Luiz Paulo Luna de Oliveira

A Model for Generating and Animating Groups of Virtual Agents

This paper presents a model to generate and animate groups which emerge as a function of interaction among virtual agents. The agents are characterized through the following parameters: sociability, communication, comfort, perception and memory. The emergent groups are characterized through the cohesion parameter which describes the homogeneity of ideas of the group members. In this work we are mainly interested in investigating the formation of groups (membership and time for grouping), the groups characterization (cohesion parameter) and their visual representation (group formation). The overall results suggest that the interaction among agents contributes to larger groups and higher crowd cohesion values.

An algorithm for automatic detection and orientation estimation of planar structures in LiDAR-scanned outcrops

The spatial orientation of linear and planar structures in geological fieldwork is still obtained using simple hand-held instruments such as a compass and clinometer. Despite their ease of use, the amount of data obtained in this way is normally smaller than would be considered as representative of the area available for sampling. LiDAR-based remote sensors are capable of sampling large areas and providing huge sets of digitized spatial points. However, the visual identification of planes in sets of points on geological outcrops is a difficult and time-consuming task. An automatic method for detecting and estimating the orientation of planar structures has been developed to reduce analysis and processing times, and to fit the best plane for each surface represented by a set of points and thus to increase the sampled area. The algorithm detects clusters of points that are part of the same plane based on the principal component analysis (PCA) technique. When applied to real cases, it has shown high precision in both the detection and orientation of fractures planes. HighlightsWe propose a method for plane detection and orientation in LiDAR point clouds.The method, simple and automatic, is statistical in its essence, using PCA.The whole point cloud is sequentially sub-divided until planar patches are found.It opposes other methods that search for small planer patches and expand it outwards.

GUGA: A tool for participatory cities

Participatory cities are those that allow the participation of citizens in the construction and improvement of their common daily life. In this work we present a tool for that participation, allowing the citizens to register the occurrences as well as take knowledge about the global geographic status of their city in on a variety of contexts (security, transit, etc.). However, a tool like that, fed by the people, certainly will deal with a large amount of information, distributed geographically. To accomplish that, a precise criterion for visualizing the resultant density distribution of occurrences must be used. In this paper, we also propose an automatic method for that visualization based on Voronoi Diagrams. The Voronoi polygons divide the region according to the concentration of occurrences. In this scheme, the area of each Voronoi polygon defines the density of the occurrences of the specific categories which are shown in the city map in color and transparency intensities for visualization. This can easily reveal the space distribution of important issues, in a variety of contexts such as criminality, commercial and industrial activities, drugs traffic, illumination concerns, and others.

A competitive searching-based chaotic cipher

In this paper we propose a high performance searching-based chaotic cipher. Experiments shows that its efficiency is comparable to the efficiencies of some widely used and known ciphers, namely, AES, RC4 and Sosemanuk. Also, its performance is better than some recently proposed chaotic ciphers of the same kind. The proposed cryptosystem shows independence with respect to the statistical characteristics of the plain texts, which prevents statistical attacks. The results of the tests suggest that this chaotic cipher can be competitive for practical usage.

Periodicity and Predictability in Chaotic Systems

Most of the good mathematical models available for natural phenomena are non linear, and these are often chaotic. Sensitive dependence on initial conditions can foil any attempt at prediction. In fact, measurement errors in collecting the initial data, intrinsic to any observational method, will propagate under the computational use of the model. With this, the final results obtained from the model may be useless when compared with the real future of the phenomena. Even in the strictly computational context, the sensitive dependence on initial conditions often makes a chaotic system S unpredictable because of representation errors. In fact, most of the orbits obtained in computers are not even good approximations to the actual ones. Real number representations by computers fall under two headings: floating-point (or numerical) and algebraic (or symbolic). In the former case, given the finite amount of memory, only numbers with finite decimal representations are treated without (roundoff) errors. In the symbolic setting, exact representation extends to some alge braic irrationals, to some transcendentals, and to various algebraic combinations of these. Therefore, the development of a dynamical system inside a computer is prone to successive errors, which is usually fatal to predictions concerning chaotic systems. In this article, we look at the question of computational predictability more closely and show that unpredictability in chaotic systems is also related to the scheme in which the system is represented. For simplicity, we restrict our discussions to discrete-time dynamical systems (i.e., to systems S defined by maps / : V -> V for metric spaces V). The orbit of S corresponding to the initial condition x0 is defined as the sequence y : N -+ V given by y(n) ? xn ? fn(x0), where N = {0, 1, 2, ...}. The time variable of S is n, and V is its state space. The space V is usually a subset of M.d for some natural number d, the dimension of the system. The orbits of S may be open, eventually periodic, or periodic. We write (eventually) periodic when referring to either of the last two categories. We call S periodic if all its orbits are (eventually) periodic.

