SEARCH · Search NASA

Results for “spatial prediction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 829 records · Page 46

All sources NASA NTRS DOE OSTI

NASA NTRS1997

Bio-Optical Properties of the Arabian Sea as Determined by In Situ and Sea WiFS Data

The overall objective of this work was to characterize optical and fluorescence properties in the euphotic zone during two British Ocean Flux Study (BOFS) Arabian Sea cruises. This was later expanded in 1995 to include three U.S. JGOFS Arabian Sea Cruises. The region was to be divided into one or more "bio-optical provinces," within each of which a single set of regression models was to be developed to relate the vertical distribution of irradiance attenuation and normalized fluorescence (SF and NF) to remote sensing reflectance and diffuse attenuation coefficient. The working hypothesis was that over relatively large spatial and temporal scales, the vertical profiles of bio-optical properties were predictable. The specific technical objectives were: (1) To characterize the vertical distribution of the inherent and apparent optical properties by measuring downwelling and upwelling irradiances, upwelling radiances, scalar irradiance of PAR, and beam transmissions at each station - from these data, spectral diffuse attenuation coefficients, irradiance reflectances, remote sensing reflectances, surface-leaving radiances and beam attenuation coefficients were determined; (2) To characterize the spectral absorption of total particulate, detrital, and dissolved organic material at each station from discrete water samples; (3) To describe the vertical distribution of photoadaptive properties in the water column by measuring profiles of stimulated (SF) and natural (NF) fluorescence and examining relationships between SF and NF as a function of diffuse optical depth, pigment biomass and primary productivity; and (4) To establish locally derived, in-water algorithms relating remote sensing reflectance spectra to diffuse attenuation coefficients, phytoplankton pigment concentrations and primary productivity, through intercomparisons with in situ measurements, for application to SeaWiFS data.

Trees, Charles C.↗

NASA NTRS1998

Bio-Optical Properties of the Arabian Sea as Determined by In-Situ and SeaWifs Data

Trees, Charles C.↗

NASA NTRS1998

Remote Sensing of Tropospheric Aerosols from Space: Past, Present, and Future

Aerosol particles originate from man-made sources such as urban/industrial activities,rurning associated with land use processes, wind-blown dust, and natural sources. Their interaction with sunlight and their effect on cloud microphysics forms a major uncertainty in predicting climate change. Furthermore, the lifetime of only a few days causes high spatial variability in aerosol optical and radiative properties that requires global observations from space. Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sun-photometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

King, Michael D.↗

NASA NTRS2006

A Theoretical Investigation of Composite Overwrapped Pressure Vessel (COPV) Mechanics Applied to NASA Full Scale Tests

A theoretical investigation of the factors controlling the stress rupture life of the National Aeronautics and Space Agency's (NASA) composite overwrapped pressure vessels (COPVs) continues. Kevlar(TradeMark) fiber overwrapped tanks are of particular concern due to their long usage and the poorly understood stress rupture process in Kevlar(TradeMark) filaments. Existing long term data show that the rupture process is a function of stress, temperature and time. However, due to the presence of a load sharing liner, the manufacturing induced residual stresses and the complex mechanical response, the state of actual fiber stress in flight hardware and test articles is not clearly known. This paper is a companion to the experimental investigation reported in [1] and develops a theoretical framework necessary to design full-scale pathfinder experiments and accurately interpret the experimentally observed deformation and failure mechanisms leading up to static burst in COPVs. The fundamental mechanical response of COPVs is described using linear elasticity and thin shell theory and discussed in comparison to existing experimental observations. These comparisons reveal discrepancies between physical data and the current analytical results and suggest that the vessel's residual stress state and the spatial stress distribution as a function of pressure may be completely different from predictions based upon existing linear elastic analyses. The 3D elasticity of transversely isotropic spherical shells demonstrates that an overly compliant transverse stiffness relative to membrane stiffness can account for some of this by shifting a thin shell problem well into the realm of thick shell response. The use of calibration procedures are demonstrated as calibrated thin shell model results and finite element results are shown to be in good agreement with the experimental results. The successes reported here have lead to continuing work with full scale testing of larger NASA COPV hardware.

