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The COVID-19 Pandemic, Problematic Internet Use, Post-traumatic Stress and Mental Health
The COVID-19 pandemic has caused tremendous loss of human life and disruption of normal daily activities across the globe. The COVID-19 pandemic can be traumatic and have short-term and long-term influences on individual behaviors and well-being. To contain and control the spread of COVID-19, various public health and social measures (e.g., social distancing, quarantine, isolation, and extensive lockdown of cities) have been implemented in countries worldwide. With such social and environmental changes, the prolonged feelings of fear, worry, stress, and the lack of social activities and interaction may greatly increase the prevalence of mental health issues (e.g., anxiety and depression). Nowadays, Internet has permeated into everyone’s life, which may play an increasingly important role in coping with COVID-19 related stress and anxiety. However, the increasing reliance on the Internet may lead to problematic Internet use (PIU), prolonged screen time, and sedentary lifestyles, and pose great risks to public health.
Advances in Neuroergonomics and Cognitive Engineering
This book offers a broad perspective on the field of cognitive engineering and neuroergonomics, covering emerging practices and future trends toward the harmonious integration of human operators with computational systems. It reports on novel theoretical findings on mental workload and stress, activity theory, human reliability, error and risk, and neuroergonomic measures alike, together with a wealth of cutting-edge applications. Further, the book describes key advances in our understanding of cognitive processes, including mechanisms of perception, memory, reasoning, and motor response, with a special emphasis on their role in interactions between humans and other elements of computer-based systems. Based on the AHFE’s main track on Neuroergonomics and Cognitive Engineering, held on July 17–21, 2017 in Los Angeles, California, USA, it provides readers with a comprehensive overview of the current challenges in cognitive computing and factors influencing human performance.
Federated Learning
Federated Learning: Theory and Practice provides a holistic treatment to federated learning, starting with a broad overview on federated learning as a distributed learning system with various forms of decentralized data and features. A detailed exposition then follows of core challenges and practical modeling techniques and solutions, spanning a variety of aspects in communication efficiency, theoretical convergence and security, viewed from different perspectives. Part II features emerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service, and Part III and IV present a wide array of industrial applications of federated l...
