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New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

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ISBN: 9783039282906 / 9783039282913 Year: Pages: 428 DOI: 10.3390/books978-3-03928-291-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Industrial Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Abstract

Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.

Keywords

cutting insert selection --- cutting parameter optimization --- artificial neural networks --- genetic algorithm --- connected enterprise --- smart manufacturing --- big data --- machine learning --- data reduction --- predictive analytics --- in-line dimensional inspection --- warm forming --- 3D mesh reconstruction --- optical system --- revolution workpiece --- defect detection --- polymer lithium-ion battery --- convolutional neural network --- deep learning --- blister defect --- flower pollination algorithm --- Industry 4.0 --- anomaly detection --- scheduling --- neural network --- skyline queries --- Cyber-Physical Systems (CPS) --- scalability test --- Internet of Things (IoT) --- INDUSTRY 4.0 --- economic recession --- research and development indicators --- maintenance expert --- competence --- decision support --- micro-armature --- defect detection --- convolutional neural networks --- computer vision --- capacity control --- job shop systems --- RMTs --- operator theory --- 4th industrial revolution --- industry 4.0 --- AHP --- QFD --- matching --- fibre of preserved Szechuan pickle --- contour detection --- dilated convolutions --- HED --- social network --- industry 4.0 --- industrial knowledge graph --- deep learning --- industrial big data --- intellectualization of industrial information --- digital manufacturing --- smart factory --- Industry 4.0 --- digital platforms --- automated surface inspection --- D-VGG16 --- bilinear model --- Grad-CAM --- classification --- localization --- elliptical paraboloid array --- self-calibration method --- vertex distance --- optical slope sensor --- geometric relationship --- relative angle --- fabric defect detection --- LGM --- FCM --- image smoothing --- Industry 4.0 --- marketing innovations --- innovative marketing tools --- impacts marketing innovations --- Industry 4.0 --- configure-to-order --- BIM --- construction equipment --- digital information flow --- lean assembly --- digital twins --- cyber-physical production systems --- depthwise separable convolution --- YOLOv3 --- feature pyramid --- aircraft structure crack detection --- industrial load management --- demand-side management --- demand-side response --- energy flexibility --- IT concept --- platform-based ecosystem --- control service --- smart service --- control as a service --- cloud-based control system --- automation system --- chatter --- train wheel --- smart system --- turning --- edge computing --- n/a

Applications of Computational Intelligence to Power Systems

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ISBN: 9783039217601 / 9783039217618 Year: Pages: 116 DOI: 10.3390/books978-3-03921-761-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-11-08 11:31:56
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Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.

Ultrasonic Guided Waves

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ISBN: 9783039282982 / 9783039282999 Year: Pages: 376 DOI: 10.3390/books978-3-03928-299-9 Language: eng
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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The propagation of ultrasonic guided waves in solids is an important area of scientific inquiry, primarily due to their practical applications for nondestructive characterization of materials, such as nondestructive inspection, quality assurance testing, structural health monitoring, and providing a material state awareness. This Special Issue of Applied Sciences covers all aspects of ultrasonic guided waves (e.g., phased array transducers, meta-materials to control wave propagation characteristics, scattering, attenuation, and signal processing techniques) from the perspective of modeling, simulation, laboratory experiments, or field testing. In order to fully utilize ultrasonic guided waves for these applications, it is necessary to have a firm grasp of their requisite characteristics, which include that they are multimodal, dispersive, and are comprised of unique displacement profiles through the thickness of the waveguide.

