2,246 research outputs found

    UMaine Engineering

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    Promotional magazine for the University of Maine\u27s College of Engineering. This issue explores the energy generation and energy transmission-related engineering programs being conducted by faculty, staff, and students with the College of Engineering. Topics include the College of Engineering\u27s response to COVID-19, particle research in aquaculture, Evergreen AI, and harnessing off-shore wind power.https://digitalcommons.library.umaine.edu/umaine_today/1078/thumbnail.jp

    ME-EM 2014-15 Annual Report

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    Table of Contents Human-centered Engineering Endowed Department Chair Enrollment & Degrees Graduates Department News Faculty & Staff Alumni Donors Contracts & Grants Patents & Publications Faculty & Staff Directoryhttps://digitalcommons.mtu.edu/mechanical-annualreports/1004/thumbnail.jp

    Development of an empirical dust storm attenuation prediction model for microwave links in arid area – a proposed framework

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    Wireless communication service providers are currently facing challenges due to the congested frequencies spectrum which has imposed the use of higher and higher frequencies. However, higher frequency bands are more sensitive to weather condition and the microwave signal attenuation due to atmospheric particles increases rapidly at higher frequency bands. Consequently dust storms and other phenomena cause signal attenuation which can limit the performance of wireless communication systems for the frequencies above 10GHz in arid area. The paper aim is to show that real dust storm is a complex phenomena which is difficult to be described by the theoretical physical or mathematical models. An empirical dust storm prediction model based on the long term statistical observations of dust storm properties and its corresponding microwave signal levels will be a step forward to provide microwave link designers with a precise tool to rely on. This paper has proposed a research framework to collect necessary data from Khartoum, Sudan and develop an empirical attenuation prediction model
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