ALBERT

Description: Discusses the ramifications from a privacy and network security point of view given today's systems that offer access to huge amounts of data and database systems. These information and data sharing interactions capture varied aspects of our lives, such as our shopping behavior, our mental and physical health, our likes and dislikes, political and religious opinions, products we shop for, how we drive our cars, how much energy we use, and even more nebulous things such as our hopes and aspirations. Credit card companies record every purchase we make, with the time and place of purchase; companies like Amazon and Netflix not only record our purchases but also our interest in things we merely peruse on their websites. Loyalty cards and digital profiles of our purchases even in brick-and mortar stores such as Target and Walmart and our local supermarkets create a record of all our purchases, easily being able to infer our shopping patterns.

Description: In various disciplines, information about the same phenomenon can be acquired from different types of detectors, at different conditions, in multiple experiments or subjects, among others. We use the term “modality” for each such acquisition framework. Due to the rich characteristics of natural phenomena, it is rare that a single modality provides complete knowledge of the phenomenon of interest. The increasing availability of several modalities reporting on the same system introduces new degrees of freedom, which raise questions beyond those related to exploiting each modality separately. As we argue, many of these questions, or “challenges,” are common to multiple domains. This paper deals with two key issues: “why we need data fusion” and “how we perform it.” The first issue is motivated by numerous examples in science and technology, followed by a mathematical framework that showcases some of the benefits that data fusion provides. In order to address the second issue, “diversity” is introduced as a key concept, and a number of data-driven solutions based on matrix and tensor decompositions are discussed, emphasizing how they account for diversity across the data sets. The aim of this paper is to provide the reader, regardless of his or her community of origin, with a taste of the vastness of the field, the prospects, and the opportunities that it holds.

Description: Multimodal data are ubiquitous in engineering, communications, robotics, computer vision, or more generally speaking in industry and the sciences. All disciplines have developed their respective sets of analytic tools to fuse the information that is available in all measured modalities. In this paper, we provide a review of classical as well as recent machine learning methods (specifically factor models) for fusing information from functional neuroimaging techniques such as: LFP, EEG, MEG, fNIRS, and fMRI. Early and late fusion scenarios are distinguished, and appropriate factor models for the respective scenarios are presented along with example applications from selected multimodal neuroimaging studies. Further emphasis is given to the interpretability of the resulting model parameters, in particular by highlighting how factor models relate to physical models needed for source localization. The methods we discuss allow for the extraction of information from neural data, which ultimately contributes to 1) better neuroscientific understanding; 2) enhance diagnostic performance; and 3) discover neural signals of interest that correlate maximally with a given cognitive paradigm. While we clearly study the multimodal functional neuroimaging challenge, the discussed machine learning techniques have a wide applicability, i.e., in general data fusion, and may thus be informative to the general interested reader.

Description: This article presents results from the integration of a noncontact physiological radar monitoring system (PRMS) with a type I polysomnography (PSG) system to perform sleep monitoring. The PRMS system consists of two continuous-wave Doppler radars operating at the industrial, scientific, and medical (ISM) band of 2.45 GHz. The system can acquire data, perform digital processing, and output appropriate conventional analog outputs with a latency of approximately 130 ms, which can be recorded and displayed by a gold standard sleep monitoring system along with other standard sensor measurements. Radar data was also used to successfully detect paradoxical motion that was simulated using linear movers and to categorize normal breathing, apnea, and hypopnea in sleeping subjects with obstructive sleep apnea (OSA).

Description: A quantitative and explicit validation of the performance and safety of microwave systems and devices that have electromagnetic interaction with the human body is critical in the technological development process. Although a numerical model of the system environment can be ideally simulated, it cannot reflect the realistic environment that is vulnerable to various electrical, mechanical, and environmental interferences. Hence, the presence of the human body is the best measurement environment for these systems. However, newly designed devices/ systems that rely on the human body electromagnetic field interactions require multiple tests/measurements under a controlled environment. This environment is needed to validate the performance in all the possible scenarios of operation and make sure of the safety of those devices and systems. For example, a breast imaging system needs to be evaluated by detecting tumors in multiple locations, and it is unthinkable to do that on a real patient; hence, breast phantoms are needed to obtain an optimum system design and algorithms before moving to human clinical trials. Moreover, some experiments, such as the specific absorption rate (SAR) and hyperthermia, cannot be done on human beings due to the need to monitor the variation of the power intensity and temperature inside tissues. Employing live human participants for testing devices exposes the entire test procedure to several inherent uncertainties, such as respiratory movement, cardiovascular vibration, and variable skin humidity in addition, of course, to the safety concern of the new devices. Also, the application of the devices and systems on human subjects or human-related materials is a serious ethical issue where the researchers must receive an ethical clearance from the proper authorities, and it can be difficult to reasonably estimate and investigate the level of risks from various scientific, physical, and psychological aspects beforehand. Thus, the utilization of ar- ificial tissue-emulating (ATE) phantoms is highly beneficial for testing a device or system.

