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At least 1,387 records · Page 77

Piloted Simulation of Various Synthetic Vision Systems Terrain Portrayal and Guidance Symbology Concepts for Low Altitude En-Route Scenario

In support of the NASA Aviation Safety Program's Synthetic Vision Systems Project, a series of piloted simulations were conducted to explore and quantify the relationship between candidate Terrain Portrayal Concepts and Guidance Symbology Concepts, specific to General Aviation. The experiment scenario was based on a low altitude en route flight in Instrument Metrological Conditions in the central mountains of Alaska. A total of 18 general aviation pilots, with three levels of pilot experience, evaluated a test matrix of four terrain portrayal concepts and six guidance symbology concepts. Quantitative measures included various pilot/aircraft performance data, flight technical errors and flight control inputs. The qualitative measures included pilot comments and pilot responses to the structured questionnaires such as perceived workload, subjective situation awareness, pilot preferences, and the rare event recognition. There were statistically significant effects found from guidance symbology concepts and terrain portrayal concepts but no significant interactions between them. Lower flight technical errors and increased situation awareness were achieved using Synthetic Vision Systems displays, as compared to the baseline Pitch/Roll Flight Director and Blue Sky Brown Ground combination. Overall, those guidance symbology concepts that have both path based guidance cue and tunnel display performed better than the other guidance concepts.

Takallu, M. A.↗

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗

Exploiting Molecular Weight Distribution Shape to Tune Domain Spacing in Block Copolymer Thin Films

We report a method for tuning the domain spacing ( D sp ) of self-assembled block copolymer thin films of poly(styrene-block-methyl methacrylate) (PS- b -PMMA) over a large range of lamellar periods. By modifying the molecular weight distribution (MWD) shape (including both the breadth and skew) of the PS block via temporal control of polymer chain initiation in anionic polymerization, we observe increases of up to 41% in D sp for polymers with the same overall molecular weight ( M n ≈ 125 kg mol –1 ) without significantly changing the overall morphology or chemical composition of the final material. In conjunction with our experimental efforts, we have utilized concepts from population statistics and least-squares analysis to develop a model for predicting D sp based on the first three moments of the MWDs. This statistical model reproduces experimental D sp values with high fidelity (with mean absolute errors of 1.2 nm or 1.8%) and provides novel physical insight into the individual and collective roles played by the MWD moments in determining this property of interest. As a result, this work demonstrates that both MWD breadth and skew have a profound influence over D sp , thereby providing an experimental and conceptual platform for exploiting MWD shape as a simple and modular handle for fine-tuning D sp in block copolymer thin films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of modular analytical wake models to the Lillgrund wind plant

Efficient and accurate wake models are required for wind plant performance modeling and the suite of engineering processes that support wind plant layout, control, and monitoring. Although many analytical and engineering wake models with low computational costs have been proposed, their ability to represent the power production of large wind plants in a wide range of atmospheric conditions is not completely understood. The following validation study reviews the underlying theory for analytical wake models, outlines quality control procedures for observational data, and compares model results with observational data from the Lillgrund Wind Plant. Lillgrund makes a valuable case study for wake modeling because of its regular arrangement and the relatively close spacing of constituent wind turbines, which lead to regular and significant wake interactions within the wind plant and the development of deep array flow conditions. Formulations for the velocity deficit, wake-added turbulence, and wake superposition methods are considered in a modular sense, yielding many possible configurations to represent wind turbine wakes, of which seven are examined in detail. Velocity deficit models that account for flow conditions in the near wake are better able to reproduce power production for wind turbines in the transitional region of the wind plant, where wind turbines experience as many as five wakes from upstream turbines. Finally, in the deep array, where power production reaches asymptotic values and wake statistics become quasi-periodic, wake superposition schemes become the largest driver in error reduction; using the linear or maximum wake superposition methods can reduce the relative root mean square error by as much as 40% in the deep array.

