Antenna Selection for Next Generation IEEE 802.16 Mobile Stations

The IEEE 802.16/WiMAX standard has fully embraced multi-antenna technology and can, thus, deliver robust and high transmission rates and higher system capacity. Nevertheless,due to its inherent form-factor constraints and cost concerns, a WiMAX mobile station (MS) should preferably contain fewer radio frequency (RF) chains than antenna elements.This is because RF chains are often substantially more expensive than antenna elements. Thus, antenna selection, wherein a subset of antennas is dynamically selected to connect to the limited RF chains for transceiving, is a highly appealing performance enhancement technique for multi-antenna WiMAX terminals.In this paper, a novel antenna selection protocol tailored for next-generation IEEE 802.16 mobile stations is proposed. As demonstrated by the extensive OPNET simulations, the proposed protocol delivers a significant performance improvement over conventional 802.16 terminals that lack the antenna selection capability. Moreover, the new protocol leverages the existing signaling methods defined in 802.16, thereby incurring a negligible signaling overhead and requiring only diminutive modifications of the standard. To the best of our knowledge, this paper represents the first effort to support antenna selection capability in IEEE 802.16 mobile stations.

Compiler-Directed Frequency and Voltage Scaling for a Multiple Clock Domain

Multiple Clock Domain processors provide an attractive solution to the increasingly challenging problems of clock distribution and power dissipation. They allow their chips to be partitioned into different clock domains, and each domain’s frequency (voltage) to be independently configured. This flexibility adds new dimensions to the Dynamic Voltage and Frequency Scaling problem, while providing better scope for saving energy and meeting performance demands. In this paper, we propose a compiler directed approach for MCD-DVFS. We build a formal petri net based program performance model, parameterized by settings of microarchitectural components and resource configurations, and integrate it with our compiler passes for frequency selection.Our model estimates the performance impact of a frequency setting, unlike the existing best techniques which rely on weaker indicators of domain performance such as queue occupancies(used by online methods) and slack manifestation for a particular frequency setting (software based methods).We evaluate our method with subsets of SPECFP2000,Mediabench and Mibench benchmarks. Our mean energy savings is 60.39% (versus 33.91% of the best software technique)in a memory constrained system for cache miss dominated benchmarks, and we meet the performance demands.Our ED2 improves by 22.11% (versus 18.34%) for other benchmarks. For a CPU with restricted frequency settings, our energy consumption is within 4.69% of the optimal.

On Selection of Features for Regional Hydrologic Studies

Feature selection is an important first step in regional hydrologic studies (RHYS). Over the past few decades, advances in data collection facilities have resulted in development of data archives on a variety of hydro-meteorological variables that may be used as features in RHYS. Currently there are no established procedures for selecting features from such archives. Therefore, hydrologists often use subjective methods to arrive at a set of features. This may lead to misleading results. To alleviate this problem, a probabilistic clustering method for regionalization is presented to determine appropriate features from the available dataset. The effectiveness of the method is demonstrated by application to regionalization of watersheds in conterminous United States for low flow frequency analysis. Plausible homogeneous regions that are formed by using the proposed clustering method are compared with those from conventional methods of regionalization using L-moment based homogeneity tests. Results show that the proposed methodology is promising for RHYS.

Task Dependent Boundary Mannequins in Statistical DHM

The primary objective of the paper is to make use of statistical digital human model to better understand the nature of reach probability of points in the taskspace. The concept of task-dependent boundary manikin is introduced to geometrically characterize the extreme individuals in the given population who would accomplish the task. For a given point of interest and task, the map of the acceptable variation in anthropometric parameters is superimposed with the distribution of the same parameters in the given population to identify the extreme individuals. To illustrate the concept, the task space mapping is done for the reach probability of human arms. Unlike the boundary manikins, who are completely defined by the population, the dimensions of these manikins will vary with task, say, a point to be reached, as in the present case. Hence they are referred to here as the task-dependent boundary manikins. Simulations with these manikins would help designers to visualize how differently the extreme individuals would perform the task. Reach probability at the points in a 3D grid in the operational space is computed; for objects overlaid in this grid, approximate probabilities are derived from the grid for rendering them with colors indicating the reach probability. The method may also help in providing a rational basis for selection of personnel for a given task.

