3,041 research outputs found
Presentazione
No full textIntroduzione al Volume curato da Filomena Albano, Giuseppe Cassano, Paolo Corder e Giacomo Oberto
Replication vs erasure coding in data centric storage for wireless sensor networks
No full textIn-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability
La visita di Zanardelli, di Michele Tedesco, dipinto
No full textScheda scientifica del dipinto di Michele Tedesco, pittore lucano d'origine, esponente del panorama artistico napoletano, fiorentino ed europeo del secondo Ottocent
Hierarchical P2P Overlays for DVE: An Additively Weighted Voronoi Based Approach
No full text—This paper presents a support for the development
of Distributed Virtual Environments (DVEs) on P2P architectures.
A hierarchical overlay is defined by pairing each peer with a
weight which is proportional to its networking bandwidth. Peers
characterized by higher weights are assigned a greater workload,
in terms of connections with other peers and of number of
passive objects they manage, and can act as superpeers that offer
a set of services to peers characterized by lower bandwidth.
Additively Weighted Voronoi (AWV) Diagrams are exploited to
define a partition of the DVE that assigns to each peer a region
whose size is dependent on the peer’s weight. Superpeers are
modeled by sites of the tessellation that have absorbed at least
the Voronoi region of another site. A set of experimental results
shows that this approach can be a load balancing mechanism for
peer-to-peer networks, that does not impair usual properties of
Voronoi-based peer-to-peer network
A Model-Checking Static Analysis of Task-Based Energy Neutrality for Energy Harvesting IoT
No full textWe address the problem of energy neutrality in energy harvesting IoT devices by means of a model checking approach, aiming at analyzing the dynamics of the battery charge in energy-neutral IoT devices. Our approach allows to compute the best task schedule and to study the maximum utility when operating on other parameters such as the initial battery charge, the number and structure of the available tasks, the size of the photo-voltaic panel that recharges the device, the day of the year, and the variable weather conditions that affect the energy production. The simulations confirm the state space explosion typical of model checking, but also hint that a small number of alternative tasks can achieve an overall utility very close to a large number of tasks. This conjecture has a strong practical relevance since it can pave the way to the wider adoption of energy neutrality concept in low-power IoT devices
ABOUT POINT CLOUDS_2nd EDITION
No full textIniziativa incentrata sul tema del "RILIEVO LASER SCANNER 3D" curata con la collaborazione della Leica Geosystems. Seconda edizione del Seminario al quale sono stati invitati a partecipare tutti gli studenti dei Corsi di Laurea Triennale e Magistrale della Scuola che ha previsto, anche con partecipazione di relatori esterni (in rappresentanza della Leica Geosystems), comunicazioni frontali sulle basi tecnico-operative relativi al funzionamento e all’utilizzo della strumentazione ed esercitazioni in esterno e in aula: sessioni di rilievo strumentale sul campo e aspetti teorico-pratici della restituzione da nuvole di punti
AOI cast by Tolerance Based Compass Routing in Distributed Virtual Environments
No full textThis paper presents an Area of Interest(AOI)-cast
strategy for P2P Distributed Virtual Environment (DVE) which
exploits a Delaunay Triangulation of the DVE to define a
compass-based routing algorithm. A set of formal results for
circular AOI is presented. Inconsistencies between local views
of different peers due to the network latency are faced by
introducing a tolerance threashold in the compass routing
Michele Taruffo: el magisterio y la obra ejemplares del genial procesalista «todoterreno»
No full textThe author reflects on Michele Taruffo’s extraordinarily important contribution to the renewal of both conventional procedural law scholarship and the theoretical background of law-court professionals. Taruffo’s contribution was achieved by means of introducing to mainstream culture in those circles the necessary knowledge of the underlying epistemic dimension, which was traditionally suppressed by the strictly legal one.El autor discurre acerca de la importantísima contribución de Michele Taruffo a la renovación del procesalismo convencional y del bagaje teórico de los profesionales de la jurisdicción, mediante la incorporación a la cultura dominante en tales medios del imprescindible conocimiento de la dimensión epistémica subyacente y tradicionalmente sofocada por la propiamente jurídica
Small sample properties of ML estimator in Vasicek and CIR models: a simulation experiment
No full textIn this paper we analyze small sample properties of the ML estimation procedure in Vasicek and CIR models. In particular, we consider short time series, with a length between 20 and 200, typically values observed in the field of survival data. We perform a simulation study in order to investigate which properties of the parameter estimators still remain valid and to evaluate the effect of a bootstrap bias correction method. The results show that the bias of the estimators can be really strong for small samples and the relative bias seems to be worse when the true parameters of the models are near to the nonstationarity case. The bootstrap bias correction is enough efficient in correcting the bias also for very small sample sizes, but the increase in RMSE of the estimator is greater as much as smaller is the bias in the ML estimator. Moreover, the bootstrap correction does not improve the performance of the tests on the parameters
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