I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 23 papers covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Internet Technologies,” “Network Security,” “Network Virtualization,” “Optical Communications,” “Vehicular and Sensor Communications,” and “Wireless Communications

Trusted third parties (TTPs) are frequently used for serving as an authority to issue and verify transactions in applications. Although the TTP-based paradigm provides customers with convenience, it causes a whole set of inevitable problems such as security threats, privacy vulnerabilities, and censorship. The TTP-based paradigm is not suitable for all modern networks, e.g., 5G and beyond networks

Online advertising has become the backbone of the Internet economy by revolutionizing business marketing. It provides a simple and efficient way for advertisers to display their advertisements to specific individual users, and over the last couple of years has contributed to an explosion in the income stream for several Web-based businesses. For example, Google’s income from advertising grew 51.6%

Cyber Threat Intelligence (CTI) is threat information intended for security purposes. However, use for incident response demands standardization. This study examines the broader security incident response perspective. Introducing 18 core concepts, we assist efforts to establish and assess current standardization approaches. We further provide the reader with a detailed analysis of 6 incident response

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Human brains can do amazing things with little power consumption. The bigger question is how can we build such machines” [1] .

This issue of IEEE Control Systems includes two features and one “Focus on Education” article. The feature “Neuromorphic Control” draws from the Ph.D. dissertation of my coauthor and former student Luka Ribar. Neuromorphic engineering is a rapidly developing field that takes inspiration from the biological organization of neural systems to develop a novel technology for computing, sensing, and actuating

My colleague John Doyle once said to me, “The gap between theory and practice is a lot bigger in practice than in theory.” In this column, I will share my journey across this gap through entrepreneurship, especially the mistakes I have made, in response to Thomas Parisini’s invitation to share personal experiences on how control theory impacts applications. I do not conduct research to create start-ups

Automatic vehicle following is an important feature of a fully or partially automated highway system (AHS). The on-board vehicle control system should be able to accept and process inputs from the driver, the infrastructure, and other vehicles, perform diagnostics, and provide the appropriate commands to actuators so that the resulting motion of the vehicle is safe and compatible with the AHS objectives

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Reports on news of interest to CSS society members.

Reports on the technical activities of the CS society Technical Committee on Distributed Parameter Systems.

Reports on the technical activities of the CS society Technical Committee on Networks and Communication Systems.

In this issue of IEEE Control Systems , we speak with Giulia Giordano, an assistant professor at the University of Trento, Italy, and Tamer Başar, who is currently a Swanlund Endowed Chair Emeritus and the Center for Advanced Study (CAS) professor emeritus of electrical and computer engineering as well as a research professor at the Coordinated Science Laboratory (CSL) and Information Trust Institute

Q. How did your education and early career lead to your initial and continuing interest in the control field?

Neuromorphic electronic engineering takes inspiration from the biological organization of nervous systems to rethink the technology of computing, sensing, and actuating (see “Summary”). It started three decades ago with the realization by Carver Mead, a pioneer of very large-scale integration (VLSI) technology, that the operation of a conventional transistor in the analog regime closely resembles the

Among the multitude of modern control methods, model predictive control (MPC) is one of the most successful [1] – [4] . As noted in “Summary,” this success is largely due to the ability of MPC to respect constraints on controls and enforce constraints on outputs, both of which are difficult to handle with linear control methods, such as linear quadratic regulator (LQR) and linear quadratic Gaussian

Massive open online courses (MOOCs) have become a recent hotspot in educational research because of their large-scale accessibility, openness, flexibility, and convenience (see “Summary”). They are an effective way to meet the growing demand for education. MOOC platforms have been created around the world, such as Coursera, founded by Stanford University; edX, cofounded by the Massachusetts Institute

This book falls within the category of what has been labeled “advanced mathematics for scientists and engineers” and is written for first-year graduate students of engineering and physical science. It is assumed that the reader has gone through the standard undergraduate courses in calculus, linear algebra, ordinary differential equations, and partial differential equations. Unlike other popular texts

by J. BECHHOEFER

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Really good question. Actually, someone asked me that before, but I never got around to looking into it.

