Search

We analyze the binary-state (either ? or ?) k-majority dynamics in a biased communication model where nodes have some fixed probability p, independent of the dynamics, of being seen in state ? by their neighbors. In this setting we study how p, as well as the initial unbalance between the two states, impact on the speed of convergence of the process, identifying sharp phase transitions.

We analyze the binary-state (either ℛ or ℬ) k-majority dynamics in a biased communication model where nodes have some fixed probability p, independent of the dynamics, of being seen in state ℬ by their neighbors. In this setting we study how p, as well as the initial unbalance between the two states, impact on the speed of convergence of the process, identifying sharp phase transitions.

Consider a graph where each of the $n$ nodes is either in state $\mathcal{R}$ or $\mathcal{B}$. Herein, we analyze the \emph{synchronous $k$-Majority dynamics}, where in each discrete-time round nodes simultaneously sample $k$ neighbors uniformly at random with replacement and adopt the majority state among those of the nodes in the sample (breaking ties uniformly at random). Differently from previous work, we study the robustness of the $k$-Majority in \emph{maintaining a $\mathcal{R}$ majority}, when the dynamics is subject to two forms of \emph{bias} toward state $\mathcal{B}$. The bias models an external agent that attempts to subvert the initial majority by altering the communication between nodes, with a probability of success $p$ in each round: in the first form of bias, the agent tries to alter the communication links by transmitting state $\mathcal{B}$; in the second form of bias, the agent tries to corrupt nodes directly by making them update to $\mathcal{B}$. Our main result shows a \emph{sharp phase transition} in both forms of bias. By considering initial configurations in which every node has probability $q \in (\frac{1}{2},1]$ of being in state $\mathcal{R}$, we prove that for every $k\geq3$ there exists a critical value $p_{k,q}^*$ such that, with high probability, the external agent is able to subvert the initial majority either in $n^{\omega(1)}$ rounds, if $pp_{k,q}^*$. When $k<3$, instead, no phase transition phenomenon is observed and the disruption happens in $O(1)$ rounds for $p>0$., Comment: Preliminary versions published in DISC 2020 (Brief Announcement) and ICDCN 2021. Full version published in Distributed Computing

We investigate opinion dynamics in multi-agent networks when a bias toward one of two possible opinions exists; for example, reflecting a status quo vs a superior alternative. Starting with all agents sharing an initial opinion representing the status quo, the system evolves in steps. In each step, one agent selected uniformly at random adopts the superior opinion with some probability $\alpha$, and with probability $1 - \alpha$ it follows an underlying update rule to revise its opinion on the basis of those held by its neighbors. We analyze convergence of the resulting process under two well-known update rules, namely majority and voter. The framework we propose exhibits a rich structure, with a non-obvious interplay between topology and underlying update rule. For example, for the voter rule we show that the speed of convergence bears no significant dependence on the underlying topology, whereas the picture changes completely under the majority rule, where network density negatively affects convergence. We believe that the model we propose is at the same time simple, rich, and modular, affording mathematical characterization of the interplay between bias, underlying opinion dynamics, and social structure in a unified setting., Comment: The paper has appeared in the Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. The SOLE copyright holder is IJCAI (International Joint Conferences on Artificial Intelligence), all rights reserved. Link to the proceedings: https://www.ijcai.org/Proceedings/2020/8

Spectral techniques have proved amongst the most effective approaches to graph clustering. However, in general they require explicit computation of the main eigenvectors of a suitable matrix (usually the Laplacian matrix of the graph). Recent work (e.g., Becchetti et al., SODA 2017) suggests that observing the temporal evolution of the power method applied to an initial random vector may, at least in some cases, provide enough information on the space spanned by the first two eigenvectors, so as to allow recovery of a hidden partition without explicit eigenvector computations. While the results of Becchetti et al. apply to perfectly balanced partitions and/or graphs that exhibit very strong forms of regularity, we extend their approach to graphs containing a hidden k partition and characterized by a milder form of volume-regularity. We show that the class of k-volume regular graphs is the largest class of undirected (possibly weighted) graphs whose transition matrix admits k "stepwise" eigenvectors (i.e., vectors that are constant over each set of the hidden partition). To obtain this result, we highlight a connection between volume regularity and lumpability of Markov chains. Moreover, we prove that if the stepwise eigenvectors are those associated to the first k eigenvalues and the gap between the k-th and the (k+1)-th eigenvalues is sufficiently large, the Averaging dynamics of Becchetti et al. recovers the underlying community structure of the graph in logarithmic time, with high probability.

