On-Line Dependability Enhancement of Multiprocessor SoCs by Resource Management

This paper describes a new approach towards dependable design of homogeneous multi-processor SoCs in an example satellite-navigation application. First, the NoC dependability is functionally verified via embedded software. Then the Xentium processor tiles are periodically verified via on-line self-testing techniques, by using a new IIP Dependability Manager. Based on the Dependability Manager results, faulty tiles are electronically excluded and replaced by fault-free spare tiles via on-line resource management. This integrated approach enables fast electronic fault detection/diagnosis and repair, and hence a high system availability. The dependability application runs in parallel with the actual application, resulting in a very dependable system. All parts have been verified by simulation

Tracking and data relay satellite fault isolation and correction using PACES: Power and attitude control expert system

The Power and Attitude Control Expert System (PACES) is an object oriented and rule based expert system which provides spacecraft engineers with assistance in isolating and correcting problems within the Power and Attitude Control Subsystems of the Tracking and Data Relay Satellites (TDRS). PACES is designed to act in a consultant role. It will not interface to telemetry data, thus preserving full operator control over spacecraft operations. The spacecraft engineer will input requested information. This information will include telemetry data, action being performed, problem characteristics, spectral characteristics, and judgments of spacecraft functioning. Questions are answered either by clicking on appropriate responses (for text), or entering numeric values. A context sensitive help facility allows access to additional information when the user has difficulty understanding a question or deciding on an answer. The major functionality of PACES is to act as a knowledge rich system which includes block diagrams, text, and graphics, linked using hypermedia techniques. This allows easy movement among pieces of the knowledge. Considerable documentation of the spacecraft Power and Attitude Control Subsystems is embedded within PACES. The development phase of TDRSS expert system technology is intended to provide NASA with the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking and Data Relay Satellite Program

3-D Microwave Imaging for Breast Cancer

We introduce a novel microwave imaging technique for breast cancer detection. Our approach provides a one-pass inverse image solution, which is completely new and unprecedented, unrelated to tomography or radar-based algorithms, and unburdened by the optimization toil which lies at the heart of numerical schemes. It operates effectively at a single frequency, without requiring the bandwidth of radar techniques. Underlying this new method is our unique Field Mapping Algorithm (FMA), which transforms electromagnetic fields acquired upon one surface, be it through outright measurement or some auxiliary computation, into those upon another in an exact sense

Properties of two U.S. inflation measures (1985-2005)

Analyses are presented of 84 quarterly observations 1/85-4/05 on two U.S. index numbers of nominal prices often employed to measure inflation. Analyses are designed to answer two key questions of interest to macroeconomists. Is inflation stationary (I(0)) or stochastically non-stationary (I(1))? If it is I(1), is it scalar or multivariate? Both measures of inflation are found clearly to be I(1) and, for these measures, inflation is found clearly to be scalar. The paper also illustrates univariate analysis procedures (and report standards) considered to be more effective and convincing than those found in the existing literature on inflation measures

Third Conference on Artificial Intelligence for Space Applications, part 2

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed

Dynamic test input generation for multiple-fault isolation

Recent work is Causal Reasoning has provided practical techniques for multiple fault diagnosis. These techniques provide a hypothesis/measurement diagnosis cycle. Using probabilistic methods, they choose the best measurements to make, then update fault hypotheses in response. For many applications such as computers and spacecraft, few measurement points may be accessible, or values may change quickly as the system under diagnosis operates. In these cases, a hypothesis/measurement cycle is insufficient. A technique is presented for a hypothesis/test-input/measurement diagnosis cycle. In contrast to generating tests a priori for determining device functionality, it dynamically generates tests in response to current knowledge about fault probabilities. It is shown how the mathematics previously used for measurement specification can be applied to the test input generation process. An example from an efficient implementation called Multi-Purpose Causal (MPC) is presented

Sensitivity and foreground modelling for large-scale CMB B-mode polarization satellite missions

The measurement of the large-scale B-mode polarization in the cosmic microwave background (CMB) is a fundamental goal of future CMB experiments. However, because of unprecedented sensitivity, future CMB experiments will be much more sensitive to any imperfect modelling of the Galactic foreground polarization in the reconstruction of the primordial B-mode signal. We compare the sensitivity to B-modes of different concepts of CMB satellite missions (LiteBIRD, COrE, COrE+, PRISM, EPIC, PIXIE) in the presence of Galactic foregrounds. In particular, we quantify the impact on the tensor-to-scalar parameter of incorrect foreground modelling in the component separation process. Using Bayesian fitting and Gibbs sampling, we perform the separation of the CMB and Galactic foreground B-modes. The recovered CMB B-mode power spectrum is used to compute the likelihood distribution of the tensor-to-scalar ratio. We focus the analysis to the very large angular scales that can be probed only by CMB space missions, i.e. the Reionization bump, where primordial B-modes dominate over spurious B-modes induced by gravitational lensing. We find that fitting a single modified blackbody component for thermal dust where the "real" sky consists of two dust components strongly bias the estimation of the tensor-to-scalar ratio by more than 5{\sigma} for the most sensitive experiments. Neglecting in the parametric model the curvature of the synchrotron spectral index may bias the estimated tensor-to-scalar ratio by more than 1{\sigma}. For sensitive CMB experiments, omitting in the foreground modelling a 1% polarized spinning dust component may induce a non-negligible bias in the estimated tensor-to-scalar ratio.Comment: 20 pages, 8 figures, 6 tables. Updated to match version accepted by MNRA

PROPERTIES OF TWO U.S. INFLATION MEASURES (1985-2005)

Analyses are presented of 84 quarterly observations 1/85-4/05 on two U.S. index numbers of nominal prices often employed to measure inflation. Analyses are designed to answer two key questions of interest to macroeconomists. Is inflation stationary (I(0)) or stochastically non-stationary (I(1))? If it is I(1), is it scalar or multivariate? Both measures of inflation are found clearly to be I(1) and, for these measures, inflation is found clearly to be scalar. The paper also illustrates univariate analysis procedures (and report standards) considered to be more effective and convincing than those found in the existing literature on inflation measures.

Automatic fault detection on BIPV systems without solar irradiation data

BIPV systems are small PV generation units spread out over the territory, and whose characteristics are very diverse. This makes difficult a cost-effective procedure for monitoring, fault detection, performance analyses, operation and maintenance. As a result, many problems affecting BIPV systems go undetected. In order to carry out effective automatic fault detection procedures, we need a performance indicator that is reliable and that can be applied on many PV systems at a very low cost. The existing approaches for analyzing the performance of PV systems are often based on the Performance Ratio (PR), whose accuracy depends on good solar irradiation data, which in turn can be very difficult to obtain or cost-prohibitive for the BIPV owner. We present an alternative fault detection procedure based on a performance indicator that can be constructed on the sole basis of the energy production data measured at the BIPV systems. This procedure does not require the input of operating conditions data, such as solar irradiation, air temperature, or wind speed. The performance indicator, called Performance to Peers (P2P), is constructed from spatial and temporal correlations between the energy output of neighboring and similar PV systems. This method was developed from the analysis of the energy production data of approximately 10,000 BIPV systems located in Europe. The results of our procedure are illustrated on the hourly, daily and monthly data monitored during one year at one BIPV system located in the South of Belgium. Our results confirm that it is possible to carry out automatic fault detection procedures without solar irradiation data. P2P proves to be more stable than PR most of the time, and thus constitutes a more reliable performance indicator for fault detection procedures.Comment: 7 pages, 8 figures, conference proceedings, 29th European Photovoltaic Solar Energy Conference and Exhibition, Amsterdam, 201