News & Press Releases

The second workshop in the three-part series covers working with text frames, threading text and importing text from other documents. Placing images, the Links palette, the Direct Selection tool and Text Wrap are also covered. Previous InDesign experience, or Part 1 of the Introduction class is required. This workshop will take place in the Claire T. Library, room 128. Contact Rich Legault for more information at 508-999-8799, or email RLegault@umassd.edu. Seating is limited, so please register today!

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Interested in studying abroad? Do you have a quick question about the opportunities that are available or the overall process? Stop by the International Programs Office's virtual advising session! Students will be seen on a first come, first served basis. Email intl_programs@umassd.edu for the zoom link.

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Topic: Experimental Demonstration of Sound Source Bearing Estimation at a Single Receiver Using Spectral Cues Location: Lester W. Cory Conference Room Science & Engineering Building (SENG), Room 213A Abstract: Traditionally, bearing estimation of a sound source is accomplished by exploiting relative time differences of arrival across an array of sensors. For scenarios where arrays of sensors cannot be effectively utilized due to size or cost, an alternative method for source localization must be considered. Yovel et al. [Science, 2010] discovered one such method when observing that bats steer the main response axis (MRA) of their echolocation beams askew of a target. While this strategy reduces the SNR of a received echo, it paradoxically improves the Fisher information about a target's bearing angle. This trade-off suggests there are spectral cues which improve target localization despite the lost signal power. For a single sensor with far-field frequency-dependent directivity, and a known broadband waveform of finite temporal support and sufficient SNR, it is possible to locate a sound source by the angle-dependent lowpass filtering of the signal at the receiver. Furthermore, there exists an angle which minimizes the bearing angle estimate that is near to, but not coincident with the main response angle of the receiver. This thesis presents experiments demonstrating a man-made system estimating a source's bearing from signal spectral information using a single directional sensor with frequency dependence over the bandwidth of the received signal. A linear FM chirp from a source in the far field is recorded, measuring the beampattern of the receiver. Maximum likelihood estimates (MLE) of source bearing are calculated in a Monte Carlo algorithm, comparing noise-corrupted recordings to a randomized dictionary of template recordings. Mean-squared error (MSE) is computed as a function of source angle and compared to the Cramer-Rao lower bound (CRLB). Experimental results support that the MSE is not proportional to angle-dependent SNR, rather there are local variance minima away from the receiver MRA where the received signal power is attenuated. The MSE local minima are consistent with optimal angles observed in previous studies simulating the exploitation of spectral cues on target localization [Kloepper et al., JASA-EL 2018] [Tidwell & Buck, IEEE SSPD 2019]. Advisor(s): Dr. John R. Buck, Chancellor Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth Committee Members: Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Paul J. Gendron, Associate 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. John R. Buck email at jbuck@umassd.edu Zoom Conference Link: https://umassd.zoom.us/j/91744864902 Meeting ID: 917 4486 4902 Passcode: 844492

Science & Engineering Building, Lester W. Cory Conference Room: Room 213A

Interested in studying abroad? Do you have a quick question about the opportunities that are available or the overall process? Stop by the International Programs Office (IPO)! Students will be seen on a first come, first served basis.

International Programs Office LARTS 016

Department of Fisheries Oceanography "Diverse uses for Species Distribution Models (SDMs) in New England fisheries management" Michelle Bachman Lead Fishery Analyst, NEFMC Wednesday, November 27, 2024 3pm-4pm SMAST E 101-102 and via Zoom Abstract: Species Distribution Models (SDMs) combine presence / absence or relative abundance data from fishery-independent surveys with environmental data to predict the probability of marine fish and shellfish species occurrence through space and time. Using Community Basis Function Modeling techniques (Hui et al. 2023), offshore and inshore fish survey data, and a diverse suite of environmental predictors, we are estimating distributions for New England Council and Mid-Atlantic Council managed species and other abundant species in the Northeast U.S. Shelf Ecosystem. A solid understanding of current species distributions and the factors that influence them is essential to fisheries management decision-making in an era of climate change. We envision diverse applications for model outputs that aim to improve the responsiveness and resilience of fisheries management. The initial application for these model outputs is revising essential fish habitat designation maps. The Council's essential fish habitat designations support fisheries management decisions as well as consultations on non-fishing projects that are likely to impact fish habitats, and, by extension, fishery resources and fisheries. The three climate-resilience applications are: (1) identifying considerations for designating ecosystem component species in our fishery management plans, (2) developing revisions to governance approaches to account for current vs. historic species distributions, and (3) evaluating the results of portfolio analyses that will be used to identify opportunities and gaps in our management system, for example how fishing permits are structured. This talk will briefly describe our modeling approach and share how the results will be applied to each of these four projects. Potential future updates to these SDMs will also be noted. Join the Zoom Note: Meeting passcode required, email contact below to receive To request the Zoom passcode, or for any other questions, please email Callie Rumbut at c.rumbut@umassd.edu

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Financial Aid Services wants to remind all students to file their FAFSA! Join Financial Aid Services for FAFSA Help Labs in LARTS 203 on Wednesdays and Fridays from 3-4pm for help filing your FAFSA and learning more about financial aid. Contact Mark Yanni myanni@umassd.edu

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