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[en] The aim of this study was to find a model able to extract the net time per unit of net worked area from different agricultural field basic shapes (square, circle, rectangle and triangle) considering the following variables: field gross area, working speed, number of turnings (these depending on the effective working width), side length parallel and orthogonal to working direction, and working direction type. Being this a non-linear problem, an approach based on artificial neural networks is proposed. The model was trained using an artificial dataset calculated for the various shapes (internal test) and then tested on 47 different agricultural operations extracted by a real field dataset for the estimation of the net time (external test). The net time records obtained from both, the trained model and the external test, were correlated and the performance parameter r was extracted. Both regression coefficients (r), for the training and internal test, appear to be excellent being equal to 0.98 with respect to traditional linear approach (0.13). The variable “number of turnings” scored the highest impact, with a value equal to 44.34% for the net time estimation. Finally, the r correlation parameter for the external test resulted to be very high (0.80). This information is very valuable of the use of information management system for precision agriculture.
[en] The progressive microelectronics ULSI device shrinking towards improving the performances has driven the development of new materials and process technologies. A good example is given by oxynitride, an innovative material which is thought for the next generation of 0.25 μm MOS circuits. Oxynitrides have replaced thermal silicon oxides as gate insulator due to the properties of good masking against impurity diffusion, together with the excellent dielectric strength and the better resistance to dielectric breakdown. The strong request from microelectronics industries for a complete and accurate characterization of this new material and the technological processes concerned, has considerably stimulated the research, particularly in the field of analytical methodology. Secondary Ion Mass Spectrometry, linked since the beginning with microelectronics development, shows again to be the most reliable and suitable microanalytical technique to give answers to this topics. In this work we present some examples of methodologies applied to an accurate quantitative characterization of this new material, together with its impact on the production processes. We show how the complementary employing of several mass spectrometry techniques, such as magnetic sector SIMS, SNMS and ToF-SIMS, can give a more complete overview both to process issues and to methodological developements of the techniques themselves
[en] The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.
[en] Complete text of publication follows. For the purpose of understanding the response of the coupled thermosphere-ionosphere (T-I) system to magnetic activity, first-principles models of the T-I system, such as Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model, have been continuously improved and have undergone extensive validation against various types of observations. Recent comparison demonstrates that the CTIPe model can reasonably capture the neutral density variations for both the quiet and magnetically disturbed conditions obtained from the CHAMP observations. The study indicates that the energy budget in the T-I system described in the model is consistent with uncertainties in empirical or physics-based estimates, although quantification of the precise external forcing from the solar and geomagnetic sources still remains one of the major challenges towards accurate prediction and short-term forecast of neutral density, for satellite drag and other space weather applications. An effort has also been underway to coupling the magnetosphere and T-I models towards an improved understanding of the electrodynamic and mass coupling processes between the magnetosphere and T-I system. Modeling the response of the global ionospheric electric field to magnetic activity is one such example. The storm time electric fields can be reproduced in reasonable agreement with observations, by including into the models, the externally applied potentials by the prompt penetration process as well as the internally generated electric potentials by the disturbance dynamo process. The approach of self-consistent coupling allows study of the feedback of the T-I system to the magnetosphere, such as represented by the fly wheel effect. With an anticipation of more sophisticated measurements of the electromagnetic pointing vector from the upcoming SWARM mission, together with the ionospheric electric and magnetic fields, we will attempt to suggest some ideas how the mission could help the future modeling effort to address some outstanding issues such as the energy flow from the magnetosphere to T-I system and the response of the dynamics and energetics in the T-I system.
[en] Complete text of publication follows. Ground based photometric observations of OI 630.0 nm emission line have been carried out from Kolhapur station (Geog. Lat.16.8degN , Geo. Long 74.2degE) and GPS data processed by UNB Ionospheric Modeling Technique and RDRINEX software used to get both TEC and variation in TEC i.e d(TEC)/dT from Hyderabad (17.41degN, 78.55degE) and Bangalore (13.02degN, 77.57degE) station, India during the period of the largest geomagnetic storm of the solar cycle 23 which occurred on 20 November 2003, with minimum Dst index -472 nT occurring around mid-night hours. We observed that on 19 November 2003 which was geomagnetically quiet day, the airglow activity of OI 630 nm emission and d(TEC)/dT were subdued and it was decreasing monotonically. However, on the night of November 20, 2003 the enhancement is observed during geomagnetic storm due to the increased electron density at the altitude of the F region which is related to the downward transport of electrons from the plasmasphere to the F-region. Airglow intensity at OI 630.0 nm and d(TEC)/dt showed increase around midnight on November 21, 2003 but comparatively on a smaller scale. On this night the Dst index was about -100 nT. This implies that the effect of the geomagnetic storm persisted on that night also. These observations have been explained by the penetration of magnetospheric electric field to the low latitude region and the subsequent modulation of meridional wind during the magnetic disturbance at night.
[en] In this paper we describe the synthetic solar spectral irradiance (SSI) calculated from 2010 to 2015 using data from the Atmospheric Imaging Assembly (AIA) instrument, on board the Solar Dynamics Observatory spacecraft. We used the algorithms for solar disk image decomposition (SDID) and the spectral irradiance synthesis algorithm (SISA) that we had developed over several years. The SDID algorithm decomposes the images of the solar disk into areas occupied by nine types of chromospheric and 5 types of coronal physical structures. With this decomposition and a set of pre-computed angle-dependent spectra for each of the features, the SISA algorithm is used to calculate the SSI. We discuss the application of the basic SDID/SISA algorithm to a subset of the AIA images and the observed variation occurring in the 2010–2015 period of the relative areas of the solar disk covered by the various solar surface features. Our results consist of the SSI and total solar irradiance variations over the 2010–2015 period. The SSI results include soft X-ray, ultraviolet, visible, infrared, and far-infrared observations and can be used for studies of the solar radiative forcing of the Earth’s atmosphere. These SSI estimates were used to drive a thermosphere–ionosphere physical simulation model. Predictions of neutral mass density at low Earth orbit altitudes in the thermosphere and peak plasma densities at mid-latitudes are in reasonable agreement with the observations. The correlation between the simulation results and the observations was consistently better when fluxes computed by SDID/SISA procedures were used.