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Artificial Intelligence and the Internet of Things

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Book Series: CAMRI Policy Briefs ISBN: 9781911534839 9781911534822 9781911534839 9781911534846 Year: Pages: 31 DOI: 10.16997/book25 Language: English
Publisher: University of Westminster Press
Subject: Philosophy
Added to DOAB on : 2019-01-15 13:34:39
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"Through algorithms and artificial intelligence (AI), objects and digital services now demonstrate new skills they did not have before, right up to replacing human activity through pre-programming or by making their own decisions. As part of the internet of things, AI applications are already widely used today, for example in language processing, image recognition and the tracking and processing of data.&#xD;&#xD;This policy brief illustrates the potential negative and positive impacts of AI and reviews related policy strategies adopted by the UK, US, EU, as well as Canada and China. Based on an ethical approach that considers the role of AI from a democratic perspective and considering the public interest, the authors make policy recommendations that help to strengthen the positive impact of AI and to mitigate its negative consequences."&#xD;

New Trends on Genome and Transcriptome Characterizations

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889456109 Year: Pages: 157 DOI: 10.3389/978-2-88945-610-9 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Genetics
Added to DOAB on : 2019-01-23 14:53:43
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This Research Topic is devoted to bioinformaticians, geneticists and researchers who study or apply methods and algorithms for genomes and transcriptome analyses, aimed at understanding pathology discriminations and classifications. Papers are encouraged that use unconventional approaches and/or where mathematical and computational concepts are applied to biological and medical contexts in original ways. The contributions presented in the Topic should be of interest also to a wide class of scientists and students involved in the several fields where genomic and transcriptomic approaches are becoming essential for future investigations.

Non-Knowledge and Digital Cultures

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Book Series: Digital Cultures ISBN: 9783957961266 Year: Pages: 160 DOI: 10.14619/1259 Language: English
Publisher: meson press
Subject: Media and communication
Added to DOAB on : 2019-11-15 17:02:26
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Making available massive amounts of data that are generated, distributed, and modeled, digital media provide us with the possibility of abundant information and knowledge. This possibility has been attracting various scenarios in which technology either eliminates non-knowledge or plants it deep within contemporary cultures through the universal power and opacity of algorithms. This volume comprises contributions from media studies, literary studies, sociology, ethnography, anthropology, and philosophy to discuss non-knowledge as an important concept for understanding contemporary digital cultures.

Foundations of Trusted Autonomy

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Book Series: Studies in Systems, Decision and Control ISSN: 2198-4182 ISBN: 9783319648156 9783319648163 Year: Pages: 395 DOI: https://doi.org/10.1007/978-3-319-64816-3 Language: English
Publisher: Springer Grant: Defence Science and Technology Group, Department of Defence, Australia
Subject: Computer Science
Added to DOAB on : 2018-06-26 16:59:49
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This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness.Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume.The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems.The book augments theory with real-world applications including cybersecurity, defence and space.

Structural Health Monitoring (SHM) of Civil Structures

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ISBN: 9783038427834 9783038427841 Year: Pages: X, 490 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering
Added to DOAB on : 2018-04-20 14:47:20
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At the current time of writing, the American Society of Civil Engineers (ASCE) has awarded American infrastructure a grade of D+, meaning poor and at risk. Part of the reason for the low grade is due to the rapid deterioration of structural integrity and the inability of most places to safely meet future demands. Deficiencies in these areas may be remediated by advancements in structural health monitoring (SHM) technologies that provide sensing systems to automatically and economically diagnose structural integrity. In a sense, SHM technologies will help pave the way to intelligent structures that are able to detect damage by themselves and even warn occupants of any danger due to impending structural failure. Engineering sensors and developing smart algorithms for SHM often involves the close collaboration of a surprisingly large breadth of specialties. In this book, we have collected a thin but representative slice of the most recent research in SHM, and hope that the reader will gain an inspiring view of today’s research landscape and a notion of what is to come.

Algorithms for Scheduling Problems

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ISBN: 9783038971191 9783038971207 Year: Pages: XIV, 194 Language: Englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science --- Mathematics
Added to DOAB on : 2018-08-24 16:46:30
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This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more.

