375 resultados para rate prediction


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Hot deformation behavior of a hypoeutectic Ti-6Al-4V-0.1B alloy in (alpha + beta) phase field is investigated in the present study with special reference to flow response, kinetics and microstructural evolution. For a comparison, the base alloy Ti-6Al-4V was also studied under identical conditions. Dynamic recovery of alpha phase occurs at low temperatures while softening due to globularization and/or dynamic recrystallization dominates at high temperatures irrespective of boron addition. Microstructural features for both the alloys display bending and kinking of alpha lamellae for near alpha test temperatures. Unlike Ti-6Al-4V, no sign of instability formation was observed in Ti-6Al-4V-0.1B for any deformation condition except for cavitation around TiB particles, due to deformation incompatibility and strain accumulation at the particle-matrix interface. The absence of macroscopic instabilities and early initiation of softening mechanisms as a result of boron addition has been attributed to microstructural features (e.g. refined prior beta grain and alpha colony size, absence of grain boundary alpha layer, presence of TiB particles at prior beta boundaries, etc.) of the respective alloys prior to deformation. (C) 2012 Elsevier B.V. All rights reserved.

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Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

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In an effort to study the role of strain rate response on the tribological behavior of metals, room temperature experiments were conducted by sliding commercially pure titanium and a-iron pins against an H-11 die steel flats of various surface textures. The steel flat surface textures were specifically prepared to allow for imposing varying amounts of strain rates at the contacting interface during sliding motion. In the experiments, it was observed that titanium (a harder material than iron) formed a transfer layer on H-11 steel surface textures that produced higher strain rates. In contrast, the titanium pins abraded the steel surfaces that produced lower strain rates. The iron pins were found to abrade the H-11 steel surface regardless of the surface texture characteristics. This unique tribological behavior of titanium is likely due to the fact that titanium undergoes adiabatic shear banding at high strain rates, which creates pathways for lower resistance shear planes. These shear planes lead to fracture and transfer layer formation on the surface of the steel flat, which ultimately promotes a higher strain rate of deformation at the asperity level. Iron does not undergo adiabatic shear banding and thus more naturally abrades the surfaces. Overall, the results clear indicated that a materials strain rate response can be an important factor in controlling the tribological behavior of a plastically deforming material at the asperity level. DOI: 10.1115/1.4007675]

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Genetic Algorithm for Rule-set Prediction (GARP) and Support Vector Machine (SVM) with free and open source software (FOSS) - Open Modeller were used to model the probable landslide occurrence points. Environmental layers such as aspect, digital elevation, flow accumulation, flow direction, slope, land cover, compound topographic index and precipitation have been used in modeling. Simulated output of these techniques is validated with the actual landslide occurrence points, which showed 92% (GARP) and 96% (SVM) accuracy considering precipitation in the wettest month and 91% and 94% accuracy considering precipitation in the wettest quarter of the year.

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We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

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Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

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We consider the design of a linear equalizer with a finite number of coefficients in the context of a classical linear intersymbol-interference channel with additive Gaussian noise for channel estimation. Previous literature has shown that Minimum Bit Error Rate(MBER) based detection has outperformed Minimum Mean Squared Error (MMSE) based detection. We pose the channel estimation problem as a detection problem and propose a novel algorithm to estimate the channel based on the MBER framework for BPSK signals. It is shown that the proposed algorithm reduces BER compared to an MMSE based channel estimation when used in MMSE or MBER detection.

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In this paper, we consider a slow-fading nt ×nr multiple-input multiple-output (MIMO) channel subjected to block fading. Reliability (in terms of achieved diversity order) and rate (in number of symbols transmitted per channel use) are of interest in such channels. We propose a new precoding scheme which achieves both full diversity (nt ×nrth order diversity) as well as full rate (nt symbols per channel use) using partial channel state information at the transmitter (CSIT). The proposed scheme achieves full diversity and improved coding gain through an optimization over the choice of constellation sets. The optimization maximizes dmin2 for our precoding scheme subject to an energy constraint. The scheme requires feedback of nt - 1 angle parameter values, compared to 2ntnr real coefficients in case of full CSIT. Further, for the case of nt × 1 system, we prove that the capacity achieved by the proposed scheme is same as that achieved with full CSIT. Error rate performance results for nt = 3,4,8 show that the proposed scheme performs better than other precoding schemes in the literature; the better performance is due to the choice of the signal sets and the feedback angles in the proposed scheme.

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Size independent fracture energy and size effect on fracture energy are the key concerns for characterization of concrete fracture. Although there have been inconsistencies in results, a consensual fact is that the fracture energy from a large specimen is size independent. The fracture energy is proportional to the size of the fracture process zone (FPZ). FPZ size increases with size of the specimen, but the rate of increase of FPZ size decreases with increase in specimen size 1] implying that rate of increase of fracture energy decreases with increase in specimen size, more appropriately with increase in un-cracked ligament length. The ratio of fracture energy to the un-cracked ligament length almost becomes a constant at larger un-cracked ligament lengths. In the present study an attempt is made to obtain size independent fracture energy from fracture energy release rate. (C) 2012 Elsevier Ltd. All rights reserved.

