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Community detection in networks has recently obtained a huge interest in both natural and social sciences, for its variety of implications and applications. Several algorithms and strategies have been proposed up to now, mainly focusing on speed optimization or on the quality of the nal clustering obtained. The main scope of this paper is to bridge these two ap- proaches, via the introduction of heuristic schemes, which may be intended as a ranking of nodes inside a graph, indicating those who pose major prob- lems in community assignment. By performing the slowest, most eective algorithms (renement) on only a small fraction of the whole network, this approach is made applicable to huge networks.

The need to cut off lead times, to increase the products innovation, to respond to changing customer requirements and to integrate new technologies into business process pushes companies to increase the collaboration. In particular, collaboration, knowledge sharing and information exchange in the Aerospace Value Network, need to a clear definition and identification of competencies of several actors. Main contractors, stakeholders, customers, suppliers, partners, have different expertise and backgrounds and in this collaborative working environment are called to work together in projects, programs and process. To improve collaboration and support the knowledge sharing, a competencies definition methodology and the related dictionary result useful tools among actors within an extended supply chain. They can use the same terminology and be informed on the competencies available. It becomes easy to specify who knows to do required activities stimulating collaboration and improving communication. Based on an action research developed in the context of the iDesign Foundation project, the paper outlines a competency definition methodology and it presents examples from the implementation in Alenia Aeronautica company. A new definition of competency is suggested supporting by a new method to specify the structural relationship between competencies and activities of aeronautical processes.

We extend the correlated basis functions theory (CBF) for nuclei with different number of protons and neutrons and in j-j coupling scheme. By means of the Fermi hypernetted chain integral equations, in conjunction with the single operator chain approximation (FHNC/SOC), we evaluate the ground state and the one-body densities for 40Ca, 48Ca and 208Pb nuclei. The realistic Argonne V8' two-nucleon potentials has been used. We compare the ground-state properties of these nuclei calculated by using correlation functions with and without tensor components., 4 Pages, 2 figures, Talk presented at the workshop , Cortona (It) 6-9 Oct. 2004

Influence measures, like social network analysis (SNA) metrics, Twitter social parameters, sentiment score and influence maximisation, are used in the literature in order to provide a characterisation of the user role and the content of messages inside a social media communication network. Using a Twitter network related to the international event EXPO2015, crawled from the event’s page, the paper measures the correlation between different influence measurements. The aim is to obtain an influence indicator framework able to interpret different user behaviour through the evaluation of user popularity, participation, influence and polarity of texts.

The application of the Correlated basis function theory and of the Fermi hypernetted chain technique, to the description of the ground state of medium-heavy nuclei is reviewed. We discuss how the formalism, originally developed for symmetric nuclear matter, should be changed in order to describe finite nuclear systems, with different number of protons and neutrons. This approach allows us to describe doubly closed shell nuclei by using microscopic nucleon-nucleon interactions. We presents results of numerical calculations done with two-nucleon interactions of Argonne type,implemented with three-body forces of Urbana type. Our results regard ground-state energies, matter, charge and momentum distributions, natural orbits, occupation numbers, quasi-hole wave functions and spectroscopic factors of 12C, 16O, 40Ca, 48Ca and 208Pb nuclei., 127 Pages, 37 figures, Accepted for publication in Physics Reports

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, aiming at the reconstruction of a networked structure from observations of the states of the nodes in the network. The inverse Potts model, normally applied to observations of quantum states, is here addressed to observations of the node states in a network and their (anti)correlations, thus inferring interactions as links connecting the nodes. Adopting the Bethe approximation, such an inverse problem is known to be tractable. Within this operational framework, we discuss and apply this network-reconstruction method to a small real-world social network, where it is easy to track statuses of its members: the Italian parliament, adopted as a case study. The dataset is made of (co)sponsorships of law proposals by parliament members. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with standard methods, outlining discrepancies and advantages.

The role of human resources has become a key factor for the success of an organization. Based on a research collaboration with an aeronautical company, the paper proposes a comparison of two different approaches for the reconstruction of a collaborative social network in the business realm: the use of traditional Social Network Analysis and novel statistical inference models. Both approaches were evaluated against data provided by the company, in order to scout the key people in the network and the knowledge-transfer processes. As a main outcome of this paper, it was found how the network reconstruction using statistical models has an increased robustness, as well as sensitivity, allowing to discover hidden correlations among the users.

This research aims to apply models extracted from the many-body quantum mechanics to describe social dynamics. It is intended to draw macroscopic characteristics of organizational communities starting from the analysis of microscopic interactions with respect to the node model. In this chapter, the authors intend to give an answer to the following question: which models of the quantum physics are suitable to represent the behaviour and the evolution of business processes? The innovative aspects of the project are related to the application of models and methods of the quantum mechanics to social systems. In order to validate the proposed mathematical model, the authors intend to define an open-source platform able to model nodes and interactions within a network, to visualize the macroscopic results through a digital representation of the social networks.

The complexity in engineering processes of high technology companies needs to carefully and efficiently manage the human resources competences dedicated to the related activities. Focus on an Italian aerospace company, Alenia Aeronautica, the paper wants to illustrate the use of set theory in order to represent objects, rules and indexes of the competence management methodology. This mathematical formalism allows to easily represent the complexity of this context and to guide the implementation of a future competence management system (CMS). In addition, the use of an algebraic approach allows the implementation of a competence management information system that may be customized to any industrial context. In addition, this flexible structure can be easily modified to respond to a continuously changing competence scenario related to the business environment.

In this paper, the authors apply models extracted from the Many-Body Quantum Mechanics to understand how knowledge production is correlated to the innovation potential of a work team. This study is grounded in key assumtpions. First, complexity theory applied to social science suggests that it is of paramount importance to consider elements of non-objectivity and non-determinism in the statistical description of socio-economic phenomena. Second, a typical factor of indeterminacy in the explanation of these phenomena lead to the need to apply the instruments of quantum physics to formally describe social behaviours. In order to experiment the validity of the proposed mathematic model, the research intends to: 1) model nodes and interactions; 2) simulate the network behaviour starting from specific defined models; 3) visualize the macroscopic results emerging during the analysis/simulation phases through a digital representation of the social network.

The correlated basis function theory is applied to the study of medium-heavy doubly closed shell nuclei with different wave functions for protons and neutrons and in the jj coupling scheme. State dependent correlations including tensor correlations are used. Realistic two-body interactions of Argonne and Urbana type, together with three-body interactions have been used to calculate ground state energies and density distributions of the 12C, 16O, 40Ca, 48Ca and 208Pb nuclei., Comment: Latex 10 pages, 3 Tables, 10 Figures