Comparative Case Study: Expeditionary Combat Vehicle (EFV) Amphibious Combat Vehicle (ACV)

Symposium Student Poster ShowThe failed AAAV/EFV program cost the taxpayers $3 billion from 1988 to 2011. WHY? Bona fide need to replace aging AAV EFV requirements challenges EFV reliability and testing issues Did the ACV learn from the EFV program?Approved for public release; distribution is unlimited

Automating the Boring Stuff: A Deep Learning and Computer Vision Workflow for Coral Reef Habitat Mapping

High-resolution underwater imagery provides a detailed view of coral reefs and facilitates insight into important ecological metrics concerning their health. In recent years, anthropogenic stressors, including those related to climate change, have altered the community composition of coral reef habitats around the world. Currently the most common method of quantifying the composition of these communities is through benthic quadrat surveys and image analysis. This requires manual annotation of images that is a time-consuming task that does not scale well for large studies. Patch-based image classification using Convolutional Neural Networks (CNNs) can automate this task and provide sparse labels, but they remain computationally inefficient. This work extended the idea of automatic image annotation by using Fully Convolutional Networks (FCNs) to provide dense labels through semantic segmentation. Presented here is an improved version of Multilevel Superpixel Segmentation (MSS), an existing algorithm that repurposes the sparse labels provided to an image by automatically converting them into the dense labels necessary for training a FCN. This improved implementation—Fast-MSS—is demonstrated to perform considerably faster than the original without sacrificing accuracy. To showcase the applicability to benthic ecologists, this algorithm was independently validated by converting the sparse labels provided with the Moorea Labeled Coral (MLC) dataset into dense labels using Fast-MSS. FCNs were then trained and evaluated by comparing their predictions on the test images with the corresponding ground-truth sparse labels, setting the baseline scores for the task of semantic segmentation. Lastly, this study outlined a workflow using the methods previously described in combination with Structure-from-Motion (SfM) photogrammetry to classify the individual elements that make up a 3-D reconstructed model to their respective semantic groups. The contributions of this thesis help move the field of benthic ecology towards more efficient monitoring of coral reefs through entirely automated processes by making it easier to compute the changes in community composition using 2-D benthic habitat images and 3-D models

COMPARATIVE CASE STUDY: EXPEDITIONARY FIGHTING VEHICLE AND AMPHIBIOUS COMBAT VEHICLE

The Marine Corps Expeditionary Fighting Vehicle (EFV) program cost taxpayers over $3 billion from inception to cancellation. The Amphibious Combat Vehicle (ACV) attempts to replace the Amphibious Assault Vehicle (AAV) and pick up where the EFV left off. A program comparison can be used to learn from previous management mistakes and prevent failures of this magnitude. By analyzing the two amphibious vehicle programs, I assess pertinent successes and failures against the model with available program management tools, including decision science principles. This report compares key junctures in both programs' life cycles and offers recommendations for future amphibious combat vehicle acquisition. The conclusion reveals that unbalanced cost and schedule increases overpowered the EFV performance goal, leading to cancellation. As a result, the ACV shows less performance but at a lower cost in comparison. Through research, acquisition professionals can better understand the importance of oversight, find solutions, and effectively equip themselves to manage major defense weapon systems.ARPMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

Climate and Land-Use Controls on Surface Water Diversions in the Central Valley, California

California’s Central Valley (CV) is one of the most productive agricultural regions in the world, enabled by the conjunctive use of surface water and groundwater. We investigated variations in the CV’s managed surface water diversions relative to climate variability. Using a historical record (1979−2010) of diversions from 531 sites, we found diversions are largest in the wetter Sacramento basin to the north, but most variable in the drier Tulare basin to the south. A rotated empirical orthogonal function (REOF) analysis finds 72% of the variance of diversions is captured by the first three REOFs. The leading REOF (35% of variance) exhibited strong positive loadings in the Tulare basin, and the corresponding principal component time-series (RPC1) was strongly correlated (ρ > 0.9) with contemporaneous hydrologic variability. This pattern indicates larger than average diversions in the south, with neutral or slightly less than average diversions to the north during wet years, with the opposite true for dry years. The second and third REOFs (20% and 17% of variance, respectively), were strongest in the Sacramento basin and San Francisco Bay−Delta. RPC2 and RPC3 were associated with variations in agricultural- and municipal-bound diversions, respectively. RPC2 and RPC3 were also moderately correlated with 7-year cumulative precipitation based on lagged correlation analysis, indicating that diversions in the north and central portions of the CV respond to longer-term hydrologic variations. The results illustrate a dichotomy of regimes wherein diversions in the more arid Tulare are governed by year-to-year hydrologic variability, while those in wetter northern basins reflect land-use patterns and low-frequency hydrologic variations

Probing Light Atoms at Sub-nanometer Resolution: Realization of Scanning Transmission Electron Microscope Holography

Atomic resolution imaging in transmission electron microscopy (TEM) and scanning TEM (STEM) of light elements in electron-transparent materials has long been a challenge. Biomolecular materials, for example, are rapidly altered when illuminated with electrons. These issues have driven the development of TEM and STEM techniques that enable the structural analysis of electron beam-sensitive and weakly scattering nano-materials. Here, we demonstrate such a technique, STEM holography, capable of absolute phase and amplitude object wave measurement with respect to a vacuum reference wave. We use an amplitude-dividing nanofabricated grating to prepare multiple spatially separated electron diffraction probe beams focused at the sample plane, such that one beam transmits through the specimen while the others pass through vacuum. We raster-scan the diffracted probes over the region of interest. We configure the post specimen imaging system of the microscope to diffraction mode, overlapping the probes to form an interference pattern at the detector. Using a fast-readout, direct electron detector, we record and analyze the interference fringes at each position in a 2D raster scan to reconstruct the complex transfer function of the specimen, t(x). We apply this technique to image a standard target specimen consisting of gold nanoparticles on a thin amorphous carbon substrate, and demonstrate 2.4 angstrom resolution phase images. We find that STEM holography offers higher phase-contrast of the amorphous material while maintaining Au atomic lattice resolution when compared with high angle annular dark field STEM.Comment: 9 pages, 5 figures in main text, 1 supplemental figure in the appendi

Affective flexibility as a developmental building block of cognitive reappraisal: An fMRI study

Cognitive reappraisal is a form of emotion regulation that involves reinterpreting the meaning of a stimulus, often to downregulate one’s negative affect. Reappraisal typically recruits distributed regions of prefrontal and parietal cortex to generate new appraisals and downregulate the emotional response in the amygdala. In the current study, we compared reappraisal ability in an fMRI task with affective flexibility in a sample of children and adolescents (ages 6–17, N = 76). Affective flexibility was defined as variability in valence interpretations of ambiguous (surprised) facial expressions from a second behavioral task. Results demonstrated that age and affective flexibility predicted reappraisal ability, with an interaction indicating that flexibility in children (but not adolescents) supports reappraisal success. Using a region of interest-based analysis of participants’ BOLD time courses, we also found dissociable reappraisal-related brain mechanisms that support reappraisal success and affective flexibility. Specifically, late increases in middle prefrontal cortex activity supported reappraisal success and late decreases in amygdala activity supported flexibility. Together, these results suggest that our novel measure of affective flexibility – the ability to see multiple interpretations of an ambiguous emotional cue – may represent part of the developmental building blocks of cognitive reappraisal ability

Prospectus, September 5, 2002

https://spark.parkland.edu/prospectus_2002/1020/thumbnail.jp