Bibliografías temáticas / Air Data System

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Literatura académica sobre el tema "Air Data System"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 19 de febrero de 2022

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Artículos de revistas sobre el tema "Air Data System"

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Lie, F. Adhika Pradipta y Demoz Gebre-Egziabher. "Synthetic Air Data System". Journal of Aircraft 50, n.º 4 (julio de 2013): 1234–49. http://dx.doi.org/10.2514/1.c032177.

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Shyam Mohan, N., M. Jayakumar, T. Sivamurugan, K. C. Finitha, S. B. Vidya, Jayanta Dhoaya, N. Remesh, M. Prasath, Shashi Krishna y Aisha Sidhique. "Flush Air Data Sensing System". Current Science 114, n.º 01 (10 de enero de 2018): 68. http://dx.doi.org/10.18520/cs/v114/i01/68-73.

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ZHOU, WeiJiang, GuoHui DOU, XiuXin DOU, WuYue LIU y GuangQiang CHEN. "Flush air data sensing system design for air breathing air-to-air missile". SCIENTIA SINICA Technologica 46, n.º 11 (28 de octubre de 2016): 1193–206. http://dx.doi.org/10.1360/n092016-00258.

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Benbassat, Danny y Levent Ileri. "Next Generation Air Transportation System: Data Communications". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 54, n.º 1 (septiembre de 2010): 114–15. http://dx.doi.org/10.1177/154193121005400125.

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Freeman, Paul, Peter Seiler y Gary J. Balas. "Air data system fault modeling and detection". Control Engineering Practice 21, n.º 10 (octubre de 2013): 1290–301. http://dx.doi.org/10.1016/j.conengprac.2013.05.007.

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Schmidt, Walter, Ari-Matti Harri, Timo Nousiainen, Harri Hohti, Lasse Johansson, Olli Ojanperä, Erkki Viitala et al. "CITYZER observation network and data delivery system". Geoscientific Instrumentation, Methods and Data Systems 9, n.º 2 (13 de octubre de 2020): 397–406. http://dx.doi.org/10.5194/gi-9-397-2020.

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Abstract. CITYZER develops new digital services and products to support decision-making processes related to weather and air quality in cities. This includes, for example, early warnings and forecasts (0–24 h), which allow for avoiding weather-related accidents, mitigate human distress and costs from weather-related damage and bad air quality, and generally improve the resilience and safety of the society. The project takes advantage of the latest scientific know-how and directly exploits the expertise obtained from earlier projects. Central to the project is the Observation Network Manager NM10 developed by Vaisala, on which CITYZER defines and builds new commercial services and connects new sensor networks, for example, for air quality measurements, as well as the ENFUSER local-scale air quality modelling system developed by the Finnish Meteorological Institute, for real-time air quality forecasts and nowcasts.
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Liu, A. Gu Da Mu, Peng Yang, Wen Sheng Lv y Jie Liu. "Air Quality Data Management System Based on VB.NET". Advanced Materials Research 955-959 (junio de 2014): 1147–50. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.1147.

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In order to achieve the automatic management of air quality monitoring data, the air quality data management system has been developed using VB.NET platform and Oracle as background database. It is also combined with the situation of the air quality in Beijing and based on the air quality monitoring data. The paper analyzes the system from 6 aspects, including technology selection, system architecture, system data flow diagram, system development environment, system functions and system features. Finally this paper explains the significance of the system development and application prospects.
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Czechowski, Piotr, Artur Badyda y Grzegorz Majewski. "Data Mining System for Air Quality Monitoring Networks". Archives of Environmental Protection 39, n.º 4 (1 de diciembre de 2013): 123–47. http://dx.doi.org/10.2478/aep-2013-0041.

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Abstract The use of quantitative methods, including stochastic and exploratory techniques in environmental studies does not seem to be sufficient in practical aspects. There is no comprehensive analytical system dedicated to this issue, as well as research regarding this subject. The aim of this study is to present the Eco Data Miner system, its idea, construction and implementation possibility to the existing environmental information systems. The methodological emphasis was placed on the one-dimensional data quality assessment issue in terms of using the proposed QAAH1 method - using harmonic model and robust estimators beside the classical tests of outlier values with their iterative expansions. The results received demonstrate both the complementarity of proposed classical methods solution as well as the fact that they allow for extending the range of applications significantly. The practical usefulness is also highly significant due to the high effectiveness and numerical efficiency as well as simplicity of using this new tool.
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Jing, You Yin, Qian Qian Liu y Jiang Jiang Wang. "System Optimization and Exergy Analysis of Air Conditioning System for Data Center". Applied Mechanics and Materials 291-294 (febrero de 2013): 1857–62. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.1857.

