Costificazione delle matrici per estrusione mediante approccio "feature-based cost".

In questo elaborato viene presentato un nuovo modello di costo per le matrici per estrusione basato su un approccio feature-based. Nel particolare si è cercato di definire il costo di questi prodotti sulla base delle loro caratteristiche geometriche e tecnologiche.

Design the support for granting required sla in public cloud environments based on cloud foundry

Through the use of Cloud Foundry "stack" concept, a new isolation is provided to the application running on the PaaS. A new deployment feature that can easily scale on distributed system, both public and private clouds.

Antarctic cloud spectral emission from ground-based measurements, a focus on far infrared signatures

The present work belongs to the PRANA project, the first extensive field campaign of observation of atmospheric emission spectra covering the Far InfraRed spectral region, for more than two years. The principal deployed instrument is REFIR-PAD, a Fourier transform spectrometer used by us to study Antarctic cloud properties. A dataset covering the whole 2013 has been analyzed and, firstly, a selection of good quality spectra is performed, using, as thresholds, radiance values in few chosen spectral regions. These spectra are described in a synthetic way averaging radiances in selected intervals, converting them into BTs and finally considering the differences between each pair of them. A supervised feature selection algorithm is implemented with the purpose to select the features really informative about the presence, the phase and the type of cloud. Hence, training and test sets are collected, by means of Lidar quick-looks. The supervised classification step of the overall monthly datasets is performed using a SVM. On the base of this classification and with the help of Lidar observations, 29 non-precipitating ice cloud case studies are selected. A single spectrum, or at most an average over two or three spectra, is processed by means of the retrieval algorithm RT-RET, exploiting some main IR window channels, in order to extract cloud properties. Retrieved effective radii and optical depths are analyzed, to compare them with literature studies and to evaluate possible seasonal trends. Finally, retrieval output atmospheric profiles are used as inputs for simulations, assuming two different crystal habits, with the aim to examine our ability to reproduce radiances in the FIR. Substantial mis-estimations are found for FIR micro-windows: a high variability is observed in the spectral pattern of simulation deviations from measured spectra and an effort to link these deviations to cloud parameters has been performed.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Novel materials for direct X-ray detectors based on semiconducting organic polymers

Conventional inorganic materials for x-ray radiation sensors suffer from several drawbacks, including their inability to cover large curved areas, me- chanical sti ffness, lack of tissue-equivalence and toxicity. Semiconducting organic polymers represent an alternative and have been employed as di- rect photoconversion material in organic diodes. In contrast to inorganic detector materials, polymers allow low-cost and large area fabrication by sol- vent based methods. In addition their processing is compliant with fexible low-temperature substrates. Flexible and large-area detectors are needed for dosimetry in medical radiotherapy and security applications. The objective of my thesis is to achieve optimized organic polymer diodes for fexible, di- rect x-ray detectors. To this end polymer diodes based on two different semi- conducting polymers, polyvinylcarbazole (PVK) and poly(9,9-dioctyluorene) (PFO) have been fabricated. The diodes show state-of-the-art rectifying be- haviour and hole transport mobilities comparable to reference materials. In order to improve the X-ray stopping power, high-Z nanoparticle Bi2O3 or WO3 where added to realize a polymer-nanoparticle composite with opti- mized properities. X-ray detector characterization resulted in sensitivties of up to 14 uC/Gy/cm2 for PVK when diodes were operated in reverse. Addition of nanoparticles could further improve the performance and a maximum sensitivy of 19 uC/Gy/cm2 was obtained for the PFO diodes. Compared to the pure PFO diode this corresponds to a five-fold increase and thus highlights the potentiality of nanoparticles for polymer detector design. In- terestingly the pure polymer diodes showed an order of magnitude increase in sensitivity when operated in forward regime. The increase was attributed to a different detection mechanism based on the modulation of the diodes conductivity.