A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

Control of Redundant Joint Structures Using Image Information During the Tracking of Non-Smooth Trajectories

Visual information is increasingly being used in a great number of applications in order to perform the guidance of joint structures. This paper proposes an image-based controller which allows the joint structure guidance when its number of degrees of freedom is greater than the required for the developed task. In this case, the controller solves the redundancy combining two different tasks: the primary task allows the correct guidance using image information, and the secondary task determines the most adequate joint structure posture solving the possible joint redundancy regarding the performed task in the image space. The method proposed to guide the joint structure also employs a smoothing Kalman filter not only to determine the moment when abrupt changes occur in the tracked trajectory, but also to estimate and compensate these changes using the proposed filter. Furthermore, a direct visual control approach is proposed which integrates the visual information provided by this smoothing Kalman filter. This last aspect permits the correct tracking when noisy measurements are obtained. All the contributions are integrated in an application which requires the tracking of the faces of Asperger children.

Structures, Systems and Organizational Communication Processes in Franchises in times of crisis: the Spanish case

Current economic crisis together with the Internet revolution has had direct impacts on the franchise sector of Spain: in particular on its unique communication network. The aim of this research is to analyse how Spanish franchise companies have adapted to these changes through its corporate communications management. We want to determine whether the management of communications is ideal to the growth and consolidation of companies in the market. Corporate communications plans and organizational structures were analyzed to verify whether or not information technology (i.e. the use of the Internet) is maximized: the communications aspect being a critical area of company growth. We found that most franchise companies surveyed had adapted well to the changes in information technology, despite economic challenges. The Internet as a communications tool has been limited to its utility as a “bulletin board” for information. The marketing advantage of Internet communication, or its use as an avenue for customer exchange and exchange of goods and services has yet to be maximized. Future research may look into the details of how companies are able to maximize the communications-marketing advantage that Online/Internet can contribute to the franchise sector.