17 WIND ENERGY↗

Quantifying and simulating the weather forecast uncertainty for advanced building control

Weather forecast uncertainty is unavoidable despite technological advancements. Accurately quantifying and modelling this uncertainty is essential for developing and comparing advanced building controllers. In this study, we present a structured approach using a first-order autoregressive model (AR(1)) to model uncertainty in ambient temperature and global solar irradiation (GHI) forecasts. We analyzed weather data from four cities and employed Jensen–Shannon divergence (JSD) to evaluate the similarity between synthetic and actual forecast errors. The average JSD values for temperature are 0.027 (Berkeley), 0.021 (Leuven), 0.018 (Berlin), and 0.008 (Oslo), and for GHI, the average JSD values are 0.016 (Berkeley), 0.058 (Leuven), and 0.013 (Berlin). The low JSD values indicate a high similarity between the synthetic and real forecast error distributions. Further, our approach successfully generates synthetic weather forecasts that mirror the statistical properties of actual forecasts. The implementation of our method for uncertain forecast generation is being added to the BOPTEST framework.

54 ENVIRONMENTAL SCIENCES↗

Improved lattice computation of proton decay matrix elements

In this paper, we present an improved result for the lattice computation of the proton decay matrix elements in N f = 2 + 1 QCD. In this study, by adopting the error reduction technique of all-mode-averaging, a significant improvement of the statistical accuracy is achieved for the relevant form factor of proton (and also neutron) decay on the gauge ensemble of N f = 2 + 1 domain-wall fermions with m π = 0.34 – 0.69 GeV on a 2.7 fm 3 lattice, as used in our previous work. We improve the total accuracy of matrix elements to 10–15% from 30–40% for p → πe + or from 20–40% for p → K$\bar{ν}$. The accuracy of the low-energy constants α and β in the leading-order baryon chiral perturbation theory (BChPT) of proton decay are also improved. The relevant form factors of p → π estimated through the “direct” lattice calculation from the three-point function appear to be 1.4 times smaller than those from the “indirect” method using BChPT with α and β . It turns out that the utilization of our result will provide a factor 2–3 larger proton partial lifetime than that obtained using BChPT. Lastly, we also discuss the use of these parameters in a dark matter model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models includes the characterization of patient-specific response with implications for treatment management and research study design.

60 APPLIED LIFE SCIENCES↗

Elimination LArTPC Simulation Uncertainty

Liquid Argon Time Projection Chambers (LArTPC) are essential for detecting muons and neutrinos by capturing electrons released during particle collisions, which drift toward wire planes under an electric field and induce currents measured to reconstruct particle paths. However, LArTPCs face challenges from effects such as electron-ion recombination, electron diffusion, and electron attenuation, complicating data simulation. The Short Baseline Neutrino (SNB) detector aims to measure neutrinos before oscillation occurs. To bridge the gap between simulation and actual data, we propose modifying the amplitude and width of signals on the TPC wires, addressing uncertainties by adjusting signal characteristics to better match observed data. A Gaussian fit to current waveforms produces hits with associated charge and width, and by comparing data and simulated values, discrepancies highlight areas where the model fails. Initial results indicate the current modification algorithm may increase divergence between simulation and data, necessitating further refinement. A discovered bug in the WireModMakeHist_plug.cpp file, which incorrectly computed simulation and data ratios, underscores the need for precise algorithm adjustments. Future work involves correcting code errors, fine-tuning the model, and conducting multiple simulation runs to enhance statistical confidence and reduce uncertainties, ultimately aiming for accurate LArTPC operation and reliable neutrino detection.

Mkrtchyan, Ka'ren↗

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗

Measuring the Properties of Dark Energy with Photometrically Classified Pan-STARRS Supernovae. I. Systematic Uncertainty from Core-collapse Supernova Contamination

The Pan-STARRS (PS1) Medium Deep Survey discovered over 5000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3147 of these likely SNe and estimate that ∼1000 are Type Ia SNe (SNe Ia) with light-curve quality sufficient for a cosmological analysis. We use these data with simulations to determine the impact of core-collapse SN (CC SN) contamination on measurements of the dark energy equation of state parameter, w. Using the method of Bayesian Estimation Applied to Multiple Species (BEAMS), distances to SNe Ia and the contaminating CC SN distribution are simultaneously determined. We test light-curve-based SN classification priors for BEAMS as well as a new classification method that relies upon host galaxy spectra and the association of SN type with host type. By testing several SN classification methods and CC SN parameterizations on large SN simulations, we estimate that CC SN contamination gives a systematic error on w (σ{sub w}{sup CC}) of 0.014, 29% of the statistical uncertainty. Our best method gives σ{sub w}{sup CC}=0.004, just 8% of the statistical uncertainty, but could be affected by incomplete knowledge of the CC SN distribution. This method determines the SALT2 color and shape coefficients, α and β, with ∼3% bias. However, we find that some variants require α and β to be fixed to known values for BEAMS to yield accurate measurements of w. Finally, the inferred abundance of bright CC SNe in our sample is greater than expected based on measured CC SN rates and luminosity functions.

79 ASTRONOMY AND ASTROPHYSICS↗

Microwave landing system requirements for STOL operations

The operational/functional requirements for the new Microwave Landing System (MLS) are examined for STOL operations. The study utilizes a nonlinear six-degree-of-freedom simulation of a De Havilland Buffalo C-8A aircraft and automatic flight control system to assess the MLS/STOL accuracy, coverage, and data rate requirements for the azimuth, DME, primary elevation, and flare elevation functions. The aircraft performance is statistically determined for representative curved flight paths through touchdown. A range of MLS errors and coverages, environmental disturbances, and navigation filtering are investigated. The study indicates that STOL applications do not place any unique requirements on the MLS.

Burrous, C. N.↗

Ultraviolet television data from the orbiting astronomical observatory. II - Stellar ultraviolet colors and interstellar extinction

The results from the Celescope Catalog of Ultraviolet Stellar Observations (Davis, Deutschman, and Haramundanis 1973) are studied, emphasizing statistical groups and subgroups of stars. In spite of the rather large observational errors, the great number of Celescope observations make it possible to do that kind of study with reasonable accuracy. Some stars have ultraviolet colors that differ significantly from those of the group to which they have been assigned on the basis of ground-based observations. An attempt is made to describe the general properties of the ultraviolet colors of the stars as observed by the Celescope experiment on board NASA's Orbiting Astronomical Observatory (OAO-2). Besides the direct applicability of these results to the general study of stellar atmospheres and of interstellar extinction, they are also considered as a frame of reference for further studies of individual stars and groups of stars.

Peytremann, E.↗

Digital preprocessing of SEASAT imagery

A model for radar image data is derived for use in developing enhancement techniques. This model describes the image data as the result of a multiplicative-convolved noise process. This information is then used to design a minimum mean square error (MMSE) filter. The resulting filter is implemented adaptively to change with local statistics. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure is thus developed. This technique has been implemented and tested using digitally correlated SEASAT-A synthetic aperture radar (SAR) imagery.

Frost, V. S.↗

Fine-scale motion in the central Orion nebula

The inner region of M42 has been mapped in the O III N1 forbidden line at an unprecedented combination of velocity and spatial resolution and photometric accuracy. Three separate velocity systems along the line of sight are identified. Differential mass flow is present in two of these systems. All three systems show random fluctuations in velocity well above their measurement errors. The point-by-point velocities are used to determine the diagnostic statistical parameter, the structure function. The random motions show correlation with spatial separation, as expected for turbulence; but comparison with the predictions of classical theory for nebular turbulence shows poor agreement. If Kolmogorov (1941, 1942) theory applies, then the energy must be input at many scales.

Castaneda, Hector O.↗

Performance of the image statistics decoder in conjunction with the Goldstone-VLA array

During Voyager's Neptune encounter, the National Radio Astronomy Observatory's Very Large Array (VLA) will be arrayed with Goldstone antennas to receive the transmitted telemetry data from the spacecraft. The telemetry signal from the VLA will drop out periodically, resulting in a periodic drop in the received signal-to-noise ratio (SNR). The Image Statistics Decoder (ISD), which assumes a correlation between pixels, can improve the bit error rate (BER) for images during these dropout periods. Simulation results have shown that the ISD, in conjunction with the Goldstone-VLA array can provide a 3-dB gain for uncompressed images at a BER of 5.0 x 10(exp -3).

