Third International Symposium on Space Mission Operations and Ground Data Systems, part 2

Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The symposium papers focus on improvements in the efficiency, effectiveness, and quality of data acquisition, ground systems, and mission operations. New technology, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations. This volume covers expert systems, systems development tools and approaches, and systems engineering issues

Uncertainty Quantification in Biophotonic Imaging using Invertible Neural Networks

Owing to high stakes in the field of healthcare, medical machine learning (ML) applications have to adhere to strict safety standards. In particular, their performance needs to be robust toward volatile clinical inputs. The aim of the work presented in this thesis was to develop a framework for uncertainty handling in medical ML applications as a way to increase their robustness and trustworthiness. In particular, it addresses three root causes for lack of robustness that can be deemed central to the successful clinical translation of ML methods: First, many tasks in medical imaging can be phrased in the language of inverse problems. Most common ML methods aimed at solving such inverse problems implicitly assume that they are well-posed, especially that the problem has a unique solution. However, the solution might be ambiguous. In this thesis, we introduce a data-driven method for analyzing the well-posedness of inverse problems. In addition, we propose a framework to validate the suggested method in a problem-aware manner. Second, simulation is an important tool for the development of medical ML systems due to small in vivo data sets and/or a lack of annotated references (e. g. spatially resolved blood oxygenation (sO 2 )). However, simulation introduces a new uncertainty to the ML pipeline as ML performance guarantees generally rely on the testing data being sufficiently similar to the training data. This thesis addresses the uncertainty by quantifying the domain gap between training and testing data via an out-of-distribution (OoD) detection approach. Third, we introduce a new paradigm for medical ML based on personalized models. In a data-scarce regime with high inter-patient variability, classical ML models cannot be assumed to generalize well to new patients. To overcome this problem, we propose to train ML models on a per-patient basis. This approach circumvents the inter-patient variability, but it requires training without a supervision signal. We address this issue via OoD detection, where the current status quo is encoded as in-distribution (ID) using a personalized ML model. Changes to the status quo are then detected as OoD. While these three facets might seem distinct, the suggested framework provides a unified view of them. The enabling technology is the so-called invertible neural network (INN), which can be used as a flexible and expressive (conditional) density estimator. In this way, they can encode solutions to inverse problems as a probability distribution as well as tackle OoD detection tasks via density-based scores, like the widely applicable information criterion (WAIC). The present work validates our framework on the example of biophotonic imaging. Biophotonic imaging promises the estimation of tissue parameters such as sO 2 in a non-invasive way by evaluating the “fingerprint” of the tissue in the light spectrum. We apply our framework to analyze the well-posedness of the tissue parameter estimation problem at varying spectral and spatial resolutions. We find that with sufficient spectral and/or spatial context, the sO 2 estimation problem is well-posed. Furthermore, we examine the realism of simulated biophotonic data using the proposed OoD approach to gauge the generalization capabilities of our ML models to in vivo data. Our analysis shows a considerable remaining domain gap between the in silico and in vivo spectra. Lastly, we validate the personalized ML approach on the example of non-invasive ischemia monitoring in minimally invasive kidney surgery, for which we developed the first-in-human laparoscopic multispectral imaging system. In our study, we find a strong OoD signal between perfused and ischemic kidney spectra. Furthermore, the proposed approach is video-rate capable. In conclusion, we successfully developed a framework for uncertainty handling in medical ML and validated it using a diverse set of medical ML tasks, highlighting the flexibility and potential impact of our approach. The framework opens the door to robust solutions to applications like (recording) device design, quality control for simulation pipelines, and personalized video-rate tissue parameter monitoring. In this way, this thesis facilitates the development of the next generation of trustworthy ML systems in medicine

Development of boundary conditions for building drainage system components through novel numerical, laboratory and photogrammetric methods

Improvements in public health through better sanitary plumbing systems has been mainly due to the prevention afforded by barrier technologies to the ingress of foul air, which can contain toxic gases and pathogens, notwithstanding the nuisance of malodour. The main defence against this ingress is the ‘trap seal’ which comes in two forms; the ‘water trap seal’ and the ‘waterless trap seal’. Whilst these devices form effective barriers, they are vulnerable to, or can produce, transient air pressure fluctuations in the system which can lead to seal loss. Greater understanding of the characteristics of these devices is essential for the development of better protection strategies. The development of novel analytical techniques is central to this research as it increases computer model resolution at these important system extremities. Current methods employ a laboratory only approach, whereby a single loss co-efficient is developed. These laboratory derived boundary conditions are inherently static and in the case of the waterless trap seal, ignore structure flexibility. This research has produced new methodologies to evaluate performance and generate dynamic boundary conditions suitable for inclusion in an existing 1-D Method of Characteristics based model, AIRNET, which solves for pressure and velocity via the St. Venant equations of continuity and momentum in a finite difference scheme. The first novel technique developed uses photographic image and pressure data, transformed via photogrammetric and Fourier analysis to produce mathematical representations of the opening and closing of a waterless trap under transient pressures. The second novel technique developed focusses on the dynamic response of a water trap seal. Current boundary conditions use a steady state friction factor, ignoring separation losses. Analysis via ANSYS CFX allowed a frequency dependent dynamic representation of velocity change in the water trap seal to be developed, integrating unsteady friction and separation losses for the first time. Incorporation of these new boundary conditions in AIRNET confirms that frequency dependent whole system responses are possible and more realistic, reflecting both laboratory and on-site observations

