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At least 721 records · Page 40

Large Scale Caching and Streaming of Training Data for Online Deep Learning

The training of deep neural network models on large data remains a difficult problem, despite progress towards scalable techniques. In particular, there is a mismatch between the random but predetermined order in which AI flows select training samples and the streaming I/O patterns for which traditional HPC data storage (e.g., parallel file systems) are designed. In addition, as more data are obtained, it is feasible neither simply to train learning models incrementally, due to catastrophic forgetting (i.e., bias towards new samples), nor to train frequently from scratch, due to prohibitive time and/or resource constraints. In this paper, we study data management techniques that combine caching and streaming with rehearsal support in order to enable efficient access to training samples in both offline training and continual learning. We revisit state-of-art streaming approaches based on data pipelines that transparently handle prefetching, caching, shuffling, and data augmentation, and discuss the challenges and opportunities that arise when combining these methods with data-parallel training techniques. We also report on preliminary experiments that evaluate the I/O overheads involved in accessing the training samples from a parallel file system (PFS) under several concurrency scenarios, highlighting the impact of the PFS on the design of the data pipelines.

data pipelines↗

AutoFocus: AI-driven alignment of nanofocusing X-ray mirror systems

We describe the application of an AI-driven system to autonomously align complex x-ray-focusing mirror systems, including mirrors systems with variable focus spot sizes. The system has been developed and studied on a digital twin of nanofocusing X-ray beamlines, built using advanced optical simulation tools calibrated with wavefront sensing data collected at the beamline. We experimentally demonstrated that the system is reliably capable of positioning a focused beam on the sample, both by simulating the variation of a beamline with random perturbations due to typical changes in the light source and optical elements over time, and by conducting similar tests on an actual focusing mirror system.

47 OTHER INSTRUMENTATION↗

A method for determining the preferred orientation of crystallites normal to a surface

It is pointed out that in principle all of the preferred-orientation information for the direction normal to a surface will be contained in the intensity differences between X-ray diffraction peaks for a sample with a preferred orientation and one with a fully random crystallite orientation. An experimental investigation is discussed along with questions regarding the procedure used in the evaluation process.

Snyder, R. L.↗

Coronary heart disease index based on longitudinal electrocardiography

A coronary heart disease index was developed from longitudinal ECG (LCG) tracings to serve as a cardiac health measure in studies of working and, essentially, asymptomatic populations, such as pilots and executives. For a given subject, the index consisted of a composite score based on the presence of LCG aberrations and weighted values previously assigned to them. The index was validated by correlating it with the known presence or absence of CHD as determined by a complete physical examination, including treadmill, resting ECG, and risk factor information. The validating sample consisted of 111 subjects drawn by a stratified-random procedure from 5000 available case histories. The CHD index was found to be significantly more valid as a sole indicator of CHD than the LCG without the use of the index. The index consistently produced higher validity coefficients in identifying CHD than did treadmill testing, resting ECG, or risk factor analysis.

Townsend, J. C.↗

Application of information theory to the design of line-scan imaging systems

Information theory is used to formulate a single figure of merit for assessing the performance of line scan imaging systems as a function of their spatial response (point spread function or modulation transfer function), sensitivity, sampling and quantization intervals, and the statistical properties of a random radiance field. Computational results for the information density and efficiency (i.e., the ratio of information density to data density) are intuitively satisfying and compare well with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV systems.

Huck, F. O.↗

Space infrared telescope pointing control system. Infrared telescope tracking in the presence of target motion

