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Liquidity, markets and trading in action : An interdisciplinary perspective
This book addresses four standard business school subjects: microeconomics, macroeconomics, finance and information systems as they relate to trading, liquidity, and market structure. It provides a detailed examination of the impact of trading costs and other impediments of trading that the authors call “frictions”. It also presents an interactive simulation model of equity market trading, TraderEx, that enables students to implement trading decisions in different market scenarios and structures. Addressing these topics shines a bright light on how a real-world financial market operates, and the simulation provides students with an experiential learning opportunity that is informative and fun.
Learning Analytics : Using Talent Data to Improve Business Outcomes
Effective evaluation and measurement of learning and development initiatives is critical to maximise the impact of training, identify gaps for improvement and ensure that efforts are aligned to the business' needs. Learning Analytics outlines how analytical approaches can respond to these challenges, the types and benefits of technological solutions and how to ask the right questions of organizational data in order to build a learning organization that boosts performance and competitive advantage.
Knowledge graphs and big data processing
This book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights.
Business statistics : Communicating with numbers
Takes a comprehensive and contemporary approach that aims to bridge the gap between how statistics is taught and applied in the business world. this title not only prepares students in basic statistics but also gets them excited about further exploration of data analytics. the authors emphasize communicating with numbers rather than number crunching, through relatable case studies with relevant statistical methods and takeaways. this title incorporates timely examples from various fields, reinforces core features from previous editions, uses Excel and R to analyze data and solve problems, and includes new improvements, such as a revised chapter on data visualization, an exclusive chapter on logistic regression, and digital enhancements such as a big data capstone project with algorithmic exercises that span across multiple chapt.
Building information modeling : BIM in current and future practice
"Thought leaders from universities and professional practice composed essays exploring BIM's potential to improve the products and processes of architectural design including the structure and content of the tools themselves. These authors provide insights for assessing the current practice and research directions of BIM and speculate about its future. Design Thinking and BIM / BIM Analytics / Comprehensive BIM / Reasoning with BIM / Professional BIM / BIM Speculations"
Biopharmaceutical manufacturing progress, trends and challenges
Source of the latest innovative research and technical development in biomanufacturing systems. It is organised into 2 parts: 1) Manufacturing of recombinant therapeutic proteins (e.g. therapeutic antibodies, biosimilars/biogenerics) and 2) Manufacturing aspects of cell and gene therapy. Each with selected chapters on the following topics for both up- and downstream, such as: Advanced process strategies, especially continuous manufacturing, Advanced culture techniques, especially single-use systems, Process transfer, scale-up/scale-down models, Processing advances/Manufacturing productivity/efficiency, Model-assisted process understanding and development/Digital Twins, Process controls and analytics, Quality control, Quality by design, Facility design and full-scale commercial systems, manufacturing technology innovation.
Biomedical data mining for information retrieval : Methodologies, techniques, and applications
Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.
Bioanalytics : Analytical methods and concepts in biochemistry and molecular biology
Analytical methods are the essential enabling tools of the modern biosciences. This book presents a comprehensive introduction into these analytical methods, including their physical and chemical backgrounds, as well as a discussion of the strengths and weakness of each method. It covers all major techniques for the determination and experimental analysis of biological macromolecules, including proteins, carbohydrates, lipids and nucleic acids.
Big Data in Context : Legal, Social and Technological Insights
Sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.
Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
Big Data : A Road Map for Successful Digital Marketing
Explores recent trends in the use of big data to predict consumer behavior, strategies to engage online customers, integration of big data with other data sources, and its applications in social media analytics, mobile marketing, search engine optimization and customer relationship management.
Big Data – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Artificial intelligence-based Internet of things systems
Discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects. Addresses the complete functional framework workflow in AI-enabled IoT ecosystem; Presents intelligent object identification and object discovery through the IoT ecosystem and its implications to the real world ;Explores security and privacy issues and trustworthy machine learning related to data-intensive technologies in AI-based IoT ecosystems.
Artificial intelligence and machine learning in health care and medical sciences : Best practices and pitfalls
Provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks.
Artificial intelligence and legal analytics : new tools for law practice in the digital age
The field of artificial intelligence (AI) and the law is on the cusp of a revolution. This book - designed to explain computational processes to non-programmers - describes how text analytic programs will change the practice of law, specifically by connecting computational models of legal reasoning directly with legal text.
Approaches to the purification, analysis and characterization of antibody-based therapeutics
Provides the interested and informed reader with an overview of current approaches, strategies and considerations relating to the purification, analytics and characterization of therapeutic antibodies and related molecules. While there are obviously other books published in and around this subject area, they seem to be either older (c.a. year 2000 publication date) or are more limited in scope. The book will include an extensive bibliography of the published literature in the respective areas covered. It is not, however, intended to be a how-to methods book.
Analytics of Protein-DNA Interactions
This book covers trends in modern biotechnology. All aspects of this interdisciplinary technology, where knowledge, methods and expertise are required from chemistry, biochemistry, microbiology, genetics, chemical engineering and computer science, are treated. More information as well as the electronic version is available at springer.com.
Analytical Techniques in Forensic Science
Analytical Techniques in Forensic Science is a comprehensive guide written in accessible terms that examines the interface between analytical chemistry and trace evidence in forensic science. With contributions from noted experts on the topic, the text features a detailed introduction analysis in forensic science and then subsequent chapters explore the laboratory techniques grouped by shared operating principles. For each technique, the authors incorporate specific theory, application to forensic analytics, interpretation, forensic specific developments, and illustrative case studies.
AI in marketing, sales and service : How marketers without a data science degree can use AI, big data and bots
Shows you: how customer and market potential can be automatically identified and profiled; how media planning can be intelligently automated and optimized with AI and Big Data; how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter; how you can optimize Customer Journeys based on Algorithmics and AI; and how to conduct market research in more efficient and smarter way.
AI in learning : Designing the future
AI (artificial intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning.
