Tesi di Dottorato
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Item Global Optimization and Fractal Curves(Università della Calabria, 2022-07-13) Nasso, Maria Chiara; Crupi, Felice; Sergeev, YaroslavIl presente lavoro di tesi è principalmente dedicato all'ottimizzazione globale e in particolare a metodi numerici di ottimizzazione globale basati su frattali. Viene affrontato lo studio teorico di alcune curve frattali, vengono proposti nuovi algoritmi che si basano su approcci frattali per ridurre la dimensione del problema e vengono introdotti nuovi metodi di ottimizzazione globale basati sulla tecnica del Local Tuning. Ciascuno dei nuovi metodi proposti è stato implementato e studiato dal punto di vista teorico. Inoltre, gli esperimenti numerici, condotti su diverse centinaia di funzioni test, tratte dalla letteratura e generate in maniera random confermano i vantaggi degli algoritmi presentati.Item Arm growth and regeneration in octopus (Octopus vulgaris and Eledone moschata)(Università della Calabria, 2020-02-12) Baldascino, Elena; Cerra, Maria Carmela; Fiorito, GrazianoHere I evaluated the timing and rate of arm regeneration in octopus, a cephalopod mollusc, and contributed to the understanding of the molecular machinery involved in arm growth and regeneration in two octopus’ species: Octopus vulgaris and Eledone moschata. This work stands and revisit in part the first experimental study on arm regeneration in cephalopod molluscs, including the two species carried out by M. Lange (1920). An arm of octopus may fully regenerate and regrowth in few months after amputation. Lange recognized three stages: wound healing, tissue degeneration and tissue renewal. I applied the 3Rs principle to this study utilizing samples and data from a previous study, thus limiting the number or live animals humanely killed for the purpose of this PhD project. During the analysis of data, I found the same three stages in O. vulgaris arm regeneration to occur. I was not able to observe similar series of events in E. moschata, probably due to limited time and conditions of the animals. I found that O. vulgaris increased significantly body weight in 21 weeks. The growth appeared to be affected by repeated anesthesia, thus encouraging further studies on the physiological responses to stress in octopus. Data I analyzed confirm the view that O. vulgaris is characterized by rapid non-asymptotic growth, with high individual variability. Octopuses elongate their arms continuing to grow over time with no significant difference in the relative rate of elongation between anterior and posterior arms. The arms that underwent to regeneration, appear to have a faster growth when compared with the contralateral arms (but repeated anesthesia influenced the rate of growth of regenerating arms). Data analyzed extent the study of Lange, by providing morphometric information on the relative growth rate of the arms (regenerating vs contralateral), for the first time. A significant change in the relative expression profile of the tip vs the proximal part of the arm in O. vulgaris was observed using different approaches, confirming and extending the view that the tip the arm represents an exceptional biological system where continuous growth is achieved through massive cellular differentiation and interesting molecular events. I identified 39 genes in O. vulgaris and seven in E. moschata and studied their involvement in arm growth and/or regeneration events in octopus arms. These studies are novel.Item New on-line model for shoreline evolution at beaches composed of not cohesive grains of any size(Università della Calabria, 2020-02-12) Francone, Antonio; Furgiuele, Franco; Tomasicchio, Giuseppe Roberto; Frega, FerdinandoOver recent decades, efforts have been made to find robust methods for predicting shoreline evolution near to the coastal structures. This requires a rigorous understanding of the key coastal processes that drive sediment transport, and how they are impacted by the presence of structures. Once this understanding is reached, a method for predicting morphological shoreline evolution is required. In this context, numerical modelling plays an important role. A new one-line model for shoreline evolution at beaches composed of not cohesive grains of any size is proposed: the General Shoreline beach (GSb). GSb model is based on the one-line theory, for which it is assumed that the equilibrium beach profile remains unchanged (Dean, 1990), thereby allowing beach change to be described uniquely in terms of the shoreline position. The longshore sediment transport rate is estimated by means of a general formula/procedure (Tomasicchio et al., 1994; Lamberti and Tomasicchio, 1997; Tomasicchio et al., 2013; Tomasicchio et al., 2015) combining an energy flux approach with an empirical/statistical relationship between the waveinduced forcing and the number of moving units. The uniqueness of the proposed new one-line model consists in the possibility to simulate beach change, including the effects of coastal structures (i.e. groynes, detached breakwaters), at a mound composed of not cohesive grains of any size, from sand to rock units. Despite other existing models, the GSb model presents a calibration factor, KGSb solely and it has been calibrated and verified against field and laboratory data on sandy and mixed beach (sand and gravel) referring to simple groyne and detached breakwater (Ming and Chiew, 2000; Hamilton et al., 2001; Martin-Grandes et al., 2009; Medellin et al., 2018;). Optimal values of KGSb, valid for different types of not cohesive grains and coastal structures, have been reported. It is showed that the GSb model can be considered a reliable engineering tool to conduct morphodynamics studies. A demo version of the GSb model, for Mac and Windows systems, has been released for the scientific community and is available at www.scacr.eu.Item Methodologies and Applications for Big Data Analytics(Università della Calabria, 2020-05-02) Cassavia, Nunziato; Crupi, Felice; Flesca, Sergio; Masciari, Elio;Due to the emerging Big Data paradigm, driven by the increase availability of users generated data, traditional data management techniques are inadequate in many real life scenarios. The availability of huge amounts of data pertaining to user social interactions calls for advanced analysis strategies in order to extract meaningful information. Furthermore, heterogeneity and high speed of user generated data require suitable data storage and management and a huge amount of computing power. This dissertation presents a Big Data framework able to enhances user quest for information by exploiting previous knowledge about their social environment. Moreover an introduction to Big Data and NoSQL systems is provided and two basic architecture for Big Data analysis are presented. The framework that enhances user quest, leverages the extent of influence that the users are potentially subject to and the influence they may exert on other users. User influence spread, across the network, is dynamically computed as well to improve user search strategy by providing specific suggestions, represented as tailored faceted features. The approach is tested in an important application scenario such as tourist recommendation where several experiment have been performed to assess system scalability and data read/write efficiency. The study of this system and of advanced analysis on Big Data has shown the need for a huge computing power. To this end an high performance computing system named CoremunitiTM is presented. This system represents a P2P solution for solving complex works by using the idling computational resources of users connected to this network. Users help each other by asking the network computational resources when they face high computing demanding tasks. Differently from many proposals available for volunteer computing, users providing their resources are rewarded with tangible credits. This approach is tested in an interesting scenario as 3D rendering where its efficiency has been compared with "traditional" commercial solutions like cloud platforms and render farms showing shorter task completion times at low cost.