Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V;E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K, and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios.
Researchers at the University of Washington have devised a new app for smart speakers like Amazon's Echo to help parents monitor their baby's breathing. Called BreathJunior, the experimental app will be able to measure the rate of a baby's breathing and detect symptoms of sleep apnea. The team initially conducted a test of the device with five babies in the neonatal intensive care unit at a hospital in Washington. BreathJunior (pictured above) is an experimental app that monitors a baby's breathing using a smart speaker According to a report from MIT Tech Review, the team plans to eventually release the app as a commercial product via the company Sound Life Sciences. But first, they'll present the results of the trial at the upcoming MobiCom, a yearly conference on mobile computing in Los Cabos, Mexico.
People who use dating apps such as Tinder may be up to 27 times as likely to use drastic or unhealthy techniques to try and stay slim. Deliberately vomiting, taking laxatives and even using anabolic steroids is more common among dating app users, a study found. Researchers found'unrealistic' desires to look like celebrities on television and social media are driving people to damaging behaviour. And with an estimated 50million people around the world signed up to Tinder the scientists warned experts must better understand its damaging effects. Researchers said social media and TV shows reinforce'ideal' body images which drive men to try and become more muscly and women slimmer, which may drive them to drastic weight loss measures (Pictured: Love Island contestants Anton Danyluk and Amber Gill – the show is well-known for displaying young people with extremely honed bodies.
Parimbelli, Enea (University of Ottawa) | Pala, Daniele (University of Pavia) | Bellazzi, Riccardo (University of Pavia) | Vera-Munoz, Cecilia (Universidad Politecnica de Madrid) | Casella, Vittorio (University of Pavia)
The percentage of the world’s population living in urban areas is projected to increase significantly in the next decades. This makes the urban environment the perfect bench for research aiming to manage and respond to dramatic demographic and epidemiological transitions. In this context the PULSE project has partnered with five global cities to transform public health from a reactive to a predictive system focused on both risk and resilience. PULSE aims at producing an integrated data ecosystem based on continuous large-scale collection of information available within the smart city environment. The integration of environmental data, citizen science and location-specific predictive modeling of disease onset allows for richer analytics that promote informed, data-driven health policy decisions. In this paper we describe the PULSE ecosystem, with a special focus on its WebGIS component and its prototype version based on New York city data.
Data integration is central in Web application development because these applications typically deal with a variety of information formats. Ontology-driven applications face the additional challenge of integrating these multiple formats with the information stored in ontologies. A number of mappings are required to reconcile the variety of formats to produce a coherent overall system. To address these mappings we have developed a number of open source tools that support transformations between some of the common formats encountered when developing an ontology-driven Web application. The Semantic Web Rule Language (SWRL) is a central building block in these tools. We describe these tools and illustrate their use in the development of a prototype Web-based application.