In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications.
Olive growing is expanding rapidly in many countries around the world in which olives have not previously been widely cultivated. Pruning olive trees is quite different from pruning other fruit trees of the temperate zone, because of their biological peculiarities. Errors in pruning may result in yield losses or higher cultivation costs. Pruning also determines the training system which, in turn, is one of the major factors for successful tree performance and orchard profitability. Pruning and Training Systems for Modern Olive Growing summarises the information available on current pruning techniques and training systems. It specifically addresses the problems faced by growers, professionals and students who are new to olive growing and provides information previously not available in English. The fundamental aim of this book is to explain the basic concepts at a practical level. It will allow the reader, whether experienced horticulturalist or beginner, to develop his or her own skills and pruning strategy.
This book collects notes that were prepared for a university course taught in the Spring of 2018, and delivered to an audience of students enrolled in the Master course in Logic, philosophy and history of science of the University of Florence. The goal of the course was to introduce students to some basic concepts from the area of research generally known as decision theory. This is done by focussing on the concept of ‘rational choice’, which is analyzed, methodologically speaking, by the means of the theory of games. To minimize prerequisites it was decided to restrict the attention to the theory of finite games in particular. The topics treated are vary, and belongs to both the theory of games ‘in normal form’ as well as that of games ‘in extensive form’, as they are usually referred to. The classical issues in both fields, such as the theory of ‘equilibria’ and the study of properties such as determinacy, are carefully discussed to make them clear to beginners and are addressed from a novel perspective which makes use of formal methods that are typical of researches connected with the study of logic.
In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications.
Olive growing is expanding rapidly in many countries around the world in which olives have not previously been widely cultivated. Pruning olive trees is quite different from pruning other fruit trees of the temperate zone, because of their biological peculiarities. Errors in pruning may result in yield losses or higher cultivation costs. Pruning also determines the training system which, in turn, is one of the major factors for successful tree performance and orchard profitability. Pruning and Training Systems for Modern Olive Growing summarises the information available on current pruning techniques and training systems. It specifically addresses the problems faced by growers, professionals and students who are new to olive growing and provides information previously not available in English. The fundamental aim of this book is to explain the basic concepts at a practical level. It will allow the reader, whether experienced horticulturalist or beginner, to develop his or her own skills and pruning strategy.
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