David L. García

Extensive operators in partition lattices for image sequence analysis

This paper deals with the class of extensive operators in the lattice of partitions. These operators are merging techniques. They can be used as filtering tools or as segmentation algorithms. In the first case, they are known as connected operators and, in the second case, they are region growing techniques. This paper discusses the basic elements that have to be defined to create a merging algorithm: merging order, merging criterion and region model. This analysis highlights the similarity and differences between a filtering tool, such as a connected operator, and a segmentation algorithm. Taking benefit from the filtering and segmentation viewpoints, we propose a general merging algorithm that can be used to create new connected operators (in particular self-dual operators) and efficient segmentation algorithms (robust criteria and efficient implementation).

Improving performance of a real ad-hoc network by tuning OLSR parameters

A key element for MANET performance is the routing protocol. Surprisingly, little effort has been devoted up to now to analyzing the impact of routing protocol parameter settings on MANET performance. We define and study in detail the route change latency (RCL) after link failures, a critical performance metric in a non-static ad-hoc scenario, and its dependence on routing protocol parameter settings and implementation issues using OLSR. We experiment with a set of OLSR settings in a real network environment and derive its potential effect in a generic situation, showing that end-to-end connectivity can be enhanced using different parameter settings from the default ones.

Parallelization of Microscopic Traffic Simulation for Att Systems Analysis

Simulation is a process based on building a computer model that suitably represents a real or proposed system which enables to extract valid inferences on the behavior of the modeled system, from the outcomes of the computer experiments conducted on its model. Simulation has become in recent years one of the most used and powerful tools for systems analysis and design, by its proven ability to answer “what if” questions helping the system designer to find solutions for building new systems, or assess the impact of proposed changes on an already existing system. A simulation model is always a simplified representation of a system that addresses specifically those aspects of the studied system relevant for the purposes of the analysis from the point of view of the system analyst. A simulation model is therefore specific, both for the problem and for whoever tries to use the model for finding solutions to the problem. A simulation study has usually the objective of helping to get a better understanding on how a system behaves, evaluating the impact of changes in the system, or in values of the parameters governing the system, or of decisions on the policies controlling the system.

Intelligent data analysis approaches to churn as a business problem: a survey

Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.

Cartogram visualization for nonlinear manifold learning models

Real-world applications of multivariate data analysis often stumble upon the barrier of interpretability. Simple data analysis methods are usually easy to interpret, but they risk providing poor data models. More involved methods may instead yield faithful data models, but limited interpretability. This is the case of linear and nonlinear methods for multivariate data visualization through dimensionality reduction. Even though the latter have provided some of the most exciting visualization developments, their practicality is hindered by the difficulty of explaining them in an intuitive manner. The interpretability, and therefore the practical applicability, of data visualization through nonlinear dimensionality reduction (NLDR) methods would improve if, first, we could accurately calculate the distortion introduced by these methods in the visual representation and, second, if we could faithfully reintroduce this distortion into such representation. In this paper, we describe a technique for the reintroduction of the distortion into the visualization space of NLDR models. It is based on the concept of density-equalizing maps, or cartograms, recently developed for the representation of geographic information. We illustrate it using Generative Topographic Mapping (GTM), a nonlinear manifold learning method that can provide both multivariate data visualization and a measure of the local distortion that the model generates. Although illustrated here with GTM, it could easily be extended to other NLDR visualization methods, provided a local distortion measure could be calculated. It could also serve as a guiding tool for interactive data visualization.

Emotinet: A Framework for the Development of Social Awareness Systems

This chapter describes Emotinet, a flexible and extensible framework for the development of social awareness systems. Emotinet was initially designed and developed to facilitate our explorations on how to augment a person’s work environment with information which enables his/her to feel the presence of intimate companions. The vehicle we deem to be appropriate for this situation is indirect communication. The presence we intend is based on the activities of these intimate people. A first social awareness system has already been developed by using Emotinet. This system is also described in this chapter. In short, with a certain periodicity the user is presented, on a peripheral user interface (windows desktop or digital picture frame), with a new collage composed of pictures indirectly triggered by their loved ones. In particular the pictures are triggered by the text they write and read, while working on their PCs.

Towards affective collages of presences

This paper describes ongoing work aimed to explore how to augment a person’s work environment with information which enables her to feel the presence of intimate companions. The vehicle we deem to be appropriate for this situation is indirect communication (in some ways related to peripheral communication). The presence we intend is based on the activities of these intimate people. In short, with a certain periodicity the user is presented, on a peripheral user interface (windows desktop or digital picture frame), with a new collage composed of pictures indirectly triggered by their loved ones. In particular the pictures are triggered by the text they write and read, and the songs they listen to, while working on their PCs.

A PARALLEL ENVIRONMENT FOR A REAL-TIME TRAFFIC MANAGEMENT AND INFORMATION SYSTEM

Abstract Modem Traffic Management Systems provide the traffic engineer with the information on current and forecasted traffic conditions, traffic conflicts, etc., required to support a rational decision making process. That information is the outcome of a computing process whose inputs are the raw traffic data supplied in real-time by various data sources, and whose components are complex algorithmic procedures implementing numerically models for dynamic traffic assignment, OlD estimation, traffic simulation, etc., which imply a heavy computational overhead. This paper describes the architecture, the parallel approach taken in developing a prototype of such a system, its implementation on a shared memory environment, and the preliminary results of testing the system on Barcelonas Ring Roads.

Electricity Rate Planning for the Current Consumer Market Scenario Through Segmentation of Consumption Time Series

The current European legislation requires households the installation of smart metering systems. These will eventually allow electric utilities to gather richly detailed data of consumption. In this scenario, the implementation of data mining procedures for actionable knowledge extraction could be the key to competitive advantage. These may take the form of market segmentation using clustering techniques for the identification of customer behaviour patterns of electricity consumption that could justify the definition of tailored tariffs. In this brief paper, we show that the combination of a standard clustering algorithm with a similarity measure specifically defined for non-i.i.d. data, namely Dynamic Time Warping, can reveal an actionable segmentation of a real consumer market, combining business criteria and quantitative evaluation.

Memotice Board: A Notice Board with Spatio-temporal Memory

This paper describes the design and development of a novel digital notice board which allows non experienced users to easily interact with digital information. In particular, the system allows the user to receive and handle media elements (pictures, text messages, videos). Instead of employing the file system to interact with information, the user interface promotes a kind of interaction which relies on spatial and temporal memory, which we believe to be more adequate.