Synthesis, Structure, Negative Thermal Expansion, and Photocatalytic Property of Mo Doped ZrV(2)O(7)

A new series of compounds identified in the phase diagram of ZrO(2)-V(2)O(8)-MoO(3) have been synthesized via the solution combustion method. Single crystals of one of the compounds in the series, ZrV(1.50)Mo(0.50)O(7.25), were grown by the melt-cool technique from the starting materials with double the MoO(3) quantity. The room temperature average crystal structure of the grown crystals was solved using the single crystal X-ray diffraction technique. The crystals belong to the cubic crystal system, space group Pa (3) over bar (No. 205) with a = 8.8969 (4) angstrom, V = 704.24 (6) angstrom(3), and Z = 4. The final R(1) value of 0.0213 was achieved for 288 independent reflections during the structure refinement. The Zr(4+) occupies the special position (4a) whereas V(5+) and Mo(6+) occupy two unique (8c) Wyckoff positions. Two fully occupied O atoms, (24d) and (4b), one partially occupied 0 atom (8c) have been identified for this molybdovanadate, which is a unique feature for these crystals. The structure is related to both ZrV(2)O(7) and cubic ZrMo(2)O(8). The temperature dependent single crystal studies show negative thermal expansion above 370 K. The compounds have been characterized by powder X-ray diffraction, solid-state UV-vis diffuse reflectance spectra, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The photocatalytic activity of these compounds has been investigated for the degradation of various dyes, and these compounds show specificity toward the degradation of non-azoic dyes.

Antenna Selection Training in MIMO-OFDM/OFDMA Cellular Systems

Antenna selection allows multiple-antenna systems to achieve most of their promised diversity gain, while keeping the number of RF chains and, thus, cost/complexity low. In this paper we investigate antenna selection for fourth-generation OFDMA- based cellular communications systems, in particular, 3GPP LTE (long-term evolution) systems. We propose a training method for antenna selection that is especially suitable for OFDMA. By means of simulation, we evaluate the SNR-gain that can be achieved with our design. We find that the performance depends on the bandwidth assigned to each user, the scheduling method (round-robin or frequency-domain scheduling), and the Doppler spread. Furthermore, the signal-to-noise ratio of the training sequence plays a critical role. Typical SNR gains are around 2 dB, with larger values obtainable in certain circumstances.

Efficiency enhancement in DSSC using metal nanoparticles: A size dependent study

The photoelectrode of Eosin-Y sensitised DSSC was modified by incorporating Au-nanoparticles to enhance the power conversion efficiency via scattering from surface plasmon polaritons. Size dependence of Au nanoparticle on conversion efficiency was performed in DSSC for the first time by varying the particle size from 20 to 94 nm. It was found that, the conversion efficiency is highly dependent on the size of the Au nanoparticles. For larger particles (>50 nm), the efficiency was found to be increased due to constructive interference between the transmitted and scattered waves from the Au nanoparticle while for smaller particles, the efficiency decreases due to destructive interference. Also a reduction in the V-oc was observed in general, due to the negative shifting of the TiO2 Fermi level on the adsorption of Au nanoparticle. This shift was negligible for larger particles. When 94 nm size particles were employed the conversion efficiency was doubled from 0.74% to 1.52%. This study points towards the application of the scattering effect of metal nanoparticle to enhance the conversion efficiency in DSSCs. (C) 2011 Elsevier Ltd. All rights reserved.

