Giuseppe Giordano – författare

This volume gathers the latest advances, innovations, and applications in the field of biosystems engineering, as presented at the 12th Conference of the Italian Association of Agricultural Engineering (AIIA), held in Palermo, Italy, on September 19-22, 2022. Focusing on the challenges of improving the resilience of agriculture, forestry and food systems in the post-Covid era, it shows how the research has addressed the following topics: Monitoring and modelling hydraulic and hydrological processes in agriculture and forestry systems; Challenges in stream rehabilitation and soil conservation strategies; Sustainable water resource management under climate change scenarios; Planning safe, healthy and resilient territorial, built and green systems; Cultural heritage preservation and rural landscape protection, planning and management; Plant and livestock production processes and technologies. Healthy and Organic farming. Animal welfare; Energy, waste and by-products smart use; Post-harvest logistics and food chain structures technology; Applications and experiences in smart agriculture and forestry; One Health, management and standardization for agriculture and forestry machinery and structures; Big data, machine learning and data hub in biosystems engineering. The contributions were selected by a rigorous peer-review process, and offer an extensive and multidisciplinary overview of the research in the field of biosystems engineering for sustainable agriculture.Chapter 110 is available open access under a Creative Commons Attribution BY-NC-ND 4.0 license via link.springer.com.

This volume gathers the latest advances, innovations, and applications in the field of biosystems engineering, as presented at the 12th Conference of the Italian Association of Agricultural Engineering (AIIA), held in Palermo, Italy, on September 19-22, 2022. Focusing on the challenges of improving the resilience of agriculture, forestry and food systems in the post-Covid era, it shows how the research has addressed the following topics: Monitoring and modelling hydraulic and hydrological processes in agriculture and forestry systems; Challenges in stream rehabilitation and soil conservation strategies; Sustainable water resource management under climate change scenarios; Planning safe, healthy and resilient territorial, built and green systems; Cultural heritage preservation and rural landscape protection, planning and management; Plant and livestock production processes and technologies. Healthy and Organic farming. Animal welfare; Energy, waste and by-products smart use; Post-harvest logistics and food chain structures technology; Applications and experiences in smart agriculture and forestry; One Health, management and standardization for agriculture and forestry machinery and structures; Big data, machine learning and data hub in biosystems engineering. The contributions were selected by a rigorous peer-review process, and offer an extensive and multidisciplinary overview of the research in the field of biosystems engineering for sustainable agriculture.Chapter 110 is available open access under a Creative Commons Attribution BY-NC-ND 4.0 license via link.springer.com.

This volume presents a selection of articles which explore methodological and applicative aspects of textual data analysis. Divided into four parts, it begins by focusing on statistical methods, and then moves on to problems in quantitative language processing. After discussing the challenging task of text mining in relation to emotional and sentiment analyses, the book concludes with a collection of studies in the social sciences and public health which apply textual data analysis methods.The refereed contributions were originally presented at the 16th International Conference on Statistical Analysis of Textual Data (JADT 2022), which took place in Naples, Italy, on July 6-8, 2022. The biennial JADT meeting discusses theories, problems, and practical uses of textual data analysis in various fields, sharing a quantitative approach to the study of lexical, textual, pragmatic or discursive features of information expressed in natural language.

This volume presents a selection of articles which explore methodological and applicative aspects of textual data analysis. Divided into four parts, it begins by focusing on statistical methods, and then moves on to problems in quantitative language processing. After discussing the challenging task of text mining in relation to emotional and sentiment analyses, the book concludes with a collection of studies in the social sciences and public health which apply textual data analysis methods.The refereed contributions were originally presented at the 16th International Conference on Statistical Analysis of Textual Data (JADT 2022), which took place in Naples, Italy, on July 6-8, 2022. The biennial JADT meeting discusses theories, problems, and practical uses of textual data analysis in various fields, sharing a quantitative approach to the study of lexical, textual, pragmatic or discursive features of information expressed in natural language.

This book on statistical models and learning methods for complex data comprises a selection of peer-reviewed post-conference papers presented at the 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2023), held in Salerno, Italy, September 11–13, 2023. The contributions span a variety of topics, including different approaches to clustering and classification, multidimensional data analysis, panel data, social networks, time series, statistical inference, and mixture models. These methodologies are applied to a range of empirical domains such as economics, finance, hydrology, the social sciences, education, and sports.Organized biennially by international scientific committees, the CLADAG meetings advance methodological research in multivariate statistics, with a strong focus on data analysis and classification. They facilitate the exchange of ideas in these fields and promote the dissemination of concepts, numerical methods, algorithms, and computational and applied results.Chapter "Identification of misogynistic accounts on Twitter through Graph Convolutional Networks" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.