Keywords

electromagnetic wave --- group velocity --- time-frequency domain reflectometry --- dispersive medium --- ultrasonic guided wave --- nondestructive testing --- square steel bar --- non-detection zone --- surface flaw --- Rayleigh wave --- scattering --- modified BEM --- reconstruction --- adhesive joint --- single lap joint --- non-destructive testing --- damage identification --- Lamb waves --- scanning laser vibrometry --- signal processing --- ultrasonic guided waves --- axial transmission --- ultrasonic guided waves --- fiber optics --- fiber Bragg grating --- nondestructive testing --- structural health monitoring --- pipe inspection --- partial wave method --- slowness curves --- lamb wave --- stoneley wave --- mode sorting --- acoustic leakage --- rayleigh wave --- surface waves --- elastodynamics --- guided waves --- lamb wave --- dispersion curves --- phase velocity --- group velocity --- signal processing --- SH0 mode --- circumferential scanning --- synthetic aperture focusing --- exploding reflector model --- Lamb wave --- local wavenumber --- air-coupled transducer --- wavenumber domain filtering --- hybrid and non-contact system --- signal processing --- SNR --- split-spectrum processing --- ultrasonic guided waves --- signal processing --- defect detection --- spatial domain --- array analysis --- pipeline inspection --- ultrasonic guided waves (UGWs) --- metamaterial --- resonator --- low-frequency --- lamb wave --- adaptive filtering --- leaky normalized mean square --- ultrasonic guided waves --- pipeline inspection --- SNR enhancement --- signal processing --- guided wave --- multi-wire cable --- wave structure --- contact acoustic nonlinearity --- energy transfer --- rail --- ultrasonic guided wave --- semi-analytical finite element --- single mode extraction algorithm --- defect location --- signal processing --- defect detection --- torsional wave --- power spectrum --- sliding window --- pipeline inspection --- ultrasonic guided-waves (UGWs) --- magnetostrictive patch transducer --- shear mode --- soft magnetic patch --- dynamic magnetic field optimization --- signal strength enhancement --- acoustic emission --- nondestructive testing --- leakage location --- fault diagnosis --- n/a --- lamb waves --- composite --- ultrasonic testing --- numerical modelling --- pressure vessels

Non-destructive Testing of Materials in Civil Engineering

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ISBN: 9783039216901 / 9783039216918 Year: Pages: 448 DOI: 10.3390/books978-3-03921-691-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Abstract

This book was proposed and organized as a means to present recent developments in the field of nondestructive testing of materials in civil engineering. For this reason, the articles highlighted in this editorial relate to different aspects of nondestructive testing of different materials in civil engineering—from building materials to building structures. The current trend in the development of nondestructive testing of materials in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. From this point of view, interesting results with significance for building practices have been obtained

Keywords

non-destructive testing --- masonry structures --- strengthening --- ultrasonic tomography --- adhesion assessment --- autoclaved aerated concrete (AAC) --- compressive strength --- shape and size of specimen --- moisture of AAC --- ultrasonic testing --- gantry crane --- RMF technique --- civil engineering --- fibre-cement boards --- non-destructive testing --- acoustic emission --- degree of degradation --- thermovision --- active thermography --- thermal contrast --- defect detection --- location of inclusions --- non-destructive testing --- materials research --- building partition --- cement-based composites --- fiber cement boards --- durability --- ultrasound measurements --- spun concrete --- micro-computed tomography --- nanoindentation --- deconvolution --- mathematical morphology --- non-destructive evaluation --- structural damage --- natural frequency --- singular value truncation --- multiple feedbacks --- data noise --- NDT methods --- rebar location --- eddy-current method --- GPR method --- concrete --- concrete mix design --- concrete strength prediction --- data mining --- machine learning --- timber structures --- non-destructive methods --- ultrasonic wave --- stress wave --- drilling resistance --- X-ray micro-computed tomography --- waste brick dust --- adsorption --- lead --- cesium --- surface complexation --- precipitation --- solid-state NMR spectroscopy --- Lamb waves --- scanning laser vibrometry --- adhesive joints --- non-destructive testing --- damage detection --- excitation frequency --- nondestructive testing --- thermography --- monitoring of structures --- reinforced concrete chimney --- corrosion processes --- service life of a structure --- viscoelastic parameters --- creep test --- fatigue tests --- asphalt mixtures --- Burgers model --- four point bending beam --- pattern recognition --- acoustic emission --- Structural Health Monitoring --- brittle fracture --- diagnostics --- non-destructive testing --- reinforced concrete grandstand stadium --- vibration analysis --- crowd-induced excitation --- structural tuning --- concrete slabs and floorings --- horizontal casting --- compressive strength --- ultrasonic tests --- fibre-cement boards --- non-destructive testing --- acoustic emission --- artificial neural networks --- SEM --- non-destructive method --- damage --- mercury intrusion porosimetry --- X-ray computed tomography --- acoustic emission AE --- acoustic spectrum --- quasi brittle cement composites --- destruction process --- resistance measurement --- wood moisture sensing --- non-destructive testing --- moisture safety --- cellulose fibre cement boards --- microstructure --- nanoindentation --- SEM-EDS analysis --- temperature --- concrete elements --- concrete strength --- reinforced concrete tanks --- concrete corrosion --- sulphate corrosion --- ultrasound tests --- rebound hammer --- SilverSchmidt --- concrete --- compressive strength --- non-destructive testing --- non-destructive testing --- diagnostic --- acoustic methods --- ultrasound --- building materials --- defects

