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Anatomical Imaging : Towards a New Morphology
This book presents selected works of contemporary evolutionary morphologists and includes such topics as broad scale reconstructions of the brain and ear of dinosaurs, inference of locomotor habits from cancellous bone architecture in fossil primates, and a comparison of the independently evolved manipulating apparatuses in the lesser and giant pandas. Insight is provided into the application of modern noninvasive technologies, including digital imaging techniques and virtual 3D reconstruction, to the investigation of complex anatomical features and coherences. In combination with traditional methods, this allows for the formulation of improved hypotheses on coordinated function and evolution. The creation of virtual translucent specimens makes it possible to realize the age-old dream of the classical anatomists: looking through the skin into the inner organization of an organism. On full display here is the dramatic and promising impact that modern imaging techniques have on scientific progress in evolutionary morphology.
Basic Python for Data Management, Finance, and Marketing : Advance Your Career by Learning the Most Powerful Analytical Tool
Learn how to gather, manipulate, and analyze data with Python. This book is a practical guide to help you get started with Python from ground zero and to the point where you can use coding for everyday tasks. Python is used in all aspects of financial industry, from algo trading, reporting and risk management to building valuations models and predictive machine learning programs. You will: Get started with Python from square one / Extend what's possible on excel with Python / Automate tasks with Python / Analyze data more precisely
Adaptive-robust control with limited knowledge on systems dynamics : An artificial input delay approach and beyond
investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler–Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data
