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AI based Robot Safe Learning and Control

Authors: --- --- --- --- et al.
ISBN: 9789811555039 Year: Pages: 127 DOI: 10.1007/978-981-15-5503-9 Language: English
Publisher: Springer Nature
Subject: Agriculture (General) --- Computer Science
Added to DOAB on : 2020-06-16 23:57:53
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This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

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ISBN: 9783039285761 / 9783039285778 Year: Pages: 244 DOI: 10.3390/books978-3-03928-577-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:57
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Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.

Keywords

memristor --- artificial synapse --- neuromorphic computing --- memristor-CMOS hybrid circuit --- temporal pooling --- sensory and hippocampal responses --- cortical neurons --- hierarchical temporal memory --- neocortex --- memristor-CMOS hybrid circuit --- defect-tolerant spatial pooling --- boost-factor adjustment --- memristor crossbar --- neuromorphic hardware --- memristor --- compact model --- emulator --- neuromorphic --- synapse --- STDP --- pavlov --- neuromorphic systems --- spiking neural networks --- memristors --- spike-timing-dependent plasticity --- RRAM --- vertical RRAM --- neuromorphics --- neural network hardware --- reinforcement learning --- AI --- neuromorphic computing --- multiscale modeling --- memristor --- optimization --- RRAM --- simulation --- memristors --- neuromorphic engineering --- OxRAM --- self-organization maps --- synaptic device --- memristor --- neuromorphic computing --- artificial intelligence --- hardware-based deep learning ICs --- circuit design --- memristor --- RRAM --- variability --- time series modeling --- autocovariance --- graphene oxide --- laser --- memristor --- crossbar array --- neuromorphic computing --- wire resistance --- synaptic weight --- character recognition --- neuromorphic computing --- Flash memories --- memristive devices --- resistive switching --- synaptic plasticity --- artificial neural network --- spiking neural network --- pattern recognition --- strongly correlated oxides --- resistive switching --- neuromorphic computing --- transistor-like devices --- artificial intelligence --- neural networks --- resistive switching --- memristive devices --- deep learning networks --- spiking neural networks --- electronic synapses --- crossbar array --- pattern recognition

Social Safety and Security

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ISBN: 9783039281466 9783039281473 Year: Pages: 112 DOI: 10.3390/books978-3-03928-147-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Law
Added to DOAB on : 2020-01-30 16:39:46
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Social safety in social environments entails the sense of feeling safe with other people. Thus, social safety and security are very important to our life. Although research in this area has made significant progress in the past few years, there are still many social problems that require attention and further development in order to secure peace of mind. There is a very clear and accurate understanding and judgment of the overall situation of social security in the current and future period. This Special Issue focuses on a number of contemporary issues in social safety and security. The objective of this book is to rapidly disseminate the latest research and knowledge in this important area.

Advanced Approaches Applied to Materials Development and Design Predictions

Authors: --- --- --- --- et al.
ISBN: 9783039284122 9783039284139 Year: Pages: 164 DOI: 10.3390/books978-3-03928-413-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering --- Technology (General)
Added to DOAB on : 2020-04-07 23:07:09
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This thematic issue on advanced simulation tools applied to materials development and design predictions gathers selected extended papers related to power generation systems, presented at the XIX International Colloquium on Mechanical Fatigue of Metals (ICMFM XIX), organized at University of Porto, Portugal, in 2018. In this issue, the limits of the current generation of materials are explored, which are continuously being reached according to the frontier of hostile environments, whether in the aerospace, nuclear, or petrochemistry industry, or in the design of gas turbines where efficiency of energy production and transformation demands increased temperatures and pressures. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on failure mechanism modeling and simulation of materials are covered. As the Guest Editors, we would like to thank all the authors who submitted papers to this Special Issue. All the papers published were peer-reviewed by experts in the field whose comments helped to improve the quality of the edition. We also would like to thank the Editorial Board of Materials for their assistance in managing this Special Issue.