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Description: In this article, the author reflects upon both the both the brilliance and limits of Moore's Law on its 50th anniversary.

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Description: Recent information-theoretic results on a class of broadcast channels with layered decoding and/or layered secrecy are reviewed. In this class of models, a transmitter sends multiple messages to a set of legitimate receivers in the presence of a set of eavesdroppers, whose channels can be ordered based on the quality of received signals. Receivers with better channel quality are required to decode more messages, and eavesdroppers with worse channel quality are required to be kept ignorant of more messages. The design of achievable schemes and the characterization of the corresponding secrecy capacity regions are presented. Comparison of the designs for different models is discussed. Applications of these information-theoretic models to the study of secure communication over fading wiretap channels and secret sharing are also presented to illustrate potential applications of these models.

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Description: The Internet of Things (IoT) will feature pervasive sensing and control capabilities via a massive deployment of machine-type communication (MTC) devices. The limited hardware, low-complexity, and severe energy constraints of MTC devices present unique communication and security challenges. As a result, robust physical-layer security methods that can supplement or even replace lightweight cryptographic protocols are appealing solutions. In this paper, we present an overview of low-complexity physical-layer security schemes that are suitable for the IoT. A local IoT deployment is modeled as a composition of multiple sensor and data subnetworks, with uplink communications from sensors to controllers, and downlink communications from controllers to actuators. The state of the art in physical-layer security for sensor networks is reviewed, followed by an overview of communication network security techniques. We then pinpoint the most energy-efficient and low-complexity security techniques that are best suited for IoT sensing applications. This is followed by a discussion of candidate low-complexity schemes for communication security, such as on–off switching and space-time block codes. The paper concludes by discussing open research issues and avenues for further work, especially the need for a theoretically well-founded and holistic approach for incorporating complexity constraints in physical-layer security designs.

Description: When the control functions of various types of power electronics systems are examined, a significant degree of common functionality emerges, irrespective of the target application. It is possible to define hierarchical control architectures for these systems using common interface definitions between control system divisions or layers. Such definitions enable the use of common designs for multiple applications and the use of commercially available electronics and communications modules allowing cost reduction in power electronics applications. This paper presents various partitioning strategies of a hierarchical control architecture for use in high power electronics control systems and defines various parameters/functions that need to be handled within each layer, and those that need to be communicated between the layers. Each layer has characteristic processing and communication speed requirements, irrespective of the final applications.

Description: Three motors that were developed for icebreakers epitomize the history of electric propulsion motor development in Japan. Direct current (dc) motors were developed for Fuji , commissioned in 1965, and Shirase I , commissioned in 1982, and induction motors were developed for Shirase II , commissioned in 2009. Three separate groups in Japan are actively developing superconducting motors for marine propulsion. The Tokyo University of Marine Science and Technology group developed the world’s first axial-gap coreless high-temperature superconducting motor (HTS) with a 100-kW output for a liquid neon thermosiphon cooled superconducting machine over a period from 2004 to 2007. The IHI Corporation group has developed four types of axial-type HTS motors since 2004. Using a cooling system based on liquid nitrogen, they achieved the world’s highest output at 365 kW in 2007. The Kawasaki Heavy Industries group has been developing radial-type HTS motors since 2007. In 2010, the group developed a 1-MW motor that achieved an output of 450 kW. In 2013, the group also developed a 3-MW motor that achieved an output of 3 MW. Furthermore, the group has developed key hardware technologies for a 20-MW motor.

Description: Presents the 2015 author/subject index for this publication.

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Description: Selection of power and propulsion system architecture is one of the most far-reaching and irreversible decisions made by the designer of a modern ship. However, most texts and design handbooks pay little attention to the implications of this design decision nor is sufficient attention paid to the attributes of the various alternatives available to the ship designer/owner. Integrated power systems, made possible over the past three decades by the advances in modern high-power power electronics, provide many benefits to the ship owner, including reduced operating costs, arrangement flexibility, superior reliability and survivability, and support for advanced weapons on sensors warships. This paper will outline the architecture options available to today’s ship designer and will discuss the design implications and pitfalls inherent in the power system architecture selection, paying particular attention to the unique aspects of integrated power systems.

Description: Both the brain and digital computers process information, but they do this in completely different ways. Neurons in the brain transmit information not through bits, but through spikes. Spikes are short voltage increases that are generated near the cell body of a neuron, with average spike rates below 10 Hz. These spikes are transmitted via fine axonal fibers and synapses to about 10 000 other neurons. Neurons also differ in another fundamental aspect from processors in a digital computer: they produce spikes according to stochastic rather than deterministic rules. This article discusses recent progress in understanding how complex computations can be carried out with such stochastically spiking neurons. Other recent developments suggest that spike-based neural networks can be emulated by neuromorphic hardware at a fraction of the energy consumed by current digital computing hardware. Can both developments be merged to provide a blueprint for substantially more energy-efficient computing devices? Explores these issues and examines the viability of such a merger.

