This book focuses on distributed event-triggered control of multi-agent systems, in which the event-triggering mechanism is utilized to reduce the communication frequencies in order to compensate for constrained network bandwidths, an aspect that poses significant challenges for distributed control design. The book summarizes the authors’ original, systematic contributions on scalability and robustness, two core issues in distributed event-triggered control. Specifically, the book presents...

This book offers a comprehensive overview of using artificial intelligence and quantitative approaches in many phases of flight safety management, from proactive assessment of potential risks of flights before taking-off to automatic analysis of occurred flight events, for commercial airlines. Flight safety is commonly the core values of airlines. Serious flight disasters always bring tremendous impacts and losses to the industry and the society; thus, airlines and the authorities always t...

In this volume, Prof. Ye and his coworkers propose and review the concept of nano-bio probe design for biochemical analysis on the basis of their recent published works. A unique biochemical analysis technology based on fluorescence polarization enhanced by nanoparticles is described here with successful applications in environmental monitoring, rapid and sensitive sensing protease activity and high-throughput screening of inhibitors. Furthermore, they introduce a versatile molecular beaco...

This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-com...

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded wit...

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based...

This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including g...

"Drone Systems and Operations""Drone Systems and Operations" provides a comprehensive and forward-thinking exploration of unmanned aerial vehicles (UAVs), laying out the foundational architectures and design principles that power today's advanced drone fleets. Targeted at engineers, researchers, and industry professionals, the book systematically covers the classification of UAV platforms, intricate avionics and propulsion subsystem design, reliability engineering, and the intricat...

This book is a foundational guide to graph representation learning, including state-of-the art advances, and introduces the highly successful graph neural network (GNN) formalism.Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind ...

A perennial bestseller, the Digital Avionics Handbook offers a comprehensive view of avionics. Complete with case studies of avionics architectures as well as examples of modern systems flying on current military and civil aircraft, this Third Edition includes:Ten brand-new chapters covering new topics and emerging trendsSignificant restructuring to deliver a more coherent and cohesive storyUpdates to all existing chapters...

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic.The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions.T...

Pressing On is an exploration of an aviation safety problem that has plagued commercial airline operators for years. Recent airline accidents like Asiana 214 at the San Francisco International Airport (see cover image) provide examples of this phenomenon, when pilots continue an unstable approach to a landing attempt. The risk of collision with terrain and/or a runway excursion has been identified by both governmental regulators and airlines alike, yet this risk to a catastrophe c...