Prediction of PM10 concentrations using Fuzzy c-Means and ANN

Salamanca has been considered among the most polluted cities in Mexico. The vehicular park, the industry and the emissions produced by agriculture, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Particulate Matter less than 10 μg/m3 in diameter (PM10). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables (wind speed, wind direction, temperature and relative humidity) and air pollutant concentrations of PM10. Before the prediction, Fuzzy c-Means clustering algorithm have been implemented in order to find relationship among pollutant and meteorological variables. These relationship help us to get additional information that will be used for predicting. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of PM10 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results shown that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours

Analysis and 2D Simulation of a Hexapod Robot Leg for Remote Exploration

A walking machine is a wheeled rover alternative, well suited for work in an unstructured environment and specially in abrupt terrain. They have some drawback like speed and power consumption, but they can achieve complex movements and protrude very little the environment they are working on. The locomotion system is determined by the terrain conditions and, in our case, this legged design has been chosen based in a working area like Rio Tinto in the South of Spain, which is a river area with abrupt terrain. A walking robot with so many degrees of freedom can be a challenge when dealing with the analysis and simulations of the legs. This paper shows how to deal with the kinematical analysis of the equations of a hexapod robot based on a design developed by the Center of Astrobiology INTA-CSIC following the classical formulation of equations

1D and 2D neutral particle patterning by dielectrophoretic forces on z-cut Fe:LiNbO3 crystals

1D and 2D patterning of uncharged micro- and nanoparticles via dielectrophoretic forces on photovoltaic z-cut Fe:LiNbO3 have been investigated for the first time. The technique has been successfully applied with dielectric micro-particles of CaCO3 (diameter d = 1-3 μm) and metal nanoparticles of Al (d = 70 nm). At difference with previous experiments in x- and y-cut, the obtained patterns locally reproduce the light distribution with high fidelity. A simple model is provided to analyse the trapping process. The results show the remarkably good capabilities of this geometry for high quality 2D light-induced dielectrophoretic patterning overcoming the important limitations presented by previous configurations.

Studies of Central American plants. by Paul C. Standley and Julian A. Steyermark.

v.22:no.4(1940)