Wildlife management by habitat units: A preliminary plan of action

Procedures for yielding vegetation type maps were developed using LANDSAT data and a computer assisted classification analysis (LARSYS) to assist in managing populations of wildlife species by defined area units. Ground cover in Travis County, Texas was classified on two occasions using a modified version of the unsupervised approach to classification. The first classification produced a total of 17 classes. Examination revealed that further grouping was justified. A second analysis produced 10 classes which were displayed on printouts which were later color-coded. The final classification was 82 percent accurate. While the classification map appeared to satisfactorily depict the existing vegetation, two classes were determined to contain significant error. The major sources of error could have been eliminated by stratifying cluster sites more closely among previously mapped soil associations that are identified with particular plant associations and by precisely defining class nomenclature using established criteria early in the analysis

Design of a three-phase, 15-kilovolt-ampere static inverter for motor-starting a Brayton space power system

The design of a three-phase, 400-Hz, 15-kVA static inverter for motor-starting the 2- to 15-kWe Brayton electrical space power system is described. The inverter operates from a nominal 56-V dc source to provide a 28-V, rms, quasi-square-wave output. The inverter is capable of supplying a 200-A peak current. Integrated circuitry is used to generate the three-phase, 400-Hz reference signals. Performance data for a drive stage that improves switching speed and provides efficient operation over a range of output current and drive supply voltage are presented. A transformerless, transistor output stage is used

Moose abundance estimation using finite population block kriging on Togiak National Wildlife Refuge, Alaska

Master's Project (M.S.) University of Alaska Fairbanks, 2016Monitoring the size and demographic characteristics of animal populations is fundamental to the fields of wildlife ecology and wildlife management. A diverse suite of population monitoring methods have been developed and employed during the past century, but challenges in obtaining rigorous population estimates remain. I used simulation to address survey design issues for monitoring a moose population at Togiak National Wildlife Refuge in southwestern Alaska using finite population block kriging. In the first chapter, I compared the bias in the Geospatial Population Estimator (GSPE; which uses finite population block kriging to estimate animal abundance) between two survey unit configurations. After finding that substantial bias was induced through the use of the historic survey unit configuration, I concluded that the ’’standard” unit configuration was preferable because it allowed unbiased estimation. In the second chapter, I examined the effect of sampling intensity on performance of the GSPE. I concluded that bias and confidence interval coverage were unaffected by sampling intensity, whereas the coefficient of variation (CV) and root mean squared error (RMSE) decreased with increasing sampling intensity. In the final chapter, I examined the effect of spatial clustering by moose on model performance. Highly clustered moose distributions induced a small amount of positive bias, confidence interval coverage lower than the nominal rate, higher CV, and higher RMSE. Some of these issues were ameliorated by increasing sampling intensity, but if highly clustered distributions of moose are expected, then substantially greater sampling intensities than those examined here may be required

Performance of a new generation of acoustic current meters

Author Posting. © American Meteorological Society, 2007. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 37 (2007): 148–161, doi:10.1175/JPO3003.1.As part of a program aimed at developing a long-duration, subsurface mooring, known as Ultramoor, several modern acoustic current meters were tested. The instruments with which the authors have the most experience are the Aanderaa RCM11 and the Nortek Aquadopp, which measure currents using the Doppler shift of backscattered acoustic signals, and the Falmouth Scientific ACM, which measures changes in travel time of acoustic signals between pairs of transducers. Some results from the Doppler-based Sontek Argonaut and the travel-time-based Nobska MAVS are also reported. This paper concentrates on the fidelity of the speed measurement but also presents some results related to the accuracy of the direction measurement. Two procedures were used to compare the instruments. In one, different instruments were placed close to one another on three different deep-ocean moorings. These tests showed that the RCM11 measures consistently lower speeds than either a vector averaging current meter or a vector measuring current meter, both more traditional instruments with mechanical velocity sensors. The Aquadopp in use at the time, but since updated to address accuracy problems in low scattering environments, was biased high. A second means of testing involved comparing the appropriate velocity component of each instrument with the rate of change of pressure when they were lowered from a ship. Results from this procedure revealed no depth dependence or measurable bias in the RCM11 data, but did show biases in both the Aquadopp and Argonaut Doppler-based instruments that resulted from low signal-to-noise ratios in the clear, low scattering conditions beneath the thermocline. Improvements in the design of the latest Aquadopp have reduced this bias to a level that is not significant.This material is based upon work supported by the National Science Foundation under Grant 9810641

Robust, automated sleep scoring by a compact neural network with distributional shift correction.

Studying the biology of sleep requires the accurate assessment of the state of experimental subjects, and manual analysis of relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram and electromyogram data has shown great promise as a sleep scoring method, approaching the limits of inter-rater reliability. As with any machine learning algorithm, the inputs to a sleep scoring classifier are typically standardized in order to remove distributional shift caused by variability in the signal collection process. However, in scientific data, experimental manipulations introduce variability that should not be removed. For example, in sleep scoring, the fraction of time spent in each arousal state can vary between control and experimental subjects. We introduce a standardization method, mixture z-scoring, that preserves this crucial form of distributional shift. Using both a simulated experiment and mouse in vivo data, we demonstrate that a common standardization method used by state-of-the-art sleep scoring algorithms introduces systematic bias, but that mixture z-scoring does not. We present a free, open-source user interface that uses a compact neural network and mixture z-scoring to allow for rapid sleep scoring with accuracy that compares well to contemporary methods. This work provides a set of computational tools for the robust automation of sleep scoring

LOX/GOX mechanical impact tester assessment

The performances of three existing high pressure oxygen mechanical impact test systems were tested at two different test sites. The systems from one test site were fabricated from the same design drawing, whereas the system tested at the other site was of different design. Energy delivered to the test sample for each test system was evaluated and compared. Results were compared to the reaction rates obtained

Cosmic ray measurements Final report

Balloon flight measurements of cosmic gamma radiation above 50 MeV in Northern Hemispher

Observations of the Gas Reservoir around a Star Forming Galaxy in the Early Universe

We present a high signal-to-noise spectrum of a bright galaxy at z = 4.9 in 14 h of integration on VLT FORS2. This galaxy is extremely bright, i_850 = 23.10 +/- 0.01, and is strongly-lensed by the foreground massive galaxy cluster Abell 1689 (z=0.18). Stellar continuum is seen longward of the Ly-alpha emission line at ~7100 \AA, while intergalactic H I produces strong absorption shortward of Ly-alpha. Two transmission spikes at ~6800 Angstroms (A) and ~7040 A are also visible, along with other structures at shorter wavelengths. Although fainter than a QSO, the absence of a strong central ultraviolet flux source in this star forming galaxy enables a measurement of the H I flux transmission in the intergalactic medium (IGM) in the vicinity of a high redshift object. We find that the effective H I optical depth of the IGM is remarkably high within a large 14 Mpc (physical) region surrounding the galaxy compared to that seen towards QSOs at similar redshifts. Evidently, this high-redshift galaxy is located in a region of space where the amount of H I is much larger than that seen at similar epochs in the diffuse IGM. We argue that observations of high-redshift galaxies like this one provide unique insights on the nascent stages of baryonic large-scale structures that evolve into the filamentary cosmic web of galaxies and clusters of galaxies observed in the present universe.Comment: Accepted for publication in ApJL (corrected typos