Making smart cities smarter using artificial intelligence techniques for smarter mobility

The term Smart City is tipically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter. As example we will describe the usage of Artificial Intellgence techniques to provide Smart Mobility in the context of the SUPERHUB Project.Postprint (published version

Social network data analysis for event detection

Cities concentrate enough Social Network (SN) activity to empower rich models. We present an approach to event discovery based on the information provided by three SN, minimizing the data properties used to maximize the total amount of usable data. We build a model of the normal city behavior which we use to detect abnormal situations (events). After collecting half a year of data we show examples of the events detected and introduce some applications.Peer ReviewedPostprint (published version

tweetStimuli : discovering social structure of influence

Social influence has become a field of study about how people might induce effect on others. Diffusion of information in large networks has been studied to analyze how the information flows over the network producing cascades as a main proxy of influence. For instance, microblogs such as Twitter has allowed to identify and rank influencers based on message propagation (retweets). Different factors of influence on Twitter have been identified such as: audience, interaction, users’ actions and message content. In this paper, a new web application is presented. It allows to study these factors in a temporal order based on the perspective of local influence: given a target user, who influences the user as well as who has been influenced by the user. This application is able to retrieve all retweets and favorites to filter and rank them from different perspectives based on the type of tweets and attributes such as mentions or hashtags, as well as two kind of visualizations: clusters and networks which are the outcome of user behavior by retweeting and marking as favorites

Discovering social structures of local influence by using tweetStimuli

Information diffusion in large-scale networks has been studied to identify the users influence. The influence has been targeted as a key feature either to reach large populations or influencing public opinion. Through the use of micro-blogs, such as Twitter, global influencers have been identified and ranked based on message propagation (retweets). In this paper, a new application is presented, which allows to find first and classify then the local influence on Twitter: who have influenced you and who have been influenced by you. Until now, social structures of tweets’ original authors that have been either retweeted or marked as favourites are unobservable. Throughout this application, these structures can be discovered and they reveal the existence of communities formed by users of similar profile (that are connected among them) interrelated with other similar profile users’ communitiesPeer Reviewe

Discovering social structures of local influence by using tweetStimuli

Information diffusion in large-scale networks has been studied to identify the users influence. The influence has been targeted as a key feature either to reach large populations or influencing public opinion. Through the use of micro-blogs, such as Twitter, global influencers have been identified and ranked based on message propagation (retweets). In this paper, a new application is presented, which allows to find first and classify then the local influence on Twitter: who have influenced you and who have been influenced by you. Until now, social structures of tweets’ original authors that have been either retweeted or marked as favourites are unobservable. Throughout this application, these structures can be discovered and they reveal the existence of communities formed by users of similar profile (that are connected among them) interrelated with other similar profile users’ communitiesPeer Reviewe

tweetStimuli : discovering social structure of influence

Social influence has become a field of study about how people might induce effect on others. Diffusion of information in large networks has been studied to analyze how the information flows over the network producing cascades as a main proxy of influence. For instance, microblogs such as Twitter has allowed to identify and rank influencers based on message propagation (retweets). Different factors of influence on Twitter have been identified such as: audience, interaction, users’ actions and message content. In this paper, a new web application is presented. It allows to study these factors in a temporal order based on the perspective of local influence: given a target user, who influences the user as well as who has been influenced by the user. This application is able to retrieve all retweets and favorites to filter and rank them from different perspectives based on the type of tweets and attributes such as mentions or hashtags, as well as two kind of visualizations: clusters and networks which are the outcome of user behavior by retweeting and marking as favorites

Bone loss at implant with titanium abutments coated by soda lime glass containing silver nanoparticles: A histological study in the dog

This is an open-access article distributed under the terms of the Creative Commons Attribution License.The aim of the present study was to evaluate bone loss at implants connected to abutments coated with a soda-lime glass containing silver nanoparticles, subjected to experimental peri-implantitis. Also the aging and erosion of the coating in mouth was studied. Five beagle dogs were used in the experiments. Three implants were placed in each mandible quadrant: in 2 of them, Glass/n-Ag coated abutments were connected to implant platform, 1 was covered with a Ti-mechanized abutment. Experimental peri-implantitis was induced in all implants after the submarginal placement of cotton ligatures, and three months after animals were euthanatized. Thickness and morphology of coating was studied in abutment cross-sections by SEM. Histology and histo-morphometric studies were carried on in undecalfied ground slides. After the induced peri-implantitis: 1.The abutment coating shown losing of thickness and cracking. 2. The histometry showed a significant less bone loss in the implants with glass/n-Ag coated abutments. A more symmetric cone of bone resorption was observed in the coated group. There were no significant differences in the peri-implantitis histological characteristics between both groups of implants. Within the limits of this in-vivo study, it could be affirmed that abutments coated with biocide soda-lime-glass-silver nanoparticles can reduce bone loss in experimental peri-implantitis. This achievement makes this coating a suggestive material to control peri-implantitis development and progression. © 2014 Martinez et al.This work was supported by the Spanish Ministry of Science and Innovation (MICINN) under the projects MAT2009-14542-C02-01 and MAT2012-38645. B. Cabal thanks the CSIC JAE-Doc Program for a postdoctoral contract.Peer Reviewe

The challenge and impact of nuclear physics

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