Spectral techniques have proved amongst the most effective approaches to graph clustering. However, in general they require explicit computation of the main eigenvectors of a suitable matrix (usually the Laplacian matrix of the graph). Recent work (e.g., Becchetti et al., SODA 2017) suggests that observing the temporal evolution of the power method applied to an initial random vector may, at least in some cases, provide enough information on the space spanned by the first two eigenvectors, so as to allow recovery of a hidden partition without explicit eigenvector computations. While the results of Becchetti et al. apply to perfectly balanced partitions and/or graphs that exhibit very strong forms of regularity, we extend their approach to graphs containing a hidden k partition and characterized by a milder form of volume-regularity. We show that the class of k-volume regular graphs is the largest class of undirected (possibly weighted) graphs whose transition matrix admits k "stepwise" eigenvectors (i.e., vectors that are constant over each set of the hidden partition). To obtain this result, we highlight a connection between volume regularity and lumpability of Markov chains. Moreover, we prove that if the stepwise eigenvectors are those associated to the first k eigenvalues and the gap between the k-th and the (k+1)-th eigenvalues is sufficiently large, the Averaging dynamics of Becchetti et al. recovers the underlying community structure of the graph in logarithmic time, with high probability.

Spectral techniques have proved amongst the most effective approaches to graph clustering. However, in general they require explicit computation of the main eigenvectors of a suitable matrix (usually the Laplacian matrix of the graph). Recent work (e.g., Becchetti et al., SODA 2017) suggests that observing the temporal evolution of the power method applied to an initial random vector may, at least in some cases, provide enough information on the space spanned by the first two eigenvectors, so as to allow recovery of a hidden partition without explicit eigenvector computations. While the results of Becchetti et al. apply to perfectly balanced partitions and/or graphs that exhibit very strong forms of regularity, we extend their approach to graphs containing a hidden $k$ partition and characterized by a milder form of volume-regularity. We show that the class of $k$-volume-regular graphs is the largest class of undirected (possibly weighted) graphs whose transition matrix admits $k$ "stepwise" eigenvectors (i.e., vectors that are constant over each set of the hidden partition). To obtain this result, we highlight a connection between volume regularity and lumpability of Markov chains. Moreover, we prove that if the stepwise eigenvectors are those associated to the first $k$ eigenvalues and the gap between the $k$-th and the ($k$+1)-th eigenvalues is sufficiently large, the averaging dynamics of Becchetti et al. recovers the underlying community structure of the graph in logarithmic time, with high probability., Comment: Preliminary version appeared in Proceedings of ISAAC 2019

El texto presenta una experiencia didáctica interdisciplinar que se está llevando a cabo en el Campus Terracini de la Università di Bologna (por miembros académicos de la Universidad de Bolonia investigadores del centro ENEA y de la Universitat Politècnica de València). La actividad se centra en la realización de un pequeño pabellón, sede del Trasition Team, un grupo experimental, involucrados en temáticas ambientales y sostenibles, internas y externas a la dinámica académica del Campus. Para ello, se ha estructurado una experiencia didáctica constructiva, centrada en este caso, en el empleo de materiales locales, que cumplen con requisitos determinados, prestaciones energéticas e impacto sostenible. Gracias a esta experiencia participativa de autoconstrucción, basada en la aplicación, análisis y definición del LCA de algunos materiales constructivos se está experimentando una propuesta didáctica alternativa, basada en el concepto de clase inversa o flipped classroom, crucial para futuros profesionales vinculados directa e indirectamente al mundo de la construcción., The paper outlines a didactic project undertaken at Campus Terracini (University of Bolonia Italy) thanks to local staff members and with the support of researchers from ENEA agency, Italy and professors of Polytechnic University of Valencia, Spain. The activity tries to To make sustainability transitions happen, considering that it is crucial not only to have a strategic planning processes committed by the top management, but also to encourage community engagement, approaching and promoting a bottom-up process. For this reason the project is concerning the layout of a small pavilion, head quarter of Transition Team (a multifunction group involved in sustainability plan of Unibo). To meet environmental performances, the space is planned with the use of appropriate building technologies, employing low impact and local materials. In addition, the space is realized in auto-construction, in order to strengthen the involvement of final users, the students. This paper will show an evaluation of appropriate building technologies with an LCA approach, combined with flipped classroom didactic methodology.

