Available bandwidth estimation in smart VPN bonding technique based on a NARX neural network

Today many applications require a high Quality of Service (QoS) to the network, especially for real time applications like VoIP services, video/audio conferences, video surveillance, high definition video transmission, etc. Besides, there are many application scenarios for which it is essential to guarantee high QoS in high speed mobility context using an Internet Mobile access. However, internet mobile networks are not designed to support the real-time data traffic due to many factors such as resource sharing, traffic congestion, radio link, coverage, etc., which affect the Quality of Experience (QoE). In order to improve the QoS in mobility scenarios, the authors propose a new technique named "Smart VPN Bonding" which is based on aggregation of two or more internet mobile accesses and is able to provide a higher end-to-end available bandwidth due to an adaptive load balancing algorithm. In this paper, in order to dynamically establish the correct load balancing weights of the smart VPN bonder, a neural network approach to predict the main Key Performance Indicators (KPIs) values in a determinate geographical point is proposed

New Method for Estimating Fractal Dimension in 3D Space and Its Application to Complex Surfaces

The concept of “surface modeling” generally describes the process of representing a physical or artificial surface by a geometric model, namely a mathematical expression. Among the existing techniques applied for the characterization of a surface, terrain modeling relates to the representation of the natural surface of the Earth. Cartographic terrain or relief models as three-dimensional representations of a part of the Earth's surface convey an immediate and direct impression of a landscape and are much easier to understand than two-dimensional models. This paper addresses a major problem in complex surface modeling and evaluation consisting in the characterization of their topography and comparison among different textures, which can be relevant in different areas of research. A new algorithm is presented that allows calculating the fractal dimension of images of complex surfaces. The method is used to characterize different surfaces and compare their characteristics. The proposed new mathematical method computes the fractal dimension of the 3D space with the average space component of Hurst exponent H, while the estimated fractal dimension is used to evaluate, compare and characterize complex surfaces that are relevant in different areas of research. Various surfaces with both methods were analyzed and the results were compared. The study confirms that with known coordinates of a surface, it is possible to describe its complex structure. The estimated fractal dimension is proved to be an ideal tool for measuring the complexity of the various surfaces considered

New method for estimating fractal dimension in 3d space and its application to complex surfaces

The concept of “surface modeling” generally describes the process of representing a physical or artificial surface by a geometric model, namely a mathematical expression. Among the existing techniques applied for the characterization of a surface, terrain modeling relates to the representation of the natural surface of the Earth. Cartographic terrain or relief models as threedimensional representations of a part of the Earth's surface convey an immediate and direct impression of a landscape and are much easier to understand than two-dimensional models. This paper addresses a major problem in complex surface modeling and evaluation consisting in the characterization of their topography and comparison among different textures, which can be relevant in different areas of research. A new algorithm is presented that allows calculating the fractal dimension of images of complex surfaces. The method is used to characterize different surfaces and compare their characteristics. The proposed new mathematical method computes the fractal dimension of the 3D space with the average space component of Hurst exponent H, while the estimated fractal dimension is used to evaluate, compare and characterize complex surfaces that are relevant in different areas of research. Various surfaces with both methods were analyzed and the results were compared. The study confirms that with known coordinates of a surface, it is possible to describe its complex structure. The estimated fractal dimension is proved to be an ideal tool for measuring the complexity of the various surfaces considered

Closed Cycle Drying Process to Retrain Industrial Sludge into Construction Products

The article describes a new bio-inspired method for the Advanced Treatment of Industrial Sludge with a Closed Cycle Drying Process. This process represents an innovative way of treating sludge and other shovelable residues deriving from sludge treatment with centrifuges and other industrial processes taking place in large installations, such as refineries, steel mills, chemical plants, glass processing installations, cosmetics manufacturing facilities, pharmaceutical plants. The process is under development within the research project TAFIPACC funded by Horizon 2020. In particular, the process allows retraining Industrial Sludge into construction materials using the new Closed Cycle Drying Process. The study deals with sludge produced by an industrial treatment plant/industrial discharges and civil waste water in the industrial area of Priolo Gargallo (SR) Esso-Erg-Enichem petrochemical plants and by the municipalities of Priolo Gargallo, and Melilli. The plants produce about 30 cubic meters of sludge per day, disposed of 50% in underground dumps and for the other 50% in hazardous and non hazardous waste recovery plants. The difficulty in the treatment is mainly due to the nature of these muds, as pasty and difficult to mix with additives (cement, limestone, H2O, granulometric mix). The presence of bad odours derives from light and heavy hydrocarbons, aromatics, and organic solvents (benzene, toluene, styrene, xylene, etc), causing some problems to operators and inhabitants living in the areas surrounding the plants

closed cycle drying process to retrain industrial sludge into construction products

The article describes a new bio-inspired method for the Advanced Treatment of Industrial Sludge with a Closed Cycle Drying Process. This process represents an innovative way of treating sludge and other shovelable residues deriving from sludge treatment with centrifuges and other industrial processes taking place in large installations, such as refineries, steel mills, chemical plants, glass processing installations, cosmetics manufacturing facilities, pharmaceutical plants. The process is under development within the research project TAFIPACC funded by Horizon 2020. In particular, the process allows retraining Industrial Sludge into construction materials using the new Closed Cycle Drying Process. The study deals with sludge produced by an industrial treatment plant/industrial discharges and civil waste water in the industrial area of Priolo Gargallo (SR) Esso-Erg-Enichem petrochemical plants and by the municipalities of Priolo Gargallo, and Melilli. The plants produce about 30 cubic meters of sludge per day, disposed of 50% in underground dumps and for the other 50% in hazardous and non hazardous waste recovery plants. The difficulty in the treatment is mainly due to the nature of these muds, as pasty and difficult to mix with additives (cement, limestone, H2O, granulometric mix). The presence of bad odours derives from light and heavy hydrocarbons, aromatics, and organic solvents (benzene, toluene, styrene, xylene, etc), causing some problems to operators and inhabitants living in the areas surrounding the plants

A Multithread Nested Neural Network Architecture to Model Surface Plasmon Polaritons Propagation

Surface Plasmon Polaritons are collective oscillations of electrons occurring at the interface between a metal and a dielectric. The propagation phenomena in plasmonic nanostructures is not fully understood and the interdependence between propagation and metal thickness requires further investigation. We propose an ad-hoc neural network topology assisting the study of the said propagation when several parameters, such as wavelengths, propagation length and metal thickness are considered. This approach is novel and can be considered a first attempt at fully automating such a numerical computation. For the proposed neural network topology, an advanced training procedure has been devised in order to shun the possibility of accumulating errors. The provided results can be useful, e.g., to improve the efficiency of photocells, for photon harvesting, and for improving the accuracy of models for solid state devices

A Multithread Nested Neural Network Architecture to Model Surface Plasmon Polaritons Propagation

Surface Plasmon Polaritons are collective oscillations of electrons occurring at the interface between a metal and a dielectric. The propagation phenomena in plasmonic nanostructures is not fully understood and the interdependence between propagation and metal thickness requires further investigation. We propose an ad-hoc neural network topology assisting the study of the said propagation when several parameters, such as wavelengths, propagation length and metal thickness are considered. This approach is novel and can be considered a first attempt at fully automating such a numerical computation. For the proposed neural network topology, an advanced training procedure has been devised in order to shun the possibility of accumulating errors. The provided results can be useful, e.g., to improve the efficiency of photocells, for photon harvesting, and for improving the accuracy of models for solid state devices