It is entering an era of big data, which facilitated great improvement in various sectors. Particularly, assisted by wireless communications and mobile computing, mobile devices have emerged with a great potential to renovate the healthcare industry. Although the advanced techniques will make it possible to understand what is happening in our body more deeply, it is extremely difficult to handle and process the big health data anytime and anywhere. Therefore, data analytics and mobile computing are significant for the healthcare systems to meet many technical challenges and problems that need to be addressed to realize this potential. Furthermore, the advanced healthcare systems have to be upgraded with new capabilities such as machine learning, data analytics, and cognitive power for providing human with more intelligent and professional healthcare services. To explore recent advances and disseminate state-of-the-art techniques related to data analytics and mobile computing on designing, building, and deploying novel technologies, to enable intelligent healthcare services and applications, this paper presents the detailed design for developing intelligent healthcare systems assisted by data analytics and mobile computing. Moreover, some representative intelligent healthcare applications are discussed to show that data analytics and mobile computing are available to enhance the performance of the healthcare services.

It is entering an era of big data, which facilitated great improvement in various sectors. Particularly, assisted by wireless communications and mobile computing, mobile devices have emerged with a great potential to renovate the healthcare industry. Although the advanced techniques will make it possible to understand what is happening in our body more deeply, it is extremely difficult to handle and process the big health data anytime and anywhere. Therefore, data analytics and mobile computing are significant for the healthcare systems to meet many technical challenges and problems that need to be addressed to realize this potential. Furthermore, the advanced healthcare systems have to be upgraded with new capabilities such as machine learning, data analytics, and cognitive power for providing human with more intelligent and professional healthcare services. To explore recent advances and disseminate state-of-the-art techniques related to data analytics and mobile computing on designing, building, and deploying novel technologies, to enable intelligent healthcare services and applications, this paper presents the detailed design for developing intelligent healthcare systems assisted by data analytics and mobile computing. Moreover, some representative intelligent healthcare applications are discussed to show that data analytics and mobile computing are available to enhance the performance of the healthcare services.

The thermal management is an important issue for AlGaN/GaN high-electron-mobility transistors (HEMTs). In this work, the influence of the diamond layer on the electrical characteristics of AlGaN/GaN HEMTs is investigated by simulation. The results show that the lattice temperature can be effectively decreased by utilizing the diamond layer. With increasing the drain bias, the diamond layer plays a more significant role for lattice temperature reduction. It is also observed that the diamond layer can induce a negative shift of threshold voltage and an increase of transconductance. Furthermore, the influence of the diamond layer thickness on the frequency characteristics is investigated as well. By utilizing the 10-μm-thickness diamond layer in this work, the cutoff frequency fT and maximum oscillation frequency fmax can be increased by 29% and 47%, respectively. These results demonstrate that the diamond layer is an effective technique for lattice temperature reduction and the study can provide valuable information for HEMTs in high-power and high-frequency applications.

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The features and application ranges of several database design proposals applied in SaaS are discussed. Based on shared database / shared framework, three relationship-based extension models which are custom field, pre-allocation field and name-value pairs and XML based extension model are discussed and the latter implementation approach in data definition, query and update is also given, along with some examples to illustrate its feasibility.