Relevant bibliographies by topics / Air-mobile

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Air-mobile'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Air-mobile"

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Timoshek, Alexandra, Douglas Eisinger, Song Bai, and Deb Niemeier. "Mobile Source Air Toxic Emissions." Transportation Research Record: Journal of the Transportation Research Board 2158, no. 1 (January 2010): 77–85. http://dx.doi.org/10.3141/2158-10.

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Collet, Susan. "Mobile Source Air Toxic Emissions." Journal of the Air & Waste Management Association 66, no. 2 (January 15, 2016): 97. http://dx.doi.org/10.1080/10962247.2016.1128721.

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Goldstein, B. D., and J. Warren. "HEI's mobile air toxics project." Environmental Health Perspectives 101, no. 3 (August 1993): 256–58. http://dx.doi.org/10.1289/ehp.93101256.

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Kochneva, O. V., L. V. Podkolzina, A. V. Kozlovich, and D. V. Shabanov. "Mobile robotic air cushion system." IOP Conference Series: Earth and Environmental Science 539 (August 13, 2020): 012119. http://dx.doi.org/10.1088/1755-1315/539/1/012119.

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Hoffmann, Gabriele. "Refrigerants for Mobile Air Conditioning." ATZ worldwide 119, no. 1 (January 2017): 16–21. http://dx.doi.org/10.1007/s38311-016-0162-x.

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Lihui Lv, Lihui Lv, Wenqing Liu Wenqing Liu, Guangqiang Fan Guangqiang Fan, Tianshu Zhang Tianshu Zhang, Yunsheng Dong Yunsheng Dong, Zhenyi Chen Zhenyi Chen, Yang Liu Yang Liu, Haoyun Huang Haoyun Huang, and and Yang Zhou and Yang Zhou. "Application of mobile vehicle lidar for urban air pollution monitoring." Chinese Optics Letters 14, no. 6 (2016): 060101–60106. http://dx.doi.org/10.3788/col201614.060101.

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Cook, C. "Modeling Interference Effects for Land-Mobile and Air-Mobile Communications." IEEE Transactions on Communications 35, no. 2 (1987): 151–65. http://dx.doi.org/10.1109/tcom.1987.1096752.

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Erlangga, Yuliar Yasin, and Heri Setiawan. "PERANCANGAN MESIN PENGOLAH AIR BERSIH BERGERAK DENGAN MENGGUNAKAN SISTIM MODULAR UNTUK PENANGGULANGAN KEADAAN DARURAT AIR." Machine : Jurnal Teknik Mesin 4, no. 1 (January 2, 2018): 21–28. http://dx.doi.org/10.33019/jm.v4i1.448.

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ABSTRAK Pengolahan air bersih (Water Treatment) sistem modular/mobile (compact mobile) merupakan pengembangan dari sistem penyaringan air dengan sistem “up flow” yang sudah dikembangkan oleh BPPT dengan penambahan dan perbaikan fungsi proses dalam upaya mengoptimalkan proses pengolahan air baku menjadi air bersih. Pengembangan yang dilakukan pada penelitian ini yaitu dengan mengubah dari instalasi pengolahan yang tetap yang biasanya berbentuk civil work ke dalam sub fungsi-fungsi pengolah yang bersifat modular/mobile (compact mobile) dengan ukuran / dimensi yang tidak terlalu besar (compact design). Keuntungan yang bisa didapatkan dari sistem tersebut terutama dalam segi penanganan selama proses pengolahan dan dalam hal penyediaan suku cadang yang mudah sehingga waktu perbaikan disaat terjadi kerusakan pada mesin pengolahan air bersih ini menjadi sangat singkat dan juga ukuran / dimensi dari perangkat ini yang cukup kecil (compact) sehingga mudah dalam pemindahan antar lokasi untuk keadaan darurat air. Pada akhir penelitian ini setelah melalui proses perancangan menurut VDI 2222 dan sudah dilakukan penilaian berdasarkan beberapa aspek maka terbangun sebuah prototipe modular mobile water treatment berkapasitas pengolahan 1 M² per jam yaitu rancangan nomer 2 dengan nilai 92%. Aspek terbarukan yang dipelajari adalah desain modular mobile water treatment itu sendiri, penentuan dan pemilihan solusi dari sub fungsi bagian serta bagaimana sub-sub fungsi bagian tersebut diikatkan pada rangka sehingga instalasi tersebut menjadi kompak untuk dijadikan sebagai mobile water treatment.
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Reilly, Charles D., Stephen G. Waller, William J. Flynn, Miguel A. Montalvo, and Jane B. Ward. "U.S. Air Force Mobile Ophthalmic Surgery Team." Military Medicine 169, no. 12 (December 2004): 952–57. http://dx.doi.org/10.7205/milmed.169.12.952.

