No Arabic abstract
Tablet computers are widely used by young children. A report in 2016 shows that children aged 5 to 15 years are spending more time online than watching TV. A 2017 update of the same report shows that parents are becoming more concerned about their childrens online risks compared to the previous year. Parents are working hard to protect their childrens online safety. An increasing number of parents are setting up content filtering at home or having regular discussions with their children regarding online risks. However, although risks related to Social Media platforms or social video sharing sites (like YouTube) are widely known, risks posed by mobile applications or games (i.e. `apps) are less known. Behind the cute characters, apps used by children can not only have the possibility of exposing them to age-inappropriate content or excessive in-app promotions, but may also make a large amount of their personal information accessible to third-party online marketing and advertising industry. Such practices are not unique to childrens apps, but young children are probably less capable of resisting the resulting personalised advertisements and game promotions. In this report, we present findings from our online survey of 220 parents with children aged 6-10, mainly from the U.K. and other western countries, regarding their privacy concerns and expectations of their childrens use of mobile apps. Parents play a key role in childrens use of digital technology, especially for children under 10 years old. Recent reports have highlighted parents lack of sufficient support for choosing appropriate digital content for their children. Our report sheds some initial light on parents key struggles and points to immediate steps and possible areas of future development.
Driven by the popularity of the Android system, Android app markets enjoy a booming prosperity in recent years. One critical problem for modern Android app markets is how to prevent apps that are going to receive low ratings from reaching end users. For this purpose, traditional approaches have to publish an app first and then collect enough user ratings and reviews so as to determine whether the app is favored by end users or not. In this way, however, the reputation of the app market has already been damaged. To address this problem, we propose a novel technique, i.e., Sextant , to detect low rating Android apps based on the .apk files.With our proposed technique, an Android app market can prevent from risking its reputation on exposing low rating apps to users. Sextant is developed based on novel static analysis techniques as well as machine learning techniques. In our study, our proposed approach can achieve on average 90.50% precision and 94.31% recall.
Children are increasingly using the internet nowadays. While internet use exposes children to various privacy and security risks, few studies have examined how parents perceive and address their childrens cybersecurity risks. To address this gap, we conducted a qualitative study with 25 parents living in Norway with children aged between 10 to 15. We conducted semi-structured interviews with the parents and performed a thematic analysis of the interview data. The results of this paper include a list of cybersecurity awareness needs for children from a parental perspective, a list of learning resources for children, and a list of challenges for parents to ensure cybersecurity at home. Our results are useful for developers and educators in developing cybersecurity solutions for children. Future research should focus on defining cybersecurity theories and practices that contribute to childrens and parents awareness about cybersecurity risks, needs, and solutions.
In this early draft, we describe a decentralized, app-based approach to COVID-19 vaccine distribution that facilitates zero knowledge verification, dynamic vaccine scheduling, continuous symptoms reporting, access to aggregate analytics based on population trends and more. To ensure equity, our solution is developed to work with limited internet access as well. In addition, we describe the six critical functions that we believe last mile vaccination management platforms must perform, examine existing vaccine management systems, and present a model for privacy-focused, individual-centric solutions.
The use of emergent constraints to quantify uncertainty for key policy relevant quantities such as Equilibrium Climate Sensitivity (ECS) has become increasingly widespread in recent years. Many researchers, however, claim that emergent constraints are inappropriate or even under-report uncertainty. In this paper we contribute to this discussion by examining the emergent constraints methodology in terms of its underpinning statistical assumptions. We argue that the existing frameworks are based on indefensible assumptions, then show how weakening them leads to a more transparent Bayesian framework wherein hitherto ignored sources of uncertainty, such as how reality might differ from models, can be quantified. We present a guided framework for the quantification of additional uncertainties that is linked to the confidence we can have in the underpinning physical arguments for using linear constraints. We provide a software tool for implementing our general framework for emergent constraints and use it to illustrate the framework on a number of recent emergent constraints for ECS. We find that the robustness of any constraint to additional uncertainties depends strongly on the confidence we can have in the underpinning physics, allowing a future framing of the debate over the validity of a particular constraint around the underlying physical arguments, rather than statistical assumptions.
Classical turning surfaces of Kohn-Sham potentials, separating classically-allowed regions (CARs) from classically-forbidden regions (CFRs), provide a useful and rigorous approach to understanding many chemical properties of molecules. Here we calculate such surfaces for several paradigmatic solids. Our study of perfect crystals at equilibrium geometries suggests that CFRs are absent in metals, rare in covalent semiconductors, but common in ionic and molecular crystals. A CFR can appear at a monovacancy in a metal. In all materials, CFRs appear or grow as the internuclear distances are uniformly expanded. Calculations with several approximate density functionals and codes confirm these behaviors. A classical picture of conduction suggests that CARs should be connected in metals, and disconnected in wide-gap insulators. This classical picture is confirmed in the limits of extreme uniform compression of the internuclear distances, where all materials become metals without CFRs, and extreme expansion, where all materials become insulators with disconnected and widely-separated CARs around the atoms.