Description: This paper presents an overview of the development and present state of the art of hybrid propulsion drive systems as applied to high-performance naval combatants. Motivations for implementing hybrid electric drive architectures are reviewed including potential benefits in term of fuel savings/reduced emissions and additional power generation capacity. Both back-fit into existing propulsion and power generation architectures as well as forward-fit are discussed. Issues associated with coupling the mechanical drive train and electric power generation system together are reviewed.

Description: Electric propulsion has emerged as one of the most efficient propulsion arrangements for several vessel types over the last decades. Even though examples can be found in the history at the end of 19th century, and further into the 20th century, the modern use of electric propulsion started in the 1980s along with the development of semiconductor switching devices to be used in high power drives (dc drives and later ac-to-ac drives). This development opened up for full rpm control of propellers and thrusters, and thereby enabling a simplification of the mechanical structure. However, the main reason for using electric propulsion in commercial ship applications is the potential for fuel savings compared to equivalent mechanical alternatives, except for icebreakers where the performance of an electric powered propeller is superior to a combustion engine powered propeller. The fuel saving potential lies within the fact that the applicable vessels have a highly varying operation profile and are seldom run at full power. This favors the power plant principle in which electric power can be produced at any time with optimum running of prime movers, e.g., diesel engines, by turning on and off units depending on the power demand for propulsion and other vessel loads. Icebreakers were among the first vessels to take advantage of this technology later followed by cruise vessel, and the offshore drilling vessels operating with dynamic positioning (DP). The converter technology was rapidly developing and soon the dc drives were replaced with ac drives. In the same period electric propulsion emerged as basic standard for large cruise liners, and DP operated drilling vessels, but also found its way into other segments as shuttle tankers, ferries, and other special vessels. At the same time podded propulsion were introduced, where the electric motor was mounted directly on the propeller shaft in a submerged 360 $^{circ}$ steerable pod, adding better efficiency, improved maneuvering, and reduced installation space/cost to the benefits of electric propulsion. The future trends are now focusing on further optimization of efficiency by allowing multiple energy sources, independent operation of individual power producers, and energy storage for various applications, such as power back up, peak shaving, or emission free operation (short voyages).

Description: Modern technology combined with the desire to minimize the size and weight of a ship's power system are leading to renewed interest in more electric or all-electric ships. An important characteristic of the emerging ship power system is an increasing level of load variability, with some future pulsed loads requiring peak power in excess of the available steady-state power. This inevitably leads to the need for some additional energy storage beyond that inherent in the fuel. With the current and evolving technology, it appears that storage will be in the form of batteries, rotating machines, and capacitors. All of these are in use on ships today and all have enjoyed significant technological improvements over the last decade. Moreover, all are expected to be further enhanced by today's materials research. A key benefit of storage is that, when it can be justified for a given load, it can have additional beneficial uses such as ride-through capability to restart a gas turbine if there is an unanticipated power loss; alternatively, storage can be used to stabilize the power grid when switching large loads. Knowing when to stage gas turbine utilization versus energy storage is a key subject in this article. The clear need for storage has raised the opportunity to design a comprehensive storage system, sometimes called an energy magazine, that can combine intermittent generation as well as any or all of the other storage technologies to provide a smaller, lighter and better performing system than would individual storage solutions for each potential application.

Description: Electric propulsion of ships has experienced steady expansion for several decades. Since the early 20th century, icebreakers have employed the flexibility and easy control of direct current (dc) motors to provide for ship operations that split ice with back and forth motion of the ship. More recently, cruise ships have employed diesel-electric propulsion systems to take advantage of the flexibility of diesel, as opposed to steam engines, and because the electric plant can also be used for hotel loads. Research vessels, ferries, tankers, and special purpose vessels have also taken advantage of increased flexibility and fuel efficiency with electric propulsion. Today, the U.S. Navy is building an “all electric” destroyer to be named “Zumwalt,” which employs two induction motors for propulsion. There are several different classes of motors that might be considered for use in ship propulsion, ranging from dc (commutator) motors through conventional induction and synchronous motors to permanent magnet synchronous machines, doubly fed machines and superconducting alternating current (ac) and acyclic homopolar machines. This review paper describes features of some of the major classes of motor that might be used in ship propulsion.

Description: This contribution starts with a review of the state of the art of existing high-voltage shore connection (HVSC) systems in terms of principles, rules, publications, technologies, and relevant installations. Then, tutorial sections present the main technical aspects of HVSC systems as ship-to-shore interface, shore equipment (transformers, converters, etc.), onboard devices (cubicles, shore switchboard, etc.), operating sequences, and feasibility aspects, for both commercial and military applications. Finally, some technical challenges are presented, concerning intentional/unintentional bonding, interactions between HVSC bonding and cathodic protection systems, bonding opportunity, and electrical safety aspects related to bonding issues in case of large earth fault currents in port facilities.

Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.

Description: While electric propulsion for warships has existed for nearly a century, it has only been since the end of the Cold War that modern integrated power systems have been developed and implemented on U.S. Navy warships. The principal enablers have been the products of research and development for rotating machines (generators and propulsion motors), power electronics (power conversion and motor drives), energy storage, and controls. The U.S. Navy has implemented this advanced technology incrementally. Notably, DDG 1000 with its integrated propulsion system and CVN 78 with its electromagnetic aircraft launch system will soon join the fleet and mark another important advance to the electric warship. In the future, the integration of electric weapons such as railguns, high power radars, and lasers will result in the final achievement of the electric warship.

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Description: The concept of an all-electric ship, while offering unprecedented advantages from the point of view of efficiency and flexibility of operation, has introduced new challenges in terms of stability and power flow control. The advent of a full power electronics power system has raised new questions from the point of view of system dynamics, particularly when dealing with the new medium-voltage direct current distribution. The overall goal of guaranteeing a secure operation of the power system has brought researchers to consider two main approaches: reducing the dynamics of the large load to operate in a range of dynamics compatible with traditional generation systems, or making the generator set smarter through its power electronics interface. This paper compares these approaches to stable operation, focusing on the latter considered more in line with the progress of technology and in general more appealing.

Description: Presents the front cover for this issue of the publication.

Description: Examines the development of marine vehicle power systems from an historical perspective. from the earliest forms of power systems to the current development of all electric ship technologies.

Description: Presents the 2015 author/subject index for this publication.

Description: The articles in this special issue focus on brain-computer interfacing. The papers are dedicated to this growing and diversifying research enterprise, and features important review articles as well as some important current examples of research in this area. The field of brain-computer interface (BCI) research began to develop about 25 years ago and transformed from initially isolated demonstrations by a few groups into a large scientific enterprise that is currently producing hundreds of peer-reviewed articles and several dedicated conferences and workshops each year. This level of productivity is reflective of the large and continually growing enthusiasm by the scientific community, funding agencies, and the public.

Description: Electrification has been one of the greatest engineering achievements in human history. In spite of the fantastic progress in all areas of electrotechnology, a large section of humanity has limited access to electricity, and some do not have any access to it at all. Fifteen years into the 21st century, it is hard to imagine that more than 1.2 billion people around the world have never been touched by the electric grid and another 3 billion people have intermittent or limited grid connectivity. Life and economic activity in large areas of the developing world remain unchanged, as access to reliable electricity is key to participate in and enjoy the benefits of modern conveniences.

Description: Brain-computer interfaces (BCIs) have been explored in the field of neuroengineering to investigate how the brain can use these systems to control external devices. We review the principles and approaches we have taken to develop a sensorimotor rhythm electroencephalography (EEG)-based brain-computer interface (BCI). The methods include developing BCI systems incorporating the control of physical devices to increase user engagement, improving BCI systems by inversely mapping scalp-recorded EEG signals to the cortical source domain, integrating BCI with noninvasive neuromodulation strategies to improve learning, and incorporating mind-body awareness training to enhance BCI learning and performance. The challenges and merits of these strategies are discussed, together with recent findings. Our work indicates that the sensorimotor-rhythm-based noninvasive BCI has the potential to provide communication and control capabilities as an alternative to physiological motor pathways.

Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.

Description: Brain–computer interfaces (BCIs) are successfully used in scientific, therapeutic and other applications. Remaining challenges are among others a low signal-to-noise ratio of neural signals, lack of robustness for decoders in the presence of inter-trial and inter-subject variability, time constraints on the calibration phase and the use of BCIs outside a controlled lab environment. Recent advances in BCI research addressed these issues by novel combinations of complementary analysis as well as recording techniques, so called hybrid BCIs . In this paper, we review a number of data fusion techniques for BCI along with hybrid methods for BCI that have recently emerged. Our focus will be on sensorimotor rhythm-based BCIs. We will give an overview of the three main lines of research in this area, integration of complementary features of neural activation, integration of multiple previous sessions and of multiple subjects, and show how these techniques can be used to enhance modern BCI systems.

Description: One of the major limitations of brain–computer interfaces (BCI) is their long calibration time, which limits their use in practice, both by patients and healthy users alike. Such long calibration times are due to the large between-user variability and thus to the need to collect numerous training electroencephalography (EEG) trials for the machine learning algorithms used in BCI design. In this paper, we first survey existing approaches to reduce or suppress calibration time, these approaches being notably based on regularization, user-to-user transfer, semi-supervised learning and a priori physiological information. We then propose new tools to reduce BCI calibration time. In particular, we propose to generate artificial EEG trials from the few EEG trials initially available, in order to augment the training set size. These artificial EEG trials are obtained by relevant combinations and distortions of the original trials available. We propose three different methods to do so. We also propose a new, fast and simple approach to perform user-to-user transfer for BCI. Finally, we study and compare offline different approaches, both old and new ones, on the data of 50 users from three different BCI data sets. This enables us to identify guidelines about how to reduce or suppress calibration time for BCI.

