1,444 research outputs found
Navigating the Skies: An Exploration of Stakeholder Perspectives on Rules for Orbital Traffic Coordination using Grounded Theory and Case Study Research Methodologies
This dissertation explored standards, rules, or regulations ( rules ) of orbital traffic coordination to reduce the risk of collisions in space between active space objects. The research questions explored topics associated with areas for potential implementation of rules include maneuvering capabilities, liability and insurance, zoning, right-of-way, and tracking of objects in space.
The researcher utilized an exploratory qualitative research method because of the developing field of study and a growing domain for potential regulation. The research design is a mixture of a case study for bounding and structuring the data collection and grounded theory for a rigorous and well-defined analysis approach. The primary data source is semi-structured interviews used to explore the perspectives of three stakeholder groups with a vested interest in space traffic management. The three groups are space industry, space insurance industry, and space law and policy experts. Amongst the three groups, 19 interviews were conducted.
The data were analyzed to summarize and compare the different perspectives of each group and across the groups. From the summarized perspectives, the intent was to recommend a set of rules, but participants offered few specific rules. Instead, the dissertation’s results present shared considerations across the six research questions to provide the current state of thinking across the community.
Results from this dissertation will provide valuable insight to policymakers beyond feedback generally received during comment periods associated with federal rulemaking. National space traffic management legal frameworks need to harmonize globally to optimize space transportation operations and practices. This dissertation contributes to a larger global effort to standardize and solidify rules defining interactions between space operators by capturing the perspectives of experts primarily in and concerning the United States
“The future is blurry”: The (hydro)power relations of the Muskrat Falls Project
The Canadian Muskrat Falls hydroelectric project (MFP) has presented social, political, economic and wellbeing challenges to the province of Newfoundland and Labrador for over a decade. Despite significant public discussion on the economic issues associated with MFP, the lived experience of Inuit from the affected area has received less attention. This research aims to share Inuit perspectives in Rigolet, Nunatsiavut, the community anticipated to be most affected by the project, to inform health and social responses by government and grassroots organizations. Through a sociological approach guided by Indigenous research methodologies, this research employed culturally responsive and creative methods including semi-structured interviews, surveys, and participatory photography. The research found that participants positioned the MFP within the social and historical context of a previous (1960s-70s) hydroelectric project, the Upper Churchill Falls project, which shapes their contemporary questions and concerns. Participants also associate implementation of MFP with colonialism, as they feel they have not been adequately consulted or informed, a continuation of colonial hierarchies of knowledge. Rigolet residents also expressed uncertainty about the social, cultural, and health impacts of potential methylmercury contamination and wider environmental changes the project may cause. The power relations associated with the hydroelectric project has resulted in a ‘silencing’ of concerns over time, with some participants changing their diet because of contamination concerns for traditional foods critical to local diets, cultural practices, and connections to the land. Results of this study have important implications for public health and health risk communication strategies, as traditional foods and associated land-based activities are known to benefit Inuit physical, mental, and cultural health and wellbeing. Overall, the dissertation demonstrates how the MFP fits within a settler colonial structure within Canada, especially as Indigenous communities have been and continue to be sites for resource extraction. This system of exploitation contrasts with Inuit perspectives on the role and importance of the land and environment in social life and relationships. The research makes several recommendations for improving health risk communications, including the importance of: improved health risk communication; the delivery of clear scientific data; facilitating access to traditional foods; supporting safe ice and water travel; and improved consultation and environmental assessment processes
Measuring the impact of COVID-19 on hospital care pathways
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted
Sampling-Based Exploration Strategies for Mobile Robot Autonomy
A novel, sampling-based exploration strategy is introduced for Unmanned Ground Vehicles (UGV) to efficiently map large GPS-deprived underground environments. It is compared to state-of-the-art approaches and performs on a similar level, while it is not designed for a specific robot or sensor configuration like the other approaches. The introduced exploration strategy, which is called Random-Sampling-Based Next-Best View Exploration (RNE), uses a Rapidly-exploring Random Graph (RRG) to find possible view points in an area around the robot. They are compared with a computation-efficient Sparse Ray Polling (SRP) in a voxel grid to find the next-best view for the exploration. Each node in the exploration graph built with RRG is evaluated regarding the ability of the UGV to traverse it, which is derived from an occupancy grid map. It is also used to create a topology-based graph where nodes are placed centrally to reduce the risk of collisions and increase the amount of observable space. Nodes that fall outside the local exploration area are stored in a global graph and are connected with a Traveling Salesman Problem solver to explore them later
Neural-Kalman Schemes for Non-Stationary Channel Tracking and Learning
This Thesis focuses on channel tracking in Orthogonal Frequency-Division Multiplexing (OFDM), a
widely-used method of data transmission in wireless communications, when abrupt changes occur
in the channel. In highly mobile applications, new dynamics appear that might make channel
tracking non-stationary, e.g. channels might vary with location, and location rapidly varies with
time. Simple examples might be the di erent channel dynamics a train receiver faces when it is
close to a station vs. crossing a bridge vs. entering a tunnel, or a car receiver in a route that
grows more tra c-dense. Some of these dynamics can be modelled as channel taps dying or being
reborn, and so tap birth-death detection is of the essence.
In order to improve the quality of communications, we delved into mathematical methods to
detect such abrupt changes in the channel, such as the mathematical areas of Sequential Analysis/
Abrupt Change Detection and Random Set Theory (RST), as well as the engineering advances
in Neural Network schemes. This knowledge helped us nd a solution to the problem of abrupt
change detection by informing and inspiring the creation of low-complexity implementations for
real-world channel tracking. In particular, two such novel trackers were created: the Simpli-
ed Maximum A Posteriori (SMAP) and the Neural-Network-switched Kalman Filtering (NNKF)
schemes.
The SMAP is a computationally inexpensive, threshold-based abrupt-change detector. It applies
the three following heuristics for tap birth-death detection: a) detect death if the tap gain
jumps into approximately zero (memoryless detection); b) detect death if the tap gain has slowly
converged into approximately zero (memory detection); c) detect birth if the tap gain is far from
zero.
The precise parameters for these three simple rules can be approximated with simple theoretical
derivations and then ne-tuned through extensive simulations. The status detector for each
tap using only these three computationally inexpensive threshold comparisons achieves an error
reduction matching that of a close-to-perfect path death/birth detection, as shown in simulations.
This estimator was shown to greatly reduce channel tracking error in the target Signal-to-Noise
Ratio (SNR) range at a very small computational cost, thus outperforming previously known systems.
The underlying RST framework for the SMAP was then extended to combined death/birth
and SNR detection when SNR is dynamical and may drift. We analyzed how di erent quasi-ideal
SNR detectors a ect the SMAP-enhanced Kalman tracker's performance. Simulations showed
SMAP is robust to SNR drift in simulations, although it was also shown to bene t from an accurate
SNR detection.
The core idea behind the second novel tracker, NNKFs, is similar to the SMAP, but now the tap
birth/death detection will be performed via an arti cial neuronal network (NN). Simulations show
that the proposed NNKF estimator provides extremely good performance, practically identical to a detector with 100% accuracy.
These proposed Neural-Kalman schemes can work as novel trackers for multipath channels,
since they are robust to wide variations in the probabilities of tap birth and death. Such robustness
suggests a single, low-complexity NNKF could be reusable over di erent tap indices and
communication environments.
Furthermore, a di erent kind of abrupt change was proposed and analyzed: energy shifts from
one channel tap to adjacent taps (partial tap lateral hops). This Thesis also discusses how to
model, detect and track such changes, providing a geometric justi cation for this and additional
non-stationary dynamics in vehicular situations, such as road scenarios where re ections on trucks
and vans are involved, or the visual appearance/disappearance of drone swarms. An extensive
literature review of empirically-backed abrupt-change dynamics in channel modelling/measuring
campaigns is included.
For this generalized framework of abrupt channel changes that includes partial tap lateral
hopping, a neural detector for lateral hops with large energy transfers is introduced. Simulation
results suggest the proposed NN architecture might be a feasible lateral hop detector, suitable for
integration in NNKF schemes.
Finally, the newly found understanding of abrupt changes and the interactions between Kalman
lters and neural networks is leveraged to analyze the neural consequences of abrupt changes
and brie y sketch a novel, abrupt-change-derived stochastic model for neural intelligence, extract
some neuro nancial consequences of unstereotyped abrupt dynamics, and propose a new
portfolio-building mechanism in nance: Highly Leveraged Abrupt Bets Against Failing Experts
(HLABAFEOs). Some communication-engineering-relevant topics, such as a Bayesian stochastic
stereotyper for hopping Linear Gauss-Markov (LGM) models, are discussed in the process.
The forecasting problem in the presence of expert disagreements is illustrated with a hopping
LGM model and a novel structure for a Bayesian stereotyper is introduced that might eventually
solve such problems through bio-inspired, neuroscienti cally-backed mechanisms, like dreaming
and surprise (biological Neural-Kalman). A generalized framework for abrupt changes and expert
disagreements was introduced with the novel concept of Neural-Kalman Phenomena. This Thesis
suggests mathematical (Neural-Kalman Problem Category Conjecture), neuro-evolutionary and
social reasons why Neural-Kalman Phenomena might exist and found signi cant evidence for their
existence in the areas of neuroscience and nance.
