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At least 127 records · Page 7

Measuring Cities with Software-Defined Sensors

The Chicago Array of Things (AoT) project, funded by the US National Science Foundation, created an experimental, urban-scale measurement capability to support diverse scientific studies. Initially conceived as a traditional sensor network, collaborations with many science communities guided the project to design a system that is remotely programmable to implement Artificial Intelligence (AI) within the devices-at the “edge” of the network-as a means for measuring urban factors that heretofore had only been possible with human observers, such as human behavior including social interaction. The concept of “software-defined sensors” emerged from these design discussions, opening new possibilities, such as stronger privacy protections and autonomous, adaptive measurements triggered by events or conditions. We provide examples of current and planned social and behavioral science investigations uniquely enabled by software-defined sensors as part of the SAGE project, an expanded follow-on effort that includes AoT.

97 MATHEMATICS AND COMPUTING↗

Switched Band-Pass Filters for Adaptive Transceivers

Switched band-pass filters are key components of proposed adaptive, software- defined radio transceivers that would be parts of envisioned digital-data-communication networks that would enable real-time acquisition and monitoring of data from geographically distributed sensors. Examples of sensors to be connected to such networks include security cameras, radio-frequency identification units, and geolocation units based on the Global Positioning System. Through suitable software configuration and without changing hardware, these transceivers could be made to operate according to any of a number of complex wireless-communication standards that could be characterized by diverse modulation schemes, bandwidths, and data-handling protocols. The adaptive transceivers would include field-programmable gate arrays (FPGAs) and digital signal-processing hardware. In the receiving path of a transceiver, the incoming signal would be amplified by a low-noise amplifier (LNA). The output spectrum of the LNA would be processed by a band-pass filter operating in the frequency range between 900 MHz and 2.4 GHz. Then a down-converter would translate the signal to a lower frequency range to facilitate analog-to-digital conversion, which would be followed by baseband processing by one or more FPGAs. In the transmitting path, a digital stream would first be converted to an analog signal, which would then be up-converted to a selected frequency band before being applied to a transmitting power amplifier. The aforementioned band-pass filter in the receiving path would be a combination of resonant inductor-and-capacitor filters and switched band-pass filters. The overall combination would implement a switch function designed mathematically to exhibit desired frequency responses and to switch the signal in each frequency band to an analog-to-digital converter appropriate for that band to produce a digital intermediate-frequency signal for digital signal processing.

Wang, Ray↗

In-Space Networking on NASA's SCAN Testbed

The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios and a flight computer for supporting in-space communication research. New technologies being studied using the SCaN Testbed include advanced networking, coding, and modulation protocols designed to support the transition of NASAs mission systems from primarily point to point data links and preplanned routes towards adaptive, autonomous internetworked operations needed to meet future mission objectives. Networking protocols implemented on the SCaN Testbed include the Advanced Orbiting Systems (AOS) link-layer protocol, Consultative Committee for Space Data Systems (CCSDS) Encapsulation Packets, Internet Protocol (IP), Space Link Extension (SLE), CCSDS File Delivery Protocol (CFDP), and Delay-Tolerant Networking (DTN) protocols including the Bundle Protocol (BP) and Licklider Transmission Protocol (LTP). The SCaN Testbed end-to-end system provides three S-band data links and one Ka-band data link to exchange space and ground data through NASAs Tracking Data Relay Satellite System or a direct-to-ground link to ground stations. The multiple data links and nodes provide several upgradable elements on both the space and ground systems. This paper will provide a general description of the testbeds system design and capabilities, discuss in detail the design and lessons learned in the implementation of the network protocols, and describe future plans for continuing research to meet the communication needs for evolving global space systems.

space networks↗

In-Space Networking On NASA's SCaN Testbed

The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios (SDRs) and a programmable flight computer. The purpose of the Testbed is to conduct inspace research in the areas of communication, navigation, and networking in support of NASA missions and communication infrastructure. Multiple reprogrammable elements in the end to end system, along with several communication paths and a semi-operational environment, provides a unique opportunity to explore networking concepts and protocols envisioned for the future Solar System Internet (SSI). This paper will provide a general description of the system's design and the networking protocols implemented and characterized on the testbed, including Encapsulation, IP over CCSDS, and Delay-Tolerant Networking (DTN). Due to the research nature of the implementation, flexibility and robustness are considered in the design to enable expansion for future adaptive and cognitive techniques. Following a detailed design discussion, lessons learned and suggestions for future missions and communication infrastructure elements will be provided. Plans for the evolving research on SCaN Testbed as it moves towards a more adaptive, autonomous system will be discussed.

