29 resultados para Activation function-1

em Indian Institute of Science - Bangalore - Índia


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In this brief, we present a new circuit technique to generate the sigmoid neuron activation function (NAF) and its derivative (DNAF). The circuit makes use of transistor asymmetry in cross-coupled differential pair to obtain the derivative. The asymmetry is introduced through external control signal, as and when required. This results in the efficient utilization of the hard-ware by realizing NAF and DNAF using the same building blocks. The operation of the circuit is presented in the subthreshold region for ultra low-power applications. The proposed circuit has been experimentally prototyped and characterized as a proof of concept on the 1.5-mum AMI technology.

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A new performance metric, Peak-Error Ratio (PER) has been presented to benchmark the performance of a class of neuron circuits to realize neuron activation function (NAF) and its derivative (DNAF). Neuron circuits, biased in subthreshold region, based on the asymmetric cross-coupled differential pair configuration and conventional configuration of applying small external offset voltage at the input have been compared on the basis of PER. It is shown that the technique of using transistor asymmetry in a cross-coupled differential pair performs on-par with that of applying external offset voltage. The neuron circuits have been experimentally prototyped and characterized as a proof of concept on the 1.5 mu m AMI technology.

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A new performance metric, Peak-Error Ratio (PER) has been presented to benchmark the performance of a class of neuron circuits to realize neuron activation function (NAF) and its derivative (DNAF). Neuron circuits, biased in subthreshold region, based on the asymmetric cross-coupled differential pair configuration and conventional configuration of applying small external offset voltage at the input have been compared on the basis of PER. It is shown that the technique of using transistor asymmetry in a cross-coupled differential pair performs on-par with that of applying external offset voltage. The neuron circuits have been experimentally prototyped and characterized as a proof of concept on the 1.5 mu m AMI technology.

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Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

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This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

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In this paper, we use optical flow based complex-valued features extracted from video sequences to recognize human actions. The optical flow features between two image planes can be appropriately represented in the Complex plane. Therefore, we argue that motion information that is used to model the human actions should be represented as complex-valued features and propose a fast learning fully complex-valued neural classifier to solve the action recognition task. The classifier, termed as, ``fast learning fully complex-valued neural (FLFCN) classifier'' is a single hidden layer fully complex-valued neural network. The neurons in the hidden layer employ the fully complex-valued activation function of the type of a hyperbolic secant function. The parameters of the hidden layer are chosen randomly and the output weights are estimated as the minimum norm least square solution to a set of linear equations. The results indicate the superior performance of FLFCN classifier in recognizing the actions compared to real-valued support vector machines and other existing results in the literature. Complex valued representation of 2D motion and orthogonal decision boundaries boost the classification performance of FLFCN classifier. (c) 2012 Elsevier B.V. All rights reserved.

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In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.

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The reactivation kinetics of passivated boron accepters in hydrogenated silicon during zero bias annealing in the temperature range of 65-130 degrees C are reported, For large annealing times and high annealing temperatures, the reactivation process follows second-order kinetics and is rate limited by a thermally activated <(H)over tilde (2)> complex formation process, For short annealing times and low annealing temperatures, the reactivation rate is found to be larger than that due to <(H)over tilde (2)> complex formation alone. We conclude that the faster reactivation is caused by the diffusion of the liberated hydrogen atoms into the bulk as well as <(H)over tilde (2)> complex formation. The effective diffusion coefficient of hydrogen is measured and found to obey the Arrhenius relation with an activation energy (1.41 +/- 0.1) eV. (C) 1997 American Institute of Physics.

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Transactivator protein C of bacteriophage mu is essential for the transition from middle to late gene expression during the phage life cycle. The unusual, multistep activation of mom promoter (Pmom) by C protein involves activator-mediated promoter unwinding to recruit RNA polymerase and subsequent enhanced promoter clearance of the enzyme. To achieve this, C binds its site overlapping the -35 region of the mom promoter with a very high affinity, in Mg2+-dependent fashion. Mg2+-mediated conformational transition in C is necessary for its DNA binding and transactivation. We have determined the residues in C which coordinate Mg2+, to induce allosteric transition in the protein, required for the specific interaction with DNA. Residues E26 and D40 in the putative metal binding motif (E26X10D37X2D40) present toward the N-terminus of the protein are found to be important for Mg2+ ion binding. Mutations in these residues lead to altered Mg2+-induced conformation, compromised DNA binding, and reduced levels of transcription activation. Although Mg2+ is widely used in various DNA transaction reactions, this report provides the first insights on the importance of the metal ion-induced allosteric transitions in regulating transcription factor function.

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We analyze recent experimental results of Sundström and Gillbro by using the theory of Bagchi, Fleming and Oxtoby. The experimental results are in good agreement with this theory, but not with the earlier theory of Förster and Hoffmann. By fitting the new experimental results to the theory, we obtain approximate estimates of the frequency of the excited surface (assumed harmonic) and the width of the sink function.

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There exist many investigations of ionic transport in a variety of glasses. These studies exhibit strong correlation between ionic conductivity and activation energy: Typically, it is found that higher conductivity is associated with lower activation energies and vice versa. Although there are explanations for this at a phenomenological level, there is no consistent physical picture to explain the correlation between conductivity and activation energy. We have carried out molecular dynamics simulation as a function of the size of the impurity atom or diffusant (both neutral and charged) in a host amorphous matrix. We find that there is a maximum in self-diffusivity as a function of the size of the impurity atom suggesting that there is an appropriate size for which the diffusivity is maximum. The activation energy is found to be the lowest for this size of the impurity. A similar maximum has been previously found in other condensed phases, such as confined fluids and dense liquids, and has its origin in the levitation effect. The implications of this result for understanding ionic conductivity in glasses are discussed. Our results suggest that there is a relation between microscopic structure of the amorphous solid, diffusivity or conductivity, and activation energy. The nature of this relationship is discussed in terms of the levitation parameter showing that diffusivity is maximum when the size of the neck or doorway radius is comparable with the size of the diffusant. Our computational results here are in excellent agreement with independent experimental results of Nascimento et al. [Braz. J. Phys. 35, 626 (2005)] that structural features of the glass are important in determining the ionic conductivity.

