High-resolution Observations of the Low Atmospheric Response to Small Coronal Heating Events in an Active Region Core
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Data from the Voyager 1 infrared spectroscopy investigation have been used to retrieve temperature profiles in the atmosphere of Jupiter. An analysis of information content indicates good vertical resolution with low measurement noise propagation in the Jovian troposphere and reduced resolution in the stratosphere. Among the problems found in common with the sounding of the terrestrial atmosphere are limited tropopause definition and dependence on upper boundary constraints. Preliminary results obtained by using a constrained linear algorithm and a filtered Chahine approach are presented.
Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.
The project consisted of two parts. The first was to obtain new low-dispersion, long-wavelength, high S/N IUE spectra of F-G-K dwarf stars with previously determined abundances, temperatures, and gravities. To insure high quality, the spectra are either trailed, or multiple exposures are taken within the large aperture. Second, the spectra are assembled into a library which combines the new data with existing IUE Archive data to yield mean spectral energy distributions for each important type of star. My principal responsibility is the construction and maintenance of this UV spectral library. It covers the spectral range 1200-3200A and is maintained in two parts: a version including complete wavelength coverage at the full spectral resolution of the Low Resolution cameras; and a selected bandpass version, consisting of the mean flux in pre-selected 20A bands. These bands are centered on spectral features or continuum regions of special utility - e.g. the C IV lambda 1550 or Mg II lambda 2800 feature. In the middle-UV region, special emphasis is given to those features (including continuum 'breaks') which are most useful in the study of F-G-K star spectra in the integrated light of old stellar populations.
Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.
Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high resolution spectral measurements may be too costly to perform on a large sample and therefore lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. In past work [1], we addressed this problem using Virtual Sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. We demonstrated this method by using models trained on the high spectral resolution Terra MODIS instrument to estimate what the equivalent of the MODIS 1.6 micron channel would be for the NOAA AVHRR2 instrument. The scientific motivation for the simulation of the 1.6 micron channel is to improve the ability of the AVHRR2 sensor to detect clouds over snow and ice. This work contains preliminary experiments demonstrating that the use of spatial information can improve our ability to estimate these spectra.
A major challenge of memory analysis tools is combining high-resolution analysis and low overhead measurement. Currently, hardware/software-based analysis of load-level sequences incurs time slowdowns of O(100×). We present MemGaze, a tool for low-overhead, high-resolution memory analysis. MemGaze uses Intel’s Processor Tracing (PT) instruction ptwrite to collect sampled and compressed memory address traces for load-level, sequence-aware analysis of data reuse. We describe multi-resolution analysis for locations vs. operations, accesses vs. spatio-temporal reuse, and reuse (distance, rate, volume) vs. access patterns. Both trace size and resolution are controllable. We use MemGaze to elucidate the memory effects of different data structures and algorithms. For sampled traces that are ˜1% of a full one, analysis metrics have 1-25% MAPE for histograms of varying dynamic sequence lengths. With current suboptimal kernel support (PT runs continuously), MemGaze’s time overhead is typically 10–95%; 7× at worst. However, when PT runs only during samples, overhead is 10–35% on memory intensive regions and correlates with executed ptwrites.
Lineloads serve a unique and important role in aerodynamic database development as well as configuration design and analysis. A new software suite was constructed which can compute lineloads rapidly enough that the calculations can run in tandem with high-fidelity fluid flow solvers. This enables the calculation of iteration- or time-dependent lineloads, which have thus far been too computationally costly to create for complicated systems like launch vehicles. The suite is organized into a standalone Python module named PCLAM (PCLAM Computes Lineloads And Moments) which can be imported into other software with minimal restructuring by the user or developer. The computed lineloads are integrated with a $C^0$ numerical quality and exhibit the expected sensitivity to underlying grid resolution. Even at low grid and lineload resolutions, the computed lineloads were found to be in strong agreement with several analytical test cases.
Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K −1 , which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.
