Utvidet returrett til 31. januar 2025

Bøker i Modeling and Optimization in Science and Technologies-serien

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  • - Methods and Exercises in MATLAB
    av Gautam B. Singh
    2 344,-

    This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox (TM). The last part of the book, dedicated to systems biology, covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays.

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    2 163,-

    Byproviding researchers and professionals with a timely snapshot of emergingmobile communication systems, and highlighting the main pitfalls and potentialsolutions, the book fills an important gap in the literature and will fosterthe further developments of 5G hosting IoT devices.

  • - Modeling Assistance Strategies for Large Archaeological Data Sets
    av Patricia Martin-Rodilla
    1 386,-

    This book focuses on innovative strategies to manage and build software systems for generating new knowledge from large archaeological data setsThe book also reports on two case studies carried out in real-world scenarios within the Cultural Heritage setting.

  • - Results of the HP-SEE User Forum 2012
     
    1 428,-

    This book is a collection of carefully reviewed papers presented during the HP-SEE User Forum, the meeting of the High-Performance Computing Infrastructure for South East Europe's (HP-SEE) Research Communities, held in October 17-19, 2012, in Belgrade, Serbia.

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    1 386,-

    Thanks to its synthetic yet meticulous and practice-oriented approach, the book is a perfect guide for graduate students, researchers and professionals willing to applying metaheuristic algorithms in civil engineering and other related engineering fields, such as mechanical, transport and geotechnical engineering.

  •  
    2 163,-

    Byproviding researchers and professionals with a timely snapshot of emergingmobile communication systems, and highlighting the main pitfalls and potentialsolutions, the book fills an important gap in the literature and will fosterthe further developments of 5G hosting IoT devices.

  • - Theory and Applications
     
    2 061,-

    The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization.

  • - Modeling, Methodologies and Tools
     
    1 933,-

    This book reports on cutting-edge modeling techniques, methodologies and tools used to understand, design and engineer nanoscale communication systems, such as molecular communication systems.

  • av Shengrong Gong
    713,-

    This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others.The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning,dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts. The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.

  • - Concepts and Developments
     
    2 084,-

    This book offers a transdisciplinary perspective on the concept of "smart villages" Written by an authoritative group of scholars, it discusses various aspects that are essential to fostering the development of successful smart villages.

  • av Luca Oneto
    1 386,-

    Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data.

  • av Vipul Jain, Srikanta Patnaik & Kayhan Tajeddini
    2 344,-

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