Intelligent Imaging and Analysis

Authors: ---
ISBN: 9783039219209 / 9783039219216 Year: Pages: 492 DOI: 10.3390/books978-3-03921-921-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:08
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Imaging and analysis are widely involved in various research fields, including biomedical applications, medical imaging and diagnosis, computer vision, autonomous driving, and robot controls. Imaging and analysis are now facing big changes regarding intelligence, due to the breakthroughs of artificial intelligence techniques, including deep learning. Many difficulties in image generation, reconstruction, de-noising skills, artifact removal, segmentation, detection, and control tasks are being overcome with the help of advanced artificial intelligence approaches. This Special Issue focuses on the latest developments of learning-based intelligent imaging techniques and subsequent analyses, which include photographic imaging, medical imaging, detection, segmentation, medical diagnosis, computer vision, and vision-based robot control. These latest technological developments will be shared through this Special Issue for the various researchers who are involved with imaging itself, or are using image data and analysis for their own specific purposes.

Keywords

image inspection --- non-referential method --- feature extraction --- fault pattern learning --- weighted kernel density estimation (WKDE) --- rail surface defect --- UAV image --- defect detection --- gray stretch maximum entropy --- image enhancement --- defect segmentation --- semi-automatic segmentation --- MR spine image --- vertebral body --- graph-based segmentation --- correlation --- surface defect of steel sheet --- image segmentation --- saliency detection --- low-rank and sparse decomposition --- intervertebral disc --- segmentation --- convolutional neural network --- fine grain segmentation --- U-net --- deep learning --- magnetic resonance image --- lumbar spine --- image adjustment --- colorfulness --- contrast --- sharpness --- high dynamic range --- local registration --- iterative closest points --- multimodal medical image registration --- machine vision --- point cloud registration --- greedy projection triangulation --- local correlation --- three-dimensional imaging --- optimization arrangement --- cavitation bubble --- water hydraulic valve --- defect inspection --- image processing --- feature extraction --- classification methods --- medical image registration --- image alignment in medical images --- misalignment correction in MRI --- midsagittal plane extraction --- symmetry detection --- PCA --- conformal mapping --- mesh parameterization --- mesh partitioning --- pixel extraction --- texture mapping --- image analysis --- image retrieval --- spatial information --- image classification --- computer vision --- image restoration --- motion deburring --- image denoising --- sparse feedback --- Image processing --- segmentation --- spline --- grey level co-occurrence matrix --- gradient detection --- threshold selection --- OpenCV --- machine learning --- transfer learning --- Inception-v3 --- geological structure images --- convolutional neural networks --- image segmentation --- active contour model --- level set --- signed pressure force function --- image segmentation --- deep learning --- synthetic aperture radar (SAR) --- oil slicks --- segnet --- pectus excavatum --- nuss procedure --- patient-specific nuss bar --- minimally invasive surgery --- computerized numerical control bending machine --- computer-aided design --- computer-aided manufacturing --- statistical body shape model --- self-intersection penalty term --- 3D pose estimation --- 3D semantic mapping --- incrementally probabilistic fusion --- CRF regularization --- road scenes --- deep learning --- medical image classification --- additional learning --- CT image --- automatic training --- GoogLeNet --- intelligent evaluation --- automated cover tests --- deviation of strabismus --- pupil localization --- shape from focus --- wear measurement --- sprocket teeth --- normal distribution operator image filtering --- adaptive evaluation window --- reverse engineering --- human parsing --- depth-estimation --- computational efficiency --- capacity optimization --- underwater visual localization method --- line segment features --- PL-SLAM --- face sketch synthesis --- face sketch recognition --- joint training model --- data imbalance --- Contrast Tomography (CT) --- pre-training strategy --- segmentation --- super-resolution --- dual-channel --- residual block --- convolutional kernel parameter --- long-term and short-term memory blocks --- n/a

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