI. We are currently working with an EEG device (known as EPOC) manufactured by Emotiv that provides an interface for human computer interaction. The Emotiv EPOC uses sensors to tune into electrical signals produced by the brain. The expectation is that the EEG signal thus generated can be correlated to motor actions and expressions. The goals of this study are to (a) generate EEG data using EPOC, and (b) create computational models from the signals generated. Specifically, EEG data has been successfully used in classifying the types of sleep (REM, deep sleep etc.). We will explore this and related areas.
Project Title: Characterizing the Power Consumption of Supercomputing Applications
Faculty Mentor: Dr. Suzanne Rivoire, Department of Computer Science
The Titan supercomputer at Oak Ridge National Laboratory in Tennessee, which is the fastest computer in the world, consumes 9 megawatts of power -- as much as 9,000 typical homes -- in a space the size of a basketball court. One of the biggest challenges in supercomputing is finding ways to improve the performance of supercomputers without corresponding increases in power consumption. The goal of this project is to measure and analyze the power consumption of typical supercomputing applications with the hope of finding predictable patterns and applying this knowledge to use a supercomputer's fixed power budget more efficiently.
Project Title: End-to-End Electronic Communication System
Faculty Mentor: Dr. Ali Kujoory, Department of Engineering Science
In this project, the intern who is interested in electrical engineering will learn about electronic communication systems. It involves an end-to-end electronic communication system: how a sender can transmit a signal to a receiver over a communication channel, the major communication blocks, how these operate to manipulate the signal, how to transfer the signal over the channel, the effect of noise, and how to increase the signal-to-noise ratio as much as possible. The student will examine wire, fiber, and wireless communication channels. The project will allow the student to get hands-on experience with major electronic power supply, measurement, and test equipment such as signal generators, DC power supplies, multimeters, oscilloscopes, and protoboards, as well as electronic components such as resistors, capacitors, coils and antennas, diodes, transistors, and integrated circuits in the Engineering Science Department's Electronics Lab. The student can also learn how to troubleshoot an electronic circuit.
Project Title: Applications of Digital Signal Processing in Music
Faculty Mentor: Dr. Jack Ou, Department of Engineering Science
Digital signal processing (DSP) is a technique that is widely used in music synthesis, voice recognition, and consumer electronics. In this project, we are applying DSP techniques to analyze sound collected from a variety of sources (e.g. nature, music instruments, etc). We will use a dedicated DSP processor to implement DSP algorithms. We will learn to analyze sound and apply DSP techniques to produce special audio effects. In addition to laboratory work, the selected student will have a chance work with experts in fields outside of engineering. Preference will be given to applicants who have strong interest in music/acoustics, and strong background in physics, math and programming.
Project Title: Effects of Caffeine Intake on Muscle Fiber Recruitments, Muscle Strength, and Oxygen Consumption and Cycling Performance
Faculty Mentor: Dr. Bülent Sökmen, Department of Kinesiology
This study will examine the effects of acute caffeine intake on cycling efficiency, neuromuscular activity of the skeletal muscle, physiological (oxygen consumption) and metabolic (glucose and lactate) responses, isokinetic muscle strength, and perceptual responses during time trials following intermittent cycling in trained males and females. Using a double-blind, randomized, crossover experimental design, twelve male and female competitive cyclists will complete two experimental trials: one caffeine and one placebo, separated by at least one week. Subjects will perform 120 minutes of intermittent cycling on a stationary ergometer, alternating three min at 30% VO2max and one min at 100% VO2max prior to time to fatigue at 90% of VO2max and before and after maximal voluntary strength testing.
Project Title: Evaluating the Effectiveness of Program Visualization Tools
Faculty Mentor: Elizabeth Giuliani, Department of Mathematics and Statistics
The Online Python Tutor is an innovative tool that allows programmers to understand the internal processes of the programs they write. It is used in introductory programming classes around the world, but its benefits for student learning have never been quantified. We will continue and update a research study to understand how to use this learning tool effectively based on analysis of data from 2012-2013.
Project Title: Modeling Features of Traffic Flow at Regulated Intersections
Faculty Mentor: Dr. Martha Shott, Department of Mathematics and Statistics
The city of Cotati recently voted to prohibit the contruction of "roundabouts, traffic circles, or any other similar traffic features" anywhere within the city limits. From the perspective of optimizing traffic flow, was this a good decision? In this project, the student will learn basic elements of traffic flow modeling to examine the efficacy of roundabouts versus two traditional alternatives, signalized intersections and four-way stops. In addition to developing and implementing appropriate models (which may include either using existing traffic simulation software or creating an original code in a common computing language), we will likely collect field data to use in calibrating and validating the models we use. Measures of total traffic system delay and maximum and average queue length will be the main factors used in evaluating which traffic features are preferable. The student will have the option to present his/her findings to other members of the SSU community in the fall.
Project Title: Fabrication and Characterization of MgxZn1-xO Thin Films
Faculty Mentor: Dr. Hongtao Shi, Department of Physics and Astronomy
Due to its outstanding physical properties, MgxZn1-xO is currently considered as a promising material for the improvement of optoelectronic devices operating in the ultraviolet regime, such as light-emitting diodes and laser diodes. The emission wavelengths from these devices strongly depend on the Mg content in the alloy, which is a function of the film deposition parameters. In this project, we will use a low-temperature electrochemical approach to fabricate MgxZn1-xO thin films on transparent substrates. We will monitor how the growth temperature, electrolyte, applied voltage and current will affect the quality of the deposited films. All samples will be thoroughly characterized on campus using the facilities in the Keck Microanalysis laboratory, such as the x-ray diffractometer, scanning electron microscope with an attached energy dispersive x-ray spectrometer, and atomic force microscope. Our goal is to optimize such a synthesis process to facilitate the development of prototyped optical devices.