ICESat-2/ATLAS Onboard Flight Science Receiver Algorithms: Purpose, Process, and Performance.
Ontology highlight
ABSTRACT:
SUBMITTER: McGarry JF
PROVIDER: S-EPMC8243955 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The Advanced Topographic Laser Altimetry System (ATLAS) onboard the NASA Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is the newest Earth observing satellite for global elevation studies. The primary objectives for ICESat-2 follow the objectives of its predecessor, ICESat and also focus on providing cryospheric measurements to determine ice sheet mass balance, and monitor both sea ice thickness and extent. However, the global observations support secondary science objectives as well such as biomass estimation, inland water elevation, sea state height and aerosol concentrations. Since launch of ICESat-2, ATLAS has collected more than a trillion measurements. This study provides a mission overview, a description of the operational components that enable the altimeter products for science, on-orbit observatory performance, and assessment of the spacecraft attitude control systems that enable repeat measurements to within 10 m and pointing control within ±45 m. These metrics should be considered for ground-based validation campaigns or science investigations.
| S-EPMC8265375 | biostudies-literature
Project description:In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, ?, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than ? do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than ?, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose ? in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies.
| S-EPMC5804623 | biostudies-literature
Project description:Bathymetry retrievals from 2D, multispectral imagery, referred to as Satellite-Derived Bathymetry (SDB), afford the potential to obtain global, nearshore bathymetric data in optically clear waters. However, accurate SDB depth retrievals are limited in the absence of "seed depths." The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) space-based altimeter has proven capable of accurate bathymetry, but methods of employing ICESat-2 bathymetry for SDB retrievals over broad spatial extents are immature. This research aims to establish and test a baseline methodology for generating bathymetric surface models using SDB with ICESat-2. The workflow is operationally efficient (17-37 min processing time) and capable of producing bathymetry of sufficient vertical accuracy for many coastal science applications, with RMSEs of 0.96 and 1.54 m when using Sentinel-2 and Landsat 8, respectively. The highest priorities for further automation have also been identified, supporting the long-range goal of global coral reef habitat change analysis using ICESat-2-aided SDB.
| S-EPMC7988556 | biostudies-literature
Project description:In the Global Navigation Satellite System (GNSS) community, the Quasi-Zenith Satellite System (QZSS) is an augmentation system for users in the Asia-Pacific region. However, the characteristics and performance of four QZSS satellite clocks in a long-term scale are unknown at present. However, it is crucial to the positioning, navigation and timing (PNT) services of users, especially in Asia-Pacific region. In this study, the characteristics and performance variation of four QZSS satellite clocks, which including the phase, frequency, frequency drift, fitting residuals, frequency accuracy, periodic terms, frequency stability and short-term clock prediction, are revealed in detail for the first time based on the precise satellite clock offset products of nearly 1000 days. The important contributions are as follows: (1) It is detected that the times of phase and frequency jump are 2.25 and 1.5 for every QZSS satellite clock in one year. The magnitude of the frequency drift is about 10-18. The periodic oscillation of frequency drift of J01 and J02 satellite clocks is found. The clock offset model precision of QZSS is 0.33 ns. (2) The two main periods of QZSS satellite clock are 24 and 12 hours, which is the influence of the satellite orbit; (3) The frequency stability of 100, 1000 and 10,000 s are 1.98 × 10-13, 6.59 × 10-14 and 5.39 × 10-14 for QZSS satellite clock, respectively. The visible "bump" is found at about 400 s for J02 and J03 satellite clocks. The short-term clock prediction accuracy of is 0.12 ns. This study provides a reference for the state monitoring and performance variation of the QZSS satellite clock.
| S-EPMC6928888 | biostudies-literature
Project description:Scaling a flying robot down to the size of a fly or bee requires advances in manufacturing, sensing and control, and will provide insights into mechanisms used by their biological counterparts. Controlled flight at this scale has previously required external cameras to provide the feedback to regulate the continuous corrective manoeuvres necessary to keep the unstable robot from tumbling. One stabilization mechanism used by flying insects may be to sense the horizon or Sun using the ocelli, a set of three light sensors distinct from the compound eyes. Here, we present an ocelli-inspired visual sensor and use it to stabilize a fly-sized robot. We propose a feedback controller that applies torque in proportion to the angular velocity of the source of light estimated by the ocelli. We demonstrate theoretically and empirically that this is sufficient to stabilize the robot's upright orientation. This constitutes the first known use of onboard sensors at this scale. Dipteran flies use halteres to provide gyroscopic velocity feedback, but it is unknown how other insects such as honeybees stabilize flight without these sensory organs. Our results, using a vehicle of similar size and dynamics to the honeybee, suggest how the ocelli could serve this role.
