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Machine Learning Paradigms
The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification an...
Machine Learning Paradigms
At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book ar...
Modern Technologies for Big Data Classification and Clustering
Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage. Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.
Advances in Assistive Technologies
This book aims at exposing its readers to some of the most significant advances in assistive technologies. Assistive technologies develop devices to assist vulnerable people, including elderly people, people with cognitive disabilities such as memory problems or dementia, and people with functional disabilities such as those needing support in toileting, moving around, eating, bathing, dressing, grooming, and taking personal care. The ever-increasing life expectancy and world population, along with the emergence of new diseases and the regrettable continuation of armed conflicts, press for development and availability of assistive technologies that offer people in need the opportunity to liv...
Knowledge-Based Software Engineering: 2018
This book summarizes the new research results presented at the 12th Joint Conference on Knowledge-Based Software Engineering (JCKBSE 2018), which took place on August 27–30, 2018 on the island of Corfu, Greece. The JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence in Software Engineering. The JCKBSE 2018 was organized by the Department of Informatics of the University of Piraeus, the Department of Computer and Information Engineering of Nippon Institute of Technology, and the Department of Informatics of Ionian University. The book will benefit not only experts and researchers in the field of (Knowledge-Based) Software Engineering, but also general readers in the fields of Artificial Intelligence, Computational Intelligence and Computer Science who wish to learn more about the field of (Knowledge-Based) Software Engineering and its applications. An extensive list of bibliographic references at the end of each paper encourages readers to probe further into the application areas that interest them most.
Machine Learning Paradigms
This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.
Democracia econômica e protagonismo estatal frente aos desafios da Inteligência Artificial
A Inteligência Artificial tem ocupado um espaço na produção de bens e na prestação de serviços que põe em sérios riscos a empregabilidade no mundo todo. Isso porque a tecnologia já disponível pode ser usada para substituir mão de obra humana em diversos setores da economia. Assim como nas revoluções industriais anteriores, essa substituição pode aumentar lucros e reduzir custos, e isso alinha a automação a um princípio básico do funcionamento do mercado capitalista. O objetivo geral da pesquisa que resulta no presente livro, então, foi identificar as ferramentas que o Direito Econômico oferece ao Estado no enfrentamento dos desafios que os processos de substituição de...
Credit Risk Management
Credit Risk Management: Basic Concepts is the first book of a series of three with the objective of providing an overview of all aspects, steps, and issues that should be considered when undertaking credit risk management, including the Basel II Capital Accord, which all major banks must comply with in 2008. The introduction of the recently suggested Basel II Capital Accord has raised many issues and concerns about how to appropriately manage credit risk. Managing credit risk is one of the next big challenges facing financial institutions. The importance and relevance of efficiently managing credit risk is evident from the huge investments that many financial institutions are making in this ...
Self Portrait in Green
'NDiaye is a hypnotic storyteller with an unflinching understanding of the rock-bottom reality of most people's life.' New York Times ' One of France's most exciting prose stylists.' The Guardian. Obsessed by her encounters with the mysterious green women, and haunted by the Garonne River, a nameless narrator seeks them out in La Roele, Paris, Marseille, and Ouagadougou. Each encounter reveals different aspects of the women; real or imagined, dead or alive, seductive or suicidal, driving the narrator deeper into her obsession, in this unsettling exploration of identity, memory and paranoia. Self Portrait in Green is the multi-prize winning, Marie NDiaye's brilliant subversion of the memoir. Written in diary entries, with lyrical prose and dreamlike imagery, we start with and return to the river, which mirrors the narrative by posing more questions than it answers.
Data, Models, and Decisions
Combines topics from two traditionally distinct quantitative subjects, probability/statistics and management science/optimization, in a unified treatment of quantitative methods and models for management. Stresses those fundamental concepts that are most important for the practical analysis of management decisions: modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.