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As the air conditioning energy consumption of the date center has increasingly become the focus of attention, reformation for the energy consumption and exploration for the suitable combination model of the air conditioning system have significance in energy saving. This paper makes a program design for the air-conditioning system of a data center in Beijing, makes an analysis of the system operation mode and uses the concept of exergy efficiency to optimize the air conditioning system in order to achieve maximum efficiency.
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Johnston, Ian A., Peter A. Jacobs y Takayuki Shimoda. "Flush Air Data System Calibration Using Numerical Simulation". Journal of Spacecraft and Rockets 35, n.º 6 (noviembre de 1998): 812–20. http://dx.doi.org/10.2514/2.3404.

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Tesis sobre el tema "Air Data System"

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Morrison, Thomas M. "THE USE OF TELEMETRY DATA IN AN AIR DATA SYSTEM". International Foundation for Telemetering, 2006. http://hdl.handle.net/10150/604135.

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ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California
Telemetry data are usually collected for analysis at some later time and can be monitored to follow the progress of a test. In the case of an Air Data System the signals from the sensors are sent to a computer that calculates the air data parameters for use on multiple LabView-generated displays, as well as to the Data Acquisition System. The readouts on the multiple displays need to be real-time so they are useful to the flight crew. Equations that control the different air data values are determined by what telemetry data are available and the preference of those doing the test planning. These systems need to display the information in a format useful to the flight crew and be reliable.
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Lin, Joyce C. (Joyce Chaisin) 1979. "VisualFlight : the air traffic control data analysis system". Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87266.

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Gray, Paula Margaret. "System tool for aircraft routing". Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/24398.

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Operations Planning at CP Air is responsible for keeping an up-to-date visual representation of the aircraft routings for the current schedule period and co-ordinating subsequent changes. Examples of changes are requests for extra usage such as charters or extra sections, changes to the maintenance schedule, and unforeseen circumstances. The present approach is a manual charting method used in the same or similar form by many airlines as well as at CP Air. This manual process is long and tedious and even minor changes can cause much work to keep the charts up-to-date and everyone informed. What is needed is an automated system that will present the information produced on the charts in the most useable manner plus the ability to make changes so that, the resulting information can be more effectively used than with the present manual method. The approach taken is the development of a. Decision Support tool that will allow Operations Planning to make decisions based on their knowledge and experience. This solution is a starting point in an area at CP Air that has long needed some automation. The system has been developed on the Virtual Machine operating system using I BrA 3279 equipment for its color capabilities, and it is currently in the stages of system testing and user-training.
Business, Sauder School of
Graduate
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Ochodnická, Zuzana. "Data mining process automatization of air pollution data by the LISp-Miner system". Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-192393.

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This thesis is focused on the area of automated data mining. The aim of this thesis is a description of the area of automated data mining, creation of a design of an automated data mining tasks creation process for verification of set domain knowledge and new knowledge search, and also an implementation of verification of set domain knowledge of attribute dependency type influence with search space adjustments. The implementation language is the LMCL language that enables usage of the LISp-Miner system's functionality in an automated way. These data analyses were performed on data from air pollution monitoring. The design and implementation were successful and the created scripts could be used (with some manual changes in initial parameters) for analyses of another dataset as well.
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Ozer, Huseyin Erman. "Air Data System Calibration For Military Transport Aircraft Modernization Program". Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615690/index.pdf.

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This thesis presents the calibration processes of the pitot-static system, which is a part of the air data system of a military transport aircraft through flight tests. Tower fly-by method is used for air data system calibration. Altitude error caused by the position of the static port on the aircraft is determined by analyzing the data collected during four sorties with different weight, flap and landing gear configurations. The same data has been used to determine the airspeed measurement error. It has been shown that both the altitude and airspeed errors are within the allowable limits specified by FAR 25. Same method is also used for trailing cone calibration that is used for high altitude test flights for RVSM certification.
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Raghuraman, Arvind Greene Michael E. "Efforts toward design, development and implementation of an integrated and flexible support system for calibration of air data attitude heading reference systems". Auburn, Ala., 2007. http://repo.lib.auburn.edu/2006%20Fall/Theses/RAGHURAMAN_ARVIND_46.pdf.

