Hierarchical Agent-based Adaptation for Self-Aware Embedded Computing Systems

Siirretty Doriast

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

Applications in Electronics Pervading Industry, Environment and Society

This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

INTER-ENG 2020

These proceedings contain research papers that were accepted for presentation at the 14th International Conference Inter-Eng 2020 ,Interdisciplinarity in Engineering, which was held on 8–9 October 2020, in Târgu Mureș, Romania. It is a leading international professional and scientific forum for engineers and scientists to present research works, contributions, and recent developments, as well as current practices in engineering, which is falling into a tradition of important scientific events occurring at Faculty of Engineering and Information Technology in the George Emil Palade University of Medicine, Pharmacy Science, and Technology of Târgu Mures, Romania. The Inter-Eng conference started from the observation that in the 21st century, the era of high technology, without new approaches in research, we cannot speak of a harmonious society. The theme of the conference, proposing a new approach related to Industry 4.0, was the development of a new generation of smart factories based on the manufacturing and assembly process digitalization, related to advanced manufacturing technology, lean manufacturing, sustainable manufacturing, additive manufacturing, and manufacturing tools and equipment. The conference slogan was “Europe’s future is digital: a broad vision of the Industry 4.0 concept beyond direct manufacturing in the company”

Producció científica de l'ETSEIB a Futur. Articles de revista i publicacions a congressos dels investigadors de l'ETSEIB durant l'any 2019

Postprint (author's final draft

Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on the Energy Internet, blockchain technology and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Artificial Neural Networks in Agriculture

Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible