… by big data, artificial intelligence, the internet of things, and a … of artificial intelligence and
machine learning into energy tech… study have solved the endogenous problems, and the results …

… A review of urban computing for mobile phone traces: current methods, challenges and …
for semi-supervised learning. Proc 32 nd AAAI Conf on Artificial Intelligence, p.3538-3545. …

… challenges and opportunities faced by the Internet of Things field. The corresponding solutions
… Security and Privacy issues in the vehicle IoT environment; 2. Bayesian inference model …

… has outlined a blueprint for our future world, where individuals can … and delves into the
security and privacy issues that may arise in … and identity addressing in Internet of Things[J]. IEEE …

… of machine learning and deep learning. Finally, reflections and summaries on current research
issues were presented, and future … of Internet of things ( IoT): current analysis, challenges, …

… in Artificial Intelligence (AI)-based technologies and services. … empirical model for multi-collinearity
issues. All the constructs’ … Lexicon-based training, supervised learning methods, and …

… role in the country's comprehensive security strategy. By studying … variety of technologies to
develop solutions for privacy protection. … Future iterations will address this by incorporating a …

… sets are a challenging bottleneck for deep learning research. … Chapter 3 gives brief information
about deep learning … analysis was performed for future research. The impacts of the semi-…

… , federated learning (FL) is a distributed machine learning framework … services by sensing
the raw data from IoT devices such as … In view of above challenges, wetakethe model quality as …

… To address these challenges, we leverage federated reinforcement learning techniques. …
a promising approach to mitigate burst traffic challenges in information-centric environments. …