905 resultados para two-to-one trapdoor functions


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In many cases, a mobile user has the option of connecting to one of several IEEE 802.11 access points (APs),each using an independent channel. User throughput in each AP is determined by the number of other users as well as the frame size and physical rate being used. We consider the scenario where users could multihome, i.e., split their traffic amongst all the available APs, based on the throughput they obtain and the price charged. Thus, they are involved in a non-cooperative game with each other. We convert the problem into a fluid model and show that under a pricing scheme, which we call the cost price mechanism, the total system throughput is maximized,i.e., the system suffers no loss of efficiency due to selfish dynamics. We also study the case where the Internet Service Provider (ISP) could charge prices greater than that of the cost price mechanism. We show that even in this case multihoming outperforms unihoming, both in terms of throughput as well as profit to the ISP.

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We report a Raman study of single crystal pyrochlore Er(2)Ti(2)O(7) as a function of temperature from 12 to 300 K. In addition to the phonons, various photoluminescence (PL) lines of Er(3+) in the visible range are also observed. Our Raman data show an anomalous red-shift of two phonons (one at similar to 200 cm(-1) and another at similar to 520 cm(-1)) upon cooling from room temperature which is attributed to phonon-phonon anharmonic interactions. However, the phonons at similar to 310, 330, and 690 cm(-1) initially show a blue-shift upon cooling from room temperature down to about 130 K, followed by a red-shift, indicating a structural deformation at similar to 130 K. The intensities of the PL bands associated with the transitions between the various levels of the ground state manifold ((4)I(15/2)) and the (2)H(11/2) as well as (4)S(3/2) excited state manifolds of Er(3+) show a change at similar to 130 K. Moreover, the temperature dependence of the peak position of the two PL bands shows a change in their slope (d(omega)/d(T)) at similar to 130 K, thus further strengthening the proposal of a structural deformation. The temperature dependence of the peak positions of the PL bands has been analyzed using the theory of optical dephasing in crystals.

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A second order transfer function with two poles and two zeros exhibits a step response characterized by a sudden rise to the steady state value, followed by oscillations around this steady state. With proper choice of the coefficients, it is possible to obtain transfer functions suitable for pulse transmission purposes.

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This study presents the future seismic hazard map of Coimbatore city, India, by considering rupture phenomenon. Seismotectonic map for Coimbatore has been generated using past earthquakes and seismic sources within 300 km radius around the city. The region experienced a largest earthquake of moment magnitude 6.3 in 1900. Available earthquakes are divided into two categories: one includes events having moment magnitude of 5.0 and above, i.e., damaging earthquakes in the region and the other includes the remaining, i.e., minor earthquakes. Subsurface rupture character of the region has been established by considering the damaging earthquakes and total length of seismic source. Magnitudes of each source are estimated by assuming the subsurface rupture length in terms of percentage of total length of sources and matched with reported earthquake. Estimated magnitudes match well with the reported earthquakes for a RLD of 5.2% of the total length of source. Zone of influence circles is also marked in the seismotectonic map by considering subsurface rupture length of fault associated with these earthquakes. As earthquakes relive strain energy that builds up on faults, it is assumed that all the earthquakes close to damaging earthquake have released the entire strain energy and it would take some time for the rebuilding of strain energy to cause a similar earthquake in the same location/fault. Area free from influence circles has potential for future earthquake, if there is seismogenic source and minor earthquake in the last 20 years. Based on this rupture phenomenon, eight probable locations have been identified and these locations might have the potential for the future earthquakes. Characteristic earthquake moment magnitude (M-w) of 6.4 is estimated for the seismic study area considering seismic sources close to probable zones and 15% increased regional rupture character. The city is divided into several grid points at spacing of 0.01 degrees and the peak ground acceleration (PGA) due to each probable earthquake is calculated at every grid point in city by using the regional attenuation model. The maximum of all these eight PGAs is taken for each grid point and the final PGA map is arrived. This map is compared to the PGA map developed based on the conventional deterministic seismic hazard analysis (DSHA) approach. The probable future rupture earthquakes gave less PGA than that of DSHA approach. The occurrence of any earthquake may be expected in near future in these eight zones, as these eight places have been experiencing minor earthquakes and are located in well-defined seismogenic sources.

