ON-ICE DETECTION, CLASSIFICATION, LOCALIZATION AND TRACKING OF ANTHROPOGENIC ACOUSTIC SOURCES WITH MACHINE LEARNING

Arctic acoustics have been of concern in recent years for the US navy. First-year ice is now the prevalent factor in ice coverage in the Arctic, which changes the previously understood acoustic properties. Due to the ice melting each year, anthropogenic sources in the Arctic region are more common: military exercises, shipping, and tourism. For the navy, it is of interest to detect, classify, localize, and track these sources to have situational awareness of these surroundings. Because the sources are on-water or on-ice, acoustic radiation propagates at a longer distance and so acoustics are the method by which the sources are detected, classified, localized, and tracked. These methods are all part of sound navigation and ranging (SONAR). This dissertation describes algorithms which will better SONAR results without modification of the sensors or the environment and the process by which to arrive to this point. The focus is to use supervised machine learning algorithms to facilitate such technological enhancements. Specifically, neural networks analyze labeled experimental data from a first-year, shore-fast, shallow and narrow water environment. The experiments were conducted over the span of three years from 2019 to 2022, mostly during the months from January to March where ice formed over the Keweenaw Waterway at the Michigan Technological University. All experiments were conducted to analyze a passive acoustic source; that is, the source was non-cooperative and did not send any localizing pings for active SONAR. The experiments were recorded using an underwater pa-type acoustic vector sensor (AVS). The data and analysis were done intermittently to update any upcoming experiments with discrepancies found in the analysis to create a more generalized algorithm. The work in this dissertation focuses on two topics for passive SONAR: localization and classification. Because of the ``black box nature in machine learning, tracking the target source is an extension of localization and thought of as the same goal within machine learning. To introduce and verify the complexity of the testing environment, an underwater acoustic simulation is shown with Ray tracing and bathymetry data to compare with the experimental results used in machine learning. The focus of the algorithms is to produce the best results for the experiments and compare the results with traditional methods, such as a simulation or a linear Gaussian localization with a Kalman filter. Experiments studying neural network types have shown that the Vision Transformer (ViT) produces excellent results. The ViT is capable of analyzing acoustic intensity azimuthal spectrogram (azigram) data and localizing a moving target at high accuracy, and the ViT is capable of classifying multiple acoustic sources with the acoustic intensity magnitude spectrogram at high accuracy as well

Indigenous environmental justice and sustainability

A distinct formulation of Indigenous environmental justice (IEJ) is required in order to address the challenges of the ecological crisis as well the various forms of violence and injustices experienced specifically by Indigenous peoples. A distinct IEJ formulation must ground its foundations in Indigenous philosophies, ontologies, and epistemologies in order to reflect Indigenous conceptions of what constitutes justice. This approach calls into question the legitimacy and applicability of global and nationstate political and legal mechanisms, as these same states and international governing bodies continue to fail Indigenous peoples around the world. Not only do current global, national and local systems of governance and law fail Indigenous peoples, they fail all life. Indigenous peoples over the decades have presented a distinct diagnosis of the planetary ecological crisis evidenced in the observations shared as part of Indigenous environmental declarations

How Multinational Corporations Use Information Technology to Manage Global Operations

Despite a generally-acknowledged importance of information technology (IT) in enabling global strategy and a broad understanding of the manner in which IT enhances coordination and reduces cost, few studies have focused precisely on how multinational corporations (MNCs) use IT to facilitate globalization. To address this gap in the literature, we conduct a case study across four large MNCs, and use primary data to develop theoretical propositions on the characteristics of products, processes and customers that impact the ways in which MNCs use IT to manage their global operations

Burning Surface Temperature Measurements of Propellants and Explosives using Phosphor Thermography

Temperature measurements of propellants and explosives are necessary to create accurate models which lead to better understanding of energetic characteristics such as burning rate. Previous attempts at measuring surface temperatures of burning propellants and explosives using thermocouples have suffered from large uncertainty. Thermographic phosphor thermography employs ceramic powders called phosphors whose spectroscopic properties can be used to remotely and nearly non-intrusively measure temperature. Improved methods were developed for application of this technique to energetic materials to yield more accurate, two-dimensional temperature measurements. In this study, zinc oxide doped with gallium, a thermographic phosphor, was mixed into HMX and RDX powder, two propellant ingredients. These were excited by a laser while burning, and the resulting luminescence was captured by a high-speed camera. The ratio of the intensity of the luminescence at two wavelength bands was measured, and the corresponding temperature dependence was used to determine the surface temperature of the burning materials based on prior calibrations. High precision has been achieved, although further experiments must be performed to validate the accuracy of the data. Methods have been developed to achieve high resolution and more optimal signal strength for this application of phosphor thermography. The experimental data may lead to more accurate accepted values for reacting surface temperatures and improved modeling of these energetic materials