Structural and phase dependent thermo and photoluminescent properties of Dy(OH)(3) and Dy2O3 nanorods

Hexagonal Dy(OH)(3) and cubic Dy2O3 nanorods were prepared by hydrothermal method. Dy(OH)(3) nanorods was directly obtained at 180 degrees C for 20 h after hydrothermal treatment whereas subsequently heat treatment at 750 degrees C for 2 h gives pure cubic Dy2O3. SEM micrographs reveal that needle shaped rods with different sizes were observed in both the phases. TEM results also confirm this. The TL response of hexagonal Dy(OH)(3) and cubic Dy2O3 nanorods have been analyzed for gamma-irradiation over a wide range of exposures (1-5 kGy). TL glow peak intensity increases with gamma dose in both the phases. The activation energy (E), order of kinetics (6), and frequency factor (s) for both the phases have been determined using Chen's peak shape method. The simple glow curve shape, structure and linear response to gamma-irradiation over a large span of exposures makes the cubic Dy2O3 as a useful dosimetric material to estimate high exposures of gamma-rays. (c) 2012 Elsevier Ltd. All rights reserved.

Optical frequency metrology with an Rb-stabilized ring-cavity resonator-study of cavity-dispersion errors

We have developed a technique to measure the absolute frequencies of optical transitions by using an evacuated Rb-stabilized ring-cavity resonator as a transfer cavity. The absolute frequency of the Rb D-2 line (at 780 nm) used to stabilize the cavity is known and allows us to determine the absolute value of the unknown frequency. We study wavelength-dependent errors due to dispersion at the cavity mirrors by measuring the frequency of the same transition in the Cs D-2 line (at 852 nm) at three cavity lengths. The spread in the values shows that dispersion errors are below 30 kHz, corresponding to a relative precision of 10(-10). We give an explanation for reduced dispersion errors in the ring-cavity geometry by calculating errors due to the lateral shift and the phase shift at the mirrors, and show that they are roughly equal but occur with opposite signs. We have earlier shown that diffraction errors (due to Guoy phase) are negligible in the ring-cavity geometry compared to a linear cavity; the reduced dispersion error is another advantage. Our values are consistent with measurements of the same transition using the more expensive frequency-comb technique. Our simpler method is ideally suited for measuring hyperfine structure, fine structure, and isotope shifts, up to several hundreds of gigahertz.

Size-dependent free flexural vibration behavior of functionally graded nanoplates

In this paper, size dependent linear free flexural vibration behavior of functionally graded (FG) nanoplates are investigated using the iso-geometric based finite element method. The field variables are approximated by non-uniform rational B-splines. The nonlocal constitutive relation is based on Eringen's differential form of nonlocal elasticity theory. The material properties are assumed to vary only in the thickness direction and the effective properties for the FG plate are computed using Mori-Tanaka homogenization scheme. The accuracy of the present formulation is demonstrated considering the problems for which solutions are available. A detailed numerical study is carried out to examine the effect of material gradient index, the characteristic internal length, the plate thickness, the plate aspect ratio and the boundary conditions on the global response of the FG nanoplate. From the detailed numerical study it is seen that the fundamental frequency decreases with increasing gradient index and characteristic internal length. (c) 2012 Elsevier B.V. All rights reserved.

A physics-based flexural phonon-dependent thermal conductivity model for single layer graphene

In this paper, we address a physics-based closed-form analytical model of flexural phonon-dependent diffusive thermal conductivity (kappa) of suspended rectangular single layer graphene sheet. A quadratic dependence of the out-of-plane phonon frequency, generally called flexural phonons, on the phonon wave vector has been taken into account to analyze the behavior of kappa at lower temperatures. Such a dependence has further been used for the determination of second-order three-phonon Umklapp and isotopic scatterings. We find that these behaviors in our model are best explained through the upper limit of Debye cut-off frequency in the second-order three-phonon Umklapp scattering of the long phonon waves that actually remove the thermal conductivity singularity by contributing a constant scattering rate at low frequencies and note that the out-of-plane Gruneisen parameter for these modes need not be too high. Using this, we clearly demonstrate that. follows a T-1.5 and T-2 law at lower and higher temperatures in the absence of isotopes, respectively. However in their presence, the behavior of kappa sharply deviates from the T-2 law at higher temperatures. The present geometry-dependent model of kappa is found to possess an excellent match with various experimental data over a wide range of temperatures which can be put forward for efficient electro-thermal analyses of encased/supported graphene.