Description: This paper presents an important step forward towards increasing the independence of people with severe motor disabilities, by using brain–computer interfaces to harness the power of the Internet of Things. We analyze the stability of brain signals as end-users with motor disabilities progress from performing simple standard on-screen training tasks to interacting with real devices in the real world. Furthermore, we demonstrate how the concept of shared control—which interprets the user's commands in context—empowers users to perform rather complex tasks without a high workload. We present the results of nine end-users with motor disabilities who were able to complete navigation tasks with a telepresence robot successfully in a remote environment (in some cases in a different country) that they had never previously visited. Moreover, these end-users achieved similar levels of performance to a control group of 10 healthy users who were already familiar with the environment.

Description: In their early days, brain–computer interfaces (BCIs) were only considered as control channel for end users with severe motor impairments such as people in the locked-in state. But, thanks to the multidisciplinary progress achieved over the last decade, the range of BCI applications has been substantially enlarged. Indeed, today BCI technology cannot only translate brain signals directly into control signals, but also can combine such kind of artificial output with a natural muscle-based output. Thus, the integration of multiple biological signals for real-time interaction holds the promise to enhance a much larger population than originally thought end users with preserved residual functions who could benefit from new generations of assistive technologies. A BCI system that combines a BCI with other physiological or technical signals is known as hybrid BCI (hBCI). In this work, we review the work of a large scale integrated project funded by the European commission which was dedicated to develop practical hybrid BCIs and introduce them in various fields of applications. This article presents an hBCI framework, which was used in studies with nonimpaired as well as end users with motor impairments.

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Description: Current rehabilitation therapies for stroke rely on physical practice (PP) by the patients. Motor imagery (MI), the imagination of movements without physical action, presents an alternate neurorehabilitation for stroke patients without relying on residue movements. However, MI is an endogenous mental process that is not physically observable. Recently, advances in brain–computer interface (BCI) technology have enabled the objective detection of MI that spearheaded this alternate neurorehabilitation for stroke. In this review, we present two strategies of using BCI for neurorehabilitation after stroke: detecting MI to trigger a feedback, and detecting MI with a robot to provide concomitant MI and PP. We also present three randomized control trials that employed these two strategies for upper limb rehabilitation. A total of 125 chronic stroke patients were screened over six years. The BCI screening revealed that 103 (82%) patients can use electroencephalogram-based BCI, and 75 (60%) performed well with accuracies above 70%. A total of 67 patients were recruited to complete one of the three RCTs ranging from two to six weeks of which 26 patients, who underwent BCI neurorehabilitation that employed these two strategies, had significant motor improvement of 4.5 measured by Fugl-Meyer Motor Assessment of the upper extremity. Hence, the results demonstrate clinical efficacy of using BCI as an alternate neurorehabilitation for stroke.

Description: Presents information on future special issues and sections sections of the Proceedings of the IEEE.

Description: For individuals with high spinal cord injury (SCI), restoring missing grasping function is a high priority. Neuroprostheses based on functional electrical stimulation (FES) can partly compensate the loss of upper extremity function in people suffering from tetraplegia. With noninvasive, multichannel neuroprostheses a pinch and power grasp can be accomplished for everyday use. Hybrid systems combining FES with active orthoses hold promise for restoring a completely lost arm function. Novel control interfaces are needed to make full use of the many degrees of freedom of complex hybrid neuroprostheses. Motor imagery (MI)-based brain–computer interfaces (BCIs) are an emerging technology that may serve as a valuable adjunct to traditional control interfaces for neuroprosthetic control. Shared control and context-specific autonomy are most effective for reducing the users' workload. The modularity of upper extremity neuroprostheses as well as their associated control interfaces enable customization of the systems to adapt to the impairment and needs of each individual end user. This work provides an overview of the application of noninvasive hybrid BCI-controlled upper extremity neuroprostheses in individuals with high SCI with a strong focus on the results from the European Integrated Project Tools for Brain-Computer Interaction and will describe the challenges and promises for the future.

Description: In 1992 Frederik Nebeker of the History Center interviewed Thelma Estrin (1924???2014), first female IEEE vice president and one of the first female Life Fellows. She was noted for her pioneering contributions in the 1960s and 1970s to brain research and biomedical computing. Here Estrin discusses the impact of a strong mother; being one of the first women to pursue an electrical engineering education and profession; her application of computer systems to neuroscientific research; and her efforts to improve society as an administrator. The transcript of this candid interview, in which Estrin recalls many of the people who discriminated against her because of her gender or profession, can be read at http://ethw.org/Oral-History:Thelma_Estrin_(1992).

