The studies in this volume share a focus on religion in the ancient Mediterranean world: How ritual, myth, spectatorship, and travel reflect the continual interaction of human beings with the richly fictive beings who defined the boundaries of groups, access to the past, and mobility across land and seascapes. They share as well the methodological exploration of the intersection between human sciencesthe integration of numerous disciplines around the study of all aspects of human life from the biological to the culturaland the study of the past. In so doing, they continue a long dialogue that engages with critical models derived from specializations within history, philology, archaeology, sociology, and anthropology, and addresses, increasingly, the potentialities and pitfalls of quantitative and digital analyses. Many of the threads in this long conversation inform these chapters: the comparative project, human social evolution, disciplinary reflexivity, religion as an embedded, functional, and structural system, and the role for agency, networks, and materiality.

This book uses ancient souvenirs and memorabilia to reveal the experiences, interests, imaginations, and aspirations of ordinary ancient Romans.

This volume illustrates how the epigraphic habit is ubiquitous but variously expressed. Inscriptions become part of the fabric of Greek and Roman culture.

Traces the story of how ancient cultures envisioned artificial life, automata, self-moving devices and human enhancements, sharing insights into how the mythologies of the past related to and shaped ancient machine innovations.

This volume brings together scholars in religion, archaeology, philology, and history to explore case studies and theoretical models of converging religions. The twenty-four essays offered in this volume, which derive from Hittite, Cilician, Lydian, Phoenician, Greek, and Roman cultural settings, focus on encounters at the boundaries of cultures, landscapes, chronologies, social class and status, the imaginary, and the materially operative. Broad patterns ultimately emerge that reach across these boundaries, and suggest the state of the question on the study of convergence, and the potential fruitfulness for comparative and interdisciplinary studies as models continue to evolve.

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.