University of Pennsylvania
Center for Sensor Technologies

SUNFEST Projects Summer 1997 


    • ANALYSIS AND DESIGN OF ELECTRO-THERMAL-COMPLIANT MICRO DEVICES
    • IMPLEMENTING LEARNING ALGORITHMS FOR PATTERN RECOGNITION ON A NEUROCOMPUTER
    • STUDY TO IMPROVE FLUORESCENT DETECTION METHODS
    • A MICROLENS ARRAY TO INCREASE THE FILL FACTOR OF A CMOS CAMERA
    • LANDMARK BASED LOCALIZATION AND LANDMARK FEATURE TRACKING: METHODOLOGY AND APPLICATIONS
    • SPEECH SYNTHESIS FROM A SPECTROGRAM
    • SAM: A GRAPHICAL USER INTERFACE FOR THE ANALYSIS AND MANIPULATION OF SPECTROGRAMS
    • IMPLEMENTATION AND TESTING OF A DIGITAL CMOS CAMERA

For more detailed information click on the title below.


ANALYSIS AND DESIGN OF ELECTRO-THERMAL-COMPLIANT MICRO DEVICES


Tim Moulton (MEAM) - University of Pennsylvania
Advisor: G. K. Ananthasuresh

A computer aided design method for implementation of thermal actuation into micro-compliant mechanisms was created using Matlab. Thermal actuation on the micro scale provides high force actuation without the control problems associated with electrostatic actuators. First a finite element model was made in ANSYS and used in the design of a new building block that could be place electrically and mechanically in series with other structures. The finite element model was then written in Matlab and implemented in the design process and optimization of thermally actuated microstructures. Software was written to design chains of building blocks so that they assume a determined profile when a voltage is applied. Additional software was then written to generate the appropriate fabrication information file and finite element data for the profile.


IMPLEMENTING LEARNING ALGORITHMS FOR PATTERN RECOGNITION ON A NEUROCOMPUTER
(Work presented at the Frontiers in Education Conference, FIE '97, Pittsburgh, 1997)

Joseph Murray - (EE) University of Oklahoma

Advisors: Dr. Paul Mueller and Dr. Jan Van der Spiegel

Neural network learning algorithms were implemented for the University of Pennsylvania/Corticon NP-4 Neurocomputer. The NP-4 is a large-scale, programmable analog computer with a fully parallel architecture. The algorithms were implemented in software and include backpropagation, correlation matrix memories, and unsupervised Hebbian learning. The system was successfully tested on two real-time image processing tasks: detecting oriented edges and identifying the digits '0' through '9'. The speed, accuracy and performance in the presence of noise were measured.


STUDY TO IMPROVE FLUORESCENT DETECTION METHODS
(Work presented at the Frontiers in Education Conference, FIE '97, Pittsburgh, 1997)

Juan Carlos Sez (Chemistry) - University of Puerto Rico, Cayey
Advisor: Dr. David J. Graves (Chemical Engineering) - University of Pennsylvania

Fluorescence microscopy is rapidly becoming a powerful tool because this method allows identification with high sensitivity of specific fluorescently-labeled molecules in biological material [5]. Fluorescein is one of the fluorescent dyes most commonly coupled to biological protein probes; other examples are rhodamine and Cy5. A major problem accompanying the use of these dyes in microscopy is light-induced bleaching, apparent as fading of the emitted fluorescent light [5]. One can see in our results that anti-fade agents do not help with the fluorescein bleaching problem very much. However, we found a new dye, Cy5, that is far more resistant to the photobleaching process than fluorescein. Cy5 appears to be an excellent dye for fluorescence studies and shows very good characteristics such as resistance to photobleaching, ability to be analyzed dry and wet, available in a chemical form that can easily be attached to protein and DNA, easily measured to very low concentration (attomole level 10-18) with the CCD camera, excited by an inexpensive HeNe laser or laser diode and having a good quantum yield (> 28%). Now, many different types of analyses can be carried out in this way including rapid detection of DNA mutational events, disease analysis, forensic identifications and sequencing by hybridization.


