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Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

online signature verification --- shape contexts --- function features --- SC-DTW --- symbolic representation --- two-stage method --- finger features --- multimodal recognition --- local coding --- Gabor filter --- LGS --- human identification --- biomarker --- ECG --- machine learning --- Physionet --- Lviv Biometric Dataset --- biometry --- identification --- bloodstream --- image recognition --- multi-biometrics --- bit planes --- block --- mutual information --- cross-device --- dorsal hand vein recognition --- person re-identification --- superpixel --- temporally aligned pooling --- walking cycle --- automatic recognition --- face --- voice --- body motion --- autism spectrum disorder (ASD) --- assessment --- intervention --- curve similarity --- curve similarity model --- curve similarity transformation --- similarity distance --- segmentation matching --- evolutionary computation --- finger vein recognition --- hand vein recognition --- contactless acquisition device --- public vascular pattern dataset --- biometric recognition performance evaluation --- face verification --- optical correlation --- Hausdorff distance --- image classification --- face detection --- depth map ensemble --- filtering --- geometric deep learning --- ear detection --- structured prediction --- semantic segmentation --- rotation equivariance --- Gaussian mixture model --- superpixels --- face recognition systems --- person identification --- biometric systems --- survey --- automatic signature verification --- touch-screen sensor --- data quality --- enrollment phase --- performance assessment --- augmented signature --- security enhancement --- mobile conditions --- biometric recognition --- visible light iris images --- image quality assessment --- image covariates --- quality filtering --- vascular biometric recognition --- wrist vein recognition --- contactless dataset --- pattern recognition --- infrared camera --- non-contact devices --- Scale-Invariant Feature Transform (SIFT®) --- Speeded Up Robust Features (SURF®) --- Oriented FAST and Rotated BRIEF (ORB) --- fingerprint --- presentation attack detection --- deep learning

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Disasters such as earthquakes, cyclones, floods, heat waves, nuclear accidents, and large-scale pollution incidents take lives and incur major health problems. The majority of large-scale disasters affect the most vulnerable populations, which often comprise extreme ages, remote living areas, and endemic poverty, as well as people with low literacy. Health emergency and disaster risk management (Health-EDRM) refers to the systematic analysis and management of health risks surrounding emergencies and disasters, and plays an important role in reducing the hazards and vulnerability along with extending preparedness, responses, and recovery measures. This concept encompasses risk analyses and interventions, such as accessible early warning systems, the timely deployment of relief workers, and the provision of suitable drugs and medical equipment to decrease the impact of disasters on people before, during, and after an event (or events). Currently, there is a major gap in the scientific literature regarding Health-EDRM to facilitate major global policies and initiatives for disaster risk reduction worldwide.

infection spread and control --- infection risk --- human behavior --- close contact --- sensor-based --- indoor environment --- indoor positioning --- head and body motion --- open-plan office --- disaster --- psychosocial impacts --- community resilience --- Kumamoto earthquake --- DMHISS --- disaster psychiatry --- Japan --- acute mental health needs --- duration of activity --- DPAT (Disaster Psychiatric Assistance Team) --- cold --- personal health protective behaviour --- associated factors --- risk perception --- subtropical city --- disaster responders --- support --- psychosocial --- risk management --- COVID-19 --- urban --- health risks --- Health-Emergency and Disaster Risk Management --- biological hazard --- pandemic --- PHEIC --- Hong Kong --- Fukushima nuclear accident --- mass media --- Internet --- public health practice --- community mental health services --- typhoon --- hurricane --- cyclone --- strong wind levels --- natural disaster --- Health-EDRM --- risk-taking behaviour --- sensation seeking --- landslide displacement --- predictive uncertainty --- ensemble prediction --- probability combination scheme --- quantile regression neural networks (QRNNs) --- kernel density estimation (KDE) --- Daegu --- sense of belonging --- pride --- mental health --- disaster relief fund --- non-communicable disease --- self-care --- NCD management --- home care --- early phase of pandemic --- health-EDRM --- primary prevention --- vector-borne disease --- biological hazards --- climate change --- narrative review --- Asia Pacific --- Health EDRM --- long-term impact --- public health --- case study --- disaster management --- multi-case analysis --- Europe --- flood --- elderly --- cardiovascular diseases --- cerebrovascular diseases --- H-EDRM --- extreme temperature --- socioeconomic vulnerability --- health disparities --- n/a