Through-Ice Acoustic Source Tracking Using Vision Transformers with Ordinal Classification

Ice environments pose challenges for conventional underwater acoustic localization techniques due to theirmultipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Vision Transformers (ViTs), for passive localization and tracking of single moving, on-ice acoustic sources using two underwater acoustic vector sensors. We incorporate ordinal classification as a localization approach and compare the results with other standard methods. We conduct experiments passively recording the acoustic signature of an anthropogenic source on the ice and analyze these data. The results demonstrate that Vision Transformers are a strong contender for tracking moving acoustic sources on ice. Additionally, we show that classification as a localization technique can outperform regression for networks more suited for classification, such as the CNN and ViTs

Digital Transformation of Global Business Processes: The Role of Dual Embeddedness

While much existing research on MNC digital transformation has followed a linear design and implementation logic using cross-sectional data, the multiple and divergent needs of headquarters (HQ) and subsidiaries suggest that MNC digital transformation actually involves a more iterative journey. In this paper, we apply the theoretical perspective of embeddedness to better define the complexities of MNC digital transformation, and identify how HQ and subsidiaries can navigate the complexities. This paper presents a longitudinal multi-case study of five Forbes Global 2000 firms that are HQ in Europe with large subsidiaries in the U.S. We find that the process of digital transformation is significantly influenced by internal embeddedness (relationship of HQ with subsidiaries and across subsidiaries) and external embeddedness (relationship of subsidiaries with their local markets), and also by strategy, financial and technology considerations. While HQ and subsidiaries have different perspectives, an understanding of these influences can help HQ and subsidiaries navigate digital transformation

A Model to Support IT Infrastructure Planning and the Allocation of IT Governance Authority

Information technology (IT) requires a significant investment, involving up to 10.5% of revenue for some firms. Managers responsible for aligning IT investments with their firm\u27s strategy seek to minimize technology costs, while ensuring that the IT infrastructure can accommodate increasing utilization, new software applications, and modifications to existing software applications. It becomes more challenging to align IT infrastructure and IT investments with firm strategy when firms operate in multiple geographic markets, because the firm faces different competitive positions and unique challenges in each market. We discussed these challenges with IT executives at four Forbes Global 2000 firms headquartered in Northern Europe. We build on interviews with these executives to develop a discrete-time, finite-horizon Markov decision model to identify the most economically-beneficial IT infrastructure configuration from a set of alternatives. While more flexibility is always better (all else equal) and lower cost is always better (all else equal), our model helps firms evaluate the tradeoff between flexibility and cost given their business strategy and corporate structure. Our model supports firms in the decision process by incorporating their data and allowing firms to include their expectations of how future business conditions may impact the need to make IT changes. Because the model is flexible enough to accept parameters across a range of business strategies and corporate structures, the model can help inform decisions and ensure that design choices are consistent with firm strategy

Myelin water fraction estimation using small- tip fast recovery MRI

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155960/1/mrm28259.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155960/2/mrm28259-sup-0001-Supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155960/3/mrm28259_am.pd

Exploring Adaptation and Fidelity in Parenting Program Implementation: Implications for Practice With Families

The vast majority of evidence-based programs (EBPs) for parenting are manualized and, as evaluated in research settings, have been implemented with a high degree of fidelity. In the real world, providers make changes to evidence-based programs they deliver, including combining programs and modifying materials to meet client needs. Additional research on adaptation of EBPs delivered in natural settings is needed to understand the nature of and reasons for adaptation in program delivery. Moore, Bumbarger, & Cooper (2013) proposed a taxonomy for categorizing adaptations based on fit, timing, and valence. In order to examine the utility of this taxonomy, a qualitative study was conducted with parenting education practitioners to better understand the adaptation options and motivations facing practitioners. Semi-structured interviews were conducted with program coordinators from three community providers in a Southeastern U.S. state. Interviews were followed by an in-person focus groups with program coordinators and participants. Questions were adapted from Moore et al. to explore fit, timing, and valence. A new dimension, autonomy, was added to explore the degree to which the provider can freely make changes to the program or is constrained by external ecological influences. Qualitative responses were coded by two members of the research team across the four domains. Internal validity was assessed by a third team member coding a sample of the team’s coding for comparison. Implications for use of the Moore et al. taxonomy in natural settings are discussed, including implications for community providers in multicultural settings and who are facing real-world external pressures