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Colon, Sigmoid --- Diagnostic imaging.

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Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

keyframes --- time-delay --- whale optimization algorithm --- multilevel thresholding --- multi-exposure image fusion --- additive manufacturing --- patch structure decomposition --- ultra-sound images --- 3D scanning --- Arimoto entropy --- contrast enhancement --- spatial filling factor --- depth maps --- image processing --- 3D prints --- differential evolution --- field of experts --- normalized divergence measure --- image privacy --- multiscale top-hat transform --- q-exponential --- texture information entropy --- diffusion --- hybrid algorithm --- Weibull statistics --- adaptive selection --- nonextensive entropy --- computer aided diagnostics --- fatty liver --- random forest --- DNA encoding --- low contrast --- entropy --- Minkowski island --- fuzzy entropy --- free-form deformations --- person re-identification --- chaotic system --- DNA computing --- pavement --- information entropy --- discrete entropy --- Tsallis statistics --- video skimming --- prime-indexed primes --- natural scene statistics (NSS) --- Hénon map --- q-sigmoid --- image entropy --- Shannon entropy --- macrotexture --- Shannon’s entropy --- binary image --- multi-feature fusion --- image analysis --- uncertainty assessment --- non-rigid registration --- hash layer --- Cantor set --- dynamic filtering --- deep neural network --- security analysis --- multiple-image encryption --- Hamming distance --- blind image quality assessment (BIQA) --- q-Gaussian --- remote sensing --- decay trend --- chaotic cryptography --- chaotic strategy --- cross-entropy loss --- random insertion --- metabolic syndrome --- sign languages --- generalized entropies --- relevance feedback --- image retrieval --- two-dimensional chaotic economic map --- cryptanalysis --- infrared images --- 3D Latin cube --- SHA-256 hash value --- gradient distributions --- structural entropy --- discrete cosine transform (DCT) --- chaotic map --- hepatic steatosis --- machine vision --- electromagnetic field optimization --- security --- image segmentation --- quantization loss --- colonoscopy --- video summarization --- permutation --- Kapur’s entropy --- surface quality assessment --- permutation-diffusion --- Ramanujan primes --- Rényi entropies --- chosen-plaintext attack --- image encryption --- dynamic index --- color image segmentation --- ultrasound --- Otsu method --- sigmoid --- reconstruction --- image information entropy --- 3-D digital imaging --- positron emission tomography --- medical imaging

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Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs.

TROOP --- truck platooning --- path planning --- kalman filter --- V2V communication --- string stability --- off-tracking --- articulated cargo trucks --- kabsch algorithm --- potential field --- sigmoid curve --- autonomous vehicles --- connected and autonomous vehicles --- artificial neural networks --- end-to-end learning --- multi-task learning --- urban vehicle platooning --- simulation --- attention --- executive control --- simulated driving --- task-cuing experiment --- electroencephalogram --- fronto-parietal network --- object vehicle estimation --- radar accuracy --- data-driven --- radar latency --- weighted interpolation --- autonomous vehicle --- urban platooning --- vehicle-to-vehicle communication --- in-vehicle network --- analytic hierarchy architecture --- traffic scenes --- object detection --- multi-scale channel attention --- attention feature fusion --- collision warning system --- ultra-wideband --- dead reckoning --- time to collision --- vehicle dynamic parameters --- Unscented Kalman Filter --- multiple-model --- electric vehicle --- unified chassis control --- unsprung mass --- autonomous driving --- trajectory tracking --- real-time control --- model predictive control --- tyre blow-out --- yaw stability --- roll stability --- vehicle dynamics model --- n/a

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Metalliferous minerals play a central role in the global economy. They will continue to provide the raw materials we need for industrial processes. Significant challenges will likely emerge if the climate-driven green and low-carbon development transition of metalliferous mineral exploitation is not managed responsibly and sustainably. Green low-carbon technology is vital to promote the development of metalliferous mineral resources shifting from extensive and destructive mining to clean and energy-saving mining in future decades. Global mining scientists and engineers have conducted a lot of research in related fields, such as green mining, ecological mining, energy-saving mining, and mining solid waste recycling, and have achieved a great deal of innovative progress and achievements. This Special Issue intends to collect the latest developments in the green low-carbon mining field, written by well-known researchers who have contributed to the innovation of new technologies, process optimization methods, or energy-saving techniques in metalliferous minerals development.