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Adams, Matthew, and Denis Corr. "A Mobile Air Pollution Monitoring Data Set." Data 4, no. 1 (December 22, 2018): 2. http://dx.doi.org/10.3390/data4010002.

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Air pollution was observed in Hamilton, Ontario, Canada using monitors installed in a mobile platform from November 2005 up to November 2016. The dataset is an aggregation of several project specific monitoring days, which attempted to quantify air pollution spatial variation under varying conditions or in specific regions. Pollutants observed included carbon monoxide, nitric oxide, nitrogen dioxide, total nitrogen oxides, ground-level ozone, particulate matter concentrations for size cuts of 10 µm, 2.5 µm and 1 µm, and sulfur dioxide. Observations were collected over 114 days, which occurred in varying seasons and months. During sampling, the mobile platform travelled at an average speed of 27 km/h. The samples were collected as one-minute integrated samples and are prepared as line-segments, which include an offset for instrument response time. Sampling occurred on major freeways, highways, arterial and residential roads. This dataset is shared in hopes of supporting research on how to best utilize air pollution observations obtained with mobile air pollution platforms, which is a growing technique in the field of urban air pollution monitoring. We conclude with limitations in the data capture technique and recommendations for future mobile monitoring studies.
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Dissertations / Theses on the topic "Air-mobile"

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Alvear, Alvear Óscar Patricio. "Mobile Sensing Architecture for Air Pollution Monitoring." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/107928.