Apart from providing speci c examples, practical guidelines and historical (out)performance
for some HLABAFEO investing portfolios, this multidisciplinary research suggests that a Neural-
Kalman architecture for ever granular stereotyping providing a practical solution for continual
learning in the presence of unstereotyped abrupt dynamics would be extremely useful in communications
and other continual learning tasks.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Luis Castedo Ribas.- Secretaria: Ana García Armada.- Vocal: José Antonio Portilla Figuera
PGET Monte Carlo simulations using Serpent
Since 2017, over 100 spent nuclear fuel assemblies at the Finnish nuclear power plants have been imaged with the Passive Gamma Emission Tomography (PGET) device in preparation of the implementation of PGET in the safeguards infrastructure of the Finnish geological repository. In order to increase understanding of the PGET method and guide its further development, we have recently implemented PGET in Serpent, a widely-used neutron and photon transport Monte Carlo simulation code. We will discuss the major aspects of this implementation and illustrate the usefulness of the simulations with a few examples. The PGET device as used in the measurements (which was developed under the guidance of IAEA and is approved for safeguards inspections) was implemented in a very realistic way based on its technical drawings. The simulation produces sinograms in user-defined energy windows as well as the uncertainty on these sinograms. Tomographic images are then reconstructed using the exact same algorithm as used for the measured data. A dedicated variance reduction scheme was implemented, increasing the computational efficiency by about a factor of 30. The simulation of the PGET response at one angular measurement position for 1 billion primary photons takes a few hours on a single 40-core node. The 1-sigma uncertainty in the highest intensity sinogram pixels is about a few percent. Aiming at improving the imaging of VVER-440 assemblies, we have simulated assemblies containing one or a few missing fuel rods or having only one emitting rod (the other rods being present but not emitting) in various well-chosen places, configurations that are not accessible in practice. The single-emitting rod results show in great detail those parts of the sinogram that contain most of the information for the particular rod position. How this information might be used for obtaining better images, especially of the central region of a fuel assembly, will be discussed
A Generalized Ray Formulation For Wave-Optics Rendering
Under ray-optical light transport, the classical ray serves as a local and
linear "point query" of light's behaviour. Such point queries are useful, and
sophisticated path tracing and sampling techniques enable efficiently computing
solutions to light transport problems in complex, real-world settings and
environments. However, such formulations are firmly confined to the realm of
ray optics, while many applications of interest, in computer graphics and
computational optics, demand a more precise understanding of light. We
rigorously formulate the generalized ray, which enables local and linear point
queries of the wave-optical phase space. Furthermore, we present sample-solve:
a simple method that serves as a novel link between path tracing and
computational optics. We will show that this link enables the application of
modern path tracing techniques for wave-optical rendering, improving upon the
state-of-the-art in terms of the generality and accuracy of the formalism, ease
of application, as well as performance. Sampling using generalized rays enables
interactive rendering under rigorous wave optics, with orders-of-magnitude
faster performance compared to existing techniques.Comment: For additional information, see
https://ssteinberg.xyz/2023/03/27/rtplt
Position measurement of the superCDMS HVeV detector and implementation of an importance sampling algorithm in the superCDMS simulation software
La matière sombre est considérée comme l'un des plus grands mystères dans la cosmologie moderne. En effet, on peut dire que l’on connaît plus sur ce que la matière sombre n'est pas que sur sa vraie nature. La collaboration SuperCDMS travaille sans répit pour réussir à faire la première détection directe de la matière sombre. À cet effet, la collaboration a eu recours à plusieurs expériences et simulations à diverses échelles, pouvant aller de l'usage d'un seul détecteur semi-conducteur, jusqu'à la création d'expériences à grande échelle qui cherchent à faire cette première détection directe de la matière sombre. Dans ce texte, on verra différentes méthodes pour nous aider à mieux comprendre les erreurs systématiques liées à la position du détecteur utilisé dans le cadre des expériences IMPACT@TUNL et IMPACT@MTL, soit l'usage des simulations et de la radiologie industrielle respectivement. On verra aussi comment l'implémentation de la méthode de réduction de variance connue comme échantillonnage préférentiel, peut aider à améliorer l'exécution des simulations de l'expérience à grande échelle planifiée pour le laboratoire canadien SNOLAB. En outre, on verra comment l'échantillonnage préférentiel s'avère utile non seulement pour mieux profiter des ressources disponibles pour la collaboration, mais aussi pour avoir une meilleure compréhension des source de bruits de fond qui seront présentes à SNOLAB, tels que les signaux générés par la désintégration radioactive de divers isotopes.Dark matter is one of the biggest mysteries of modern-day cosmology. Simply put, we know much more about what it is not, rather than what it actually is. The SuperCDMS collaboration works relentlessly toward making the first direct detection of this type of matter. To this effect, multiple experiments and simulations have been performed, ranging from small-scale testing of the detectors to large-scale, long-term experiments, looking for the actual detection of dark matter. In this work, I will analyze different methods to help understand the systematic errors linked to detector position in regard to the small-scale experiments IMPACT@TUNL and IMPACT@MTL, through simulation and industrial radiography respectively. We will also see how the implementation of the variance reduction method known as importance sampling can be used to improve the simulation performance of the large-scale experiment in the Canadian laboratory SNOLAB. Additionally, we will see how this method can provide not only better management of the computing resources available to the collaboration, but also how it can be used to better the understanding of the background noises, such as the signals generated by radioactive decay of different isotopes, that will be present at SNOLAB
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