Lossy distribution source coding with side information

In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at distant locations. We study such a scenario in which multiple encoders transmit their correlated data at finite rates to a distant and common decoder. In particular, we derive inner and outer bounds on the rate region for the random field to be estimated with a given mean distortion.

Evolving Random Geometric Graph Models for Mobile Wireless Networks

We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. We derive properties similar to those above.

An Accurate Model for EESM and its Application to Analysis of CQI Feedback Schemes and Scheduling in LTE

The Effective Exponential SNR Mapping (EESM) is an indispensable tool for analyzing and simulating next generation orthogonal frequency division multiplexing (OFDM) based wireless systems. It converts the different gains of multiple subchannels, over which a codeword is transmitted, into a single effective flat-fading gain with the same codeword error rate. It facilitates link adaptation by helping each user to compute an accurate channel quality indicator (CQI), which is fed back to the base station to enable downlink rate adaptation and scheduling. However, the highly non-linear nature of EESM makes a performance analysis of adaptation and scheduling difficult; even the probability distribution of EESM is not known in closed-form. This paper shows that EESM can be accurately modeled as a lognormal random variable when the subchannel gains are Rayleigh distributed. The model is also valid when the subchannel gains are correlated in frequency or space. With some simplifying assumptions, the paper then develops a novel analysis of the performance of LTE's two CQI feedback schemes that use EESM to generate CQI. The comprehensive model and analysis quantify the joint effect of several critical components such as scheduler, multiple antenna mode, CQI feedback scheme, and EESM-based feedback averaging on the overall system throughput.

Assessment of estrus cyclicity in the Asian elephant (Elephas maximus) by measurement of fecal progesterone metabolite 5 alpha-P-3OH, using a non-invasive assay

Reproductive management of the Asian elephant (Elephas maximus) is important for its conservation. To monitor its estrous cyclicity, we earlier used an indirect ELISA to show that levels of fecal progesterone (P(4))-metabolite (allopregnanolone: 5 alpha-P-3OH) in semi-captive females sampled randomly positively correlated with serum P(4) levels [12]. In this longitudinal study (51 weeks), we measured levels of fecal 5 alpha-P-3OH and serum P(4) in seven semi-captive female elephants. Females exhibited three types of hormonal profiles. Four females showed cyclical patterns of fecal 5 alpha-P-3OH and serum P(4) typical of normal estrous cycles, two showed acyclic pattern while one showed high values indicative of a pregnant animal. Values for anestrous or follicular phases were <= 0.3 mu g g(-1), (5 alpha-P-3OH) and <= 0.3 ng mL(-1) (P(4)); for luteal phase 0.32-11.09 mu g g(-1) (5 alpha-P-3OH) and 0.32-1.48 ng mL(-1) (P(4)); for pregnancy 1.41-7.38 mu g g(-1) (5 alpha-P-3OH) and 0.39-1.6 ng mL(-1) (R(4)). A positive correlation (t = 8.8, p < 0.01, n = 321) between levels of fecal 5 alpha-P-3OH and serum P4 was observed. A random sample of 30 free-ranging female elephants showed fecal 5 alpha-P-3OH values of 0.06-23.4 mu g g(-1), indicating them to be in different stages of estrous cyclicity. This study is the first to assess the reproductive phases of female Asian elephants based on the correlative-patterns of both the fecal 5 alpha-P-3OH and serum P(4) values over multiple estrous cycles. This has a potential application in the reproductive management and conservation of Asian elephants. (C) 2011 Elsevier Inc. All rights reserved.

