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At least 253 records · Page 14

Synchronization and fault-masking in redundant real-time systems

A real time computer may fail because of massive component failures or not responding quickly enough to satisfy real time requirements. An increase in redundancy - a conventional means of improving reliability - can improve the former but can - in some cases - degrade the latter considerably due to the overhead associated with redundancy management, namely the time delay resulting from synchronization and voting/interactive consistency techniques. The implications of synchronization and voting/interactive consistency algorithms in N-modular clusters on reliability are considered. All these studies were carried out in the context of real time applications. As a demonstrative example, we have analyzed results from experiments conducted at the NASA Airlab on the Software Implemented Fault Tolerance (SIFT) computer. This analysis has indeed indicated that in most real time applications, it is better to employ hardware synchronization instead of software synchronization and not allow reconfiguration.

Krishna, C. M.↗

SIRTF controller simulation - Instability masked by numerical integration

In the course of a simulation study of a candidate design for the Space Infrared Telescope Facility (SIRTF), an unusual phenomenon was observed. The uncompensated control system was unstable, but a numerical simulation with the fixed-step-size classical fourth-order Runge-Kutta method gave a stable response. This phenomenon is described in the setting in which it occurred. The Runge-Kutta simulation model is analyzed as a discrete linear system and shown to be stable, thus corroborating the numerical results.

Rajan, N.↗

Masking failures of multidimensional sensors (extended abstract)

When a computer monitors a physical process, the computer uses sensors to determine the values of the physical variables that represent the state of the process. A sensor can sometimes fail, however, and in the worst case report a value completely unrelated to the true physical value. The work described is motivated by a methodology for transforming a process control program that can not tolerate sensor failure into one that can. In this methodology, a reliable abstract sensor is created by combining information from several real sensors that measure the same physical value. To be useful, an abstract sensor must deliver reasonably accurate information at reasonable computational cost. Sensors are considered that deliver multidimensional values (e.g., location or velocity in three dimensions, or both temperature and pressure). Geometric techniques are used to derive upper bounds on abstract sensor accuracy and to develop efficient algorithms for implementing abstract sensors.

Chew, Paul↗

Infrared Signature Masking by Air Plasma Radiation

Detailed measurements and modeling of the spectral emission of an atmospheric pressure air plasma at temperatures up to -3400 K have been made. The cold gas injected in the plasma torch contained an estimated mole fraction of water vapor of approximately 4.5 x 10(exp -3) and an estimated carbon dioxide mole fraction of approximately 3.3 x 10(exp -4). Under these conditions, the minimum level of air plasma emission is found to be between 3.9 and 4.15 microns. Outside this narrow region, significant spectral emission is detected that can be attributed to the fundamental and overtone bands of NO and OH, and to the v(sub 3) and the (v(sub 1)+v(sub 3)) bands Of CO2. Special attention was paid to the effects of ambient air absorption in the optical path between the plasma and the detector. Excellent quantitative agreement is obtained between the measured and simulated spectra, which are both on absolute intensity scales, thus lending confidence in the radiation models incorporated into NEQAIR2-IR over the course of this research program.

Kruger, C. H.↗

Perceptual Classification Images from Vernier Acuity Masked by Noise

Letting external noise rather than internal noise limit discrimination performance allows information to be extracted about the observer's stimulus classification rule. A perceptual classification image is the correlation over trials between the noise amplitude at a spatial location and the observer's responses. If, for example, the observer followed the rule of the ideal observer, the perceptual classification image would be an estimate of the ideal observer filter, the difference between the two unmasked images being discriminated. Perceptual classification images were estimated for a vernier discrimination task. The display screen had 48 pixels per degree horizontally and vertically. The no-offset image had a dark horizontal line of 4 pixels, a 1 pixel space, and 4 more dark pixels. Classification images were based on 1600 discrimination trials with the line contrast adjusted to keep the error rate near 25 percent. In the offset image, the second line was one pixel higher. Unlike the ideal observer filter (a horizontal dipole), the observer perceptual classification images are strongly oriented. Fourier transforms of the classification images had a peak amplitude near one cycle per degree and an orientation near 25 degrees. The spatial spread is much more than image blur predicts, and probably indicates the spatial position uncertainty in the task.

