The McGraw-Hill 36-hour course : online marketing / by 520073 Thomas, Lorrie

McGraw-Hill 36-hour course, Operations management / by 235000 Brennan, Linda L.

Office hour : fresh corporate environments from around the globe / by Shaoqiang, Wang 494619

Woman's Hour Book of Humour : The Century's Funniest Female Writing / by Feldman, Sally, author 559363

The Long, Long Day : Homage to the Le Mans 24 Hours / by Nissan Motor 546901

iPhone and iPad app 24-hour trainer / by Mishra, Abhishek, Backlin, Gene

Sams teach yourself C++ in one hour a day / by Rao, Siddhartha.

Social media marketing [electronic resource] : an hour a day / by Evans, Dave, 1956-

Reagan at Reykjavik : forty-eight hours that ended the Cold War / by 238191 Adelman, Kenneth L.

Extreme productivity : boost your results, reduce your hours / by Pozen, Robert C., author

Multivariate disaggregation of daily to hourly rainfall series [electronic resource] / by Lim, Tou Hin, 1988- 1988- author, Fadhilah Yusof, Fakulti Sains

Sams teach yourself Microsoft Project 98 in 24 hours / by Pyron, Tim

Sams teach yourself Microsoft Project 2000 in 24 hours / by 182454 Pyron, Tim

The McGraw-Hill 36-hour course Six Sigma / by 220223 Brue, Greg

Sams teach yourself Microsoft Access 2000 in 24 hours / by 175368 Eddy, Craig, Buchanan, Timothy

Sams teach yourself to create web pages in 24 hours/ by 460925 Snell, Ned

Visual C# 2005 in 24 hours : complete starter kit / by 321777 Foxall, James

The probability distribution of annual maximum hourly and daily rainfall in Kemaman by Aasha, Thiaharajan

“…The objectives of this study are: (i) to perform the probability distribution analysis using Log-Pearson Type III Distribution and Gumbel Distribution for annual maximum hourly and daily rainfall in Kemaman, (ii) to estimate the most appropriate probability distribution for annual maximum hourly and daily rainfall in Kemaman and (iii) to estimate the annual maximum hourly and daily rainfall intensity for selected return periods. …”
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Association between asthma and sleep hours in Brazilian adolescents: ERICA by Natalia Rocha do Amaral Estanislau, Erica Azevedo de Oliveira Costa Jordão, Gabriela de Azevedo Abreu, Katia Vergetti Bloch, Maria Cristina Caetano Kuschnir, Mara M.R. Felix, Fabio Chigres Kuschnir

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Regression model-based hourly aggregated electricity demand prediction by Radharani Panigrahi, Nita R. Patne, Sumanth Pemmada, Ashwini D. Manchalwar

“…The ability to predict ggregated electricity demand of n electrical grid on an hourly basis is crucial for energy and demand management. …”
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