1,721,299 research outputs found
Understanding political violence: a criminological analysis
No full textUnderstanding Political Violence introduces political violence in the context of sociological and criminological debates. The author distinguishes between political violence from below, for example collective violence, insurgency, armed struggle and terrorism; and political violence from above, which includes indiscriminate repression, institutional and state violence, torture and war. Vincenzo Ruggiero discusses and critiques the contribution of criminological theory to understanding political violence. He draws on stimulating case studies to illustrate the theory, including interviews with former members of the Red Army Faction in Germany and the Brigate Rosse in Italy.The concluding chapter examines the recent development of a criminology of war and calls for a general ceasefire and the criminalisation of war, the most extreme form of institutional violence.This is essential reading for students and researchers in criminology, political studies, sociology, and war and conflict studies.
This book, published in 2006, is now available in Italian and a Spanish and a Russian edition will soon be available
Editorial: Special issue mathematical methods and numerical computations in honor of Ilio Galligani
No full textThis special issue is a tribute to Professor Ilio Galligani. The presence of contributions in various and different fields of Numerical Mathematics shows how many researchers recognize Ilio as a reference figure for the community and remember him with great affection and gratitude
Generalizzazione dell'algoritmo di Grau per la valutazione numerica dei moduli degli zeri di un polinomio a coefficienti reali
No full textThe application of methods of the Graeffe-Lobachevsky type on an electronic computer introduces a practical difficulty: the process is severaly limited because of the problem of number range. In this paper a generalisation of Grau algorithm is presented, where this problem has been removed. © 1980 Università degli Studi di Ferrara
Effects of the Addition of Small Amounts of a Thermotropic liquid Crystalline Polymer on the Processing Characteristics of Polypropylene Oxide-Polyamide Alloys
No full textSpecial issue for SIMAI 2020–2021: large-scale optimization and applications
No full textIn 2016 the biennial congress of the Italian Society of Industrial and Applied Mathematics (SIMAI) was held at Politecnico di Milano (Italy). Promoting collaboration between mathematicians, industrial practitioners and management scientists is among
the main goals of SIMAI. In Milan, a number of minisymposiawere dedicated to applications and computational aspects of numerical optimization. The contributions from the SIMAI conference included in this special issue are far
from giving a complete picture of the mutual impact between numerical optimization and real world problems. Nevertheless, they span a diverse range of topics and applications, and in particular they show that even mathematical issues, that at first glance appear to be very theoretical, can have application-related aspects
Presentazione
No full textIl contributo è una breve introduzione al numero monografico dedicato al tema "Il metodo mafioso". Più in particolare, si è cercato di comporre letture interdisciplinari e comparate sui legami tra criminalità dei colletti bianchi, mafie, corruzione politica, controllo dell’informazione e sistemi di riciclaggio di capitali, analizzando gli effetti prodotti da tali legami sulla democrazia del nostro paese e sul suo sistema di relazioni internazionali, in uno scenario caratterizzato da una profonda crisi della rappresentanza e da una generale disaffezione dei cittadini per la politica, tentando anche di valutare l’impatto sul territorio di alcune attività di contrasto alla criminalità, condividendo esperienze di promozione della cittadinanza e di educazione alla democrazia
How Covid-19 Will Affect the Cruise Ship Projects.
No full textThis paper analyses the problems observed on cruise ships during the Covid-19 pandemic and proposes a series of changes in the design of passenger ships to face similar pandemics to allow the cruise ship market to re-open. The hospital facilities on board play a key role in this
On the efficiency of splitting and projection methods for large strictly convex quadratic programs
No full text--
Reprint of Inexact Bregman iteration for deconvolution of superimposed extended and point sources
No full textIn this paper we consider the deconvolution of high contrast images consisting of very bright stars (point component) and smooth structures underlying the stars (diffuse component). A typical case is a weak diffuse jet line emission superimposed to a strong stellar continuum. In order to reconstruct the diffuse component, the original object can be regarded as the sum of these two components. When the position of the point sources is known, a regularization term can be introduced for the second component. An approximation of the original object can be obtained by solving a reduced variational problem whose unknowns are the intensities of the stars and the diffuse component. We analyze this problem when the detected image is corrupted by Poisson noise and Tikhonov-like regularization is used, giving conditions for the existence and the uniqueness of the solution. Furthermore, since only an overestimation of the regularization parameter is available, we propose to solve the variational problem by inexact Bregman iteration combined with a Scaled Gradient Projection method (SGP). Numerical simulations show that the images obtained with this approach enable us to reconstruct the original intensity distribution around the point source with satisfactory accuracy
Ritz-like values in steplength selections for stochastic gradient methods
Full text linkThe steplength selection is a crucial issue for the effectiveness of the stochastic gradient methods for large-scale optimization problems arising in machine learning. In a recent paper, Bollapragada et al. (SIAM J Optim 28(4):3312–3343, 2018) propose to include an adaptive subsampling strategy into a stochastic gradient scheme, with the aim to assure the descent feature in expectation of the stochastic gradient directions. In this approach, theoretical convergence properties are preserved under the assumption that the positive steplength satisfies at any iteration a suitable bound depending on the inverse of the Lipschitz constant of the objective function gradient. In this paper, we propose to tailor for the stochastic gradient scheme the steplength selection adopted in the full-gradient method knows as limited memory steepest descent method. This strategy, based on the Ritz-like values of a suitable matrix, enables to give a local estimate of the inverse of the local Lipschitz parameter, without introducing line search techniques, while the possible increase in the size of the subsample used to compute the stochastic gradient enables to control the variance of this direction. An extensive numerical experimentation highlights that the new rule makes the tuning of the parameters less expensive than the trial procedure for the efficient selection of a constant step in standard and mini-batch stochastic gradient methods
- …
