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In this paper, data concerning MILANO EXPO2015 is collected from the official twitter page of the event before and after its opening. In order to extract a semi-supervised ontology and to evaluate the global sentiment around the event, a variety of language processing techniques has been applied on the collected “tweets”: Latent Semantic Analysis, sentiment polarity tracking, along with gap analysis has allowed the semantic evaluation of users’ opinions. Moreover, the generalized cross entropy approach has been applied for the first time on web data, adding prior information on the effect of semantic classes on the global sentiment, improving accuracy and adding detail to the analysis.

Cultural events are an important driver of socio-cultural-economic transformation. The growth of Information and Communication Technologies (ICTs) has affected the ways in which people can play an active role in cultural event management and urban planning. This work proposes a methodological approach that identifies the key elements for building bottom-up urban e-planning strategies. After a brief theoretical analysis of the impact of cultural activities, tourism and ICTs on urban planning, this paper presents the results of an empirical study carried out in the Puglia region (south of Italy) during the cultural event known as “La Notte della Taranta”, in which the crowd created added-value information via comments posted on social media. Data were collected using a mobile application specifically created for this event as part of the Folkture project, as well as from Facebook and Twitter posts. Using network-analytic and sentiment/semantic algorithms, the work aims to support the event management decisional process and produce results valuable to the field of urban planning.

In this paper, we present a pattern language for sharing practical knowledge to design innovative projects, which we call project design patterns. This pattern language consists of 32 patterns about designing projects, which are organised into five categories: core, learn, create, live, and pleasure. This collection of practical knowledge behind designing projects was created through a mining process of interviewing professional project designers, organising the mined elements using the KJ method (a method for clustering ideas named based on the initials of its originator), and writing the information in the pattern format: pattern name, illustration, context, problem, solution, and consequence. This paper presents three patterns in full as well as summaries of all 32 patterns. Survey results and responses of workshop participants and users, presented in the later sections of the paper, provide exploratory data which testify to the potential power of the proposed language for thinking, reflection, and dialogue on designing innovative projects.

This study examines the University-Industry (UI) interface, in Triple Helix (TH) Model. In the era of Knowledge-based Economy, the Third Mission generates new value that depending from UI interface. New businesses, revealed with the Spin-offs creation, catalyzed by this interface, aims to commercialize the results coming from research activities. The purpose of this article is to understand features of an UI interface in order to support adequately the spin-off establishment and reduce the risk of not overcome the Death Valley. The study was conducted through direct interviews to 39 CEOs of the University of Salento' spin-offs. So, applying Social Network Analysis (SNA) and Sentiment Analysis (SA) techniques, four clusters of main emerged themes and the relative text sentiment were identified.

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 compares two different approaches for the reconstruction of a collaborative social network in the business realm. Traditional social network analysis and novel statistical inference models were both evaluated against data provided by the company, with the final scope of scouting key employees in the network, as well as exploiting 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.

Due to their delta-like density of states, quantum dots (QDs) were expected to improve laser device performances with respect to quantum wells (QWs). Nevertheless, some important drawbacks limit this technology. For instance, QD laser still suffers from a low value of the modal gain, due to the low areal density of QDs, and inhomogeneous broadening, especially when multistacked layers are used. In this paper, we demonstrate that a linear increase of the QD modal gain with the QD layers number, as typically achieved in multi-QW lasers, is possible by a careful control of the Stranski-Krastanov QDs growth and QDs stacking optimization. A low-transparency current density of 10 A/cm(2) per QD layer and a modal gain of 6 cm(-1) per QD layer Were achieved from laser structures containing up to seven QD layers. We demonstrate 10-Gb/s direct modulation (until a temperature of 50 degrees C and high T-0 (110 K) from a single-mode device containing six QD layers.

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.

The need for urban regeneration does not come only by structural requirements, but also by socio- cultural needs. What we are going to propose is the urban regeneration as a way to perceive, in a different way, the surrounding spaces allowing users to receive and provide a wide range of information on the urban environment. Each space of a city has a variety of intrinsic meanings provided by human groups interacting with each other everyday. The purpose is collecting the hidden information thanks to citizens' contribution. The objective is the involvement of citizens as "builders of sense" through a playful attitude as "builders of virtual cities", and using game based on motivation as impetus for the regeneration. Urban regeneration is innovative thanks to a new participatory and cooperative methodology based on the perception of every citizen, and on the collection of players' experiences.

High performance 1300 nm lasers based on self-organized InAs/InGaAs quantum dots (QDs) are reported. By optimizing the QD growth parameters and decreasing the waveguide thickness, a high modal gain and a low transparency current density of 32 cm(-1) and 35 A cm(-2), respectively, were obtained from a device containing five stacked QD layers. The internal quantum efficiency is as high as 90%.

The authors have recently demonstrated the enhancement of the quantum dot laser modal gain, linearly scaling with the number of stacked QD layers. These results allowed the achievement of multi-quantum dot (MQD) lasers, the zero-dimensional counterpart of MQW lasers, with a modal gain as high as 42 cm(-1), in a seven-layer structure. A detailed investigation of the structural and optical properties was performed on laser structures with three, five and seven QD layers. Such an investigation clearly shows that the high uniformity of QD layer features is responsible for the linear increase of the modal gain and its high value.