Ahumada, A. J.↗

Entropy Masking

This paper details two projects that use the World Wide Web (WWW) for dissemination of curricula that focus on remote sensing. 1) Presenting grade-school students with the concepts used in remote sensing involves educating the teacher and then providing the teacher with lesson plans. In a NASA-sponsored project designed to introduce students in grades 4 through 12 to some of the ideas and terminology used in remote sensing, teachers from local grade schools and middle schools were recruited to write lessons about remote sensing concepts they could use in their classrooms. Twenty-two lessons were produced and placed in seven modules that include: the electromagnetic spectrum, two- and three-dimensional perception, maps and topography, scale, remote sensing, biotic and abiotic concepts, and landscape chi rise. Each lesson includes a section that evaluates what students have learned by doing the exercise. The lessons, instead of being published in a workbook and distributed to a limited number of teachers, have been placed on a WWW server, enabling much broader access to the package. This arrangement also allows for the lessons to be modified after feedback from teachers accessing the package. 2) Two-year colleges serve to teach trade skills, prepare students for enrollment in senior institutions of learning, and more and more, retrain students who have college degrees in new technologies and skills. A NASA-sponsored curriculum development project is producing a curriculum using remote sensing analysis an Earth science applications. The project has three major goals. First, it will implement the use of remote sensing data in a broad range of community college courses. Second, it will create curriculum modules and classes that are transportable to other community colleges. Third, the project will be an ongoing source of data and curricular materials to other community colleges. The curriculum will have these course pathways to a certificate; a) a Science emphasis, b) an Arts and Letters emphasis, and c) a Computer Science emphasis Each pathway includes course work in remote sensing, geographical information systems (GIS), computer science, Earth science, software and technology utilization, and communication. Distribution of products from this project to other two-year colleges will be accomplished using the WWW.

Watson, Andrew B.↗

Masking by Gratings Predicted by an Image Sequence Discriminating Model: Testing Models for Perceptual Discrimination Using Repeatable Noise

Adding noise to stimuli to be discriminated allows estimation of observer classification functions based on the correlation between observer responses and relevant features of the noisy stimuli. Examples will be presented of stimulus features that are found in auditory tone detection and visual vernier acuity. using the standard signal detection model (Thurstone scaling), we derive formulas to estimate the proportion of the observers decision variable variance that is controlled by the added noise. one is based on the probability of agreement of the observer with him/herself on trials with the same noise sample. Another is based on the relative performance of the observer and the model. When these do not agree, the model can be rejected. A second derivation gives the probability of agreement of observer and model when the observer follows the model except for internal noise. Agreement significantly less than this amount allows rejection of the model.

Ahumada, Albert J., Jr.↗

Evaluation of a ''CMOS'' Imager for Shadow Mask Hard X-ray Telescope

We have developed a hard x-ray coder that provides high angular resolution imaging capability using a coarse position sensitive image plane detector. The coder consists of two Fresnel zone plates. (FZP) Two such 'FZP's generate Moire fringe patterns whose frequency and orientation define the arrival direction of a beam with respect to telescope axis. The image plane detector needs to resolve the Moire fringe pattern. Pixilated detectors can be used as an image plane detector. The recently available 'CMOS' imager could provide a very low power large area image plane detector for hard x-rays. We have looked into a unit made by Rad-Icon Imaging Corp. The Shadow-Box 1024 x-ray camera is a high resolution 1024xl024 pixel detector of 50x50 mm area. It is a very low power, stand alone camera. We present some preliminary results of our investigation of evaluation of such camera.

