Graphical Analysis of Social Group Dynamics

Identifying communities in social networks becomes an increasingly important research problem. Several methods for identifying such groups have been developed, however, qualitative analysis (taking into account the scale of the problem) still poses serious problems. This paper describes a tool for facilitating such an analysis, allowing to visualize the dynamics and supporting localization of different events (such as creation or merging of groups). In the final part of the paper, the experimental results performed using the benchmark data (Enron emails) provide an insight into usefulness of the proposed tool.Comment: Fourth International Conference on Computational Aspects of Social Networks, CASoN 2012, Sao Carlos, Brazil, November 21-23, 2012, pp. 41-46; IEEE Computer Society, 201

Collaborative method to maintain business process models updated

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.info:eu-repo/semantics/publishedVersio

Distributed Adaptive Networks: A Graphical Evolutionary Game-Theoretic View

Distributed adaptive filtering has been considered as an effective approach for data processing and estimation over distributed networks. Most existing distributed adaptive filtering algorithms focus on designing different information diffusion rules, regardless of the nature evolutionary characteristic of a distributed network. In this paper, we study the adaptive network from the game theoretic perspective and formulate the distributed adaptive filtering problem as a graphical evolutionary game. With the proposed formulation, the nodes in the network are regarded as players and the local combiner of estimation information from different neighbors is regarded as different strategies selection. We show that this graphical evolutionary game framework is very general and can unify the existing adaptive network algorithms. Based on this framework, as examples, we further propose two error-aware adaptive filtering algorithms. Moreover, we use graphical evolutionary game theory to analyze the information diffusion process over the adaptive networks and evolutionarily stable strategy of the system. Finally, simulation results are shown to verify the effectiveness of our analysis and proposed methods.Comment: Accepted by IEEE Transactions on Signal Processin

Road Maps: a guide to learning system dynamics

MIT System Dynamics Education Project developed Road Maps, a series of self-guides, modeling and selected literature to help students and teachers learn the principles of system dynamics. This site is part of that project, and provides listings of articles and othe webpages containing discussion of Road Maps publications. Road Maps are a series of self-guides that use modeling exercises and selected literature to provide a resource for learning about the principles and practices of system dynamics. Educational levels: High school, Middle school, Undergraduate lower division, Undergraduate upper division

Proposal for a contents design of a graphic engineering lecture

In this project the subject of Industrial Design from the bachelor’s degree in Industrial Technologies and Economic Analysis of the ETSEIB is reviewed considering the contents and the teaching and evaluating methods. To acquire a great level and teach the subject with great quality, this project has been developed in order to grant that some of the best methods are used to teach and evaluate the students. The contents have also been reviewed to certify that a similar structure of contents is being followed the same way as some of the more relevant engineering schools. As this subject is part of the bachelor’s degree in Industrial Technologies and Economic Analysis, some of the subjects of the bachelor’s degree in Industrial Technologies, which is another degree from the ETSEIB, are used to compare and conclude the methods that could be used to benefit the subject. This has been done since these subjects have been used as a background to develop the contents and the organization of the Industrial Design subject. Research on some of the most relevant engineering schools in the world and in similar subjects such as Graphical Expression or Computer Aided Design has been done. This has determined the differences between the relevant and prestigious schools and the subjects of Graphical Expression or CAD. Once these different methods have been identified, they are considered to be applied to the organization of the subject, as a proposal, in order to enhance its quality and its reputation. To define which universities are better and more adequate for this project, some crucial facts have been used to reduce the research to a more specific group of engineering schools. The idea behind this project is to be able to clarify and help achieving a greater quality in the subject by reviewing some of the most relevant industrial design schools worldwide to apply some of the ways that they use to achieve such quality and reputation

A statistical network analysis of the HIV/AIDS epidemics in Cuba

The Cuban contact-tracing detection system set up in 1986 allowed the reconstruction and analysis of the sexual network underlying the epidemic (5,389 vertices and 4,073 edges, giant component of 2,386 nodes and 3,168 edges), shedding light onto the spread of HIV and the role of contact-tracing. Clustering based on modularity optimization provides a better visualization and understanding of the network, in combination with the study of covariates. The graph has a globally low but heterogeneous density, with clusters of high intraconnectivity but low interconnectivity. Though descriptive, our results pave the way for incorporating structure when studying stochastic SIR epidemics spreading on social networks