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Geotechnical and Geophysical Site Characterization
Geotechnical and Geophysical Site Characterization collects the papers presented at the Third International Conference on Site Characterization (ISC 3) that took place in Taipei from April 1-4, 2008. The subjects covered include new developments in mechanical in-situ testing and interpretation techniques, statistical analysis of test data, geo
Foundation Engineering Analysis and Design
One of the core roles of a practising geotechnical engineer is to analyse and design foundations. This textbook for advanced undergraduates and graduate students covers the analysis, design and construction of shallow and deep foundations and retaining structures as well as the stability analysis and mitigation of slopes. It progressively introduces critical state soil mechanics and plasticity theories such as plastic limit analysis and cavity expansion theories before leading into the theories of foundation, lateral earth pressure and slope stability analysis. On the engineering side, the book introduces construction and testing methods used in current practice. Throughout it emphasizes the...
Supervised and Unsupervised Data Engineering for Multimedia Data
SUPERVISED and UNSUPERVISED DATA ENGINEERING for MULTIMEDIA DATA Explore the cutting-edge realms of data engineering in multimedia with Supervised and Unsupervised Data Engineering for Multimedia Data, where expert contributors delve into innovative methodologies, offering invaluable insights to empower both novices and seasoned professionals in mastering the art of manipulating multimedia data with precision and efficiency. Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in ...
Closing the Gap Between ASIC & Custom
This book carefully details design tools and techniques for high-performance ASIC design. Using these techniques, the performance of ASIC designs can be improved by two to three times. Important topics include: Improving performance through microarchitecture; Timing-driven floorplanning; Controlling and exploiting clock skew; High performance latch-based design in an ASIC methodology; Automatically identifying and synthesizing complex logic gates; Automated cell sizing to increase performance and reduce power; Controlling process variation.These techniques are illustrated by designs running two to three times the speed of typical ASICs in the same process generation.
Computer Vision – ECCV 2020
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Geo-Architecture and Landscape in China’s Geographic and Historic Context
This book approaches the concept of geo-architecture by analyzing the symbolic characters of architectures. It proves that the relationship between architecture and geography is not merely an embodiment of physical and functional demands but rather a formal expression of the materialization of culture. After analyzing the vast number of villages, groups of buildings and individual buildings the forms of which closely resemble the forms of the Bagua (symbol of the Eight Trigrams), Taichi, animals and plants, this book finds that this kind of symbolism creatively places living and working places within the natural geographic environment and, by seeking a relationship between architecture and i...
Elements of Dimensionality Reduction and Manifold Learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and manifold learning. Three main aspects of dimensionality reduction are covered: spectral dimensionality reduction, probabilistic dimensionality reduction, and neural network-based dimensionality reduction, which have geometric, probabilistic, and information-theoretic points of view to dimensionality reduction, respectively. The necessary background and preliminaries on linear algebra, optimization, an...
Proceedings of China-Europe Conference on Geotechnical Engineering
This book compiles the first part of contributions to the China–Europe Conference on Geotechnical Engineering held 13.-16. August 2016 in Vienna, Austria. About 400 papers from 35 countries cover virtually all areas of geotechnical engineering and make this conference a truly international event. The contributions are grouped into thirteen special sessions and provide an overview of the geoengineering research and practice in China, Europe and the world: · Constitutive model · Micro-macro relationship · Numerical simulation · Laboratory testing · Geotechnical monitoring, instrumentation and field test · Foundation engineering · Underground construction · Environmental geotechnics · New geomaterials and ground improvement · Cold regions geotechnical engineering · Geohazards – risk assessment, mitigation and prevention · Unsaturated soils and energy geotechnics · Geotechnics in transportation, structural and hydraulic Engineering
NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS
The second edition of this book provides a comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence, which in recent years, has turned synonymous to it. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems. The hybridization of the technologies is demonstrated on architectures such as fuzzy backpropagation network (NN-FS hybrid), genetic algorithm-based backpropagation network (NN-EA hybrid), simplified fuzzy ARTMAP (NN-FS hybri...
Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals
Epilepsy is a common and diverse set of chronic neurological disorders characterized by seizures. It is a paroxysmal behavioral spell generally caused by an excessive disorderly discharge of cortical nerve cells of the brain. Epilepsy is marked by the term “epileptic seizures”. Epileptic seizures result from abnormal, excessive or hyper-synchronous neuronal activity in the brain. About 50 million people worldwide have epilepsy, and nearly 80% of epilepsy occurs in developing countries. The most common way to interfere with epilepsy is to analyse the EEG (electroencephalogram) signal which is a non-invasive, multi channel recording of the brain’s electrical activity. It is also essential to classify the risk levels of epilepsy so that the diagnosis can be made easier. This study investigates the possibility of Extreme Learning Machine (ELM) and Continuous GA as a post classifier for detecting and classifying epilepsy of various risk levels from the EEG signals. Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are used for dimensionality reduction.
