A Knowledge-Based Deep Learning Architecture for Aspect-Based Sentiment Analysis.

The task of sentiment analysis tries to predict the affective state of a document by examining its content and metadata through the application of machine learning techniques. Recent advances in the field consider sentiment to be a multi-dimensional quantity that pertains to different interpretations (or aspects), rather than a single one. Based on earlier research, the current work examines the said task in the framework of a larger architecture that crawls documents from various online sources.

A Novel Approach to Image Recoloring for Color Vision Deficiency.

In this paper, a novel method to modify color images for the protanopia and deuteranopia color vision deficiencies is proposed. The method admits certain criteria, such as preserving image naturalness and color contrast enhancement. Four modules are employed in the process.

IoT Contextual Factors on Healthcare.

With the emergence of the Internet of Things, new services in healthcare will be available and existing systems will be integrated in the IoT framework, providing automated medical supervision and efficient medical treatment. Context awareness plays a critical role in realizing the vision of the IoT, providing rich contextual information that can help the system act more efficiently. Since context in healthcare has its unique characteristics, it is necessary to define an appropriate context aware framework for healthcare IoT applications.