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Description: Presents the back cover for this issue of the publication.

Description: Provides an overview of the technical articles and features presented in this issue.

Description: This paper presents a comprehensive study on the state-of-the-art and emerging wind energy technologies from the electrical engineering perspective. In an attempt to decrease cost of energy, increase the wind energy conversion efficiency, reliability, power density, and comply with the stringent grid codes, the electric generators and power electronic converters have emerged in a rigorous manner. From the market based survey, the most successful generator-converter configurations are addressed along with few promising topologies available in the literature. The back-to-back connected converters, passive generator-side converters, converters for multiphase generators, and converters without intermediate dc-link are investigated for high-power wind energy conversion systems (WECS), and presented in low and medium voltage category. The onshore and offshore wind farm configurations are analyzed with respect to the series/parallel connection of wind turbine ac/dc output terminals, and high voltage ac/dc transmission. The fault-ride through compliance methods used in the induction and synchronous generator based WECS are also discussed. The past, present and future trends in megawatt WECS are reviewed in terms of mechanical and electrical technologies, integration to power systems, and control theory. The important survey results, and technical merits and demerits of various WECS electrical systems are summarized by tables. The list of current and future wind turbines are also provided along with technical details.

Description: This paper begins with a brief overview of how digital rights management (DRM) technologies are being used to limit consumer rights. Next we show how this code is combined with a legal component, including the use of contractual agreements, to further narrow user rights. Providing a summary of the legal history, we build up to the current legal environment surrounding DRM in the United States, showing the need for DRM policy and coding changes to better balance the interests of copyright holders and the public.

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Description: Leaky waves have been among the most active areas of research in microwave engineering over the second half of the 20th century. They have been shown to dominate the near-field of several open wave-guiding structures, of great interest to tailor their radiation, guidance and filtering properties. The elegant theoretical analyses and deep physical insights in this area, developed in an era in which computational resources were limited, represent a fundamental scientific legacy that is still extremely relevant in today's engineering society and beyond. In this regard, the relevance of leaky-wave concepts has been increasingly recognized in recent times over a broader scientific community, including optics and physics societies. In this paper, after revisiting the fundamental concepts of leaky-wave theory, we discuss and connect different relevant research activities in which leaky-wave concepts have been applied, with the goal of facilitating multidisciplinary interactions on these topics. In addition to the canonical microwave applications of leaky waves, particular attention is devoted to a few areas of interest in modern optics, such as directive optical antennas, extraordinary optical transmission, and embedded scattering eigenvalues, in which leaky waves play a fundamental role.

Description: Information security has emerged as an important system and application metric. Classical security solutions use algorithmic mechanisms that address a small subset of emerging security requirements, often at high-energy and performance overhead. Further, emerging side-channel and physical attacks can compromise classical security solutions. Hardware security solutions overcome many of these limitations with less energy and performance overhead. Nanoelectronics-based hardware security preserves these advantages while enabling conceptually new security primitives and applications. This tutorial paper shows how one can develop hardware security primitives by exploiting the unique characteristics such as complex device and system models, bidirectional operation, and nonvolatility of emerging nanoelectronic devices. This paper then explains the security capabilities of several emerging nanoelectronic devices: memristors, resistive random-access memory, contact-resistive random-access memory, phase change memories, spin torque-transfer random-access memory, orthogonal spin transfer random access memory, graphene, carbon nanotubes, silicon nanowire field-effect transistors, and nanoelectronic mechanical switches. Further, the paper describes hardware security primitives for authentication, key generation, data encryption, device identification, digital forensics, tamper detection, and thwarting reverse engineering. Finally, the paper summarizes the outstanding challenges in using emerging nanoelectronic devices for security.

Description: This paper proposes a three-tier algorithmic framework as the basis for the flexible design of data-driven structural health monitoring (SHM) systems. The three major functions of the SHM system, including data normalization, feature extraction, and hypothesis testing (HT), are mapped to the three layers of the framework. The first tier of the framework is devoted to data normalization. Machine learning (ML) methods are adopted to normalize available data sets by binning data sets to similar environmental and operational conditions (EOCs) of the system. Specifically, affinity propagation clustering is used to delineate data into groups of similar EOC. Once data are normalized by EOC, the second tier of the framework extracts features from the data to serve as condition parameters (CPs) for damage assessment. To ascertain the health state of the structure, the third tier of the framework is devoted to statistical analysis of the CP through HT. An intrinsic goal of the study is to explore the modularity of the three tier framework as a means of offering SHM system designers opportunity to explore and test different computational block sets at each layer to maximize the detection capability of the SHM system. Various realizations of the three-tier modular framework are presented and applied to acceleration and EOC data collected from an operational 3-kW wind turbine. In total, 354 data sets are collected from the turbine, including tower lateral accelerations in two orthogonal directions at six heights, wind speed and wind direction; 317 of the data sets correspond to the wind turbine in a healthy state and 37 with the wind turbine in a damage state. Using quantitative metrics derived from receiver operating characteristic (ROC) curves, the damage classification capabilities of the framework are validated and shown to accurately identify intentionally introduced damage in the turbine.