The use of charge-coupled-devices, or CCD's, has been documented by a number of sources as an effective means of providing a measurement of spacecraft attitude with respect to the stars. A method exists of defocussing and interpolation of the resulting shape of a star image over a small subsection of a large CCD array. This yields an increase in the accuracy of the device by better than an order of magnitude over the case when the star image is focussed upon a single CCD pixel. This research examines the effect that image motion has upon the overall precision of this star sensor when applied to an orbiting infrared observatory. While CCD's collect energy within the visible spectrum of light, the targets of scientific interest may well have no appreciable visible emissions. Image motion has the effect of smearing the image of the star in the direction of motion during a particular sampling interval. The presence of image motion is incorporated into a Kalman filter for the system, and it is shown that the addition of a gyro command term is adequate to compensate for the effect of image motion in the measurement. The updated gyro model is included in this analysis, but has natural frequencies faster than the projected star tracker sample rate for dim stars. The system state equations are reduced by modelling gyro drift as a white noise process. There exists a tradeoff in selected star tracker sample time between the CCD, which has improved noise characteristics as sample time increases, and the gyro, which will potentially drift further between long attitude updates. A sample time which minimizes pointing estimation error exists for the random drift gyro model as well as for a random walk gyro model.

Powell, J. D.↗

Machine-z: Rapid Machine-Learned Redshift Indicator for Swift Gamma-Ray Bursts

Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the Hubble expansion. Rapid selection of high-z candidates from GRB samples reported in real time by dedicated space missions such as Swift is the key to identifying the most distant bursts before the optical afterglow becomes too dim to warrant a good spectrum. Here, we introduce 'machine-z', a redshift prediction algorithm and a 'high-z' classifier for Swift GRBs based on machine learning. Our method relies exclusively on canonical data commonly available within the first few hours after the GRB trigger. Using a sample of 284 bursts with measured redshifts, we trained a randomized ensemble of decision trees (random forest) to perform both regression and classification. Cross-validated performance studies show that the correlation coefficient between machine-z predictions and the true redshift is nearly 0.6. At the same time, our high-z classifier can achieve 80 per cent recall of true high-redshift bursts, while incurring a false positive rate of 20 per cent. With 40 per cent false positive rate the classifier can achieve approximately 100 per cent recall. The most reliable selection of high-redshift GRBs is obtained by combining predictions from both the high-z classifier and the machine-z regressor.

gamma-ray burst: general↗

Aliasing and blurring in 2-D sampled imagery

The quality of image reconstructions from discrete data suffers not only from the blurring of spatial detail caused by limitations in the spatial frequency response of electrooptical systems, but also from the aliasing generated if spatial detail has been undersampled. Previous studies have observed that reasonable spot intensity profiles and photosensor aperture shapes of equivalent size result in about equal blurring but that some profiles and shapes suppress aliasing better than others. This paper presents quantitative results of the magnitude of aliasing and blurring as a function of random radiance fields typical for natural scenes and of spatial responses and sampling intervals typical for TV cameras and optical-mechanical scanners. These results indicate that aliasing may often be a larger source of degradation than either blurring or electronic noise.

Huck, F. O.↗

Accelerating multicanonical sampling with irreversibility

Flat-histogram Monte Carlo simulations are well-established, robust methods to perform random walks in a physical observable or parameter space, making them suitable for finding ground states or studying phase transitions in complex systems in statistical physics. However, their efficiency can be limited by the time to attain the desired flat distribution, which is generally unknown prior to the simulations. In particular, they might suffer from slowing down towards the end of a simulation due to the diffusive nature of random walks. In this work we apply irreversibility to the multicanonical Monte Carlo method via the lifting approach to alleviate this behavior. We achieve a 2–4 times speedup in ground-state search for a two-dimensional (2D) Ising model, and up to an order of magnitude of speedup for finding the ground-state energy in an Edwards–Anderson spin glass, compared to traditional multicanonical sampling. In conclusion, the round-trip times between ground states show a narrower distribution and are significantly shorter compared to the reversible counterpart, suggesting that a lower convergence time with a smaller time variance is feasible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Detection of signals by weighted integrate-and-dump filter

A Weighted Integrate and Dump Filter (WIDF) is presented that results in reducing those losses in telemetry symbol signal to noise ratio (SNR) which occur in digital Integrate and Dump Filters (IDFs) when the samples are not phase locked to the input data symbol clock. The Minimum Mean Square Error (MMSE) criterion is used to derive a set of weights for approximating the analog integrate and dump filter, which is the matched filter for detection of signals in additive white Gaussian noise. This new digital matched filter results in considerable performance improvement compared to unweighted digital matched filters. An example is presented for a sampling rate of four times the symbol rate. As the sampling offset (or phase) varies with respect to the data symbol boundaries, the output SNR varies 1 dB for an unweighted IDF, but only 0.3 dB for the optimum WIDF, averaged over random data patterns. This improvement in performance relative to unweighted IDF means that significantly lower sampling and processing rates can be used for given telemetry symbol rates, resulting in reduced system cost.