| S-EPMC4208359 | biostudies-literature
Project description:In the pursuit of advancing research in continuous user authentication, we introduce COUNT-OS-I and COUNT-OS-II, two distinct performance counter datasets from Windows operating systems, crafted to bolster research in continuous user authentication. Encompassing data from 63 computers and users, the datasets offer rich, real-world insights for developing and evaluating authentication models. COUNT-OS-I spans 26 users in an IT department, capturing 159 attributes across diverse hardware and software environments over 26 h on average per user. COUNT-OS-II, on the other hand, encompasses 37 users with identical system configurations, recording 218 attributes per sample over a 48-hour period. Both datasets utilize pseudonymization to safeguard user identities while maintaining data integrity and statistical accuracy. The well-balanced nature of the data, confirmed by comprehensive statistical analysis, positions these datasets as reliable benchmarks for the continuous user authentication domain. Through their release, we aim to empower the development of robust, real-world applicable authentication models, contributing to enhanced system security and user trust.
| S-EPMC10788215 | biostudies-literature
Project description:Gene expression throughout the reproductive process in rice (Oryza sativa) beginning with primordia development through pollination/fertilization to zygote formation was analyzed. We analyzed 25 stages/organs of rice reproductive development including early microsporogenesis stages with 57,381 probe sets, and identified around 26,000 expressed probe sets in each stage. Fine dissection of 25 reproductive stages/organs combined with detailed microarray profiling revealed dramatic, coordinated and finely tuned changes in gene expression. Decrease of expressed genes in the pollen maturation process was observed in a similar way with Arabidopsis and maize. An almost equal number of ab initio predicted genes and cloned genes appeared or disappeared coordinated with developmental stage progression. A large number of organ-/stage-specific genes were identified; notably 2,593 probe sets for developing anther, including 932 probe sets corresponding to ab initio predicted genes. Analysis of cell cycle-related genes revealed that several CDKs, cyclins and components of SCF E3 ubiquitin ligase complexes were expressed specifically in reproductive organs. Cell wall biosynthesis or degradation protein genes and transcription factor genes expressed specifically in reproductive stages were also newly identified. Rice genes homologous to reproduction-related genes in other plants showed expression profiles both consistent and inconsistent with their predicted functions. The rice reproductive expression atlas is likely to be the deepest and most comprehensive dataset available, indispensable for unraveling functions of many specific genes in plant reproductive processes that have not yet been thoroughly analyzed. This SuperSeries is composed of the following subset Series: GSE13988: Rice expression atlas (1): Anther development GSE14298: Rice expression atlas (2): Pollination - Fertilization GSE14299: Rice expression atlas (3): Early embryogenesis GSE14300: Rice expression atlas (4): Vegetative tissues GSE14301: Rice expression atlas (5): Anther development (Agilent data) Refer to individual Series
2010-11-11 | E-GEOD-14304 | biostudies-arrayexpress
Project description:Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield.
| S-EPMC9814253 | biostudies-literature
Project description:Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images.
| S-EPMC4806537 | biostudies-literature
Project description:Computing is highly segregated and stratified by gender. While there is abundant scholarship investigating this problem, emerging evidence suggests that a hierarchy of value exists between the social and technical dimensions of Computer Science and Engineering (CSE) and this plays a role in the underrepresentation of women in the field. This ethnographic study of women's experiences in computing offers evidence of a systemic preference for the technical dimensions of computing over the social and a correlation between gender and social aspirations. Additionally, it suggests there is a gap between the exaltation of computing's social contributions and the realities of them. My participants expressed a yearning to contribute to the collective well-being of society using their computing skills. I trace moments of rupture in my participants' stories, moments when they felt these aspirations were in conflict with the cultural values in their organizations. I interpret these ruptures within a consideration of yearning, a need my participants had to contribute meaningfully to society that remained unfulfilled. The yearning to align one's altruistic values with one's careers aspirations in CSE illuminates an area for greater exploration on the path to realizing gender equity in computing. I argue that before a case can be made that careers in computing do indeed contribute to social and civil engagements, we must first address the meaning of the social within the values, ideologies and practices of CSE institutions and next, develop ways to measure and evaluate the field's contributions to society.
| S-EPMC5513966 | biostudies-literature