An inter-comparison between a VIS/IR and a MW satellite-based methods for cloud detection and classification

This thesis is aimed to assess similarities and mismatches between the outputs from two independent methods for the cloud cover quantification and classification based on quite different physical basis. One of them is the SAFNWC software package designed to process radiance data acquired by the SEVIRI sensor in the VIS/IR. The other is the MWCC algorithm, which uses the brightness temperatures acquired by the AMSU-B and MHS sensors in their channels centered in the MW water vapour absorption band. At a first stage their cloud detection capability has been tested, by comparing the Cloud Masks they produced. These showed a good agreement between two methods, although some critical situations stand out. The MWCC, in effect, fails to reveal clouds which according to SAFNWC are fractional, cirrus, very low and high opaque clouds. In the second stage of the inter-comparison the pixels classified as cloudy according to both softwares have been. The overall observed tendency of the MWCC method, is an overestimation of the lower cloud classes. Viceversa, the more the cloud top height grows up, the more the MWCC not reveal a certain cloud portion, rather detected by means of the SAFNWC tool. This is what also emerges from a series of tests carried out by using the cloud top height information in order to evaluate the height ranges in which each MWCC category is defined. Therefore, although the involved methods intend to provide the same kind of information, in reality they return quite different details on the same atmospheric column. The SAFNWC retrieval being very sensitive to the top temperature of a cloud, brings the actual level reached by this. The MWCC, by exploiting the capability of the microwaves, is able to give an information about the levels that are located more deeply within the atmospheric column.

TuCSoN on Cloud: Revisione dell'architettura

In questa tesi si revisiona l'architettura di TuCSoN on Cloud. Sono trattati i problemi riguardanti la gestione dei nodi TuCSoN su un cloud simulato su Cloudify; ovvero come sono memorizzati i vari tuple centre per ogni utente. É inoltre trattato il problema della concorrenza e della sicurezza, ovvero di come é gestita la password dell'utente.

Radiologia distribuita: Cloud e Post Processing 3D

L’effetto dell’informatica e dell’automazione sulle procedure medico sanitarie si sta manifestando in maniera sempre più ampia, portando notevoli vantaggi per la salute e il benessere di tutti i pazienti e al tempo stesso ponendo sfide sempre più complesse alle istituzioni sanitarie e ai produttori di dispositivi medico-sanitari. Al di là dei meriti del singolo prodotto o tecnologia, esiste un fattore strategico che dovrebbe essere sempre considerato nel momento di progettare un software o un dispositivo da utilizzare in ambito sanitario (da parte dei produttori) o nel momento di pianificare l’acquisto di sistemi medicali o diagnostici complessi (da parte delle istituzioni sanitarie): l’aspetto dell’Integrazione, ovvero la capacità del sistema di inserirsi in maniera semplice, efficace e poco costosa in un Workflow (flusso di lavoro) completamente integrato. Nel primo capitolo di questo elaborato finale è stato fatto un quadro generale sull’organizzazione del flusso di lavoro in radiologia e sono stati trattati i vari standard di comunicazione e scambio dati in ambito clinico, in primis DICOM, HL7 e IHE. L’oggetto del secondo capitolo è l’organizzazione e gli obbiettivi del Dipartimento di Radiologia attuati dal Gruppo Villa Maria (GVM) e il confronto di questi ultimi con il contenuto del documento: ‘Linee guida per l’assicurazione di qualita` in teleradiologia ‘che è stata redatta dal Istituto Superiore di Sanita` destinata ad apportare, non solo ai medici radiologi ed ai TSRM ma anche agli altri professionisti della sanità coinvolti, gli elementi di informazione e di metodo per l’organizzazione della teleradiologia nel rispetto delle esigenze della deontologia medica, della sicurezza del paziente, compreso il consenso, anche per quanto riguarda la radioprotezione, la privacy e la qualità. Nel terzo capitolo sono elencati gli strumenti con cui il Dipartimento di radiologia intende perseguire i suoi obbiettivi. Il quarto capitolo tratta la mia esperienza presso una clinica esterna al GVM, in particolare la clinica Santo Stefano, di Porto Potenza Picena, dove sono stati fatti dei test volti a valutare i tempi di caricamento di esami di TAC e RMN sul cloud di GVM.