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In this study, the influence of tool rotation speed and feed rate on the forming limit of friction stir welded Al 6061-T651 sheets has been investigated. The forming limit curve was evaluated by limit dome height test performed on all the friction stir welded sheets. The welding trials were conducted at a tool rotation speed of 1300 and 1400 r/min and feed rate of 90 and 100 mm/min. A third trial of welding was performed at a rotational speed of 1500 r/min and feed rate 120 mm/min. It is found that with increase in the tool rotation speed, from 1300 to 1400 r/min, for a constant feed rate, the forming limit of friction stir welded blank has improved and with increase in feed rate, from 90 to 100 mm/min, for a constant tool rotation speed, it has decreased. The forming limit of friction stir welded sheets is better than unwelded sheets. The thickness gradient after forming is severe in the cases of friction stir welded blanks made at higher feed rate and lower rotation speed. The strain hardening exponent of weld (n) increases with increase in tool rotation speed and it decreases with increase in feed rate. It has been demonstrated that the change in the forming limit of friction stir welded sheets with respect to welding parameters is due to the thickness distribution severity and strain hardening exponent of the weld region during forming. There is not much variation in the dome height among the friction stir welded sheets tested. When compared with unwelded sheets, dome height of friction stir welded sheets is higher in near-plane-strain condition, but it is lesser in stretching strain paths.

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The effect of strain rate, (epsilon) over dot, and temperature, T, on the tension-compression asymmetry (TCA) in a dilute and wrought Mg alloy, AM30, over a temperature range that covers both twin accommodated deformation (below 250 degrees C in compression) as well as dislocation-mediated plasticity (above 250 degrees C) has been investigated. For this purpose, uniaxial tension and compression tests were conducted at T ranging from 25 to 400 degrees C with (epsilon) over dot varying between 10(-2) and 10 s(-1). In most of the cases, the stress-strain responses in tension and compression are distinctly different; with compression responses `concaving upward,' due to {10 (1) over bar2} tensile twinning at lower plastic strains followed by slip and strain hardening at higher levels of deformation, for T below 250 degrees C. This results in significant levels of TCA at T < 250 degrees C, reducing substantially at high temperatures. At T=150 and 250 degrees C, high (epsilon) over dot leads to high TCA, in particular at T=250 degrees C and (epsilon) over dot=10 s(-1), suggesting that twin-mediated plastic deformation takes precedence at high rates of loading even at sufficiently high T. TCA becomes negligible at T=350 degrees C; however at T=400 degrees C, as (epsilon) over dot increases TCA gets higher. Microscopy of the deformed samples, carried out by using electron back-scattered diffraction (EBSD), suggests that at T > 250 degrees C dynamic recrystallization begins between accompanied by reduction in the twinned fraction that contributes to the decrease of the TCA.

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In animal populations, the constraints of energy and time can cause intraspecific variation in foraging behaviour. The proximate developmental mediators of such variation are often the mechanisms underlying perception and associative learning. Here, experience-dependent changes in foraging behaviour and their consequences were investigated in an urban population of free-ranging dogs, Canis familiaris by continually challenging them with the task of food extraction from specially crafted packets. Typically, males and pregnant/lactating (PL) females extracted food using the sophisticated `gap widening' technique, whereas non-pregnant/non-lactating (NPNL) females, the relatively underdeveloped `rip opening' technique. In contrast to most males and PL females (and a few NPNL females) that repeatedly used the gap widening technique and improved their performance in food extraction with experience, most NPNL females (and a few males and PL females) non-preferentially used the two extraction techniques and did not improve over successive trials. Furthermore, the ability of dogs to sophisticatedly extract food was positively related to their ability to improve their performance with experience. Collectively, these findings demonstrate that factors such as sex and physiological state can cause differences among individuals in the likelihood of learning new information and hence, in the rate of resource acquisition and monopolization.

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This brief discusses the convergence analysis of proportional navigation (PN) guidance law in the presence of delayed line-of-sight (LOS) rate information. The delay in the LOS rate is introduced by the missile guidance system that uses a low cost sensor to obtain LOS rate information by image processing techniques. A Lyapunov-like function is used to analyze the convergence of the delay differential equation (DDE) governing the evolution of the LOS rate. The time-to-go until which decreasing behaviour of the Lyapunov-like function can be guaranteed is obtained. Conditions on the delay for finite time convergence of the LOS rate are presented for the linearized engagement equation. It is observed that in the presence of line-of-sight rate delay, increasing the effective navigation constant of the PN guidance law deteriorates its performance. Numerical simulations are presented to validate the results.

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The paper presents a new controller inspired by the human experience based, voluntary body action control (dubbed motor control) learning mechanism. The controller is called Experience Mapping based Prediction Controller (EMPC). EMPC is designed with auto-learning features without the need for the plant model. The core of the controller is formed around the motor action prediction-control mechanism of humans based on past experiential learning with the ability to adapt to environmental changes intelligently. EMPC is utilized for high precision position control of DC motors. The simulation results are presented to show that accurate position control is achieved using EMPC for step and dynamic demands. The performance of EMPC is compared with conventional PD controller and MRAC based position controller under different system conditions. Position Control using EMPC is practically implemented and the results are presented.