A hybrid analysis of LBSN data to early detect anomalies in crowd dynamics

Undoubtedly, Location-based Social Networks (LBSNs) provide an interesting source of geo-located data that we have previously used to obtain patterns of the dynamics of crowds throughout urban areas. According to our previous results, activity in LBSNs reflects the real activity in the city. Therefore, unexpected behaviors in the social media activity are a trustful evidence of unexpected changes of the activity in the city. In this paper we introduce a hybrid solution to early detect these changes based on applying a combination of two approaches, the use of entropy analysis and clustering techniques, on the data gathered from LBSNs. In particular, we have performed our experiments over a data set collected from Instagram for seven months in New York City, obtaining promising results.This work is funded by: the European Regional Development Fund (ERDF) and the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC), Spain, the Spanish Ministry of Economy and Competitiveness under the National Science Program (TEC2014-54335-C4-3-R, TEC2014-54335-C4-2-R, TEC2017-84197-C4-3-R and TEC2017-84197-C4-2-R), and by the Madrid Regional Government eMadrid Excellence Network, Spain (S2013/ICE-2715)

INRISCO: INcident monitoRing in Smart COmmunities

Major advances in information and communication technologies (ICTs) make citizens to be considered as sensors in motion. Carrying their mobile devices, moving in their connected vehicles or actively participating in social networks, citizens provide a wealth of information that, after properly processing, can support numerous applications for the benefit of the community. In the context of smart communities, the INRISCO [1] proposal intends for (i) the early detection of abnormal situations in cities (i.e., incidents), (ii) the analysis of whether, according to their impact, those incidents are really adverse for the community; and (iii) the automatic actuation by dissemination of appropriate information to citizens and authorities. Thus, INRISCO will identify and report on incidents in traffic (jam, accident) or public infrastructure (e.g., works, street cut), the occurrence of specific events that affect other citizens' life (e.g., demonstrations, concerts), or environmental problems (e.g., pollution, bad weather). It is of particular interest to this proposal the identification of incidents with a social and economic impact, which affects the quality of life of citizens.This work was supported in part by the Spanish Government through the projects INRISCO under Grant TEC2014-54335-C4-1-R, Grant TEC2014-54335-C4-2-R, Grant TEC2014-54335-C4-3-R, and Grant TEC2014-54335-C4-4-R, in part by the MAGOS under Grant TEC2017-84197-C4-1-R, Grant TEC2017-84197-C4-2-R, and Grant TEC2017-84197-C4-3-R, in part by the European Regional Development Fund (ERDF), and in part by the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC)

Advanced practices: micro learning, practice oriented teaching and gamified learning

The development, introduction and evaluation of ICT based techniques have been at the forefront of educational reform of all levels for the last two decades. Microlearning, gamified learning are two novel ICT techniques most appropriate for e-learning material and programs which attracted renewed attention because of the CoVID-19 social distancing measures. Alongside those, the more established technique of practice-oriented learning is being revisited to adapt to the new challenges. This article presents the main results and conclusions of deliverable 3.1. of the ERASMUS+ Capacity Building for Higher Education project “Electrical Energy Markets and Engineering Education (ELEMEND)” which is devoted to training partner staff in micro learning, practice oriented teaching and gamified learning. After the goals of ELEMEND are presented in the light of modern engineering education, the concept of micro learning as a training paradigm is discussed. Next, gamification technology is described in view of its role in the educational process and specific implementation examples are given. Finally, the practice-oriented approach both in teaching and in learning with the methods used to carry on this approach is presented

Transverse-momentum and pseudorapidity distributions of charged hadrons in pppp collisions at s\sqrt{s} = 7 TeV

Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at $\sqrt{s} = 7$~TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit-pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity \dnchdeta|_{|\eta| < 0.5} = 5.78\pm 0.01\stat\pm 0.23\syst for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from $\sqrt{s} = 0.9$ to 7~TeV is 66.1\%\pm 1.0\%\stat\pm 4.2\%\syst. The mean transverse momentum is measured to be 0.545\pm 0.005\stat\pm 0.015\syst\GeVc. The results are compared with similar measurements at lower energies.Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at sqrt(s) = 7 TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit-pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity, dN(charged)/d(eta), for |eta| < 0.5, of 5.78 +/- 0.01 (stat) +/- 0.23 (syst) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from sqrt(s) = 0.9 to 7 TeV is 66.1% +/- 1.0% (stat) +/- 4.2% (syst). The mean transverse momentum is measured to be 0.545 +/- 0.005 (stat) +/- 0.015 (syst) GeV/c. The results are compared with similar measurements at lower energies

Measurement of the charge ratio of atmospheric muons with the CMS detector

We present a measurement of the ratio of positive to negative muon fluxes from cosmic ray interactions in the atmosphere, using data collected by the CMS detector both at ground level and in the underground experimental cavern at the CERN LHC. Muons were detected in the momentum range from 5 GeV/ c to 1 TeV/ c . The surface flux ratio is measured to be 1.2766±0.0032(stat.)±0.0032(syst.) , independent of the muon momentum, below 100 GeV/ c . This is the most precise measurement to date. At higher momenta the data are consistent with an increase of the charge ratio, in agreement with cosmic ray shower models and compatible with previous measurements by deep-underground experiments.We present a measurement of the ratio of positive to negative muon fluxes from cosmic ray interactions in the atmosphere, using data collected by the CMS detector both at ground level and in the underground experimental cavern at the CERN LHC. Muons were detected in the momentum range from 5 GeV/c to 1 TeV/c. The surface flux ratio is measured to be 1.2766 \pm 0.0032(stat.) \pm 0.0032 (syst.), independent of the muon momentum, below 100 GeV/c. This is the most precise measurement to date. At higher momenta the data are consistent with an increase of the charge ratio, in agreement with cosmic ray shower models and compatible with previous measurements by deep-underground experiments

Observation of Long-Range, Near-Side Angular Correlations in Proton-Proton Collisions at the LHC

Results on two-particle angular correlations for charged particles emitted in proton-proton collisions at center-of-mass energies of 0.9, 2.36, and 7 TeV are presented, using data collected with the CMS detector over a broad range of pseudorapidity (eta) and azimuthal angle ($\phi$). Short-range correlations in $\Delta\eta$, which are studied in minimum bias events, are characterized using a simple "independent cluster" parametrization in order to quantify their strength (cluster size) and their extent in $\eta$ (cluster decay width). Long-range azimuthal correlations are studied differentially as a function of charged particle multiplicity and particle transverse momentum using a 980 inverse nb data set at 7 TeV. In high multiplicity events, a pronounced structure emerges in the two-dimensional correlation function for particle pairs with intermediate transverse momentum of 1-3 GeV/c, 2.0 < |$\Delta\eta$| < 4.8 and $\Delta\phi \approx 0$. This is the first observation of such a long-range, near-side feature in two-particle correlation functions in $pp$ or $p\overline{p}$ collisions.Results on two-particle angular correlations for charged particles emitted in proton-proton collisions at center-of-mass energies of 0.9, 2.36, and 7 TeV are presented, using data collected with the CMS detector over a broad range of pseudorapidity (eta) and azimuthal angle (phi). Short-range correlations in Delta(eta), which are studied in minimum bias events, are characterized using a simple 'independent cluster' parametrization in order to quantify their strength (cluster size) and their extent in eta (cluster decay width). Long-range azimuthal correlations are studied differentially as a function of charged particle multiplicity and particle transverse momentum using a 980 inverse nb data set at 7 TeV. In high multiplicity events, a pronounced structure emerges in the two-dimensional correlation function for particle pairs with intermediate transverse momentum of 1-3 GeV/c, 2.0< |Delta(eta)| <4.8 and Delta(phi) near 0. This is the first observation of such a long-range, near-side feature in two-particle correlation functions in pp or p p-bar collisions