Coordination nel Cloud: Elasticità in Respect

L'elasticità è un concetto fondamentale nell'ambito del cloud computing, ma propone problemi di coordinazione che, se non compresi nella loro natura, rischiano di renderla inefficiente. Tramite il concetto di “elasticità consapevole della coordinazione” (coordination-aware elasticity), in questa tesi si discute come si possa espandere il linguaggio per l’elasticità cloud SYBL in modo che possa eseguire alcune funzioni elastiche tramite il linguaggio di coordinazione ReSpecT.

Surface cloud radiative forcing from broadband radiation measurements on the Antarctic plateau

Surface based measurements systems play a key role in defining the ground truth for climate modeling and satellite product validation. The Italian-French station of Concordia is operative year round since 2005 at Dome C (75°S, 123°E, 3230 m) on the East Antarctic Plateau. A Baseline Surface Radiation Network (BSRN) site was deployed and became operational since January 2006 to measure downwelling components of the radiation budget, and successively was expanded in April 2007 to measure upwelling radiation. Hence, almost a decade of measurement is now available and suitable to define a statistically significant climatology for the radiation budget of Concordia including eventual trends, by specifically assessing the effects of clouds and water vapor on SW and LW net radiation. A well known and robust clear sky-id algorithm (Long and Ackerman, 2000) has been operationally applied on downwelling SW components to identify cloud free events and to fit a parametric equation to determine clear-sky reference along the Antarctic daylight periods (September to April). A new model for surface broadband albedo has been developed in order to better describe the features the area. Then, a novel clear-sky LW parametrization, based on a-priori assumption about inversion layer structure, combined with daily and annual oscillations of the surface temperature, have been adopted and validated. The longwave based method is successively exploited to extend cloud radiative forcing studies to nighttime period (winter). Results indicated inter-annual and intra-annual warming behaviour, i.e. 13.70 W/m2 on the average, specifically approaching neutral effect in summer, when SW CRF compensates LW CRF, and warming along the rest of the year due prevalentely to CRF induced on the LW component.

Integration of Internet of Things and Cloud computing. A case study on vital signs monitoring.

Il progresso scientifico e le innovazioni tecnologiche nei campi dell'elettronica, informatica e telecomunicazioni, stanno aprendo la strada a nuove visioni e concetti. L'obiettivo della tesi è quello d'introdurre il modello del Cloud computing per rendere possibile l'attuale visione di Internet of Thing. Nel primo capitolo si introduce Ubiquitous computing come un nuovo modo di vedere i computer, cercando di fare chiarezza sulla sua definizione, la sua nascita e fornendo un breve quadro storico. Nel secondo capitolo viene presentata la visione di Internet of Thing (Internet delle “cose”) che si avvale di concetti e di problematiche in parte già considerate con Ubiquitous computing. Internet of Thing è una visione in cui la rete Internet viene estesa agli oggetti di tutti i giorni. Tracciare la posizione degli oggetti, monitorare pazienti da remoto, rilevare dati ambientali sono solo alcuni esempi. Per realizzare questo tipo di applicazioni le tecnologie wireless sono da considerare necessarie, sebbene questa visione non assuma nessuna specifica tecnologia di comunicazione. Inoltre, anche schede di sviluppo possono agevolare la prototipazione di tali applicazioni. Nel terzo capitolo si presenta Cloud computing come modello di business per utilizzare su richiesta risorse computazionali. Nel capitolo, vengono inizialmente descritte le caratteristiche principali e i vari tipi di modelli di servizio, poi viene argomentato il ruolo che i servizi di Cloud hanno per Internet of Thing. Questo modello permette di accelerare lo sviluppo e la distribuzione di applicazioni di Internet of Thing, mettendo a disposizione capacità di storage e di calcolo per l'elaborazione distribuita dell'enorme quantità di dati prodotta da sensori e dispositivi vari. Infine, nell'ultimo capitolo viene considerato, come esempio pratico, l'integrazione di tecnologie di Cloud computing in una applicazione IoT. Il caso di studio riguarda il monitoraggio remoto dei parametri vitali, considerando Raspberry Pi e la piattaforma e-Health sviluppata da Cooking Hacks per lo sviluppo di un sistema embedded, e utilizzando PubNub come servizio di Cloud per distribuire i dati ottenuti dai sensori. Il caso di studio metterà in evidenza sia i vantaggi sia le eventuali problematiche che possono scaturire utilizzando servizi di Cloud in applicazioni IoT.

