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"Using sensors, networks, and arduino to see, hear, and feel your world"--Cover.

The workbenches of hobbyists, hackers, and makers have become overrun with microcontrollers, computers-on-a-chip that power homebrewed video games, robots, toys, and more. In Making Things Talk, Tom Igoe, one of the creators of Arduino, shows how to make these gadgets talk.

Igoe Tom: Making Things Talk

Making Things Talk

Using Sensors, Networks, and Arduino to See, Hear, and Feel Your World

Self-contained resource on fundamental concepts and the planning, provisionining, design, and operations of 3GPP-based NTNs 3GPP-based Non-Terrestrial Networks in 5G and 6G: Expanding the Frontiers of Wireless Communications provides an overview of Non-Terrestrial Networks (NTNs) in the context of 3GPP systems such as 4G LTE and 5G NR. Unique challenges of NTNs such as long and variable propagation delays, large and time-varying Doppler shifts, different types of beams including Earth-fixed beams, quasi-Earth-fixed beams, and Earth-moving beams and transparent and regenerative payloads are discussed. The mechanisms that 3GPP foresees to tackle these NTN-specific challenges are described and, furthermore, the planning, provisioning, design, and operations of the radio and core networks for NTNs are illustrated. NTN considerations in the book range from physical-layer aspects (e.g., synchronization, random access, and uplink and downlink data transmission), to mobility management including handover and cell reselection, and to network architecture. Fundamentals of the associated concepts of NR, eMTC (i.e., LTE_M), and NB-IoT are described so that their customizations for NTNs become clear in NTN-specific discussions. NTN features in 3GPP Release 17, 18, and 19 are described andhe role of NTN in 6G is also summarized. A companion website provides exercises to help learners to reinforce concepts, along with software utilities (e.g., Excel spreadsheets) that provide templates to investigate the impact of various factors (e.g., carrier frequency and channel bandwidth) on the performance of NTNs (e.g., coverage and capacity/throughput). 3GPP-based Non-Terrestrial Networks in 5G and 6G includes information on: <ul> <li>Earth-fixed beams, Earth-moving beams, and quasi-Earth-fixed beams, as well as characteristics of Geo Synchronous Orbit (GSO) and Non-GSO (NGSO) satellites such as Low Earth Orbit (LEO) satellites</li> <li>Challenges unique to NTNs including large coverage areas, mobility of cells, and different types of payloads (e.g., transparent and regenerative)</li> <li>Issues surrounding data transfer in NTNs such as time and frequency pre-compensation, timers for different radio protocol stack layers, and HARQ enabling/disabling</li> <li>Random access, RRC connection setup, registration/attach, and PDU session/EPS bearer setup for LTE-M, NB-IoT, and 5G NR</li> </ul> 3GPP-based Non-Terrestrial Networks in 5G and 6G is an essential resource for wireless communications and satellite industry engineers and professionals seeking to facilitate the design, provisioning, deployment, operations, maintenance, and optimization of 5G-based NTNs and identify R&amp;D areas for 5G-advanced-based and 6G-based NTNs.

Expanding the Frontiers of Wireless Communications

Non-Terrestrial Networks in 5G and 6G

Machine Learning For Dummies

Exploring the Wireless Frontier

Wearable Antennas

Automated target tracking is a necessary function of the airborne radar and radio control systems. At the present time, there is no a classified approach to design and construct the principles, functioning features, methods, algorithms and procedures of synthesis and analysis of the airborne radar target tracking systems by the range, velocity and azimuth satisfying all long-term requirements. The present Volume 1 "Air-borne Radar Systems and Single Target Tracking" of the two-volumes book "Target Tracking by Airborne Radar Systems" is intended to cover demands of this uncertainty.<ul> <li>Contains factual information about the current status of the automated airborne radar target tracking systems that is useful to a wide range of expert participants in and out of the uniform, radio engineers, radar engineers and designers, and others.</li> <li>Deals with the several new perspective methods of the synthesis and analysis and designing the air-borne radar target tracking systems</li> <li>Discusses new theoretical approaches to design the airborne radar target tracking systems are in this Volume.</li> <li>Deals with the general theoretical problems of synthesis and analysis of the information-controlled systems based on the modified statistical theory of optimal control and estimation, not only the classical theory.</li> <li>Presents general information about the integrated on-board and control systems and possible ways to improve the airborne radar target tracking system performance.</li> </ul>Additionally, there are a lot of application examples confirming the theoretical results. Under discussion of the specific algorithms of the airborne radar target tracking system operation, a great attention is paid to the methods of synthesis and analysis of the suggested algorithms.The procedure of algorithmic realizations is delivered in detail that will be useful without any doubts for the radio and radar engineers, radar experts, MS and PhD students. A great attention is paid to the design problems of new airborne radar system generation and analysis of operation principles and modes.

