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Intelligent Data Mining in Law Enforcement Analytics
This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.
Artificial Adaptive Systems Using Auto Contractive Maps
This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.
Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection
This two-volume set LNCS 11196 and LNCS 11197 constitutes the refereed proceedings of the 7th International Conference on Digital Heritage, EuroMed 2018, held in Nicosia, Cyprus, in October/November 2018. The 21 full papers, 47 project papers, and 29 short papers presented were carefully reviewed and selected from 537 submissions. The papers are organized in topical sections on 3D Digitalization, Reconstruction, Modeling, and HBIM; Innovative Technologies in Digital Cultural Heritage; Digital Cultural Heritage –Smart Technologies; The New Era of Museums and Exhibitions; Digital Cultural Heritage Infrastructure; Non Destructive Techniques in Cultural Heritage Conservation; E-Humanities; Reconstructing the Past; Visualization, VR and AR Methods and Applications; Digital Applications for Materials Preservation in Cultural Heritage; and Digital Cultural Heritage Learning and Experiences.
Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics a...
CyberResearch on the Ancient Near East and Neighboring Regions
CyberResearch on the Ancient Near East and Neighboring Regions is now available on PaperHive! PaperHive is a new free web service that offers a platform to authors and readers to collaborate and discuss, using already published research. Please visit the platform to join the conversation. CyberResearch on the Ancient Near East and Neighboring Regions provides case studies on archaeology, objects, cuneiform texts, and online publishing, digital archiving, and preservation. Eleven chapters present a rich array of material, spanning the fifth through the first millennium BCE, from Anatolia, the Levant, Mesopotamia, and Iran. Customized cyber- and general glossaries support readers who lack either a technical background or familiarity with the ancient cultures. Edited by Vanessa Bigot Juloux, Amy Rebecca Gansell, and Alessandro Di Ludovico, this volume is dedicated to broadening the understanding and accessibility of digital humanities tools, methodologies, and results to Ancient Near Eastern Studies. Ultimately, this book provides a model for introducing cyber-studies to the mainstream of humanities research.
Chemical Health Threats
This book examines the European guidelines for the risk assessment and management of serious international public health threats.
Artificial Adaptive Systems in Medicine
"New Theories and Models for New Applications - This Ebook covers the emerging and most important theories underlying artificial intelligence applications in a variety of medical problems. It is written for physicians, researchers, engineers, statisticians"
Archeologia e Calcolatori, Supplemento 6, 2014. ARCHEOSEMA. Artificial Adaptive Systems for the Analysis of Complex Phenomena. Collected Papers in Honour of David Leonard Clarke
ARCHEOSEMA, a meta-disciplinary project of theoretical, analytical and experimental archaeology, has been recently awarded by La Sapienza University of Rome. The project title is an acronym which sums up its two main theoretical foundations: the openness of modern archaeology (ARCHEO) to the analysis of physical, historical, linguistic signs (SEMA) underlying natural and cultural systems reconstructed and simulated through Artificial Sciences. This volume edited by Marco Ramazzotti, a Supplement to «Archeologia e Calcolatori», is a Special Issue dedicated to the memory of the English archaeologist David Leonard Clarke (1937-1976), and is a further attempt to collect some applicative studies of complex natural and cultural phenomena following the Artificial Intelligence computational models through the lens of Analytical Archaeology.
