Context-aware systems in a smart space environment must be aware of the surrounding contexts and adapt to changing contexts in highly dynamic environments. Data managements of contextual information are different from traditional approaches because of the contextual information are dynamic, transient, and fallible. Consequently, capabilities to detect context inconsistency and maintain consiste...

Although many context-aware systems have been developed, little attention has been paid to building a uniform framework of a Context Base and Context Base Management Systems (CBMS). Consequently, each context-aware system has to be built from the ground up. It is important that context-aware systems share context data across different domains and with all devices or services. Therefore, context...

In ubiquitous computing the provisioning of context-aware services is typically aided by a context provisioning middleware. The essential functionalities undertaken by the middleware include distributed data acquisition from sensors, context modelling, context synthesis, reasoning and context dissemination. This paper focuses on the evaluation methodologies of context-aware systems that aim to ...

Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices, especially for real time image-based analysis. Increasingly, multi-faced knowledge is extracted by executing multiple DNNs inference models, e.g., identifying objects, faces, and genders from images. It paramount importance to guarantee low response times such multi-DNN executions as it af...

 Recommender systems are a branch of retrieval systems and information matching, which through identifying the interests and requires of the user, help the users achieve the desired information or service through a massive selection of choices. In recent years, the recommender systems apply describing information in the terms of the user, such as location, time, and task, in order to produce re...