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Black, Richard Allyn. "A flush mounted microelectromechanical system (MEMS) pressure and flow sensor based air data system /". Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/10012.

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Carvalho, Rubens Felipe Quintanilha de. "Um método para modelagem de sistemas aplicado a um air data system". Instituto Tecnológico de Aeronáutica, 2011. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=2815.

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Nas últimas décadas constatou-se o uso cada vez mais massivo de sistemas computadorizados principalmente em setores da indústria aeronáutica. Na busca pelo aumento de eficiência no desenvolvimento, recomenda-se o uso do Desenvolvimento Baseado em Modelos (MBD). Este trabalho de pesquisa propõe um Método para Modelagem de Sistemas, denominado M2S, como forma de se bene?ciar da modelagem do sistema desde os estágios iniciais de concepção do sistema. Esta abordagem visa diminuir o ciclo de vida de desenvolvimento e aumentar a qualidade das especi?cações. Nesse sentido, o método proposto se baseia na Linguagem de Modelagem de Sistemas (SysML), no Processo Uni?cado (RUP), no uso de Ambientes Integrados de Engenharia de Software Auxiliada por Computador (I-CASE-E) e na geração automática de código. Após combinar estes elementos num conjunto de passos que compõe o método proposto, realizou-se por meio de um estudo de caso a veri?cação da aplicação do método. O estudo de caso envolveu o desenvolvimento de um protótipo do Sistema de Dados Anemométricos (Air Data System - ADS), com dois experimentos. Foi possível constatar a facilidade em segregar as fases de desenvolvimento, realizar a evolução gradual das especi?cações e modelos, para ?nalmente se chegar a transformação dos modelos independentes de plataforma em código fonte e se constituir o protótipo. Aplicou-se testes e métricas de Halstead, de Linhas de Código e de Complexidade Ciclomática como forma de comparar os dois experimentos.
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Zhalgasbekova, Aigerim. "CollMule: An Opportunistic Data Collection System for IoT-based Indoor Air Quality Monitoring". Thesis, Luleå tekniska universitet, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65346.

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Jensen, Luke L. "Data-driven flight procedure simulation and noise analysis in a large-scale air transportation system". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119288.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 227-234).
Aircraft noise is a growing source of community concern around airports. Despite the introduction of quieter aircraft, increased precision of onboard guidance systems has resulted in new noise impacts driven by overflight frequency effects. Noise issues present a potential barrier to the continued rollout of advanced operational procedures in the US. This thesis presents a data-driven approach to simulating and communicating noise effects in the flight procedure development and modernization process, with input from multiple stakeholders with varying objectives that are technical, operational, and political in nature. First, a system-level framework is introduced for developing novel noise-reducing arrival and departure flight procedures, clarifying the role of the analyst given diverse stakeholder objectives. The framework includes relationships between baseline impact assessment, community negotiation, iterative flight procedure development, and formal implementation processes. Variability in stakeholder objectives suggests a need to incorporate noise issues in conjunction with other key operational objectives as part of larger-scale US air transportation system modernization. As part of this framework development, an airport-level noise modeling method is developed to enable rapid exposure and impact analysis for system-level evaluation of advanced operational procedures. The modeling method and framework are demonstrated by evaluating potential benefits of specific advanced procedures at 35 major airports in the US National Airspace System, including Performance Based Navigation guidance and a speed-managed departure concept.
by Luke L. Jensen.
Ph. D.
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Libros sobre el tema "Air Data System"

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Schroder, Ron. Content Data Model (CDM) and Improved Technical Data System (ITDS) compatibility analysis. Brooks Air Force Base, Tex: Air Force Human Resources Laboratory, Air Force Systems Command, 1989.

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Leeuwen, S. Storm van. A simple and low cost system to measure delay times in pneumatic systems. Amsterdam: National Aerospace Laboratory, 1990.

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Wilkinson, S. W. The NOAA King Air Airborne Data Acquisition System: Description and user's guide. Silver Spring, Md: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1988.

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Wilkison, Stan W. The NOAA King Air Airborne Data Acquisition System: Description and user's guide. Silver Spring, Md: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1988.

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S, Barnhardt Robert, Walker Warren E, Rand Corporation y United States Air Force, eds. Selecting a decision support system generator for the Air Force's Enlisted Force Management System. Santa Monica, CA: Rand, 1986.

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G, Walker Robert. Selecting a decision support system generator for the Air Force's enlisted force management system. Santa Monica, CA: The Rand Corp., 1985.

