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.

Introduction to Coding Theory for Flow Equations of Complex Systems Models

The modeling of complex dynamic systems depends on the solution of a differential equations system. Some problems appear because we do not know the mathematical expressions of the said equations. Enough numerical data of the system variables are known. The authors, think that it is very important to establish a code between the different languages to let them codify and decodify information. Coding permits us to reduce the study of some objects to others. Mathematical expressions are used to model certain variables of the system are complex, so it is convenient to define an alphabet code determining the correspondence between these equations and words in the alphabet. In this paper the authors begin with the introduction to the coding and decoding of complex structural systems modeling.

Acceptability of pandemic A(H1N1) influenza vaccination by Essential Community Workers in 2010 Alicante (Spain), perceived seriousness and sources of information

Objective. Describe acceptability of pandemic A(H1N1) influenza vaccination by Essential Community Workers (ECWs) from Alicante province (Spain) in January 2010. Evaluate the correlation with attitudes, beliefs, professional advice and information broadcasted by media. Method. In this cross-sectional study, face-to-face interviews were conducted with 742 ECWs to assess their attitudes towards vaccination against the pandemic influenza strain. A multivariable regression model was made to adjust the Odds Ratios (ORs). Results. Some ECWs reported having been vaccinated with seasonal vaccine, 21.5% (95%IC 18.6–24.9); only 15.4% (95%IC 12.8–18.4) with the pandemic one. ECWs vaccinated regularly against seasonal flu (OR 5.1; 95%IC 2.9–9.1), those who considered pandemic influenza as a severe or more serious disease than seasonal flu (OR 3.8; 95%IC 2.1–6.7) and those who never had doubts about vaccine safety (OR 3.7; 95%IC2.1–6.7) had a better acceptance of pandemic vaccine. Finally, 78.7% (95%IC 75.1–81.4) had doubts about pandemic vaccine's effectiveness. Conclusion. The vast amount of information provided by the media did not seem to be decisive to prevent doubts or to improve the acceptability of the vaccine in ECWs. Professional advice should be the focus of interest in future influenza vaccination campaigns. These results should be taken into account by health authorities.

Implementation Feasibility of a Digital Nervous System for the Construction Industry: For Efficient and Effective Information Management across the Project Lifecycle

The construction industry has long been considered as highly fragmented and non-collaborative industry. This fragmentation sprouted from complex and unstructured traditional coordination processes and information exchanges amongst all parties involved in a construction project. This nature coupled with risk and uncertainty has pushed clients and their supply chain to search for new ways of improving their business process to deliver better quality and high performing product. This research will closely investigate the need to implement a Digital Nervous System (DNS), analogous to a biological nervous system, on the flow and management of digital information across the project lifecycle. This will be through direct examination of the key processes and information produced in a construction project and how a DNS can provide a well-integrated flow of digital information throughout the project lifecycle. This research will also investigate how a DNS can create a tight digital feedback loop that enables the organisation to sense, react and adapt to changing project conditions. A Digital Nervous System is a digital infrastructure that provides a well-integrated flow of digital information to the right part of the organisation at the right time. It provides the organisation with the relevant and up-to-date information it needs, for critical project issues, to aid in near real-time decision-making. Previous literature review and survey questionnaires were used in this research to collect and analyse data about information management problems of the industry – e.g. disruption and discontinuity of digital information flow due to interoperability issues, disintegration/fragmentation of the adopted digital solutions and paper-based transactions. Results analysis revealed efficient and effective information management requires the creation and implementation of a DNS.