Performance analysis of fixed gain amplify-and-forward relaying with time-efficient cascaded channel estimation

In a cooperative system with an amplify-and-forward relay, the cascaded channel training protocol enables the destination to estimate the source-destination channel gain and the product of the source-relay (SR) and relay-destination (RD) channel gains using only two pilot transmissions from the source. Notably, the destination does not require a separate estimate of the SR channel. We develop a new expression for the symbol error probability (SEP) of AF relaying when imperfect channel state information (CSI) is acquired using the above training protocol. A tight SEP upper bound is also derived; it shows that full diversity is achieved, albeit at a high signal-to-noise ratio (SNR). Our analysis uses fewer simplifying assumptions, and leads to expressions that are accurate even at low SNRs and are different from those in the literature. For instance, it does not approximate the estimate of the product of SR and RD channel gains by the product of the estimates of the SR and RD channel gains. We show that cascaded channel estimation often outperforms a channel estimation protocol that incurs a greater training overhead by forwarding a quantized estimate of the SR channel gain to the destination. The extent of pilot power boosting, if allowed, that is required to improve performance is also quantified.

Energy-efficient training for antenna selection in time-varying channels

Training for receive antenna selection (AS) differs from that for conventional multiple antenna systems because of the limited hardware usage inherent in AS. We analyze and optimize the performance of a novel energy-efficient training method tailored for receive AS. In it, the transmitter sends not only pilots that enable the selection process, but also an extra pilot that leads to accurate channel estimates for the selected antenna that actually receives data. For time-varying channels, we propose a novel antenna selection rule and prove that it minimizes the symbol error probability (SEP). We also derive closed-form expressions for the SEP of MPSK, and show that the considered training method is significantly more energy-efficient than the conventional AS training method.

Efficient post-processing techniques for speech enhancement

We address the problem of speech enhancement in real-world noisy scenarios. We propose to solve the problem in two stages, the first comprising a generalized spectral subtraction technique, followed by a sequence of perceptually-motivated post-processing algorithms. The role of the post-processing algorithms is to compensate for the effects of noise as well as to suppress any artifacts created by the first-stage processing. The key post-processing mechanisms are aimed at suppressing musical noise and to enhance the formant structure of voiced speech as well as to denoise the linear-prediction residual. The parameter values in the techniques are fixed optimally by experimentally evaluating the enhancement performance as a function of the parameters. We used the Carnegie-Mellon university Arctic database for our experiments. We considered three real-world noise types: fan noise, car noise, and motorbike noise. The enhancement performance was evaluated by conducting listening experiments on 12 subjects. The listeners reported a clear improvement (MOS improvement of 0.5 on an average) over the noisy signal in the perceived quality (increase in the mean-opinion score (MOS)) for positive signal-to-noise-ratios (SNRs). For negative SNRs, however, the improvement was found to be marginal.

Efficient energy transport in photosynthesis: roles of coherence and entanglement

Recently it has been discovered---contrary to expectations of physicists as well as biologists---that the energy transport during photosynthesis, from the chlorophyll pigment that captures the photon to the reaction centre where glucose is synthesised from carbon dioxide and water, is highly coherent even at ambient temperature and in the cellular environment. This process and the key molecular ingredients that it depends on are described. By looking at the process from the computer science view-point, we can study what has been optimised and how. A spatial search algorithmic model based on robust features of wave dynamics is presented.

Computationally efficient yet accurate analysis of composite plate

This article does not have an abstract.

Supersymmetry of classical solutions in Chern-Simons higher spin supergravity

We construct and study classical solutions in Chern-Simons supergravity based on the superalgebra sl(N vertical bar N = 1). The algebra for the N = 3 case is written down explicitly using the fact that it arises as the global part of the super conformal W-3 superalgebra. For this case we construct new classical solutions and study their supersymmetry. Using the algebra we write down the Killing spinor equations and explicitly construct the Killing spinor for conical defects and black holes in this theory. We show that for the general sl(N|N - 1) theory the condition for the periodicity of the Killing spinor can be written in terms of the products of the odd roots of the super algebra and the eigenvalues of the holonomy matrix of the background. Thus the supersymmetry of a given background can be stated in terms of gauge invariant and well defined physical observables of the Chern-Simons theory. We then show that for N >= 4, the sl(N|N - 1) theory admits smooth supersymmetric conical defects.