Technology: general issues --- History of engineering & technology --- Mining technology & engineering --- metallurgical slag-based binders --- solidification/stabilisation --- As(III) --- As(V) --- calcium hydroxide --- sublevel caving --- numerical simulation --- physical model --- structural parameter --- green mining --- limestone --- high temperature --- confining pressure --- SHPB --- constitutive model --- open-pit mine --- PLAXIS 3D --- dynamic load --- safety factor --- acceleration --- particle sedimentation --- filling mining --- degree of influence --- pipeline transportation --- solid waste utilization --- tailings --- reclamation risk --- hazard identification --- complex network --- hazard management --- digital mine --- mine short-term production planning --- haulage equipment dispatch plan --- ABCA --- NSGA --- settlement velocity measurement --- K-means --- tailings backfill --- unsupervised learning --- cemented paste backfill --- ESEM --- picture processing --- floc networks --- pumping agent --- fractal dimension --- backfill slurry --- strength of cemented backfill --- inhomogeneity of cemented backfill --- cemented tailings backfill --- copper --- zinc --- recovery --- sulfide concentrate --- artificial microbial community --- granular backfill --- bearing characteristics --- numerical model --- particle size --- surface subsidence --- blasting dust movement --- dust concentration --- particle size distribution --- blasting dust reduction --- backfill --- metal mine --- log-sigmoid --- tailings pond --- regional distribution --- dam break --- accident statistics --- causation analysis --- backfilling --- increasing resistance and reducing pressure --- computational fluid dynamics --- spiral pipe --- stowing gradient --- coal-based solid waste --- orthogonal experiment --- strength development --- regression analysis --- engineering performance --- n/a

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The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is nowadays possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability and to serve their intended purpose. However, old unsolved problematics as well as new challenges exist. Furthermore, unprecedented conditions, such as stricter safety requirements and ageing civil infrastructure, pose new challenges for confrontation. Therefore, this Special Issue gathers the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring in dealing with old and new aspects of this ever-growing research field.

dynamic characteristic --- GB-RAR --- super high-rise building --- displacement --- wheel flat --- real-time monitoring --- strain distribution characteristics --- multisensor array --- precise positioning --- noncontact remote sensing (NRS) --- optical flow algorithm --- structural health monitoring (SHM) --- uniaxial automatic cruise acquisition device --- noise robustness --- sensitivity analysis --- cross-modal strain energy --- damage detection --- subspace system identification --- data-driven stochastic subspace identification (SSI-DATA) --- covariance-driven stochastic subspace identification (SSI-COV) --- combined subspace system identification --- PRISMA --- vibration-based damage detection --- crack damage detection --- piezoelectric impedance --- piezoelectric admittance --- peak frequency --- Bayesian inference --- uncertainty quantification --- masonry structures --- seismic structural health monitoring --- Bouc–Wen model --- model calibration --- hysteretic system identification --- BOTDR --- CFRP sheet --- un-bonded position --- cover delamination --- interfacial de-bonding --- monitoring system --- pipeline --- health and structural integrity --- Particle Impact Damper --- adaptive-passive damping --- damping of vibrations --- experiments --- submerged floating tunnel --- deep neural network --- machine learning --- sensor optimization --- failure monitoring accuracy --- mooring line --- sigmoid function --- Adamax --- categorical cross-entropy --- bending test --- bridge --- “compression–softening” theory --- frequency --- inverse problem --- nondestructive testing (NDT) method --- prestressed concrete (PC) girder --- prestress force determination --- prestress loss --- vertical deflection measurement --- rail --- guided wave ultrasound --- broken rail detection --- rail diagnostics --- structural health monitoring --- non destructive testing --- shape sensing --- inverse Finite Element Method --- fiber optics --- full-field reconstruction --- Structural Health Monitoring --- extreme function theory --- non-destructive testing --- extreme value theory --- generalised extreme distribution --- n/a --- Bouc-Wen model --- "compression-softening" theory