Assuring Safe Operation of Robotic Systems under Uncertainty: Control and Learning Methods applies set-theoretic and reinforcement learning approaches to formulate, analyze, and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment.The authors adopt learning-supported, set-theoretic methods—specifically, the barrier Lyapunov function and the control barrier function—to achieve desirable robust safety with guaranteed performance in co...

As the media landscape has evolved over the past few years, especially with the emergence of interactive and social media, the philosophy of advertising is significantly changing. Most businesses realize that the days when they relied on three national networks (ABC, NBC, and CBS) and a few national newspapers to advertise are gone; thus, they begin to find alternatives to standardized advertising. Many of them begin to adopt more individualized advertising approaches, empowered by Interne...

An organization can have a high number of «likes» on its Facebook page and lots of «followers» on its Twitter account, but does that mean anything from a financial perspective? Is it worth the organization’s effort to maintain an active presence on social media in order to generate more revenue? Is it possible to use social media metrics such as the number of «likes» and the number of «followers» to predict an organization’s «success» even though those metrics are nonfinancial indicators? ...

This book constitutes the proceedings of the 12th International Conference on Network and System Security, NSS 2018, held in Hong Kong, China, in August 2018.The 26 revised full papers and 9 short papers presented in this book were carefully reviewed and selected from 88 initial submissions. The papers cover a wide range of topics in the field, including blockchain, mobile security, applied cryptography, authentication, biometrics, IoT, privacy, and education.

Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type of optimization problem, and the alternating direction method of multipliers (ADMM) is a commonly used algorithm to solve constrained problems, especially linearly constrained ones. Written by experts in machine learning and optimization, this is the first book providing a state-of-the-art review on ADMM under various scenarios, including deterministic and c...

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning.Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review ...

Food quality analysis is an area of interest that has always attracted the attention of everyone, and making suitable tools for food analysis is especially important. This volume presents such techniques and their state-of-the-art applications. It covers different spectroscopic methods spread over the wide range of electromagnetic spectrum that are being applied in food analysis. Detection of ammonia nitrogen using spectroscopic process is also included as it is the source of protein synth...

Comprehensive review of key topics in root science, including root architecture, root growth regulators, root anatomy and nutrient acquisitionCoverage of root response to both biotic and abiotic variablesDiscusses the range of techniques to optimize root function, from phenotyping to identify desirable root traits and exploiting the genetics of root traits to the use of plant growth-promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AM)

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and l...

This open-access textbook provides a comprehensive, up-to-date guide for students and practitioners wishing to access in a single volume the key disciplines and principles of wheat breeding. Wheat is a cornerstone of food security: it is the most widely grown of any crop and provides 20% of all human calories and protein. The authorship of this book includes world class researchers and breeders whose expertise spans cutting-edge academic science all the way to impacts in farmers’ fields. T...

This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, a...

Drawing on her many years as a consultant to numerous companies big and small, author Rose Hightower infuses Internal Controls Policies and Procedures with her wealth of experience and knowledge. Instead of reinventing the wheel, your company can use this useful how-to manual to quickly and effectively put a successful program of internal controls in place. Complete with flowcharts and checklists, this essential desktop reference is a best practices model for establishing and enha...