Modelling consumers decision-making process about excluding products as a result of mutual influence

We present a model for the evolution of opinion distribution in a society with respect to two excluding concepts or choices A and B. It is considered a situation where two excluding concepts are on a dispute for exclusivity, through the consecutive interactions among the consumers, one trying to persuade the other of their position. The strength of influence of each consumer over those it relates with, depends on its social status as well as the enthusiasm (extremism degree) it defends its side. Here we propose a model taking these factors into consideration using an approach based on agents. Each agent is equipped with a fixed social status, as well as a variable position with respect to the two concepts. They are put to interact among themselves, following a rule such that the change an agent imposes to the other is proportional to the persuader status and its degree of decision (opinion) for one or other concept. This makes the position of the interacting agents to vary in time. We then analyse the tendencies of consumers opinion as a whole as time passes, for a variety of initial configurations, to see what the final stationary results and how fast they are attained. We found that extremism was always the final state of society opinion, that is, with all consumers opting for the same product, with an extreme (maximum) degree of decision. Also, we conclude that the most important factor for deciding which choice wins, and how fast, is the ratio between the status averages of both groups, the one of those more convinced of A and the one of those more convinced of B. In fact, the group with the larger social status average wins the other even in significant initial disadvantages in number of individuals or in average degree of conviction.

Visualization and analysis of interacting occurences in a smart city

New information and communication technologies enable a better management of the available resources in a smart city. Leaders need tools to analyze data for better decisions, anticipate problems and resolve them proactively. In this context, this article proposes a simulation tool to analyze the interaction of typical cities occurrences like criminal and police. The information of both occurrences, including their densities, are inserted and visualized on a city map. Each record is marked on the GPS point where it happened. From these inputs data, the interactions are modeled by Voronoi Diagrams. The occurrences change their position according to the size area of the opposite event. In this way, crimes runway from police and police catch crimes occurrences. As results, we show that a large increase of police actions will not influence quantitatively in the reduction of criminal occurrences out of a critical zone.

Modeling and Visualization Individual and Collective Opinions towards Extremism in a Society

Abstract The present work is an attempt to approach the modeling and visualization of individual opinion towards extremism in a society. We consider a scenario where two opposite concepts are on a dispute for exclusivity, via the effort of the individuals to convince each other of their own oppinion/decision. The power of convincement of each individual over the community depends on its influence, its communicability and on the enthusiasm (extremism) it defends its side. Here we propose a model taking these three factors into consideration. We analyze the system changes in real time by following the agents extremism parameter of the society, representing its distribution in a graphical fashion and present realizations of the proposed model for a variety of initial configurations (input parameter sets). The results analysis suggest that the most important factor is influence more then the number of individuals defending a position. Moreover, communicability has small or no relevance. Visualization schemes for following individuals interactions are also included.

Opinion dynamics: A study of the relation between status and communicability

A remarkable characteristic of human beings is their tendency to form societies. That put themselves in a social position, where they interact with the environment and try to convince others of their own convictions. This study proposes a model for interactions among individuals of a society, accompanying the evolution of their opinions over time. We consider a situation where the individuals are subordinated to choose between two mutually exclusive options, A and B. Each one of the individuals is gifted with status, opinion and communicability, forming groups according to their degree of conviction to A or B. In this analysis we tried to identify which initial parameters of the groups - average opinion, average status and number of individuals - could cause the greatest impact on the dynamics outcome. When communicability is independent of status, an equilibrium between initial parameters was noticed, showing that none of them is more relevant than the other. However, when communicability is an increasing status function, status presented the major importance. We conclude that status must be associated to communicability to have a prominent role in the dynamics. According to this study, in usual situations where the status shows to be more relevant, it must be somehow associated to communicability.

Vis-Health: Exploratory Analysis and Visualization of Dengue Cases in Brazil

This paper presents a tool, Vis-Health, for analysis and visualization of public health data covariance with variables chosen by the user, in order to give her/him clues for a better understanding of disease occurrences. Vis-Health is a system that allows: (a) the government authorities store data of different nature and from different methods, (b) the user (common citizen or government) to choose an interest variable as dependent(output) and n other as dependent (or inputs), in order to study the covariance study between them and (c) visualize the result in a clear way. The covariance study is made by the use of Principal Component Analysis (PCA), resulting in a linear orthogonal regression. The method permits that many users, choosing different variables as dependent or independent, can use Vis-Health simultaneously, thanks to the optimized performance of the included algorithm based on PCA. Vis-Health is an open tool, and can help government to have more adequate actions, but any common citizen can use Vis-Health for making her/his particular exploration. As a illustration, a study of the numbers of cases of Dengue in Brazil is studied as a function of climatic variables.