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This explorative study aims to gain insight about which privacy settings and features on the interfaces are commonly used by Facebook users. User data was collected using an online survey. Based on the survey data, a set of the commonly used privacy strategies on Facebook were identified. We found that these strategies were mainly used to manage three types of privacy concerns: 1) personal profile visibility, 2) personal networking boundary, and 3) personal privacy awareness. A point-biserial correlation analysis revealed that only networking privacy strategies were significantly correlated with the feeling of control users felt in mitigating hackers, blackmailers, stalkers as well as compromising relations and job positions. Hence, when the goal of the sites is to empower users for protecting their privacy, it is important to understand how users make decisions with the help of these privacy settings and features on user interfaces. Implications of these findings as well as suggestions for future research are discussed.Social network sites; privacy settings; sense of control; privacy design

This paper discusses about lips and eyebrows are used to detect driver cognitive distraction by using faceAPI toolkit. A few number of classification algorithms like Support Vector Machine (SVM), Logistic Regression (LR) and Static Bayesian Network (SBN) and Dynamic Bayesian Network (DBN) have been used for accuracy rate comparison.