11 resultados para Input Distance Function

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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This paper proposes novel universal logic gates using the current quantization characteristics of nanodevices. In nanodevices like the electron waveguide (EW) and single-electron (SE) turnstile, the channel current is a staircase quantized function of its control voltage. We use this unique characteristic to compactly realize Boolean functions. First we present the concept of the periodic-threshold threshold logic gate (PTTG), and we build a compact PTTG using EW and SE turnstiles. We show that an arbitrary three-input Boolean function can be realized with a single PTTG, and an arbitrary four-input Boolean function can be realized by using two PTTGs. We then use one PTTG to build a universal programmable two-input logic gate which can be used to realize all two-input Boolean functions. We also build a programmable three-input logic gate by using one PTTG. Compared with linear threshold logic gates, with the PTTG one can build digital circuits more compactly. The proposed PTTGs are promising for future smart nanoscale digital system use.

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Random field theory has been used to model the spatial average soil properties, whereas the most widely used, geostatistics, on which also based a common basis (covariance function) has been successfully used to model and estimate natural resource since 1960s. Therefore, geostistics should in principle be an efficient way to model soil spatial variability Based on this, the paper presents an alternative approach to estimate the scale of fluctuation or correlation distance of a soil stratum by geostatistics. The procedure includes four steps calculating experimental variogram from measured data, selecting a suited theoretical variogram model, fitting the theoretical one to the experimental variogram, taking the parameters within the theoretical model obtained from optimization into a simple and finite correlation distance 6 relationship to the range a. The paper also gives eight typical expressions between a and b. Finally, a practical example was presented for showing the methodology.

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Although studies on carbon burial in lake sediments have shown that lakes are disproportionately important carbon sinks, many studies on gaseous carbon exchange across the water-air interface have demonstrated that lakes are supersaturated with CO2 and CH4 causing a net release of CO2 and CH4 to the atmosphere. In order to more accurately estimate the net carbon source/sink function of lake ecosystems, a more comprehensive carbon budget is needed, especially for gaseous carbon exchange across the water-air interface. Using two methods, overall mass balance and gas exchange and carbon burial balance, we assessed the carbon source/sink function of Lake Donghu, a subtropical, eutrophic take, from April 2003 to March 2004. With the overall mass balance calculations, total carbon input was 14 905 t, total carbon output was 4950 1, and net carbon budget was +9955 t, suggesting that Lake Donghu was a great carbon sink. For the gas exchange and carbon burial balance, gaseous carbon (CO2 and CH4) emission across the water-air interface totaled 752 t while carbon burial in the lake sediment was 9477 t. The ratio of carbon emission into the atmosphere to carbon burial into the sediment was only 0.08. This low ratio indicates that Lake Donghu is a great carbon sink. Results showed good agreement between the two methods with both showing Lake Donghu to be a great carbon sink. This results from the high primary production of Lake Donghu, substantive allochthonous carbon inputs and intensive anthropogenic activity. Gaseous carbon emission accounted for about 15% of the total carbon output, indicating that the total output would be underestimated without including gaseous carbon exchange. (C) 2007 Elsevier Ltd. All rights reserved.

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In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

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One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue of multi-thresholded, the variable transfer function neuron switch on among different nonlinear excitated state. And the comparison of output's transfer characteristics between it and single-thresholded neuron will be illustrated, with some practical application experiments on Bi-level logic operation, at last the simple comparison with conventional BP, RBF, and even DBF NN is taken to expect the development foreground on the variable neuron.. The novel nonlinear transfer function neuron could implement the random nonlinear mapping relationship between input layer and output layer, which could make variable transfer function neuron have one much wider applications on lots of reseach realm such as function approximation pattern recognition data compress and so on.

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A matrix analysis for free-space switching networks, such as perfect shuffle-exchange omega, crossover and Banyan is presented. On the basis of matrix analysis, the equivalence of these three switching networks and the route selection between input and output ports are simply explained. Furthermore, an optical crossover switching network, where MQW SEED arrays are used as electrically addressed four-function interchange nodes, is described and the optical crossover interconnection of 64 x 64, and high-speed four-function, interchange nodes is demonstrated in the experiment.

