1,721,448 research outputs found
Diversity management e anticorruzione nella Direttiva 95/2014: passione e ispirazione quali motori della loro unione
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A preliminary experimentation for large scale epidemic forecasting simulations
No full textAgent-based modeling and simulation are some powerful techniques that are widely used with success for analyzing complex and emergent phenomena in many research and application areas. Many different reasons are behind the success of such techniques, among which an important mention goes to the availability of a great variety of software tools, that ease the development of models, as well as the execution of simulations and the analysis of results. This paper presents an actor software library, called ActoDeS, for the development of concurrent and distributed systems, and shows how it can be a suitable mean for building flexible and scalable epidemic forecasting simulations. In particular, the paper presents the first results of the experimentation of ActoDeS for defining a COVID-19 epidemic diffusion model and for supporting the simulation in large populations
Appalti e criterio dell’offerta economicamente più vantaggiosa: dal massimo ribasso a condotte d’impresa responsabile con impatto sociale
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Valorizzare la diversità di genere è responsabilità delle imprese, in Sviluppo & Organizzazione
No full textActorNode2Vec: An Actor-based solution for Node Embedding over large networks
No full textThe application of Machine Learning techniques over networks, such as prediction tasks over nodes and edges, is becoming often crucial in the analysis of Complex systems in a wide range of research fields. One of the enabling technologies in that sense is represented by Node Embedding, which enables us to learn features automatically over the network. Among the different approaches proposed in the literature, the most promising are DeepWalk and Node2Vec, where the embedding is computed by combining random walks and neural language models. However, characteristic limitations with these techniques are related to memory requirements and time complexity. In this paper, we propose a distributed and scalable solution, named ActorNode2vec, that keeps the best advantages of Node2Vec and overcomes the limitations with the adoption of the actor model to distribute the computational load. We demonstrate the efficacy of this approach with a large network by analyzing the sensitivity of walk length and number of walks parameters and make a comparison also with Deep walk and an Apache Spark distributed implementation of Node2Vec. Results show that with ActorNode2vec computational times are drastically reduced without losing embedding quality and overcoming memory issues
Creare valore economico e fare il bene comune: la nuova sfida della strategia d'impresa
No full textCorporate reputation has fallen down to the lowest historical level. Companies are faced by a strong and growing request to act as conscious social actors and not only as cynical profit maximizers; on the other side the well-known CSR (Corporate Social Responsibility) movement, originally arisen just for that, is more and more criticized, being accused to have missed its own main objective. Even the recent model of “Shared Value Creation”, proposed by Porter and Kramer as the solution, is contested as a simplistic and superficial approach. In this confused and complex scenario our contribute, stemming from an empirical and consistent analysis of a large number of companies, aims at framing a model which integrates the “Common Good” construct into the corporate strategies, identifying a viable path to reconcile the “common good perspective” with the inescapable goal of creating economic value
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