Greene, N.↗

NASA NTRS2008

An Overview of the Hurricane Imaging Radiometer (HIRAD)

Accurate observations of ocean surface vector winds (OSVW) with high spatial and temporal resolution are critically important to improve both our understanding and predictability of tropical cyclones. As the successful NASA QuikSCAT satellite continues to age beyond its planned life span, many members of the tropical cyclone research and operational community recognize the need to develop new observational technologies and strategies to meet the essential need for OSVW information. This concern has been expressed in both the "Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond" developed by the National Research Council Committee on Earth Science and Applications from Space and the "Interagency Strategic Research Plan for Tropical Cyclone The Way Ahead" developed by the Joint Action Group for Tropical Cyclone Research (JAG-TCR) sponsored by the Office of the Federal Coordinator for Meteorology. One innovative technology development which offers the potential for new, unique remotely sensed observations of tropical cyclone OSVW and precipitation is the Hurricane Imaging Radiometer (HIRAD). This new instrument is passive microwave synthetic thinned aperture radiometer under development at the NASA Marshall Space Flight Center that will operate at the C-Band frequencies of 4, 5, 6, and 7 GHz. These frequencies have been successfully demonstrated by the NOAA nadir-staring Stepped Frequency Microwave Radiometer (SFMR) as useful for monitoring tropical cyclone ocean surface wind speeds and rain rates from low altitude reconnaissance aircraft. The HIRAD design incorporates a unique antenna design as well as several technologies that have been successfully demonstrated by the University of Michigan Lightweight Rain Radiometer sponsored by NASA Earth Science Technology Office Instrument Incubator Program. HIRAD will be a compact, lightweight, low-power instrument with no moving parts that will produce imagery of ocean wind surface wind parameters and rain rate during the strong wind and heavy rain hurricane conditions that hamper the observational capabilities of higher frequency passive microwave radiometers or scatterometers. It will also produce imagery of sea surface temperature under cloudy and lightly precipitating skies eliminating the need for additional thermal infrared imagers. The strategic plan for HIRAD includes a roadmap for ocean surface wind speed and OSVW technology development using flight demonstrations on piloted aircraft, uninhabited aerial vehicle systems, and satellite platforms. The roadmap will include exit opportunities for technology transfer from research to operations based on satisfactory demonstrations. The first aircraft version of HIRAD will be singular polarization sensor designed to observe ocean surface wind speed and rainfall. The second aircraft version of HIRAD will be dual polarization sensor designed to observe OSVW as a prototype for a future satellite sensor.

Source record↗

NASA NTRS2009

A Theoretical Investigation of Composite Overwrapped Pressure Vessel (COPV) Mechanics Applied to NASA Full Scale Tests

A theoretical investigation of the factors controlling the stress rupture life of the National Aeronautics and Space Administration's (NASA) composite overwrapped pressure vessels (COPVs) continues. Kevlar (DuPont) fiber overwrapped tanks are of particular concern due to their long usage and the poorly understood stress rupture process in Kevlar filaments. Existing long term data show that the rupture process is a function of stress, temperature and time. However due to the presence of a load sharing liner, the manufacturing induced residual stresses and the complex mechanical response, the state of actual fiber stress in flight hardware and test articles is not clearly known. This paper is a companion to a previously reported experimental investigation and develops a theoretical framework necessary to design full-scale pathfinder experiments and accurately interpret the experimentally observed deformation and failure mechanisms leading up to static burst in COPVs. The fundamental mechanical response of COPVs is described using linear elasticity and thin shell theory and discussed in comparison to existing experimental observations. These comparisons reveal discrepancies between physical data and the current analytical results and suggest that the vessel s residual stress state and the spatial stress distribution as a function of pressure may be completely different from predictions based upon existing linear elastic analyses. The 3D elasticity of transversely isotropic spherical shells demonstrates that an overly compliant transverse stiffness relative to membrane stiffness can account for some of this by shifting a thin shell problem well into the realm of thick shell response. The use of calibration procedures are demonstrated as calibrated thin shell model results and finite element results are shown to be in good agreement with the experimental results. The successes reported here have lead to continuing work with full scale testing of larger NASA COPV hardware.

Thesken, John C.↗

NASA NTRS2010

Excitation of Crossflow Instabilities in a Swept Wing Boundary Layer

The problem of crossflow receptivity is considered in the context of a canonical 3D boundary layer (viz., the swept Hiemenz boundary layer) and a swept airfoil used recently in the SWIFT flight experiment performed at Texas A&M University. First, Hiemenz flow is used to analyze localized receptivity due to a spanwise periodic array of small amplitude roughness elements, with the goal of quantifying the effects of array size and location. Excitation of crossflow modes via nonlocalized but deterministic distribution of surface nonuniformity is also considered and contrasted with roughness induced acoustic excitation of Tollmien-Schlichting waves. Finally, roughness measurements on the SWIFT model are used to model the effects of random, spatially distributed roughness of sufficiently small amplitude with the eventual goal of enabling predictions of initial crossflow disturbance amplitudes as functions of surface roughness parameters.

