Lucia Errico, Andrea Mosca and Sandro Rondinella
This study explores whether ethnic minorities exhibit varying levels of income inequality compared to the host population.
Abstract
Purpose
This study explores whether ethnic minorities exhibit varying levels of income inequality compared to the host population.
Design/methodology/approach
The research leverages a unique immigration event in Italy, specifically the settlement of multiple Albanian groups in southern Italy during the 16th century. This historical occurrence enables an investigation into the role of cultural traits in income inequality, as these groups are situated in the same geographical region and often share borders.
Findings
The results, which remain consistent after undergoing various robustness checks, indicate that Albanian villages, while still preserving their identity and tradition, tend to experience an approximately 2% lower level of income concentration compared to similar Italian municipalities.
Originality/value
Our findings aim to provide supporting evidence for future policy considerations regarding the long-term impact of immigration on income inequality.
Details
Keywords
Questioning gender is about taking an active, critical role in the technological design of our daily behaviour. It is a deconstruction of the oppositions that exist in the…
Abstract
Questioning gender is about taking an active, critical role in the technological design of our daily behaviour. It is a deconstruction of the oppositions that exist in the discourses of Ambient Intelligence designers, the ICT industry and computer scientists. What underlies the assumption that Ambient Intelligence will, by disappearing into our environment, bring humans both an easy and entertaining life? The gender perspective can uncover power relations within the promotion and realisation of Ambient Intelligence that satisfy an obvious wish for a technological heaven. The deconstruction of the promise of progress and a better life reveals what is overvalued, what is undervalued and what is ignored. This paper is a deconstruction of the view, currently prevalent in the discourses of Ambient Intelligence; a view of humans and the way they live. A view that will influence the way women and men will be allowed to construct their lives.
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Marcello Sylos Labini, Arturo Covitti, Giuseppe Delvecchio and Ferrante Neri
Sets out a method for determining the dangerous areas on the soil surface. The touch voltages are calculated by a Maxwell's subareas program. The search for the areas in which the…
Abstract
Sets out a method for determining the dangerous areas on the soil surface. The touch voltages are calculated by a Maxwell's subareas program. The search for the areas in which the touch voltages are dangerous is performed by a suitably modified genetic algorithm. The fitness is redefined so that the genetic algorithm does not lead directly to the only optimum solution, but to a certain number of solutions having pre‐arranged “goodness” characteristics. The algorithm has been called “quasi‐genetic” algorithm and has been successfully applied to various grounding systems.
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Giuseppe Delvecchio, Claudio Lofrumento, Ferrante Neri and Marcello Sylos Labini
This paper aims to design an algorithm able to locate all the possible dangerous areas generated by the leaking of a fault current in a grounding system (i.e. the areas where the…
Abstract
Purpose
This paper aims to design an algorithm able to locate all the possible dangerous areas generated by the leaking of a fault current in a grounding system (i.e. the areas where the limits of the technical standards are not respected) and thus locate, inside each area, the point which takes locally the maximum value of touch voltage.
Design/methodology/approach
A fast evolutionary‐deterministic algorithm to solve constrained multimodal optimization problems is proposed. The algorithm is composed by three algorithmic blocks: a Quasi Genetic Algorithm to find a population of feasible solutions, a Fitness Sharing Selection to choose a subpopulation of feasible and fitter solutions having high diversity, a Hooke‐Jeeves Algorithm to find all the global and local feasible maxima.
Findings
The proposed algorithm has been successfully applied to various current field (i.e. to many shapes of grounding grids) problems to find the dangerous values of touch voltages generated by various grounding systems having any shape and it has turned out to be fast and reliable.
Originality/value
For this kind of problems, in fact, there is a lack, in literature, of multimodal optimization methods under safety constraints and the application of classical methods (e.g. genetic algorithms or deterministic methods) would be often inadequate since these methods are made so as to converge towards a single maximum point and so they unavoidably lose the information related to all the other possible maxima. On the contrary, a good application of the proposed allows the overcoming of these limits.