https://hdl.handle.net/10807/214 Sun, 02 Aug 2026 10:53:59 GMT 2026-08-02T10:53:59Z https://hdl.handle.net/10807/343678 Titolo: Strategizing in the entrepreneurial process during periods of chaos Autori: chiara cantu Abstract: The main aim of this paper is to investigate the key changes affecting the strategies configuration in the entrepreneurial process of SMEs, in order to address the main challenges characterizing periods of chaos. In particular, the paper investigates the changes affecting strategies characterizing an Italian SME, considering the challenges of Twin Transition and globalization process. Findings highlight the relevance of networking for opportunities identification and management, that sustain the growth of SMEs. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/10807/343678 2026-01-01T00:00:00Z https://hdl.handle.net/10807/343677 Titolo: Innovation Ecosystem towards sustainability: the role of innovation intermediaries Autori: Chiara Cantu Abstract: Green and digital transitions are affecting the current situation and will affect the future of several industries. Over the years a growing attention has been recognized to collaborative strategies that foster Twin transition and its development. Among the collaborative strategies, scholars have emphasized the importance of relationships characterizing the Innovation Ecosystem. This latter supports the innovation development on the basis of interactions between firms, institutions, universities, and various organization belonging mainly to the same geographical area. In a wider perspective, Innovation Network, based on IMP perspective, recognizes the key role of relationships belonging to various geographic areas and characterized by the same relational proximity. In this contex, the aim of this research is to investigate the potentialities of Innovation Network on the value configuration of technology start-ups, sopporting their growth to become scale- ups and their orientation towards sustainability. In particular, the research analysis the role of Innovation Intermediaries in this process of transition. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/10807/343677 2026-01-01T00:00:00Z https://hdl.handle.net/10807/341563 Titolo: Comparison of different similarity measures in hierarchical clustering Autori: Vagni, Marica; Giordano, Noemi; Balestra, Gabriella; Rosati, Samanta Abstract: The management of datasets containing heterogeneous types of data is a crucial point in the context of precision medicine, where genetic, environmental, and life-style information of each individual has to be analyzed simultaneously. Clustering represents a powerful method, used in data mining, for extracting new useful knowledge from unlabeled datasets. Clustering methods are essentially distance-based, since they measure the similarity (or the distance) between two elements or one element and the cluster centroid. However, the selection of the distance metric is not a trivial task: it could influence the clustering results and, thus, the extracted information. In this study we analyze the impact of four similarity measures (Manhattan or L1 distance, Euclidean or L2 distance, Chebyshev or L∞ distance and Gower distance) on the clustering results obtained for datasets containing different types of variables. We applied hierarchical clustering combined with an automatic cut point selection method to six datasets publicly available on the UCI Repository. Four different clusterizations were obtained for every dataset (one for each distance) and were analyzed in terms of number of clusters, number of elements in each cluster, and cluster centroids. Our results showed that changing the distance metric produces substantial modifications in the obtained clusters. This behavior is particularly evident for datasets containing heterogeneous variables. Thus, the choice of the distance measure should not be done a-priori but evaluated according to the set of data to be analyzed and the task to be accomplished. Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/10807/341563 2021-01-01T00:00:00Z https://hdl.handle.net/10807/341559 Titolo: T-Wave Alternans Identification in Direct Fetal Electrocardiography Autori: Marcantoni, Ilaria; Vagni, Marica; Agostinelli, Angela; Sbrollini, Agnese; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura Abstract: Very little is known about the incidence and etiology of fetal T-wave alternans (TWA), an electrophysiologic phenomenon potentially associated to fetal suboptimal outcomes. Thus, availability of automatic methods for quantification of TWA from digital electrocardiograms (ECG) is desirable, since TWA occurrence might indicate the need of taking actions before or during delivery. The heart-rate adaptive match filter (HRAMF) is a well-established method to identify TWA in adult ECG. Aim of the present study was to investigate the possibility of using HRAMF to identify and quantify TWA also in direct fetal ECG (DFECG) recordings. To this aim, HRAMF was applied to 5 min-long DFECG acquired during delivery ("Abdominal and Direct Fetal Electrocardiogram Database" by Physionet) of five healthy fetuses. Significant levels of TWA were measured in all DFECG. Specifically, on average, TWA was quite high in amplitude (9±2 μV) and variable in time, as indicated by values of standard deviation (6±2 μV) and maximum (28±10 μV) of TWA amplitude. Eventually, a positive correlation (ρ=0.68) was observed between maximum TWA and fetal heart rate, even though the limited number of recordings makes this result preliminary. In conclusion, HRAMF proved to be a suitable tool to automatically identify TWA from DFECG. Sun, 01 Jan 2017 00:00:00 GMT https://hdl.handle.net/10807/341559 2017-01-01T00:00:00Z