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At least 37 records · Page 2

Opening remarks

The year's accomplishments at the onset of the yearly NAPEX meetings are reviewed. Therefore, I will present the last year's accomplishments and the plans for the next year. The studies supported by the Propagation Program during the last year are listed: OLYMPUS data collection and analysis; the ACTS Propagation Program; low elevation angle 11-GHz measurements; satellite broadcast and mobile studies; radiometric techniques; propagation models database; NASA Reference Publication 1274; CCIR activities; fade detection and compensation; rain rate measurements; and information dissemination.

Davarian, Faramaz↗

A Full-Text-Based Search Engine for Finding Highly Matched Documents Across Multiple Categories

This report demonstrates the full-text-based search engine that works on any Web-based mobile application. The engine has the capability to search databases across multiple categories based on a user's queries and identify the most relevant or similar. The search results presented here were found using an Android (Google Co.) mobile device; however, it is also compatible with other mobile phones.

Web-based mobile application↗

An approach to efficient mobility management in intelligent networks

Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.

Murthy, K. M. S.↗

Traffic model for the satellite component of UMTS

An algorithm for traffic volume estimation for satellite mobile communications systems has been developed. This algorithm makes use of worldwide databases for demographic and economic data. In order to provide for such an estimation, the effects of competing services have been considered so that likely market demand can be forecasted. Different user groups of the predicted market have been identified according to expectations in the quality of services and mobility requirement. The number of users for different user groups are calculated taking into account the gross potential market, the penetration rate of the identified services and the profitability to provide such services via satellite.

Hu, Y. F.↗

Mobile satellite system fade statistics for shadowing and multipath from roadside trees at UHF and L-band

Field tests related to planned mobile satellite systems were performed, and results that add to the existing database of propagation measurements at L-band (1.5 GHz) are described. They are considered particularly useful in that propagation effects were studied systematically, with repeated and controlled runs pertaining to different path elevation angles, road types, and path geometries defining shadowing and line-of-sight modes. In addition, simultaneous L-band and UHF measurements were performed for the purpose of establishing scaling factors applicable to previous UHF (870 MHz) results. The control of the experimental parameters was made possible by using a helicopter as the source platform and a mobile van to house the receiver.

Goldhirsh, Julius↗

Spacesuit Fit and Mobility Assessments by Digital Human Modeling

Spacesuit Fit and Mobility Assessments by Digital Human Modeling K. Han Kim (Leidos, Inc.) Elizabeth A. Benson (KBR, Inc.) Sudhakar L. Rajulu (NASA Johnson Space Center) Spacesuits are required to accommodate safe operations for astronauts across gender and a wide variety of body shapes and sizes. This goal has been of particular importance given the increasing diversity of NASA crewmembers for upcoming Missions. While testing with design prototypes is a critical step for spacesuit development, iterative mockup design, fabrication, and human subject tests can be extremely costly and time consuming. Moreover, testing with a limited subject pool has often raised questions for validity, as test subjects need to represent the entire astronaut population, not only of the past or current, but also the future. This study is aimed at demonstrating how digital human modeling (DHM) tools have been built and directly supported NASA spacesuit developments. With DHM, the computer aided design (CAD) model of a spacesuit was integrated with human body models. Two use scenarios are presented in this paper, namely fit and mobility. For fit assessments, the suit-to-body contact and compression patterns were estimated using 3D human body scan models virtually wearing a spacesuit model. A statistical fit classifier was made from the contact patterns and applied against a large database of body scans (N=2,500). With this technique, the NASA reference design spacesuit Exploration EVA Mobility Unit (xEMU)was verified to accommodate 90% of the astronaut-like population, with the critical dimensions covering 1stto 99thpercentiles of the target body measurements. A similar technique assessed XEMU mobility. The maximum reach envelopes were considered, within which the work objects and critical hardware interfaces should be located for safe and ergonomic operations. While the reach envelope geometry varies significantly with the suit wearer’s body size and strength, the existing test data did not include the subjects critically required to define suit mobility requirements, such as very small females or large males. Using the xEMU virtual model kinematically simulated and permuted for a hypothetical wearer, however, the existing data were statistically transformed and scaled. This method enabled for a parametric estimation of the reach envelopes from the 1stpercentile female or 99thpercentile male. The outcome was successfully incorporated for requirement developments. With the new DHM tools, human integration of the spacesuit was structurally simulated and predictively assessed, which would have been otherwise impossible. Also, the needs for iterative mockup and subject tests were significantly reduced, which resulted in time and cost saving. Additional work is in progress to integrate additional vehicles, tools, and hardware with DHM framework.

K Han Kim↗

Engineering of Data Acquiring Mobile Software and Sustainable End-User Applications

The criteria for which data acquiring software and its supporting infrastructure should be designed should take the following two points into account: the reusability and organization of stored online and remote data and content, and an assessment on whether abandoning a platform optimized design in favor for a multi-platform solution significantly reduces the performance of an end-user application. Furthermore, in-house applications that control or process instrument acquired data for end-users should be designed with a communication and control interface such that the application's modules can be reused as plug-in modular components in greater software systems. The application of the above mentioned is applied using two loosely related projects: a mobile application, and a website containing live and simulated data. For the intelligent devices mobile application AIDM, the end-user interface have a platform and data type optimized design, while the database and back-end applications store this information in an organized manner and manage access to that data to only to authorized user end application(s). Finally, the content for the website was derived from a database such that the content can be included and uniform to all applications accessing the content. With these projects being ongoing, I have concluded from my research that the applicable methods presented are feasible for both projects, and that a multi-platform design for the mobile application only marginally drop the performance of the mobile application.

Smith, Benton T.↗

Anthropometric Requirements for Constellation

This slide presentation reviews the requirement from an Anthropometric standpoint for the development of the Constellation's programs hardware, specifically the Orion crew exploration vehicle. The NASA JSC Anthropometry and Biomechanics Facility (ABF) provides anthropometry, strength, mobility, and mass properties requirements; gathers, interprets, manages and maintains the flight crew anthropometry database; and participates and provides input during crew selection. This is used to assist in requirements for vehicle and space suit design and for crew selection.

Raulu, Sudhakar↗

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected from the treadmill, cycle ergometer, and resistance strength training hardware are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are post processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates have recently been made to how this valuable data are stored, adding an additional level of data security, increasing data accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries over the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 - current day. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the inflight data it into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory's output time of crew reports by 67%. Expansion of the SQL database to be inclusive of additional medical requirement metrics, addition of 'app-like' tools for mobile visualization, and collaborative use (e.g. operational support teams, research groups, and International Partners) of the data system is currently being explored.

Buxton, R. E.↗

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected, treadmill, cycle ergometer, and resistance strength training hardware, are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates recently have been made to how these valuable data are stored, adding an additional level of security, increasing accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries regarding the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 to current date. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the in-flight data into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory’s output time of crew reports by 67%. Expansion of the SQL database, to be inclusive of additional medical requirement metrics, addition of ‘app-like’ tools for mobile visualization, and collaborative use (e.g., operational support teams, research groups, and International Partners) of the data system, is currently being explored.