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El crecimiento industrial ha acarreado grandes avances tecnológicos para nuestra sociedad. Lamentablemente, el precio a pagar por estos avances ha sido un aumento significativo de los niveles de contaminación del aire en todo el mundo, afectando tanto a zonas urbanas como a las zonas rurales. Por lo general, la monitorización de la calidad aire se realiza mediante estaciones de monitorización fijas. Sin embargo, este método es demasiado costoso, poco escalable y difícil de implementar en nuestras ciudades, las cuales están cada vez más pobladas. El uso de Mobile CrowdSensing, paradigma en el cual la monitorización la realizan los propios usuarios, permite realizar monitorización ambiental utilizando sensores móviles integrados en vehículos. Los posibles escenarios se pueden dividir en dos: entornos urbanos, donde hay un amplio conjunto de vehículos disponibles, y entornos rurales o industriales, donde el tráfico vehicular es escaso y está limitado a las principales arterias de transporte. Teniendo en cuenta estos dos escenarios, esta tesis propone una arquitectura, llamada EcoSensor, que permite monitorizar la contaminación del aire utilizando pequeños sensores de bajo coste instalados en diferentes tipos de vehículos, tales como bicicletas, automóviles o autobuses del sistema de transporte público, en el caso de entornos urbanos, y en drones o UAS en entornos rurales. La arquitectura propuesta está compuesta por tres componentes: un sensor de bajo coste para capturar datos de contaminación, un smartphone para realizar un preprocesamiento de la información y para transmitir los datos hacia un servidor central, y el servidor central, encargado de almacenar y procesar la información de contaminación ambiental. Para entornos urbanos, analizamos diferentes alternativas con respecto al diseño de una unidad de monitorización de bajo coste basada en plataformas de prototipado comerciales como RaspberryPi o Arduino, junto con sensores también de precio reducido. En la tesis realizamos un análisis, y proponemos un proceso, para llevar a cabo la monitorización ambiental utilizando la arquitectura propuesta. Este proceso abarca cuatro operaciones básicas: captura de datos, conversión de unidades, reducción de la variabilidad temporal, e interpolación espacial. Para entornos rurales, proponemos el uso de drones como unidades de sensorización móviles. Específicamente, equipamos el drone con capacidades de monitorización a través de un microordenador RaspberryPi y sensores de calidad del aire de bajo coste. Finalmente, se propone un algoritmo llamado PdUC para controlar el vuelo del UAV con el objetivo de realizar monitorización ambiental, identificando las áreas más contaminadas, y tratando de ese modo de mejorar la precisión general y la velocidad de monitorización. Además, proponemos una mejora a este algoritmo, denominada PdUC-D, basada en la discretización del área a monitorizar dividiéndola en pequeñas áreas (tiles), donde cada tile se monitoriza una sola vez, evitando así realizar muestreos redundantes. En general, verificamos que la monitorización móvil es una aproximación eficiente y fiable para monitorizar la contaminación del aire en cualquier entorno, ya sea usando vehículos o bicicletas en entornos urbanos, o UAVs en entornos rurales. Con respecto al proceso de monitorización ambiental, validamos nuestra propuesta comparando los valores obtenidos por nuestros sensores móviles de bajo coste con respecto a los valores típicos de referencia ofrecidos por las estaciones de monitorización fijas para el mismo período y ubicación, comprobando que los resultados son semejantes, y están acuerdo a lo esperado. Además, demostramos que PdUC-D, permite guiar autónomamente un UAV en tareas de monitorización del aire, ofreciendo un mejor rendimiento que los modelos de movilidad típicos, reduciendo tanto los errores de predicción como el tiempo para cubrir el área completa,
Industrial growth has brought unforeseen technological advances to our society. Unfortunately, the price to pay for these advances has been an increase of the air pollution levels worldwide, affecting both urban and countryside areas. Typically, air pollution monitoring relies on fixed monitoring stations to carry out the pollution control. However, this method is too expensive, not scalable, and hard to implement in any city. The Mobile Crowdsensing (MCS) approach, a novel paradigm whereby users are in charge of performing monitoring tasks, allows environment monitoring to be made using small sensors embedded in mobile vehicles. The possible scenarios can be divided into two: urban scenarios, where a wide set of vehicles are available, and rural and industrial areas, where vehicular traffic is scarce and limited to the main transportation arteries. Considering these two scenarios, in this thesis we propose an architecture, called EcoSensor, to monitor the air pollution using small sensors installed in vehicles, such as bicycles, private cars, or the public transportation system, applicable to urban scenarios, and the use of an Unmanned Aerial System (UAS) in rural scenarios. Three main components compose our architecture: a low-cost sensor to capture pollution data, a smartphone to preprocess the pollution information and transmit the data towards a central server, and the central server, to store and process pollution information. For urban scenarios, we analyze different alternatives regarding the design of a low-cost sensing unit based on commercial prototyping platforms such as Raspberry Pi or Arduino, and Commercial Off-the-shelf (COTS) air quality sensors. Moreover, we analyze and propose a process to perform pollution monitoring using our architecture. This process encompasses four basic operations: data reading, unit conversion, time variability reduction, and spatial interpolation. For rural