Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

Granularity and disaggregation in compositional modelling with applications to ecological systems

In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.

From SMART to agent systems development

n order for agent-oriented software engineering to prove effective it must use principled notions of agents and enabling specification and reasoning, while still considering routes to practical implementation. This paper deals with the issue of individual agent specification and construction, departing from the conceptual basis provided by the smart agent framework. smart offers a descriptive specification of an agent architecture but omits consideration of issues relating to construction and control. In response, we introduce two new views to complement smart: a behavioural specification and a structural specification which, together, determine the components that make up an agent, and how they operate. In this way, we move from abstract agent system specification to practical implementation. These three aspects are combined to create an agent construction model, actsmart, which is then used to define the AgentSpeak(L) architecture in order to illustrate the application of actsmart.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

SSM samba: a survey of brazilian approaches to soft systems methodology (1999-2005)

This paper reports the results of a survey intended to discover the manner in which Soft Systems Methodology (SSM) is understood and used in Brazil. The focus is upon SSM papers published in national and international journals, and conferences, incorporating a refereeing procedure. To be included in the survey, publications had to meet at least one of the following criteria: (a) authorship is clearly of Brazilian nationality; or, (b) authorship is affiliated to a Brazilian institution; or (c) application is set in Brazil. Similar surveys reporting on the United Kingdom, Australia and, to a lesser extent, Spain have been published previously in the literature. This paper, therefore, contributes to the growing international understanding and usage of SSM. Ultimately the paper serves as an initial map of the developing context in Brazilian SSM theory and practice.

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Grain quality of upland rice cultivars in response to cropping systems in the Brazilian tropical savanna

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Gaps in the welfare State and reforms to pension systems in Latin America

Includes bibliography

Robust controller design of a wheelchair mobile via LMI approach to SPR systems with feedback output

This article discusses the design of robust controller applied to Wheelchair Furniture via Linear Matrix Inequalities (LMI), to obtain Strictly Positive Real (SPR) systems. The contributions of this work were the choice of a mathematical model for wheelchair: mobile with uncertainty about the position of the center of gravity (CG), the decoupling of the kinematic and dynamical systems, linearization of the models, the headquarters building of parametric uncertainties, the proposal of the control loop and control law with a specified decay rate.

Application of reactive fluid transport modeling to hydrothermal systems

A one-dimensional multi-component reactive fluid transport algorithm, 1DREACT (Steefel, 1993) was used to investigate different fluid-rock interaction systems. A major short coming of mass transport calculations which include mineral reactions is that solid solutions occurring in many minerals are not treated adequately. Since many thermodynamic models of solid solutions are highly non-linear, this can seriously impact on the stability and efficiency of the solution algorithms used. Phase petrology community saw itself faced with a similar predicament 10 years ago. To improve performance and reliability, phase equilibrium calculations have been using pseudo compounds. The same approach is used here in the first, using the complex plagioclase solid solution as an example. Thermodynamic properties of a varying number of intermediate plagioclase phases were calculated using ideal molecular, Al-avoidance, and non-ideal mixing models. These different mixing models can easily be incorporated into the simulations without modification of the transport code. Simulation results show that as few as nine intermediate compositions are sufficient to characterize the diffusional profile between albite and anorthite. Hence this approach is very efficient, and can be used with little effort. A subsequent chapter reports the results of reactive fluid transport modeling designed to constrain the hydrothermal alteration of Paleoproterozoic sediments of the Southern Lake Superior region. Field observations reveal that quartz-pyrophyllite (or kaolinite) bearing assemblages have been transformed into muscovite-pyrophyllite-diaspore bearing assemblages due to action of fluids migrating along permeable flow channels. Fluid-rock interaction modeling with an initial qtz-prl assemblage and a K-rich fluid simulates the formation of observed mineralogical transformation. The bulk composition of the system evolves from an SiO2-rich one to an Al2O3+K2O-rich one. Simulations show that the fluid flow was up-temperature (e.g. recharge) and that fluid was K-rich. Pseudo compound approach to include solid solutions in reactive transport models was tested in modeling hydrothermal alteration of Icelandic basalts. Solid solutions of chlorites, amphiboles and plagioclase were included as the secondary mineral phases. Saline and fresh water compositions of geothermal fluids were used to investigate the effect of salinity on alteration. Fluid-rock interaction simulations produce the observed mineral transformations. They show that roughly the same alteration minerals are formed due to reactions with both types of fluid which is in agreement with the field observations. A final application is directed towards the remediation of nitrate rich groundwaters. Removal of excess nitrate from groundwater by pyrite oxidation was modeled using the reactive fluid transport algorithm. Model results show that, when a pyrite-bearing, permeable zone is placed in the flow path, nitrate concentration in infiltrating water can be significantly lowered, in agreement with proposals from the literature. This is due to nitrogen reduction. Several simulations investigate the efficiency of systems with different mineral reactive surface areas, reactive barrier zone widths, and flow rates to identify the optimum setup.

Photophysics of Carbon Nanotubes: from Dispersion to Supramolecular Systems

The aim of this PhD thesis is the investigation of the photophysical properties of materials that can be exploited in solar energy conversion. In this context, my research was mainly focused on carbon nanotube-based materials and ruthenium complexes. The first part of the thesis is devoted to carbon nanotubes (CNT), which have unique physical and chemical properties, whose rational control is of substantial interest to widen their application perspectives in many fields. Our goals were (i) to develop novel procedures for supramolecular dispersion, using amphiphilic block copolymers, (ii) to investigate the photophysics of CNT-based multicomponent hybrids and understand the nature of photoinduced interactions between CNT and selected molecular systems such as porphyrins, fullerenes and oligo (p-phynylenevinylenes). We established a new protocol for the dispersion of SWCNTs in aqueous media via non-covalent interactions and demonstrated that some CNT-based hybrids are suitable for testing in PV devices. The second part of the work is focussed on the study of homoleptic and heteroleptic Ru(II) complexes with bipyridine and extended phenanthroline ligands. Our studies demonstrated that these compounds are potentially useful as light harvesting systems for solar energy conversion. Both CNT materials and Ru(II) complexes have turned out to be remarkable examples of photoactive systems. The morphological and photophysical characterization of CNT-based multicomponent systems allowed a satisfactory rationalization of the photoinduced interactions between the individual units, despite several hurdles related to the intrinsic properties of CNTs that prevent, for instance, the utilization of laser spectroscopic techniques. Overall, this work may prompt the design and development of new functional materials for photovoltaic devices.