Sadr, R.↗

Evaluation of Treadmill Exercise in a Lower Body Negative Pressure Chamber as a Countermeasure for Weightlessness-Induced Bone Loss: a Bed Rest Study with Identical Twins

Counteracting bone loss is required for future space exploration. We evaluated the ability of treadmill exercise in a LBNP chamber to counteract bone loss in a 30-day bed rest study. Eight pairs of identical twins were randomly assigned to sedentary control or exercise groups. Exercise within LBNP decreased the bone resorption caused by bed rest and may provide a countermeasure for spaceflight. INTRODUCTION: Bone loss is one of the greatest physiological challenges for extended-duration space missions. The ability of exercise to counteract weightlessness-induced bone loss has been studied extensively, but to date, it has proven ineffective. We evaluated the effectiveness of a combination of two countermeasures-treadmill exercise while inside a lower body negative pressure (LBNP) chamber-on bone loss during a 30-day bed rest study. MATERIALS AND METHODS: Eight pairs of identical twins were randomized into sedentary (SED) or exercise/LBNP (EX/LBNP) groups. Blood and urine samples were collected before, several times during, and after the 30-day bed rest period. These samples were analyzed for markers of bone and calcium metabolism. Repeated measures ANOVA was used to determine statistical significance. Because identical twins were used, both time and group were treated as repeated variables. RESULTS: Markers of bone resorption were increased during bed rest in samples from sedentary subjects, including the collagen cross-links and serum and urinary calcium concentrations. For N-telopeptide and deoxypyridinoline, there were significant (p < 0.05) interactions between group (SED versus EX/LBNP) and phase of the study (sample collection point). Pyridinium cross-links were increased above pre-bed rest levels in both groups, but the EX/LBNP group had a smaller increase than the SED group. Markers of bone formation were unchanged by bed rest in both groups. CONCLUSIONS: These data show that this weight-bearing exercise combined with LBNP ameliorates some of the negative effects of simulated weightlessness on bone metabolism. This protocol may pave the way to counteracting bone loss during spaceflight and may provide valuable information about normal and abnormal bone physiology here on Earth.

Twin Study↗

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗

Reassessing the MCNP Random Number Generator

Random number generators are integral components to Monte Carlo codes. They provide the pseudorandom number sequence used to actually sample the distributions of interest. As a result, they are one of the most important components to the software. The current recommended MCNP random number generator is a 63-bit linear congruential generator (LCG). This generator is quite fast, but it has some drawbacks. First, it only has a period of 2 63 . Due to the necessarily non-optimal usage of random numbers to ensure parallel reproducibility, this amount is too few to guarantee random number sequences are not reused in all configurations the code runs under. As simulation size increases, users will need to be aware of the limitations of the generator and tune configuration variables to best suit their simulations, or they will need to assume that reuse is not negatively affecting their answers. Neither of these are optimal. Second, small LCGs are fairly weak in bit generation quality, and this can have an unknown impact on the quality of the simulation. This paper is an investigation into whether or not more modern random number generators can supersede the current ones. The goal is to find a generator that is similar or superior in speed to the LCGs, has a state space large enough to make strong guarantees about random number reuse, and passes all modern random number test suites. If such a generator is found, it would eliminate the need for the user to even be aware of the limitations of the random number generator and would simplify the use of the code. This paper will be broken into several parts. Sec. 2 will discuss the evolution of the random number generator within the MCNP code. Sec. 3 will go over what a Monte Carlo code needs from a generator to be reproducible and portable and how the current generator behaves in that light. Sec. 4 goes through how each generator was tested. Finally, Sec. 5 will discuss improvements that could be made to the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Geographic source attribution of honey by strontium isotope analyses: Latvia and India measurements compared to model predictions in a feasibility study

