Ultralow noise field-effect transistor from multilayer graphene

We present low-frequency electrical resistance fluctuations, or noise, in graphene-based field-effect devices with varying number of layers. In single-layer devices, the noise magnitude decreases with increasing carrier density, which behaved oppositely in the devices with two or larger number of layers accompanied by a suppression in noise magnitude by more than two orders in the latter case. This behavior can be explained from the influence of external electric field on graphene band structure, and provides a simple transport-based route to isolate single-layer graphene devices from those with multiple layers. ©2009 American Institute of Physics

Nondiffusive Quantum Transport in a Dynamically Disordered Medium

For a dynamically disordered continuum it is found that the exact quantum mechanical mean square displacement 〈x2(t)〉∼t3, for t→∞. A Gaussian white-noise spectrum is assumed for the random potential. The result differs qualitatively from the diffusive behavior well known for the one-band lattice Hamiltonian, and is understandable in terms of the momentum cutoff inherent in the lattice, simulating a "momentum bath."

Study of switching characteristics and thermal noise in ferroelectric crystals both in the pure and radiation damaged state

The phase transition in gamma-irradiated triglycine sulphate (TGS) has been investigated by using a method based on the measurement of thermal noise. The results of a study of the polarization switching characteristics of gamma irradiated TGS and sodium nitrite (NaNO2) have also been presented. The effect of irradiation on the phase transition and the switching processes has been discussed.

Quantization noise in binary holograms

The signal-to-noise (S/N) ratio in the reconstructed image from a binary hologram has been quantitatively related to the amplitude and phase quantization levels. The S/N ratio increases monotonically with increasing number of quantization levels. This observation is further supported by experimental results.

Multi-state-choice automata model for expedient learning in random environment

A new automata model Mr,k, with a conceptually significant innovation in the form of multi-state alternatives at each instance, is proposed in this study. Computer simulations of the Mr,k, model in the context of feature selection in an unsupervised environment has demonstrated the superiority of the model over similar models without this multi-state-choice innovation.

Optimal maintenance policy for equipment subject to random deterioration and random failure A modern control theory approach.

The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example

Generalized aerodynamic noise equation

An exact aerodynamic noise equation is formulated for Newtonian fluids. The cause−effect problem is discussed. Finally, the importance of external additions of mass, momentum, and energy is examined. Physics of Fluids is copyrighted by The American Institute of Physics.

Sequence distribution in Acrylonitrile-methylacrylate random copolymers by N.M.R spectroscopy

The sequence distribution studies on the acrylonitrile-methylmethacrylate copolymer of high methylmethacrylate (M) content (30%

Effect of creep deformations in mechanical systems under combined deterministic and random inputs

The effect of creep on the vibrations of a single degree of freedom system subjected to combined random and deterministic excitation has been studied in this paper. The deterministic part of the excitation is assumed to be a sinusoidal function while the random part of the excitation is considered as a narrow band process with a central frequency equal to the frequency of sinusoidal part of the excitation. Creep, an energy absorbing process, introduces an equivalent damping into the system. A measure of this damping and the statistical properties of the response of the mechanical system have been derived.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

The interference environment of radio Noise froh4 lightning

The paper furnishes a review and air ovendepr "f radio noise *om lightning as rr so~irce of interference to analogue and digital Corn?tunicatioiz. The parameters of fhe different fornls < f, noise necessary .for pssessigth e interfering effect of the rloise are described. 4railublr irfjrncroiun thrr tndevstor71zs, thunder-clouds, convecrion cells and lightning are er ieveadn d their liizitatimsp ointed oui. Thew fol101r.s a descripiicn of how the source, popugafiona nd receiver chaacteristidse termine the sfrticture qf a/rnosplro.ic noise as receiwd at a point of observation. The tratrrral unit for this noise i.s the mise burst rtrising from o w complete lightning.flas4. The pmuneters of the nrise birrst as a 11.hole and its structure ctetennine the inrqfflrrence enrirnniient. A hisforic reriel$. qf t2sophericii oke .studies sho1(5 that it i. wrreirt(v of importance oldy in thc ropicarl egions of' the wr ldf i>rs hichf hc neailable data are wry defective. New data are ficnrished. The contribution of atmospheric noise for backgrouzd interference even in remote places ,for r.adicj astronomy at VHF is firrnished. The imporlance of aimcspizeric nctise cceurring ;vporadiea@ in high values fur slzort inier.als at VHF and higher frequencies in the tropics is brought out.

Power Minimization for CDMA under Colored Noise

Rate-constrained power minimization (PMIN) over a code division multiple-access (CDMA) channel with correlated noise is studied. PMIN is. shown to be an instance of a separable convex optimization problem subject to linear ascending constraints. PMIN is further reduced to a dual problem of sum-rate maximization (RMAX). The results highlight the underlying unity between PMIN, RMAX, and a problem closely related to PMIN but with linear receiver constraints. Subsequently, conceptually simple sequence design algorithms are proposed to explicitly identify an assignment of sequences and powers that solve PMIN. The algorithms yield an upper bound of 2N - 1 on the number of distinct sequences where N is the processing gain. The sequences generated using the proposed algorithms are in general real-valued. If a rate-splitting and multi-dimensional CDMA approach is allowed, the upper bound reduces to N distinct sequences, in which case the sequences can form an orthogonal set and be binary +/- 1-valued.

A Proof of Convergence of the B-RED and P-RED Algorithms for Random Early Detection

In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

Random network behaviour of protein structures

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure. At a coarse-grained level, we show that the network conforms remarkably well to realizations of random graphs and displays associated percolation behavior. Thus, within the rigid framework of the protein backbone that restricts the structure space, the side-chain interactions exhibit an element of randomness, which account for the functional flexibility and diversity shown by proteins. However, at a finer level, the network exhibits deviations from these random graphs which, as we demonstrate for a few specific examples, reflect the intrinsic uniqueness in the structure and stability, and perhaps specificity in the functioning of biological proteins.