A MICROLENS ARRAY TO INCREASE THE FILL FACTOR OF A CMOS CAMERA

Ali Husain (Electrical Engineering) University of Pennsylvania

Advisor: Dr. J. Van der Spiegel

This report describes the implementation of microlenses including design, fabrication and preliminary test results. The lenses will be used to increase the fill factor of a CMOS camera. Microlenses have been fabricated out of photoresist. The photoresist was patterned on a silicon substrate into cylinders and melted into spherical lenses. The fabrication of the lenses has several problems so far: mask patterns that do not closely approximate circles, buckling of the lens surface due to surface tension effects, and optical properties of the lenses. Future directions will include further fabrication attempts with thicker resist layers, measurement of focal lengths, monolithic fabrication of the arrays, and modeling of the lens surface.

 


LANDMARK BASED LOCALIZATION AND LANDMARK FEATURE TRACKING: METHODOLOGY AND APPLICATIONS


John A. Rieffel - Swarthmore College
Advisor: Peter L. Venetianer, GRASP Lab, U PENN


The concept of landmark-based localization as a navigational technique for robotic agents is introduced and explored. A method for overcoming the technique's limitations by locally tracking specific features of a landmark when normal landmark navigation fails is described and then implemented on a set of mobile agents in UPENN's GRASP Lab. In practice, software to track specific features of a landmark proves to be effective and promises to be a useful supplement to current landmark navigation methods.


SPEECH SYNTHESIS FROM A SPECTROGRAM

Gavin Haentjens (EE) - University of Pennsylvania

Advisors: Mr. Ahmed Abdelatty Ali, Dr. Paul Mueller, and Dr. Jan Van der Spiegel

A Matlab program was developed to quickly generate high quality speech from spectrograms with linear and nonlinear distributions of frequency channels. The program adds sine waves together to synthesize speech, but can also produce speech via cepstral analysis for spectrograms with linearly distributed frequency channels. The program also allows the user to generate spectrograms from speech samples (in .wav, .mat, or text format) and adjust the scaling of the spectrograms by specifying a frequency scale. The program is intended to be used in conjunction with a graphical interface developed by my partners that allows spectrograms to be manipulated in a vast number of ways. The highest quality speech was produced using the sine wave method on spectrograms that were scaled using the bark scale, but the cepstral method, which produced lower quality (noisier) speech, was significantly faster.


SAM: A GRAPHICAL USER INTERFACE FOR THE ANALYSIS AND MANIPULATION OF SPECTROGRAMS

O'Neil Palmer (EE) and Kelum Pinnaduwage (EE) - University of Pennsylvania

Advisors: Mr. Ahmed Abdelatty Ali, Dr. Paul Mueller, and Dr. Jan Van der Spiegel

The analysis and manipulation of a spectrogram can be very useful in the field of speech recognition. This prompted the idea of creating a user-friendly Graphical User Interface (GUI) that would enable the user to better understand speech patterns. The "Spectrogram Analyzer and Manipulator" (S.A.M.) interface, along with the "Speech Synthesis" program, can be used as a very powerful tool in this regard.


IMPLEMENTATION AND TESTING OF A DIGITAL CMOS CAMERA

Francis Chew (EE) - University of Pennsylvania

Advisor: Prof. Jan Van der Spiegel

A Complementary Metal Oxide Semiconductor (CMOS) digital camera was developed by L.P. Ang, Raymond Tong and D.J. Yoon as their senior design project - completed in May, 1997. Though preliminary testing has been done on the camera to ensure that the CMOS chip and board circuitry are working in a desirable manner, no testing was done on the sensitivity and sharpness of the camera as a complete unit/device. Improvements were made on chip-to-camera mounting, imaging/focusing and optimization of wiring methods. Viable image sensor applications are also introduced for the implementation of the CMOS digital camera.



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