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.
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniqu
Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happening in the world of big data and digital innovation and to understand these impacts on our minds and relationships between people, traceability and the computability of behavior of individuals and social organizations.This book analyses contemporary and future issues related to big data, algorithms, data analysis, artificial intelligence and the internet. It introduces and discusses relationships between digital technologies and power, the role of the pervasive algorithms in our life and the risk of technological alienation, the relationships between the use of big data, the privacy of citizens and the exercise of democracy, the techniques of artificial intelligence and their impact on the labor world, the Industry 4.0 at the time of the Internet of Things, social media, open data and public innovation.Each chapter raises a set of questions and answers to help the reader to know the key issues in the enormous maze that the tools of info-communication have built around us.
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. - Introduces data analysis techniques and cloud computing concepts - Describes cloud-based models and systems for Big Data analytics - Provides examples of the state-of-the-art in cloud data analysis - Explains how to develop large-scale data mining applications on clouds - Outlines the main research trends in the area of scalable Big Data analysis
The transition from Latin to vernacular languages in the late Middle Ages and the dramatic rise of a new readership produced a huge bulk of translations, particularly of religious literature in its various genres. The solutions are so multifarious that they defy any attempt to outline general theories. This is particularly visible when the same text is translated or rewritten at different times and in different languages or genres. Through a minute analysis of texts this book aims at highlighting lexical, syntactic and stylistic choices dictated not only by the source but also by new readers and patrons, or by new destinations of the works. Established categories such as 'literalness' and 'fidelity' are thus questioned and integrated with these other factors which, while being more 'external', do nonetheless impinge on the very idea of 'translation', and consequently on its assessment. Far from being a mere transfer from one language to another, a medieval translation verges on a form of creative writing, and as such its study becomes a fascinating investigation into the very process of textual production.
Since 1971, the International Congress for Neo-Latin Studies has been organised every three years in various cities in Europe and North America. In August 2009, Uppsala in Sweden was the venue of the fourteenth Neo-Latin conference, held by the International Association for Neo-Latin Studies. The proceedings of the Uppsala conference have been collected in this volume under the motto Litteras et artes nobis traditas excolere Reception and Innovation. Ninety-nine individual and five plenary papers spanning the period from the Renaissance to the present offer a variety of themes covering a range of genres such as history, literature, philology, art history, and religion. The contributions will be of relevance not only for scholarly readers, but also for an interested non-professional audience.
The problem of integrating multiple information sources into a uni?ed data store is currently one of the most important challenges in data management. Within the ?eld of source integration, the problem of automatically gen- ating an integrated description of the data sources is surely one of the most relevant. The signi?cance of the issue can be best understood if one c- siders the huge number of information sources that an organization has to integrate. Indeed, it is even impossible to try to do all the work by hand. Like other important issues in data management, the problem of integrating multiple data sources into a unique global system has several facets, each of which represents, “per se”, an interesting research problem, and comprises, for instance, that of recognizing, at the intensional level, similarities and dissimilarities among scheme objects, that of resolving representation m- matches among schemes, and that of deciding how to obtain an integrated data store out of a set of input sources and of a semantic description of their contents. The research and application relevance of such issues has attracted wide interest in the database community in recent years. And, as a con- quence, several techniques have been presented in the literature attacking one side or another of this complex and multifarious problem.
Raffaele Pettazzoni (1883–1959), Professor of the History of Religions at the University of Rome and one of the leading historians of religions in the twentieth century, maintained a long correspondence with Herbert Jennings Rose (1883–1961), the gifted Canadian scholar who was Professor of Greek at St Andrews and is best known for his work in the field of ancient religion and folklore. These letters, spanning the years 1927 to 1958, bear witness to the close relationship between the two scholars and focus on two of Pettazzoni’s books, both translated by Rose: Essays on the History of Religions (1954) and The All-Knowing God (1956). They also shed light on Pettazzoni’s initiative to the foundation of the journal NVMEN (1954), and reveal Rose’s brilliant personality.