Airborne Radar Systems and Single Target Tracking

Target Tracking by Airborne Radar Systems

This unique compendium presents the basics of the theory of computing at a level and in a manner that can be easily understood by computer science students in a large university. It offers the student a firm foundation in logical reasoning and covers many traditional topics in unconventional ways.The useful reference text benefits professionals, academics, researchers and undergraduate students in the area of theoretical computer science.

Foundation Of Computation: Languages And Machines

Previous research on finite/fixed/predefined-time control and its relevant sliding mode structures focus on forcing a system state (vector) to converge within a certain time moment, regardless of how each state element converges. Time-Synchronized Control and Applications for Autonomous Systems introduces a control problem with unique finite/fixed/predefined-time stability considerations, namely time-synchronized stability, where at the same time, all the system state elements converge to the origin. This book also delves into the wide-ranging applications of time-synchronized control in various practical control systems, including but not limited to spacecraft attitude control/tracking, satellite orbit control, dynamic positioning of vessels, cooperative control of autonomous vehicles, etc. In addition, a diverse array of control system models are considered, encompassing disturbed systems, chaotic systems, multi-input multi-output (MIMO) systems, nonlinear systems, and Euler-Lagrange systems. Through an in-depth exploration of these specific cases, this book showcases the versatility and effectiveness of time-synchronized control methods across different domains, providing readers with a comprehensive perspective on their practical utility.

Time-Synchronized Control and Applications for Autonomous Systems

Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource capturing the challenges and mitigation strategies involved in designing such systems. Divided into nine sections, the book covers the most important applications of safety-critical systems, helping readers understand how related problems are being solved in different domains/problem settings. The goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety. The authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models.

A Comprehensive Guide

Artificial Intelligence and Machine Learning for Safety-Critical Systems

Power Electronics and Applications Series

An Introduction

Electric Energy

To write effective code and applications, software engineers and developers have to be able to frame user/customer needs effectively, capture program requirements and use cases, and then develop suitable software architecture and code to meet the need. Code Chronicles: The Art of Storytelling in Software helps readers write better software by teaching readers how to write stories in the context of software development. The book explains the roots of storytelling, clarifies that storytelling historically has been a very powerful tool used to pass along knowledge, presents where storytelling is already present implicitly in software development, discusses how to make it more effective, and finally present experiences in storytelling from software engineering and other scientific disciplines, to foster a full understanding of its power. The authors comprehensively present the pivotal role of storytelling in writing software, and they explain how to do it in a simple, hands-on approach, also taking advantage of clear case studies written by experts in the field.

The Art of Storytelling in Software

Code Chronicles

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

Advances in Computers

Quantum Machine Learning (QML): Platform, Tools and Applications: Volume 140

Comprehensive overview of the principles, theories, and techniques behind deep learning-enabled semantic communications Deep Learning Enabled Semantic Communications explores the synergy between deep learning and semantic communication, particularly in the context of advancing 6G networks. It provides a focused introduction to the subject, systematically covering deep learning-enabled semantic communication systems and task-oriented semantic transmission paradigms in wireless communication. The book reviews various aspects of semantic communications, including information theory, multimodal technologies, semantic noise, and semantic sensing. It explores cutting-edge semantic communication architectures, highlighting their advantages over traditional approaches and their potential to drive the future of intelligent information industry. The book also details applications of deep learning-based semantic communication systems across various sources, including text, speech, images, and videos, comprehensively addressing system design, performance optimization, and measurement metrics. The book is divided into eight main parts, which cover foundational knowledge, system design, multimodal and multitask-oriented semantic communication systems, joint semantic sensing and sampling, semantic noise suppression, and generative AI enabled systems. Written by a diverse group of experts in academia and research institutions, Deep Learning Enabled Semantic Communications includes information on: <ul> <li>Fundamental knowledge about the deep learning and semantic communications, including the history, neural networks, and semantic information theory</li> <li>Compression of multimodal inputs, extraction of global semantic information, and the design of neural networks to boost the capability of handling lengthy speech</li> <li>Incorporation of different sources to extract semantic features and serve diverse intelligent tasks at the receiver</li> <li>Introduction of semantic impairments in communications to uncover how to design robust systems</li> <li>Joint design of data sampling, compression, and coding schemes under the guidance of semantic information</li> <li>Framework of generative semantic communications to detail the principles of incorporating generative models into semantic communications</li> </ul> Deep Learning Enabled Semantic Communications is an essential learning resource and reference for graduate and undergraduate students pursuing degrees in wireless communications, signal processing, or deep learning as well as engineers in the telecommunications and IT industries focusing on wireless communication techniques.

Deep Learning Enabled Semantic Communications

Making Things Talk

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