Nel corso del mio lavoro di ricerca mi sono occupata di identificare strategie che permettano il risparmio delle risorse a livello edilizio e di approfondire un metodo per la valutazione ambientale di tali strategie. La convinzione di fondo è che bisogna uscire da una visione antropocentrica in cui tutto ciò che ci circonda è merce e materiale a disposizione dell’uomo, per entrare in una nuova era di equilibrio tra le risorse della terra e le attività che l’uomo esercita sul pianeta. Ho quindi affrontato il tema dell’edilizia responsabile approfondendo l’ambito delle costruzioni in balle di paglia e terra. Sono convinta che l’edilizia industriale abbia un futuro molto breve davanti a sé e lascerà inevitabilmente spazio a tecniche non convenzionali che coinvolgono materiali di semplice reperimento e posa in opera. Sono altresì convinta che il solo utilizzo di materiali naturali non sia garanzia di danni ridotti sull’ecosistema. Allo stesso tempo ritengo che una mera certificazione energetica non sia sinonimo di sostenibilità. Per questo motivo ho valutato le tecnologie non convenzionali con approccio LCA (Life Cycle Assessment), approfondendo gli impatti legati alla produzione, ai trasporti degli stessi, alla tipologia di messa in opera, e ai loro possibili scenari di fine vita. Inoltre ho approfondito il metodo di calcolo dei danni IMPACT, identificando una carenza nel sistema, che non prevede una categoria di danno legata alle modifiche delle condizioni idrogeologiche del terreno. La ricerca si è svolta attraverso attività pratiche e sperimentali in cantieri di edilizia non convenzionale e attività di ricerca e studio sull’LCA presso l’Enea di Bologna (Ing. Paolo Neri)., During my research period I worked to find strategies that assure saving resources in building field. I also worked to examine in depth a method for environmental evaluation of those strategies. I believe that human being has to leave the actual anthropocentric vision, in which all around us there is merchandise at our disposal. We have to entry into a new age of equilibrium between natural resources and human activities. I analyzed straw and clay as raw materials for sustainable buildings. In my opinion, industrialized construction building has to go flat and leave enough space for non conventional techniques and materials. I believe that we have to do more than only use natural materials in buildings. I believe also that energetic certification is not synonymous with reliability towards an eco-friendly product. For those reasons, I evaluated non conventional techniques with an LCA approach, analyzing impact in production phase, transporting, construction phase, end of life scenarios. Furthermore I studied IMPACT methodology for damage assessment and I find that there is a lack: the method doesn’t consider a damage category linked to human modification to natural hydrogeological conditions. I carried out the research through practical and experimental activities in construction sites, and LCA studies at Enea_Bologna (Ing. Paolo Neri).

Nel corso del mio lavoro di ricerca mi sono occupata di identificare strategie che permettano il risparmio delle risorse a livello edilizio e di approfondire un metodo per la valutazione ambientale di tali strategie. La convinzione di fondo è che bisogna uscire da una visione antropocentrica in cui tutto ciò che ci circonda è merce e materiale a disposizione dell’uomo, per entrare in una nuova era di equilibrio tra le risorse della terra e le attività che l’uomo esercita sul pianeta. Ho quindi affrontato il tema dell’edilizia responsabile approfondendo l’ambito delle costruzioni in balle di paglia e terra. Sono convinta che l’edilizia industriale abbia un futuro molto breve davanti a sé e lascerà inevitabilmente spazio a tecniche non convenzionali che coinvolgono materiali di semplice reperimento e posa in opera. Sono altresì convinta che il solo utilizzo di materiali naturali non sia garanzia di danni ridotti sull’ecosistema. Allo stesso tempo ritengo che una mera certificazione energetica non sia sinonimo di sostenibilità. Per questo motivo ho valutato le tecnologie non convenzionali con approccio LCA (Life Cycle Assessment), approfondendo gli impatti legati alla produzione, ai trasporti degli stessi, alla tipologia di messa in opera, e ai loro possibili scenari di fine vita. Inoltre ho approfondito il metodo di calcolo dei danni IMPACT, identificando una carenza nel sistema, che non prevede una categoria di danno legata alle modifiche delle condizioni idrogeologiche del terreno. La ricerca si è svolta attraverso attività pratiche e sperimentali in cantieri di edilizia non convenzionale e attività di ricerca e studio sull’LCA presso l’Enea di Bologna (Ing. Paolo Neri)., During my research period I worked to find strategies that assure saving resources in building field. I also worked to examine in depth a method for environmental evaluation of those strategies. I believe that human being has to leave the actual anthropocentric vision, in which all around us there is merchandise at our disposal. We have to entry into a new age of equilibrium between natural resources and human activities. I analyzed straw and clay as raw materials for sustainable buildings. In my opinion, industrialized construction building has to go flat and leave enough space for non conventional techniques and materials. I believe that we have to do more than only use natural materials in buildings. I believe also that energetic certification is not synonymous with reliability towards an eco-friendly product. For those reasons, I evaluated non conventional techniques with an LCA approach, analyzing impact in production phase, transporting, construction phase, end of life scenarios. Furthermore I studied IMPACT methodology for damage assessment and I find that there is a lack: the method doesn’t consider a damage category linked to human modification to natural hydrogeological conditions. I carried out the research through practical and experimental activities in construction sites, and LCA studies at Enea_Bologna (Ing. Paolo Neri).