Desai, Upendra D.↗

Masked Proportional Routing

Distributed approach for determining a path connecting adjacent network nodes, for probabilistically or deterministically transporting an entity, with entity characteristic mu from a source node to a destination node. Each node i is directly connected to an arbitrary number J(mu) of nodes, labeled or numbered j=jl, j2, .... jJ(mu). In a deterministic version, a J(mu)-component baseline proportion vector p(i;mu) is associated with node i. A J(mu)-component applied proportion vector p*(i;mu) is determined from p(i;mu) to preclude an entity visiting a node more than once. Third and fourth J(mu)-component vectors, with components iteratively determined by Target(i;n(mu);mu),=alpha(mu).Target(i;n(mu)-1;mu)j+beta(mu).p* (i;mu)j and Actual(i;n(mu);+a(mu)j. Actual(i;n(mu)-l;mu)j+beta(mu).Sent(i;j'(mu);n(mu)-1;mu)j, are computed, where n(mu) is an entity sequence index and alpha(mu) and beta(mu) are selected numbers. In one embodiment, at each node i, the node j=j'(mu) with the largest vector component difference, Target(i;n(mu);mu)j'- Actual (i;n(mu);mu)j'. is chosen for the next link for entity transport, except in special gap circumstances, where the same link is optionally used for transporting consecutively arriving entities. The network nodes may be computer-controlled routers that switch collections of packets, frames, cells or other information units. Alternatively, the nodes may be waypoints for movement of physical items in a network or for transformation of a physical item. The nodes may be states of an entity undergoing state transitions, where allowed transitions are specified by the network and/or the destination node.

David H Wolpert↗

The Dangers of Failure Masking in Fault-Tolerant Software: Aspects of a Recent In-Flight Upset Event

On 1 August 2005, a Boeing Company 777-200 aircraft, operating on an international passenger flight from Australia to Malaysia, was involved in a significant upset event while flying on autopilot. The Australian Transport Safety Bureau's investigation into the event discovered that an anomaly existed in the component software hierarchy that allowed inputs from a known faulty accelerometer to be processed by the air data inertial reference unit (ADIRU) and used by the primary flight computer, autopilot and other aircraft systems. This anomaly had existed in original ADIRU software, and had not been detected in the testing and certification process for the unit. This paper describes the software aspects of the incident in detail, and suggests possible implications concerning complex, safety-critical, fault-tolerant software.

Johnson, C. W.↗

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Wilson, Michael J.↗

Comparison of Aerosol Classification Results from Airborne High Spectral Resolution Lidar (HSRL) Measurements and the Calipso Vertical Feature Mask

Knowledge of the vertical profile, composition, concentration, and size of aerosols is required for assessing the direct impact of aerosols on radiation, the indirect effects of aerosols on clouds and precipitation, and attributing these effects to natural and anthropogenic aerosols. Because anthropogenic aerosols are predominantly submicrometer, fine mode fraction (FMF) retrievals from satellite have been used as a tool for deriving anthropogenic aerosols. Although column and profile satellite retrievals of FMF have been performed over the ocean, such retrievals have not yet been been done over land. Consequently, uncertainty in satellite estimates of the anthropogenic component of the aerosol direct radiative forcing is greatest over land, due in large part to uncertainties in the FMF. Satellite measurements have been used to detect and evaluate aerosol impacts on clouds; however, such efforts have been hampered by the difficulty in retrieving vertically-resolved cloud condensation nuclei (CCN) concentration, which is the most direct parameter linking aerosol and clouds. Recent studies have shown correlations between average satellite derived column aerosol optical thickness (AOT) and in situ measured CCN. However, these same studies, as well as others that use detailed airborne in situ measurements have noted that vertical variability of the aerosol distribution, impacts of relative humidity, and the presence of coarse mode aerosols such as dust introduce large uncertainties in such relations.

Burton, S. P.↗

Comparison of Aerosol Classification From Airborne High Spectral Resolution Lidar and the CALIPSO Vertical Feature Mask

Knowledge of aerosol composition and vertical distribution is crucial for assessing the impact of aerosols on climate. In addition, aerosol classification is a key input to CALIOP aerosol retrievals, since CALIOP requires an inference of the lidar ratio in order to estimate the effects of aerosol extinction and backscattering. In contrast, the NASA airborne HSRL-1 directly measures both aerosol extinction and backscatter, and therefore the lidar ratio (extinction-to-backscatter ratio). Four aerosol intensive properties from HSRL-1 are combined to infer aerosol type. Aerosol classification results from HSRL-1 are used here to validate the CALIOP aerosol type inferences.

Burton, Sharon P.↗

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