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The article deals with a real-time implementation of a decentralized sliding mode controller applied to a twin rotor multi-input multi-output system, a system with 2 degrees of freedom, strongly coupled and its dynamic resembles that of a helicopter. The work is motivated by the fact that in the literature several control techniques have been proposed for the twin rotor multi-input multi-output system control without being applied to the system, and the considered authors presented just the simulation results. To control the vertical and horizontal positions of the twin rotor multi-input multi-output system, the system is decoupled into two subsystems, vertical and horizontal, controlled by two independent sliding mode regulators calculated from the mathematical models of vertical and horizontal subsystems, respectively. From the results of real-time control of the twin rotor multi-input multi-output system in stabilization and tracking modes, and performing robustness and disturbance rejection tests, the effectiveness of the suggested control scheme was proven.

Habitat heterogeneity has been shown to promote co-existence of closely related species. Based on this concept, a field study was conducted on the niche partitioning of three territorial congeneric species of skimmers (Anisoptera: Libellulidae) in Northeast Algeria during the breeding season of 2011. According to their size, there is a descending hierarchy between Orthetrum nitidinerve Sélys, O. chrysostigma (Burmeister), and O. coerulescens anceps (Schneider). After being marked and surveyed, the two latter species had the same breeding behavior sequence. Knowing that they had almost the same size, such species could not co-occur in the same habitat according to the competitive exclusion principle. The spatial distribution of the three species was investigated at two different microhabitats, and it was found that these two species were actually isolated at this scale. O. chrysostigma and O. nitidinerve preferred open areas, while O. c. anceps occurred in highly vegetated waters. This study highlights the role of microhabitat in community structure as an important niche axis that maintains closely related species in the same habitat.

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The authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the real rolling mill data. Completely independent set of real rolling data were used to evaluate the capacity of the fitted ANN model to predict the unseen regions of data. As a result, test rolls obtained by the suggested hybrid model have shown high prediction quality comparatively to the usual empirical prediction models