SPARSE SIGNAL RECONSTRUCTION BASED ON SIGNAL DEPENDENT NON-UNIFORM SAMPLES

The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

On the Selection of Optimum Savitzky-Golay Filters

Savitzky-Golay (S-G) filters are finite impulse response lowpass filters obtained while smoothing data using a local least-squares (LS) polynomial approximation. Savitzky and Golay proved in their hallmark paper that local LS fitting of polynomials and their evaluation at the mid-point of the approximation interval is equivalent to filtering with a fixed impulse response. The problem that we address here is, ``how to choose a pointwise minimum mean squared error (MMSE) S-G filter length or order for smoothing, while preserving the temporal structure of a time-varying signal.'' We solve the bias-variance tradeoff involved in the MMSE optimization using Stein's unbiased risk estimator (SURE). We observe that the 3-dB cutoff frequency of the SURE-optimal S-G filter is higher where the signal varies fast locally, and vice versa, essentially enabling us to suitably trade off the bias and variance, thereby resulting in near-MMSE performance. At low signal-to-noise ratios (SNRs), it is seen that the adaptive filter length algorithm performance improves by incorporating a regularization term in the SURE objective function. We consider the algorithm performance on real-world electrocardiogram (ECG) signals. The results exhibit considerable SNR improvement. Noise performance analysis shows that the proposed algorithms are comparable, and in some cases, better than some standard denoising techniques available in the literature.

Sonic hedgehog-Dependent Induction of MicroRNA 31 and MicroRNA 150 Regulates Mycobacterium bovis BCG-Driven Toll-Like Receptor 2 Signaling

Hedgehog (HH) signaling is a significant regulator of cell fate decisions during embryogenesis, development, and perpetuation of various disease conditions. Testing whether pathogen-specific HH signaling promotes unique innate recognition of intracellular bacteria, we demonstrate that among diverse Gram-positive or Gram-negative microbes, Mycobacterium bovis BCG, a vaccine strain, elicits a robust activation of Sonic HH (SHH) signaling in macrophages. Interestingly, sustained tumor necrosis factor alpha (TNF-alpha) secretion by macrophages was essential for robust SHH activation, as TNF-alpha(-/-) macrophages exhibited compromised ability to activate SHH signaling. Neutralization of TNF-alpha or blockade of TNF-alpha receptor signaling significantly reduced the infection-induced SHH signaling activation both in vitro and in vivo. Intriguingly, activated SHH signaling downregulated M. bovis BCG-mediated Toll-like receptor 2 (TLR2) signaling events to regulate a battery of genes associated with divergent functions of M1/M2 macrophages. Genome-wide expression profiling as well as conventional gain-of-function or loss-of-function analysis showed that SHH signaling-responsive microRNA 31 (miR-31) and miR-150 target MyD88, an adaptor protein of TLR2 signaling, thus leading to suppression of TLR2 responses. SHH signaling signatures could be detected in vivo in tuberculosis patients and M. bovis BCG-challenged mice. Collectively, these investigations identify SHH signaling to be what we believe is one of the significant regulators of host-pathogen interactions.

Feature selection for unsupervised learning

In this paper, we present a methodology for identifying best features from a large feature space. In high dimensional feature space nearest neighbor search is meaningless. In this feature space we see quality and performance issue with nearest neighbor search. Many data mining algorithms use nearest neighbor search. So instead of doing nearest neighbor search using all the features we need to select relevant features. We propose feature selection using Non-negative Matrix Factorization(NMF) and its application to nearest neighbor search. Recent clustering algorithm based on Locally Consistent Concept Factorization(LCCF) shows better quality of document clustering by using local geometrical and discriminating structure of the data. By using our feature selection method we have shown further improvement of performance in the clustering.