This volume brings together a set of classic essays by Domenico Sella in which he reassesses the economic fortunes of Northern Italy, in particular Lombardy and Venice, during the 16th and 17th centuries. In addition, the literature on the economics and society of northern Italy had hitherto dealt primarily with the major cities, Milan, Florence and Venice, and their celebrated manufactures, extensive commercial activities and banking. By contrast their countryside was largely neglected and its population dismissed as an undifferentiated mass of peasants fully engaged in farming. The essays in this volume represent as many soundings into this "long forgotten" rural world. As it turns out, rural communities often harbored handicraft industries, and the latter appear to have avoided the debacle that hit the urban economies and their celebrated manufactures, highly regulated as they were by the guilds, in the face of international competition.
VETERINARY PARASITOLOGY The definitive reference for identification, diagnosis, and treatment in veterinary parasitology Veterinary Parasitology serves as a comprehensive reference on the subject for both specialists and general practitioners. The fifth edition has undergone significant updates to reflect recent advances in research and medical practice. It has been restructured and now more accessible and user-friendly. For ease of reference, the new edition is divided by parasite taxonomy and host species including dogs and cats, equids, cattle, sheep, ungulates, birds, exotics, and laboratory animals. This important field contributes to protecting animal health and welfare, preventing economic losses, ensuring food safety, safeguarding public health, and is an essential component of the One Health approach. As such, the authors cover all major aspects of veterinary parasitology, including biology, diagnostic techniques, drugs, and effective vaccines. Readers of the fifth edition of Veterinary Parasitology will also find: Detailed new contents on the biological life cycles of parasites Video-based practical guides to the diagnosis in veterinary parasitology, New figures and images to facilitate the reader experience Modification of taxonomic names based on molecular advances Coverage of new approaches to control and distribution of parasites. Parasites constitute some of the most common cases in veterinary medicine and Veterinary Parasitology is the ideal reference for students and practitioners seeking an easy-to-use listing of all parasites of importance in veterinary practice. It will also appeal to veterinary parasitology specialists and researchers.
Domenico Ghirlandaio was one of the most popular artists in fifteenth-century Florence. He worked in a variety of media, including panel paintings, wall murals, mosaic, and manuscript illumination, and his workshop - to which Michelangelo was apprenticed - was highly influential. This beautiful book offers a radically new interpretation of Ghirlandaio’s life and work, viewing him primarily as an artisan active within the craft traditions, guild structure, and workshop organizations of his day. Jean K. Cadogan argues that Ghirlandaio was a pivotal figure in the transformation of the artist from medieval artisan to Renaissance genius. She traces his gradual social elevation, which reflected the increasing respect with which he was treated by his patrons. And she notes that the changes in the way he and other artists were viewed created a milieu that encouraged innovation in technique, style, and content, qualities that were vividly displayed in Ghirlandaio’s work. Cadogan explains how his working method, his pragmatic, artisan approach to technique, the organization and functioning of his workshop, and his relations with his patrons affected the works of art Ghirlandaio produced. Her text is complemented by a catalogue raisonné of Ghirlandaio’s works in all media as well as an appendix of documents useful for scholars.
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. - Introduces data analysis techniques and cloud computing concepts - Describes cloud-based models and systems for Big Data analytics - Provides examples of the state-of-the-art in cloud data analysis - Explains how to develop large-scale data mining applications on clouds - Outlines the main research trends in the area of scalable Big Data analysis
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.
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented. The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics. Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.
Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happening in the world of big data and digital innovation and to understand these impacts on our minds and relationships between people, traceability and the computability of behavior of individuals and social organizations.This book analyses contemporary and future issues related to big data, algorithms, data analysis, artificial intelligence and the internet. It introduces and discusses relationships between digital technologies and power, the role of the pervasive algorithms in our life and the risk of technological alienation, the relationships between the use of big data, the privacy of citizens and the exercise of democracy, the techniques of artificial intelligence and their impact on the labor world, the Industry 4.0 at the time of the Internet of Things, social media, open data and public innovation.Each chapter raises a set of questions and answers to help the reader to know the key issues in the enormous maze that the tools of info-communication have built around us.
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