Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Adaptive Integrated Circuit Design for Variation Resilience and Security

The past few decades witness the burgeoning development of integrated circuit in terms of process technology scaling. Along with the tremendous benefits coming from the scaling, challenges are also presented in various stages. During the design time, the complexity of developing a circuit with millions to billions of smaller size transistors is extended after the variations are taken into account. The difficulty of analyzing these nondeterministic properties makes the allocation scheme of redundant resource hardly work in a cost-efficient way. Besides fabrication variations, analog circuits are suffered from severe performance degradations owing to their physical attributes which are vulnerable to aging effects. As such, the post-silicon calibration approach gains increasing attentions to compensate the performance mismatch. For the user-end applications, additional system failures result from the pirated and counterfeited devices provided by the untrusted semiconductor supply chain. Again analog circuits show their weakness to this threat due to the shortage of piracy avoidance techniques. In this dissertation, we propose three adaptive integrated circuit designs to overcome these challenges respectively. The first one investigates the variability-aware gate implementation with the consideration of the overhead control of adaptivity assignment. This design improves the variation resilience typically for digital circuits while optimizing the power consumption and timing yield. The second design is implemented as a self-validation system for the calibration of diverse analog circuits. The system is completely integrated on chip to enhance the convenience without external assistance. In the last design, a classic analog component is further studied to establish the configurable locking mechanism for analog circuits. The use of Satisfiability Modulo Theories addresses the difficulty of searching the unique unlocking pattern of non-Boolean variables

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma

Developing preclinical devices for neuroscience research in the fields of animal tracking, fMRI acquisition, and 3D histology cutting