Observations to characterize planets larger than Earth but smaller than Neptune have led to largely inconclusive interpretations at low spectral resolution due to hazes or clouds that obscure molecular features in their spectra. However, here we show that high-resolution spectroscopy (R ∼ 25,000–100,000) enables one to probe the regions in these atmospheres above the clouds where the cores of the strongest spectral lines are formed. We present models of transmission spectra for a suite of GJ 1214b–like planets with thick photochemical hazes covering 1–5 μm at a range of resolutions relevant to current and future ground-based spectrographs. Furthermore, we compare the utility of the cross-correlation function that is typically used with a more formal likelihood-based approach, finding that only the likelihood-based method is sensitive to the presence of haze opacity. We calculate the signal-to-noise ratio (S/N) of these spectra, including telluric contamination, Required to robustly detect a host of molecules such as CO, CO{sub 2}, H{sub 2}O, and CH{sub 4} and photochemical products like HCN as a function of wavelength range and spectral resolution. Spectra in the M band require the lowest S/N{sub res} to detect multiple molecules simultaneously. CH{sub 4} is only observable for the coolest models (T {sub eff} = 412 K) and only in the L band. We quantitatively assess how these requirements compare to what is achievable with current and future instruments, demonstrating that characterization of small cool worlds with ground-based high-resolution spectroscopy is well within reach.
High resolution very low altitude maps of a quiescent filament at three frequencies are presented. The spatial resolution (approx. 15" at 1.45 GHz, approx. 6" at 4.9 GHz, and approx. 2" at 15 GHz) is several times better than previously attained. At each frequency, the filament appears as a depression in the quiet Sun background. The depression is measurably wider and longer in extent than the corresponding H alpha filament at 1.45 GHz and 4.9 GHz, indicating that the depression is due in large part to a deficit in coronal density associated with the filament channel. In contrast, the shape of the radio depression at 15 CHz closely matches that of the H alpha filament. In addition, the 15 GHz map shows enhanced emission along both sides of the radio depression. A similar enhancement is seen in an observation of a second filament 4 days later, which suggests that the enhancement is a general feature of filaments. Possible causes of the enhanced emission are explored.
Recent advancements in composite materials technologies have broken further from traditional designs and require advanced instrumentation and analysis capabilities. Success or failure is highly dependent on design analysis and manufacturing processes. By monitoring smart structures throughout manufacturing and service life, residual and operational stresses can be assessed and structural integrity maintained. Composite smart structures can be manufactured by integrating fiber optic sensors into existing composite materials processes such as ply layup, filament winding and three-dimensional weaving. In this work optical fiber was integrated into 3D woven composite parts at a commercial woven products manufacturing facility. The fiber was then used to monitor the structures during a VARTM manufacturing process, and subsequent static and dynamic testing. Low cost telecommunications-grade optical fiber acts as the sensor using a high resolution commercial Optical Frequency Domain Reflectometer (OFDR) system providing distributed strain measurement at spatial resolutions as low as 2mm. Strain measurements using the optical fiber sensors are correlated to resistive strain gage measurements during static structural loading. Keywords: fiber optic, distributed strain sensing, Rayleigh scatter, optical frequency domain reflectometry
The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.
To identify the molecular composition of the low-energy states in cyanobacterial Photosystem I (PSI) of Synechocystis PCC6803, we focus on high resolution (low-temperature) absorption, emission, resonant, and nonresonant hole burned spectra obtained for wild-type (WT) PSI and three PSI mutants. In the Red_a mutant, the B33 chlorophyll (Chl) is added to the B31-B32 dimer; in Red_b, histidine 95 (His95) on PsaB (which coordinates Mg in the B7 Chl within the His95-B7-A31-A32- cluster) is replaced with glutamine (Gln), while in the Red_ab mutant, both mutations are made. We show that the C706 state (B31-B32) changes to the C710 state (B31-B32-B33) in both Red_a and Red_ab mutants, while the C707 state in WT Synechocystis (localized on the His95-B7-A31-A32 cluster) is modified to C716 in both Red_b and Red_ab. Excitation energy transfer from C706 to the C714 trap in the WT PSI and Red_b mutant is hampered as reflected by a weak emission at 712 nm. Large electron-phonon coupling strength (exposed via resonant hole-burned spectra) is consistent with a strong mixing of excited states with intermolecular charge transfer states leading to significantly red-shifted emission spectra. We conclude that excitation energy transfer in PSI is controlled by fine-tuning the electronic states of a small number of highly conserved red states. Finally, we show that mutations modify the protein potential energy landscape as revealed by different shapes and shifts of the blue- and red-shifted antiholes.
