Описание: Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions, lead current research toward the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. The book at hand, devoted to Smart Software Applications in Cyber-Physical Systems, constitutes the second volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in Smart Software Applications in (i) Scientific Document Processing, (ii) Enterprise Modeling, (iii) Education, (iv) Health care and Medicine, and (v) Infrastructure Monitoring. Professors, researchers, scientists, engineers, and students in artificial intelligence, software engineering, and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.
Описание: In the lively, but desperate world of D.C.`s underbelly, filled with back-alley deals, gentrification clashes, and unexpected encounters between politicians and bottom-rung natives-all set against a soundscape of patois, street Spanish, and D.C. slang-a Black homeless man must hone his detective skills before he is punished for a brutal crime he didn`t commit.
Описание: This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community. In the era when the world is grappling with many unforeseen challenges, scientists and researchers are envisioning smart cyber systems that guarantee sustainable development for a better human life. The main contributors that destined to play a huge role in developing such systems, among others, are AI and IoT. While AI provides intelligence to machines and data by identifying patterns, developing predictions, and detecting anomalies, IoT performs as a nerve system by connecting a huge number of machines and capturing an enormous amount of data. AI-enabled IoT, therefore, redefines the way industries, businesses, and economies function with increased automation and efficiency and reduced human interaction and costs. This book is an attempt to publish innovative ideas, emerging trends, implementation experience, and use-cases pertaining to the merger of AI and IoT. The primary market of this book is centered around students, researchers, academicians, industrialists, entrepreneurs, and professionals working in electrical/computer engineering, IT, telecom/electronic engineering, and related fields. The secondary market of this book is related to individuals working in the fields such as finance, management, mathematics, physics, environment, mechatronics, and the automation industry.
Novel strategies for data-driven evolutionary optimization
Machine learning using distance-based methods
Counting cells and predicting immunoscore using gradient boosted convolutional neural networks
Kubelka-Munk model and stochastic model comparison in skin physical parameter retrieval using neural networks
A combined approach of neural networks and graphical models in skin cancer inference using spectral imaging
Using wave propagation simulations and convolutional neural networks to retrieve thin coating's thickness from hyperspectral images
Predicting future overweight and obesity from childhood growth data: A case study
Variable selection under a value acquisition budget
Stochastic approximation by successive piecewise linearization
Non-convex robust low-rank matrix recovery
Neural network learning via successive piecewise linearization
Learning for scientific computing purposes
Computational intelligence in design of new nanomaterials
Modeling flow, reactive transport and geomechanics in porous media
Physics constrained machine learning for industrial applications
Parameter and type identification in partial differential equations using deep neural networks
Stability maximization for layered moving web with total mass constraint
Similarity solutions for condensation on a non-isothermal vertical plate
Enhanced topology optimization approach using moving morphable components coupled with NURBS curves
Combined model order reduction and artificial neural network for data assimilation and damage detection in structures
Towards the optimization of fuzzy pattern trees by abs - linearization
Support vector machines in clusterwise linear regression
A Second-order method with enriched hessian information for composite sparse optimization problems
Missing value imputation via nonsmooth optimization and clusterwise linear regression
Parsimonious neural networks
Nobody can stop advancing artificial intelligence (AI) where developing
Computational sciences, physics field theories and geometry
Mini-symposium on ethics in AI
Essentializing software engineering practices for ethically designing and developing artificial intelligence systems 30 Ethics is important, but how can we implement it? Survey on software developers' views on AI ethics
Industrial IoT capabilities in reducing the LCOE of offshore wind energy: A review
High-Performance data analysis with the Helmholtz Analytics Toolkit (HeAT)
Dynamic data-driven application systems based on tensor factorization: learning the physics of model evolution
Predicting customer experience
Puhti-AI: Finland's new AI supercomputer
Using Artificial Intelligence to Classify Textual Applications for Reporting Purposes Application of machine learning methods to error control of approximate solutions
Iterative data selection strategy in offline data-driven evolutionary multiobjective optimization
On surrogate management in interactive multiobjective building energy system design
A modified deep neural network for the rapid inversion of geo-physical resistivity measurements
Using agents for automatic meta-modelling algorithm selection in data-driven multiobjective optimization problems
Future cooperation between Computational Science and AI in Industrial and Societal Applications - challenges, impact and expectations?
Описание: Second International Conference ICIRA 2009 Singapore December 1618 2009 Proceedings. .
Автор: Elhoseny Mohamed, Shankar K., Abdel-Basset Mohamed Название: Artificial Intelligence Techniques in IoT Sensor Networks ISBN: 0367681455 ISBN-13(EAN): 9780367681456 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the frontiers and challenges of applying Artificial Intelligence (AI) techniques to Sensor Networks. It covers how sensor networks are widely used to collect environmental parameters in homes, buildings, vehicles, etc., and how they are used as a source of information to aid decision-making processes.
Описание: The book explains the need to decarbonise energy supplies, urban systems and industrial processes to reduce global greenhouse gases and meet the ambitious emissions reduction goals set out in the Paris Agreement 2016. It discusses how the introduction of AI to cyber-physical systems (CPS) can do this, using illustrations throughout to highlight the potential impacts. Intelligent Decarbonisation comprehensively assesses the current and future impact of digital technologies and artificial intelligence (AI) on the decarbonisation of key economic sectors. The book is divided into four parts – Technology, Impact, Implications and Incubation – moving clearly from the theoretical and technical to the real-world effects and areas for future development. It also presents insights into the economic and environmental transformation fostered by digital technologies. Intelligent Decarbonisation brings together work from private and public sector professionals, academics and think tank experts, and provides truly comprehensive insights into the topic. It is an interesting and informative text for policymakers, researchers and industry professionals alike.
Описание: The thoroughly updated fourth edition features new coverage of deep learning algorithms. Using clear and concise language, it explains the principles of artificial intelligence (AI) and its practical applications. It gives engineers and scientists a solid grounding in AI so that its they can implement systems in their own domain of interest.
Автор: Kumar Bhoi Название: Hybrid Artificial Intelligence and IoT in Healthcare ISBN: 9811629749 ISBN-13(EAN): 9789811629747 Издательство: Springer Рейтинг: Цена: 21953.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers applications for hybrid artificial intelligence (AI) and Internet of Things (IoT) for integrated approach and problem solving in the areas of radiology, drug interactions, creation of new drugs, imaging, electronic health records, disease diagnosis, telehealth, and mobility-related problems in healthcare.
Описание: This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community. In the era when the world is grappling with many unforeseen challenges, scientists and researchers are envisioning smart cyber systems that guarantee sustainable development for a better human life. The main contributors that destined to play a huge role in developing such systems, among others, are AI and IoT. While AI provides intelligence to machines and data by identifying patterns, developing predictions, and detecting anomalies, IoT performs as a nerve system by connecting a huge number of machines and capturing an enormous amount of data. AI-enabled IoT, therefore, redefines the way industries, businesses, and economies function with increased automation and efficiency and reduced human interaction and costs. This book is an attempt to publish innovative ideas, emerging trends, implementation experience, and use-cases pertaining to the merger of AI and IoT. The primary market of this book is centered around students, researchers, academicians, industrialists, entrepreneurs, and professionals working in electrical/computer engineering, IT, telecom/electronic engineering, and related fields. The secondary market of this book is related to individuals working in the fields such as finance, management, mathematics, physics, environment, mechatronics, and the automation industry.
Описание: This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.