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Three-dimensional printing, or additive manufacturing, is an emerging manufacturing process. Research and development are being performed worldwide to provide a better understanding of the science and technology of 3D printing to make high-quality parts in a cost-effective and time-efficient manner. This book includes contemporary, unique, and impactful research on 3D printing from leading organizations worldwide.

Technology: general issues --- metal additive manufacturing --- directed energy deposition --- alloy design --- elemental powder mixture --- advanced materials --- composition control --- porosity --- additive technology --- SLM --- computer tomography --- additive manufacture --- SLM Ti-6Al-4V --- variability --- anisotropy --- fatigue crack growth --- Ti-6Al-4V alloy --- laser powder bed fusion --- powder bed temperature --- microstructure evolution --- mechanical properties --- additive manufacturing --- pore --- pulsed emission --- X-ray imaging --- non-spherical --- hydride-dehydride (HDH) Ti-6Al-4V powder --- post-process heat treatment --- microstructure --- ductile fracture --- stress state --- Ti-6Al-4V --- 316L stainless steel --- soft materials --- smart materials --- stretchable devices --- FRP --- 3D printing --- defense --- FDM --- topology optimization --- neural network --- neural style transfer --- binder jetting --- sands --- vacuum thermoforming --- fiber reinforced composite --- n/a

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Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now, with the advent of wearable, mobile, and ubiquitous technologies, that we can aim to sense and recognize emotions, continuously and in real time. This book brings together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and the recognition of human emotions.

self-management interview application --- emotion analysis --- facial recognition --- image-mining --- deep convolutional neural network --- emotion recognition --- pattern recognition --- texture descriptors --- mobile tool --- neuromarketing --- brain computer interface (BCI) --- consumer preferences --- EEG signal --- deep learning --- deep neural network (DNN) --- electroencephalogram (EEG) --- logistic regression --- Gaussian kernel --- Laplacian prior --- affective computing --- human–robot interaction --- thermal IR imaging --- social robots --- facial expression analysis --- line segment feature analysis --- dimensionality reduction --- convolutional recurrent neural network --- driver health risk --- intelligent speech signal processing --- human computer interaction --- supervised learning --- computer vision --- optical flow --- micro facial expressions --- real-time processing --- driver stress state --- IR imaging --- machine learning --- support vector machine (SVR) --- advanced driver-assistance systems (ADAS) --- artificial intelligence --- image processing --- video processing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now, with the advent of wearable, mobile, and ubiquitous technologies, that we can aim to sense and recognize emotions, continuously and in real time. This book brings together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and the recognition of human emotions.

Information technology industries --- self-management interview application --- emotion analysis --- facial recognition --- image-mining --- deep convolutional neural network --- emotion recognition --- pattern recognition --- texture descriptors --- mobile tool --- neuromarketing --- brain computer interface (BCI) --- consumer preferences --- EEG signal --- deep learning --- deep neural network (DNN) --- electroencephalogram (EEG) --- logistic regression --- Gaussian kernel --- Laplacian prior --- affective computing --- human–robot interaction --- thermal IR imaging --- social robots --- facial expression analysis --- line segment feature analysis --- dimensionality reduction --- convolutional recurrent neural network --- driver health risk --- intelligent speech signal processing --- human computer interaction --- supervised learning --- computer vision --- optical flow --- micro facial expressions --- real-time processing --- driver stress state --- IR imaging --- machine learning --- support vector machine (SVR) --- advanced driver-assistance systems (ADAS) --- artificial intelligence --- image processing --- video processing --- self-management interview application --- emotion analysis --- facial recognition --- image-mining --- deep convolutional neural network --- emotion recognition --- pattern recognition --- texture descriptors --- mobile tool --- neuromarketing --- brain computer interface (BCI) --- consumer preferences --- EEG signal --- deep learning --- deep neural network (DNN) --- electroencephalogram (EEG) --- logistic regression --- Gaussian kernel --- Laplacian prior --- affective computing --- human–robot interaction --- thermal IR imaging --- social robots --- facial expression analysis --- line segment feature analysis --- dimensionality reduction --- convolutional recurrent neural network --- driver health risk --- intelligent speech signal processing --- human computer interaction --- supervised learning --- computer vision --- optical flow --- micro facial expressions --- real-time processing --- driver stress state --- IR imaging --- machine learning --- support vector machine (SVR) --- advanced driver-assistance systems (ADAS) --- artificial intelligence --- image processing --- video processing