Syndromic surveillance is a new mechanism utilized to detect naturally occurring and bioterroristic outbreaks. The public health significance is its potential to alert public health to outbreaks earlier and allow a timelier public health response. It involves monitoring data that can be collected in near real-time to find anomalous data. Syndromic surveillance includes school and work absenteeism, over-the-counter drug sales, and hospital admissions data to name a few. This study is an assessment of an extension of the use of syndromic surveillance as an improvement to the traditional method to detect more routine public health problems, specifically, the detection of influenza outbreaks. The assessment involves the prediction of outbreaks in four areas during the period October 15, 2003 to March 31, 2004. The four areas studied included Allegheny County, Pennsylvania, Jefferson County, Kentucky, Los Angeles County, California, and Salt Lake County, Utah. Two aspects of community activity were used as the method for syndromic surveillance, over-the-counter pharmaceutical sales and hospital chief complaints. The over-the-counter sales encompassed a panel of six items including anti-diarrheal medication, anti-fever adult medication, anti-fever pediatric medication, cough and cold products, electrolytes, and thermometers. Additionally, two of the seven hospital chief complaints used in the RODS open source paradigm were monitored. These were constitutional and respiratory chief complaints. Application of standard statistical algorithms showed that the system was able to identify unusual activity several weeks prior to the time when the local health departments were able to identify an outbreak using the standard methods. The largest improvement in detection using syndromic surveillance occurred in Los Angeles where the outbreak was detected 52 days before the Centers for Disease Control had declared widespread activity for the state. In each county over-the-counter sal

Syndromic surveillance is a new mechanism utilized to detect naturally occurring and bioterroristic outbreaks. The public health significance is its potential to alert public health to outbreaks earlier and allow a timelier public health response. It involves monitoring data that can be collected in near real-time to find anomalous data. Syndromic surveillance includes school and work absenteeism, over-the-counter drug sales, and hospital admissions data to name a few. This study is an assessment of an extension of the use of syndromic surveillance as an improvement to the traditional method to detect more routine public health problems, specifically, the detection of influenza outbreaks. The assessment involves the prediction of outbreaks in four areas during the period October 15, 2003 to March 31, 2004. The four areas studied included Allegheny County, Pennsylvania, Jefferson County, Kentucky, Los Angeles County, California, and Salt Lake County, Utah. Two aspects of community activity were used as the method for syndromic surveillance, over-the-counter pharmaceutical sales and hospital chief complaints. The over-the-counter sales encompassed a panel of six items including anti-diarrheal medication, anti-fever adult medication, anti-fever pediatric medication, cough and cold products, electrolytes, and thermometers. Additionally, two of the seven hospital chief complaints used in the RODS open source paradigm were monitored. These were constitutional and respiratory chief complaints. Application of standard statistical algorithms showed that the system was able to identify unusual activity several weeks prior to the time when the local health departments were able to identify an outbreak using the standard methods. The largest improvement in detection using syndromic surveillance occurred in Los Angeles where the outbreak was detected 52 days before the Centers for Disease Control had declared widespread activity for the state. In each county over-the-counter sal