Books about Rantamaki from Amazon.com

A wildly outlandish glimpse of everday insanity. (Helmet not included) When the government refused to recognize “reality” as a handicap, humor columnist Rick Rantamaki set out to “properly document” his claim – in one of America’s major newspapers. Discover, as Atlanta has, the hilariously debilitating effect reality can have on the ingrained perceptions of an American son raised on a steady diet of public schools and Saturday morning cartoons. At last, an uncut, unaltered collection of Rick’s columns (including those deemed to ‘edgy’ for public consumption) reveals why sanity never had a chance. "A mindblowing ride on the short bus." – CHICAGO SUN-TIMES "Completly unrelated to particulate filtration!" – US NEWS & WORLD REPORT "Deplorable, simply deplorable. Send more." – BOSTON HERALD "... cease and desist!" – ATLANTA CHAMBER OF COMMERCE.
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This book is part of the Our Name in History series, a collection of fascinating facts and statistics, alongside short historical commentary, created to tell the story of previous generations who have shared this name. The information in this book is a compendium of research and data pulled from census records, military records, ships' logs, immigrant and port records, as well as other reputable sources. Topics include:

• Name Meaning and Origin
• Immigration Patterns and Census Detail
• Family Lifestyles
• Military Service History
• Comprehensive Source Guide, for future research

Plus, the "Discover Your Family" section provides tools and guidance on how you can get started learning more about your own family history.

About the Series
Nearly 300,000 titles are currently available in the Our Name in History series, compiled from Billions of records by the world's largest online resource of family history, Ancestry.com..
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This digital document is a journal article from Atmospheric Environment, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
In this paper, a multi-layer perceptron (MLP) model and the Finnish variant of the numerical weather prediction model HIRLAM (High Resolution Limited Area Model) were integrated and evaluated for the forecasting in time of urban pollutant concentrations. The forecasts of the combination of the MLP and HIRLAM models are compared with the corresponding forecasts of the MLP models that utilise meteorologically pre-processed input data. A novel input selection method based on the use of a multi-objective genetic algorithm (MOGA) is applied in conjunction with the sensitivity analysis to reduce the excessively large number of potential meteorological input variables; its use improves the performance of the MLP model. The computed air quality forecasts contain the sequential hourly time series of the concentrations of nitrogen dioxide (NO"2) and fine particulate matter (PM"2"."5) from May 2000 to April 2003; the corresponding concentrations have also been measured at two urban air quality stations in Helsinki. The results obtained with the MLP models that use HIRLAM forecasts show fairly good overall agreement for both pollutants. The model performance is substantially better, when the HIRLAM forecasts are used, compared with those obtained both using either HIRLAM analysis data or meteorological pre-processor, for both pollutants. The performance of the currently widely used statistical forecasting methods (such as those based on neural networks) could therefore be significantly improved by using the forecasts of NWP models, instead of the conventionally utilised directly measured or meteorological pre-processed input data. However, the performance of all operational models considered is relatively worse in the course of air pollution episodes. n episodes. .
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This digital document is a journal article from Atmospheric Environment, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
The main objective of this work is to evaluate the performance of two operational versions of the numerical weather prediction model HIRLAM (HIgh Resolution Limited Area Model) in severe wintertime air pollution conditions. The evaluation has been done by comparing the predicted temperature, wind speed and relative humidity with observational data during one specific episode in December 1995. Simulations were executed with versions 4.6.2 (operational 1999-2003) and 6.2.1 (operational since 2004) of the HIRLAM model. During 27-29 December 1995, an area of high pressure was formed over Southern Scandinavia and Finland, leading to the formation of an exceptionally strong ground-based temperature inversion. According to radiosonde measurements, the maximum strength of the inversion was 18^oC at Jokioinen. These conditions caused poor air quality for 2 days, especially in the Helsinki Metropolitan Area. The simulations with both model versions were able to predict the occurrence of the inversions, but the surface temperatures and wind speeds near the surface were generally overestimated, thus leading to underestimation of the strength of the inversion. However, the more recent model version performed better in predicting the ground-based inversions. The improved performance of the more recent model version is probably due to both the improved surface parameterisation and the better vertical resolution in the lowest atmospheric layers, compared with those of the older model version. .
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