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[null,"1.","Record Nr.",null,"UNISA990003363620203316"]
[null,null,"Autore",null,"ARNICHES, Carlos"]
[null,null,"Titolo",null,"Del Madrid castizo Sainetes / Carlos Arniches ; edición de José Montero Padilla"]
[null,null,"Pubbl/distr/stampa",null,"Madrid : Cátedra, copyr. 1981"]
[null,null,"ISBN",null,"84-376-0143-6"]
[null,null,"Descrizione fisica",null,"161 p. ; 18 cm"]
[null,null,"Collana",null,"Letras Hispánicas ; 80"]
[null,null,"Disciplina",null,"862.5"]
[null,null,"Soggetti",null,"Teatro spagnolo"]
[null,null,"Collocazione",null,"II.5.COLL.1/80"]
[null,null,"Lingua di pubblicazione",null,"Spagnolo"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910580237403321"]
[null,null,"Autore",null,"Alexandre‑Bidon Danièle"]
[null,null,"Titolo",null,"Le château médiéval, forteresse habitée : (XIe-XVIe s.) Archéologie et histoire : perspectives de la recherche en Rhône-Alpes / / Jean-Michel Poisson"]
[null,null,"Pubbl/distr/stampa",null,"Paris, : Éditions de la Maison des sciences de l’homme, 2021"]
[null,null,"ISBN",null,"2-7351-2583-1"]
[null,null,"Descrizione fisica",null,"1 online resource (176 p.)"]
[null,null,"Collana",null,"Documents d’archéologie française"]
[null,null,"Soggetti",null,"Archaeology"]
[{"$nulls":4},"Moyen Âge"]
[{"$nulls":4},"comté de Forez"]
[{"$nulls":4},"résidence"]
[{"$nulls":4},"fortification"]
[{"$nulls":4},"Rhône-Alpes"]
[{"$nulls":4},"sanctuaires castraux"]
[null,null,"Lingua di pubblicazione",null,"Francese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Qui étaient les habitants du château, principal centre de pouvoir au Moyen Âge ? Quel était leur cadre de vie ? Autant de questions auxquelles les études regroupées dans cet ouvrage veulent répondre. Confrontant les données archéologiques et les sources écrites, inhabituellement traitées ici comme des sciences auxiliaires de l’archéologie, elles nous offrent l’image inattendue d’un château peu habité. Portant principalement sur la région Rhône-Alpes, avec quelques incursions à titre de comparaison en Alsace, en Espagne et en Pologne, leur objet dépasse largement ces limites régionales et suscitera l’intérêt de tout archéologue et historien médiéviste.  Who were the inhabitants of the castle, the main center of power during the Middle-Ages? What um their life style? These are some of the many questions to which this Collective study hopes to reply. Confronted by archaeological and written evidence, unusually treated here as sciences auxiliary to archaeology we are offered here an unusual lieu of a sparsly inhabited castle. This study is centred on the region of the Rhône-Alpes with several incursions for comparison in Alsace, Spain "]
[{"$nulls":4},"and in Poland, their objective goes far outside the regional limits and should provoke the interest of all archaeologists and medieval historians."]
[null,"3.","Record Nr.",null,"UNINA9910557776003321"]
[null,null,"Autore",null,"Gómez Vela Francisco A"]
[null,null,"Titolo",null,"Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast"]
[null,null,"Pubbl/distr/stampa",null,"Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021"]
[null,null,"Descrizione fisica",null,"1 online resource (100 p.)"]
[null,null,"Soggetti",null,"Research & information: general"]
[{"$nulls":4},"Technology: general issues"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting. In light of the above, this Special Issue collects the latest research on relevant topics, in particular in energy demand forecasts, and the use of advanced optimization methods and big data techniques. Here, by energy, we mean any kind of energy, e.g., electrical, solar, microwave, or wind"]