Full spin and spatial symmetry adapted technique for correlated electronic hamiltonians: Application to an icosahedral cluster

One of the long standing problems in quantum chemistry had been the inability to exploit full spatial and spin symmetry of an electronic Hamiltonian belonging to a non-Abelian point group. Here, we present a general technique which can utilize all the symmetries of an electronic (magnetic) Hamiltonian to obtain its full eigenvalue spectrum. This is a hybrid method based on Valence Bond basis and the basis of constant z-component of the total spin. This technique is applicable to systems with any point group symmetry and is easy to implement on a computer. We illustrate the power of the method by applying it to a model icosahedral half-filled electronic system. This model spans a huge Hilbert space (dimension 1,778,966) and in the largest non-Abelian point group. The C60 molecule has this symmetry and hence our calculation throw light on the higher energy excited states of the bucky ball. This method can also be utilized to study finite temperature properties of strongly correlated systems within an exact diagonalization approach. (C) 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012

A Refined Methodology for Durability-Based Service Life Estimation of Reinforced Concrete Structural Elements Considering Fuzzy and Random Uncertainties

A reliable method for service life estimation of the structural element is a prerequisite for service life design. A new methodology for durability-based service life estimation of reinforced concrete flexural elements with respect to chloride-induced corrosion of reinforcement is proposed. The methodology takes into consideration the fuzzy and random uncertainties associated with the variables involved in service life estimation by using a hybrid method combining the vertex method of fuzzy set theory with Monte Carlo simulation technique. It is also shown how to determine the bounds for characteristic value of failure probability from the resulting fuzzy set for failure probability with minimal computational effort. Using the methodology, the bounds for the characteristic value of failure probability for a reinforced concrete T-beam bridge girder has been determined. The service life of the structural element is determined by comparing the upper bound of characteristic value of failure probability with the target failure probability. The methodology will be useful for durability-based service life design and also for making decisions regarding in-service inspections.

Exact entanglement studies of strongly correlated systems: role of long-range interactions and symmetries of the system

We study the bipartite entanglement of strongly correlated systems using exact diagonalization techniques. In particular, we examine how the entanglement changes in the presence of long-range interactions by studying the Pariser-Parr-Pople model with long-range interactions. We compare the results for this model with those obtained for the Hubbard and Heisenberg models with short-range interactions. This study helps us to understand why the density matrix renormalization group (DMRG) technique is so successful even in the presence of long-range interactions. To better understand the behavior of long-range interactions and why the DMRG works well with it, we study the entanglement spectrum of the ground state and a few excited states of finite chains. We also investigate if the symmetry properties of a state vector have any significance in relation to its entanglement. Finally, we make an interesting observation on the entanglement profiles of different states (across the energy spectrum) in comparison with the corresponding profile of the density of states. We use isotropic chains and a molecule with non-Abelian symmetry for these numerical investigations.

Reactive biased target ion beam deposited W-DLC nanocomposite thin films - Microstructure and its mechanical properties

Tungsten incorporated diamond like carbon (W-DLC) nanocomposite thin films with variable fractions of tungsten were deposited by using reactive biased target ion beam deposition technique. The influence of tungsten incorporation on the microstructure, surface topography, mechanical and tribological properties of the DLC were studied using X-ray photoelectron spectroscopy (XPS), Raman spectroscopy. Atomic force microscope (AFM), transmission electron microscopy (TEM), nano-indentation and nano-scratch tests. The amount of W in films gets increases with increasing target bias voltage and most of the incorporated W reacts with carbon to form WC nanoclusters. Using TEM and FFT pattern, it was found that spherical shaped WC nanoclusters were uniformly dispersed in the DLC matrix and attains hexagonal (W2C) crystalline structure at higher W concentration. On the other hand, the incorporation of tungsten led to increase the formation of C-sp(2) hybridized bonding in DLC network and which is reflected in the hardness and elastic modulus of W-DLC films. Moreover, W-DLC films show very low friction coefficient and increased adhesion to the substrate than the DLC film, which could be closely related to its unique nanostructure of the W incorporated thin films. (C) 2011 Elsevier B.V. All rights reserved.

Percolation and connectivity in AB random geometric graphs

Given two independent Poisson point processes Phi((1)), Phi((2)) in R-d, the AB Poisson Boolean model is the graph with the points of Phi((1)) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centered at these points contains at least one point of Phi((2)). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d >= 2 and derive bounds fora critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and tau n in the unit cube. The AB random geometric graph is defined as above but with balls of radius r. We derive a weak law result for the largest nearest-neighbor distance and almost-sure asymptotic bounds for the connectivity threshold.

