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Tuesday, May 23, 2023
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11:30 AM
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1:30 PM
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ELE Master of Science Thesis Defense by Ryan Ferreira
- Location: Science and Engineering Building
, 285 Old Westport Road, Dartmouth, MA
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: Performance Assessment of an Environmentally Aware Bayes Factor Monostatic Active Acoustic Detection System
Location: Science & Engineering Building (SENG), Room 212
Abstract:
The performance of a Bayes factor (BF) monostatic active acoustic detection scheme with small vertical aperture at relatively high frequencies under various refractive ocean conditions, and target body depth uncertainty scenarios for the noise limited regime is explored. The Bayes factor frames composite hypotheses via marginalization resulting in a time-varying quadratic form over the beam-delay space representation of the scattered acoustic field. The quadratic form rejects strong reverberation and noise subspaces, passing apriori highly probable target signatures at range while permitting target uncertainty in depth. The distribution of the BF under the composite null hypothesis is shown to be a superposition of weighted central chi-squared variates. The total degrees of freedom being the number of in-phase and quadrature components associated with the at-range target body subspace under depth uncertainty, a stark reduction relative to the observation space. The distribution under the composite alternative is likewise a weighted sum of non-central chi-squared variates with non-centrality parameters associated with the beam-delay target strength components at range. These distributions do not admit simple closed forms but can be well approximated in a number of ways and this thesis considers two such methods. The asymptotic method of Davies and a fast approximation based on the method of moments. The agreement of the two methods is demonstrated. From the distribution of the BF detector under null and alternative it is straightforward to summarize performance via the receiver operating characteristic (ROC) curve. The improved acoustic focusing that this environmentally aware BF provides is demonstrated. Understood features of the waveguide dispersion in beam and delay are identified and used to combine power and improve performance. A number of refractive and iso-velocity environments are considered in the noise limited regime and results demonstrate the improvement of the BF active sonar with uncertain depth with multipath combining over the case of a single fixed and known direct specular arrival.
Advisor(s): Dr. Paul J. Gendron, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Committee Members: Dr. David A. Brown, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
*For further information, please contact Dr. Paul J. Gendron at 508.999.8510 or via email at pgendron@umassd.edu
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
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1:00 PM
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3:00 PM
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BMEBT MS Thesis Defense by Kaitlyn Bernier
- Location: > See description for location
- Contact: > See Description for contact information
- Description: BMEBT MS Thesis Defense by Kaitlyn Bernier
Date: Tuesday, May 24th, 2023
Time: 1:00 pm
Location: Textiles 219
Title: The Conversion of Triacylglycerol to Biofuels Using a Recombinant Strain of Rhodococcus Opacus Containing Chitinase B
Abstract:
The search for an environmentally friendly fuel source has been a major obstacle for many years as concerns surrounding climate change increase. Utilizing biofuels could provide the solution for the production of a renewable, green energy source which would limit the effects of climate change. The ever-growing levels of food waste has led to an increased amount of shellfish waste, making it a viable resource for the production of biofuels. By utilizing the polymer chitin, found in the shells of many crustaceans, food waste can be a source of biofuels without decreasing the earth’s already limited supply of feed stock, land, and water. Chitin can be isolated from shellfish using either chemical or biological methods and can be further broken down into chitosan using deacetylation. Various enzymes including chitinases A, B, and C from the chitinase family 18 break chitin into its monomers including N-acetyl-d-glucosamine (GlcNAc) which can be utilized as a carbon source for the production of triacyclglycerols (TAG). Chitinases are broken into two families, family 18 and 19, based on their amino acid sequences. Each chitinase plays an important role in the breakdown of chitin, with Chi A degrading chitin from the reducing end, Chi B degrading chitin from the non-reducing end, and Chi C degrading more soluble chitin. The GlcNAc produced by the chitin is broken down and converted into TAGs by R. Opacus which can then be easily converted into biofuels. In this work, purified Chitin previously isolated from the shells of crustaceans will be used as a feedstock for a modified Rhodococcus Opacus (R. Opacus) strain. R. Opacus PD630 is a gram-positive soil bacterium that can accumulate up to 78% of its dry cell weight in lipids. This allows for the bacteria to accumulate large amounts of TAGs which makes it an excellent choice for the production of biofuels. Since R. Opacus does not contain the proper enzymes to breakdown chitin, this project will focus on creating a recombinant strain of R. Opacus, using an electroporation protocol that was developed along with a Gibson Assembly protocol, that will contain the specific chitinase enzyme, chitinase B (Chi B), allowing for the breakdown of chitin.
