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While several books are available today that address the mathematical and philosophical foundations of fuzzy logic, none, unfortunately, provides the practicing knowledge engineer, system analyst, and project manager with specific, practical information about fuzzy system modeling. Those few books that include applications and case studies concentrate almost exclusively on engineering problems: pendulum balancing, truck backeruppers, cement kilns, antilock braking systems, image pattern recognition, and digital signal processing. Yet the application of fuzzy logic to engineering problems represents only a fraction of its real potential. As a method of encoding and using human knowledge in a form that is very close to the way experts think about difficult, complex problems, fuzzy systems provide the facilities necessary to break through the computational bottlenecks associated with traditional decision support and expert systems. Additionally, fuzzy systems provide a rich and robust method of building systems that include multiple conflicting, cooperating, and collaborating experts (a capability that generally eludes not only symbolic expert system users but analysts who have turned to such related technologies as neural networks and genetic algorithms). Yet the application of fuzzy logic in the areas of decision support, medical systems, database analysis and mining has been largely ignored by both the commercial vendors of decision support products and the knowledge engineers who use them.

Computers. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Mathematical modelling

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Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0.

Computers / Artificial Intelligence --- Computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Industry & industrial studies

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The United Nations Sustainable Development Goals initiative has the potential to set the direction for a future world that works for everyone.  Approved by 193 United Nations member countries in September 2016 to help guide global and national development policies in the period to 2030, the 17 goals build on the successes of the Millennium Development Goals, but also include new priority areas, such as climate change, economic inequality, innovation, sustainable consumption, peace and justice.  Assessed against common agreed targets and indicators, the goals should facilitate inter-governmental cooperation and the development of regional and even global development strategies.  However, each goal presents considerable challenges in terms of collecting and analysing relevant data and producing the statistics needed to measure progress.  Most governments in lower resourced countries simply do not yet have the systems and controls in place to produce high quality, reliable data and statistics, and it is questionable whether the quality and integrity of the available information is adequate to support meaningful decisions and set direction for the future. There are substantial implications:  where progress cannot be measured accurately because of inadequate or flawed statistics, the result can be misguided decisions, doubts about achievement of the goals and significant wasted resources.  Getting statistics 'right' depends upon the quality and integrity of the data used to produce them and on  the quality of the processes for collecting, manipulating and analysing the data.  Without a documentary records as evidence of how the data were gathered and analysed or how statistics were produced and disseminated, it is not  possible to confirm that the statistics are complete, accurate and relevant.     Various global organisations do recognise the importance of high quality data and statistics for measuring the SDG indicators reliably, but there has been little attention to the role of records in providing the evidence needed to trust the data and statistics. There is, moreover, a lack of awareness that digital information simply will not survive without policies and procedures to manage and preserve it through time.  As a result, digital data, statistics and records are being lost regularly on a large scale, particularly in lower resource countries, where the structures needed to protect and preserve them are not  yet in place.     This book explores, through a series of case studies, the substantial challenges for assembling reliable data and statistics to address pressing development challenges, particularly in Africa. Hopefully, by highlighting the enormous potential value of creating and using high quality data, statistics and records as an interconnected resource and describing how this can be achieved, the book will contribute to  defining meaningful and realistic global and national development policies in the critical period to 2030.

Technology & Engineering / Agriculture --- Computers / Data Science --- Computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace

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The exchange of orbit information is becoming more important in view of the increasing population of objects in space as well as the increase in parties involved in space operations. The aim of this thesis was to investigate how orbit information maintained by a space surveillance system can be provided to its users. Services like collision avoidance require very accurate information, while other services might be less stringent. An approach was studied, which allows to derive orbit and covariance information of predetermined accuracy from a reference orbit. Using Chebyshev polynomials, continuous state vector and covariance matrix information can be provided. The major advantage is that no inter- or extrapolation on the user's side is required. A method to reduce the data amount by interpolating the variance envelope functions was also studied. The proposed method in this thesis gives access to highly accurate information from the catalogue, where this information is required. On the other hand it can also provide less accurate information, where requirements are less restrictive, thereby allowing for a significantly reduced amount of data to be transferred and stored.

Orbital mechanics. --- Computers. --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Astrodynamics --- Mechanics --- Orbits --- space debris --- space surveillance --- space situational awareness

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Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain-machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications.

Computers / Data Science / Neural Networks --- Computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Data Science --- Neural Networks