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Antioxidants as nutraceuticals

Provides a comprehensive overview of antioxidants and nutraceuticals, including their sources, mechanisms of action, and health benefits, this new volume first covers the basics of the types of antioxidants as nutraceuticals, including the importance of phytochemical antioxidants and their nutritional and pharmacological intervention in the treatment of disease. It discusses the natural origins of antioxidants, classification, mechanisms of action, calculation of antioxidant potential of nutraceutical substances, safety, toxicity, and their significant involvement in the prevention of many degenerative and chronic diseases.

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Anorectal Malformations in Children : Embryology, Diagnosis, Surgical Treatment, Follow-up

The book assembles many new aspects in the broad field of anorectal and genitourinary malformations. Special attention is given to the new surgical techniques posterior sagittal anorectal plasty (PSARP), urogenital sinue advancement, and laparoscopy. The results of an international workshop of 26 international authorities on congenital malformations of the organs of the pelvis and perineum are presented. The new classification proposed at the Krickenberg Conference will enable future studies comparing the types and the results of treatment of anorectal malformations.

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Analysing Ecological Data

This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ecological studies or research projects. The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate analysis, time series analysis (e.g. common trends) and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the first authors. The case studies include topics ranging from terrestrial ecology to marine biology.

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African Biodiversity : molecules, organisms, ecosystems

BIOTA is an interdisciplinary research project focusing on sustainable use and conservation of biodiversity in Africa (http://www.biote-africa.de). Session titles were Biogeography and Speciation Processes, Phylogenetic Patterns and Systematics, Diversity Declines and Conservation, and Applied Biodiversity Informatics

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Advances in Network Electrophysiology : Using Multi-Electrode Arrays

This book book is an attempt to review the recent progress in both electronics and computational tools developed to analyze the functional operations of large ensembles of neurons and to provide the readers with a sense of the applications made possible by these technological tools. While considerable progress has been made over the last decades in our understanding of electrophysiological processes at the single channel, single synapse, and single neuron levels, our understanding of electrophysiological

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Mathematical Linguistics

Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up, with no prior knowledge of linguistics being assumed, covering more than the average two-semester introductory course in linguistics.This comprehensive, reader-friendly volume offers readers a high-level orientation, discussing the foundations of the field and presenting both the classical work and the most recent results. It covers an extremely rich array of topics including not only syntax and semantics but also phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting.

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Management of Data Center Networks

Discover state-of-the-art developments in DCNs from leading international voices in the field. Delivers a rigorous and insightful exploration of the network management challenges that present within intra- and inter-data center networks, including reliability, routing, and security. The book also discusses new architectures found in data center networks that aim to minimize the complexity of network management while maximizing Quality of Service, like Wireless/Wired DCNs, server-only DCNs, and more. offers: A thorough overview of the architectures of data center networks, including the classification of switch-centric, server-centric, enhanced, optical, and wireless DCN architectures An exploration of resource management in wired and wireless data center networks, including routing and wireless channel allocation and assignment challenges and criteria Practical discussions of inter-data center networks, including an overview of basic virtual network embedding Examinations of energy and security management in data center networks

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Machine learning methods for reverse engineering of defective structured surfaces

Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.

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Machine learning for data streams : With practical examples in MOA

The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.

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Machine Learning for Audio, Image and Video Analysis : Theory and Applications

The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text

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Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining

Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod­ els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe­ matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com­ puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter­ net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

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Charting a new course : Natural language processing and information retrieval : Essays in Honour of Karen Spärck Jones

This book celebrates the life and work of Karen Spärck Jones in her seventieth year. she is one of the major figures of 20th century and early 21st Century computing and information processing. It book consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.

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Biological and artificial intelligence environments

The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.

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Beginning deep learning with TensorFlow : Work with Keras, MNIST data sets, and advanced neural networks

Stats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! You will: Develop using deep learning algorithms Build deep learning models using TensorFlow 2 Create classification systems and other, practical deep learning applications

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Autonomous vehicles technological trends

The automotive industry has always been synonymous with research and innovation, but nowadays the industry is adding pressure and is establishing the agenda of the researchers from the field. Visions have been provided, and the hardware and the software exist; the only question remaining is: “who is going to deliver”? To answer this question, we encouraged scientists, researchers, industry specialists, and academics to share their vision of autonomous vehicles. What will the platform look like? What kind of hardware and software is most suitable? Who will make the connection between these two interdependent environments (and how), so that in the end the AI will define the process? These are the pressing issues of the current moment, and this Special Issue will help all those interested in the topic to promote their vision and ideas.

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Assistive technologies, robotics, and automated machines in the health domain

The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.

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Artificial neural networks : Recent advances, new perspectives and applications

This book explores the potential of ANNs for applications in different fields. Itincludes eight chapters that discuss deep learning, ANN tools, and other cutting-edgetechnologies. It also suggests avenues for further research into ANN techniques formedical imaging to detect breast tumors, classification of COVID-19 surveillancedatasets, health management, estimation of materials processing parameters, solarenergy management, and control of a petrochemical unit.

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Artificial Intelligent Techniques for Wireless Communication and Networking

Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments.

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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.

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Artificial Intelligence Applications for Health Care

Covers topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided.

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