Buxton, R. E.↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

Opening remarks: Current and future activities

It is our custom to present the Propagation Program's recent accomplishments and future plans at the onset of a NAPEX meeting. A summary is presented. The data analysis phase of the U.S. Olympus Campaign is nearing its end. The final report will be published by Virginia Tech by midsummer 1993. The report will comprise measurement analysis for 12 months. It will include monthly and annual attenuation statistics and statistics on scintillation effects. A number of prediction models will be presented. The ACTS propagation experiment preparations are moving forward as expected. The mobile/personal channel characterization efforts continued during the last year. Data collected by the University of Texas in 1992 are being analyzed and will become available by September 1993. We have recently started a study to characterize LEO mobile/personal channels. Topics such as indoor reception, tree shadowing, blockage, and delay spread will be investigated. These results will become available in one to two years from now. We have also collected Ka-band mobile data using Olympus 20 GHz beacon transmissions. The University of Texas has already collected five years of low-elevation angle, 11GHz propagation data. The work on database for propagation models has progressed very well. The first release is ready, and the participants of this meeting will receive a copy of the software. We had an active year where CCIR is concerned. An input document on land mobile satellite system (LMSS) propagation models was submitted to the U.S. national committee and was approved and sent to Geneva.

Davarian, Faramaz↗

L- and K-band LMSS propagation measurements using MARECS-B, OLYMPUS, and ACTS

L-band measurements of land mobile satellite systems (LMSS) propagation effects were last made at the end of 1988, but some voids were left in the database, making modeling of low elevation roadside tree shadowing and multipath reflections difficult for some path geometries. Transmission of a pilot tone from MARECS-B at 55 deg West during Sep. and Dec. 1991 gave an opportunity to fill the gaps in the experimental results. Two campaigns during which fade data were obtained at elevation angles from 7 deg to 40 deg are described. Below 15 deg, specular terrain reflections in a non-shadowing, hilly environment were observed to introduce significant fading. Although the reflecting surface was at a distance of up to several km, it is shown that the reflected signals are delayed by less than 1 microsec. Mobile measurements were also attempted receiving the 20 GHz Olympus beacon, but antenna pointing problems restricted first results to straight-line driving.

Vogel, W. J.↗

Assessing High-Intensity Radiated Fields (HIRF) from High-Power Antennas for Air Vehicle Safety

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum effective isotropic radiated powers of the antenna are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show that the current standards for protecting vehicles are inadequate. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗

Assessing High-Intensity Radiated Fields (HIRF) from High-Power Antennas for Air Vehicle Safety

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum effective isotropic radiated powers of the antenna are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show that the current standards for protecting vehicles are inadequate. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗

HIRF Avoidance Approach for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based HIRF avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum antenna effective isotropic radiated powers are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show the current standards are far adequate in protecting the vehicles. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗

EMU Lessons Learned Database

As manned space exploration takes on the task of traveling beyond low Earth orbit, many problems arise that must be solved in order to make the journey possible. One major task is protecting humans from the harsh space environment. The current method of protecting astronauts during Extravehicular Activity (EVA) is through use of the specially designed Extravehicular Mobility Unit (EMU). As more rigorous EVA conditions need to be endured at new destinations, the suit will need to be tailored and improved in order to accommodate the astronaut. The Objective behind the EMU Lessons Learned Database(LLD) is to be able to create a tool which will assist in the development of next-generation EMUs, along with maintenance and improvement of the current EMU, by compiling data from Failure Investigation and Analysis Reports (FIARs) which have information on past suit failures. FIARs use a system of codes that give more information on the aspects of the failure, but if one is unfamiliar with the EMU they will be unable to decipher the information. A goal of the EMU LLD is to not only compile the information, but to present it in a user-friendly, organized, searchable database accessible to all familiarity levels with the EMU; both newcomers and veterans alike. The EMU LLD originally started as an Excel database, which allowed easy navigation and analysis of the data through pivot charts. Creating an entry requires access to the Problem Reporting And Corrective Action database (PRACA), which contains the original FIAR data for all hardware. FIAR data are then transferred to, defined, and formatted in the LLD. Work is being done to create a web-based version of the LLD in order to increase accessibility to all of Johnson Space Center (JSC), which includes converting entries from Excel to the HTML format. FIARs related to the EMU have been completed in the Excel version, and now focus has shifted to expanding FIAR data in the LLD to include EVA tools and support hardware such as the Pistol Grip Tool (PGT) and the Battery Charger Module (BCM), while adding any recently closed EMU-related FIARs.

Matthews, Kevin M., Jr.↗