L’Utilisation D’Entretiens Quantitatifs Pour Détecter L’influence des Parents Dans le Développement de Compétences Sportives Chez Les Athlètes

Past research has indicated that parents influence children’s sport performance, but studies using qualitative methodologies and lacking comparison groups have failed to outline specific parent behaviors that constitute support, pressure, involvement, and resource provision at each stage of development. This paper presents a quantitative methodology that assesses specific, observable, verifiable parent behaviors across development, allowing future researchers to highlight differences in parental behaviors of athletes who reach high levels of performance and those who do not. The combined survey and interview methodology examines parents’ demographic information, children’s involvement in sporting activities, and the nature of parents’ involvement in those activities. A case study conducted with the parents of three Canadian junior ice hockey athletes using this methodology found parents’ invested time and specific behaviors changed throughout the development of the athlete.

Agricultura urbana, condición para el desarrollo sostenible y la mejora del paisaje

Este artículo resulta de investigaciones en torno al “enverdecimiento” de las ciudades y las oportunidades de la agricultura urbana para la alimentación de una población en constante aumento que no trabaja la tierra. También es fruto de actividades de mejora de ambientes urbanos realizadas con la Escuela de Ingenieros Agrónomos de la Universidad Politécnica de Madrid. A través de casos de agricultura urbana, entendiendo por ella el conjunto de prácticas para la producción de alimentos y plantas ornamentales dentro de las ciudades y en sus entornos, se analizan alternativas para la recuperación de espacios construidos e incremento de la calidad de vida de la población. Todo ello se traduce, además, en creación de riqueza y mejora del paisaje urbano, siempre desde criterios de sostenibilidad que favorecen el desarrollo local desde la Cumbre de la Tierra de Río de 1992 y la Conferencia sobre Desarrollo Sostenible Río+20 de 2013.

Indicadores de sostenibilidad ambiental en el periurbano de la ciudad de Mar del Plata, Argentina

Los indicadores de sostenibilidad conforman herramientas útiles para la toma de decisiones. Las ciudades latinoamericanas, y especialmente las áreas de expansión sin planificación adecuada, enfrentan desafíos cada vez mayores para revertir problemáticas que amenazan su sostenibilidad. El presente trabajo evalúa de manera preliminar, la sostenibilidad ambiental del periurbano de Mar del Plata (Argentina) tomando como referencia algunos de los indicadores propuestos por el modelo del Banco Interamericano de Desarrollo en la Iniciativa Ciudades Emergentes y Sostenibles. Se construyó un índice sintético (Índice de Sostenibilidad Ambiental, ISA) que integra trece indicadores agrupados en ocho temas. Las situaciones más críticas (ISA: 0,45-0,558) se identifican fundamentalmente en zonas en las que se desarrollan actividades rurales y en las que se localizan asentamientos de carácter precario. El estudio realizado profundiza en el conocimiento de la dimensión ambiental de la sostenibilidad, enfatizando en el análisis de los contrastes internos del periurbano marplatense.

Genetic algorithms for local controller network construction

Local Controller Networks (LCNs) provide nonlinear control by interpolating between a set of locally valid, subcontrollers covering the operating range of the plant. Constructing such networks typically requires knowledge of valid local models. This paper describes a new genetic learning approach to the construction of LCNs directly from the dynamic equations of the plant, or from modelling data. The advantage is that a priori knowledge about valid local models is not needed. In addition to allowing simultaneous optimisation of both the controller and validation function parameters, the approach aids transparency by ensuring that each local controller acts independently of the rest at its operating point. It thus is valuable for simultaneous design of the LCNs and identification of the operating regimes of an unknown plant. Application results from a highly nonlinear pH neutralisation process and its associated neural network representation are utilised to illustrate these issues.

On velocity-based local model networks for nonlinear identification

This paper exposes the strengths and weaknesses of the recently proposed velocity-based local model (LM) network. The global dynamics of the velocity-based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub-models are continuous-time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub-models. In this paper, a velocity-based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity-based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity-based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.

Comparison of two construction algorithms for local model networks

The divide-and-conquer approach of local model (LM) networks is a common engineering approach to the identification of a complex nonlinear dynamical system. The global representation is obtained from the weighted sum of locally valid, simpler sub-models defined over small regions of the operating space. Constructing such networks requires the determination of appropriate partitioning and the parameters of the LMs. This paper focuses on the structural aspect of LM networks. It compares the computational requirements and performances of the Johansen and Foss (J&F) and LOLIMOT tree-construction algorithms. Several useful and important modifications to each algorithm are proposed. The modelling performances are evaluated using real data from a pilot plant of a pH neutralization process. Results show that while J&F achieves a more accurate nonlinear representation of the pH process, LOLIMOT requires significantly less computational effort.