Elasticity in Cloud Computing: Tecnologia e applicazione aziendale presso Onit

Il Cloud Computing permette di utilizzare al meglio le risorse distribuite allo scopo di risolvere problemi di computazione su larga scala, e viene distribuito dai provider all'utente finale sotto forma di servizio. Presentati i diversi modelli di distribuzione dei servizi Cloud, si discutono le varie tipologie di servizi offerti. Efficaci meccanismi di elasticità e scalabilità hanno permesso al Cloud Computing di superare lo scoglio iniziale di utilizzo medio dei server al 10%. L'elasticità (rapid elasticity) è l’abilità di acquisire e rilasciare le risorse di un'infrastruttura Cloud su richiesta, l’abilità di un'applicazione di cambiare le sue dimensione durante il suo tempo di esecuzione; la scalabilità è un prerequisito per ottenere una buona elasticità per il sistema, ed è l'abilità che ha un layer di sostenere carichi di lavoro variabili continuando ad adempiere agli obblighi imposti dallo SLA allocando o disallocando risorse computazionali. Le diverse modalità di scaling e il loro utilizzo determinano la scalabilità e di conseguenza l'elasticità del sistema, e sfruttano la virtualizzazione per poter funzionare. Ciò ha portato notevoli benefici perchè aumenta l'utilizzo dei server, migliora l'efficienza del sistema, e dona flessibilità in caso di errori massimizzando il tempo di funzionamento. Sono stati introdotti due esempi di sistemi elastici basati ovviamente sulla virtualizzazione come Amazon Web Services e Microsoft Azure, che dominano il mercato del Cloud Computing e fanno uso dei più efficenti meccanismi d'elasticità. Il cuore di questo elaborato è l'analisi dell'ampliamento dell'adozione del Cloud Computing in azienda Onit Group srl. L'obiettivo è trattare i punti fondamentali per il Cloud Computing, analizzarli e immagazzinare tutte queste conoscenze per analizzare lo stato attuale del Cloud nell'azienda focalizzando l'attenzione sui vantaggi e sugli svantaggi che un sostanziale ampliamento dell'adozione ai sistemi Cloud poteva apportare.

Tecniche Cloud Avanzate per Adaptive Hadoop Load Balancing tramite Sahara

Ogni giorno vengono generati grandi moli di dati attraverso sorgenti diverse. Questi dati, chiamati Big Data, sono attualmente oggetto di forte interesse nel settore IT (Information Technology). I processi digitalizzati, le interazioni sui social media, i sensori ed i sistemi mobili, che utilizziamo quotidianamente, sono solo un piccolo sottoinsieme di tutte le fonti che contribuiscono alla produzione di questi dati. Per poter analizzare ed estrarre informazioni da questi grandi volumi di dati, tante sono le tecnologie che sono state sviluppate. Molte di queste sfruttano approcci distribuiti e paralleli. Una delle tecnologie che ha avuto maggior successo nel processamento dei Big Data, e Apache Hadoop. Il Cloud Computing, in particolare le soluzioni che seguono il modello IaaS (Infrastructure as a Service), forniscono un valido strumento all'approvvigionamento di risorse in maniera semplice e veloce. Per questo motivo, in questa proposta, viene utilizzato OpenStack come piattaforma IaaS. Grazie all'integrazione delle tecnologie OpenStack e Hadoop, attraverso Sahara, si riesce a sfruttare le potenzialita offerte da un ambiente cloud per migliorare le prestazioni dell'elaborazione distribuita e parallela. Lo scopo di questo lavoro e ottenere una miglior distribuzione delle risorse utilizzate nel sistema cloud con obiettivi di load balancing. Per raggiungere questi obiettivi, si sono rese necessarie modifiche sia al framework Hadoop che al progetto Sahara.

Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed

The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.