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This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name

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These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

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IEEE Signal Processing Magazine ( SPM ) is a fully edited magazine. This means that, after the review process, the final files provided by the authors are processed by a team of editors under the supervision and the responsibility of the magazine’s managing editor, Jessica Welsh. The contributions of Jessica and the editorial and production teams are very important, since they transform all the final

With the year coming to a close, I couldn’t help but reflect on our experiences in 2020 and 2021. I began my term as president of the IEEE Signal Processing Society (SPS) roughly 65 days before we were told to work from home due to the COVID-19 pandemic. As I write this column 18 months later, I find myself, like many of you, still largely working remotely. During this period, we have learned a great

Researchers in an almost endless number of fields are embracing artificial intelligence (AI) and machine learning (ML) to develop tools and systems that can predict and adapt to a wide range of changing situations, optimize system performance, and intelligently filter signals. In areas as diverse as firefighter protection, solar power optimization, and exoplanet discovery, researchers are turning to

Affective computing is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. Human emotion and affect in general are fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning and communication, but are also fundamental to human health and well-being. The field of affective computing has matured over its

Recent advances in the field of machine learning have shown great potential for the automatic recognition of apparent human emotions. In the era of Internet of Things and big-data processing, where voice-based systems are well established, opportunities to leverage cutting-edge technologies to develop personalized and human-centered services are genuinely real, with a growing demand in many areas such

Speech emotion recognition (SER) is an important research area, with direct impacts in applications of our daily lives, spanning education, health care, security and defense, entertainment, and human–computer interaction. The advances in many other speech signal modeling tasks, such as automatic speech recognition, text-to-speech synthesis, and speaker identification, have led to the current proliferation

Given the increasing prevalence of facial analysis technology, the problem of bias in the tools is now becoming an even greater source of concern. Several studies have highlighted the pervasiveness of such discrimination, and many have sought to address the problem by proposing solutions to mitigate it. Despite this effort, to date, understanding, investigating, and mitigating bias for facial affect

Monitoring physiological changes [e.g., heart rate (HR), respiration, and HR variability (HRV)] is important for measuring human emotions. Physiological responses are more reliable and harder to alter compared to explicit behaviors (such as facial expressions and speech), but they require special contact sensors to obtain. Research in the last decade has shown that photoplethysmography (PPG) signals

Humans are emotional creatures. Multiple modalities are often involved when we express emotions, whether we do so explicitly (such as through facial expression and speech) or implicitly (e.g., via text or images). Enabling machines to have emotional intelligence, i.e., recognizing, interpreting, processing, and simulating emotions, is becoming increasingly important. In this tutorial, we discuss several

This review presents, in a tutorial-like manner, the current state of research in group affects. We focus on the automatic processing of affects and their estimation, which is, of course, based on foundations in social sciences regarding multiple modalities. In addition, we highlight recent developments in methods and classification approaches. Further, a collection of suitable corpora for affect estimation

We provide a psychometric-grounded exposition of bias and fairness as applied to a typical machine learning (ML) pipeline for affective computing (AC). We expand on an interpersonal communication framework to elucidate how to identify sources of bias that may arise in the process of inferring human emotions and other psychological constructs from observed behavior. The various methods and metrics for

Mental health plays a key role in everyone’s day-to-day lives, impacting our thoughts, behaviors, and emotions. Also, over the past years, given their ubiquitous and affordable characteristics, the use of smartphones and wearable devices has grown rapidly and provided support within all aspects of mental health research and care—from screening and diagnosis to treatment and monitoring—and attained

Emotion is one of the main reasons why people engage and interact with music [1] . Songs can express our inner feelings, produce goosebumps, bring us to tears, share an emotional state with a composer or performer, or trigger specific memories. Interest in a deeper understanding of the relationship between music and emotion has motivated researchers from various areas of knowledge for decades [2]

Creating novel interpretations of existing musical compositions is and has always been an essential part of musical practice. Before the advent of recorded music, listening to a piece of music mostly meant listening to a version of it, in many cases, performed by musicians other than the original composer or performer. While this practice, along with musical notation, allows compositions to remain

Two of the most popular denoising algorithms are ℓ 2 and ℓ 1 trend filtering, which are used in science, engineering, and statistical signal and image processing. They are typically treated as separate entities, with the former as a linear time-invariant (LTI) filter, which is commonly used for smoothing the noisy data and detrending the time-series signals, while the latter is a nonlinear filtering

The signal processing and communication communities have witnessed the rise of many exciting communication technologies in recent years. Notable examples include alternative waveforms, massive multiple-input, multiple-output (MIMO) signaling, nonorthogonal multiple access (NOMA), joint communications and sensing, sparse vector coding, index modulation, and so on. It is inevitable that 6G wireless networks

Corrections were made to author information to “Smart home technologies are saving money and lives, [Special Reports] (Edwards, J.) ,” IEEE Signal Process. Mag., vol. 38, no. 5, pp. 8–11, Sept. 2021. doi: 10.1109/MSP.2021.3088401.

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Advertisement: TechRxiv is a free preprint server for unpublished research in electrical engineering, computer science, and related technology. TechRxiv provides researchers the opportunity to share early results of their work ahead of formal peer review and publication. Benefits: Rapidly disseminate your research findings; Gather feedback from fellow researchers; Find potential collaborators in the