Description: Reinforced concrete infrastructure assets built during the last century are required to stay in-service beyond their intended design lives, which requires techniques that allow the effects of deterioration and overloading to be monitored to ensure these assets are still fit for purpose. One such indicator of distress in a reinforced concrete structure is crack movement; models have been proposed that allow the internal stresses within a structure to be estimated if crack width and slip can be measured. This paper introduces a technique that uses digital image correlation (DIC) to measure not only crack width but also crack slip. The effect of curvature on this measurement technique is discussed and a method for minimizing the errors due to curvature is presented. The technique is used to measure crack width and slip in reinforced concrete beams with both small crack slip and significant crack slip. The results suggest that the technique can be used to measure crack movement in beams once the effects of curvature are accounted for. Future research in this area will focus on development of this technique for use in the field.

Description: Ultrasonic guided waves are an attractive tool for structural health monitoring due to their capability to rapidly assess large regions of a structure. Yet, most guided wave based methods for detecting, locating, and classifying structural damage rely on our ability to accurately predict guided wave behavior. Characterizing and predicting guided wave behavior is difficult, particularly in mechanically complex materials such as fiber-reinforced composites. In this paper, we address this challenge through a sparse wavenumber analysis framework. Sparse wavenumber analysis integrates physics-based models, signal processing algorithms for compressive sensing, and a small number of local measurements to predict global wave behavior. We implement sparse wavenumber analysis for three wave systems: standing waves on a string, Lamb waves in an isotropic plate, and guided waves in a unidirectional, anisotropic plate. Through the use of simulation and experimental data, we show that sparse wavenumber analysis can accurately recover the sparse representations (i.e., the eigenmodes) of each system and then use these representations to predict global wave behavior. For the anisotropic plate, we accurately predict 149765 experimental time-domain measurements from only 36 local measurements.

Description: Guided wave sensors are widely used in a number of industries and have found particular application in the oil and gas industry for the inspection of pipework. Traditionally this type of sensor was used for one-off inspections, but in recent years there has been a move towards permanent installation of the sensor. This has enabled highly repeatable readings of the same section of pipe, potentially allowing improvements in defect detection and classification. This paper proposes a novel approach using independent component analysis to decompose repeat guided wave signals into constituent independent components. This separates the defect from coherent noise caused by changing environmental conditions, improving detectability. This paper demonstrates independent component analysis applied to guided wave signals from a range of industrial inspection scenarios. The analysis is performed on test data from pipe loops that have been subject to multiple temperature cycles both in undamaged and damaged states. In addition to processing data from experimental damaged conditions, simulated damage signals have been added to “undamaged” experimental data, so enabling multiple different damage scenarios to be investigated. The algorithm has also been used to process guided wave signals from finite element simulations of a pipe with distributed shallow general corrosion, within which there is a patch of severe corrosion. In all these scenarios, the independent component analysis algorithm was able to extract the defect signal, rejecting coherent noise.

Description: Integrated structural health monitoring and damage prognosis (SHM-DP) methodologies, coupled with sensor-based nondestructive evaluation (NDE) techniques, are becoming increasingly important for the near-real-time condition assessment (i.e., SHM) and future performance predictions (i.e., DP) of aging mechanical systems, civil structures, and infrastructure networks, as well as automotive, naval, and aerospace vehicles. A successful SHM-DP strategy, capable of identifying all critical damage mechanisms while accounting for all relevant sources of uncertainty, can be used as an advanced tool to effectively and optimally manage the life-cycle of the monitored system, recursively forecast its remaining useful life (RUL), and ultimately reduce the overall ownership cost through dynamic reliability-based inspection and maintenance (RBIM) plans, system downtime minimization, catastrophic failure prevention, and potential RUL extension. In this perspective, fatigue damage propagation is one of the most critical and unpredictable deterioration processes for a large variety of structural and mechanical systems that are subjected repeatedly to cyclic and/or random operational loading during their service life. Within this limited scope, the authors developed a comprehensive NDE-based SHM-DP framework for recursively predicting the time-varying system reliability and the remaining fatigue life (RFL) of monitored systems subjected to deterioration by multi-site fatigue damage propagation. This paper provides a brief overview of the proposed framework and then uses a set of experimental fatigue test data to perform a thorough statistical performance assessment of the developed methodology at the local reliability component level (i.e., single damage mechanism and single damage location) including NDE detectability and measurement uncertainty as well as both load and model parameter uncertainty.

