Information-Based Particle Flow with Convergence Control

A new formulation of the Gaussian particle flow filter is presented using an information theoretic approach. The developed information-based form advances the Gaussian particle flow framework in two ways: it imparts physical meaning to the flow dynamics and provides the ability to easily include modifications for a non-Bayesian update. An orbit determination simulation with high initial uncertainty is used to demonstrate the consistent, robust performance of the information flow filter in situations where the extended Kalman filter fails

Speech, time-frequency representations

This paper presents a review on the use of time frequency representations in the fields of speech analysis and automatic speech processing . Three main groups of methods are considered : speech production based methods, general signal analysis methods, auditory-based methods . After this review, some short conclusions on their carrent use, and on some possible future evolutions are proposed .Le propos de cet article est de présenter une bibliographie récente sur l'utilisation des méthodes de représentation temps-fréquence en analyse et en traitement automatique de la parole. Les méthodes sont classées en trois grandes familles: méthodes dérivées de la production, méthodes d'analyse du signal, méthodes modélisant la perception. Après ce panorama, quelques rapides conclusions sur l'état actuel de l'utilisation de ces méthodes, et quelques perspectives sont tentée

Target localization and tracking by fusing doppler differentials from cellular emanations with a multi-spectral video tracker

We present an algorithm for fusing data from a constellation of RF sensors detecting cellular emanations with the output of a multi-spectral video tracker to localize and track a target with a specific cell phone. The RF sensors measure the Doppler shift caused by the moving cellular emanation and then Doppler differentials between all sensor pairs are calculated. The multi-spectral video tracker uses a Gaussian mixture model to detect foreground targets and SIFT features to track targets through the video sequence. The data is fused by associating the Doppler differential from the RF sensors with the theoretical Doppler differential computed from the multi-spectral tracker output. The absolute difference and the root-mean-square difference are computed to associate the Doppler differentials from the two sensor systems. Performance of the algorithm was evaluated using synthetically generated datasets of an urban scene with multiple moving vehicles. The presented fusion algorithm correctly associates the cellular emanation with the corresponding video target for low measurement uncertainty and in the presence of favorable motion patterns. For nearly all objects the fusion algorithm has high confidence in associating the emanation with the correct multi-spectral target from the most probable background target

On-orbit spacecraft reliability

Operational and historic data for 350 spacecraft from 52 U.S. space programs were analyzed for on-orbit reliability. Failure rates estimates are made for on-orbit operation of spacecraft subsystems, components, and piece parts, as well as estimates of failure probability for the same elements during launch. Confidence intervals for both parameters are also given. The results indicate that: (1) the success of spacecraft operation is only slightly affected by most reported incidents of anomalous behavior; (2) the occurrence of the majority of anomalous incidents could have been prevented piror to launch; (3) no detrimental effect of spacecraft dormancy is evident; (4) cycled components in general are not demonstrably less reliable than uncycled components; and (5) application of product assurance elements is conductive to spacecraft success

Effects of Non-motorized Voluntary Running on Experimental and Spontaneous Metastasis in Mice

Abstract. The Epidemiologic studies suggest that physical activity reduces the risk of certain types of cancer, e.g. colorectal cancer (1, 2) and breast cancer in humans (3, 4). This risk reduction may be associated with changes in energy expenditure, body composition or dietary practice. Support for the epidemiologic observations includes findings that certain patterns of physical activity reduce experimentally induced tumorigenesis (e.g. mammary carcinogenesis (5, 6)) in laboratory rodents. Both epidemiologic and animal studies indicate that physical activity may play a favorable role in primary cancer prevention. Metastasis, the spread of malignant cells from a primary tumor to different sites of the same organ or to distant organs, is the most devastating aspect of cancer. Its occurrence directly affects the prognosis and survival of cancer patients. Because early diagnosis and treatment of primary tumor have markedly improved the survival rate of cancer patients, there has been great interest in secondary cancer prevention in both general public and research community in recent years. Studies on the relationship between physical activity and metastasis are limited, and data from available laboratory studies (non-motorized voluntary running or forced exercise by treadmill) are inconsistent. While some studies show that voluntary (7) and forced exercise (8) reduce malignant spread, others show no such an inhibitory effect (9), or even that it tends to increase metastatic yield (10). This inconsistency could be a result of variations in the type, duration and intensity of the exercise, the strain of animals used, or the metastatic process investigated. Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure beyond resting expenditure, and it is different from exercise that is planned, structured, repetitive, and purposeful in the sense that improvement of maintenance of physical fitness is the objective (11). The purpose of the present study was to investigate the effects of moderate physical activity, achieved by non-motorized voluntary running, on malignant spread in C57BL/6 mice, by using commonly used models of experimental and spontaneous metastasis

