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At least 1,081 records · Page 60

Tracking Data Acquisition System (TDAS) for the 1990's. Volume 6: TDAS navigation system architecture

One-way range and Doppler methods for providing user orbit and time determination are examined. Forward link beacon tracking, with on-board processing of independent navigation signals broadcast continuously by TDAS spacecraft; forward link scheduled tracking; with on-board processing of navigation data received during scheduled TDAS forward link service intervals; and return link scheduled tracking; with ground-based processing of user generated navigation data during scheduled TDAS return link service intervals are discussed. A system level definition and requirements assessment for each alternative, an evaluation of potential navigation performance and comparison with TDAS mission model requirements is included. TDAS satellite tracking is also addressed for two alternatives: BRTS and VLBI tracking.

Elrod, B. D.↗

Wireless augmented reality communication system

The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.

Devereaux, Ann↗

Wireless Augmented Reality Communication System

The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.

Devereaux, Ann↗

Wireless Augmented Reality Communication System

The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.

Devereaux, Ann↗

Wireless Augmented Reality Communication System

The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.

Devereaux, Ann↗

Automated Pneumothorax Diagnosis using Deep Neural Networks

Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.

US Army collaboration↗

Client/Server data serving for high performance computing

This paper will attempt to examine the industry requirements for shared network data storage and sustained high speed (10's to 100's to thousands of megabytes per second) network data serving via the NFS and FTP protocol suite. It will discuss the current structural and architectural impediments to achieving these sorts of data rates cost effectively today on many general purpose servers and will describe and architecture and resulting product family that addresses these problems. The sustained performance levels that were achieved in the lab will be shown as well as a discussion of early customer experiences utilizing both the HIPPI-IP and ATM OC3-IP network interfaces.

Wood, Chris↗

Telemetry handling on the Space Station data management system

This paper examines the impact of telemetry handling on the design of the onboard networks that are part of the Space Station Data Management System (DMS). An architectural approach to satisfying the DMS requirement for support of the high throughput needed for telemetry transport and for servicing distributed computer systems is discussed. Several of the functionality vs. performance tradeoffs that must be made in developing an optimized mechanism for handling telemetry data in the DMS are considered.

Whitelaw, Virginia A.↗

RDMA vs. RPC for Implementing Distributed Data Structures

Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distributed data structures: remote direct memory access (RDMA) and remote procedure call (RPC). We focus on operations that require individual accesses to remote portions of a distributed data structure, e.g., accessing a hash table bucket or distributed queue, rather than global operations in which all processors collectively exchange information. We look at the trade-offs between the two styles through microbenchmarks and a performance model that approximates the cost of each. The RDMA operations have direct hardware support in the network and therefore lower latency and overhead, while the RPC operations are more expressive but higher cost and can suffer from lack of attentiveness from the remote side. We also run experiments to compare the real-world performance of RDMA- and RPC-based data structure operations with the predicted performance to evaluate the accuracy of our model, and show that while the model does not always precisely predict running time, it allows us to choose the best implementation in the examples shown. We believe this analysis will assist developers in designing data structures that will perform well on current network architectures, as well as network architects in providing better support for this class of distributed data structures.

distributed data structures↗

The Massively Parallel Processor and its applications

A long-term experimental development program conducted at Goddard Space Flight Center to implement an ultrahigh-speed data processing system known as the Massively Parallel Processor (MPP) is described. The MPP is a single instruction multiple data stream computer designed to perform logical, integer, and floating point arithmetic operations on variable word length data. Information is presented on system architecture, the system configuration, the array unit architecture, individual processing units, and expected operating rates for several image processing applications (including the processing of Landsat data).

Strong, J. P.↗

Communication Network Awareness Machine System Phase I Development: The Intelligent Party-Line Schema

As NextGen continues toward the full implementation of a Net-Centric Architecture (N-CA)it will inherently provide a continuous increase to the Three-Vs components (Volume, Velocity, and Variety) of big data . This will create an insurmountable environment for direct-action aviation personnel (DAAP)as the DAAP’s natural abilities to manage and process data into actionable information will be overmatched by the Three-Vs. Therefore, conducting operations within a N-CA requires that new tools and applications be researched and developed to aid the DAAP’s ability to understand and manage data, mitigate non-normals, create contingency plans and actions. This paper will describe a research area at NASA Langley Research Center known as the Intelligent Party-Line (IPL).

