204 resultados para parameter tuning, swarm intelligence, controllo semaforico, auto-organizzazione


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Equivalence of certain classes of second-order non-linear distributed parameter systems and corresponding linear third-order systems is established through a differential transformation technique. As linear systems are amenable to analysis through existing techniques, this study is expected to offer a method of tackling certain classes of non-linear problems which may otherwise prove to be formidable in nature.

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The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

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The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

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Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

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This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

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A novel, cost effective,environment-friendly and energetically beneficial alternative method for the synthesis of giant dielectric pseudo-perovskite material CaCu3Ti4O12 (CCTO) is presented. The method involved auto-combustion of an aqueous precursor solution in oxygen atmosphere with the help of external fuels and is capable of producing high amount of CCTO at ultra-low temperature, in the combustion residue itself. The amount of phase generated was observed to be highly dependent on the combustion process i.e. on the nature and amount of external-fuels added for combustion. Two successful fuel combinations capable of producing reasonably higher amount of the desired compound were investigated. On a structural characterization grain size was observed to decrease drastically to nano-dimension compared to submicron-size that was obtained in a traditional sol-gel combustion and subsequent cacination method. Therefore, the method reported can produce nano-crystalline CaCu3Ti4O12 ceramic matrix at an ultra-low temperature and is expected to be applicable for other multifunctional perovskite oxide materials.

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The apparent contradiction between the exact nature of the interaction parameter formalism as presented by Lupis and Elliott and the inconsistencies discussed recently by Pelton and Bale arise from the truncation of the Maclaurin series in the latter treatment. The truncation removes the exactness of the expression for the logarithm of the activity coefficient of a solute in a multi-component system. The integrals are therefore path dependent. Formulae for integration along paths of constant Xi,or X i/Xj are presented. The expression for In γsolvent given by Pelton and Bale is valid only in the limit that the mole fraction of solvent tends to one. The truncation also destroys the general relations between interaction parameters derived by Lupis and Elliott. For each specific choice of parameters special relationships are obtained between interaction parameters.

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We show that the characteristic Mn2+ d emission color from Mn2+-doped CdS nanocrystals can be tuned over as much as 40 nm, in contrast to what should be expected from such a nearly localized d-d transition. This is achieved surprisingly by a fine-tuning of the host particle diameter from 1.9 to 2.6 nm, thereby changing the overall emission color from red to yellow. Systematic experiments in conjunction with state-of-the-art ab initio calculations with full geometry optimization establish that Mn2+ ions residing at surface/subsurface regions have a distorted tetrahedral coordination resulting in a larger ligand field splitting. Consequently, these near-surface Mn2+ species exhibit a lower Mn2+ d emission energy, compared to those residing at the core of the nanocrystal with an undisturbed tetrahedral coordination. The origin of the tunability of the observed Mn2+ emission is the variation of emission contributions arising from Mn2+ doped at the core, subsurface, and surface of the host. Our findings provide a unique and easy method to identify the location of an emitting Mn2+ ion in the nanocrystal, which would be otherwise very difficult to decipher.

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Novel one and two dimensional NMR techniques are proposed and utilized for the determination of the signs of the order parameters used for the study of the mobility of the fatty acid chains. The experiments designed to extract this information involve the use of the intensities of the side bands in the spectra of oriented systems spinning at the magic angle. Advantages of the two dimensional technique over the one dimensional method are discussed. The utility of the method in the study of the dynamic properties of membranes and model systems is pointed out.

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The use of the intensities of the spinning sidebands in the magic-angle spinning spectra of oriented molecules is proposed for the determination of the signs of the order parameters. The method is demonstrated for benzene and chloroform oriented in nematic phases of liquid crystals. On the basis of the theoretical expressions derived for the various order sidebands, the applicability of the method for different experimental conditions is discussed.

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We calculate the kaon B parameter in quenched lattice QCD at beta=6.0 using Wilson fermions at kappa=0.154 and 0.155. We use two kinds of nonlocal (''smeared'') sources for quark propagators to calculate the matrix elements between states of definite momentum. The use of smeared sources yields results with much smaller errors than obtained in previous calculations with Wilson fermions. By combining results for p=(0,0,0) and p=(0,0,1), we show that one can carry out the noperturbative subtraction necessary to remove the dominant lattice artifacts induced by the chiral-symmetry-breaking term in the Wilson action. Our final results are in good agreement with those obtained using staggered fermions. We also present results for B parameters of the DELTAI = 3/2 part of the electromagnetic penguin operators, and preliminary results for B(K) in the presence of two flavors of dynamical quarks.

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We elucidate the relationship between effective mass and carrier concentration in an oxide semiconductor controlled by a double-doping mechanism. In this model oxide system, Sr1-xLaxTiO3-delta, we can tune the effective mass ranging from 6 to 20m(e) as a function of filling (carrier concentration) and the scattering mechanism, which are dependent on the chosen lanthanum-and oxygen-vacancy concentrations. The effective mass values were calculated from the Boltzmann transport equation using the measured transport properties of thin films of Sr1-xLaxTiO3-delta. We show that the effective mass decreases with carrier concentration in this large-band-gap, low-mobility oxide, and this behavior is contrary to the traditional high-mobility, small-effective-mass semiconductors.

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A four and a five-parameter functions are used to analyse and interpret the high and low temperature thermodynamic data and phase equilibria in the Ga-In system.