scenarios, we propose the use of an Unmanned Aerial Vehicle (UAV) as a mobile sensor. Specifically, we equip the UAV with sensing capabilities through a Raspberry Pi microcomputer and low-cost air quality sensors. Finally, we propose an algorithm, called Pollution-driven UAV Control (PdUC), to control the UAV flight for monitoring tasks by focusing on the most polluted areas, and thereby attempting to improve the overall accuracy while minimizing flight time. We then propose an improvement to this algorithm, called Discretized Pollution-driven UAV Control (PdUC-D), where we discretize the target area by splitting it into small tiles, where each tile is monitored only once, thereby avoiding redundant sampling. Overall, we found that mobile sensing is a good approach for monitoring air pollution in any environment, either by using vehicles or bicycles in urban scenarios, or an UAVs in rural scenarios. We validate our proposal by comparing obtained values by our mobile sensors against typical values reported by monitoring stations at the same time and location, showing that the results are right, matching the expected values with a low error. Moreover, we proved that PdUC-D, our protocol for the autonomous guidance of UAVs performing air monitoring tasks, has better performance than typical mobility models in terms of reducing the prediction errors and reducing the time to cover the whole area.Moreover, we analyze and propose a process to perform pollution monitoring using our architecture. This process encompasses four basic operations: data reading, unit conversion, time variability reduction, and spatial interpolation.
El creixement industrial ha implicat grans avanços tecnològics per a la nostra societat. Lamentablement, el preu que cal pagar per aquests avanços ha sigut un augment significatiu dels nivells de contaminació de l'aire a tot el món, que afecta tant zones urbanes com zones rurals. En general, el monitoratge de la qualitat aire es fa mitjançant estacions de monitoratge fixes. No obstant això, aquest mètode és massa costós, poc escalable i difícil d'implementar a les nostres ciutats, les quals estan cada vegada més poblades. L'ús de Mobile CrowdSensing (MCS), paradigma en el qual el monitoratge el duen a terme els mateixos usuaris, permet realitzar monitorització ambiental tenint sensors mòbils integrats en vehicles. Els possibles escenaris es poden dividir en dos: entorns urbans, on hi ha un ampli conjunt de vehicles disponibles, i entorns rurals o industrials, on el trànsit vehicular és escàs i està limitat a les principals artèries de transport. Tenint en compte aquests dos escenaris, aquesta tesi proposa una arquitectura, anomenada EcoSensor, que permet monitorar la contaminació de l'aire utilitzant petits sensors de baix cost instal·lats en diferents tipus de vehicles, com ara bicicletes, automòbils o autobusos del sistema de transport públic, en el cas d'entorns urbans, i en UAVs (Unmanned Aerial Vehicles) en entorns rurals. L'arquitectura proposada està composta per tres components: un sensor de baix cost per a capturar dades de contaminació, un smartphone per a realitzar un preprocessament de la informació i per a transmetre les dades cap a un servidor central, i el servidor central, encarregat d'emmagatzemar i processar la informació de contaminació ambiental. Per a entorns urbans, analitzem diferents alternatives pel que fa al disseny d'una unitat de monitoratge (sensor mòbil) de baix cost basada en plataformes de prototipatge comercials com Raspberry Pi o Arduino, juntament amb sensors també de preu reduït. En la tesi fem una anàlisi, i proposem un procés, per a dur a terme el monitoratge ambiental utilitzant l'arquitectura proposada. Aquest procés abasta quatre operacions bàsiques: captura de dades, conversió d'unitats, reducció de la variabilitat temporal, i interpolació espacial. Per a entorns rurals, proposem l'ús de drons o Unmanned Aerial Vehicles (UAVs) com a unitats de sensorització mòbils. Específicament, equipem el dron amb capacitats de monitoratge a través d'un microordinador Raspberry Pi i sensors de qualitat de l'aire de baix cost. Finalment, es proposa un algorisme anomenat PdUC (Pollution-driven UAV Control) per a controlar el vol del UAV amb l'objectiu de realitzar monitoratge ambiental, que identifica les àrees més contaminades i que, d'aquesta manera, tracta de millorar la precisió general i la velocitat de monitoratge. A més, proposem una millora a aquest algorisme, denominada PdUC-D, basada en la discretització de l'àrea a monitorar dividint-la en xicotetes àrees (tiles), on cada tile es monitora una sola vegada, fet que evita dur a terme mostrejos redundants. En general, verifiquem que el monitoratge mòbil és una aproximació eficient i fiable per a monitorar la contaminació de l'aire en qualsevol entorn, ja siga usant vehicles o bicicletes en entorns urbans, o UAVs en entorns rurals. Pel que fa al procés de monitoratge ambiental, validem la nostra proposta comparant els valors obtinguts pels nostres sensors mòbils de baix cost pel que fa als valors típics de referència oferits per les estacions de monitoratge fixes per al mateix període i ubicació, i es comprova que els resultats són semblants, i estan d'acord amb el resultat esperat. A més, es demostra que PdUC-D permet guiar autònomament un UAV en tasques de monitoratge de l'aire, oferint un millor rendiment que els models de mobilitat típics, reduint tant els errors de predicció com el temps per a cobrir l'àrea completa, i aconseguint una major precisió dins de les àrees més
Alvear Alvear, ÓP. (2018). Mobile Sensing Architecture for Air Pollution Monitoring [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/107928
TESIS
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Rajaram, Dinakaran. "Secure Over the Air (OTA) Management Of Mobile Applications." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-116693.