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Photoemission spectroscopy offers the unique possibility of mapping out the electronic structure of the occupied electron states. However, the extreme surface sensitivity of this technique ensures that only the surface and the near-surface regions of any sample are probed. An important question arises in this context—Is the electronic structure of the surface region the same as that of the bulk? We address this issue using two different series of vanadium oxides, Ca1−xSrxVO3 and La1−xCaxVO3. Our results clearly establish that the electronic structure of the surface region is drastically different from that of the bulk in both these cases. We provide a method to separate the two contributions: one arising from the near-surface region and the other representative of the bulk. This separation allows us to deduce some very unusual behaviors of the electronic structures in these systems.

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Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

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The paper presents a rational approach to model the behavior of bonded soils within the frame work of hardening plasticity. The approach is based on the premise that the resistance of bonded materials is a superposition of the two components of cement bond strength and soil frictional strength and that the deformation of the soil is associated with the frictional component of stresses just as in the case of a remoulded soil, the bonds offering additional resistance at any given strain level. This concept is similar to two stiffnesses acting in parallel for the same strain response. The proposed model considers the constitutive laws separately for the two components (bond and frictional) and adds the two to get the overall response. The unbonded soil component is described by the well known 'modified Cam clay' model. The response of the bond component is also described by a strain softening elasto-plastic model, considering the behavior to be elastic up to the yield surface and elasto-plastic beyond yield surface. To illustrate the capability of the proposed, model some laboratory test results of both compression and-extension shear tests are predicted. Despite the model being simple, several typical features of the behavior of bonded materials are well reproduced. The model parameters are well defined and easily determinable.

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In recent years a number of white dwarfs have been observed with very high surface magnetic fields. We can expect that the magnetic field in the core of these stars would be much higher (similar to 10(14) G). In this paper, we analytically study the effect of high magnetic field on relativistic cold electron, and hence its effect on the stability and the mass-radius relation of a magnetic white dwarf. In strong magnetic fields, the equation of state of the Fermi gas is modified and Landau quantization comes into play. For relatively very high magnetic fields (with respect to the average energy density of matter) the number of Landau levels is restricted to one or two. We analyze the equation of states for magnetized electron degenerate gas analytically and attempt to understand the conditions in which transitions from the zeroth Landau level to first Landau level occurs. We also find the effect of the strong magnetic field on the star collapsing to a white dwarf, and the mass-radius relation of the resulting star. We obtain an interesting theoretical result that it is possible to have white dwarfs with mass more than the mass set by Chandrasekhar limit.

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Study of laminar boundary layer in mixed convection from vertical plates is carried out. The surface temperature along the vertical plate is assumed to vary arbitrarily with vertical distance. Perturbation technique is used to solve the governing boundary layer equations. The differentials of the wall temperature are used as perturbation elements, which are functions of vertical distance, to obtain universal functions. The universal functions are valid for any type of vertical wall temperature variation. Heat transfer rates and fluid velocity inside the boundary layer can be expressed and calculated using these universal functions. Heat transfer rates are obtained for the special cases of power-law variation of the wall temperature. The effect of the governing parameter (Gr(y)/Re-y(2)) and the power index of the power-law wall temperature variation on heat transfer rates is studied. For the purpose of validation, the mixed convection results obtained by the present technique pertaining to the special cases of isothermal vertical wall are compared with those obtained by similarity analysis reported in literature, and the agreement is found to be good. (C) 2012 Elsevier Ltd. All rights reserved.