Strontium isotope ratios ( 87 Sr/ 86 Sr) can be used to determine the geographic origin of agricultural products. Here, in this study, we measured the 87 Sr/ 86 Sr of honey samples from Richland, WA, USA, Latvia, and India, and compared the results to published 87 Sr/ 86 Sr from surrounding areas and values predicted based upon a random forest isoscape model (Bataille et al., 2020). While the 87 Sr/ 86 Sr of the honey samples compared well with previously published data, the model did not accurately predict the 87 Sr/ 86 Sr of the honey samples, demonstrating that further refinement of the model would be beneficial. Because Sr cycling in terrestrial ecosystems is complex, the 87 Sr/ 86 Sr of honey is likely to reflect several sources (e.g., nectar, surface water, dust) and may change over time. In order to accurately predict the 87 Sr/ 86 Sr of honey, models must consider local geology, ecology, and bee behavior. Additional research examining how Sr is incorporated into honey is needed to inform models.

60 APPLIED LIFE SCIENCES↗

Some karyological observations on plants grown in space

Experiments were conducted to assess whether cell division in a plant root would be affected by prolonged exposure to microgravity. Root materials from sunflower, oat, and mung bean plants grown on STS-2 and STS-3 were utilized for the experiments. It is found that all oat, sunflower, and mung seedlings showed a reduced number of cells in division as they went through their first cell division cycle on earth when compared to their ground controls. A significant number of oat, mung, and sunflower plantlets exhibited random root orientation and the lack of strictly orthotropic growth of their shoot systems in the flight samples. In addition, it is found that the mung roots were apparently least affected in terms of their cytology despite the fact that their roots were often randomly oriented.

Krikorian, A. D.↗

Barium stars as tracers of s -process nucleosynthesis in AGB stars

Barium (Ba) stars help to verify asymptotic giant branch (AGB) star nucleosynthesis models since they experienced pollution from an AGB binary companion and thus their spectra carry the signatures of the slow neutron capture process (s process). For a large number (180) of Ba stars, we searched for AGB stellar models that match the observed abundance patterns. We aim to uncover any systematic deviations of the sample abundances from the predictions of the nucleosynthesis models. We employed three machine learning algorithms as classifiers: a Random Forest method, developed for this work, and the two classifiers used in our previous study. Compared to that work, we also expanded our observational sample with 11 Ba stars available in the supersolar metallicity range. We studied the statistical behaviour of the different s-process elements in the observational sample to investigate if the AGB models systematically under- or overpredict the abundances observed in the Ba stars and show the results in the form of violin plots of the residuals between spectroscopic abundances and model predictions. We inspected the correlations between the observed [Fe/H], the s-process elemental abundances, and the residuals. We employed the [Zr/Fe] and [Nb/Fe] abundances as a thermometer to constrain the operational temperature that rules the production of these elements in the sample stars, assuming a steady-state s process. We also investigated the mass distribution of the identified polluter AGB stars and the behaviour of the δ parameter, which describes the fraction of accreted AGB material relative to the Ba star envelope. We find a significant trend in the residuals that implies an underproduction of the elements just after the first s-process peak (Nb, Mo, and Ru) in the models relative to the observations. This may originate from a neutron-capture process (e.g. the intermediate neutron-capture process, i process) not yet included in the AGB models of metallicity from solar to roughly 1/5 solar, corresponding to the range of the Ba stars. Correlations are found between the residuals of these peculiar elements, suggesting a common origin for the deviations from the models. In addition, there is a weak metallicity dependence of the residuals of these elements. The s-process temperatures derived with the [Zr/Fe] – [Nb/Fe] thermometer have an unrealistic value for the majority of our stars. The most likely explanation is that at least a fraction of these elements are not produced in a steady-state s process, and instead may be due to processes not included in the AGB models. The mass distribution of the identified models confirms that our sample of Ba stars was polluted by low-mass AGB stars (< 4 M ⊙ ). Most of the matching AGB models require low accreted mass, but a few systems with high accreted mass are needed to explain the observations.