[ES] La neurociencia es un campo que abarca muchas especialidades. El objetivo de esta tesis es subsanar algunas carencias tecnológicas que existen en los métodos actuales de experimentación animal en neurociencia. En esta tesis, se presentan seis proyectos, que tendrán como objetivo mejorar el "Principio de las tres R", el cual fue enunciado por los biólogos ingleses W. M. S. Russell y R. L. Burch, durante la experimentación animal. El comportamiento es uno de los aspectos más importantes de la vida animal. Depende de los vínculos entre los animales, sus sistemas nerviosos y sus entornos. Para estudiar el comportamiento de los animales de laboratorio, se necesitan varias herramientas, pero una herramienta de seguimiento es esencial para llevar a cabo un estudio de comportamiento exhaustivo. Varias herramientas de seguimiento visual están actualmente disponibles. Sin embargo, todas tienen algunos inconvenientes. Por ejemplo, en una situación en la que un animal está dentro de una madriguera o cerca de otros animales, las cámaras de rastreo (tracking) no siempre pueden detectar la ubicación precisa o el movimiento del animal. Por esta razón, los entornos enriquecidos para intentar recrear el hábitat natural de los animales en experimentación no pueden utilizarse, ya que los datos recopilados son insuficientes/inexactos. Con la finalidad de mejorar los experimentos de tracking RFID Assisted Tracking Tile (RATT) es presentado en esta tesis. RATT es un sistema de seguimiento basado en tecnología de identificación pasiva de radiofrecuencia (RFID) y está compuesto por baldosas electrónicas con las que se puede construir una gran superficie, sobre la cual los animales pueden moverse libremente. Esto permite la identificación más precisa de los animales, así como el seguimiento de sus movimientos. Este sistema, que también se puede combinar con un sistema de seguimiento con cámaras, allana el camino para estudios completos de comportamiento en entornos enriquecidos. Dada la capacidad de rastrear animales y, por lo tanto, realizar experimentos de comportamiento exhaustivos, es posible observar cómo se comportan los sujetos desde un punto de vista externo. Sin embargo, si queremos comprender lo que sucede en el cerebro de estos sujetos, es necesario aplicar otras técnicas de análisis, por ejemplo, el estudio de señales dependientes del nivel de oxígeno en la sangre (BOLD, por sus siglas en inglés). Las señales BOLD se basan en las respuestas vasculares a la activación neuronal y se utilizan ampliamente en estudios de investigación clínicos y preclínicos. En entornos preclínicos, los animales suelen ser anestesiados. Sin embargo, los anestésicos causan cambios en la fisiología de los animales, p. Ej. hipotermia, y esto tiene el potencial de alterar las señales funcionales de MRI (fMRI). Para evitar la hipotermia en roedores anestesiados, se presenta TherMouseDuino. Este es un sistema de control automático de temperatura de código abierto, que reduce las fluctuaciones de la temperatura, lo que proporciona condiciones sólidas para realizar experimentos de resonancia magnética funcional. En los cursos de biología y neurociencia, la anatomía del cerebro se enseña generalmente utilizando imágenes de resonancia magnética (IRM) o secciones histológicas de diferentes planos. Estos muestran las áreas macroscópicas más importantes en el cerebro de un animal. Sin embargo, este método no es dinámico ni intuitivo. En esta tesis se presenta un cerebro de rata impreso en 3D con fines educativos. La manipulación manual de la estructura, facilitada por la ampliación de sus dimensiones, junto con la capacidad de desmontar el "cerebro" en algunas de sus partes principales, facilita la comprensión de la organización 3D del sistema nervioso. Este es un método alternativo y mejorado para enseñar a los estudiantes en general y a los biólogos, en particular, la anatomía del cerebro de rata.[CA] La neurociència és un camp que abasta moltes especialitats. L'objectiu d'aquesta tesi és esmenar algunes manques tecnològiques que existeixen en els mètodes actuals d'experimentació animal en neurociència. En aquesta tesi, es presenten sis projectes, que tindran com a objectiu millorar el "Principi de les tres R", el qual va ser enunciat pels biòlegs anglesos W. M. S. Russell i R. L. Burch, durant l'experimentació animal. El comportament és un dels aspectes m'és importants de la vida animal. Depèn dels vincles entre els animals, els seus sistemes nerviosos i els seus entorns. Per estudiar el comportament dels animals de laboratori, es necessiten diverses eines, però` una eina de seguiment és essencial per a dur a terme un estudi de comportament exhaustiu. Diverses eines de seguiment visual estan actualment disponibles. No obstant això, totes tenen alguns inconvenients. Per exemple, en una situació en la qual un animal esta` dins d'un cau o prop d'altres animals, les cambres de rastreig (tracking) no sempre poden detectar la ubicació precisa o el moviment de l'animal. Per aquesta raó, els entorns enriquits per a intentar recrear l'hàbitat natural dels animals en experimentació no poden utilitzar-se, ja que les dades recopilades són insuficients/inexactes. Amb la finalitat de millorar els experiments de tracking/seguiment RFID Assisted Tracking Tile (RATT) és presentat en aquesta tesi. RATT es un sistema de seguiment basat en tecnologia d'identificació passiva de radiofreqüència (RFID) i esta` compost per rajoles electròniques amb les quals es pot construir una gran superfície, sobre la qual els animals poden moures lliurement. Això permet la identificació més precisa dels animals, així com el seguiment dels seus moviments. Aquest sistema, que també es pot combinar amb un sistema de seguiment amb cambres, aplana el camí per a estudis complets de comportament en entorns enriquits. Donada la capacitat de rastrejar animals i, per tant, realitzar experiments de comportament exhaustius, és possible observar com es comporten els subjectes