Recent Developments in Cointegration

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ISBN: 9783038429555 9783038429562 Year: Pages: VIII, 210 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics
Added to DOAB on : 2018-07-05 13:20:18
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The Cointegrated VAR model allows the user to study both long-run and short-run effects in the same model. It describes an economic system where variables have been pushed away from long-run equilibria by exogenous shocks (the pushing forces) and where short-run adjustments forces pull them back toward long-run equilibria (the pulling forces). In this model framework, basic assumptions underlying an economic theory model can be translated into testable hypotheses of the order of integration and cointegration of key variables and their relationships. While the latter used to be I(1), macroeconomic and financial data have recently shown a tendency for puzzling long and persistent swings around long-run equilibrium values typical of self-reinforcing feed-back mechanisms. Such persistent fluctuations are frequently indistinguishable from I(2) data, pointing to the need for new econometric solutions. In this book, many of our most distinguished scholars in the field of cointegration offer a variety of solutions to these problems by formulating new models, tests, and asymptotics more suitable for an I(2) world. Several of the papers apply these cointegration techniques to a variety of empirical problems, thereby showing how to obtain valuable information about some of the mechanisms that have generated the recent crises.

Hybrid Advanced Techniques for Forecasting in Energy Sector

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ISBN: 9783038972907 9783038972914 Year: Pages: 250 DOI: 10.3390/books978-3-03897-291-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science --- General and Civil Engineering
Added to DOAB on : 2018-10-19 10:39:42
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Accurate forecasting performance in the energy sector is a primary factor in the modern restructured power market, accomplished by any novel advanced hybrid techniques. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated by factors such as seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. To comprehensively address this issue, it is insufficient to concentrate only on simply hybridizing evolutionary algorithms with each other, or on hybridizing evolutionary algorithms with chaotic mapping, quantum computing, recurrent and seasonal mechanisms, and fuzzy inference theory in order to determine suitable parameters for an existing model. It is necessary to also consider hybridizing or combining two or more existing models (e.g., neuro-fuzzy model, BPNN-fuzzy model, seasonal support vector regression–chaotic quantum particle swarm optimization (SSVR-CQPSO), etc.). These advanced novel hybrid techniques can provide more satisfactory energy forecasting performances.This book aimed to attract researchers with an interest in the research areas described above. Specifically, we were interested in contributions towards recent developments, i.e., hybridizing or combining any advanced techniques in energy forecasting, with the superior capabilities over the traditional forecasting approaches, with the ability to overcome some embedded drawbacks, and with the very superiority to achieve significant improved forecasting accuracy.

Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting

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ISBN: 9783038972860 9783038972877 Year: Pages: 250 DOI: 10.3390/books978-3-03897-287-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2018-10-19 11:45:03
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More accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated. Examples include seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. These forecasting models have resulted in an over-reliance on the use of informal judgment and higher expenses when lacking the ability to determine data characteristics and patterns. The hybridization of optimization methods and superior evolutionary algorithms can provide important improvements via good parameter determinations in the optimization process, which is of great assistance to actions taken by energy decision-makers.This book aimed to attract researchers with an interest in the research areas described above. Specifically, it sought contributions to the development of any hybrid optimization methods (e.g., quadratic programming techniques, chaotic mapping, fuzzy inference theory, quantum computing, etc.) with advanced algorithms (e.g., genetic algorithms, ant colony optimization, particle swarm optimization algorithm, etc.) that have superior capabilities over the traditional optimization approaches to overcome some embedded drawbacks, and the application of these advanced hybrid approaches to significantly improve forecasting accuracy.

Kernel Methods and Hybrid Evolutionary Algorithms in Energy Forecasting

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ISBN: 9783038972921 9783038972938 Year: Pages: 186 DOI: 10.3390/books978-3-03897-293-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science --- General and Civil Engineering
Added to DOAB on : 2018-10-22 10:01:53
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The development of kernel methods and hybrid evolutionary algorithms (HEAs) to support experts in energy forecasting is of great importance to improving the accuracy of the actions derived from an energy decision maker, and it is crucial that they are theoretically sound. In addition, more accurate or more precise energy demand forecasts are required when decisions are made in a competitive environment. Therefore, this is of special relevance in the Big Data era. These forecasts are usually based on a complex function combination. These models have resulted in over-reliance on the use of informal judgment and higher expense if lacking the ability to catch the data patterns. The novel applications of kernel methods and hybrid evolutionary algorithms can provide more satisfactory parameters in forecasting models. We aimed to attract researchers with an interest in the research areas described above. Specifically, we were interested in contributions towards the development of HEAs with kernel methods or with other novel methods (e.g., chaotic mapping mechanism, fuzzy theory, and quantum computing mechanism), which, with superior capabilities over the traditional optimization approaches, aim to overcome some embedded drawbacks and then apply these new HEAs to be hybridized with original forecasting models to significantly improve forecasting accuracy.

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