Wang, H. C.↗

Advanced techniques and technology for efficient data storage, access, and transfer

Advanced techniques for efficiently representing most forms of data are being implemented in practical hardware and software form through the joint efforts of three NASA centers. These techniques adapt to local statistical variations to continually provide near optimum code efficiency when representing data without error. Demonstrated in several earlier space applications, these techniques are the basis of initial NASA data compression standards specifications. Since the techniques clearly apply to most NASA science data, NASA invested in the development of both hardware and software implementations for general use. This investment includes high-speed single-chip very large scale integration (VLSI) coding and decoding modules as well as machine-transferrable software routines. The hardware chips were tested in the laboratory at data rates as high as 700 Mbits/s. A coding module's definition includes a predictive preprocessing stage and a powerful adaptive coding stage. The function of the preprocessor is to optimally process incoming data into a standard form data source that the second stage can handle.The built-in preprocessor of the VLSI coder chips is ideal for high-speed sampled data applications such as imaging and high-quality audio, but additionally, the second stage adaptive coder can be used separately with any source that can be externally preprocessed into the 'standard form'. This generic functionality assures that the applicability of these techniques and their recent high-speed implementations should be equally broad outside of NASA.

Rice, Robert F.↗

Spectral eclipse mapping of the accretion disk in the nova-like variable UX Ursae Majoris

We analyze narrow-band eclipse light curves of the nova-like cataclysmic variable UX UMa, obtained from low-resolution spectra spanning lambda lambda 3600-9800 A . The light curves for narrow bands in the continuum as well as those for individual spectral lines are treated independently, and are used to construct images of the accretion disk's brightness distribution using the maximum-entropy eclipse-mapping technique. Particular attention is paid to the propagation of statistical uncertainties in the data and to how the analysis may introduce systematic errors in the final result. From the many narrrow band images we have reconstructed the spectra from isolated parts of the accretion disk. These spectra reveal that the inner disk radiates a continuum spectrum which peaks in the near UV and has the hydrogen Balmer lines in absorption (with the exception of H-alpha), whereas the outer disk is much fainter, has a much redder spectrum, and has Balmer emission lines. Our analysis reveals the presence of an uneclipsed component of the total light, whose spectrum is very red and has Balmer lines in emission. This unexpected feature of the eclipse mapping technique offers a new tool for an independent assessment of the secondary star's spectrum in eclipsing cataclysmic variables.

Rutten, R. G. M.↗

Reprocessing Microflare Data

The report concerns work on detecting and cataloging solar microflares using an automated. An accompanying figure represents the solar microflare distribution during the period of April 1991 to November 1992, the height of solar activity after the launch of CGRO. It also shows the distribution extending below the distribution obtained at GSFC by manual means. We have implemented significant refinements in the search algorithm. The algorithm in its simplest form searches for transient events and based upon the distribution of the signal among the different BATSE detectors, we can assign it to be of solar origin if the signal distribution conforms to what one expects from a burst or transient from that direction. One of the major problems in an earlier effort was to search for microflares and large flares simultaneously. The requirement for a dynamic range of almost 10(exp 4) resulted in ambiguous identifications at the low side of the distribution. We have since restricted the search to events with peak count rates under 2000/s. Larger events are easily identified in the manual search, so we have chosen not to duplicate that work. The second problem was that missing counts existed below channel 0 in the BATSE Large Area Detector (LAD) data. These have been recovered and are now included in the search process. This provides data below 20 keV, and as we get closer to the thermal part of the spectrum, it provides greater sensitivity. The third problem was that too many BATSE detectors were used in the search. Detectors with pointing directions far from the Sun, although detecting the event, had poorly known responses. Detectors greater than approximately 60 degrees off the Sun are no longer included in the search process. By reducing the systematic errors with the large off-axis detectors we can conduct more rigorous statistical tests of a candidate event to ascertain whether it originated from the solar direction. We have reprocessed the period in the early mission that covers solar maximum and constructed the microflare distribution shown in the figure. The results of the automated search start to deviate from the manual search results below about 1000/s. Not only do we now have this distribution but we have a database of solar microflares that was used to construct the distribution. This database contains the signal at higher energy channels as well as that in channel zero (and below). From this one can, using software at GSFC, construct a photon spectrum for some of the larger microflares. It can also be used in other solar studies, especially those that correlate the X-ray flux with emission at other wavelengths. With some additional effort we hope to integrate this database into the corresponding one residing at the Solar Data Analysis Center at GSFC. The entire CGRO mission's data can now be reprocessed to obtain the microflare distribution at all phases of the solar cycle. This work is in progress. The results of this work will be presented in forthcoming scientific workshops and conferences.

Ryan, James M.↗