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This book constitutes the proceedings of the 23rd International Conference on Formal Methods for Industrial Critical Systems, FMICS 2018, held in Maynooth, Ireland, in September 2018. The 9 regular papers presented in this volume were carefully reviewed and selected from 17 submissions. The book also contains two invited talks in full-paper length. In addition, there are 8 invited contributions in honor of Susanne Graf (Director of Research at VERIMAG Grenoble, France) on the occasion of her 60th birthday. The aim of the FMICS conference series is to provide a forum for researchers who are interested in the development and application of formal methods in industry. In particular, FMICS brings together scientists and engineers who are active in the area of formal methods and interested in exchanging their experiences in the industrial usage of these methods. The FMICS conference series also strives to promote research and development for the improvement of formal methods and tools for industrial applications.
This vital new Handbook clarifies how qualitative research can be undertaken in the discipline of Information Systems (IS), observing how IS can be taught and its recent developments. Through succinctly bringing together influential research, it extensively surveys contemporary trends in qualitative IS studies.
With the emergence of smart technology and automated systems in today’s world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications. Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.