Reader’s SciGest: 07/12/18

An Engineer at Durham has helped develop a computational method for simulating wind in order to improve accuracy of short-term wind-power forecasting in wind farms. Using a Random Forest learning method (a combination of predictive algorithms), with a combination of historical data and statistics, the group successfully trained a model to predict short-term wind power. The model performed significantly better than its predecessors, and can be used to improve the efficiency of daily operation. 

Elsewhere, researchers from Durham investigated behaviour in the workplace and how it changes when different ‘Situation Contingencies’ (personality traits, specifically conscientiousness and neuroticism) are present in individuals. The term comes from Fiedler’s Contingency Theory of Leadership, which talks about the link between the leadership differences between those with more human-oriented or task-oriented dominant traits. The study observed  124 managers before, during, and after performing a range of different tasks over the course of 2 years, with their performance rated. It found that managers were more highly rated when 3 of the 6 situation contingencies were present, providing the first evidence of the predictive validity for situation contingencies.

Photograph: Jeff Kubina via Flickr Creative Commons

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