Implementation of two-stage Hopfield model and its application in nonlinear systems

This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. 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 or weighting parameters for its initialization.

Cooperação em sagüis comuns callithrix jacchus: condições e restrições

The cooperative behavior is no longer a dilemma for the theory of evolution, since there are models that explain the evolution of this behavior by means of natural selection at the individual level. However, there have been few studies on the proximal factors that interfere with cooperative behavior. In the study of the influence of cognition on cooperation, many authors have been interested in situations in which individuals decide whether to act cooperatively and select partners with different qualities to cooperate. Of the factors studied, we highlight the need for understanding the apparatus and communication between partners to the occurrence of cooperation. Recently, highlight is the proposal that the ability to cooperate would be greater in species with cooperative breeding system. Thus, the common marmoset (Callithrix jacchus) is a New World monkey which stands as a valuable species for this type of study because it presents cooperative actions in nature, such as sharing food and protection of the community territory. Our experiment investigated whether common marmosets unrelated females (n = 6) were able to cooperate using an electrical and a mechanical apparatus, if this cooperation is a byproduct of individual actions or involve social attention, if it occurs inter-individual variation in the use of devices and formation of roles (producer / scrounger) in dyads. We use the number of rewards obtained by animals (Ratio of Correct Pulls) as indicators of cooperation and glances for partners (Ratio of Correct Glances) as indicators of social attention and communication. The results indicate that the type of apparatus was not a constraint for the occurrence of cooperation between the marmosets, but still has not been verified formation of roles in the dyads. The performance of animals in the two devices showed a large variation in the learning time, not having relationship with the performance in the tests phase. In both devices the level of social glances at control phases were casually correlated with any other phase, but the data showed that there was not social attention, that is, the monkeys realized that they gave food to the partners, but the partners did

An effortless hybrid method to solve economic load dispatch problem in power systems

This paper proposes a new approach and coding scheme for solving economic dispatch problems (ED) in power systems through an effortless hybrid method (EHM). This novel coding scheme can effectively prevent futile searching and also prevents obtaining infeasible solutions through the application of stochastic search methods, consequently dramatically improves search efficiency and solution quality. The dominant constraint of an economic dispatch problem is power balance. The operational constraints, such as generation limitations, ramp rate limits, prohibited operating zones (POZ), network loss are considered for practical operation. Firstly, in the EHM procedure, the output of generator is obtained with a lambda iteration method and without considering POZ and later in a genetic based algorithm this constraint is satisfied. To demonstrate its efficiency, feasibility and fastness, the EHM algorithm was applied to solve constrained ED problems of power systems with 6 and 15 units. The simulation results obtained from the EHM were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time. (C) 2011 Elsevier Ltd. All rights reserved.

Metabolic response to feeding in Tupinambis merianae: Circadian rhythm and a possible respiratory constraint

The diurnal tegu lizard Tupinambis merianae exhibits a marked circadian variation in metabolism that is characterized by the significant increase in metabolism during part of the day. These increases in metabolic rate, found in the fasting animal, are absent during the first 2 d after meal ingestion but reappear subsequently, and the daily increase in metabolic rate is added to the increase in metabolic rate caused by digestion. During the first 2 d after feeding, priority is given to digestion, while on the third and following days, the metabolic demands are clearly added to each other. This response seems to be a regulated response of the animal, which becomes less active after food ingestion, rather than an inability of the respiratory system to support simultaneous demands at the beginning of digestion. The body cavity of Tupinambis is divided into two compartments by a posthepatic septum (PHS). Animals that had their PHS surgically removed showed no significant alteration in the postprandial metabolic response compared to tegus with intact PHS. The maximal metabolic increment during digestion, the relative cost of meal digestion, and the duration of the process were virtually unaffected by the removal of the PHS.

A constraint on the x dependence of the light antiquarks ratio

We perform a careful study on the effect of the Pauli blocking to the light antiquark structure of the proton sea. We develop the formal expressions for the antiquark distributions, highlighting the role played by quark statistics and the vacuum structure. Ratios involving the antiquarks are calculated. In particular, it is found that Delta(d) over bar (x)/Delta(u) over bar (x) should be negative and x independent. (C) 2002 Elsevier B.V. B.V. All rights reserved.

C programs for solving the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Solving the conundrum of Job: a probable biblical description of chronic renal failure with neurological symptoms

A doença descrita no livro bíblico de Jó é controversa, e tem interessado a teólogos, psiquiatras e dermatologistas, há tempos. Neste trabalho os autores apontam para evidências do diagnóstico de insuficiência renal crônica com alterações neurológicas.

Quantization of (2+1)-spinning particles and bifermionic constraint problem

This work is a natural continuation of our recent study in quantizing relativistic particles. There it was demonstrated that, by applying a consistent quantization scheme to the classical model of a spinless relativistic particle as well as to the Berezin-Marinov model of a 3 + 1 Dirac particle, it is possible to obtain a consistent relativistic quantum mechanics of such particles. In the present paper, we apply a similar approach to the problem of quantizing the massive 2 + 1 Dirac particle. However, we stress that such a problem differs in a nontrivial way from the one in 3 + 1 dimensions. The point is that in 2 + 1 dimensions each spin polarization describes different fermion species. Technically this fact manifests itself through the presence of a bifermionic constant and of a bifermionic first-class constraint. In particular, this constraint does not admit a conjugate gauge condition at the classical level. The quantization problem in 2 + 1 dimensions is also interesting from the physical viewpoint (e.g., anyons). In order to quantize the model, we first derive a classical formulation in an effective phase space, restricted by constraints and gauges. Then the condition of preservation of the classical symmetries allows us to realize the operator algebra in an unambiguous way and construct an appropriate Hilbert space. The physical sector of the constructed quantum mechanics contains spin-1/2 particles and antiparticles without an infinite number of negative-energy levels, and exactly reproduces the one-particle sector of the 2 + 1 quantum theory of a spinor field.

Solving Schrödinger equation for two dimensional potential using supersymmetry

The formalism of supersymmetric Quantum Mechanics can be extended to arbitrary dimensions. We introduce this formalism and explore its utility to solve the Schodinger equation for a bidimensional potential. This potential can be applied in several systens in physical and chemistry context, for instance, it can be used to study benzene molecule.

A W-matrix methodology for solving sparse network equations on multiprocessor computers

This paper describes a methodology for solving efficiently the sparse network equations on multiprocessor computers. The methodology is based on the matrix inverse factors (W-matrix) approach to the direct solution phase of A(x) = b systems. A partitioning scheme of W-matrix , based on the leaf-nodes of the factorization path tree, is proposed. The methodology allows the performance of all the updating operations on vector b in parallel, within each partition, using a row-oriented processing. The approach takes advantage of the processing power of the individual processors. Performance results are presented and discussed.

Neural approach for solving several types of optimization problems

Neural networks consist of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent neural net-works that can be used to solve several classes of optimization problems. More specifically, a modified Hopfield network is developed and its inter-nal parameters are computed explicitly using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points, which represent a solution of the problem considered. The problems that can be treated by the proposed approach include combinatorial optimiza-tion problems, dynamic programming problems, and nonlinear optimization problems.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft drink plants

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)