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BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.
In recent years, mathematics has experienced amazing growth in the engineering sciences. Mathematics forms the common foundation of all engineering disciplines. This book provides a comprehensive range of mathematics applied in various fields of engineering for different tasks such as civil engineering, structural engineering, computer science, and electrical engineering, among others. It offers chapters that develop the applications of mathematics in engineering sciences, conveys the innovative research ideas, offers real-world utility of mathematics, and has a significance in the life of academics, practitioners, researchers, and industry leaders. Features Focuses on the latest research in the field of engineering applications Includes recent findings from various institutions Identifies the gaps in the knowledge in the field and provides the latest approaches Presents international studies and findings in modeling and simulation Offers various mathematical tools, techniques, strategies, and methods across different engineering fields
This book constitutes the refereed proceedings of the 7th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2017, held in Vienna, Austria, in November 2017. The 28 revised papers and 8 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: foundation of algorithms in mathematics, engineering and scientific computation; combinatorics and codes in computer science; data modeling and analysis; and mathematical aspects of information security and cryptography.
Faced with the scale and intensity of the ecological crisis, environmental transition is underway, consisting of a first phase of technological mutation, aimed at replacing technologies harmful to the environment with those which have no destructive effects on the earth system and its equilibrium. This book examines the roots of the concept of environmental transition, identifying and characterizing the negative effects of technology on the environmental crisis. We will then identify the technological mutations that have the potential to contribute to environmental transition, and demonstrate how these changes are already forming part of a new emerging "technological system". We will conclude by addressing the question of the limits of technological responses to the environmental crisis, demonstrating the importance of the dimensional factors of human activity and weight of growth in this crisis, thus raising the issue of global reconsideration, with reference to the place and articulation of human activity in the Earth system.
Innovation is an essential growth lever for organizations. Like any strategic element, it must be managed to ensure the right decision is made at the right time. When we talk about management, we naturally also consider management control. However, using management tools can be a danger to developing creativity – an essential element of innovation. This book examines the interdependencies between management control and creativity. By comparing two organizational contexts, we highlight the vital role of organizations as generators of creativity. We also underline the acceptance of an imbalance between the elements in tension, which can lead to the questioning and fostering of innovation; and the role of senior management as mediators between organizations and local actors.
Resilience in healthcare organizations is a complex issue, involving all stakeholders in the healthcare field. It is a highly topical issue, even more so in the wake of the recent health crisis. This book explores the impact of collective intelligence on the resilience of these organizations, and the role played by innovation. Health organizations comprise the structures and systems involved in treating patients, as well as healthcare professionals with medical, social or medico-social expertise, along with institutional and administrative players in the field. Innovation, Collective Intelligence and Resiliency in Healthcare Organizations alternates between theoretical readings and illustrative case studies. Their diversity is the result of their contributors: university researchers, institutional players from healthcare authorities, practicing caregivers in hospital structures or healthcare coordination support systems, and managers of healthcare structures and systems.
Businesses and enterprises can no longer avoid the concern of their Natural Environmental impact, which calls into question their economic activities. Frugal Innovation and Innovative Creation is at the crossroads of economics and management in business, particularly focused on innovative enterprises and their interactions with the Natural Environment. Navigating these interactions can be perceived by companies as a costly constraint, especially in an innovation process, which is already very expensive. The aim of this book is therefore to highlight the need for a satisfactory technology level while innovating, without risking damage to the Natural Environment. The challenge here is to propo...
The book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis and related applications, arising from data science, operations research, engineering, machine learning or statistics. The chapters of this collaborative work represent a cross-section of current research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications. The published data analysis methodology includes the updated state-of-the-art rapidly developed theory and applications of data expansion, both of which go through outstanding changes nowadays. New approaches are expected to deliver and have been developed, including Artificial Intelligence.