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Shi, Feng. Learn About Time Series ARIMA in SPSS With Data From EPA’s Air Quality System Data Mart (2017). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526473141.

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Shi, Feng. Learn About Time Series Plot in SPSS With Data From EPA’s Air Quality System Data Mart (2017). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526473165.

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Petruschell, R. L. Using the Air Force maintenance data collection system data to identify candidates for improvement in relaibility and maintainability. Santa Monica, CA: Rand, 1987.

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Shi, Feng. Learn About Time Series Cross-Correlations in SPSS With Data From EPA’s Air Quality System Data Mart (2017). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526473158.

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Capítulos de libros sobre el tema "Air Data System"

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Liu, Xiufeng y Per Sieverts Nielsen. "Air Quality Monitoring System and Benchmarking". En Big Data Analytics and Knowledge Discovery, 459–70. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64283-3_34.

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Silver, Jeremy D., Jesper H. Christensen, Michael Kahnert, Lennart Robertson y Jørgen Brandt. "Evaluation of a Chemical Data Assimilation System". En Air Pollution Modeling and its Application XXIII, 439–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_72.

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Patil, Deepika, T. C. Thanuja y B. C. Melinamath. "Air Pollution Monitoring System Using Wireless Sensor Network (WSN)". En Data Management, Analytics and Innovation, 391–400. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1402-5_30.

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Jyoti, Gautam, Malsa Nitima, Singhal Vikas y Malsa Komal. "Calculating AQI Using Secondary Pollutants for Smart Air Management System". En Data Management, Analytics and Innovation, 131–40. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9364-8_10.

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Liu, Yin, Renbo Guan, Jing Ma y Ke Zhang. "Research of Data Center Fresh Air Ventilation Cooling System". En Lecture Notes in Electrical Engineering, 299–306. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39581-9_30.

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Shi, Feng, Peng Cheng, Rui Geng y Mo Yang. "An Air Traffic Flow Analysis System Using Historical Radar Data". En Recent Advances in Computer Science and Information Engineering, 541–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25766-7_72.

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Zheng, Yuwei, Zhen Li, Xiaohua Liu, Zhen Tong y Rang Tu. "Retrofit of Air-Conditioning System in Data Center Using Separate Heat Pipe System". En Lecture Notes in Electrical Engineering, 685–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39581-9_67.

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Thosar, Anil y Rohan Nathi. "Air Quality Parameter Measurements System Using MQTT Protocol for IoT Communication Over GSM/GPRS Technology". En Data Management, Analytics and Innovation, 421–33. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1402-5_32.

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Schumann, Johann, Karen Cate y Alan Lee. "Analysis of Air Traffic Track Data with the AutoBayes Synthesis System". En Logic-Based Program Synthesis and Transformation, 21–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20551-4_2.

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Chen, Guangqiang, Xiuxin Dou, Guohui Dou, Weijiang Zhou y Yunjun Yang. "Flush Air Data Sensing System Design and Test for Supersonic Vehicle". En Lecture Notes in Electrical Engineering, 74–81. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3305-7_6.

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Actas de conferencias sobre el tema "Air Data System"

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Friehmelt, Holger y Michael Jost. "Flush air data system - An advanced air data system for aerospace applications". En Atmospheric Flight Mechanics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4191.

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Jost, Michael, Frank Schwegmann y T. Kohler. "Flush Air Data System - An Advanced Air Data System for the Aerospace Industry". En AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.2004-5028.

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Tsybina, M., V. Almazov y M. Sorokin. "Estimation of characteristics of multifunctional air data probe for air data system". En 2017 2nd International Ural Conference on Measurements (UralCon). IEEE, 2017. http://dx.doi.org/10.1109/uralcon.2017.8120695.

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Abbas, S. H., M. Y. A. Khan y I. Pervez. "Automation of Air Data Test System". En 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2011). IEEE, 2011. http://dx.doi.org/10.1109/urai.2011.6145867.

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Khamlae, Ponlawat, Chollakorn Nimpattanavong, Worawat Choensawat y Kingkarn Sookhanaphibarn. "Visualization System for Air Traffic data". En 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE). IEEE, 2020. http://dx.doi.org/10.1109/gcce50665.2020.9291971.

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Tchoryk, Jr., Peter, Christopher B. Watkins, Scott K. Lindemann, Paul B. Hays y Carl A. Nardell. "Molecular optical air data system (MOADS)". En Aerospace/Defense Sensing, Simulation, and Controls, editado por Gary W. Kamerman. SPIE, 2001. http://dx.doi.org/10.1117/12.440108.

