260 research outputs found

    Mapping training and development provision for early years practitioners

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    Final report for Creativity, Culture and Educatio

    Cyclic Loading of Glued-In FRP Rods in Timber:Experimental and Analytical Study

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    A STUDY OF THE FACTORS INFLUENCING LAST MILE RESIDENTIAL FIXED BROADBAND PRICING IN KENTUCKY

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    Ever since the first telegraph, a technology management challenge has existed to expand the availability of communication services farther into rural and unserved areas, while maintaining the affordability of those services to residential users. Over the years, that challenge has transformed from telegraph to broadband communications or high-speed Internet access. The challenge of affordable expansion of broadband services is seen all across the United States including the Commonwealth of Kentucky. This study examined the extent to which community and provider-related supply and demand factors among last mile residential fixed broadband service areas impact the nonpromotional advertised price of last mile broadband service throughout the 120 counties in the Commonwealth of Kentucky. The potential factors included population density, unemployment rate, provider count, broadband availability, middle mile, actual broadband speeds, technology deployed, provider type, maximum advertised download speeds, and maximum advertised upload speeds, with a goal to reveal if any have a correlation to the actual price of broadband seen by end users. In addition, this study attempted to create a model based on the significantly correlated factors. Utilizing Pearson correlation and multiple regression analysis, this study found five variables with a significant correlation to the dependent variable, price per megabit, including a slight negative correlation with the count of middle mile providers, slight positive correlation with the technology deployed, slight negative correlation with the provider type, strong negative v correlation with the download speed tier, and strong negative correlation with the upload speed tier. Finally, a model was created to predict the price per megabit of broadband with three variables, technology used, provider type, and a joint variable representing the download and upload speeds tiers
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