Remote Sensing based Building Extraction

Authors: --- --- ---
ISBN: 9783039283828 9783039283835 Year: Pages: 442 DOI: 10.3390/books978-3-03928-383-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Construction
Added to DOAB on : 2020-04-07 23:07:09
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Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D

Keywords

roof segmentation --- outline extraction --- convolutional neural network --- boundary regulated network --- very high resolution imagery --- building boundary extraction --- convolutional neural network --- active contour model --- high resolution optical images --- LiDAR --- richer convolution features --- building edges detection --- high spatial resolution remote sensing imagery --- building --- modelling --- reconstruction --- change detection --- LiDAR --- point cloud --- 3-D --- building extraction --- deep learning --- attention mechanism --- very high resolution --- imagery --- building detection --- aerial images --- feature-level-fusion --- straight-line segment matching --- occlusion --- building regularization technique --- point clouds --- boundary extraction --- regularization --- building reconstruction --- digital building height --- 3D urban expansion --- land-use --- DTM extraction --- open data --- developing city --- accuracy analysis --- building detection --- building index --- feature extraction --- mathematical morphology --- morphological attribute filter --- morphological profile --- building extraction --- deep learning --- semantic segmentation --- data fusion --- high-resolution satellite images --- GIS data --- high-resolution aerial images --- deep learning --- generative adversarial network --- semantic segmentation --- Inria aerial image labeling dataset --- Massachusetts buildings dataset --- building extraction --- simple linear iterative clustering (SLIC) --- multiscale Siamese convolutional networks (MSCNs) --- binary decision network --- unmanned aerial vehicle (UAV) --- image fusion --- high spatial resolution remotely sensed imagery --- object recognition --- deep learning --- method comparison --- LiDAR point cloud --- building extraction --- elevation map --- Gabor filter --- feature fusion --- semantic segmentation --- urban building extraction --- deep convolutional neural network --- VHR remote sensing imagery --- U-Net --- remote sensing --- deep learning --- building extraction --- web-net --- ultra-hierarchical sampling --- 3D reconstruction --- indoor modelling --- mobile laser scanning --- point clouds --- 5G signal simulation --- building extraction --- high-resolution aerial imagery --- fully convolutional network --- semantic segmentation --- n/a

Sentiment Analysis for Social Media

Authors: ---
ISBN: 9783039285723 / 9783039285730 Year: Pages: 152 DOI: 10.3390/books978-3-03928-573-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:56
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Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.

Advances in CAD/CAM/CAE Technologies

Authors: --- ---
ISBN: 9783039287406 / 9783039287413 Year: Pages: 116 DOI: 10.3390/books978-3-03928-741-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:57
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CAD/CAM/CAE technologies find more and more applications in today’s industries, e.g., in the automotive, aerospace, and naval sectors. These technologies increase the productivity of engineers and researchers to a great extent, while at the same time allowing their research activities to achieve higher levels of performance. A number of difficult-to-perform design and manufacturing processes can be simulated using more methodologies available, i.e., experimental work combined with statistical tools (regression analysis, analysis of variance, Taguchi methodology, deep learning), finite element analysis applied early enough at the design cycle, CAD-based tools for design optimizations, CAM-based tools for machining optimizations.

Intelligent Optimization Modelling in Energy Forecasting

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ISBN: 9783039283644 9783039283651 Year: Pages: 262 DOI: 10.3390/books978-3-03928-365-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2020-04-07 23:07:09
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Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.