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Westhelle, C. "X-38 Backup Air Data System (AeroDAD)". En 40th AIAA Aerospace Sciences Meeting & Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-7.

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Gupta, Karan y Nitin Rakesh. "IoT Based Automobile Air Pollution Monitoring System". En 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, 2018. http://dx.doi.org/10.1109/confluence.2018.8442717.

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Sellers, Marvin. "AEDC's Portable Pressure-Sensitive Paint Data Acquisition System". En 2007 U.S. Air Force T&E Days. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2007. http://dx.doi.org/10.2514/6.2007-1606.

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DESHPANDE, SAMIR, RENJITH KUMAR, HANS SEYWALD y PAUL SIEMERS, III. "Air data system optimization using a genetic algorithm". En Guidance, Navigation and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-4466.

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Informes sobre el tema "Air Data System"

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Robinson, Scott B. y Laurie A. Blanchard. Cold Air Data Acquisition System Documentation. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2003. http://dx.doi.org/10.21236/ada419763.

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McLaren, Scott, Sreeram Jayashankar, William Rothermel, Corey Beaverson y Donny Powers. Back Up Velocity Estimate Following Air Data System Failure (Project Have Vest). Fort Belvoir, VA: Defense Technical Information Center, diciembre de 2007. http://dx.doi.org/10.21236/ada479288.

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Geib, Christopher, John M. Frazier y Robert S. Cook. Air Force Genomics, Proteomics, Bioinformatics System, DataCap-Data Collection Module. Phase 1: Development. Fort Belvoir, VA: Defense Technical Information Center, julio de 2004. http://dx.doi.org/10.21236/ada435020.

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Scheiber, Lane B., Richard Morton, Harold Shoemaker y Robert Walker. An Independent Assessment of Two Fire Support Systems, AFATDS (Advanced Field Artillery Tactical Data System) and MIFASS (Marine Integrated Fire and Air Support System). Fort Belvoir, VA: Defense Technical Information Center, enero de 1987. http://dx.doi.org/10.21236/ada178016.

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Bailey, William D., Andrew J. Knoedler, David A. Harris y Bruce H. McClintock. Investigation of Using Global Positioning for Air Data System Calibration of General Aviation Aircraft (Have Pacer II). Fort Belvoir, VA: Defense Technical Information Center, enero de 1996. http://dx.doi.org/10.21236/ada303524.

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Damos, Diane L. y R. B. Gould. Feasibility of Developing a Common U.S. Army Helicopter Pilot Candidate Selection System: Analysis of U.S. Air Force Data. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2007. http://dx.doi.org/10.21236/ada475385.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Illustration Transfer Using: Texas Instruments' Data Supporting: Naval Air System Command's JSOW Program, MIL-D-28003 (CGM). Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, abril de 1994. http://dx.doi.org/10.21236/ada312986.

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DiJoseph, Patricia, Brian Tetreault y Marin Kress. AIS data case Study : identifying AIS coverage gaps on the Ohio River in CY2018. Engineer Research and Development Center (U.S.), junio de 2021. http://dx.doi.org/10.21079/11681/40886.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes a method for evaluating the received coverage from Automatic Identification System (AIS) shore sites and the availability of historic vessel position reports along the Ohio River. The network of AIS shoreside sites installed and operated by the US Army Corps of Engineers (USACE) and the US Coast Guard (USCG) receive information transmitted from vessels; however, reception of these transmissions is generally line-of-sight between the vessel and the AIS site antenna. Reception may also be affected by factors such as the quality of the transceiver installation aboard the vessel as well as the state of the equipment at the receiving site. Understanding how to define and quantify coverage gaps along the inland river system can inform research utilizing AIS data, provide information on the performance of the AIS network, and provide guidance for efforts to address identified coverage gaps
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Sandberg, David V., Colin C. Hardy, Roger D. Ottmar, J. A. Kendall Snell, Ann Acheson, Janice L. Peterson, Paula Seamon, Peter Lahm y Dale Wade. National strategic plan: modeling and data systems for wildland fire and air quality. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1999. http://dx.doi.org/10.2737/pnw-gtr-450.

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Devarakonda, Ranjeet, Jitendra Kumar, Dalton Lunga, Jong Choi y Giri Prakash. AI-Driven Data Discovery to Improve Earth System Predictability. Office of Scientific and Technical Information (OSTI), abril de 2021. http://dx.doi.org/10.2172/1769671.

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