Search and Classification Using Multiple Autonomous Vehicles

Presenting the established principles underpinning space robotics (conservation of momentum and energy, stability) with a thorough and modern approach, chapters build from general physical foundations through an extensive treatment of kinematics of multi-body systems, and then to conservation principles in dynamics. The latter part of the book focuses on real-life applications related to space systems. Drawing upon years of practical experience and using numerous solved examples, illustrative applications and MATLAB, the author includes: an explanation of basic space mechanics and the dynamics of space vehicles; a rigorous treatment of conservation and variational principles in dynamics and in control theory that can be applied to a range of space vehicles and robotic systems; and a systematic presentation of the application of dynamics and control theory to real spacecraft systems.

Modern videography provides an ever-widening window into subsea echinoderm life with vast potential for new knowledge. Supported by video evidence throughout, this Element begins with time-lapse video made in 1983 on film, using an off-the-shelf camera, flash, and underwater housings. Although quality has now been significantly improved by digital imagery, films from over thirty years ago captured crinoid feeding behavior previously unknown and demonstrated a great potential to learn about many other aspects of their biology. This sequence is followed by several examples of recent digital videography from submersibles of deep-sea crinoids and remotely operated vehicles (ROVs) (stalked and unstalked), as well as close-up video of crinoids in aquaria. These recent studies enabled a new classification of crinoid arm postures, provided detailed views of food particle capture, and revealed a wide range of behaviors in taxa never before seen in life.

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are

This essential book describes the mathematical formulations and subsequent computer simulations required to accurately project the trajectory of spacecraft and rockets in space, using the formalism of optimal control for minimum-time transfer in general elliptic orbit. The material will aid research students in aerospace engineering, as well as practitioners in the field of spaceflight dynamics, in developing simulation software to carry out trade studies useful in vehicle and mission design. It will teach readers to develop flight software for operational applications in autonomous mode, so to actually transfer space vehicles from one orbit to another. The practical, real-life applications discussed will give readers a clear understanding of the mathematics of orbit transfer, allow them to develop their own operational software to fly missions, and to use the contents as a research tool to carry out even more complex analyses.

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.