Keywords

short-term load forecasting --- weighted k-nearest neighbor (W-K-NN) algorithm --- comparative analysis --- empirical mode decomposition (EMD) --- particle swarm optimization (PSO) algorithm --- intrinsic mode function (IMF) --- support vector regression (SVR) --- short term load forecasting --- crude oil price forecasting --- time series forecasting --- hybrid model --- complementary ensemble empirical mode decomposition (CEEMD) --- sparse Bayesian learning (SBL) --- multi-step wind speed prediction --- Ensemble Empirical Mode Decomposition --- Long Short Term Memory --- General Regression Neural Network --- Brain Storm Optimization --- substation project cost forecasting model --- feature selection --- data inconsistency rate --- modified fruit fly optimization algorithm --- deep convolutional neural network --- multi-objective grey wolf optimizer --- long short-term memory --- fuzzy time series --- LEM2 --- combination forecasting --- wind speed --- electrical power load --- crude oil prices --- time series forecasting --- improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) --- kernel learning --- kernel ridge regression --- differential evolution (DE) --- artificial intelligence techniques --- energy forecasting --- condition-based maintenance --- asset management --- renewable energy consumption --- Gaussian processes regression --- state transition algorithm --- five-year project --- forecasting --- Markov-switching --- Markov-switching GARCH --- energy futures --- commodities --- portfolio management --- active investment --- diversification --- institutional investors --- energy price hedging --- metamodel --- ensemble --- individual --- regression --- interpolation

Energy Efficiency in Buildings: Both New and Rehabilitated

Authors: ---
ISBN: 9783039287024 / 9783039287031 Year: Pages: 412 DOI: 10.3390/books978-3-03928-703-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Arts in general --- Architecture
Added to DOAB on : 2020-06-09 16:38:57
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Buildings are one of the main causes of the emission of greenhouse gases in the world. Europe alone is responsible for more than 30% of emissions, or about 900 million tons of CO2 per year. Heating and air conditioning are the main cause of greenhouse gas emissions in buildings. Most buildings currently in use were built with poor energy efficiency criteria or, depending on the country and the date of construction, none at all. Therefore, regardless of whether construction regulations are becoming stricter, the real challenge nowadays is the energy rehabilitation of existing buildings. It is currently a priority to reduce (or, ideally, eliminate) the waste of energy in buildings and, at the same time, supply the necessary energy through renewable sources. The first can be achieved by improving the architectural design, construction methods, and materials used, as well as the efficiency of the facilities and systems; the second can be achieved through the integration of renewable energy (wind, solar, geothermal, etc.) in buildings. In any case, regardless of whether the energy used is renewable or not, the efficiency must always be taken into account. The most profitable and clean energy is that which is not consumed.

Keywords

greenhouse --- floor envelope design --- ground heat transfer --- thermal insulation --- energy modeling --- life cycle cost analysis --- nearly zero energy building --- artificial neural network --- performance parameter design --- energy saving ratio --- dynamic simulation --- urban modelling --- co-simulation --- simulation engines --- building stock energy demand --- building --- energy --- heat load --- sensitivity --- glazing --- surface cooling --- three-phase unbalance minimization --- model predictive control --- home energy management system --- perturbation and observation --- adjustable step size --- low power loss --- maximum power point tracking --- HVAC demand --- prediction --- energy efficiency --- residential buildings --- Ipomoea batatas --- lightweight expanded clay aggregate (LECA), thermal performance --- extensive green roof --- subtropical climate --- artificial neural network --- big data --- energy-performance gap --- building energy prediction --- building user activity --- single-person household --- Korean household energy consumption --- analytical hierarchy process --- energy efficiency promotion --- influencing factors --- residential buildings --- policy design --- building energy --- passive architecture --- test method --- energy performance standard --- zero energy building --- technology package --- renovation --- energy renovation --- demolition --- new construction --- energy use --- energy performance --- life cycle cost --- optimization --- OPERA-MILP --- multi-family buildings --- Arab region --- building sector --- energy efficiency --- energy productivity --- GCC --- Maghreb --- Mashreq --- space heating --- domestic hot water (DHW) --- air, ground and water source heat pump (ASHP, GSHP and WSHP) --- coefficient of performance (COP) --- seasonal performance factor (SPF) --- energy pile --- energy tunnel --- Level(s) --- green building rating systems --- Building Research Establishment Assessment Method (BREEAM) --- Deutsche Gesellschaft für Nachhaltiges Bauen (DGNB) --- Haute Qualité Environnementale (HQE) --- Leadership in Energy &amp --- Environmental Design (LEED) --- energy efficiency --- subtropical climate building --- Minimum-Energy Building (MEB) --- building refurbishment --- building rehabilitation --- building renovation --- envelope airtightness --- envelope thermography --- envelope transmittance

Visual Sensors

Authors: ---
ISBN: 9783039283385 9783039283392 Year: Pages: 738 DOI: 10.3390/books978-3-03928-339-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.

