INVESTIGATION OF OCEAN ACOUSTICS USING AUTONOMOUS INSTRUMENTATION TO QUANTIFY THE WATER-SEDIMENT BOUNDARY PROPERTIES

Sound propagation in shallow water is characterized by interaction with the oceans surface, volume, and bottom. In many coastal margin regions, including the Eastern U.S. continental shelf and the coastal seas of China, the bottom is composed of a depositional sandy-silty top layer. Previous measurements of narrow and broadband sound transmission at frequencies from 100 Hz to 1 kHz in these regions are consistent with waveguide calculations based on depth and frequency dependent sound speed, attenuation and density profiles. Theoretical predictions for the frequency dependence of attenuation vary from quadratic for the porous media model of M.A. Biot to linear for various competing models. Results from experiments performed under known conditions with sandy bottoms, however, have agreed with attenuation proportional to f1.84, which is slightly less than the theoretical value of f2 [Zhou and Zhang, J. Acoust. Soc. Am. 117, 2494]. This dissertation presents a reexamination of the fundamental considerations in the Biot derivation and leads to a simplification of the theory that can be coupled with site-specific, depth dependent attenuation and sound speed profiles to explain the observed frequency dependence. Long-range sound transmission measurements in a known waveguide can be used to estimate the site-specific sediment attenuation properties, but the costs and time associated with such at-sea experiments using traditional measurement techniques can be prohibitive. Here a new measurement tool consisting of an autonomous underwater vehicle and a small, low noise, towed hydrophone array was developed and used to obtain accurate long-range sound transmission measurements efficiently and cost effectively. To demonstrate this capability and to determine the modal and intrinsic attenuation characteristics, experiments were conducted in a carefully surveyed area in Nantucket Sound. A best-fit comparison between measured results and calculated results, while varying attenuation parameters, revealed the estimated power law exponent to be 1.87 between 220.5 and 1228 Hz. These results demonstrate the utility of this new cost effective and accurate measurement system. The sound transmission results, when compared with calculations based on the modified Biot theory, are shown to explain the observed frequency dependence.

Large Decrease of Fluctuations for Supercooled Water in Hydrophobic Nanoconfinement

Using Monte Carlo simulations we study a coarse­grained model of a water layer confined in a fixed disordered matrix of hydrophobic nanoparticles at different particle concentrations c. For c = 0 we find a 1st order liquid­liquid phase transition (LLPT) ending in one critical point at low pressure P. For c > 0 our simulations are consistent with a LLPT line ending in two critical points at low and high pressure. For c = 25% at high P and low temperature T we find a dramatic decrease of compressibility, thermal expansion coefficient, and specific heat. Surprisingly, the effect is present also for c as low as 2.4%. We conclude that even a small presence of nanoscopic hydrophobes can drastically suppress thermodynamic fluctuations, making the detection of the LLPT more difficult.

Meanings of the Sabbath for Worship in the Seventh-Day Adventist Church

This study investigates the meanings and significance of the seventh-day Sabbath for worship in the Seventh-day Adventist Church. In recent years, both the day and concept of Sabbath have attracted ecumenical attention, but the focus of scholarship has been placed on Sunday as the Lord's Day or Sabbath with little consideration given to the seventh-day Sabbath. In contrast, this project examines the seventh-day Sabbath and worship on that day from theological, liturgical, biblical and historical perspectives. Although not intended as an apology for Seventh-day Adventist practices, the work does strive to promote a critical and creative conversation with other theological and liturgical traditions in order to promote mutual, ecumenical understanding. Historical research into the origins and nature of the principal day for weekly Christian worship provides a starting point for discussion on Sabbath. Reconsideration of the relationship between Judaism and early Christianity in recent studies suggests that the influence of Judaism lasted longer than previously supposed, thereby prolonging the developmental process of Sabbath (seventh day) to Sunday. A possible coexistence of Sabbath and Sunday in early Christianity offers an alternative to perspectives that dichotomize Sabbath and Sunday from Christian antiquity onward, and thus for the Seventh-day Adventist Church, suggests biblical and historical validity for their Sabbath worship practice. Recent theological perspectives on Sabbath and Sunday are examined, particularly those of Karl Barth, Jürgen Moltmann and Pope John Paul II. While all three of these theologians stress the continuity of Sabbath and Sunday and speak mainly to a theology of Sunday, they do highlight the significance of Sabbath—which is relevant to an interpretation of seventh-day Sabbath worship. The study concludes that the seventh-day Sabbath is significant for worship in the Seventh-day Adventist Church because it symbolizes the relationship between God and human beings, reminds humanity of the creating and redeeming God who acts in history, and invites persons to rest and fellowship with God on a day sanctified by God.

Reliable Cellular Automata with Self-Organization

In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information for more than a constant number of steps is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software", it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary-size and content caused by the faults. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization". The latter means that unless a large amount of input information must be given, the initial configuration can be chosen to be periodical with a small period.

Inferring Body Pose without Tracking Body Parts

A novel approach for estimating articulated body posture and motion from monocular video sequences is proposed. Human pose is defined as the instantaneous two dimensional configuration (i.e., the projection onto the image plane) of a single articulated body in terms of the position of a predetermined set of joints. First, statistical segmentation of the human bodies from the background is performed and low-level visual features are found given the segmented body shape. The goal is to be able to map these, generally low level, visual features to body configurations. The system estimates different mappings, each one with a specific cluster in the visual feature space. Given a set of body motion sequences for training, unsupervised clustering is obtained via the Expectation Maximation algorithm. Then, for each of the clusters, a function is estimated to build the mapping between low-level features to 3D pose. Currently this mapping is modeled by a neural network. Given new visual features, a mapping from each cluster is performed to yield a set of possible poses. From this set, the system selects the most likely pose given the learned probability distribution and the visual feature similarity between hypothesis and input. Performance of the proposed approach is characterized using a new set of known body postures, showing promising results.