Carpenter, Mark H.↗

NASA NTRS2010

ARCADE 2 Observations of Galactic Radio Emission

We use absolutely calibrated data from the Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission (ARCADE 2) flight in July 2006 to model Galactic emission at frequencies 3, 8, and 10 GHz. The spatial structure in the data is consistent with a superposition of free-free and synchrotron emission. Emission with spatial morphology traced by the Haslam 408 MHz survey has spectral index beta_synch = -2.5 +/- 0.1, with free-free emission contributing 0.10 +/- 0.01 of the total Galactic plane emission in the lowest ARCADE 2 band at 3.15 GHz. We estimate the total Galactic emission toward the polar caps using either a simple plane-parallel model with csc|b| dependence or a model of high-latitude radio emission traced by the COBE/FIRAS map of CII emission. Both methods are consistent with a single power-law over the frequency range 22 MHz to 10 GHz, with total Galactic emission towards the north polar cap T_Gal = 0.498 +/- 0.028 K and spectral index beta = -2.55 +/- 0.03 at reference frequency 0.31 GHz. The well calibrated ARCADE 2 maps provide a new test for spinning dust emission, based on the integrated intensity of emission from the Galactic plane instead of cross-correlations with the thermal dust spatial morphology. The Galactic plane intensity measured by ARCADE 2 is fainter than predicted by models without spinning dust, and is consistent with spinning dust contributing 0.4 +/- 0.1 of the Galactic plane emission at 23 GHz.

Kogut, A.↗

DOE OSTI2024

Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0

Abstract. The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations.

58 GEOSCIENCES↗

DOE OSTI2019

Spatial scale affects novel and disappeared climate change projections in Alaska

The formation of novel and disappeared climates between the last glacial maximum (LGM) and the present is important to consider to understand the expansion and contraction of species niches and distributions, as well as the formation and loss of communities and ecological interactions over time. Our choice in climate data resolution has the potential to complicate predictions of the ecological impacts of climate change, since climate varies from local to global scales and this spatial variation is reflected in climate data. To address this issue, we downscaled LGM and modern (1975–2005) 30-year averaged climate data to 60-m resolution for the entire state of Alaska for 10 different climate variables, and then upsampled each variable to coarser resolutions (60 m to 12 km). We modeled the distributions of novel and disappeared climates to evaluate the locations and fractional area of novel and disappeared climates for each of our climate variables and resolutions. Generally, novel and disappeared climates were located in southern Alaska, although there were cases where some disappeared climates existed within coastal and interior Alaska. Climate resolution affected the fractional area of novel and disappeared climates in three patterns: As the spatial resolution of climate became coarser, the fractional area of novel and disappeared climates (a) increased, (b) decreased, or (c) had no explainable relationship. Overall, we found the use of coarser climate data increased the fractional area of novel and disappeared climates due to decreased environmental variability and removal of climate extremes. Our results reinforce the importance of downscaling coarse climate data and suggest that studies analyzing the effects of climate change on ecosystems may overestimate or underestimate their conclusions when utilizing coarse climate data.

Alaska↗

NASA NTRS2005

Dynamic wake prediction and visualization with uncertainty analysis

A dynamic wake avoidance system utilizes aircraft and atmospheric parameters readily available in flight to model and predict airborne wake vortices in real time. A novel combination of algorithms allows for a relatively simple yet robust wake model to be constructed based on information extracted from a broadcast. The system predicts the location and movement of the wake based on the nominal wake model and correspondingly performs an uncertainty analysis on the wake model to determine a wake hazard zone (no fly zone), which comprises a plurality of wake planes, each moving independently from another. The system selectively adjusts dimensions of each wake plane to minimize spatial and temporal uncertainty, thereby ensuring that the actual wake is within the wake hazard zone. The predicted wake hazard zone is communicated in real time directly to a user via a realistic visual representation. In an example, the wake hazard zone is visualized on a 3-D flight deck display to enable a pilot to visualize or see a neighboring aircraft as well as its wake. The system substantially enhances the pilot's situational awareness and allows for a further safe decrease in spacing, which could alleviate airport and airspace congestion.

Holforty, Wendy L.↗

DOE OSTI2025

Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots

The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain-cropped land in the United States (US) as local markets developed for this high-yielding perennial grass (10–30 Mg DM ha −1 ). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing-derived vegetation indices to ground truth data from 105 hand-harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high-resolution satellite-sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha −1 ) and net profits ($\$$83 to $\$$1211.5 ha −1 ) was observed. All fields were profitable in all site-years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $\$$130 Mg −1 varied from 9.0–12.1 Mg ha −1 at 15% moisture content (7.6–10.3 Mg DM ha −1 ). Breakeven prices ranged from $\$$73 to $\$$122.4 Mg −1 , matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial-scale M × g production.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Multiscale Dynamics of Reactive Fronts in the Subsurface

Understanding and predicting flow and reactive transport in rocks (i.e. geologic porous media) is critical to many technologies at the heart of the energy transition, including CO 2 sequestration and H2 storage. However, accurate modeling and prediction of these systems is very complex because physico-chemical processes that occur at very small spatial scales, i.e. in the pores of the rocks, can dramatically control the system performance at the field scale (km). For example, precipitation reactions at the pore-scale can lead to large permeability changes at the field scale and dramatically alter the migration of stored gases. Properly accounting for multi-scale coupling effects is critical to achieve predictivity and confidence in model outputs, which then can guide design and optimization at the system-scale. This can be achieved through the development of rigorous mathematical models that can appropriately account for fine-scale effects at the large scale. The final report of the Early Career award DE-SC0019075 “Multiscale dynamics of reactive fronts in the subsurface” summarizes the mathematical, numerical and experimental advancements to study and predict reactive transport in geologic porous media across scales.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shockwave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantification↗

DOE OSTI2025

Equivariant Graph Attention Network - 3D Conformers & Feature Fusion

EGAN-3F (Equivariant Graph Attention Network - 3D Conformers & Feature Fusion) presents an innovative approach for predicting binding affinity between small molecules and protein targets, a fundamental task in drug discovery. Traditional structure-based methods often depend on protein-ligand complex structures obtained from crystallography or molecular docking. In contrast, ligand-only machine learning models using 1D or 2D representations such as SMILES have been developed to predict binding affinity without structural information about the target; however, their accuracy is often limited due to the lack of 3D ligand information. EGAN-3F addresses this limitation by integrating spatially aware graph learning with traditional descriptor-based features. We systematically investigate how combining 2D and 3D molecular representations enhances binding affinity prediction from SMILES strings. This approach underscores the importance of modeling conformational diversity and incorporating chemically meaningful descriptors to improve predictive accuracy. The key innovation of EGAN-3F lies in its ability to achieve robust ligand-based binding affinity predictions without requiring protein-ligand complex structures, effectively bridging the gap between purely structural and ligand-only modeling paradigms.

Shim, Heesung [Lawrence Livermore National Laborat↗

DOE OSTI2020

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Hardware-Based Emulator with Deep Learning Model for Building Energy Control and Prediction Based on Occupancy Sensors’ Data

Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber-physical system (CPS). In this paper, we aim to build a hardware-based emulation platform to study the occupancy data’s features, which can be further extracted by using machine learning models. In particular, we propose two hardware-based emulators to investigate the use of wired/wireless communication interfaces for occupancy sensor-based building CPS control, and the use of deep learning to predict the building energy consumption with the sensor data. We hypothesize is that the building energy consumption may be predicted by using the occupancy data collected by the sensors, and question what type of prediction model should be used to accurately predict the energy load. Another hypothesis is that an in-lab hardware/software platform could be built to emulate the occupancy sensing process. The machine learning algorithms can then be used to analyze the energy load based on the sensing data. To test the emulator, the occupancy data from the sensors is used to predict energy consumption. The synchronization scheme between sensors and the HVAC server will be discussed. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies, and used an enhanced deep learning model—which has sequence-to-sequence long short-term memory (Seq2Seq LSTM)—with an attention model to predict the building energy consumption with the preservation of the intrinsic patterns. Because the long-range temporal dependencies are captured, the Seq2Seq models may provide a higher accuracy by using LSTM architectures with encoder and decoder. Meanwhile, LSTMs can capture the temporal and spatial patterns of time series data. The attention model can highlight the most relevant input information in the energy prediction by allocating the attention weights. The communication overhead between the sensors and the HVAC control server can also be alleviated via the attention mechanism, which can automatically ignore the irrelevant information and amplify the relevant information during CNN training. Our experiments and performance analysis show that, compared with the traditional LSTM neural network, the performance of the proposed method has a 30% higher prediction accuracy.

Ye, Zhijing↗

NASA NTRS1993

New techniques for reversible compression of multispectral data

While spatial correlations are adequately exploited by standard lossless image compression techniques, little success has been attained in exploiting spectral correlations when dealing with multispectral image data. In this paper, we present some new lossless image compression techniques that capture spectral correlations as well as spatial correlation in a simple and elegant manner. The schemes are based on the notion of a prediction tree, which defines a non-causal prediction model for an image. We present a backward adaptive technique and a forward adaptive technique. We then give a computationally efficient way of approximating the backward adaptive technique. The approximation gives good results and is extremely easy to compute. Simulation results show that for high spectral resolution images, significant savings can be made by using spectral correlations in addition to spatial correlations. Furthermore, the increase in complexity incurred in order to make these gains is minimal.

Memon, N. D.↗