Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

n-Alkan-2-ones in peat-forming plants from the Roñanzas ombrotrophic bog (Asturias, northern Spain)

We determined the distribution of lipids (n-alkanes and n-alkan-2-ones) in present-day peat-formingplants in the RoñanzasBog in northernSpain. Consistent with the observation of others, most Sphagnum (moss) species alkanes maximized at C23, whereas the other plants maximized at higher molecular weight (C27 to C31). We show for the first time that plants other than seagrass and Sphagnum moss contain n-alkan-2-ones. Almost all the species analysed showed an n-alkan-2-one distribution between C21 and C31 with an odd/even predominance, maximizing at C27 or C29, except ferns, which maximized at lower molecular weight (C21–C23). We also observed that microbial degradation can be a major contributor to the n-alkan-2-one distribution in sediments as opposed to a direct input of ketones from plants