Thruster Communication for Subsurface Environments; Turning Waste Noise into Useful Data

Acoustic communication serves as one of the primary means of wirelessly communicating underwater. Whereas much of the developments in the field of wireless communication have focused on radio frequency technology, water highly absorbs radio waves rendering the link not feasible for most all subsurface operations. While acoustic links have enabled new capabilities for systems operating in this challenging environment, it has yet to reach the commodity availability of radio systems, meaning that an entire class of small, low-cost systems have been unable to make use of these links. The systems in question are primarily autonomous underwater vehicles (AUVs), as they typically operate untethered as compared to remotely operated vehicles (ROVs). To address this gap in capability, a prototype system was constructed leveraging the ambient noise produced by brushless electric thrusters to transmit data. This research aims to build on this work and answer some key questions about the technology. The primary research question is how the operation of a thruster as a propulsor impacts the transmission of data. A characterization of the system will be presented, isolating the behavior of the thruster. From this, it will be shown that a thruster behaves in a manner nearly identically to a purpose-built transducer solution. From this finding, an analysis into the optimization of the link is presented, analyzing protocol improvements, inter symbol interference, and approaches to leveraging signal harmonics of the data link to increase bandwidth. From this work, a transmitter implementation was demonstrated utilizing frequency shift keying to send data at a rate of 2000 bits per second. Beyond the specifics of this work, this transmission system was demonstrated on a low-cost, open-source motor controller, enabling a system to easy integrate or enable this capability. This demonstrates that most any system can leverage this technology to add additional operational capability

Application of Neural Networks to Acoustic Localization

The intent of the work conducted was to build a neural network for the purposes of acoustic localization. The target of this localization is a sound source underwater. For our purposes, it is an acoustic pinger, as it produces consistent sound at a fixed rate making it ideal for testing. The network was intended to ingest raw data streams and output location information based on the arrangement of sensors employed. To achieve an accurate network, a simulation factoring in the environment was to be created to produce a data set large and diverse enough to describe the unique parameters of the signals, including: frequency, environmental reflections, and range. This problem will be approached in multiple steps. Initial models will consider simplified problem spaces, such as individual frequencies and less descriptive training sets. Through development, this will be refined and extended. Where required, simplifications will be kept managing the scope of the problem to allow for a demonstration of the technology to be made at all. Discussion of what is the root cause of the issue navigated will be presented when this occurs. Results will then be shown to demonstrate the performance of the network created as compared to the classical approach to this problem, time difference of arrival. This paper will demonstrate the performance of a neural network as applied to the problem of acoustic localization. The network developed can accurately localize an acoustic sound source to the same order of magnitude of accuracy and execution time as the current approaches to the problem. However, the network also showed a lacking in some areas of robustness due to training factors not considered, hampering the full potential

The construction of a unit and workbook of exercises for the slow learner to develop comprehension and increase study skills for use in the teaching of an American history unit on the westward movement in the United States on a sixth grade level.

Thesis (Ed.M.)--Boston University N.B.:pages missing: 170, 171, 173 from original cop

Gate Voltage Controllable Non-Equilibrium and Non-Ohmic Behavior in Suspended Carbon Nanotubes

In this work, we measure the electrical conductance and temperature of individual, suspended quasi-metallic single-walled carbon nanotubes under high voltage biases using Raman spectroscopy, while varying the doping conditions with an applied gate voltage. By applying a gate voltage, the high-bias conductance can be switched dramatically between linear (Ohmic) behavior and nonlinear behavior exhibiting negative differential conductance (NDC). Phonon populations are observed to be in thermal equilibrium under Ohmic conditions but switch to nonequilibrium under NDC conditions. A typical Landauer transport model assuming zero bandgap is found to be inadequate to describe the experimental data. A more detailed model is presented, which incorporates the doping dependence in order to fit this data

Description, life history, and parasitism of a new species of Delphacid Planthopper (Hemiptera: Fulgoroidea)

Delphacodes scolochloa Cronin & Wilson (Hemiptera: Fulgoroidea) is a newly discovered delphacid planthopper that feeds and oviposits exclusively on the stems of sprangletop, Scolochloa festucacea (Willd.) Link (Poaceae: Pooidae), in the prairie pothole region of northeastern North Dakota. D. scolochloa is bivoltine. It is also wing dimorphic, but populations are composed predominantly of flightless brachypters. Macropters incur a substantial cost in terms of reduced longevity and fecundity relative to brachypters. The parasitoid complex attacking D. scolochloa consists of two egg parasitoids, Anagrus nigriventris Girault and Anagrus columbi Perkins (Hymenoptera: Mymaridae), and one undescribed dryinid. The proportion of eggs parasitized averages 21%, and egg parasitization is density independent. © 2007 Entomological Society of America

Autonomous Dynamic Localization System

The Robotics Association participates in all six major Association for Unmanned Vehicle Systems International (AUVSI) sponsored collegiate competitions. One such competition is Robosub, which is a competition for an autonomous submarine to navigate a course and complete various tasks. During the course of this competition, precision localization is necessary. While various underwater navigational solutions can be purchased, they are often extremely expensive. This project, Autonomous Dynamic Localization System (ADLS), is designed to use hydrophones and cameras to achieve localization and virtual object marking. Hydrophones would be used to localize distance from a pinger based on time delay, while cameras would be used to track the movement of fixed objects through the frame. These two data sources can be combined to calculate a current position, as well as a direction vector. Experimental tests of the vision system have been conducted, and have provided promising results