The flow of plasma in the solar terrestrial environment

The overall goal of our NASA Theory Program was to study the coupling, time delays, and feedback mechanisms between the various regions of the solar-terrestrial system in a self-consistent, quantitative manner. To accomplish this goal, it will eventually be necessary to have time-dependent macroscopic models of the different regions of the solar-terrestrial system and we are continually working toward this goal. However, with the funding from this NASA program, we concentrated on the near-earth plasma environment, including the ionosphere, the plasmasphere, and the polar wind. In this area, we developed unique global models that allowed us to study the coupling between the different regions. These results are highlighted in the next section. Another important aspect of our NASA Theory Program concerned the effect that localized 'structure' had on the macroscopic flow in the ionosphere, plasmasphere, thermosphere, and polar wind. The localized structure can be created by structured magnetospheric inputs (i.e., structured plasma convection, particle precipitation or Birkland current patterns) or time variations in these input due to storms and substorms. Also, some of the plasma flows that we predicted with our macroscopic models could be unstable, and another one of our goals was to examine the stability of our predicted flows. Because time-dependent, three-dimensional numerical models of the solar-terrestrial environment generally require extensive computer resources, they are usually based on relatively simple mathematical formulations (i.e., simple MHD or hydrodynamic formulations). Therefore, another goal of our NASA Theory Program was to study the conditions under which various mathematical formulations can be applied to specific solar-terrestrial regions. This could involve a detailed comparison of kinetic, semi-kinetic, and hydrodynamic predictions for a given polar wind scenario or it could involve the comparison of a small-scale particle-in-cell (PIC) simulation of a plasma expansion event with a similar macroscopic expansion event. The different mathematical formulations have different strengths and weaknesses and a careful comparison of model predictions for similar geophysical situations provides insight into when the various models can be used with confidence

Relating Spatial Patterns of Stream Metabolism to Distributions of Juveniles Salmonids at the River Network Scale

Understanding the factors that drive spatial patterns in stream ecosystem processes and the distribution of aquatic biota is important to effective management of these systems and the conservation of biota at the network scale. In this study, we conducted field surveys throughout an extensive river network in NE Oregon that supports diminishing populations of wild salmonids. We collected data on physical habitat, nutrient concentrations, biofilm standing stocks, stream metabolism (gross primary production [GPP] and ecosystem respiration [ER]), and ESA‐listed juvenile salmonid density from approximately 50 sites across two sub‐basins. Our goals were to (1) to evaluate network patterns in these metrics, and (2) determine network‐scale linkages among these metrics, thus providing inference of processes driving observed patterns. Ambient nitrate‐N and phosphate‐P concentrations were low across both sub‐basins (\u3c40 μg/L). Nitrate‐N decreased with watershed area in both sub‐basins, but phosphate‐P only decreased in one sub‐basin. These spatial patterns suggest co‐limitation in one sub‐basin but N limitation in the other; experimental results using nutrient diffusing substrates across both sub‐basins supported these predictions. Solar exposure, temperature, GPP, ER, and GPP:ER increased with watershed area, but biofilm Chl a and ash‐free dry mass (AFDM) did not. Spatial statistical network (SSN) models explained between 70% and 75% of the total variation in biofilm Chl a, AFDM, and GPP, but only 21% of the variation in ER. Temperature and nutrient concentrations were the most supported predictors of Chl aand AFDM standing stocks, but these variables explained little of the total variation compared to spatial autocorrelation. In contrast, solar exposure and temperature were the most supported variables explaining GPP, and these variables explained far more variation than autocorrelation. Solar exposure, temperature, and nutrient concentrations explained almost none of the variation in ER. Juvenile salmonids—a key management focus in these sub‐basins—were most abundant in cool stream sections where rates of GPP were low, suggesting temperature constraints on these species restrict their distribution to oligotrophic areas where energy production at the base of the food web may be limited

Advances in POST2 End-to-End Descent and Landing Simulation for the ALHAT Project

Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining design and integration capability and system performance of the lunar descent and landing system and environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. The POST2 simulation provides a six degree-of-freedom capability necessary to test, design and operate a descent and landing system for successful lunar landing. This paper presents advances in the development and model-implementation of the POST2 simulation, as well as preliminary system performance analysis, used for the testing and evaluation of ALHAT project system models