Digital processing of satellite images for geological applications with examples from North-East Scotland and North-West Malaysia

This study describes the use of Landsat MSS and TM for geological applications in two Scottish areas: Lochindorb and Loch Tuel; and one Malaysian area: Kedah-Perak. The areas are poorly exposed and highly vegetated. The data were digitally processed with the objective of producing more interpretable images. The processes include contrast enhancement, ratioing, subtraction, principal component analysis, discriminant analysis, filtering, the combination of images as colour composites, and producing negative images of the data. Geological interpretation of the most informative images was undertaken by visual interpretation. In the Lochindorb area, Landsat MSS imagery did not prove useful for superficial deposits mapping, and the resolution offers by the TM is still not sufficient for semi-detailed mapping at scale 1: 50,000. The combination of TM imagery and aerial photographs, however, made the mapping task easier and produced "better" map. In the Kedah-Perak area, textural information is more important than spectral information for lithological interpretation and many image units correlate well with major mapped rocks. Lineaments are well expressed on Landsat imagery and are mapped for the Loch Tummel and Kedäh-Perak areas. The lineament maps for both areas confirm many mapped faults and reveal a new prominent lineaments (probably faults). For the Loch Tummel area, the relative merits of TM versus MSS data were examined. Both produced similar results regarding major lineament orientations, but the TM provides a good improvement over the MSS in the ability to map lineaments. For both areas, lineaments appear to be correlated with geomorphology (lithology), and with the occurrence of ore deposits and probably geologic structure for the Kedah-Perak area. Landsat imagery can be used to aid lithological mapping in Malaysia, but has not proved useful for Scotland (U. K. ) because of different objectives and constraints. However, Landsat imagery is an effective tool in mapping lineaments for both areas

Design/cost tradeoff studies. Appendix A. Supporting analyses and tradeoffs, book 2. Earth Observatory Satellite system definition study (EOS)

Attitude reference systems for use with the Earth Observatory Satellite (EOS) are described. The systems considered are fixed and gimbaled star trackers, star mappers, and digital sun sensors. Covariance analyses were performed to determine performance for the most promising candidate in low altitude and synchronous orbits. The performance of attitude estimators that employ gyroscopes which are periodically updated by a star sensor is established by a single axis covariance analysis. The other systems considered are: (1) the propulsion system design, (2) electric power and electrical integration, (3) thermal control, (4) ground data processing, and (5) the test plan and cost reduction aspects of observatory integration and test

The 2nd Conference on Remotely Manned Systems (RMS): Technology and Applications

Control theory and the design of manipulators, teleoperators, and robots are considered. Applications of remotely manned vehicles to space maintenance and orbital assembly, industry and productivity, undersea operations, and rehabilitation systems are emphasized

AAS/GSFC 13th International Symposium on Space Flight Dynamics

This conference proceedings preprint includes papers and abstracts presented at the 13th International Symposium on Space Flight Dynamics. Cosponsored by American Astronautical Society and the Guidance, Navigation and Control Center of the Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude dynamics; and mission design

International program for Earth observations

During the 1990 summer session of the International Space University, graduate students of many different countries and with various academic backgrounds carried out a design project that focused on how to meet the most pressing environmental information requirements of the 1990's. The International Program for Earth Observations (IPEO) is the result of the students labor. The IPEO report examines the legal and institutional, scientific, engineering and systems, financial and economic, and market development approaches needed to improve international earth observations and information systems to deal with environmental issues of global importance. The IPEO scenario is based on the production of a group of lightweight satellites to be used in global remote sensing programs. The design and function of the satellite is described in detail

Third International Conference on Inverse Design Concepts and Optimization in Engineering Sciences (ICIDES-3)

Papers from the Third International Conference on Inverse Design Concepts and Optimization in Engineering Sciences (ICIDES) are presented. The papers discuss current research in the general field of inverse, semi-inverse, and direct design and optimization in engineering sciences. The rapid growth of this relatively new field is due to the availability of faster and larger computing machines

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen