Screened Optical-Phonon Pairing Mechanism in Electron Doped Cuprates

An effective two-dimensional dynamic interaction is developed which incorporates screening of electrons by plasmons and by optical phonons to discuss the nature of the pairing mechanism leading to superconductivity in layered electron doped cuprates. The system is treated as an ionic solid containing layers of electrons as carriers and a model dielectric function is set up which fulfils the appropriate sum rules on the electronic and ionic polarizabilities. Estimate of the Coulomb pseudo-potential (*=0.24), describing the screening effects on superconductivity is due to reduced electron density and large value of the optical dielectric constant as well the effective mass of electrons. The electron–phonon coupling constant () is evaluated as 1.5 which infers strong strength of coupling. Following strong coupling theory, the superconducting transition temperature of optimally doped Nd–Ce–CuO is estimated as 30 K and the energy gap ratio is larger than the BCS value. The isotope exponent, coherence length and magnetic penetration depth are also estimated. The implications of the model and its analysis are discussed.     

Nonlinear predictive control for a NNARX hydro plant model

A neural network (NN)-based nonlinear predictive control (NPC) is described for control of turbine power with variation in gate position. The studied plant includes the tunnel, surge tank and penstock effect dynamics. Multilayer perceptron neural network is chosen to represent a neural network nonlinear autoregressive with exogenous signal model of hydro power plant. With the said NN model configuration, quasi-Newton and Levenberg–Marquardt iterative optimization algorithms are applied in order to determine optimal predictive control parameters. The controlled response is simulated on different amplitude step function and trapezoidal shape reference signal. The study also discusses comparison with an approximate predictive control approach, being linearized around operating points. It is shown that NPC strategy gives impressive results in comparison to the approximated one.     

Evaluation of the performance of backpropagation and radial basis function neural networks in predicting the drill flank wear

This study compares the performance of backpropagation neural network (BPNN) and radial basis function network (RBFN) in predicting the flank wear of high speed steel drill bits for drilling holes on mild steel and copper work pieces. The validation of the methodology is carried out following a series of experiments performed over a wide range of cutting conditions in which the effect of various process parameters, such as drill diameter, feed-rate, spindle speed, etc. on drill wear has been considered. Subsequently, the data, divided suitably into training and testing samples, have been used to effectively train both the backpropagation and radial basis function neural networks, and the individual performance of the two networks is then analyzed. It is observed that the performance of the RBFN fails to match that of the BPNN when the network complexity and the amount of data available are the constraining factors. However, when a simpler training procedure and reduced computational times are required, then RBFN is the preferred choice.     

A Highly Scalable GALS Crossbar Using Token Ring Arbitration

With increases in die size and clock frequency, driving signals across dies is becoming increasingly more difficult. To reduce clock skew and power, the general trend is to use multiple clock domains on a single die, making both synchronous and asynchronous interclock domain communication possible. The 2005 International Technology Roadmap for Semiconductors states that asynchronous global signaling is required to handle multiple clock domains. According to the ITRS, the globally asynchronous, locally synchronous (GALS) methodology should address this problem. This methodology enables the use of a clocked design for smaller-scale functional units, and this has been the standard approach in industry. The GALS methodology also makes it possible to connect synchronous functional units using robust asynchronous interconnects. The efficient design of an asynchronous crossbar is one of the most promising implementations of the GALS methodology. In this article, we present a low-latency crossbar that uses a distributed arbitration mechanism in the form of token rings. We further improve the latency of this implementation by implementing asynchronous-to-synchronous and synchronous-to-asynchronous interface logic using bidirectional signals. These signals serve as requests and acknowledges, and they exhibit a very fast GasP-like implementation - although, unlike GasP, this implementation is not self-resetting.     

