310 resultados para Growing neural gas


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Polypyrrole exhibits reversible changes in their direct current resistance on exposure to organic volatiles. However, one needs to employ an array of such sensors to discriminate organic volatiles present in a mixture. Hence, polypyrrole based gas sensor is designed for the detection and discrimination of different organic volatiles. Multi frequency impedance measurement technique is used to detect the organic vapors, such as acetone, ethanol and Isopropyl alcohol, in the gas phase, over a frequency range 10 Hz to 2 MHz. The sensor response is monitored by measuring the changes in its capacitance, resistance and the dissipation factor upon exposure to organic volatiles. It is observed that the capacitive property of the sensor is more sensitive to these volatiles than its resistive property. Each volatile responds to the sensor in terms of dissipation factor at specific frequency and found that the peak magnitude has a linear relationship with their concentrations.

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The design of a solid electrolyte that permits the use of dissimilar gas electrodes in an electrochemical cell is presented. It consists of a functionally gradient material with spatial variation in composition. The activity of the conducting ion is fixed at each electrode using different gas species. The system chosen for demonstrating the concept consists of a solid solution between K2CO3 and K2SO4. The composition of the solid solution varies from pure K2CO3 in contact with a CO2 + O2 gas mixture at one electrode to pure K2SO4 exposed to a mixture of SO3 + SO2 + O2 at the other. Two types of composition profiles are studied, one with monotonic variation in composition and the other with extrema. The e.m.f. of the cells is studied as a function of temperature and composition of the gas mixture at each electrode. The results indicate that the e.m.f. is determined primarily by the difference in the chemical potential of potassium at the two electrodes. The diffusion potential caused by ionic concentration gradients in the electrolyte appears to be negligible when the corresponding ionic transport numbers are insignificant. Studies on the response characteristics of the cell based on the gradient electrolyte indicate that the nature of the variation in composition of the electrolyte has only a minor effect on the time evolution of e.m.f. The gradient solid electrolytes have potential application in multielement galvanic sensors at high temperatures.

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This study aims to determine optimal locations of dual trailing-edge flaps and blade stiffness to achieve minimum hub vibration levels in a helicopter, with low penalty in terms of required trailing-edge flap control power. An aeroelastic analysis based on finite elements in space and time is used in conjunction with an optimal control algorithm to determine the flap time history for vibration minimization. Using the aeroelastic analysis, it is found that the objective functions are highly nonlinear and polynomial response surface approximations cannot describe the objectives adequately. A neural network is then used for approximating the objective functions for optimization. Pareto-optimal points minimizing both helicopter vibration and flap power ale obtained using the response surface and neural network metamodels. The two metamodels give useful improved designs resulting in about 27% reduction in hub vibration and about 45% reduction in flap power. However, the design obtained using response surface is less sensitive to small perturbations in the design variables.

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We present a study of the growth of local, nonaxisymmetric perturbations in gravitationally coupled stars and gas in a differentially rotating galactic disk. The stars and gas are treated as two isothermal fluids of different velocity dispersions, with the stellar velocity dispersion being greater than that for the gas. We examine the physical effects of inclusion of a low-velocity dispersion component (gas) on the growth of non-axisymmetric perturbations in both stars and gas, as done for the axisymmetric case by Jog & Solomon. The amplified perturbations in stars and gas constitute trailing, material, spiral features which may be identified with the local spiral features seen in all spiral galaxies. The formulation of the two-fluid equations closely follows the one-fluid treatment by Goldreich & Lynden-Bell. The local, linearized perturbation equations in the sheared frame are solved to obtain the results for a temporary growth via swing amplification. The problem is formulated in terms of five dimensionless parameters-namely, the Q-factors for stars and gas, respectively; the gas mass fraction; the shearing rate in the galactic disk; and the length scale of perturbation. By using the observed values of these parameters, we obtain the amplifications and the pitch angles for features in stars and gas for dynamically distinct cases, as applicable for different regions of spiral galaxies. A real galaxy consisting of stars and gas may display growth of nonaxisymmetric perturbations even when it is stable against axisymmetric perturbations and/or when either fluid by itself is stable against non-axisymmetric perturbations. Due to its lower velocity dispersion, the gas exhibits a higher amplification than do the stars, and the amplified gas features are slightly more tightly wound than the stellar features. When the gas contribution is high, the stellar amplification and the range of pitch angles over which it can occur are both increased, due to the gravitational coupling between the two fluids. Thus, the two-fluid scheme can explain the origin of the broad spiral arms in the underlying old stellar populations of galaxies, as observed by Schweizer and Elmegreen & Elmegreen. The arms are predicted to be broader in gas-rich galaxies, as is indeed seen for example in M33. In the linear regime studied here, the arm contrast is shown to increase with radius in the inner Galaxy, in agreement with observations of external galaxies by Schweizer. These results follow directly due to the inclusion of gas in the problem.

