Studio ed analisi di sistemi GIS e loro applicazioni

In questa tesi viene effettuato uno studio approfondito dei Sistemi Informativi Geografici. Prima di tuttto è stato descritto un generico GIS con tutte le sue componenti e le sue funzionalità. Dopo sono stati presi in considerazione tre GIS in particolare, due freeware (Google Earth e GRASS) ed uno commerciale (ARCGIS), e ne sono stati messi in evidenza vantaggi e limiti. Alla fine vengono mostrate alcune possibili applicazioni dei GIS, in particolare al settore radaristico (Knowledge Based Radar)

Some meteorological parameters affecting the image quality of the William Herschel telescope on La Palma

Understanding of the factors which limit the image quality of a ground based telescope is still an interesting challenge despite the effort devoted to the problem since the early days of optical astronomy. At the Roque de los Muchachos observatory, on the island of La Palma (Canary Islands) this problem has been studied as part of a programme aimed to improve the optical performance of the biggest instrument at the observatory, the anglo-dutch William Herschel Telescope. The programme comprises a range of studies to investigate the possible factors deteriorating the image quality at the telescope. This thesis forms part of the meteorological studies of this programme and it is based on the data collected by a meteorological station recently installed at the observatory. In particular, phenomena such as wind direction, wind speed, pointing direction of the telescope dome relative to the wind direction, air and soil temperatures, relative internal/external temperatures, barometric pressure and humidity have been investigated and the relationship between these and the image quality at the telescope has been analyzed. The image quality is found to be particularly sensitive to the wind direction and the internal differences in temperatures. The season of the year also seems to have an influence on the image quality. In the conclusions, suggested further avenues of investigation are given

A green supply chain network design framework for the processed food industry: Application to the orange juice agrofood cluster

Food production has put enormous strain on the environment. Supply chain network design provides a means to frame this issue in terms of strategic decision making. It has matured from a field that addressed only operational and economic concerns to one that comprehensively considers the broader environmental and social issues that face industrial organizations of today. Adding the term “green” to supply chain activities seeks to incorporate environmentally conscious thinking in all processes in the supply chain. The methodology is based on the use of Life Cycle Assessment, Multi-objective Optimization via Genetic Algorithms and Multiple-criteria Decision Making tools (TOPSIS type). The approach is illustrated and validated through the development and analysis of an Orange Juice Supply Chain case study modelled as a three echelon GrSC composed of the supplier, manufacturing and market levels that in turn are decomposed into more detailed subcomponents. Methodologically, the work has shown the development of the modelling and optimization GrSCM framework is useful in the context of eco-labelled agro food supply chain and feasible in particular for the orange juice cluster. The proposed framework can help decision makers handle the complexity that characterizes agro food supply chain design decision and that is brought on by the multi-objective nature of the problem as well as by the multiple stakeholders, thus preventing to make the decision in a segmented empirical manner. Experimentally, under the assumptions used in the case study, the work highlights that by focusing only on the “organic” eco-label to improve the agricultural aspect, low to no improvement on overall supply chain environmental performance is reached in relative terms. In contrast, the environmental criteria resulting from a full lifecycle approach is a better option for future public and private policies to reach more sustainable agro food supply chains

The peculiar velocities of satellites of external disk galaxies

We analyze the angular distribution and the orbital rotation directions of a sample of carefully-selected satellite galaxies extracted from the Sloan Digital Sky Survey (SDSS). We also study these statistics in an N-body simulation of cosmological structure formation set within the LCDM paradigm under various assumptions for the orientations of disk angular momenta. Assuming that the angular momenta of the disks are aligned with the angular momenta of the inner regions of their host dark matter halos, we find that the fraction of simulated satellite halos that exhibit prograde motion is 0.55-0.60, with larger satellites more likely to be prograde. In our observational sample, approximately 60% of the satellites exhibit prograde motion, a result that is broadly consistent with the simulated sample. Contrary to several recent studies, our observational sample of satellite galaxies show no evidence for being anisotropically distributed about their primary disks. Again, this result is broadly consistent with our simulated sample of satellites under the assumption that disk and halo angular momenta are aligned. However, the small size of our observational sample does not yet allow us to distinguish between various assumptions regarding the orientations of disks in their halos. Finally, we assessed the importance of contamination by interlopers on the measured prograde and retrograde statistics.Comment: 11 pages, 6 figures, submitted to Ap

Behavior patterns related to the agricultural practices in the production of Persian lime (Citrus latifolia tanaka) in the seasonal orchard

Production of the Persian lime (Citrus latifolia tanaka) has been the main objective of several studies related to the problem of low performance of yield and fruit quality in the orchard, attributed among different technological factors to the minimal application of Good Agricultural Practices (GAP) and to the cultural aspects of the producer. This paper contributes to the recognition of the behavior patterns of GAP for seasonal orchard (SO), to allow the Persian lime producers to make the right decisions assessing and improving the management of their orchards. To identify the behavior patterns in the Persian lime production process an expert system (ES) based on fuzzy logic proposed by Fernández et al. (2014) has been used, in which a set of inference rules based on the knowledge of experts in this field is encoded to explain the interrelationship of the agricultural practices and uncertainties in the production of Persian lime: Pruning, Soil nutrition, Pests Control, Planting density, Tree production, Wind, Rainfall. The ES simulates from agricultural practices and uncertainties, the Persian lime production system in three stages of fruit growth, which represent the fuzzy models of the ES: flowering, bud, and fruit. The manipulation of the agricultural practices in the ES allowed to model production scenarios for SO of Persian lime, and helped to identify behavior patterns in these practices with production yield and fruit quality. The results demonstrate that if prior to fertilization, the practice of “pruning” the tree is performed, orchard productivity increases. However, when the “pruning” (aesthetics or stressful) is performed less than 50 mm month−1 of rain, even in optimal conditions of application of nutrients and pest control, the production yield is similar. The modeling scenarios of the ES provide information regarding behavior patterns to the producer, and the interrelation of agricultural practices in uncertain environments of rain and wind in order to improve the decision-making process in Persian lime production

An expert system for predicting orchard yield and fruit quality and its impact on the Persian lime supply chain

In recent years academics and industrials have shown an interest in agricultural systems and their complex and non-linear nature, aiming to improve production yield in the agricultural field. Innovative strategies and methodological frameworks are thus required to assist farmers in decision making for an efficient and effective resource management. In particular, this research concerns the structural problem of the Persian lime supply chain in Mexico, which still leads to low production yield over short time periods with heterogeneous fruit quality and also to the emergence of excessive middleman businesses arising from a fragmentation between orchard and exporting companies that constitute the first two links in the associated supply chain. Based on the Persian lime production cycle, an Expert System (ES) using Fuzzy Logic involving an inference engine with IF—THEN type rules is presented in this paper. A Mamdani model codifies the decision criteria related to agricultural practices for growing Persian lime in non-irrigated orchards. The ES allows the farmer to boost production in orchards by modeling application scenarios for agricultural practices. A case study based on an exporting company׳s fruit supply is discussed, in which the ES proves to be a useful tool to aid the decision making involved in the application of agricultural practices in the orchard. Results show an increase in production yield and fruit quality in the orchard, as well as a better synchronization between orchard and exporting companies, with a significant impact on inventory levels of fresh fruit in the link Persian lime exporting company