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The Thesis report analyzes the possibility to store the application inside a secure environment in over the air Environment. The report clearly explains the details about the attributes which are placed in the over the air application management. Different forms of secure elements and how it can be placed inside the secure micro SD card have been discussed. The report gives the clear idea about secure micro SD card architecture. The report describes the OTA (Over the Air) components, Roles and also the process to manage the applications in OTA environment. The report also gives the clear about the protocols ISO 7816-4 which is used to communicate the handset with secure micro SD card. The communication concepts like establishing secure channel between the handset and secure micro SD card also has been discussed. Moreover, secure channel attributes are also discussed. They are Creation session key, MAC Operation and generation of derivation data. Secure micro SD card API‘s are also discussed which is used to communicate with the secure micro SD card .Some of the implementation work has been done by this research. They are >Constructed the Design of Trusted Service Manager (TSM) and Service provider. >Implemented the Functionality of TSM Server (Download Function) and tested the Functionality whether the end terminal (Android Phone) has been able to use the function properly. >Established the secure channel between the Android phone and secure micro SD card. >Loaded the sample application inside the secure micro SD card.
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Janaaththanan, Sundarampillai. "OFDM based air interfaces for future mobile satellite systems." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/773026/.

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This thesis considers the performance of OFDM in a non-linear satellite channel and mechanisms for overcoming the degradations resulting from the high PAPR in the OFDM signal in the specific satellite architecture. It was motivated by new S-DMB applications but its results are applicable to any OFDM system via satellites. Despite many advantages of OFDM, higher PAPR is a major drawback. OFDM signals are therefore very sensitive to non-linear distortion introduced by the power amplifiers and thus, significantly reduce the power efficiency of the system, which is already crucial to satellite system economics. Simple power amplifier back-off to cope with high OFDM PAPR is not possible. Two transmitter based techniques have been considered: PAPR reduction and amplifier linearization.
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Harbi, Yahya. "Enhanced air-interfaces for fifth generation mobile broadband communication." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/19155/.

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In broadband wireless multicarrier communication systems, intersymbol interference (ISI) and intercarrier interference (ICI) should be reduced. In orthogonal frequency division multiplexing (OFDM), the cyclic prefix (CP) guarantees to reduce the ISI interference. However, the CP reduces spectral and power efficiency. In this thesis, iterative interference cancellation (IIC) with iterative decoding is used to reduce ISI and ICI from the received signal in multicarrier modulation (MCM) systems. Alternative schemes as well as OFDM with insufficient CP are considered; filter bank multicarrier (FBMC/Offset QAM) and discrete wavelet transform based multicarrier modulation (DWT-MCM). IIC is applied in these different schemes. The required components are calculated from either the hard decision of the demapper output or the estimated decoded signal. These components are used to improve the received signal. Channel estimation and data detection are very important parts of the receiver design of the wireless communication systems. Iterative channel estimation using Wiener filter channel estimation with known pilots and IIC is used to estimate and improve data detection. Scattered and interference approximation method (IAM) preamble pilot are using to calculate the estimated values of the channel coefficients. The estimated soft decoded symbols with pilot are used to reduce the ICI and ISI and improve the channel estimation. The combination of Multi-Input Multi-Output MIMO and OFDM enhances the air-interface for the wireless communication system. In a MIMO-MCM scheme, IIC and MIMO-IIC-based successive interference cancellation (SIC) are proposed to reduce the ICI/ISI and cross interference to a given antenna from the signal transmitted from the target and the other antenna respectively. The number of iterations required can be calculated by analysing the convergence of the IIC with the help of EXtrinsic Information Transfer (EXIT) charts. A new EXIT approach is proposed to provide a means to define performance for a given outage probability on quasi-static channels.
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Meyer, Peter. "Air-pollution monitoring with a mobile CO₂-laser photoacoustic system /." Zürich, 1988. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=8651.

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Perugu, Harikishan C. "Integrating Advanced Truck Models into Mobile Source PM2.5 Air Quality Modeling." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377871388.

