Guest Editorial Preface Deep Learning, Ubiquitous, and Toy Computing

Alvaro Joffre Uribe Quevedo, Patrick C. K. Hung, Shih-Chia Huang, Sarajane Marques Peres
2018 Computers in Entertainment  
The pervasive nature of digital technologies as witnessed in industry, services, and everyday life has given rise to an emergent, data-focused economy stemming from many aspects of human individual and ubiquitous applications. The richness and vastness of these data are creating unprecedented research opportunities in many fields, including urban studies, geography, economics, finance, entertainment, and social science, as well as physics, biology and genetics, public health, and many other
more » ... t devices. In addition to data, text, and machine mining research, businesses and policymakers have seized on deep learning technologies to support their decisions and proper growing smart application needs. As businesses build out emerging hardware and software infrastructure, it becomes increasingly important to anticipate technical and practical challenges and to identify best practices learned through experience in this research area. Deep learning employs software tools from advanced analytics disciplines such as data mining, predictive analytics, text, and machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers with complex structures or nonlinear transformations. At the same time, the processing and analysis of deep learning applications present methodological and technological challenges. Further, deep learning applications have an advantage by a rise in sensing technologies as witnessed in both the number of sensors and the rich diversity of sensors ranging from cell phones, personal computers, and health tracking appliances to Internet of Things technologies designed to give contextual, semantic data to entities in a ubiquitous environment that previously could not contribute intelligence to key decisions and smart devices. Recently, deep learning technologies have been applied to toy computing. Toy computing is a recently developing concept that transcends the traditional toy into a new area of computer research using ubiquitous technologies. A toy in this context can be effectively considered a computing device or peripheral called Smart Toys. We invite research and industry papers related to these specific challenges and others that are driving innovation in deep learning, ubiquitous, and toy computing. The goal of this special issue is to present both novel and industrial solutions to challenging technical issues, as well as compelling smart application use cases. This special issue shares related practical experiences to benefit the reader and provides clears proof that deep learning technologies are playing an ever-increasing important and critical role in supporting ubiquitous and toy computing applications-a new cross-discipline research topic in computer science, decision science, and information systems. All eight papers in this issue will have deep research results. In the first article, "Pegadas: A Portal for Management and Activities Planning With Games and Environments for Education in Health," focus on developing a Web portal that offers services for organizing and sequencing serious games and virtual environments that allow evaluating the performance of the user. The portal presents the potential of taking advantage of serious games for education and training in health by presenting a comprehensive approach that may help to assist the planning, management, and evaluation of user-oriented health activities. The work also presents a flexible approach that allows integrating different serious games and virtual environments that may have further applications in other fields.
doi:10.1145/3180663 fatcat:5nah7uctfze2doh5xnzzd7zq7i