space networks↗

Unique Challenges Testing SDRs for Space

This paper describes the approach used by the Space Communication and Navigation (SCaN) Testbed team to qualify three Software Defined Radios (SDR) for operation in space and the characterization of the platform to enable upgrades on-orbit. The three SDRs represent a significant portion of the new technologies being studied on board the SCAN Testbed, which is operating on an external truss on the International Space Station (ISS). The SCaN Testbed provides experimenters an opportunity to develop and demonstrate experimental waveforms and applications for communication, networking, and navigation concepts and advance the understanding of developing and operating SDRs in space. Qualifying a Software Defined Radio for the space environment requires additional consideration versus a hardware radio. Tests that incorporate characterization of the platform to provide information necessary for future waveforms, which might exercise extended capabilities of the hardware, are needed. The development life cycle for the radio follows the software development life cycle, where changes can be incorporated at various stages of development and test. It also enables flexibility to be added with minor additional effort. Although this provides tremendous advantages, managing the complexity inherent in a software implementation requires a testing beyond the traditional hardware radio test plan. Due to schedule and resource limitations and parallel development activities, the subsystem testing of the SDRs at the vendor sites was primarily limited to typical fixed transceiver type of testing. NASA s Glenn Research Center (GRC) was responsible for the integration and testing of the SDRs into the SCaN Testbed system and conducting the investigation of the SDR to advance the technology to be accepted by missions. This paper will describe the unique tests that were conducted at both the subsystem and system level, including environmental testing, and present results. For example, test waveforms were developed to measure the gain of the transmit system across the tunable frequency band. These were used during thermal vacuum testing to enable characterization of the integrated system in the wide operational temperature range of space. Receive power indicators were used for Electromagnetic Interference tests (EMI) to understand the platform s susceptibility to external interferers independent of the waveform. Additional approaches and lessons learned during the SCaN Testbed subsystem and system level testing will be discussed that may help future SDR integrators

Chelmins, David↗

Unique Challenges Testing SDRs for Space

This paper describes the approach used by the Space Communication and Navigation (SCaN) Testbed team to qualify three Software Defined Radios (SDR) for operation in space and the characterization of the platform to enable upgrades on-orbit. The three SDRs represent a significant portion of the new technologies being studied on board the SCAN Testbed, which is operating on an external truss on the International Space Station (ISS). The SCaN Testbed provides experimenters an opportunity to develop and demonstrate experimental waveforms and applications for communication, networking, and navigation concepts and advance the understanding of developing and operating SDRs in space. Qualifying a Software Defined Radio for the space environment requires additional consideration versus a hardware radio. Tests that incorporate characterization of the platform to provide information necessary for future waveforms, which might exercise extended capabilities of the hardware, are needed. The development life cycle for the radio follows the software development life cycle, where changes can be incorporated at various stages of development and test. It also enables flexibility to be added with minor additional effort. Although this provides tremendous advantages, managing the complexity inherent in a software implementation requires a testing beyond the traditional hardware radio test plan. Due to schedule and resource limitations and parallel development activities, the subsystem testing of the SDRs at the vendor sites was primarily limited to typical fixed transceiver type of testing. NASA's Glenn Research Center (GRC) was responsible for the integration and testing of the SDRs into the SCaN Testbed system and conducting the investigation of the SDR to advance the technology to be accepted by missions. This paper will describe the unique tests that were conducted at both the subsystem and system level, including environmental testing, and present results. For example, test waveforms were developed to measure the gain of the transmit system across the tunable frequency band. These were used during thermal vacuum testing to enable characterization of the integrated system in the wide operational temperature range of space. Receive power indicators were used for Electromagnetic Interference tests (EMI) to understand the platform's susceptibility to external interferers independent of the waveform. Additional approaches and lessons learned during the SCaN Testbed subsystem and system level testing will be discussed that may help future SDR integrators.