79 ASTRONOMY AND ASTROPHYSICS↗

Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization

Here, we consider unconstrained stochastic optimization problems with no available gradient information. Such problems arise in settings from derivative-free simulation optimization to reinforcement learning. We propose an adaptive sampling quasi-Newton method where we estimate the gradients using finite differences of stochastic function evaluations within a common random number framework. We develop modified versions of a norm test and an inner product quasi-Newton test to control the sample sizes used in the stochastic approximations and provide global convergence results to the neighborhood of a locally optimal solution. We present numerical experiments on simulation optimization problems to illustrate the performance of the proposed algorithm. When compared with classical zeroth-order stochastic gradient methods, we observe that our strategies of adapting the sample sizes significantly improve performance in terms of the number of stochastic function evaluations required.

97 MATHEMATICS AND COMPUTING↗

An IUE survey of interstellar H I Ly alpha absorption. 2: Interpretations

We present an analysis of interstellar neutral hydrogen column densities obtained from archival Ly alpha absorption line data toward the complete sample of B2 and hotter stars observed at high spectral resolution with the IUE satellite. The full sample includes 554 stars and more than doubles the number of lines of sight previously observed. Many of the B2 and B1.5 stars exhibit contamination from stellar Ly alpha absorption, and were excluded from the subsequent analysis. The final working sample includes 393 stars. We present statistical averages for a number of quantities derived for the sample. The stars range in distance from 0.12 to 11 kpc with an average distance of 2.1 kpc. Values for average sight-line density range from 0.017 to 8.62 atoms cm(exp -3), with an overall average of 0.23 atoms cm(exp -3). Neutral hydrogen and dust are well correlated, with N(H I)/E(B - V) = 4.93 x 10(exp 21) cm(exp -2) mag(exp -1), and N(H I)/E(Bump) = 2.17 x 10(exp 21) cm(exp -2) mag(exp -1). There is an increase in the H I to dust ratios for the densest sight lines. Evidently, the H I to dust ratios in dense clouds are higher than in the lower density medium between the clouds and in interarm directions. The effect is probably an indication of dust modification in the dense clouds. The H I to dust ratios are approx. 17% smaller for the sight lines to O stars compared to the ratios found toward B stars. We have identified sight lines with anomalously large and small values of N(H I)/E(B - V) and H(H I)/E(Bump). Some of these sight lines are well-known examples of peculiar extinction (i.e., HD 147933 and HD 37061 (NU Ori)). Others are less well known and may provide important new examples of regions with highly modified dust. The number of stars with anomalously low H I to dust ratios is disproportionately larger than the number of stars with anomalously high H I to dust ratios. The distribution of the gas away form the Galactic plane for the sample of objects is complex. For the subset of 375 stars whose lines of sight have a statistically low probablility of intersecting a large cloud, the distribution may be roughly approximated by an exponential density distribution, with a midplane density of 0.366 atoms cm(exp -3), a scale height of 195 pc, and a random logarithmic scattering parameter sigma (sub p) of 0.159 dex. For the same sample of stars, interstellar dust is found to be confined closer to the plane than the H I, with (E(B - V)/r)(sub 0) = 0.257 mag kpc(exp -1), scale height h = 152 pc, and sigma(sub p) = 0.263 dex. The dust distribution is more inhomogeneous than the gas distribution. The observed distribution of H I away from the Galactic plane can also be fitted with a two-component exponential model including the effects of patchiness. Unfortunately, the foreground contamination produced by the cloudy and more confined component of H I makes it difficult to estimate the scale height of the extended component without invoking an independent estimate of its midplane density. Assuming n(sub 2)(0) = 0.16 cm(exp -3) from the Copernicus satellite H I/H(sub 2) survey, we obtain n(sub 1)(0) = 0.247 cm(exp -3), h(sub 1) = 73 PC, and h(sub 2) + 357 pc.

Diplas, Athanassios↗