An invariant subspace-based approach to the random eigenvalue problem of systems with clustered spectrum

The repeated or closely spaced eigenvalues and corresponding eigenvectors of a matrix are usually very sensitive to a perturbation of the matrix, which makes capturing the behavior of these eigenpairs very difficult. Similar difficulty is encountered in solving the random eigenvalue problem when a matrix with random elements has a set of clustered eigenvalues in its mean. In addition, the methods to solve the random eigenvalue problem often differ in characterizing the problem, which leads to different interpretations of the solution. Thus, the solutions obtained from different methods become mathematically incomparable. These two issues, the difficulty of solving and the non-unique characterization, are addressed here. A different approach is used where instead of tracking a few individual eigenpairs, the corresponding invariant subspace is tracked. The spectral stochastic finite element method is used for analysis, where the polynomial chaos expansion is used to represent the random eigenvalues and eigenvectors. However, the main concept of tracking the invariant subspace remains mostly independent of any such representation. The approach is successfully implemented in response prediction of a system with repeated natural frequencies. It is found that tracking only an invariant subspace could be sufficient to build a modal-based reduced-order model of the system. Copyright (C) 2012 John Wiley & Sons, Ltd.

Random copolymers consisting of dithienylcyclopentadienone, thiophene and benzothiadiazole for bulk heterojunction solar cells

Novel random copolymers containing dithienylcyclopentadienone, thiophene and benzothiadiazole were synthesized and photovoltaic properties of these materials were evaluated. Thermal, structural, optical and electrochemical characterization of the synthesized copolymers was carried out. These thermally stable copolymers are solution processable unlike the homopolymer. The absorption spectra indicated that with the incorporation of alkyl chains in the thiophene moiety, the onset of absorption increases and hence band gap decreases (1.47 eV to 1.41 eV). Bulk heterojunction solar cells were fabricated with the blend of copolymer and phenyl-C61-butyric acid methyl ester (PCBM) as the active material and device parameters were extracted. The copolymer consists of alkyl thiophene exhibit higher open circuit voltage than the copolymer consisting of thiophene moiety. (c) 2012 Elsevier B.V. All rights reserved.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Nonuniform random geometric graphs with location-dependent radii

We propose a distribution-free approach to the study of random geometric graphs. The distribution of vertices follows a Poisson point process with intensity function n f(center dot), where n is an element of N, and f is a probability density function on R-d. A vertex located at x connects via directed edges to other vertices that are within a cut-off distance r(n)(x). We prove strong law results for (i) the critical cut-off function so that almost surely, the graph does not contain any node with out-degree zero for sufficiently large n and (ii) the maximum and minimum vertex degrees. We also provide a characterization of the cut-off function for which the number of nodes with out-degree zero converges in distribution to a Poisson random variable. We illustrate this result for a class of densities with compact support that have at most polynomial rates of decay to zero. Finally, we state a sufficient condition for an enhanced version of the above graph to be almost surely connected eventually.

Force Biased Molecular Dynamics Simulation Study of Effect of Dendrimer Generation on Interaction with DNA

We have studied the effect of dendrimer generation on the interaction between dsDNA and the PAMAM dendrimer using force biased simulation of dsDNA with three generations of dendrimer: G3, G4, and G5. Our results for the potential of mean force (PMF) and the dendrimer asphericity along the binding pathway, combined with visualization of the simulations, demonstrate that dendrimer generation has a pronounced impact on the interaction. The PMF increases linearly with increasing generation of the dendrimer. While, in agreement with previous results, we see an increase in the extent to which the dendrimer bends the dsDNA with increasing dendrimer generation, we also see that the deformation of the dendrimer is greater with smaller generation of the dendrimer. The larger dendrimer forces the dsDNA to conform to its structure, while the smaller dendrimer is forced to conform to the structure of the dsDNA. Monitoring the number of bound cations at different values of force bias distance shows the expected effect of ions being expelled when the dendrimer binds dsDNA.