The WorkPlace distributed processing environment

Real time control problems require robust, high performance solutions. Distributed computing can offer high performance through parallelism and robustness through redundancy. Unfortunately, implementing distributed systems with these characteristics places a significant burden on the applications programmers. Goddard Code 522 has developed WorkPlace to alleviate this burden. WorkPlace is a small, portable, embeddable network interface which automates message routing, failure detection, and re-configuration in response to failures in distributed systems. This paper describes the design and use of WorkPlace, and its application in the construction of a distributed blackboard system

The Four-Day Workweek as a Policy Option for Australia

This thesis examines the Four-Day Workweek (4DW) as a policy option for Australia. Like most advanced capitalist countries, Australia has experienced little reduction in average working hours in the postwar era despite decades of cumulative productivity gains and social surveys that report a significant number of Australians would like to work fewer hours. This thesis highlights some of the reasons for this apparent anomaly as part of its focus on the nature, purpose and extent of work. The thesis draws on the diverse traditions of political economy, including Marxian, feminist, Keynesian and institutional perspectives, as well as labour history and organisation studies. In particular, the contributions of Gorz (1999) and Weeks (2011) to the literature on work futures inform the arguments developed in this thesis. The body of the thesis is divided into three parts that focus, respectively, on the theoretical, historical and institutional levels of analysis. Part I canvasses the ‘utopian’ and ‘pragmatic’ nodes of argument in relation to change in the nature and extent of work. It highlights the obstacles to change within capitalism and also the centrality of politics in attempts to circumvent these barriers. The 4DW as a policy option for Australia is situated within this general framework. Part II focuses on the empirical evidence regarding the 4DW in the US in the 1970s and during the Great Recession. Part III centres on a case study of one Australian organisation that gives the option of a 4DW to its staff. On the basis of the evidence presented in this thesis, it is argued that the 4DW could form part of a new politics of shorter hours and chosen time in Australia. It is further argued that this reform has a greater chance of lasting success if the 4DW is adopted as a goal of the trade union movement as part of an offensive agenda

A Learning Approach To Sampling Optimization: Applications in Astrodynamics

A new, novel numerical optimization algorithm is developed, tested, and used to solve difficult numerical problems from the field of astrodynamics. First, a brief review of optimization theory is presented and common numerical optimization techniques are discussed. Then, the new method, called the Learning Approach to Sampling Optimization (LA) is presented. Simple, illustrative examples are given to further emphasize the simplicity and accuracy of the LA method. Benchmark functions in lower dimensions are studied and the LA is compared, in terms of performance, to widely used methods. Three classes of problems from astrodynamics are then solved. First, the N - impulse orbit transfer and rendezvous problems are solved by using the LA optimization technique along with derived bounds that make the problem computationally feasible. This marriage between analytical and numerical methods allows an answer to be found for an order of magnitude greater number of impulses than are currently published. Next, the N -impulse work is applied to design periodic close encounters (PCE) in space. The encounters are defined as an open rendezvous, meaning that two spacecraft must be at the same position at the same time, but their velocities are not necessarily equal. The PCE work is extended to include N -impulses and other constraints, and new examples are given. Finally, a trajectory optimization problem is solved using the LA algorithm and comparing performance with other methods based on two models-with varying complexity-of the Cassini-Huygens mission to Saturn. The results show that the LA consistently outperforms commonly used numerical optimization algorithms

Causal equivalence of frames

Frames have recently become popular in the area of applied mathematics known as digital signal processing. Frames offer a level of redundancy that bases do not provide. In a sub-area of signal processing known as data recovery, redundancy has become increasingly useful; therefore, so have frames. Just as orthonormal bases are desirable for numerical computations, Parseval frames provide similar properties as orthonormal bases while maintaining a desired level of redundancy. This dissertation will begin with a basic background on frames and will proceed to encapsulate my research as partial fulfillment of the requirements for the Ph.D. degree in Mathematics at Texas A&M University. More specifically, in this dissertation we investigate an apparently new concept we term causal equivalence of frames and techniques for transforming frames into Parseval frames in a way that generalizes the Classical Gram- Schmidt process for bases. Finally, we will compare and contrast these techniques