Intelligent Party-Line↗

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗

Harmony: Bringing Data Together by Bringing Services Together

As Earth observation data volume, velocity, and variety continues to accelerate, so do the challenges of working with those data. The computation, storage, and network transfer requirements for multi-petabyte datasets demand solutions that allow users to process, store, and move fewer bytes while still finding the valuable insights they seek. Our cloud-based data transformation framework, Harmony, tackles these challenges by providing consistent, standards-based interface to multiple disparate backend processors collocated with NASA EOSDIS data. It allows data scientists to perform data processing and harmonization activities across many datasets through familiar tooling. Simultaneously, it provides a clear, consistent interface for data providers to expose new or customized backend services for their data. This talk will discuss Harmony, its architecture and interface, and the path forward for cloud-based NASA EOSDIS data harmonization services.

Quinn, Patrick↗

Implementing Access to Data Distributed on Many Processors

A reference architecture is defined for an object-oriented implementation of domains, arrays, and distributions written in the programming language Chapel. This technology primarily addresses domains that contain arrays that have regular index sets with the low-level implementation details being beyond the scope of this discussion. What is defined is a complete set of object-oriented operators that allows one to perform data distributions for domain arrays involving regular arithmetic index sets. What is unique is that these operators allow for the arbitrary regions of the arrays to be fragmented and distributed across multiple processors with a single point of access giving the programmer the illusion that all the elements are collocated on a single processor. Today's massively parallel High Productivity Computing Systems (HPCS) are characterized by a modular structure, with a large number of processing and memory units connected by a high-speed network. Locality of access as well as load balancing are primary concerns in these systems that are typically used for high-performance scientific computation. Data distributions address these issues by providing a range of methods for spreading large data sets across the components of a system. Over the past two decades, many languages, systems, tools, and libraries have been developed for the support of distributions. Since the performance of data parallel applications is directly influenced by the distribution strategy, users often resort to low-level programming models that allow fine-tuning of the distribution aspects affecting performance, but, at the same time, are tedious and error-prone. This technology presents a reusable design of a data-distribution framework for data parallel high-performance applications. Distributions are a means to express locality in systems composed of large numbers of processor and memory components connected by a network. Since distributions have a great effect on the performance of applications, it is important that the distribution strategy is flexible, so its behavior can change depending on the needs of the application. At the same time, high productivity concerns require that the user be shielded from error-prone, tedious details such as communication and synchronization.

James, Mark↗

An Engineering Data Management System for Ipad

An overview of the capabilities and software architecture of the IPAD information processor (IPIP) is presented. IPIP is a state-of-the-art data base management system that satisfies engineering requirements not addressed by present day commercial systems. It also significantly advances a number of capabilities that are offered commercially. IPIP capabilities range from support for multiple schemas and data models to support for distributed processing, configuration control, and data inventory management. IPIP exploits semantic commonality in features offered in various forms at different user interfaces in today's commercial systems. An integrated software architecture supports all user interfaces: programming languages, interactive data manipulation, and schema languages. This approach promotes simplicity and compactness in software and permits features to be offered symmetrically across all appropriate user interfaces.

H R Johnson↗

WMS Server 2.0

This software is a simple, yet flexible server of raster map products, compliant with the Open Geospatial Consortium (OGC) Web Map Service (WMS) 1.1.1 protocol. The server is a full implementation of the OGC WMS 1.1.1 as a fastCGI client and using Geospatial Data Abstraction Library (GDAL) for data access. The server can operate in a proxy mode, where all or part of the WMS requests are done on a back server. The server has explicit support for a colocated tiled WMS, including rapid response of black (no-data) requests. It generates JPEG and PNG images, including 16-bit PNG. The GDAL back-end support allows great flexibility on the data access. The server is a port to a Linux/GDAL platform from the original IRIX/IL platform. It is simpler to configure and use, and depending on the storage format used, it has better performance than other available implementations. The WMS server 2.0 is a high-performance WMS implementation due to the fastCGI architecture. The use of GDAL data back end allows for great flexibility. The configuration is relatively simple, based on a single XML file. It provides scaling and cropping, as well as blending of multiple layers based on layer transparency.

Plesea, Lucian↗