الصفحة 7
الصفحة 7
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Machine learning for civil and environmental engineers : A practical approach to data-driven analysis, explainability, and causality

Introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain.

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Machine learning approach for cloud data analytics in IoT

Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

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Machine Learning Applications in Civil Engineering

Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.

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Learning from data streams : Processing techniques in sensor networks

The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education.

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Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part III

Constitutes the refereed proceedings of the 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, held in Zagreb, Croatia, in September 2008.The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the third volume are intelligent data processing in process systems and plants; neural information processing for data mining; soft computing approach to management engineering; advanced groupware; agent and multi-agent systems.

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Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part II

The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the second volume are artificial intelligence driven engineering design optimization; biomedical informatics: intelligent information management from nanomedicine to public health; communicative intelligence; computational intelligence for image processing and pattern recognition; computational intelligence in human cancer research; computational intelligence techniques for Web personalization; computational intelligent techniques for bioprocess modelling, monitoring and control; intelligent computing for Grid.

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Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part I

The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.

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Knowledge science, engineering and management; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I

Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.

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Knowledge science, engineering and management ; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part II

Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.

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Knowledge Processing with Interval and Soft Computing

In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.

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Knowledge graphs and big data processing

This book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights.

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Knowledge Engineering : Practice and Patterns ; 16th International Conference, EKAW 2008, Acitrezza, Italy, September 29 - October 2, 2008. Proceedings

Constitutes the refereed proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008, held in Acitrezza, Sicily, Italy, in September/October 2008.The 17 revised full papers and 15 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on knowledge patterns and knowledge representation, matching ontologies and data integration, natural language, knowledge acquisition and annotations, search, query and interaction, as well as ontologies.

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Java Challenges 100+ : Proven Tasks that Will Prepare You for Anything

Expand your knowledge of Java with this entertaining learning guide, which features 100+ exercises and programming challenges. Java Challenges will prepare you for your next exam or job interview, and covers many practical topics, such as strings, arrays, data structures, recursion, and date and time. The APIs and other material included in this book are Java 17 compatible. You will: Improve your Java knowledge by solving enjoyable but challenging programming puzzles / Solve mathematical problems, recursions, strings, arrays and more / Manage data processing and data structures like lists, sets, maps / Handle advanced recursion as well as binary trees, sorting and searching / Gamify key fundamentals for fun and easier reinforcement

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ITI treatment guide ; Vol.11 : Digital workflows in implant dentistry

Addressing the technology and tools necessary to incorporate DDT into a traditional workflow, along with the clinical steps required for data acquisition, such as CBCT imaging and intraoral, extraoral, and facial scanning. The software tools needed to interpret the digital data are presented, and instructions are given on how to integrate data sets to virtually reconstruct the patient s orofacial anatomy. In addition, a series of 13 clinical cases illustrate digital technologies applied to oral implantology.

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Computable Models of the Law : Languages, Dialogues, Games, Ontologies

This book originate from a workshop held at the European University Institute of Florence, Italy, in December 2006. The workshop was devoted to the discussion of the different ways of understanding and explaining contemporary law, for the purpose of building computable models of it -- especially models enabling the development of computer applications for the legal domain.

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Chemometrics and Cheminformatics in Aquatic Toxicology

Chemometrics and Cheminformatics in Aquatic Toxicology delivers an exploration of the existing and emerging problems of contamination of the aquatic environment through various metal and organic pollutants, including industrial chemicals, pharmaceuticals, cosmetics, biocides, nanomaterials, pesticides, surfactants, dyes, and more. The book discusses different chemometric and cheminformatic tools for non-experts and their application to the analysis and modeling of toxicity data of chemicals to various aquatic organisms.

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Chemical process engineering ; Vol.1 : Design, analysis, simulation, integration, and problem solving with microsoft Excel-UniSim software for chemical engineers computation, physical Property, fluid flow, equipment and instrument sizing

The book provides a detailed description and hands-on experience on process design in chemical engineering, and it is an integrated text that focuses on practical design with new tools, such as Excel spreadsheets and UniSim simulation software.

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Business Information Systems ; 11th International Conference, BIS 2008, Innsbruck, Austria, May 5-7, 2008. Proceedings

This book contains the refereed proceedings of the 11th International Conference on Business Information Systems, BIS 2008, held in Innsbruck, Austria, in May 2008.

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Bioinformatics tools for pharmaceutical drug product development

Presents the latest information on bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies. And include bioinformatics tools for the pharmaceutical sector and the healthcare sector. Bioinformatics brings a new era in research to accelerate drug target and vaccine design development, improving validation approaches as well as facilitating and identifying side effects and predicting drug resistance. As such, this will aid in more successful drug candidates from discovery to clinical trials to the market, and most importantly make it a more cost-effective process overall.

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BIM for design firms : Data rich architecture at small and medium scales

Expands on Building Information Modeling, showing its applicability to a range of design-oriented projects. It emphasizes the full impact that a data modeling tool has on design processes, systems, and the high level of collaboration required across the design team. It also explains the quantitative analysis opportunities that BIM affords for sustainable design and for balancing competing design agendas, while highlighting the benefits BIM offers to designing in 3D for construction. The book concludes with a deep look at the possible future of BIM and digitally-enhanced design.

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