Organophotocatalysis in nanostructured soft gel materials as tunable reaction vessels: comparison with homogeneous and micellar solutions

Riboflavin tetraacetate-catalyzed aerobic photooxidation of 1-(4-methoxyphenyl)ethanol was investigated as a model reaction under blue visible light in different soft gel materials, aiming to establish their potential as reaction vessels for photochemical transformations. Three strategies involving different degrees of organization of the catalyst within the gel network were explored, and the results compared to those obtained in homogeneous and micellar solutions. In general, physical entrapment of both the catalyst and the substrate under optimized concentrations into several hydrogel matrices (including low-molecular-weight and biopolymer-based gels) allowed the photooxidation with conversions between 55 and 100% within 120 min (TOF similar to 0.045-0.08 min(-1); k(obs) similar to 0.011-0.028 min(-1)), albeit with first-order rates ca. 1-3-fold lower than in solution under comparable non-stirred conditions. Remarkably, the organogel made of a cyclohexane-based bisamide gelator in CH3CN not only prevented the photodegradation of the catalyst but also afforded full conversion in less than 60 min (TOF similar to 0.167 min(-1); k(obs) similar to 0.073 min(-1)) without the need of additional proton transfer mediators (e. g., thiourea) as it occurs in CH3CN solutions. In general, the gelators could be recycled without detriment to their gelation ability and reaction rates. Moreover, kinetics could be fine-tuned according to the characteristics of the gel media. For instance, entangled fibrillar networks with relatively high mechanical strength were usually associated with lower reaction rates, whereas wrinkled laminated morphologies seemed to favor the reaction. In addition, the kinetics results showed in most cases a good correlation with the aeration efficiency of the gel media.

An efficient hybrid approach for design of automotive wheel bearings

Wheel bearings play a crucial role in the mobility of a vehicle by minimizing motive power loss and providing stability in cornering maneuvers. Detailed engineering analysis of a wheel bearing subsystem under dynamic conditions poses enormous challenges due to the nonlinearity of the problem caused by multiple factional contacts between rotating and stationary parts and difficulties in prediction of dynamic loads that wheels are subject to. Commonly used design methodologies are based on equivalent static analysis of ball or roller bearings in which the latter elements may even be represented with springs. In the present study, an advanced hybrid approach is suggested for realistic dynamic analysis of wheel bearings by combining lumped parameter and finite element modeling techniques. A validated lumped parameter representation serves as an efficient tool for the prediction of radial wheel load due to ground reaction which is then used in detailed finite element analysis that automatically accounts for contact forces in an explicit formulation.

Analytical solutions for diffuse fluorescence spectroscopy/imaging in biological tissues. Part I: zero and extrapolated boundary conditions

The mathematical model for diffuse fluorescence spectroscopy/imaging is represented by coupled partial differential equations (PDEs), which describe the excitation and emission light propagation in soft biological tissues. The generic closed-form solutions for these coupled PDEs are derived in this work for the case of regular geometries using the Green's function approach using both zero and extrapolated boundary conditions. The specific solutions along with the typical data types, such as integrated intensity and the mean time of flight, for various regular geometries were also derived for both time-and frequency-domain cases. (C) 2013 Optical Society of America

Analytical solutions for diffuse fluorescence spectroscopy/imaging in biological tissues. Part II: comparison and validation

The analytical solutions for the coupled diffusion equations that are encountered in diffuse fluorescence spectroscopy/ imaging for regular geometries were compared with the well-established numerical models, which are based on the finite element method. Comparison among the analytical solutions obtained using zero boundary conditions and extrapolated boundary conditions (EBCs) was also performed. The results reveal that the analytical solutions are in close agreement with the numerical solutions, and solutions obtained using EBCs are more accurate in obtaining the mean time of flight data compared to their counterpart. The analytical solutions were also shown to be capable of providing bulk optical properties through a numerical experiment using a realistic breast model. (C) 2013 Optical Society of America