transmitters receivers↗

Methods of downloading to user institutions

The Pilot Climate Data System (PCDS) not only supports the ability to output data in a uniform structure via the Common Data Format (CDF, but also supports the ability to provide data in native format for any data set supported by the PCDS. Methods are discussed for acquiring data in either format from the PCDS for further work at remote sites. Four levels of remote utilization are defined, based on the extent of offloading the National Space Science Data Center (NSSDC) computer and local PCDS processing. Characteristics of each level are thoroughly explained, including details of information and data transfers, downloading, uploading, and offloading of the NSSDC computer. Only the levels themselves are specified here. The first level defined is that of a network-based distributed PCDS. A subset of the PCDS software is ported to another VAX and made available on a network (i.e., SPAN) node. There is no subset of the PCDS at the second level, but it is also network based. Non-network utilization of the PCDS, requiring dial-up log on, is denoted as a third level. Finally, at the fourth level, personal computer utilization of the PCDS through dial-up log on with proper terminal emulation is defined.

Treinish, L.↗

An Overview of SBIR Phase 2 Communications Technology and Development

Technological innovation is the overall focus of NASA's Small Business Innovation Research (SBIR) program. The program invests in the development of innovative concepts and technologies to help NASA's mission directorates address critical research and development needs for agency projects. This report highlights innovative SBIR Phase II projects from 2007-2012 specifically addressing areas in Communications Technology and Development which is one of six core competencies at NASA Glenn Research Center. There are eighteen technologies featured with emphasis on a wide spectrum of applications such as with a security-enhanced autonomous network management, secure communications using on-demand single photons, cognitive software-defined radio, spacesuit audio systems, multiband photonic phased-array antenna, and much more. Each article in this booklet describes an innovation, technical objective, and highlights NASA commercial and industrial applications. This report serves as an opportunity for NASA personnel including engineers, researchers, and program managers to learn of NASA SBIR's capabilities that might be crosscutting into this technology area. As the result, it would cause collaborations and partnerships between the small companies and NASA Programs and Projects resulting in benefit to both SBIR companies and NASA.

secure communications software defined radio anten↗

Development of Network-based Communications Architectures for Future NASA Missions

Since the Vision for Space Exploration (VSE) announcement, NASA has been developing a communications infrastructure that combines existing terrestrial techniques with newer concepts and capabilities. The overall goal is to develop a flexible, modular, and extensible architecture that leverages and enhances terrestrial networking technologies that can either be directly applied or modified for the space regime. In addition, where existing technologies leaves gaps, new technologies must be developed. An example includes dynamic routing that accounts for constrained power and bandwidth environments. Using these enhanced technologies, NASA can develop nodes that provide characteristics, such as routing, store and forward, and access-on-demand capabilities. But with the development of the new infrastructure, challenges and obstacles will arise. The current communications infrastructure has been developed on a mission-by-mission basis rather than an end-to-end approach; this has led to a greater ground infrastructure, but has not encouraged communications between space-based assets. This alone provides one of the key challenges that NASA must encounter. With the development of the new Crew Exploration Vehicle (CEV), NASA has the opportunity to provide an integration path for the new vehicles and provide standards for their development. Some of the newer capabilities these vehicles could include are routing, security, and Software Defined Radios (SDRs). To meet these needs, the NASA/Glenn Research Center s (GRC) Network Emulation Laboratory (NEL) has been using both simulation and emulation to study and evaluate these architectures. These techniques provide options to NASA that directly impact architecture development. This paper identifies components of the infrastructure that play a pivotal role in the new NASA architecture, develops a scheme using simulation and emulation for testing these architectures and demonstrates how NASA can strengthen the new infrastructure by implementing these concepts.

Slywczak, Richard A.↗

S-Band Transponder Multi-Network Compatibility, Space Environment and Radiation Testing

This paper presents the development and testing of the Software Define Radio (SDR) transceiver to meet the emerging needs for SmallSat communication and navigation. Vulcan Wireless and NASA Goddard Space Flight Center (GSFC) collaborated in testing the Vulcan Wireless S-band SDR engineering model. Apart from testing, communication link analysis was performed for a Low Earth Orbit (LEO) 400 km scenario. The results of the compatibility, radiation, environmental testing, and link analysis are presented. Also, this paper reviews a set of SmallSat missions under development at NASA GSFC.