Advisor:
Dr. Laura Hanzly, Department of Bioengineering
Committee Members:
Dr. Tracie Ferreira, Department of Bioengineering
Dr. Mark Silby, Department of Biology
- Topical Areas: Faculty, Students, Graduate, Bioengineering, Civil and Environmental Engineering, College of Engineering, Computer and Information Science, Electrical and Computer Engineering, Mechanical Engineering, Physics
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Blended Teaching: Designing Meaningful Content Connections
- Location: Online
- Contact: CITS Instructional Development
- Description: An engaging two-week, fully online certification course that introduces faculty to current research and best practices for blended teaching and learning. Using their own discipline-specific course materials for activities, faculty will work independently, and collaboratively with peers from across campus, and with Instructional Designers to design and build one unit of blended instruction that can be incorporated into their course(s), to enhance student engagement and meaningful content connections. This unit of instruction will meet the Quality Blended Course Review Rubric criteria and be a model that faculty can reference and replicate as they continue to develop their upcoming blended course(s) in a myCourses site.
- Link: https://instructionaldev1.sites.umassd.edu/teaching-blended/
- Topical Areas: Training, Workshop, audience: Faculty
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9:00 AM
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11:00 AM
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ELE Master of Science Thesis Defense by Daniel J. Lopes
- Location: Science and Engineering Building
, 285 Old Westport Road, Dartmouth, MA
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: An Environmentally Informed Bayes Factor Approach for High Frequency Broadband Active Detection in Refractive Ocean Waveguides
Location: Science & Engineering Building (SENG), Room 212
Abstract:
Underwater active sonar detection systems face challenges in ocean environments due to ambient noise power levels, reverberation inherent with rough and moving boundaries and the volume scattering associated with the inhomogeneous media. In addition, ocean waveguides spread acoustic energy in angle and delay leading to images of the target body appearing at the receiver array via the set of refracted eigen rays of the waveguide. Such multipath angle and delay spread can confound conventional detection approaches. In this thesis, an axiomatic probabilistic approach, in conjunction with a ray theoretic modeling of the refractive waveguide is employed to construct an environmentally informed Bayes factor (BF) detector for monostatic active sonar operating in ocean waveguides. A Laplace approximation is employed to marginalize the composite alternative's target body depth uncertainty. Likewise, a multivariate Gaussian model suitable for high frequency reverberation allows for closed form marginalization under the composite null. It is found that the BF statistic takes the form of a time varying quadratic form that incorporates relevant waveguide information about the ocean environment as well as constraints on the target body depth. The structure of this quadratic form is illuminated and discussed and shown to be a time varying covariance test associated with the target body's angle delay response at the receiver array as a function of range. Case studies are employed on isovelocity, Pekeris, Munk, and constant gradient ocean profiles to develop and compare the time varying angle delay structure and reveal important features of the waveguide that provide the most information regarding the scattering body's presence. The key result is the BF extraction of depth invariant modes that provide significant leverage for detection.
Advisor(s): Dr. Paul J. Gendron, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Committee Members: Dr. David A. Brown, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
*For further information, please contact Dr. Paul J. Gendron at 508.999.8510 or via email at pgendron@umassd.edu
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
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2:00 PM
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4:00 PM
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ELE Master of Science Thesis Defense by Michael R. Bisbano
- Location: > See description for location
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: Active Sonar Localization with Acoustic Spiral Waves
Location: Science & Engineering Building (SENG), Room 212
Zoom Conference Link: https://umassd.zoom.us/j/97062327270-Bisbano
Abstract:
Acoustic Spiral-Wave Active Localization is a low-complexity technique for determining location of acoustic targets (see Dzikowicz et. al. 2019, JASA 146, 4821-4830), which relies on the phase difference between reference and spiral wavefront(s). The phase between the returned reference and spiral wavefronts directly encodes the target's bearing from the transmitter. Receivers can be standard omnidirectional hydrophones, as the phase difference is intrinsic in the methods used to generate the waves and completely independent of the receiver. This Spiral-Wave Active Localization technique allows comparatively small aperture receivers to resolve target bearing and range as an alternative to larger beam-steering receiver arrays, reducing hardware costs, signal processing requirements, and physical size of embedded Active Sonar Localization systems. This research presents a monostatic model of spiral detection and tracking for multiple targets in sparse noise limited environments. Trade-offs of different pulse compression waveforms and signal processing techniques applied to Spiral-Wave Active Localization will be evaluated. Simulation and experimental results from an acoustic spiral wave beacon in an underwater test tank will be presented. Results show good agreement to resolve targets in horizontal and vertical planes with a compact aperture. Work supported by ONR 321.
Co-Advisors: Dr. David A. Brown, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Paul J. Gendron, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Committee Members: Dr. Yifei Li, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
*For further information, please contact Dr. David A. Brown at 508.999.8479 or via email at dbrown@umassd.edu
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
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