Keywords

3D reconstruction --- RGB-D sensor --- non-rigid reconstruction --- pedestrian detection --- boosted decision tree --- scale invariance --- receptive field correspondence --- soft decision tree --- single-shot 3D shape measurement --- digital image correlation --- warp function --- inverse compositional Gauss-Newton algorithm --- UAV image --- dynamic programming --- seam-line --- optical flow --- image mosaic --- iris recognition --- presentation attack detection --- convolutional neural network --- support vector machines --- content-based image retrieval --- textile retrieval --- textile localization --- texture retrieval --- texture description --- visual sensors --- iris recognition --- iris segmentation --- semantic segmentation --- convolutional neural network (CNN) --- visible light and near-infrared light camera sensors --- laser sensor --- line scan camera --- lane marking detection --- support vector machine (SVM) --- image binarization --- lane marking reconstruction --- automated design --- vision system --- FOV --- illumination --- recognition algorithm --- action localization --- action segmentation --- 3D ConvNets --- LSTM --- visual sensors --- image retrieval --- hybrid histogram descriptor --- perceptually uniform histogram --- motif co-occurrence histogram --- omnidirectional imaging --- visual localization --- catadioptric sensor --- visual information fusion --- image processing --- underwater imaging --- embedded systems --- stereo vision --- visual odometry --- 3D reconstruction --- handshape recognition --- sign language --- finger alphabet --- skeletal data --- visual odometry --- ego-motion estimation --- stereo --- RGB-D --- mobile robots --- around view monitor (AVM) system --- automatic calibration --- lane marking --- parking assist system --- advanced driver assistance system (ADAS) --- pose estimation --- symmetry axis --- point cloud --- sweet pepper --- semantic mapping --- RGB-D SLAM --- visual mapping --- indoor visual SLAM --- adaptive model --- motion estimation --- stereo camera --- person re-identification --- end-to-end architecture --- appearance-temporal features --- Siamese network --- pivotal frames --- visual tracking --- correlation filters --- motion-aware --- adaptive update strategy --- confidence response map --- camera calibration --- Gray code --- checkerboard --- visual sensor --- image retrieval --- human visual system --- local parallel cross pattern --- pose estimation --- straight wing aircraft --- structure extraction --- consistent line clustering --- parallel line --- planes intersection --- salient region detection --- appearance based model --- regression based model --- human visual attention --- background dictionary --- quality control --- fringe projection profilometry --- depth image registration --- 3D reconstruction --- speed measurement --- stereo-vision --- large field of view --- vibration --- calibration --- CLOSIB --- statistical information of gray-levels differences --- Local Binary Patterns --- texture classification --- texture description --- Visual Sensors --- SLAM --- RGB-D --- indoor environment --- Manhattan frame estimation --- orientation relevance --- spatial transformation --- robotic welding --- seam tracking --- visual detection --- narrow butt joint --- GTAW --- LRF --- camera calibration --- extrinsic calibration --- sensors combination --- geometric moments --- camera pose --- rotation-angle --- measurement error --- robotics --- robot manipulation --- depth vision --- star image prediction --- star sensor --- Richardson-Lucy algorithm --- neural network --- tightly-coupled VIO --- SLAM --- fused point and line feature matching --- pose estimates --- simplified initialization strategy --- patrol robot --- map representation --- vision-guided robotic grasping --- object recognition --- pose estimation --- global feature descriptor --- iterative closest point --- n/a

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