System identification and pattern recognition.
Input/output model of system with finite settling time, using error correcting technique employed in pattern recognition
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Input/output model of system with finite settling time, using error correcting technique employed in pattern recognition
Visual noise induction methods investigated at seven noise levels, discussing pattern comparisons by 46 subjects
Effect of display movement on tactile pattern perception
Response latency in visual pattern perception situation
A concept of bifurcating optical pattern rocognizer (BIOPAR) is described and demonstrated experimentally, using barium titanate crystal. When an input is applied to BIOPAR, the output may be directed to two ports.
The ModelFest Phase One dataset is a collection of luminance contrast thresholds for 43 two-dimensional monochromatic spatial patterns confined to an area of approximately two by two degrees. These data were collected by a collaboration among twelve laboratories, and were designed to provide a common database for calibration and testing of spatial vision models. Here I report fits of the ModelFest data with five models: Peak Contrast, Contrast Energy, Generalized Energy, a Gabor Channels model, and a Discrete Cosine Transform model. The Gabor Channels model provides the best fit, though the other, simpler models, with the exception of Peak Contrast, provide remarkably good fits as well. Though there are clear individual differences, regularities in the data suggest the possibility of constructing a standard observer for spatial vision. c2000 Optical Society of America.
Animals exhibit an enormous diversity of life cycles and larval morphologies. The developmental basis for this diversity is not well understood. It is clear, however, that mechanisms of pattern formation in early embryos differ significantly among and within groups of animals. These differences show surprisingly little correlation with phylogenetic relationships; instead, many are correlated with ecological factors, such as changes in life histories. Copyright 2000 Academic Press.
We have implemented a model of contrast gain and control in human vision that incorporates a number of key features, including a contrast sensitivity function, multiple oriented bandpass channels, accelerating nonlinearities, and a devisive inhibitory gain control pool. The parameters of this model have been optimized through a fit to the recent data that describe masking of a Gabor function by cosine and Gabor masks [J. M. Foley, "Human luminance pattern mechanisms: masking experiments require a new model," J. Opt. Soc. Am. A 11, 1710 (1994)]. The model achieves a good fit to the data. We also demonstrate how the concept of recruitment may accommodate a variant of this model in which excitatory and inhibitory paths have a common accelerating nonlinearity, but which include multiple channels tuned to different levels of contrast.
The six Dorsal Longitudinal flight Muscles (DLMs) of Drosophila develop from three larval muscles that persist into metamorphosis and serve as scaffolds for the formation of the adult fibers. We have examined the effect of muscle scaffold ablation on the development of DLMs during metamorphosis. Using markers that are specific to muscle and myoblasts we show that in response to the ablation, myoblasts which would normally fuse with the larval muscle, fuse with each other instead, to generate the adult fibers in the appropriate regions of the thorax. The development of these de novo DLMs is delayed and is reflected in the delayed expression of erect wing, a transcription factor thought to control differentiation events associated with myoblast fusion. The newly arising muscles express the appropriate adult-specific Actin isoform (88F), indicating that they have the correct muscle identity. However, there are frequent errors in the number of muscle fibers generated. Ablation of the larval scaffolds for the DLMs has revealed an underlying potential of the DLM myoblasts to initiate de novo myogenesis in a manner that resembles the mode of formation of the Dorso-Ventral Muscles, DVMs, which are the other group of indirect flight muscles. Therefore, it appears that the use of larval scaffolds is a superimposition on a commonly used mechanism of myogenesis in Drosophila. Our results show that the role of the persistent larval muscles in muscle patterning involves the partitioning of DLM myoblasts, and in doing so, they regulate formation of the correct number of DLM fibers.
This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.
The Soberanes Fire started on July 22, 2016 in Monterey County on the California Central Coast from an illegal campfire. This fire burned for 10 weeks at a record cost of more than $208 million for protection and control. A progressive analysis of the normalized burn ratio from the Landsat satellite showed that the final high burn severity (HBS) area for the Soberanes Fire comprised 22 percent of the total area burned, whereas final moderate burn severity (MBS) area comprised about 10 percent of the total area burned of approximately 53,470 ha (132,130 acres). The resulting landscape pattern of burn severity classes from the 2016 Soberanes Fire revealed that the majority of HBS area was located in the elevation zone between 500 and 1000 m, in the slope zone between 15 percent and 30 percent, or on south-facing aspects.
Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.
In 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.
Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting expert knowledge from proven systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. Motivated by performance gains observed during a multi-year, sequential development activity, this survey reviews knowledge, architecture, and pattern literature to establish a framework for research of architectural methods for expert knowledge identification and description using Model Based System Engineering. The multi-year sequential development activity is offered as the experimental system of interest for this research. This work aims to enable a digital engineering strategy that improves concept phase decision making, accelerates knowledge acquisition from lessons learned repositories, and eases the burden of generational knowledge loss.
Effective climate sensitivity (EffCS), commonly estimated from model simulations with abrupt 4×CO 2 for 150 years, has been shown to depend on the CO 2 forcing level. To understand this dependency systematically, we performed a series of simulations with a range of abrupt CO 2 forcing in two climate models. Our results indicate that normalized EffCS values in these simulations are a non-monotonic function of the CO 2 forcing, decreasing between 3× and 4×CO 2 in CESM1-LE (2× and 3×CO 2 in GISS-E2.1-G) and increasing at higher CO 2 levels. The minimum EffCS value, caused by anomalously negative radiative feedbacks, arises mainly from sea-surface temperature (SST) relative cooling in the tropical and subtropical North Atlantic. This cooling is associated with the formation of the North Atlantic Warming Hole and Atlantic Meridional Overturning Circulation collapse under CO 2 forcing. Our findings imply that understanding changes in North Atlantic SST patterns is important for constraining near-future and equilibrium global warming.
Jet noise far field spectra and directivity patterns of jet flow
Decade, yearly and monthly distributions of meteorite time-of-fall patterns are examined, noting departures from randomness
Patterns of high- and low-density ultracentrifugal lipoprotein distribution in healthy human population