Solving power system capacity expansion planning (CEP) problems at realistic spatial resolutions is computationally challenging. Thus, a common practice is to solve CEP over zonal models with low spatial resolution rather than over full-scale nodal power networks. Due to improvements in solving large-scale stochastic mixed integer programs, these computational limitations are becoming less relevant, and the assumption that zonal models are realistic and useful approximations of nodal CEP is worth revisiting. Here, this work is the first to conduct a systematic computational study on the assumption that spatial aggregation can reasonably be used for ISO-scale CEP. By considering a realistic, large-scale test network based on the state of California with over 8000 buses, we find that well-designed small spatial aggregations can yield good approximations but that coarser zonal models may result in large distortions of investment decisions, e.g., capacity under-investment of up to 41% for the lowest resolution model considered.
In a series of papers presented in 1994, we examined the grayscale/resolution trade-off for natural images displayed on devices with discrete pixellation, such as AMLCD's. In the present paper we extend this study by examining the grayscale/resolution trade-off for text images on discrete-pixel displays. Halftoning in printing is an example of the grayscale/resolution trade-off. In printing, spatial resolution is sacrificed to produce grayscale. Another example of this trade-off is the inherent low-pass spatial filter of a CRT, caused by the point-spread function of the electron beam in the phosphor layer. On a CRT, sharp image edges are blurred by this inherent low-pass filtering, and the block noise created by spatial quantization is greatly reduced. A third example of this trade-off is text anti-aliasing, where grayscale is used to improve letter shape, size and location when rendered at a low spatial resolution. There are additional implications for display system design from the grayscale/resolution trade-off. For example, reduced grayscale can reduce system costs by requiring less complexity in the framestore, allowing the use of lower cost drivers, potentially increasing data transfer rates in the image subsystem, and simplifying the manufacturing processes that are used to construct the active matrix for AMLCD (active-matrix liquid-crystal display) or AMTFEL (active-matrix thin-film electroluminescent) devices. Therefore, the study of these trade-offs is important for display designers and manufacturing and systems engineers who wish to create the highest performance, lowest cost device possible. Our strategy for investigating this trade-off is to generate a set of simple test images, manipulate grayscale and resolution, predict discrimination performance using the ViDEOS(Sarnoff) Human Vision Model, conduct an empirical study of discrimination using psychophysical procedures, and verify the computational results using the psychophysical results.
Acquiring pressure maps of aerodynamic surfaces is very important for improving and validating the performance of aerospace vehicles. Traditional pressure measurements are taken with pressure taps embedded in the model surface that are connected to transducers. While pressure taps allow highly accurate measurements to be acquired, they do have several drawbacks. Pressure taps do not give good spatial resolution due to the need for individual pressure tubes, compounded by limited space available inside models. Also, building a model proves very costly if taps are needed because of the large amount of labor necessary to drill, connect and test each one. The typical cost to install one tap is about $200. Recently, a new method for measuring pressure on aerodynamic surfaces has been developed utilizing a technology known as pressure sensitive paints (PSP). Using PSP, pressure distributions can be acquired optically with high spatial resolution and simple model preparation. Flow structures can be easily visualized using PSP, but are missed using low spatial resolution arrays of pressure taps. PSP even allows pressure distributions to be found on rotating machinery where previously this has been extremely difficult or even impossible. The goal of this research is to develop a laser scanning system for use with pressure sensitive paints that allows accurate pressure measurements to be obtained on various aerodynamic surfaces ranging from wind tunnel models to high speed jet engine compressor blades.
Acquiring pressure maps of aerodynamic surfaces is very important for improving and validating the performance of aerospace vehicles. Traditional pressure measurements are taken with pressure taps embedded in the model surface that are connected to transducers. While pressure taps allow highly accurate measurements to be acquired, they do have several drawbacks. Pressure taps do not give good spatial resolution due to the need for individual pressure tubes, compounded by limited space available inside models. Also, building a model proves very costly if taps are needed because of the large amount of labor necessary to drill, connect and test each one. The typical cost to install one tap is about $200. Recently, a new method for measuring pressure on aerodynamic surfaces has been developed utilizing a technology known as pressure sensitive paints (PSP). Using PSP, pressure distributions can be acquired optically with high spatial resolution and simple model preparation. Flow structures can be easily visualized using PSP, but are missed using low spatial resolution arrays of pressure taps. PSP even allows pressure distributions to be found on rotating machinery where previously this has been extremely difficult or even impossible. The goal of this research is to develop a laser scanning system for use with pressure sensitive paints that allows accurate pressure measurements to be obtained on various aerodynamic surfaces ranging from wind tunnel models to high speed jet engine compressor blades.