Planar triazinium cations from vanadyl-mediated ring cyclizations: the thiazole species for efficient nuclear staining and photocytotoxicity

Planar triazinium cationic species from vanadyl-assisted cyclization of 1-(2-thiazolylazo)-2-naphthol (H-TAN, 1), 1-(2-pyridylazo)-2-naphthol (H-PAN, 2), 2-(2'-thiazolylazo)-p-cresol (H-TAC, 3) and 6-(2'-thiazolylazo)- resorcinol (H-TAR, 5) were prepared and characterized. A dioxovanadium(V) species VO2(TAR)] (4) was also isolated. Compounds 1, 2 and 4 were structurally characterized. Both 1 and 2 have planar structures. Complex 4 has (VO3N2)-O-V coordination geometry. The cyclised triazinium compound forms a radical species within -0.06 to -0.29 V vs. SCE in DMF-0.1 M tetrabutylammonium perchlorate with a second response due to formation of an anionic species. A confocal microscopic study showed higher nuclear uptake for 1 having a fused thiazole moiety than 2 with a fused pyridine ring. The compounds showed a partial intercalative mode of binding to calf thymus DNA. Compound 1 showed plasmid DNA photo-cleavage activity under argon and photocytotoxicity in HeLa and MCF-7 cells with IC50 values of 15.1 and 3.4 mu M respectively in visible light of 400-700 nm, while being essentially non-toxic in the dark with IC50 values of 90.4 and 21.9 mu M. ATDDFT study was done to rationalize the experimental data.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Generating string solutions in BTZ

Integrability of classical strings in the BTZ black hole enables the construction and study of classical string propagation in this background. We first apply the dressing method to obtain classical string solutions in the BTZ black hole. We dress time like geodesics in the BTZ black hole and obtain open string solutions which are pinned on the boundary at a single point and whose end points move on time like geodesics. These strings upon regularising their charge and spins have a dispersion relation similar to that of giant magnons. We then dress space like geodesics which start and end on the boundary of the BTZ black hole and obtain minimal surfaces which can penetrate the horizon of the black hole while being pinned at the boundary. Finally we embed the giant gluon solutions in the BTZ background in two different ways. They can be embedded as a spiral which contracts and expands touching the horizon or a spike which originates from the boundary and touches the horizon.

Multiple parents crossover operators: A new approach removes the overlapping solutions for sequencing problems

Maintaining population diversity throughout generations of Genetic Algorithms (GAs) is key to avoid premature convergence. Redundant solutions is one cause for the decreasing population diversity. To prevent the negative effect of redundant solutions, we propose a framework that is based on the multi-parents crossover (MPX) operator embedded in GAs. Because MPX generates diversified chromosomes with good solution quality, when a pair of redundant solutions is found, we would generate a new offspring by using the MPX to replace the redundant chromosome. Three schemes of MPX will be examined and will be compared against some algorithms in literature when we solve the permutation flowshop scheduling problems, which is a strong NP-Hard sequencing problem. The results indicate that our approach significantly improves the solution quality. This study is useful for researchers who are trying to avoid premature convergence of evolutionary algorithms by solving the sequencing problems.

IceCube: efficient targeted mining in data cubes

We address the problem of mining targeted association rules over multidimensional market-basket data. Here, each transaction has, in addition to the set of purchased items, ancillary dimension attributes associated with it. Based on these dimensions, transactions can be visualized as distributed over cells of an n-dimensional cube. In this framework, a targeted association rule is of the form {X -> Y} R, where R is a convex region in the cube and X. Y is a traditional association rule within region R. We first describe the TOARM algorithm, based on classical techniques, for identifying targeted association rules. Then, we discuss the concepts of bottom-up aggregation and cubing, leading to the CellUnion technique. This approach is further extended, using notions of cube-count interleaving and credit-based pruning, to derive the IceCube algorithm. Our experiments demonstrate that IceCube consistently provides the best execution time performance, especially for large and complex data cubes.