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In a practical coupling system, a cylindrical microlens is used to collimate the emission of a high powerlaser diode (LD) in the dimension perpendicular to the junction plane. Using passive alignment, the LD isplaced in the focus of the cylindrical microlens generally, regardless of the performance of the multimodeoptical fiber and the LD. In this paper, a more complete analysis is arrived at by ray-tracing technique,by which the angle θ of the ray after refraction is computed as a function of the angle θo of the ray beforerefraction. The focus of the cylindrical microlens is not always the optimal position of the LD. In fact, inorder to achieve a higher coupling efficiency, the optimal distance from the LD to the cylindrical microlensis dependent on not only the radius R and the index of refraction n of the cylindrical microlens, but alsothe divergence angle of the LD in the dimension perpendicular to the junction plane and the numericalaperture (NA) of the multimode optical fiber. The results of this discussion are in good agreement withexperimental results.

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The toughness of polypropylene (PP)/ethylene-propylene-diene monomer rubber (EPDM) blends containing various EPDM contents as a function of the tensile speed was studied. The toughness of the blends was determined from the tensile fracture energy of the side-edge notched samples. A sharp brittle-tough transition was observed in the fracture energy versus interparticle distance (ID) curves when the crosshead speed < 102.4 mm/min. It was observed that the brittle-ductile transition of PP/EPDM blend occurred either by reducing ID or by decreasing the tensile speed. The correlation between the critical interparticle distance and tensile deformation rate was compared with that between the critical interparticle distance and temperature for PP/EPDM blends. (C) 2000 Elsevier Science Ltd. All rights reserved.

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The toughness of high-density polyethylene (HDPE)/glass-bead blends containing various glass-bead contents as a function of temperature was studied. The toughness of the blends was determined from the notch Izod impact test. A sharp brittle-ductile transition was observed in impact strength-interparticle distance (ID) curves at various temperatures. The brittle-ductile transition of HDPE/glass-bead blends occurred either with reduced ID or with increased temperature. The results indicated that the brittle-ductile-transition temperature dropped markedly with increasing glass-bead content. Moreover, the correlation between the critical interparticle distance (ID.) and temperature was obtained. Similar to the ID, of polymer blends with elastomers, the ID, nonlinearly increased with increasing temperature. However, this was the first observation of the variation of the ID, with temperature for polymer blends with rigid particles. (C) 2001 John Wiley & Sons, Inc. J Polym. Sci Part B: Polym. Phys 39: 1855-1859, 2001.

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Identification of protein interaction interfaces is very important for understanding the molecular mechanisms underlying biological phenomena. Here, we present a novel method for predicting protein interaction interfaces from sequences by using PAM matrix (PIFPAM). Sequence alignments for interacting proteins were constructed and parsed into segments using sliding windows. By calculating distance matrix for each segment, the correlation coefficients between segments were estimated. The interaction interfaces were predicted by extracting highly correlated segment pairs from the correlation map. The predictions achieved an accuracy 0.41-0.71 for eight intraprotein interaction examples, and 0.07-0.60 for four interprotein interaction examples. Compared with three previously published methods, PIFPAM predicted more contacting site pairs for 11 out of the 12 example proteins, and predicted at least 34% more contacting site pairs for eight proteins of them. The factors affecting the predictions were also analyzed. Since PIFPAM uses only the alignments of the two interacting proteins as input, it is especially useful when no three-dimensional protein structure data are available.

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Based upon analyses of grain-size, rare earth element (REE) compositions, elemental occurrence phases of REE, and U-series isotopic dating, the sediment characteristics and material sources of the study area were examined for the recently formed deep-sea clays in the eastern Philippine Sea. The analytical results are summarized as follows. (1) Low accumulation rate, poor sorting and roundness, and high contents of grains coarser than fine silt indicate relatively low sediment input, with localized material source without long distance transport. (2) The REE Contents are relatively high. Shale-normalized patterns of REE indicate weak enrichment in heavy REE (HREE), Ce-passive anomaly, and Eu-positive anomaly. (3) Elemental occurrence phases of REE between the sediments with and without crust are similar. REE mainly concentrate in residual phase and then in ferromanganese oxide phase. The light REE (LREE) enrichment, Ce-positive anomaly, and Eu-positive anomaly occur in residual phase. Ferromanganese oxide phase shows the characteristics of relatively high HREE content and Ce-passive anomaly. (4) There are differences in each above mentioned aspect between the sediments with and without ferromanganese crust. (5) Synthesizing the above characteristics and source discriminant analysis, the study sediments are deduced to mainly result from the alteration of local and nearby volcanic materials. Continental materials transported by wind and/or river (ocean) flows also have minor contributions.