Near-optimal large-MIMO detection using randomized MCMC and randomized search algorithms

Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

Comparison of 3-phase, 3-level UPF rectifier circuits for high power applications

This paper presents an analysis and comparison between two circuit topologies of the 3-phase, 3-level unity power factor (Vienna) rectifier on the basis of packaging issues and semiconductor power losses. The analysis indicates the suitability of one particular circuit variant due to restrictions on switching frequency at higher power levels. A comparison is also done between hysteresis and carrier based PWM strategies for current control of the rectifier, along with experimental evaluation of the control strategies on a hardware prototype of the rectifier. The comparison indicates that the carrier based modulation strategy is better suited for use with higher order filters that are utilized in high power applications.

Sub-band envelope approach to obtain instants of significant excitation in speech

In this paper, we propose a new sub-band approach to estimate the glottal activity. The method is based on the spectral harmonicity and the sub-band temporal properties of voiced speech. We propose a method to represent glottal excitation signal using sub-band temporal envelope. Instants of maximum glottal excitation or Glottal Closure Instants (GCI) are extracted from the estimated glottal excitation pattern and the result is compared with a standard GCI computation method, DYPSA [1]. The performance of the algorithm is also compared for the noisy signal and it is shown that the proposed method is less variant to GCI estimation under noisy conditions compared to DYPSA. The algorithm is evaluated on the CMU-ARCTIC database.

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.

Improved LSB stegananalysis based on analysis of adjacent pixel pairs

We propose a simple, reliable method based on probability of transitions and distribution of adjacent pixel pairs for steganalysis on digital images in spatial domain subjected to Least Significant Bit replacement steganography. Our method is sensitive to the statistics of underlying cover image and is a variant of Sample Pair Method. We use the new method to estimate length of hidden message reliably. The novelty of our method is that it detects from the statistics of the underlying image, which is invariant with embedding, whether the results it calculate are reliable or not. To our knowledge, no steganalytic method so far predicts from the properties of the stego image, whether its results are accurate or not.

Evolution of microstructure and texture in Ni49.4Ti38.6Hf12 shape memory alloy during hot rolling

This paper deals with the evolution of microstructure and texture during hot rolling of hafnium containing NiTi based shape memory alloy Ni49.4Ti38.6Hf12. The formation of the R-phase has been associated with the precipitation of (Ti,Hf)(2)Ni phase. The crystallographic texture of the parent phase B2 as well as the product phases R and B19' have been determined. It has been found that the variant selection during the B2 -> R phase transformation is quite strong compared to the case of the B2 -> B19' transformation. During deformation, the texture of the austenite phase evolves with strong Goss and Bs components. After transformation to martensitic structure, it gives rise to a 011]parallel to RD fiber. Microstructure and texture studies reveal the occurrence of partial dynamic recrystallization during hot rolling. Large strain heterogeneities that occur surrounding (Ti,Hf)(2)Ni precipitates are relieved through extended dynamic recovery instead of particle stimulated nucleation.

Numerical analysis of geocell reinforced ballast overlying soft clay subgrade

Geotextiles and geogrids have been in use for several decades in variety of geo-structure applications including foundation of embankments, retaining walls, pavements. Geocells is one such variant in geosynthetic reinforcement of recent years, which provides a three dimensional confinement to the infill material. Although extensive research has been carried on geocell reinforced sand, clay and layered soil subgrades, limited research has been reported on the aggregates/ballast reinforced with geocells. This paper presents the behavior of a railway sleeper subjected to monotonic loading on geocell reinforced aggregates, of size ranging from 20 to 75 mm, overlying soft clay subgrades. Series of tests were conducted in a steel test tank of dimensions 700 mm x 300 mm x 700 mm. In addition to the laboratory model tests, numerical simulations were performed using a finite difference code to predict the behavior of geocell reinforced ballast. The results from numerical simulations were compared with the experimental data. The numerical and experimental results manifested the importance that the geocell reinforcement has a significant effect on the ballast behaviour. The results depicted that the stiffness of underlying soft clay subgrade has a significant influence on the behavior of the geocell-aggregate composite material in redistributing the loading system.

