Gauhar Ali

This research paper presents the prediction of the visual attention area on a visual display using an evolving rule-based fuzzy model: evolving Takagi–Sugeno (eTS). The evolving fuzzy model is feasible for predicting the visual attention area because of its non-iterative, recursive, online, and real-time nature. Visual attention area prediction through a web camera is a problem that requires online adaptive systems with higher accuracy and greater performance. The proposed approach using an evolving fuzzy model to predict the eye-gaze attention area on a visual display in an ambient environment (to provide further services) mimics the human cognitive process and its flexibility to generate fuzzy rules without any prior knowledge. The proposed Visual Attention Area Prediction using Evolving Neuro-Fuzzy Systems (VAAPeNFS) approach can quickly generate compact fuzzy rules from new data. Numerical experiments conducted in a simulated environment further validate the performance and accuracy of the proposed model. To validate the model, the forecasting results of the eTS model are compared with DeTS and ANFIS. The result shows high accuracy, transparency and flexibility achieved by applying the evolving online versions compared to other offline techniques. The proposed approach significantly reduces the computational overhead, which makes it suitable for any sort of AmI application. Thus, using this approach, we achieve reusability, robustness, and scalability with better performance with high accuracy.

Credibility, in general, can be interpreted as a sense of trust in someone. The credibility of information remarkably influences the public’s willingness to do or not to do some things. In this research study, the credibility of digital news stories can be interpreted as the sense of confidence a person has in a source of available information that affects their behavior. Humans spread less credible information instead of more credible information very quickly because humans take an interest in fear, disgust, and surprise. Less credible news may affect individuals as well as economies. Therefore, there is a dire need in the current digital era to find out what affects the credibility of digital news stories. This study aims to review the published literature and the grey literature to determine the factors affecting digital news credibility and the factors that build credibility in digital news stories. In this paper, we have developed a multivocal literature review protocol to assess the credibility of digital news stories. The multivocal literature review is an advanced version of the systematic literature review that searches for grey literature in addition to the published literature. The expected outcomes after implementing our protocol will be a list of credibility factors and their practices that can play a vital role in ensuring the credibility of digital news stories. Based on this protocol, we formulated guidelines for the quality assessment of grey literature. The future direction of this research is to analyze the factors through multi-criteria decision-making (MCDM), i.e., analytical hierarchical process.