Assessing success of forest restoration efforts in degraded montane cloud forests in southern Mexico

Montane cloud forests are home to great biodiversity. However, non-sustainable anthropogenic activities have led to the loss of forest cover in southern Mexico. Increasing conservation, restoration and sustainable use of forest resources prevents the loss of cloud forests. In this study, success of forest restoration was evaluated in a degraded forest of Highlands Chiapas. The goal of this study was to assess the structure and composition of native tree species. We evaluated vegetation composition at three sites that had undergone enrichment plantings. Floristic composition and structure of the herbaceous, seedling, sapling, and overstory layers were measured. A total of sixty-six native tree species were recorded. Enrichment planting was found to have increased tree diversity. Moreover, 54% of the planted species were found in the understory, indicating that they were successfully recruiting. In conclusion, enrichment planting can aid in the conservation of forest cover in degraded areas.

In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

QUADRUPOLE LEVITATION OF PARTICLES IN A THERMODYNAMICALLY REALISTIC CLOUD ENVIRONMENT

Understanding clouds and their role in climate depends in part on our ability to understand how individual cloud particles respond to environmental conditions. Keeping this objective in mind, a quadrupole trap with thermodynamic control has been designed and constructed in order to create an environment conducive to studying clouds in the laboratory. The quadrupole trap allows a single cloud particle to be suspended for long times. The temperature and water vapor saturation ratio near the trapped particle is controlled by the flow of saturated air through a tube with a discontinuous wall temperature. The design has the unique aspect that the quadrupole electrodes are submerged in heat transfer fluid, completely isolated from the cylindrical levitation volume. This fluid is used in the thermodynamic system to cool the chamber to realistic cloud temperatures, and a heated section of the tube provides for the temperature discontinuity. Thus far, charged water droplets, ranging from about 30-70 microns in diameter have been levitated. In addition, the thermodynamic system has been shown to create the necessary thermal conditions that will create supersaturated conditions in subsequent experiments. These advances will help lead to the next generation of ice nucleation experiments, moving from hemispherical droplets on a substrate to a spherical droplet that is not in contact with any surface.

A dose-controlled system for air-liquid interface cell exposure and application to zinc oxide nanoparticles

BACKGROUND: Engineered nanoparticles are becoming increasingly ubiquitous and their toxicological effects on human health, as well as on the ecosystem, have become a concern. Since initial contact with nanoparticles occurs at the epithelium in the lungs (or skin, or eyes), in vitro cell studies with nanoparticles require dose-controlled systems for delivery of nanoparticles to epithelial cells cultured at the air-liquid interface. RESULTS: A novel air-liquid interface cell exposure system (ALICE) for nanoparticles in liquids is presented and validated. The ALICE generates a dense cloud of droplets with a vibrating membrane nebulizer and utilizes combined cloud settling and single particle sedimentation for fast (~10 min; entire exposure), repeatable (<12%), low-stress and efficient delivery of nanoparticles, or dissolved substances, to cells cultured at the air-liquid interface. Validation with various types of nanoparticles (Au, ZnO and carbon black nanoparticles) and solutes (such as NaCl) showed that the ALICE provided spatially uniform deposition (<1.6% variability) and had no adverse effect on the viability of a widely used alveolar human epithelial-like cell line (A549). The cell deposited dose can be controlled with a quartz crystal microbalance (QCM) over a dynamic range of at least 0.02-200 mug/cm(2). The cell-specific deposition efficiency is currently limited to 0.072 (7.2% for two commercially available 6-er transwell plates), but a deposition efficiency of up to 0.57 (57%) is possible for better cell coverage of the exposure chamber. Dose-response measurements with ZnO nanoparticles (0.3-8.5 mug/cm(2)) showed significant differences in mRNA expression of pro-inflammatory (IL-8) and oxidative stress (HO-1) markers when comparing submerged and air-liquid interface exposures. Both exposure methods showed no cellular response below 1 mug/cm(2 )ZnO, which indicates that ZnO nanoparticles are not toxic at occupationally allowed exposure levels. CONCLUSION: The ALICE is a useful tool for dose-controlled nanoparticle (or solute) exposure of cells at the air-liquid interface. Significant differences between cellular response after ZnO nanoparticle exposure under submerged and air-liquid interface conditions suggest that pharmaceutical and toxicological studies with inhaled (nano-)particles should be performed under the more realistic air-liquid interface, rather than submerged cell conditions.

Improving Management of Distributed Services Using Correlations and Predictions in SLA-Driven Cloud Computing Systems

Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.