Landmark-based music recognition system optimisation using genetic algorithms

Audio fingerprinting allows us to label an unidentified music fragment within a previously generated database. The use of spectral landmarks aims to obtain a robustness that lets a certain level of noise be present in the audio query. This group of audio identification algorithms holds several configuration parameters whose values are usually chosen based upon the researcher’s knowledge, previous published experimentation or just trial and error methods. In this paper we describe the whole optimisation process of a Landmark-based Music Recognition System using genetic algorithms. We define the actual structure of the algorithm as a chromosome by transforming its high relevant parameters into various genes and building up an appropriate fitness evaluation method. The optimised output parameters are used to set up a complete system that is compared with a non-optimised one by designing an unbiased evaluation model.     

Socio-Cultural Connections and Ruptures: Social Roles of Older Adults in Chile

This research focused on determining the sociocultural factors that build the social perception of the social roles of senior citizens in Chile in the 2002–2012 period. For this purpose, public opinion was studied in newspapers El Mercurio and La Cuarta. Specialized opinion included the Senior Citizen Program of Pontificia Universidad Católica de Chile, the National Service for Senior Citizens, the Social Observatory for Aging and Old Age of Universidad de Chile, and the Society of Geriatrics and Gerontology of Chile. A comprehensive methodology was used, along with a bibliographical four-stage design. The following ten sociocultural factors were identified: Health and Quality of Life, Studies and Data, Social Images of Aging, Gerontological Concepts and Sociopolitical Participation, Gerontological Policies, Plans and Principles, Aging, Production and Gender, Institutionalization, Demographic Growth, Gerontological Training, and Exclusion and Old Age. This work suggests modifying the conceptual premise that emphasizes the inexistence of a social role for elderly people with a vision centered on the heterogeneity of social roles under permanent sociocultural construction.     

Multi-objective optimization with an adaptive resonance theory-based estimation of distribution algorithm

The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective ones. One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs). However, it has been pointed out that current MOEDAs have an intrinsic shortcoming in their model-building algorithms that hamper their performance. In this work, we put forward the argument that error-based learning, the class of learning most commonly used in MOEDAs is responsible for current MOEDA underachievement. We present adaptive resonance theory (ART) as a suitable learning paradigm alternative and present a novel algorithm called multi-objective ART-based EDA (MARTEDA) that uses a Gaussian ART neural network for model-building and a hypervolume-based selector as described for the HypE algorithm. In order to assert the improvement obtained by combining two cutting-edge approaches to optimization an extensive set of experiments are carried out. These experiments also test the scalability of MARTEDA as the number of objective functions increases.     

Efficient wavelet-based ECG processing for single-lead FHR extraction

This paper describes a novel model for fetal heart rate (FHR) monitoring from single-lead mother?s abdomen ECG (AECG) measurements. This novel method is divided in two stages: the first step consists on a one-step wavelet-based preprocessing for simultaneous baseline and high-frequency noise suppression, while the second stage efficiently detects fetal QRS complexes allowing FHR monitoring. The presented structure has been simplified as much as possible, in order to reduce computational cost and thus enable possible custom hardware implementations. Moreover, the proposed scheme and its fixed-point modeling have been tested using real abdominal ECG signals, which allow the validation of the presented approach and provide high accuracy.     

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.     

Service oriented evolutionary algorithms

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained. In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.     

Mechanical resistance properties of gravel used in subsurface flow constructed wetlands: implications for clogging

Gravel constitutes the filter medium in subsurface flow constructed wetlands (SSF CWs) and its porosity and hydraulic conductivity decrease over time (clogging), limiting the lifespan of the systems. Using gravel of poor quality accelerates clogging in wetlands. In this study, gravel samples from six different wetland systems were compared with regards to their mineral composition and mechanical resistance properties. Results showed that both mineralogy and texture are related to mechanical resistance. Accordingly, gravel with high content of quartz (> 80%) showed a lower percentage of broken particles (0.18-1.03%) than those with lower content of quartz (2.42-4.56% media broken). Although granite is formed by high durability minerals, its non-uniform texture results in a lower resistance to abrasion (ca. 10% less resistance than calcareous gravel). Therefore, it is recommended to use gravels composed mainly of quartz or, when it is not available, limestone gravels (rounded and uniform) are recommended instead. The resistance to abrasion (LAA test) seems to be a good indicator to determine the mechanical properties of gravels used in CWs. It is recommended to use gravels with LAA below 30% in order to avoid a rapid clogging due to gravel crumbling and subsequent mineral solids accumulation.