Session S1

Session S1: Sensors and DSP Education

Time:                 Monday, May 12, 10:30-12:00
Chair:                 Eduardo Perez, National Instruments Corporation
Co-Chair:          Harvey Thornburg, Arizona State University

S1-1: LabVIEW Multicore, DSP & FPGA Programming for Heterogeneous Communications, Signal & Image Processing Applications

Eduardo Pérez and Sam Shearman National Instruments Corporation, Austin TX

Modern wireless sensor, communications, signal and image processing applications are deployed in heterogeneous wireless networking environments where multicore host computers and remotely located embedded devices using DSPs and/or FPGA for intelligent processing are prevalent. Traditional text-based software development tools were not developed to quickly implement these complex applications. Working with such tools can force scientist and engineers to spend a significant amount of time creating and debugging the software infrastructure necessary to deploy their applications. This presentation discusses LabVIEW, a graphical system design environment that addresses the complexities of multicore and embedded software development allowing students, teachers, scientists and engineers to focus on the development of applications in heterogeneous environments.

S1-2: Teaching Speech Signal Processing and Coding using LabVIEW

Andreas Spanias, Jayaraman J. Thiagarajan and Karthikeyan N. Ramamurthy Arizona State University, Tempe AZ

This paper presents an educational software tool developed for teaching speech signal coding theory and algorithms with the National Instruments LabVIEW package. The framework has been built using existing MATLAB code as a library along with LabVIEW’s native functionalities. We choose to use LabVIEW because of its intuitive visual interface, ability to process real-time signals and capability to interface with DSP hardware. Standardized FS-1015 LPC, FS-1016 CELP software has been implemented. The current work focuses on developing a framework for these algorithms in LabVIEW in order to provide students with a visual understanding of the fundamental principles.

S1-3: On the Use of J-DSP in Earth Systems

Karthikeyan N. Ramamurthy, Andreas Spanias Arizona State University, Tempe AZ and Linda Hinnov Johns Hopkins University, Baltimore MD

In this paper, we describe multidisciplinary extensions to the educational online J-DSP editor that enables this system to handle Earth systems data relating to applications in geology, exploration, and environmental assessment. The new family of functions created for Earth data are bundled in our new J-DSP Earth Systems Edition. These functions allow students to experiment with different functions by taking advantage of the powerful visual programming environment of J-DSP. These new functions are being used in two different classes, namely, an exposition session for applications of DSP in electrical engineering at ASU and a computational tool session in an Earth Systems course at Johns Hopkins University.

S1-4: New Retrieval Strategies for Environmental Sounds in a Mediated Learning Environment

Gordon Wichern, Jiachen Xue, Alex Fink, Harvey Thornburg and Andreas Spanias Arizona State University, Tempe AZ

In support of the Situated Multimedia Arts Learning Laboratory (SMALLab), we are developing new technologies to explore sound as an educational tool, by enabling students to record, analyze, and construct interactive sound worlds based on their immediate sonic environment and specific learning objectives. Applications include oral retrieval of audio files for interactive storytelling and movement-sound mapping, the relation of natural and environmental sounds to acoustic ecology and environmental sustainability, and music synthesis for interactive composition. Our audio sensing system uses microphone arrays to automatically detect and record natural sound events, and tag them with location, time, and sonic characteristic information. Detected sound events are stored in a database, which stays updated in real-time, and supports standard queries along with a novel scheme for oral retrieval of audio files. Because existing audio signal processing techniques are almost exclusively tailored for speech and music applications, we have developed a unique acoustic feature set, and dynamic probabilistic models for sound segmentation and retrieval, all based on a psychoacoustic foundation. Using these audio-sensing tools, we have developed the SIRENS (Segmentation, Indexing, and Retrieval of Environmental and Natural Sounds) software package for interactive demonstration and visualization of research results.

S1-5: A Tutoring Agent For Learning With GUI-based Problems

James H. McClellan and Gregory Krudysz Georgia Institute of Technology, Atlanta GA

In this paper, we propose an interactive web-based sensing platform intended to serve as a tutoring agent for students learning via problem-solving exercises. This environment is a tool that provides feedback about a student’s understanding and then guidance on concept learning. With the overall goal of building intuition, the system acts as a reasoning agent, evaluating and advancing a student’s problem solving skills.

S1-6: Hands-On Freshman Engineering Labs Using NI LabVIEW and NI ELVIS

Lina Karam and Naji Mounsef Arizona State University, Tempe AZ

National Instruments products, including NI LabVIEW and NI ELVIS, are being used by freshmen students, who are enrolled in the Introduction to Engineering course at Arizona State University, to develop real-time analog and digital applications. The developed applications span different areas of Electrical and Computer Engineering, including analog and digital signal processing, multimedia, communications, circuits, power, controls, and robotics. In addition to getting introduced to various areas in Electrical and Computer Engineering, the students become familiar with programming concepts, instrumentation, and embedded real-time DSP technology through hands-on laboratory experiments.