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Laser mediated stimulation of biological process was amongst its very first effects documented by Mester et al. but the ambiguous and tissue-cell context specific biological effects of laser radiation is now termed ‘Photobiomodulation’. We found many parallels between the reported biological effects of lasers and a multiface-ted growth factor, Transforming Growth Factor-β (TGF-β). This review outlines the interestingparallelsbetween the twofieldsand our rationalefor pursuingtheir potential causal correlation. We explored this correlation using an in vitro assay systems and a human clinical trial on healing wound extraction sockets that we reported in a recent publication. In conclusion we report that low power laser irradiation can activate latent TGF-β1 and β3 complexes and suggest that this might be one of the major modes of the photobiomodulatory effects of low power lasers.

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Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis, infects one-third of the world's population. Activation of host immune responses for containment of mycobacterial infections involves participation of innate immune cells, such as dendritic cells (DCs). DCs are sentinels of the immune system and are important for eliciting both primary and secondary immune responses to pathogens. In this context, to understand the molecular pathogenesis of tuberculosis and host response to mycobacteria and to conceive prospective vaccine candidates, it is important to understand how cell wall Ags of M.tuberculosis and, in particular, the proline-glutamic acid-polymorphicguanine-cytosine-rich sequence (PE_PGRS) family of proteins modulate DC maturation and function. In this study, we demonstrate that two cell wall-associated/secretory PE_PGRS proteins, PE_PGRS 17 (Rv0978c) and PE_PGRS 11 (Rv0754), recognize TLR2, induce maturation and activation of human DCs, and enhance the ability of DCs to stimulate CD4(+) T cells. We further found that PE_PGRS protein-mediated activation of DCs involves participation of ERK1/2, p38 MAPK, and NF-kappa B signaling pathways. Priming of human DCs with IFN-gamma further augmented PE_PGRS 17 or PE_PGRS 11 Ag-induced DC maturation and secretion of key proinflammatory cytokines. Our results suggest that by activating DCs, PE_PGRS proteins, important mycobacterial cell wall Ags, could potentially contribute in the initiation of innate immune responses during tuberculosis infection and hence regulate the clinical course of tuberculosis. The Journal of Immunology, 2010, 184: 3495-3504.

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Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis, infects one-third of the world's population. Activation of host immune responses for containment of mycobacterial infections involves participation of innate immune cells, such as dendritic cells (DCs). DCs are sentinels of the immune system and are important for eliciting both primary and secondary immune responses to pathogens. In this context, to understand the molecular pathogenesis of tuberculosismand host response to mycobacteria and to conceive prospective vaccine candidates, it is important to understand how cell wall Ags of M. tuberculosis and, in particular, the proline-glutamic acid-polymorphic guanine-cytosine-rich sequence (PE_PGRS) family of proteins modulate DC maturation and function. In this study, we demonstrate that two cell wall-associated/secretory PE_PGRS proteins, PE_PGRS 17 (Rv0978c) and PE_PGRS 11 (Rv0754), recognize TLR2, induce maturation and activation of human DCs, and enhance the ability of DCs to stimulate CD4(+) T cells. We further found that PE_PGRS protein-mediated activation of DCs involves participation of ERK1/2, p38 MAPK, and NF-kappa B signaling pathways. Priming of human DCs with IFN-gamma further augmented PE_PGRS 17 or PE_PGRS 11 Ag-induced DC maturation and secretion of key proinflammatory cytokines. Our results suggest that by activating DCs, PE_PGRS proteins, important mycobacterial cell wall Ags, could potentially contribute in the initiation of innate immune responses during tuberculosis infection and hence regulate the clinical course of tuberculosis. The Journal of Immunology, 2010, 184: 3495-3504.

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Further purification of indoleacetaldoxime (IAOX) hydro-lyase from Gibberella fujikuroi by DEAE-cellulose chromatography is described. The purified enzyme was activated by dehydroascorbic acid (DHA), ascorbic acid (AA), and pyridoxal phosphate (PALP) and was inhibited by thiol compounds and thiol reagents including phenylthiocyanate. Ferrous ions but not ferric ions activated the purified enzyme. The enzyme was activated by dihydrofolic acid but inhibited by tetrahydrofolic acid. Phenylacetaldoxime, a competitive inhibitor, afforded partial protection of the enzyme from the action of N-ethylmaleimide suggesting the involvement of a thiol function at the active site or substrate-binding site. The inhibition of the enzyme by 2,3-dimercaptopropanol was reversed by DHA, PALP, or frozen storage. KCN inhibition of the enzyme was reversed by PALP. NaBH4 reduction of the purified enzyme in the presence of PALP gave an active enzyme which was further activated by PALP or DHA but not by ferrous ions. These results suggested a "structural" role for PALP in the activity of IAOX hydro-lyase. Dilute solutions of the purified enzyme, obtained during DEAE-cellulose chromatography and concentrated using sucrose, showed enhanced activity upon frozen storage and thawing. The increase in activity of the enzyme during certain culture conditions, the activation and inhibition of the enzyme by several unrelated compounds, and the effect of freezing indicate that IAOX hydro-lyase is probably a metabolically regulated enzyme with a structure composed of subunits.