Quasi Real-Time Autonomous Satellite Detection and Orbit Estimation

A method of near real-time detection and tracking of resident space objects (RSOs) using a convolutional neural network (CNN) and linear quadratic estimator (LQE) is proposed. Advances in machine learning architecture allow the use of low-power/cost embedded devices to perform complex classification tasks. In order to reduce the costs of tracking systems, a low-cost embedded device will be used to run a CNN detection model for RSOs in unresolved images captured by a gray-scale camera and small telescope. Detection results computed in near real-time are then passed to an LQE to compute tracking updates for the telescope mount, resulting in a fully autonomous method of optical RSO detection and tracking. Keywords: Space Domain Awareness, Neural Networks, Real-Time, Object Detection, Embedded Systems.Comment: SPIE Defense and Commercial 2023, Orlando, F

Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles is, however, still lagging behind. While conventional exact and non-exact optimal control techniques such as Dynamic Programming and Model Predictive Control have been demonstrated, they suffer from the curse of dimensionality and quickly display limitations with high system complexity and highly stochastic environment operation. This paper demonstrates that Neuroevolution associated drive cycle classification algorithms can infer optimal control strategies for any system complexity and environment, hence streamlining and speeding up the control development process. Neuroevolution also circumvents the integration of low fidelity online plant models, further avoiding prohibitive embedded computing requirements and fidelity loss. This brings the prospect of optimal control to complex multi-physics system applications. The methodology presented here covers the development of the drive cycles used to train and validate the neurocontrollers and classifiers, as well as the application of the Neuroevolution process

From Sensors to Knowledge: The Challenge of Training the Next Generation of Data Analysts

With the advent of commercial-off-the-shelf sensors for use in a variety of applications, integration with analytical software tools, and expansion of available archived datasets, there is a critical need to address the problem of transforming resultant data into comprehensible, actionable information for decision-makers through rigorous analysis. In previous research the participating authors have emphasized that users are often faced with the situation in which they are “drowning in a sea of data” but still “thirsting for knowledge”. The availability of analysis software, tools, and techniques provide opportunities for information collection of ever increasing complexity, but the need for the training of analysts to employ appropriate tools and processes to ensure accurate and applicable results has not been addressed. The purpose of this paper is to discuss the challenges and opportunities facing the training of effective analysts capable of handling a wide-range of data types in this era of dynamic tools and techniques

A review on hot-spot areas within the Cislunar region and upon the Moon surface, and methods to gather passive information from these regions

The Cislunar region is becoming a focal point of expansion over upcoming decades. Long-term Lunar infrastructure supporting Cislunar expansion must be located in key regions on the Moon\u27s surface and in space. The purpose of this research is to identify key regions of interest on and around the Moon by investigating the location of valuable resources and the destination of future missions. Once key regions are established, low-lunar orbit trajectories are analyzed to enable methods of passive information gain in identified key regions of interest. It has been found that the South Pole and Earth-sided craters are key regions on the Lunar surface in the near future. Furthermore, an analysis of low lunar orbit trajectories is completed and demonstrates a possible framework to service the South Pole region

Public toilets have reduced enteric pathogen hazards in San Francisco

Uncontained fecal wastes in cities may present exposure risks to the public. We collected discarded feces from public spaces in San Francisco, CA for analysis by RT-qPCR for a range of enteric pathogens. Out of 59 samples, we found 12 (20%) were of human origin and 47 (80%) were non-human; 30 of 59 stools were positive for ≥1 of the 35 pathogens assessed, including pathogenic E. coli, Shigella, norovirus, Cryptosporidium, and Trichuris. Using quantitative enteric pathogen estimates and data on observed fecal waste from a public reporting system, we modeled pathogens removed from the environment attributable to a recently implemented program of public toilet construction. We estimated that each new public toilet reduced the annual number of enteric pathogens released into the immediate environment (within 500 m walking distance), including 6.3 x 1012 enteropathogenic E. coli (95% CI: 4.0 x 1012–7.9 x 1012), 3.2 x 1011 enteroaggregative E. coli (95% CI: 1.3 x 1011–6.3 x 1011), and 3.2 x 108 Shigella (6.3 x 107–2.5 x 109). Improving access to public sanitation can reduce enteric pathogen hazards in cities. Interventions must also consider the hygienic disposal of animal waste to reduce microbial hazards with zoonotic infection potential