Search results for " PREDICTION"
showing 10 items of 366 documents
An NTC zone compliant knock onset prediction model for spark ignition engines
2015
Abstract Pollutant emissions reduction and energy saving policies increased the production of Spark Ignition (SI) engines operated with gaseous fuels. Natural Gas (NG) and Liquefied Petroleum Gas (LPG), thanks to their low cost and low environmental impact represent the best alternative. Bi-fuel engines, which may run either with gasoline or with gas (NG or LPG), widely spread in many countries thanks to their versatility, high efficiency and low pollutant emissions: gas fueled vehicles, as example, are allowed to run in many limited traffic zones. In the last years, supercharged SI engines fueled with either gasoline or gaseous fuel, spread in the market. Thermodynamic simulations, widely …
Coupling CFD with a one-dimensional model to predict the performance of reverse electrodialysis stacks
2017
Abstract Different computer-based simulation models, able to predict the performance of Reverse ElectroDialysis (RED) systems, are currently used to investigate the potentials of alternative designs, to orient experimental activities and to design/optimize prototypes. The simulation approach described here combines a one-dimensional modelling of a RED stack with a fully three-dimensional finite volume modelling of the electrolyte channels, either planar or equipped with different spacers or profiled membranes. An advanced three-dimensional code was used to provide correlations for the friction coefficient (based on 3-D solutions of the continuity and Navier-Stokes equations) and the Sherwoo…
Real-time parameter estimation of Zika outbreaks using model averaging
2017
SUMMARYEarly prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single- and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this…
Evaluating the effects of forest tree species on rill detachment capacity in a semi-arid environment
2021
Abstract The beneficial effects of plant roots in decreasing soil detachment in forest ecosystems exposed to rill erosion are well known. However, these effects vary largely between different plant species. There has been lots of research into the relationship between root-soil systems and rill erodibility with a particular focus on grass species. Conversely, fewer studies are available for tree species, especially in forests of semi-arid or arid environments. Greater knowledge is therefore needed to identify the most effective tree species against rill erosion in these ecosystems, where water availability is the limiting factor for vegetation growth and afforestation is often the only solu…
Measuring Field Rill Erodibility by a Simplified Method
2015
Many process-oriented erosion prediction models reproduce rill erosion as affected by site-specific parameters, as for example, rill erodibility, and thus, their practical application requires the measurement of these parameters or their estimate. The aim of this paper was establishing a method for indirectly measuring field rill erodibility. A simple mathematical approach based on a known soil detachment equation and accounting for the rill erosion dynamic process is applied. Field measurements carried out for seven natural rainfall events occurring at the plots of the Sparacia experimental station, southern Italy, are used for indirectly measuring the rill erodibility of the investigated …
The Application of Different Model of Multi-Layer Perceptrons in the Estimation of Wind Speed
2012
Wind speed forecasting is essential for effective planning of wind energy exploitation projects. The ability to predict short-term wind speed is a prerequisite for all the operators of the wind energy sector. Consequently it is essential to identify an efficient method for forecasts. In this paper, the wind speed in the province of Trapani (Sicily) is modeled by artificial neural network. Several model of neural network were generated and compared through error measures. Simulation results show that the estimated values of wind speed are in good agreement with the values measured by anemometers..
Early prediction of reading trajectories of children with and without reading instruction in kindergarten : a comparison study of Estonia and Finland
2019
Background: The present study examined differences in the prediction of reading development and reading difficulties in Estonia (n = 348) and Finland (n = 344). These neighbouring countries share many similarities in terms of their language, orthography and educational system; however, they differ in the timing of the onset of reading instruction, which is kindergarten in Estonia and Grade 1 in Finland. Methods: Children's skills were assessed three times – fall and spring in Grade 1 and spring in Grade 2. Results: The results showed that school‐entry rapid automatised naming and reading fluency predicted the development of fluency in Grade 2, but reading fluency was a stronger predictor in…
Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation
2016
This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…
Evaluating the impact of friends in predicting user’s availability in online social networks
2017
In recent years, Online Social Networks (OSNs) have changed the way people connect and interact with each other. Indeed, most people have registered an account on some popular OSNs (such as Facebook, or Google+) which is used to access the system at different times of the days, depending on their life and habits. In this context, understanding how users connect to the OSNs is of paramount importance for both the protection of their privacy and the OSN’s provider (or third-party applications) that want to exploit this information. In this paper, we study the task of predicting the availability status (online/offline) of the OSNs’ users by exploiting the availability information of their frie…
Wear modelling in mild steel orthogonal cutting when using uncoated carbide tools
2007
Abstract Wear prediction in machining has been recently studied by FEM although the use of numerical methods for such applications is still a very challenging research issue. In fact, wear phenomenon involves many aspects related to process mechanics which require a very accurate modelling. In other words, only a very punctual code set-up can help the researchers in order to obtain consistent results in FE analysis. The high relative velocity between chip and tool requires effective material models as well as friction modelling at the interface. Moreover the prediction of temperature distribution is another critical task; in the paper some different procedures are discussed. Subsequently a …