Diode Laser‐Based Sensors for Extreme Harsh Environment Data Acquisition

The world has witnessed several step changes in living standards, productivity, growth, and innovation. We are currently witnessing a convergence of intelligent devices, intelligent networks, and intelligent decision making. Obtaining long‐term accurate, in situ, and real time data from the machines is necessary for enabling the industrial Internet. This relies heavily on sensor systems. Development of robust sensors that can operate reliably in extreme environments will make it possible to gather data from previously inaccessible locations in the equipment. This will enable machine operators to monitor and optimize the performance of their machines. Diode laser‐based diagnostics technology has found applications in a variety of areas and a versatile range of operating conditions. It has proven to be a strong and reliable technique for remote measurements of concentrations and temperatures in harsh environments. Some of the major challenges for implementation of these sensors in real world are machine vibrations, window clogging, cooling, etc. In this chapter, the authors discuss about the application details and specific technologies suitable for the applications. Few case studies are considered, and the theoretical approach, algorithm development, and experimental validation are also discussed

Data governance through a multi-DLT architecture in view of the GDPR

The centralization of control over the processing of personal data threatens the privacy of individuals due to the lack of transparency and the obstruction of easy access to their data. Individuals need the tools to effectively exercise their rights, enshrined in regulations such as the European Union General Data Protection Regulation (GDPR). Having direct control over the flow of their personal data would not only favor their privacy but also a “data altruism”, as supported by the new European proposal for a Data Governance Act. In this work, we propose a multi-layered architecture for the management of personal information based on the use of distributed ledger technologies (DLTs). After an in-depth analysis of the tensions between the GDPR and DLTs, we propose the following components: (1) a personal data storage based on a (possibly decentralized) file storage (DFS) to guarantee data sovereignty to individuals, confidentiality and data portability; (2) a DLT-based authorization system to control access to data through two distributed mechanisms, i.e. secret sharing (SS) and threshold proxy re-encryption (TPRE); (3) an audit system based on a second DLT. Furthermore, we provide a prototype implementation built upon an Ethereum private blockchain, InterPlanetary File System (IPFS) and Sia and we evaluate its performance in terms of response time

Internet of Things (IoT) for Automated and Smart Applications

Internet of Things (IoT) is a recent technology paradigm that creates a global network of machines and devices that are capable of communicating with each other. Security cameras, sensors, vehicles, buildings, and software are examples of devices that can exchange data between each other. IoT is recognized as one of the most important areas of future technologies and is gaining vast recognition in a wide range of applications and fields related to smart homes and cities, military, education, hospitals, homeland security systems, transportation and autonomous connected cars, agriculture, intelligent shopping systems, and other modern technologies. This book explores the most important IoT automated and smart applications to help the reader understand the principle of using IoT in such applications

Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties

The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids

Reactive Power Procurement: Lessons from Three Leading Countries

This paper explores the international experience in the procurement of reactive power and related electricity ancillary services. It involves system operators from different jurisdictions including Australia, the United States and Great Britain. The paper evaluates the different procurement mechanisms and related compensation schemes. In addition, it also appraises a novel approach (from the Power Potential initiative in the UK) for contracting reactive power services from distributed energy resources (DERs) using a market-based mechanism. The conceptual auction design applicable to the procurement of reactive power is also discussed. Our findings suggest that competition in reactive power is very limited in comparison with other ancillary services such as frequency regulation and capacity reserves. The introduction of more market oriented mechanisms for acquiring reactive and active power services by the system operator opens new opportunities and new ways to deal with voltage stability issues. Power Potential trails a technical and commercial solution, new market roles and the new interactions required in the introduction of a competitive reactive power market

A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Modeling, Simulation and Optimization of Wind Farms and Hybrid Systems

The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems