الصفحة 21
الصفحة 21
Artificial intelligence-based Internet of things systems
Discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects. Addresses the complete functional framework workflow in AI-enabled IoT ecosystem; Presents intelligent object identification and object discovery through the IoT ecosystem and its implications to the real world ;Explores security and privacy issues and trustworthy machine learning related to data-intensive technologies in AI-based IoT ecosystems.
Artificial Intelligence. IJCAI 2019 International Workshops ; Macao, China, August 10–12, 2019, Revised Selected Best Papers
This book presents selected papers of 12 Workshops held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, in Macao, China, in August 2019.
Artificial Intelligence, Business and Civilization : Our Fate Made in Machines
Looks at what exactly artificial intelligence is, how it can be classified, how it differentiates from other concepts such as machine learning, big data, blockchain, or the Internet-of-Things, and how it has evolved and might evolve over time.
Artificial Intelligence with Python
Introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
Artificial intelligence techniques in hydrology and water resources management
The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices.
Artificial intelligence in theory and practice ; IFIP 19th World Computer Congress, TC 12: IFIP AI 2006 Stream, August 21-24, 2006, Santiago, Chile
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured.
Artificial intelligence in pharmacy
Artificial intelligence (AI) is a branch of computer science that deals with the problem-solving by the aid of symbolic programming. It has greatly evolved into a science of problem-solving with huge applications in business, health care, and engineering. One of the pivotal applications of AI is the development of the expert system. With the advent of big data and Al, robots are now becoming more trustworthy for doctors, and a large number of institutions are now employing robots along with human supervision to carry out activities that were previously done by humans...
Artificial intelligence in medicine ; 11th Conference on artificial intelligence in medicine in Europe, AIME 2007, Amsterdam, The Netherlands, July 7-11, 2007, Proceedings
This book contains development of theory, systems, and applications of AI in medicine, including the exploitationof AI approachesto molecularmedicine and biomedical informatics.
Artificial intelligence in medicine ; 10th conference on artificial intelligence in medicine, AIME 2005, Aberdeen, UK, July 23-27, 2005, Proceedings
This book constitutes the refereed proceedings of the 10th Conference on Artificial Intelligence in Medicine in Europe, AIME 2005, held in Aberdeen, UK in July 2005. The 35 revised full papers and 34 revised short papers presented together with 2 invited contributions were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on temporal representation and reasoning, decision support systems, clinical guidelines and protocols, ontology and terminology, case-based reasoning, signal interpretation, visual mining, computer vision and imaging, knowledge management, machine learning, knowledge discovery, and data mining.
Artificial intelligence in medicine
Provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting.
Artificial intelligence in mechatronics and civil engineering : Bridging the gap
Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.
Artificial intelligence in image-based screening, diagnostics, and clinical care of cardiopulmonary diseases
In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases.
Artificial intelligence in HCI ; 1st International conference, AI-HCI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings
This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence in HCI, AI-HCI 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in July 2020. The conference was planned to be held in Copenhagen, Denmark, but had to change to a virtual conference mode due to the COVID-19 pandemic.
Artificial intelligence in education ; 21st International conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part II
This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.* The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Artificial intelligence in education ; 21st International conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part I
This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.* The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Artificial intelligence in drug design
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
Artificial intelligence in dentistry
Provides an introduction to next-generation applications and technologies for improving diagnostic accuracy and prediction of treatment outcomes in dentistry through the use of artificial intelligence (AI) and machine learning (ML). The authors attempt to bridge the gap between dental research and global health outcomes, as well as provide a comprehensive guide to general and clinical aspects of dental and oral health issues and the etiology, prevalence, assessment, and management of these conditions.
Artificial intelligence for oral health care : Applications and future prospects
Offers a deeper understanding of the foundational concepts of AI, its practical applications in oral health, and the possibilities that lie ahead. From oral pathology to maxillofacial surgery, prosthodontics to orthodontics, and endodontics to dental education, it presents compelling, evidence-based insights into how AI is changing the landscape of dentistry.
Artificial intelligence for multisource geospatial information
Collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.
Artificial intelligence for customer relationship management : Solving customer problems
This book describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer.