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Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

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Gas-phase controlled absorption of ammonia in foams made of solutions of sulphuric acid has been studied experimentally. Effects of gas-phase concentration of ammonia and type of surfactant on the performance of the foam-bed reactor are investigated. Gas-phase controlled absorption from a spherical bubble is anaylzed using the asymptotic value of Sherwood number (Sh = 6.58), for both negligible as well as significant changes in the volume of the bubble. The experimental data are shown to be in good agreement with the single-stage model of the foam-bed reactor using these asymptotic sub-models, as well as the diffusion-in-sphere analysis available in literature. Influence of effective diffusivity on the time dependence of fractional gas absorption has been found to be unimportant for foam columns with large times of contact. The asymptotic sub-models have been compared and use of the rigid-sphere asymptotic sub-model is recommended for foam columns of practical relevence.

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The basic concepts and techniques involved in the development and analysis of mathematical models for individual neurons and networks of neurons are reviewed. Some of the interesting results obtained from recent work in this field are described. The current status of research in this field in India is discussed

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Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.

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Observations of surface flow patterns of steel and aluminum GTAW pools have been made using a pulsed laser visualization system. The weld pool convection is found to be three-dimensional with the azimuthal circulation depending on the location of the clamp with respect to the torch. Oscillation of steel pools and undulating motion in aluminum weld pools are also observed even with steady process parameters. Current axisymmetric numerical models are unable to explain such phenomena. A three-dimensional computational study is carried out in this study to explain the rotational flow in aluminum weld pools.

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The problem of spurious patterns in neural associative memory models is discussed, Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out, A solution based on the notion of neural self-interaction with a suitably chosen magnitude is presented for the Hebb learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns, With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.

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The statistical mechanics of a two-dimensional Coulomb gas confined to one dimension is studied, wherein hard core particles move on a ring. Exact self-duality is shown for a version of the sine-Gordon model arising in this context, thereby locating the transition temperature exactly. We present asymptotically exact results for the correlations in the model and characterize the low- and high-temperature phases. Numerical simulations provide support to these renormalization group calculations. Connections with other interesting problems, such as the quantum Brownian motion of a panicle in a periodic potential and impurity problems, are pointed out.

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In this paper we propose that the compressive tidal held in the centers of flat-core early-type galaxies and ultraluminous galaxies compresses molecular clouds producing dense gas observed in the centers of these galaxies. The effect of galactic tidal fields is usually considered disruptive in the literature. However, for some galaxies, the mass profile flattens toward the center and the resulting galactic tidal field is not disruptive, but instead it is compressive within the flat-core region. We have used the virial theorem to determine the minimum density of a molecular cloud to be stable and gravitationally bound within the tidally compressive region of a galaxy. We have applied the mechanism to determine the mean molecular cloud densities in the centers of a sample of flat-core, early-type galaxies and ultraluminous galaxies. For early-type galaxies with a core-type luminosity profile, the tidal held of the galaxy is compressive within half the core radius. We have calculated the mean gas densities for molecular gas in a sample of early-type galaxies which have already been detected in CO emission, and we obtain mean densities of [n] similar to 10(3)-10(6) cm(-3) within the central 100 pc radius. We also use our model to calculate the molecular cloud densities in the inner few hundred parsecs of a sample of ultraluminous galaxies. From the observed rotation curves of these galaxies we show that they have a compressive core within their nuclear region. Our model predicts minimum molecular gas densities in the range 10(2)-10(4) cm(-3) in the nuclear gas disks; the smaller values are applicable typically for galaxies with larger core radii. The resulting density values agree well with the observed range. Also, for large core radii, even fairly low-density gas (similar to 10(2) cm(-3)) can remain bound and stable close to the galactic center.

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A neural network has been used to predict the flow intermittency from velocity signals in the transition zone in a boundary layer. Unlike many of the available intermittency detection methods requiring a proper threshold choice in order to distinguish between the turbulent and non-turbulent parts of a signal, a trained neural network does not involve any threshold decision. The intermittency prediction based on the neural network has been found to be very satisfactory.

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A high speed photographic technique has been employed to measure the Sauter mean diameter of bubbles experimentally in a gas liquid ejector using a sodium chloride-air system. The measured values are compared with the theoretically predicted maximum bubble size diameter using Sprow's correlation. Bubble size as a function of the liquid flow rate and also of its distance from the throat of the ejector has been reported in this paper. The results obtained for this non-reactive system are also compared with those obtained earlier for the air-water system.

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We report low-frequency 1/f-noise measurements of degenerately doped Si:P delta layers at 4.2 K. The noise was found to be over six orders of magnitude lower than that of bulk Si:P systems in the metallic regime and is one of the lowest values reported for doped semiconductors. The noise was nearly independent of magnetic field at low fields, indicating negligible contribution from universal conductance fluctuations. Instead, the interaction of electrons with very few active structural two-level systems may explain the observed noise magnitude.