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The Data Renaissance: Analyzing the Disciplinary Effects of Big Data, Artificial Intelligence, and Beyond [Revised Edition]
J.J. Sylvia IV · ROTEL · 2024
The Data Renaissance delves into the complexities of data's role in various industries and its broader impact on society. It highlights the challenges in investigating data practices, citing examples like TikTok, where algorithms and data handling are closely guarded secrets. The content, contributed by students under the guidance of an expert, covers a wide range of topics, including the ethical aspects of generative AI in education and the workplace, and case studies reflecting real-world experiences. This evolving text, intended to be updated with each class, serves as a dynamic resource for educators and students alike, offering insights and discussion guides for an in-depth understanding of the ever-changing landscape of data in our digital age.
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Dynamic data processing: Recursive least-squares
Peter Teunissen · TU Delft Open · 2024
This book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters. When determining time-varying parameters from sequentially collected measurement data, one can discriminate between three types of estimation problems: filtering, prediction and smoothing. Filtering aims at the determination of current parameter values, while smoothing and prediction aim at the determination of respectively past and future parameter values. The emphasis in this book will be on recursive least-squares filtering. The theory is worked out for the important case of linear(ized) models. The measurement-update and time-update equations of recursive least-squares are discussed in detail. Models with sequentially collected data, but time-invariant parameters are treated first. In this case only the measurement-update equations apply. State-space models for dynamic systems are discussed so as to include time-varying parameters. This includes their linearization and the construction of the state transition matrix. Elements from the theory of random fun
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Conducting Mixed-Methods Research: From Classical Social Sciences to the Age of Big Data and Analytics
Viswanath Venkatesh; Susan (Sue) Brown; Yulia Sullivan · Virginia Tech Libraries · 2023
Scholars in the social sciences are increasingly expected to incorporate both quantitative and qualitative techniques and methods into their research. The growth of “mixed-methods” research is evident in social science disciplines ranging from psychology and management to marketing and information systems. This book is designed to provide principles, strategies, and guidance specifically for researchers in these disciplines so that they can use mixed-methods research more effectively. In thirteen chapters, Conducting Mixed-Methods Research takes readers through the research process, from defining research questions to writing articles using a mixed-methods approach. For those who are well trained in either qualitative or quantitative methods, the book shows them how to think about the purposes of mixed-methods research, design mixed-methods studies, and develop meta-inferences by integrating findings from both methods. Throughout, the discussion is grounded in examples taken from published research, carefully chosen to highlight best practices, thus opening a window into a broad body of mixed-methods research applications.
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Unmanned Aircraft Systems in the Cyber Domain
Randall Nichols; Hans Mumm; Wayne Lonstein · New Prairie Press · 2019
Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions.