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Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries.

Technology: general issues --- History of engineering & technology --- fault detection --- deep learning --- transfer learning --- anomaly detection --- bearing --- wind turbines --- misalignment --- fault diagnosis --- information fusion --- improved artificial bee colony algorithm --- LSSVM --- D–S evidence theory --- optimal bandwidth --- kernel density estimation --- JS divergence --- domain adaptation --- partial transfer --- subdomain --- rotating machinery --- gearbox --- signal interception --- peak extraction --- cubic spline interpolation envelope --- combined fault diagnosis --- empirical wavelet transform --- grey wolf optimizer --- low pass FIR filter --- support vector machine --- satellite momentum wheel --- Huffman-multi-scale entropy (HMSE) --- support vector machine (SVM) --- adaptive particle swarm optimization (APSO) --- rail surface defect detection --- machine vision --- YOLOv4 --- MobileNetV3 --- multi-source heterogeneous fusion --- n/a --- D-S evidence theory

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Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries.

Technology: general issues --- History of engineering & technology --- fault detection --- deep learning --- transfer learning --- anomaly detection --- bearing --- wind turbines --- misalignment --- fault diagnosis --- information fusion --- improved artificial bee colony algorithm --- LSSVM --- D-S evidence theory --- optimal bandwidth --- kernel density estimation --- JS divergence --- domain adaptation --- partial transfer --- subdomain --- rotating machinery --- gearbox --- signal interception --- peak extraction --- cubic spline interpolation envelope --- combined fault diagnosis --- empirical wavelet transform --- grey wolf optimizer --- low pass FIR filter --- support vector machine --- satellite momentum wheel --- Huffman-multi-scale entropy (HMSE) --- support vector machine (SVM) --- adaptive particle swarm optimization (APSO) --- rail surface defect detection --- machine vision --- YOLOv4 --- MobileNetV3 --- multi-source heterogeneous fusion

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This Special Issue is intended to lay the foundation of AI applications focusing on oral health, including general dentistry, periodontology, implantology, oral surgery, oral radiology, orthodontics, and prosthodontics, among others.

machine learning --- artificial intelligence --- malocclusion --- diagnostic imaging --- active learning --- maxillary sinusitis --- convolutional neural network --- deep learning --- segmentation --- oral microbiota --- LEfSe --- PCoA --- alloprevotella --- prevotella --- core microbiota --- artificial neural networks --- oral cancer diagnosis --- oral cancer prediction --- pit and fissure sealants --- caries assessment --- visual examination --- clinical evaluation --- convolutional neural networks --- transfer learning --- deep learning network --- YOLOv4 --- mandibular third molar --- inferior alveolar nerve --- contact relationship --- panoramic radiograph --- deep learning methods --- caries diagnosis --- dental panoramic images --- radiography --- Fourier transform infrared spectroscopy --- FTIR imaging --- spectral biomarker --- multivariate analysis --- discriminant model --- oral squamous cell carcinoma --- oral epithelial dysplasia --- oral potentially malignant disorder --- risk stratification --- early oral cancer detection --- dentigerous cysts --- histopathology images --- image classification --- odontogenic keratocysts --- radicular cysts --- AI --- screening --- diagnosis --- dentistry --- ultrasonography --- tongue --- algorithm --- dysphagia --- impacted --- tooth --- detection --- neural networks --- proximal caries --- training strategy --- small dataset --- periapical radiograph --- X-ray --- tooth extraction --- oroantral fistula --- operative planning --- n/a

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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network

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• Reference Manager
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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network