Description: Accurate and reliable damage characterization (i.e., damage detection, localization, and evaluation of extent) in civil structures and infrastructure is an important objective of structural health monitoring (SHM). Highly accurate and reliable characterization of damage at early stages requires continuous or quasi-continuous direct sensing of the critical parameters. Direct sensing requires deploying dense arrays of sensors, to enhance the probability that damage will result in signals that can be directly acquired by the sensors. However, coverage by dense arrays of sensors over the large areas that are of relevance represents an enormous challenge for current technologies. Large area electronics (LAE) is an emerging technology that can enable the formation of dense sensor arrays spanning large areas (several square meters) on flexible substrates. This paper explores the requirements and technology for a sensing sheet for SHM based on LAE and crystalline silicon CMOS integrated circuits (ICs). The sensing sheet contains a dense array of thin-film full-bridge resistive strain sensors, along with the electronics for strain readout, full-system self-powering, and communication. Research on several stages is presented for translating the sensing sheet to practical SHM applications. This includes experimental characterization of an individual sensor’s response when exposed to cracks in concrete and steel; theoretical and experimental performance evaluation of various geometrical parameters of the sensing sheet; and development of the electronics necessary for sensor readout, power management, and sensor-data communication. The concept of direct sensing has been experimentally validated, and the potential of a sensing sheet to provide direct sensing and successful damage characterization has been evaluated in the laboratory setting. A prototype of the sensing sheet has also been successfully developed and independently characterized in the laboratory, meeting the- required specifications. Thus, a sensing sheet for SHM applications shows promise both in terms of practicality and effectiveness.

Description: Most advanced wireless communication systems use spectrally efficient complex modulation to pack more users into the crowded frequency spectrum. Complex modulation simultaneous modulates a signal's amplitude and phase (polar coordinates) or, equivalently, the I and Q components (rectangular coordinates).

Description: Concrete and other cementitious composites used in civil infrastructure are prone to many forms of damage. For example, cracks could occur and propagate to cause catastrophic component or system-level failure. Therefore, the objective of this study was to nano-engineer a self-sensing cementitious composite that could detect and locate damage. Integration of multi-walled carbon nanotubes (MWNTs) in the mortar mix design and during casting enhanced the electromechanical or sensing properties of the cementitious composites. Instead of directly dispersing MWNTs in the cement matrix, the cement-particle interface was modified using spray-coated MWNT-latex thin films deposited directly onto dry sand particles prior to mortar casting. This procedure preserved MWNT dispersions within the thin film architecture, used minimal amounts of MWNTs, was scalable, and provided dramatic sensing performance enhancements. The mechanical and electromechanical properties of mortar specimens were characterized using compressive cyclic load tests. Furthermore, an electrical resistance tomography (ERT) algorithm was used for mapping mortar specimens' spatial resistance distributions. Since their resistance was precalibrated to strain, localized changes in calculated resistance indicated damage. Spatial damage detection was validated by drilling holes in various locations in cementitious composite plates and then by mapping resistance distributions using ERT.

Description: Wireless sensor nodes (WSNs) are essential elements for today’s structural health monitoring (SHM). As the design technology for WSNs evolves, there have been continuous efforts to address challenges for WSNs such as short lifetime, high power consumption, and bulky volume. Recent trends show energy harvesting becoming a popular solution for extending the lifetime of WSNs; even implementing energy-autonomous systems is an option. Smaller WSN form factors have been developed for volume-limited applications and sensor nodes as small as a few mm $^{3}$ were created with custom-designed integrated circuits (ICs). Custom IC-based sensor nodes enable energy-efficient implementation of WSNs for SHM. Ultralow power circuits with operation power on the order of nanowatts are introduced in this paper. Ultralow power energy harvesters, timers, wakeup receivers, sensing modalities, and microprocessors are expected to significantly extend sensor node lifetime or achieve sensor node operation with ambient energy harvesting.

Description: Many of the algorithms used for structural health monitoring (SHM) are based on, or motivated by, time series analysis. Quite often, detection methods are variants of approaches developed within the statistical process control (SPC) community. Many of the algorithms used represent mature theory and have a rigorous probabilistic or mathematical basis. However, one of the main issues facing SHM practitioners is that the structures of interest rarely respect the assumptions inherent in deriving algorithms. In the case of time series data, SPC-based approaches usually require the data to be stationary and, unfortunately, SHM data are often nonstationary because of benign variations in the environment of the structure of interest, or because of deliberate operational changes in the use of the structure. This nonstationarity can manifest itself as slowly varying trends on the data or in abrupt switches between regimes. Recent work in nonstationary time series methods for SHM has made considerable progress in accommodating nonstationarity and some of that work is discussed within this paper: in terms of understanding slowly varying trends, the cointegration algorithm from econometrics is presented; for understanding abrupt switches, Bayesian mixtures of experts are presented. Another issue in time series analysis is indirectly related to the assumption of linear behavior of structures and the impact of this assumption is briefly considered in terms of its effects on detection thresholds in SPC-like methods; again, progress has been made recently. Some issues still remain, and these are discussed also.