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Purpose: Waardenburg syndrome (WS) is characterized by sensorineural hearing loss and pigmentation defects of the eye, skin, and hair. It is caused by mutations in one of the following genes: PAX3 (paired box 3), MITF (microphthalmia-associated transcription factor), EDNRB (endothelin receptor type B), EDN3 (endothelin 3), SNAI2 (snail homolog 2, Drosophila) and SOX10 (SRY-box containing gene 10). Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder caused by mutations in the DMD gene. The purpose of this study was to identify the genetic causes of WS and DMD in an Indian family with two patients: one affected with WS and DMD, and another one affected with only WS. Methods: Blood samples were collected from individuals for genomic DNA isolation. To determine the linkage of this family to the eight known WS loci, microsatellite markers were selected from the candidate regions and used to genotype the family. Exon-specific intronic primers for EDN3 were used to amplify and sequence DNA samples from affected individuals to detect mutations. A mutation in DMD was identified by multiplex PCR and multiplex ligation-dependent probe amplification method using exon-specific probes. Results: Pedigree analysis suggested segregation of WS as an autosomal recessive trait in the family. Haplotype analysis suggested linkage of the family to the WS4B (EDN3) locus. DNA sequencing identified a novel missense mutation p.T98M in EDN3. A deletion mutation was identified in DMD. Conclusions: This study reports a novel missense mutation in EDN3 and a deletion mutation in DMD in the same Indian family. The present study will be helpful in genetic diagnosis of this family and increases the mutation spectrum of EDN3.

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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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The H-1 NMR spectroscopic discrimination of enantiomers in the solution state and the measurement of enantiomeric composition is most often hindered due to either very small chemical shift differences between the discriminated peaks or severe overlap of transitions from other chemically non-equivalent protons. In addition the use of chiral auxiliaries such as, crown ether and chiral lanthanide shift reagent may often cause enormous line broadening or give little degree of discrimination beyond the crown ether substrate ratio, hampering the discrimination. In circumventing such problems we are proposing the utilization of the difference in the additive values of all the chemical shifts of a scalar coupled spin system. The excitation and detection of appropriate highest quantum coherence yields the measurable difference in the frequencies between two transitions, one pertaining to each enantiomer in the maximum quantum dimension permitting their discrimination and the F-2 cross section at each of these frequencies yields an enantiopure spectrum. The advantage of the utility of the proposed method is demonstrated on several chiral compounds where the conventional one dimensional H-1 NMR spectra fail to differentiate the enantiomers.

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There have been several studies on the performance of TCP controlled transfers over an infrastructure IEEE 802.11 WLAN, assuming perfect channel conditions. In this paper, we develop an analytical model for the throughput of TCP controlled file transfers over the IEEE 802.11 DCF with different packet error probabilities for the stations, accounting for the effect of packet drops on the TCP window. Our analysis proceeds by combining two models: one is an extension of the usual TCP-over-DCF model for an infrastructure WLAN, where the throughput of a station depends on the probability that the head-of-the-line packet at the Access Point belongs to that station; the second is a model for the TCP window process for connections with different drop probabilities. Iterative calculations between these models yields the head-of-the-line probabilities, and then, performance measures such as the throughputs and packet failure probabilities can be derived. We find that, due to MAC layer retransmissions, packet losses are rare even with high channel error probabilities and the stations obtain fair throughputs even when some of them have packet error probabilities as high as 0.1 or 0.2. For some restricted settings we are also able to model tail-drop loss at the AP. Although involving many approximations, the model captures the system behavior quite accurately, as compared with simulations.

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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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This work is a continuation of our efforts to quantify the irregular scalar stress signals from the Ananthakrishna model for the Portevin-Le Chatelier instability observed under constant strain rate deformation conditions. Stress related to the spatial average of the dislocation activity is a dynamical variable that also determines the time evolution of dislocation densities. We carry out detailed investigations on the nature of spatiotemporal patterns of the model realized in the form of different types of dislocation bands seen in the entire instability domain and establish their connection to the nature of stress serrations. We then characterize the spatiotemporal dynamics of the model equations by computing the Lyapunov dimension as a function of the drive parameter. The latter scales with the system size only for low strain rates, where isolated dislocation bands are seen, and at high strain rates, where fully propagating bands are seen. At intermediate applied strain rates corresponding to the partially propagating bands, the Lyapunov dimension exhibits two distinct slopes, one for small system sizes and another for large. This feature is rationalized by demonstrating that the spatiotemporal patterns for small system sizes are altered from the partially propagating band types to isolated burst type. This in turn allows us to reconfirm that low-dimensional chaos is projected from the stress signals as long as there is a one-to-one correspondence between the bursts of dislocation bands and the stress drops. We then show that the stress signals in the regime of partially to fully propagative bands have features of extensive chaos by calculating the correlation dimension density. We also show that the correlation dimension density also depends on the system size. A number of issues related to the system size dependence of the Lyapunov dimension density and the correlation dimension density are discussed.