85 research outputs found

    Cognitive and Autonomous Software-Defined Open Optical Networks

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Fundamentals

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    Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

    Reconfigurable Varactor-Based Microwave Components for Low-Cost Antenna Array Design: Phase Shifters, Attenuators and Diplexers

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    Phased array antennas are important for advanced wireless communications, providing high directivity and beam steering capabilities. However, conventional phased arrays are expensive, bulky, heavy and power-hungry due to their complex architecture and electronic controls. For systems demanding low cost, light weight, compact size, and low power consumption, reconfigurable antenna arrays can be a practical alternative to traditional phased arrays. Electronically controlled reconfigurable antennas offer the ability to adjust their operating frequency, radiation pattern, polarization, or any combinations of these aspects by using tunable electronic components such as PIN diodes, switches, varactors and/or microelectromechanical systems (MEMS). One way to realize reconfigurable antenna array is to start by designing a reconfigurable feeding network and then co-designing corresponding antenna elements, before combining these two structures to form the whole array based on the system requirements. However, when designing low-cost and compact reconfigurable antenna arrays, several critical aspects should be taken into consideration. Firstly, the reconfigurable feeding network may result in a large number of components and a complex structure, leading to a higher insertion loss and a possible degradation in antenna performance through reduced efficiency. Secondly, if the feeding network is not designed properly, integrating it into the system can lead to a high demand in space, consequently enlarging the overall size, manufacture complexity and cost. In this context, compact, seamlessly-integrable, low-power, low-cost and tunable microwave components are needed to build reconfigurable feeding networks. Through using these feeding networks, low-cost and compact reconfigurable antenna arrays can be realized as alternatives to conventional phased arrays. Varactor-based phase shifters to control the signal phase, reconfigurable attenuators to control the signal magnitude and reconfigurable diplexers to control the signal frequency are essential components to construct these so-called reconfigurable feeding networks. This is in line with the goal of this thesis, which comprises three coherent objectives. Firstly, the dissertation presents a concept of low-cost varactor-based phase shifters, which are operating in differential mode. A phase shifter pair based on this concept is able to supply full- 360◦ phase difference tuning range between its two output ports. The devices can be directly integrated with 50 Ω feed transmission lines, which results in a compact, lowcost and lightweight design of the feeding network and saves space which would be required by conventional phase shifter blocks. Based on such differential phase shifter pairs, a 1×4 linear dielectric resonator antenna array is designed, which is excited by a feeding network comprising 3 phase shifter pairs to control the array scanning sumpattern continuously from -45◦ to 45◦ and the null of a difference pattern from -30◦ to 30◦. A dedicated procedure for accurately calibrating these beam-steerable antennas is also proposed, aiming to provide a general approach to enhance the performance of the reconfigurable feeding network. Secondly, a tunable transmission-type attenuator with easily-extendable and tunable attenuation level, small initial insertion loss, and satisfactorily low reflection coefficient is presented, which is integrated onto a 50 Ω microstrip transmission lines with several side-loaded shorted-end varactorbased stubs. This arrangement allows a compact and low-loss structure, as well as seamless integration with planar transmission lines in microwave circuits, which also makes them suitable for applications with limited real estate. It is proven that a 3-stub attenuator can offer tunable attenuation from 1.0 to 13.5 dB with reflection coefficient lower than -11.4 dB, and that by cascading them a larger attenuation range can be obtained. Thirdly, a frequency-switchable varactor-based diplexer concept is proposed for a low-cost and compact pattern- and frequency-switchable microstrip antenna array. This diplexer concept, which represents an extension in functionality of the differential phase shifter pair, is able to supply different responses to different frequencies in a wide-band range, instead of utilizing the phase difference performance in a narrow operation band. Seamless integration with the feeding network enables a dual-band antenna pair to become a pattern- and frequency-switchable array with unique functionality. All the results presented in this thesis are derived fromvaractor-based microwave components that offer a range of benefits, including low cost, lightweight construction, low power consumption, and a seamless integration topology. All these proposed reconfigurable devices allow construction of reconfigurable feeding networks with phase and magnitude tuning abilities, as well as frequency reconfigurability. This means that antenna arrays fed by this type of feeding networks can achieve versatile and competitive reconfigurability in their radiation performance, while maintaining a compact size, low weight, low power consumption and affordability.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Mechanical Engineering, 202

    Artificial Intelligence Technology

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    This open access book aims to give our readers a basic outline of today’s research and technology developments on artificial intelligence (AI), help them to have a general understanding of this trend, and familiarize them with the current research hotspots, as well as part of the fundamental and common theories and methodologies that are widely accepted in AI research and application. This book is written in comprehensible and plain language, featuring clearly explained theories and concepts and extensive analysis and examples. Some of the traditional findings are skipped in narration on the premise of a relatively comprehensive introduction to the evolution of artificial intelligence technology. The book provides a detailed elaboration of the basic concepts of AI, machine learning, as well as other relevant topics, including deep learning, deep learning framework, Huawei MindSpore AI development framework, Huawei Atlas computing platform, Huawei AI open platform for smart terminals, and Huawei CLOUD Enterprise Intelligence application platform. As the world’s leading provider of ICT (information and communication technology) infrastructure and smart terminals, Huawei’s products range from digital data communication, cyber security, wireless technology, data storage, cloud computing, and smart computing to artificial intelligence

    Data Acquisition Applications

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    Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

    Relaxation pathways for soft materials

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    Optimised task allocation using dynamic production data in human-robot teams

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    The demand of both industrial and consumer customers for increasingly higher degrees of customisation in products will see greater amounts of high mix production in the future of manufacturing. Despite this, automation must be implemented to improve the efficiency and output of manufacturing processes. However, traditional automation methods are often unsuitable due to long lead times for setup and little flexibility to adapt them to new tasks. Human-Robot (HR) teams provide a potential way to implement easily reconfigurable automation into future factories by utilising the best characteristics of human workers such as adaptability and intelligence with those of robot workers such as strength and repeatability. Robust task planning is required to implement such HR teams. However, current approaches allow adaptation to change in performance or composition of HR teams or optimisation of tasks as a whole but not necessarily both. In this research, a novel generalised task planning framework is proposed that uses a semi-online task planning approach, utilising online production data to determine worker capabilities then planning a manufacturing task for the HR team offline between task iterations. A system architecture is defined for such a framework but the focus of this research is the development and testing of the core technologies required for the framework to function to assess its utility. These include dynamic cost functions utilising online production data to accurately quantify the capabilities of human and robot workers across a work shift. These use continuous variables to quantify gradual changes in worker performance across a work shift; and discrete variables to detect instantaneous changes in capabilities that occur during a single task iteration. Additionally, a dynamic task planner is developed that implements dual layers of the Discrete Gravitational Search Algorithm to search for an optimum set of task assignments and task plan for a HR team given worker costs. Finally, mechanisms are proposed to intelligently implement task replanning across a work shift to optimise a HR team’s performance whilst ensuring it does not occur too frequently or unnecessarily. These core technologies were tested individually in example cases then combined together to test the ability of the task planning framework to optimise the performance of a HR team in two example manufacturing tasks across simulated work shifts. This showed that the dynamic cost functions represent an effective way to quantify and detect any changes in a worker’s capabilities across a work shift. Additionally, task replanning was shown to improve the performance of the HR team in some scenarios, such as the human worker being over fatigued, by reassigning subtasks to the robot worker as their performance declines. Importantly, the proposed task planning framework represents a generalised methodology that can easily be redeployed to different manufacturing tasks or compositions of HR teams

    Embedded System Design

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    A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues
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