On the Erdos-Szekeres n-interior-point problem

The n-interior-point variant of the Erdos Szekeres problem is the following: for every n, n >= 1, does there exist a g(n) such that every point set in the plane with at least g(n) interior points has a convex polygon containing exactly n interior points. The existence of g(n) has been proved only for n <= 3. In this paper, we show that for any fixed r >= 2, and for every n >= 5, every point set having sufficiently large number of interior points and at most r convex layers contains a subset with exactly n interior points. We also consider a relaxation of the notion of convex polygons and show that for every n, n >= 1, any point set with at least n interior points has an almost convex polygon (a simple polygon with at most one concave vertex) that contains exactly n interior points. (C) 2013 Elsevier Ltd. All rights reserved.

Spatial filtering nearly eliminates the side-lobes in single- and multi-photon 4pi-type-C super-resolution fluorescence microscopy

Super-resolution microscopy has tremendously progressed our understanding of cellular biophysics and biochemistry. Specifically, 4pi fluorescence microscopy technique stands out because of its axial super-resolution capability. All types of 4pi-microscopy techniques work well in conjugation with deconvolution techniques to get rid of artifacts due to side-lobes. In this regard, we propose a technique based on spatial filter in a 4pi-type-C confocal setup to get rid of these artifacts. Using a special spatial filter, we have reduced the depth-of-focus. Interference of two similar depth-of-focus beams in a 4 pi geometry result in substantial reduction of side-lobes. Studies show a reduction of side-lobes by 46% and 76% for single and two photon variant compared to 4pi - type - C confocal system. This is incredible considering the resolving capability of the existing 4pi - type - C confocal microscopy. Moreover, the main lobe is found to be 150 nm for the proposed spatial filtering technique as compared to 690 nm of the state-of-art confocal system. Reconstruction of experimentally obtained 2PE - 4pi data of green fluorescent protein (GFP)-tagged mitocondrial network shows near elimination of artifacts arising out of side-lobes. Proposed technique may find interesting application in fluorescence microscopy, nano-lithography, and cell biology. (C) 2013 AIP Publishing LLC.

Validation based sparse Gaussian processes for ordinal regression

This paper proposes a sparse modeling approach to solve ordinal regression problems using Gaussian processes (GP). Designing a sparse GP model is important from training time and inference time viewpoints. We first propose a variant of the Gaussian process ordinal regression (GPOR) approach, leave-one-out GPOR (LOO-GPOR). It performs model selection using the leave-one-out cross-validation (LOO-CV) technique. We then provide an approach to design a sparse model for GPOR. The sparse GPOR model reduces computational time and storage requirements. Further, it provides faster inference. We compare the proposed approaches with the state-of-the-art GPOR approach on some benchmark data sets. Experimental results show that the proposed approaches are competitive.

SEP-optimal antenna selection for average interference constrained underlay cognitive radios

In the underlay mode of cognitive radio, secondary users can transmit when the primary is transmitting, but under tight interference constraints, which limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which require less hardware and yet exploit spatial diversity, help improve the secondary system performance. In this paper, we develop the optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gains of the channels from secondary transmit antenna to primary receiver and secondary transmit antenna to secondary receive antenna. The optimal rule is different from the several ad hoc rules that have been proposed in the literature. We also propose a closed-form, tractable variant of the optimal rule and analyze its SEP. Several results are presented to compare the performance of the closed-form rule with the ad hoc rules, and interesting inter-relationships among them are brought out.

Inactivation of the Bacterial RNA Polymerase Due to Acquisition of Secondary Structure by the omega Subunit

The widely conserved omega subunit encoded by rpoZ is the smallest subunit of Escherichia coli RNA polymerase (RNAP) but is dispensable for bacterial growth. Function of omega is known to be substituted by GroEL in omega-null strain, which thus does not exhibit a discernable phenotype. In this work, we report isolation of omega variants whose expression in vivo leads to a dominant lethal phenotype. Studies show that in contrast to omega, which is largely unstructured, omega mutants display substantial acquisition of secondary structure. By detailed study with one of the mutants, omega(6) bearing N60D substitution, the mechanism of lethality has been deciphered. Biochemical analysis reveals that omega(6) binds to beta ` subunit in vitro with greater affinity than that of omega. The reconstituted RNAP holoenzyme in the presence of omega(6) in vitro is defective in transcription initiation. Formation of a faulty RNAP in the presence of mutant omega results in death of the cell. Furthermore, lethality of omega(6) is relieved in cells expressing the rpoC2112 allele encoding beta ` (2112), a variant beta ` bearing Y457S substitution, immediately adjacent to the beta ` catalytic center. Our results suggest that the enhanced omega(6)-beta ` interaction may perturb the plasticity of the RNAP active center, implicating a role for omega and its flexible state.

On Averaging Multiview Relations for 3D Scan Registration

In this paper, we present an extension of the iterative closest point (ICP) algorithm that simultaneously registers multiple 3D scans. While ICP fails to utilize the multiview constraints available, our method exploits the information redundancy in a set of 3D scans by using the averaging of relative motions. This averaging method utilizes the Lie group structure of motions, resulting in a 3D registration method that is both efficient and accurate. In addition, we present two variants of our approach, i.e., a method that solves for multiview 3D registration while obeying causality and a transitive correspondence variant that efficiently solves the correspondence problem across multiple scans. We present experimental results to characterize our method and explain its behavior as well as those of some other multiview registration methods in the literature. We establish the superior accuracy of our method in comparison to these multiview methods with registration results on a set of well-known real datasets of 3D scans.

Rad51-Rad52 Mediated Maintenance of Centromeric Chromatin in Candida albicans

Specification of the centromere location in most eukaryotes is not solely dependent on the DNA sequence. However, the non-genetic determinants of centromere identity are not clearly defined. While multiple mechanisms, individually or in concert, may specify centromeres epigenetically, most studies in this area are focused on a universal factor, a centromere-specific histone H3 variant CENP-A, often considered as the epigenetic determinant of centromere identity. In spite of variable timing of its loading at centromeres across species, a replication coupled early S phase deposition of CENP-A is found in most yeast centromeres. Centromeres are the earliest replicating chromosomal regions in a pathogenic budding yeast Candida albicans. Using a 2-dimensional agarose gel electrophoresis assay, we identify replication origins (ORI7-LI and ORI7-RI) proximal to an early replicating centromere (CEN7) in C. albicans. We show that the replication forks stall at CEN7 in a kinetochore dependent manner and fork stalling is reduced in the absence of the homologous recombination (HR) proteins Rad51 and Rad52. Deletion of ORI7-RI causes a significant reduction in the stalled fork signal and an increased loss rate of the altered chromosome 7. The HR proteins, Rad51 and Rad52, have been shown to play a role in fork restart. Confocal microscopy shows declustered kinetochores in rad51 and rad52 mutants, which are evidence of kinetochore disintegrity. CENP-A(CaCse4) levels at centromeres, as determined by chromatin immunoprecipitation (ChIP) experiments, are reduced in absence of Rad51/Rad52 resulting in disruption of the kinetochore structure. Moreover, western blot analysis reveals that delocalized CENP-A molecules in HR mutants degrade in a similar fashion as in other kinetochore mutants described before. Finally, co-immunoprecipitation assays indicate that Rad51 and Rad52 physically interact with CENP-A(CaCse4) in vivo. Thus, the HR proteins Rad51 and Rad52 epigenetically maintain centromere functioning by regulating CENP-A(CaCse4) levels at the programmed stall sites of early replicating centromeres.