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An oceanic wave measured system is disclosed wherein wave height is sensed by a barometer mounted on a buoy. The distance between the trough and crest of a wave is monitored by sequentially detecting positive and negative peaks of the output of the barometer and by combining (adding) each set of two successive half cycle peaks. The timing of this measurement is achieved by detecting the period of a half cycle of wave motion.
Reliability is the ability of a product to properly function, within specified performance limits, for a specified period of time, under the life cycle application conditions. Failure analysis is a vital tool in the effort to ensure reliability of electronic products and systems throughout their product lifecycle. Today, organizations involved in activities within the electronics supply chain are facing new challenges, not just from complex assembly styles, harsher lifecycle environments, and sophisticated supply chains, but also from customers who are demanding a quicker turn-around. Unfortunately, root cause failure analysis is often performed incompletely, leading to a poor understanding of failure mechanisms and causes and, customer dissatisfaction due to recurring failures. The PDC (Professional Development Course) starts with an introduction to reliability concepts, physics of failure and an overview of failure mechanisms that affect PCBs (Printed Circuit Boards), PCBAs (Printed Circuit Board Assembly) and components. The PDC then dives into root cause hypothesizing techniques (Pareto, FMEA (Failure Modes and Effects Analysis), fishbone (Cause-And-Effect Diagram), FTA (Fault Tree Analysis)), non-destructive and destructive analysis and, materials characterization will be discussed. Numerous failure analysis case studies will be used to illustrate the techniques and analysis principles to arrive at the root cause(s) of field failures on printed circuit boards, active components, and assemblies. What Attendees will Learn: Topics include: Overview of Reliability Concepts Failure mechanisms of electronic products Root cause analysis Failure analysis techniques -Non-destructive techniques (optical, CSAM (Confocal Scanning Electron Microscopy) etc.) -Destructive analysis (DPA (Destructive Physical Analysis), Decap (Decapsulation), FIB (Focused Ion Beam) etc.) -Materials characterization (XRF (X-Ray Fluorescence) , EDS (Error Detection Sequential), TMA/DSC (Thermal Mechanical Analysis/Differential Scanning Calorimetry) etc.)
Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
We present the first unambiguous detection of quasi-periodic wave trains within the broad pulse of a global EUV wave (so-called EIT wave) occurring on the limb. These wave trains, running ahead of the lateral coronal mass ejection (CME) front of 2-4 times slower, coherently travel to distances greater than approximately solar radius/2 along the solar surface, with initial velocities up to 1400 kilometers per second decelerating to approximately 650 kilometers per second. The rapid expansion of the CME initiated at an elevated height of 110 Mm produces a strong downward and lateral compression, which may play an important role in driving the primary EUV wave and shaping its front forwardly inclined toward the solar surface. The wave trains have a dominant 2 minute periodicity that matches the X-ray flare pulsations, suggesting a causal connection. The arrival of the leading EUV wave front at increasing distances produces an uninterrupted chain sequence of deflections and/or transverse (likely fast kink mode) oscillations of local structures, including a flux-rope coronal cavity and its embedded filament with delayed onsets consistent with the wave travel time at an elevated (by approximately 50%) velocity within it. This suggests that the EUV wave penetrates through a topological separatrix surface into the cavity, unexpected from CME-caused magnetic reconfiguration. These observations, when taken together, provide compelling evidence of the fast-mode MHD wave nature of the primary (outer) fast component of a global EUV wave, running ahead of the secondary (inner) slow component of CME-caused restructuring.
Relative merits of various coding methods used to increase reliability or data rate on data transmission channel
The formulation of the decision making of a failure detection process as a Bayes sequential decision problem (BSDP) provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Baysian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is a useful one.
A few new algorithms for region growing in pictures were developed. These algorithms are a step toward finding a satisfactory solution to the image segmentation problem, and in-depth understanding of the problems of nonsemantic image segmentation. The algorithms utilize a sequential decision approach for region boundaries detection. The sequential decisions are supported by a stochastic algorithm that maintains local statistics of the region near the boundaries as the region grows. A few illustrations of the algorithm's performance are included.
This paper considers some basic problems relating to automatic data base generation from imagery, the primary emphasis being on fast and efficient automatic extraction of relevant pictorial information. Among the techniques discussed are recursive implementations of some particular types of filters which are much faster than FFT implementations, a 'sequential similarity detection' technique of implementing matched filters, and sequential linear classification of multispectral imagery. Several applications of the above techniques are presented including enhancement of underwater, aerial and radiographic imagery, detection and reconstruction of particular types of features in images, automatic picture registration and classification of multiband aerial photographs to generate thematic land use maps.
Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.
The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.
An investigation of the behavior of the human decisionmaker is described for a task related to the problem of a pilot using a traffic situation display to avoid collisions. This sequential signal detection task is characterized by highly correlated signals with time varying strength. Experimental results are presented and the behavior of the observers is analyzed using the theory of Markov processes and classical signal detection theory. Mathematical models are developed which describe the main result of the experiment: that correlation in sequential signals induced perseveration in the observer response and a strong tendency to repeat their previous decision, even when they were wrong.
Markov chain stimulus sequence role effect upon signal detection in psychophysiological forced choice task
Polyethylene-based poly(ethylene-co-vinyl acetate) (EVA), polyolefin elastomer (POE), and thermoplastic polyolefin (TPO) are common polymer candidates for photovoltaic (PV) module encapsulants. The choice of encapsulant must be carefully considered in novel module designs, such as bifacial glass/glass laminates, to limit performance degradation through loss of optical transmittance, mechanical integrity, and corrosion - as well as potential-induced degradation. Encapsulant quality and resilience against environmental stressors are readily influenced by the additives in the encapsulant formulation. Here, we show that, the changes in optical transmittance after UV aging result from the discoloration caused by interactions between additives, and optical scattering from changes in the polymer crystal structure. We observed competing cross-linking and chain scission mechanisms, with their kinetics influenced by the presence of oxygen and elevated temperatures. Increasing chamber temperatures from 55 °C to 85 °C during the UV stress test amplified encapsulant discoloration and promoted polymer cross-linking, causing severe, irreversible damage that remains to be proven field relevant. Damp heat aging was found to be insufficient to produce significant encapsulant degradation; however, combining stress tests sequentially allowed detection of further degradation beyond the limitations of the damp heat test alone. Appropriate degradation screening methods are necessary to uncover potential encapsulant weaknesses.
Sequential and pseudorandom scanning methods in television reception
Rapid acquisition by sequential estimation /RASE/ TECHNIQUE for acquisition of pseudonoise