Software Define Radio, transceiver, S-band↗

Iris Deep-Space Transponder for SLS EM-1 CubeSat Missions

Several key design upgrades have been recently made to the Iris Deep-Space Transponder baselined to be used on secondary payload missions of the upcoming Space Launch System Exploration Mission One (SLS EM-1). The Iris Transponder is a reconfigurable software-defined radio (SDR) designed for missions requiring interoperability with NASA's Deep Space Network (DSN) on X-band frequencies (7.2 GHz uplink, 8.4 GHz downlink). The transponder provides radiometric tracking support with the DSN to provide navigational products for precise orbit determination while performing standard uplink and downlink communications in a CubeSat/SmallSat-applicable package size. The recent hardware changes include a volume reduction of 30% from previous models, with the main transponder unit weighing less than 1.0 kg, while maintaining total ionizing dose (TID) radiation tolerance of >23 krads (Si) for deep-space missions. Lab tests indicate maximum downlink rates of up to 6.25 Msps can be supported by the transponder in conventional BPSK modulation, but most SLS EM-1 CubeSat missions are link-performance limited to less than 256 kbps. A prototype unit of the flight production units has been assembled and various performance and characterization tests are underway. This talk discusses the key design aspects and specifications of the Iris Transponder and presents preliminary results from early testing of the assembled transponder.

Kobayashi, M. Michael↗

Advances in Autonomous Communications and Operations: Tes-N Series

Advances in nanosat subsystems over the past decade have taken the CubeSat standard from a communication-limited educational tool to a powerful platform enabling space research. The potential for autonomous operations may greatly increase the capability of downlinking even larger data sets. This is enabled through miniaturization of software-defined radio/cognitive communication solutions and a rapidly growing number of ground stations and satellite network crosslinks. The TechEdSat-n orbital flight series is currently demonstrating experiments using cognitive communication concepts including User Initiated Service (UIS) and High-rate Delay Tolerant Networks (HDTN), which show a significant step toward improved capability. At the core of this is the use of the Iridium L-band Short Burst Data (SBD) modems, pioneered by TES-n for space applications. SBD enables unique rapid command, control, and scheduling to initiate the UIS and HDTN protocols. This occurs by performing GPS-assisted on-orbit ephemeris determination, enabling negotiation with high bandwidth ground assets to repeatedly downlink over a specific commercial or government-owned ground station. The technique is RF band-agnostic and may be extended to higher bandwidth stations and SDRs. This may also include free-space optical communication, through both laser and omnidirectional LEDs, which can provide an attractive protocol for downlinking very large datasets over far fewer ground stations. In addition, this may be extended to lunar applications for such future concepts as LunaNet, whereby scheduling and cognitive technologies can assist in greatly improving Earth downlink capabilities with ground stations which will see greater competition for usage. Lastly, the NASA Communication Service Program (CSP), intended to eventually replace the NASA Tracking and Data Relay Satellite System (TDRSS) will also demonstrate the feasibility of commercially-provided satellite communication capabilities. All of these combined advances, including large advances in on-board computation on small platforms, will result in more remarkable data processing capability – yielding even more as of yet unknown discoveries.

Autonomy↗

Pickaxe: a Python library for the prediction of novel metabolic reactions

Abstract Background Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user’s application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation. Results Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset. Conclusion Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.

59 BASIC BIOLOGICAL SCIENCES↗

Learning In networks

Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms.

Buntine, Wray L.↗

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗

CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]

Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations. This software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).

Perry, Bruce↗

Gateway design specification for fiber optic local area networks

This is a Design Specification for a gateway to interconnect fiber optic local area networks (LAN's). The internetworking protocols for a gateway device that will interconnect multiple local area networks are defined. This specification serves as input for preparation of detailed design specifications for the hardware and software of a gateway device. General characteristics to be incorporated in the gateway such as node address mapping, packet fragmentation, and gateway routing features are described.

Source record↗

Real-time sensor data validation

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

Bickmore, Timothy W.↗