Stemming via Distribution-Based Word Segregation for Classification and Retrieval

A novel corpus-based method for stemmer refinement, which can provide improvement in both classification and retrieval, is described. The method models the given words as generated from a multinomial distribution over the topics available in the corpus and includes a procedurelike sequential hypothesis testing that enables grouping together distributionally similar words. The system can refine any stemmer, and its strength can be controlled with parameters that reflect the amount of tolerance to be allowed in computing the similarity between the distributions of two words. Although obtaining the morphological roots of the given words is not the primary objective, the algorithm automatically does that to some extent. Despite a huge reduction in dictionary size, classification accuracies are seen to improve significantly when the proposed system is applied on some existing stemmers for classifying 20 Newsgroups and WebKB data. The refinements obtained are also suitable for cross-corpus stemming. Regarding retrieval, its superiority is extensively demonstrated with respect to four existing methods     

Contrasting REE Signatures on Manganese Ores of Iron Ore Group in North Orissa, India

The distribution pattern of Rare Earth Elements （REE） in three categories of manganese ores viz. stratiform, stratabound-replacement, and detrital of Precambrian Iron Ore Group from north Orissa, India was reported. These categories of Mn-ore differed in their major and trace chemistry and exhibited contrasting REE signature. The stratiform ores were relatively enriched in ∑REE content （697 μg·g^-1） and their normalized pattern showed both positive Ce and Eu anomalies, whereas the stratabound-replacement types were comparatively depleted in ∑REE content （211 μg·g^-1） and showed negative Ce and flat Eu signatures. The detrital categories showed mixed REE pattern. The data plotted in different discrimination diagrams revealed a mixed volcaniclastic and chemogenic source of material for stratiform categories, and LREE （Light Rare Earth Elements） and HREE （Heavy Rare Earth Elements） are contributed by such sources, respectively. In contrast, the stratabound ore bodies were developed during the remobilization of stratiform ores, and associated Mncontaining rocks under supergene condition followed by the redeposition of circulating mineralized colloidal solutions in structurally favorable zones. During this process, some of the constituents were found only in very low concentration within stratabound ores, and this is attributed to their poor leachability/mobility. The detrital ores did not exhibit any significant characteristic in respect of REE as their development was via a complex combination of processes involving weathering, fragmentation, recementation, and burial under soil cover.     

Analysis of structural modifications in γ-irradiated PbO–B2O3–SiO2 glasses by FTIR spectroscopy

The effect of γ-irradiation on the structure of lead borosilicate glasses of varying composition has been probed by FTIR spectroscopy, before and immediately after γ-irradiation. The glasses were irradiated at Calliope ⁶⁰Co plant (RC ENEA Casaccia, Rome), and the spectra were recorded after absorbed doses of 50 Gy, 500 Gy, and 4 kGy. The structural analysis have been made considering both the effect of composition and of irradiation. The experimental results clearly indicate that after irradiation a significant change in structure of borosilicate glass network is observed.     

Role of Direct Reduced Iron Fines in Nitrogen Removal from Electric Arc Furnace Steel

Electric arc furnace steel contains about 70‐120 ppm nitrogen. There is no suitable method for nitrogen removal from electric arc furnace steel up to the level desired for good quality bars and flat rolled products (30 ppm max). The existing process based on vacuum degassing can remove only up to 20% of nitrogen in steel. In the present study DRI fines have been injected into a steel bath which can drift out nitrogen in steel through production of fine CO bubbles in‐situ on reaction with residual FeO in DRI fines and C in bath. For high and medium carbon steel, nitrogen got reduced to 30 ppm and 60 ppm respectively where initial nitrogen was 150 – 200 ppm in steel. Nitrogen removal also depends upon bath depth and addition level of DRI.     

Diagnostic Curve Methods for Consolidation Coefficient

Two new diagnostic curve methods, which do not require the implicit or explicit determination of initial or final dial gauge readings for primary settlement, are proposed for the identification of the consolidation coefficient. Besides the estimate of the consolidation coefficient, these methods also yield an estimate of the range of primary settlement. In these methods, the diagnostically plotted points are matched to the diagnostic curves with a parallel shift of axes to yield the estimates of the consolidation coefficient and range of primary settlement. The new methods do not require dial gauge readings up to 100% of primary consolidation and can also be used even when very scarce data are available. Using the proposed methods, a nonideal condition can also be identified.