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Intelligent Algorithms for Packing and Cutting Problem
Introduces intelligent solving algorithms for classical packing and cutting problem and their variants / Investigates novel methods, e.g. reinforcement learning algorithms, for rectangular and irregular packing problems / Presents practical engineering application cases in combination of theory and practice / investigates in detail the two-dimensional packing and cutting problems in the field of operations research and management science. It introduces the mathematical models and intelligent solving algorithms for these problems, as well as their engineering applications. Most intelligent methods reported in this book have already been applied in reality, which can provide reference for the engineers. The presented novel methods for the two-dimensional packing problem provide a new way to solve the problem for researchers interested in operations research or computer science. This book also introduces three new variants of packing problems and their solving methods, which offer a different research direction.
Integrated diagnostics and theranostics of thyroid diseases
Provides basic concepts on Integrated Diagnostics and Theranostics with special emphasis on different human thyroid diseases. Thyroid diseases are increasingly detected (incidentally in many cases) but are clinically negligible in a significant proportion of patients. Accordingly, it is urgent to move from the simple disease detection to a reliable disease characterization in order to concentrate efforts on patients in need of tailored disease management.
Information Management and Big Data ; 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings
This book constitutes the refereed proceedings of the 7th International Conference on Information Management and Big Data, SIMBig 2020, held in Lima, Peru, in October 2020.* The 32 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 122 submissions. The papers address topics such as natural language processing and text mining; machine learning; image processing; social networks; data-driven software engineering; graph mining; and Semantic Web, repositories, and visualization.
Information and communication technologies in tourism 2022 ; Proceedings of the ENTER 2022 eTourism Conference, January 11-14, 2022
The book provides an extensive overview of how information and communication technologies can be used to develop tourism and hospitality. It covers the latest research on various topics within the field, including augmented and virtual reality, website development, social media use, e-learning, big data, analytics, and recommendation systems. The readers will gain insights and ideas on how information and communication technologies can be used in tourism and hospitality.
Informatics in the Future ; Proceedings of the 11th European Computer Science Summit (ECSS 2015), Vienna, October 2015
This volume discusses the prospects and evolution of informatics (or computer science), which has become the operating system of our world, and is today seen as the science of the information society. Its artifacts change the world and its methods have an impact on how we think about and perceive the world. Classical computer science is built on the notion of an “abstract” machine, which can be instantiated by software to any concrete problem-solving machine, changing its behavior in response to external and internal states, allowing for self-reflective and “intelligent” behavior. However, current phenomena such as the Web, cyber physical systems or the Internet of Things show us that we might already have gone beyond this idea, exemplifying a metamorphosis from a stand-alone calculator to the global operating system of our society.
Industry 4.0 for SMEs : Challenges, opportunities and requirements
This book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies.
Hybrid Artificial Intelligent Systems ; 15th International Conference, HAIS 2020, Gijón, Spain, November 11-13, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2020, held in Gijón, Spain, in November 2020. The 65 regular papers presented in this book were carefully reviewed and selected from 106 submissions. The papers are grouped into these topics: advanced data processing and visualization techniques; bio-inspired models and optimization; learning algorithms; data mining, knowledge discovery and big data; and hybrid artificial intelligence applications.
How Data Quality Affects our Understanding of the Earnings Distribution
This book demonstrates how data quality issues affect all surveys and proposes methods that can be utilised to deal with the observable components of survey error in a statistically sound manner. This book begins by profiling the post-Apartheid period in South Africa's history when the sampling frame and survey methodology for household surveys was undergoing periodic changes due to the changing geopolitical landscape in the country. This book profiles how different components of error had disproportionate magnitudes in different survey years, including coverage error, sampling error, nonresponse error, measurement error, processing error and adjustment error.
How and what marketing algorithms think
Argues that the apparent omnipotence of algorithms today is not what it seems, particularly, in marketing, where they actually offer less than they could. Considering the reasons behind this, it also notes that Big Data has relaunched a kind of data glorification and automated procedures that, culturally, marketing has already recognized and overcome at least once.
High-Performance Modelling and Simulation for Big Data Applications: Selected Results of the COST Action IC1406 cHiPSet
This book is the final compendium of case studies emanated from “High-Performance Modelling and Simulation for Big Data Applications” (cHiPSet).cHiPSet has created a sustainable reference network linking applied research in High Performance Computing (HPC) and Modelling & Simulation to tangibly address Big Data challenges.cHiPSet has also endeavoured to use and exploit results through Open Science practices, i.e., open access publication, open access to data repositories, and open-source software development. A testament to this philosophy, this compendium is set to become a required reference for the fast-changing fields of HPC, Big Data, and Modelling & Simulation.
High Performance Computing for Geospatial Applications
This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study.
Heterogeneity, high performance computing, self-organization and the cloud
Addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses.
Healthcare solutions using machine learning and informatics
Covers novel and innovative solutions for the healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, intelligent IoT-based solutions for medical image analysis, medical big data processing, disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare. The book explains fundamental concepts as well as the advanced use cases illustrating how to apply emerging technologies such as machine learning, AI models, data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain
Handbook on artificial intelligence -empowered applied software engineering ; Vol.1 : Novel methodologies to engineering smart software systems
Provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence.
Handbook of smart cities
This Handbook presents a comprehensive and rigorous overview of the state-of-the-art on Smart Cities. It provides the reader with an authoritative, exhaustive one-stop reference on how the field has evolved and where the current and future challenges lie. From the foundations to the many overlapping dimensions (human, energy, technology, data, institutions, ethics etc.)
Handbook of big data analytics ; Vol.2 : Applications in ICT, security and business analytics
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time.
Handbook of big data analytics ; Vol.1 : Methodologies
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. This volume presents several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data.
Global Fintech : Financial Innovation in the Connected World
How the global financial services sector has been transformed by artificial intelligence, data science, and blockchain. Artificial intelligence, big data, blockchain, and other new technologies have upended the global financial services sector, creating opportunities for entrepreneurs and corporate innovators. Venture capitalists have helped to fund this disruption, pouring nearly $500 billion into fintech over the last five years. This book offers global perspectives on technology-fueled transformations in financial services, with contributions from a wide-ranging group of academics, industry professionals, former government officials, and current government advisors. They examine not only the struggles of rich countries to bring the old analog world into the new digital one but also the opportunities for developing countries to “leapfrog” directly into digital.
Future data and security engineering ; 7th International conference, FDSE 2020, Quy Nhon, Vietnam, November 25–27, 2020, Proceedings
This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, which was supposed to be held in Quy Nhon, Vietnam, in November 2020, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers (of 53 accepted full papers) presented together with 2 invited keynotes were carefully reviewed and selected from 161 submissions. The other 29 accepted full and 8 short papers are included in CCIS 1306. The selected papers are organized into the following topical headings: security issues in big data; big data analytics and distributed systems; advances in big data query processing and optimization; blockchain and applications; industry 4.0 and smart city: data analytics and security; advanced studies in machine learning for security; and emerging data management systems and applications.
Future data and security engineering : Big data, security and privacy, smart city and industry 4.0 applications ; 7th International Conference, FDSE 2020, Quy Nhon, Vietnam, November 25–27, 2020, Proceedings
This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, held in Quy Nhon, Vietnam, in November 2020.* The 29 full papers and 8 short were carefully reviewed and selected from 161 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; data analytics and healthcare systems; machine learning-based big data processing; emerging data management systems and applications; and short papers: security and data engineering.