des d'un punt de vista extern. No obstant això, si volem comprendre el que succeeix en el cervell d'aquests subjectes, és necessari aplicar altres tècniques d'anàlisis, per exemple, l'estudi de senyals dependents del nivell d'oxigen en la sang (BOLD, per les seues sigles en anglès). Els senyals BOLD es basen en les respostes vasculars a l'activació neuronal i s'utilitzen àmpliament en estudis d'investigació clínics i preclínics. En entorns preclínics, els animals solen ser anestesiats. No obstant això, els anestèsics causen canvis en la fisiologia de els animals, per exemple hipotèrmia, i això te el potencial d'alterar els senyals funcionals de MRI (fMRI). Per a evitar la hipotèrmia en rosegadors anestesiats, es presenta TherMouseDuino. Aquest és un sistema de control automàtic de temperatura de codi obert, que redueix les fluctuacions de la temperatura, la qual cosa proporciona condicions solides per a realitzar experiments de ressonància magnètica funcional. En els cursos de biologia i neurociència, l'anatomia del cervell s'ensenya generalment utilitzant imatges de ressonància magnètica (IRM) o seccions histològiques de diferents plans. Aquests mostren les àrees macroscòpiques més importants en el cervell de un animal. No obstant això, aquest mètode no és dinàmic ni intuïtiu. En aquesta tesi es presenta un cervell de rata imprès en 3D amb finalitats educatius. La manipulació manual de l'estructura, facilitada per l'ampliació de les seues dimensions, juntament amb la capacitat de desmuntar el "cervell" en algunes de les seues parts principals, facilita la comprensió de l'organització 3D del sistema nerviós. Aquest és un mètode alternatiu i millorat per a ensenyar a els estudiants en general i als biòlegs, en particular, l'anatomia del cervell de rata.[EN] Neuroscience is a field that covers many specialties. The objective of this thesis is to correct some technological deficiencies that exist in current methods of animal experimentation in neuroscience. In this thesis, six projects are presented, which will aim to improve the "Principle of the three Rs" in animal experimentation enunciated by the English biologists W. M. S. Russell and R. L. Burch. In the present era of impressive progress in neuroscience, it is still not arguable that a complete understanding of the brain cannot be possible without a comparable understanding of animal behavior. In order to study the behavior of laboratory animals, various tools are needed, being a reliable tracking system one of the most important to follow large populations of individual subjects that interact in complex manners. Several visual tracking tools are currently available. However, they all have some drawbacks. For example, in a situation where an animal is inside a cave, or is in close proximity to other animals, tracking cameras cannot always detect the precise location or movement of the animal. For this reason, environments that have been enriched in order to attempt to recreate the natural habitat of the animals under experiment, cannot be used, as the data gathered is insufficient/inaccurate. In order to improve the current tracking systems , the RATT is presented. RATT is a tracking system based on passive RFID technology and it is composed of electronic tiles. Using several tiles, a large surface area, on which the animals can move freely, can be built. This enables the more accurate identification of the animals, as well as the tracking of their movements. This system, which can also be combined with a visual tracking system, paves the way for complete behavioral studies in enriched environments. Given the ability to track animals and thus conduct thorough behavioral experiments, it is possible to observe how the subjects behave from an external viewpoint. However, if we want to understand what is going on in the brains of these subjects, it is necessary to apply other analysis techniques, for example the study of BOLD signals. BOLD signals are based on vascular responses to neuronal activation and are used extensively in clinical and preclinical research studies. In preclinical settings, animals are usually anesthetized. However, anesthetics cause changes in the physiology of the animals, e.g. hypothermia, and this has the potential to disrupt fMRI signals. In order to avoid hypothermia in anesthetized rodents, TherMouseDuino is presented. This is an Open-Source automatic temperature control system, which reduces temperature fluctuations, thus providing robust conditions in which to perform fMRI experiments. In biology and neuroscience courses, brain anatomy is generally taught using MRI or histological sections of different planes. These show the most important macroscopic areas in an animals' brain. However, this method is neither dynamic nor intuitive. An anatomical 3D printed rat brain with educative purposes is presented in this thesis. Hand manipulation of the structure, facilitated by the scaling up of its dimensions, together with the ability to dismantle the "brain" into some of main its constituent parts, facilitates the understanding of the 3D organization of the nervous system. This is an alternative and improved method for teaching students in general and biologists, in particular, the rat brain anatomy.This work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R (D.M.) and BFU2015-64380-C2-1-R, by EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowledges financial support from the Spanish State Research Agency, through the “Severo Ochoa” Programme for Centres of Excellence in R&D (ref. SEV-2013-0317) and by a grant “Ayudas para la formación de personal investigador (FPI)” from the Vicerrectorado de Investigación, Innovación y Transferencia of the Universitat Politècnica de València.Quiñones Colomer, DR. (2019). Developing preclinical devices for neuroscience research in the fields of animal tracking, fMRI acquisition, and 3D histology cutting [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118795TESI