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Richard, Gaetan C., and Brian Donlin. "A NEW MOBILE TELEMETRY STATION FOR TESTING AIR-TO-GROUND WEAPONS." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/608379.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California
This paper describes a new mobile self contained telemetry station designed for field testing of air-to-ground weapons. The telemetry station makes creative use of existing equipment and incorporates a unique dual axis tracking system to provide complete coverage of most missions.
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Sklavos, Alexandros. "Service area based OFDM air interface for beyond 3G mobile radio systems." Kaiserslautern Techn. Univ, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?idn=972098607.

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Feng, Qixing. "Radio channel modelling for air-to-ground mobile communications in urban enviroments." Thesis, University of Bristol, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500653.

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Next generation mobile networks envisage ubiquitous communications at very high data rates. This imposes a major challenge to connectivity and capacity for terrestrial urban mobile communications, where the radio propagation fading is extremely severe. An airbased wireless system is expected to improve the coverage, extend the range, enhance the connectivity and reduce the required transmit power when integrated into a terrestrial wireless network. Existing radio channel models for land mobile satellite systems generally consider mobiles moving along roads in open areas such as main highways with low building densities along the sides of the road. New statistical point-to-area radio channel models are required to predict coverage, including locations near buildings, taking into account the height of the air platform.
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Westerlund, Kurt. "Near-road Dispersion Modeling of Mobile Source Air Toxics (MSATs) in Florida." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5724.

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There is a growing public concern that emissions of mobile source air toxics (MSATs) from motor vehicles may pose a threat to human health. At present, no state or federal agencies require dispersion modeling of these compounds, but many agencies are concerned about potential future requirements. Current air pollution professionals are familiar with Federal Highway Administration (FHWA) and U.S. Environmental Protection Agency (EPA) requirements for dispersion modeling to produce predicted concentrations for comparison with appropriate standards. This research examined a method in which the potential near-road concentrations of MSATs were calculated. It was believed that by assessing MSATs in much the same way that are used for other pollutants, the model and methods developed in this research could become a standard for those quantifying MSAT concentrations near-roadways. This dissertation reports on the results from short-term (1-hour) and long-term (annual average) MSATs dispersion modeling that has been conducted on seven intersections and seven freeway segments in the state of Florida. To accomplish the modeling, the CAL3QHC model was modified to handle individual MSAT emissions input data and to predict the concentrations of several MSATs around these roadway facilities. Additionally, since the CAL3MSAT model is DOS based and not user-friendly, time was invested to develop a Windows&"174; graphical user interface (GUI). Real-world data (traffic volumes and site geometry) were gathered, worst-case meteorology was selected, mobile source emission factors (EFs) were obtained from MOVES2010a, and worst-case modeling was conducted. Based on a literature search, maximum acceptable concentrations (MACs) were proposed for comparison with the modeled results, for both a short-term (1-hour) averaging time and a long-term (1-year) averaging time. Results from this CAL3MSAT modeling study indicate that for all of the intersections and freeway segments, the worst-case 1-hour modeled concentrations of the MSATs were several orders of magnitude below the proposed short-term MACs. The worst-case 1-year modeled concentrations were of the same order of magnitude as the proposed long-term MACs. The 1-year concentrations were first developed by applying a persistence factor to the worst-case 1-hour concentrations. In the interest of comparing the predicted concentrations from the CAL3MSAT persistence factor approach to other dispersion models, two EPA regulatory models (CAL3QHCR and AERMOD) with the ability to account for yearly meteorology, traffic, and signal timing were used. Both hourly and annual MSAT concentrations were predicted at one large urban intersection and compared for the three different dispersion models. The short-term 1-hour results from CAL3MSAT were higher than those predicted by the two other models due to the worst-case assumptions. Similarly, results indicate that the CAL3MSAT persistence factor approach predicted a worst-case annual average concentration on the same order of magnitude as the two other more refined models. This indicated that the CAL3MSAT model might be useful as a worst-case screening approach.
Ph.D.
Doctorate
Civil, Environmental, and Construction Engineering
Engineering and Computer Science
Environmental Engineering
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Books on the topic "Air-mobile"

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Florida. Legislature. Senate. Committee on Transportation. Compliance with Federal Clean Air Act, mobile sources. [Tallahassee, FL]: The Committee, 1997.

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Wackter, David. Evaluation of mobile source air quality simulation models. Research Triangle Park, NC: The Office, 1986.

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Khan, Farooq. LTE for 4G mobile broadband: Air interface technologies and performance. Cambridge, UK: Cambridge University Press, 2009.

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LTE for 4G mobile broadband: Air interface technologies and performance. Cambridge, UK: Cambridge University Press, 2009.

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Frangos, Constantinos. Mathematical Modelling, Nonlinear Control and Performance Evaluation of a Ground Based Mobile Air Defence System. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-55498-9.

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Strub, Christopher M. The international legal implications of the Mobile Offshore Base: No army or air force is an island. Monterey, Calif: Naval Postgraduate School, 1997.

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California. Legislature. Assembly. Committee on Environmental Safety and Toxic Materials. Interim hearing on mobile air conditioners: CFC emissions and environmental impact AB 2532 (Vasconcellos), October 24, 1989. Sacramento, Calif: State Capital, 1989.

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Li yong Android qiang li kai fa Adobe AIR cheng shi. Taibei Shi: Jia kui zi xun, 2016.

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Heller, Jonathan. Manufactured housing acquisition program (MAP): Ventilation and heat recovery system cost/benefit analysis. Seattle, WA: Ecotope, 1993.

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Administration, Bonneville Power. Field measurements of the heating efficiency of electric forced-air furnaces in six manufactured homes. Seattle, WA: Ecotope, 1994.

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Book chapters on the topic "Air-mobile"

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Bernieri, A., G. Betta, L. Ferrigno, and M. Laracca. "Mobile System for Air Pollution Evaluation." In Lecture Notes in Electrical Engineering, 423–27. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00684-0_81.

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Wang, You-Chiun. "Mobile Solutions to Air Quality Monitoring." In Mobile Solutions and Their Usefulness in Everyday Life, 225–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93491-4_12.

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Deaton, Michael L., and James J. Winebrake. "Modeling Mobile Source Air Pollution Inventories." In Dynamic Modeling of Environmental Systems, 142–57. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1300-0_7.

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Wang, Yuwen, Lei Wang, WeiJiong Zhang, and Dingde Jiang. "A Space-Air-Ground Integrated Networking Method for Air Mobile Targets." In Simulation Tools and Techniques, 117–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72792-5_11.

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Frangos, Constantinos. "Overview of the Mobile Air Defence System." In Mathematical Modelling, Nonlinear Control and Performance Evaluation of a Ground Based Mobile Air Defence System, 15–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-55498-9_2.

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Khan, Mohammed Shafiul Alam, and Chris J. Mitchell. "Improving Air Interface User Privacy in Mobile Telephony." In Security Standardisation Research, 165–84. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27152-1_9.

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Koval, Anton, and Eloy Irigoyen. "Mobile Wireless System for Outdoor Air Quality Monitoring." In International Joint Conference SOCO’16-CISIS’16-ICEUTE’16, 345–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47364-2_33.

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Frangos, Constantinos. "Kinematic Model of the Mobile Air Defence System." In Mathematical Modelling, Nonlinear Control and Performance Evaluation of a Ground Based Mobile Air Defence System, 51–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-55498-9_3.

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Frangos, Constantinos. "Operational Modes of the Mobile Air Defence System." In Mathematical Modelling, Nonlinear Control and Performance Evaluation of a Ground Based Mobile Air Defence System, 83–96. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-55498-9_5.

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Hampe, J. Felix, and Gerhard Schwabe. "Enhancing Mobile Commerce: Instant Music Purchasing over the Air." In Seeking Success in E-Business, 107–30. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-0-387-35692-1_7.

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Conference papers on the topic "Air-mobile"

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Hedgecock, W., P. Völgyesi, A. Ledeczi, X. Koutsoukos, A. Aldroubi, A. Szalay, and A. Terzis. "Mobile air pollution monitoring network." In the 2010 ACM Symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1774088.1774253.

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Wiggins, Jason. "US Air Force Mobile Range Efficiencies." In SpaceOps 2012. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-1273979.

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Tudose, Dan Stefan, Traian Alexandru Patrascu, Andrei Voinescu, Razvan Tataroiu, and Nicolae Tapus. "Mobile sensors in air pollution measurement." In 2011 8th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2011. http://dx.doi.org/10.1109/wpnc.2011.5961035.

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Radecki, Richard L. "Mobile Air Conditioning and CFC's - An Update." In Automotive Industry in Expanding Countries. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1991. http://dx.doi.org/10.4271/911729.

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Ketabdar, Hamed, Peyman Moghadam, Babak Naderi, and Mehran Roshandel. "Magnetic signatures in air for mobile devices." In the 14th international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2371664.2371705.

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Carvalho, Vasco, Jose Gabriel Lopes, Helena G. Ramos, and F. Correa Alegria. "City-wide mobile air quality measurement system." In 2009 IEEE Sensors. IEEE, 2009. http://dx.doi.org/10.1109/icsens.2009.5398299.

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Magnetto, Daniela, Stefano Mola, David H. DaCosta, Mark Golben, and Matthew Rosso. "A Metal Hydride Mobile Air Conditioning System." In SAE 2006 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2006. http://dx.doi.org/10.4271/2006-01-1235.

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Song, Jie, Gábor Sörös, Fabrizio Pece, Sean Ryan Fanello, Shahram Izadi, Cem Keskin, and Otmar Hilliges. "In-air gestures around unmodified mobile devices." In UIST '14: The 27th Annual ACM Symposium on User Interface Software and Technology. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2642918.2647373.

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Park, KwangJin, Patrick Valduriez, and Hyunseung Choo. "Mobile continuous nearest neighbor queries on air." In the 16th ACM SIGSPATIAL international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1463434.1463510.

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Agrawal, Sandip, Ionut Constandache, Shravan Gaonkar, Romit Roy Choudhury, Kevin Caves, and Frank DeRuyter. "Using mobile phones to write in air." In the 9th international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1999995.1999998.

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Reports on the topic "Air-mobile"

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Mei, V., F. Chen, and D. Kyle. Alternative non-CFC mobile air conditioning. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/10191842.

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Mei, V., F. Chen, and D. Kyle. Alternative non-CFC mobile air conditioning. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/6930880.

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Brainard, Gregory F., Andrew A. Thompson, and James P. Lucas. Air Conditioner Requirements Validation Review of Mobile Subscriber Equipment (MSE). Fort Belvoir, VA: Defense Technical Information Center, May 1992. http://dx.doi.org/10.21236/ada251469.

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Adkison, Jesse D. Data Supporting Mobile Application Development for Use within the Marine Air-Ground Task Force. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ad1008832.

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Tokarz, F. J., J. F. Cooper, and D. Haley. Commercialization of LLNL Zinc Air Fuel Cell Technology For Stationary And Mobile Applications And Electromechanical Battery For Mobile Applications Final Report CRADA No. TC-1420-97. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1408984.

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Carter, Donald T. Managing the Financial and Operational Issues Associated with the Hickam Air Force Base Trunked Land Mobile Radio Project,. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada302725.

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Moskowitz, Warren P., and Gilbert Davidson. Program to Increase the Measurement Capabilities of the AFGL (Air Force Geophysics Laboratory) Fixed and Mobile High Altitude Lidar Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1988. http://dx.doi.org/10.21236/ada194614.

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Pekney, Natalie J., Matthew Reeder, Garret A. Veloski, and J. Rodney Diehl. Data Report for Monitoring at Six West Virginia Marcellus Shale Development Sites using NETL’s Mobile Air Monitoring Laboratory (July–November 2012). Office of Scientific and Technical Information (OSTI), June 2016. http://dx.doi.org/10.2172/1330216.

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Quinn, Matthew J., Curtis Hopkins, and Vern Wing. U.S. Air Force Operational Medicine: Using the Enterprise Estimating Supplies Program to Develop Materiel Solutions for the Mobile Aeromedical Staging Facility (FFQM1). Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada570243.

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Technology News 559 - mobile dry scrubber provides cleaner air for downwind roof bolter. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, September 2017. http://dx.doi.org/10.26616/nioshpub2017208.

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