Investigation into Detection of Hardware Trojans on Printed Circuit Boards

The modern semiconductor device manufacturing flow is becoming increasingly vulnerable to malicious implants called Hardware Trojans (HT). With HTs becoming stealthier, a need for more accurate and efficient detection methods is becoming increasingly crucial at both Integrated Circuit (IC) and Printed Circuit Board (PCB) levels. While HT detection at an IC level has been widely studied, there is still very limited research on detecting and preventing HTs implanted on PCBs. In recent years the rise of outsourcing design and fabrication of electronics, including PCBs, to third parties has dramatically increased the possibility of malicious alteration and consequently the security risk for systems incorporating PCBs. Providing mechanical support for the electrical interconnections between different components, PCBs are an important part of electronic systems. Modern, complex and highly integrated designs may contain up to thirty layers, with concealed micro-vias and embedded passive components. An adversary can aim to modify the PCB design by tampering the copper interconnections or inserting extra components in an internal layer of a multi-layer board. Similar to its IC counterpart, a PCB HT can, among other things, cause system failure or leakage of private information. The disruptive actions of a carefully designed HT attack can have catastrophic implications and should therefore be taken seriously by industry, academia and the government. This thesis gives an account of work carried out in three projects concerned with HT detection on a PCB. In the first contribution a power analysis method is proposed for detecting HT components, implanted on the surface or otherwise, consuming power from the power distribution network. The assumption is that any HT device actively tampering or eavesdropping on the signals in the PCB circuit will consume electrical power. Harvesting this side-channel effect and observing the fluctuations of power consumption on the PCB power distribution network enables evincing the HT. Using a purpose-built PCB prototype, an experimental setup is developed for verification of the methodology. The results confirm the ability to detect alien components on a PCB without interference with its main functionality. In the second contribution the monitoring methodology is further developed by applying machine learning (ML) techniques to detect stealthier HTs, consuming power from I/O ports of legitimate ICs on the PCB. Two algorithms, One-Class Support Vector Machine (SVM) and Local Outlier Factor (LOF), are implemented on the legitimate power consumption data harvested experimentally from the PCB prototype. Simulation results are validated through real-life measurements and experiments are carried out on the prototype PCB. For validation of the ML classification models, one hundred categories of HTs are modelled and inserted into the datasets. Simulation results show that using the proposed methodology an HT can be detected with high prediction accuracy (F1-score at 99% for a 15 mW HT). Further, the developed ML model is uploaded to the prototype PCB for experimental validation. The results show consistency between simulations and experiments, with an average discrepancy of ±5.9% observed between One-Class SVM simulations and real-life experiments. The machine learning models developed for HT detection are low-cost in terms of memory (around 27 KB). In the third contribution an automated visual inspection methodology is proposed for detecting HTs on the surface of a PCB. It is based on a combination of conventional computer vision techniques and a dual tower Siamese Neural Network (SNN), modelled in a three stage pipeline. In the interest of making the proposed methodology broadly applicable a particular emphasis is made on the imaging modality of choice, whereby a regular digital optical camera is chosen. The dataset of PCB images is developed in a controlled environment of a photographic tent. The novelty in this work is that, instead of a generic production fault detection, the algorithm is optimised and trained specifically for implanted HT component detection on a PCB, be it active or passive. The proposed HT detection methodology is trained and tested with three groups of HTs, categorised based on their surface area, ranging from 4 mm² to 280 mm² and above. The results show that it is possible to reach effective detection accuracy of 95.1% for HTs as small as 4 mm². In case of HTs with surface area larger than 280 mm² the detection accuracy is around 96.1%, while the average performance across all HT groups is 95.6%

Advanced Radio Frequency Identification Design and Applications

Radio Frequency Identification (RFID) is a modern wireless data transmission and reception technique for applications including automatic identification, asset tracking and security surveillance. This book focuses on the advances in RFID tag antenna and ASIC design, novel chipless RFID tag design, security protocol enhancements along with some novel applications of RFID

Cyber Security and Critical Infrastructures 2nd Volume

The second volume of the book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles, including an editorial that explains the current challenges, innovative solutions and real-world experiences that include critical infrastructure and 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems

Air Force Institute of Technology Research Report 2020

This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Demand Response in Smart Grids

The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer