Fusion of algorithms for compressed sensing

For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.

Stable hybrid containing haploid genomes of two obligate diploid Candida species

Candida albicans and Candida dubliniensis are diploid, predominantly asexual human-pathogenic yeasts. In this study, we constructed tetraploid (4n) strains of C. albicans of the same or different lineages by spheroplast fusion. Induction of chromosome loss in the tetraploid C. albicans generated diploid or near-diploid progeny strains but did not produce any haploid progeny. We also constructed stable heterotetraploid somatic hybrid strains (2n + 2n) of C. albicans and C. dubliniensis by spheroplast fusion. Heterodiploid (n + n) progeny hybrids were obtained after inducing chromosome loss in a stable heterotetraploid hybrid. To identify a subset of hybrid heterodiploid progeny strains carrying at least one copy of all chromosomes of both species, unique centromere sequences of various chromosomes of each species were used as markers in PCR analysis. The reduction of chromosome content was confirmed by a comparative genome hybridization (CGH) assay. The hybrid strains were found to be stably propagated. Chromatin immunoprecipitation (ChIP) assays with antibodies against centromere-specific histones (C. albicans Cse4/C. dubliniensis Cse4) revealed that the centromere identity of chromosomes of each species is maintained in the hybrid genomes of the heterotetraploid and heterodiploid strains. Thus, our results suggest that the diploid genome content is not obligatory for the survival of either C. albicans or C. dubliniensis. In keeping with the recent discovery of the existence of haploid C. albicans strains, the heterodiploid strains of our study can be excellent tools for further species-specific genome elimination, yielding true haploid progeny of C. albicans or C. dubliniensis in future.

A Hybrid Parallel Algorithm for Computing and Tracking Level Set Topology

The contour tree is a topological abstraction of a scalar field that captures evolution in level set connectivity. It is an effective representation for visual exploration and analysis of scientific data. We describe a work-efficient, output sensitive, and scalable parallel algorithm for computing the contour tree of a scalar field defined on a domain that is represented using either an unstructured mesh or a structured grid. A hybrid implementation of the algorithm using the GPU and multi-core CPU can compute the contour tree of an input containing 16 million vertices in less than ten seconds with a speedup factor of upto 13. Experiments based on an implementation in a multi-core CPU environment show near-linear speedup for large data sets.

Hybrid aggregated-vector algorithm for efficient parallelization of fast multipole method

An efficient parallelization algorithm for the Fast Multipole Method which aims to alleviate the parallelization bottleneck arising from lower job-count closer to root levels is presented. An electrostatic problem of 12 million non-uniformly distributed mesh elements is solved with 80-85% parallel efficiency in matrix setup and matrix-vector product using 60GB and 16 threads on shared memory architecture.

Carbon nanotube-ZnO nanowire hybrid architectures as multifunctional devices

We report on multifunctional devices based on CNT arrays-ZnO nanowires hybrid architectures. The hybrid structure exhibit excellent high current Schottky like behavior with ZnO as p-type and an ideality factor close to the ideal value. Further the CNT-ZnO hybrid structures can be used as high current p-type field effect transistors that can deliver currents of the order of milliamperes and also can be used as ultraviolet detectors with controllable current on-off ratio and response time. The p-type nature of ZnO and possible mechanism for the rectifying characteristics of CNT-ZnO has been presented.

The dual role of Zn-acid medium for one-step rapid synthesis of M@rGO (M = Au, Pt, Pd and Ag) hybrid nanostructures at room temperature

We report a new protocol for the synthesis of M@rGO (M = Au, Pt, Pd, Ag and rGO = reduced graphene oxide) hybrid nanostructures at room temperature in Zn-acid medium. The roles of Zn-acid are to reduce the GO by generated hydrogen and the deposition of metal nanoparticles on rGO by galvanic replacement reaction between Zn and Mn+.

Polynomial time and parameterized approximation algorithms for boxicity

The boxicity (cubicity) of a graph G, denoted by box(G) (respectively cub(G)), is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (cubes) in ℝ k . The problem of computing boxicity (cubicity) is known to be inapproximable in polynomial time even for graph classes like bipartite, co-bipartite and split graphs, within an O(n 0.5 − ε ) factor for any ε > 0, unless NP = ZPP. We prove that if a graph G on n vertices has a clique on n − k vertices, then box(G) can be computed in time n22O(k2logk) . Using this fact, various FPT approximation algorithms for boxicity are derived. The parameter used is the vertex (or edge) edit distance of the input graph from certain graph families of bounded boxicity - like interval graphs and planar graphs. Using the same fact, we also derive an O(nloglogn√logn√) factor approximation algorithm for computing boxicity, which, to our knowledge, is the first o(n) factor approximation algorithm for the problem. We also present an FPT approximation algorithm for computing the cubicity of graphs, with vertex cover number as the parameter.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing system

Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramer-Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a stage-wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Facile synthesis of Cu2CoSnS4 nanoparticles exhibiting red-edge-effect: Application in hybrid photonic devices

Cu2CoSnS4 (CCTS) quaternary semiconducting nanoparticles with size distribution from 20 nm to 60 nm were synthesized by one-pot low temperature time and surfactant dependent hydrothermal route. Nanoparticles were characterized structurally and optically. Excitation dependent fluorescence exhibited a dynamic stoke shift referring to the Red-Edge-Effect with peak shifting by a greater magnitude (>100 nm) towards red side, in all the samples. Hybrid devices, fabricated from CCTS nanoparticle inorganic counterparts benefitting from the conjugation of organic P3HT polymer matrix, were demonstrated for photodetection under infra-red and A. M 1.5 solar light illuminations. Faster rise and decay constants of 37 ms and 166 ms, with one order photocurrent amplification from 1.6 x 10(-6) A in the dark to 6.55 x 10(-5) A, upon the 18.50 mW cm(-2) IR lamp illumination, make CCTS a potential candidate for photodetector and photovoltaic applications. (C) 2013 AIP Publishing LLC.

Graphene-MoS2 hybrid structures for multifunctional photoresponsive memory devices

Combining the electronic properties of graphene(1,2) and molybdenum disulphide (MoS2)(3-6) in hybrid heterostructures offers the possibility to create devices with various functionalities. Electronic logic and memory devices have already been constructed from graphene-MoS2 hybrids(7,8), but they do not make use of the photosensitivity of MoS2, which arises from its optical-range bandgap(9). Here, we demonstrate that graphene-on-MoS2 binary heterostructures display remarkable dual optoelectronic functionality, including highly sensitive photodetection and gate-tunable persistent photoconductivity. The responsivity of the hybrids was found to be nearly 1 x 10(10) A W-1 at 130 K and 5 x 10(8) A W-1 at room temperature, making them the most sensitive graphene-based photodetectors. When subjected to time-dependent photoillumination, the hybrids could also function as a rewritable optoelectronic switch or memory, where the persistent state shows almost no relaxation or decay within experimental timescales, indicating near-perfect charge retention. These effects can be quantitatively explained by gate-tunable charge exchange between the graphene and MoS2 layers, and may lead to new graphene-based optoelectronic devices that are naturally scalable for large-area applications at room temperature.

Hybrid Energy Harvesting Wireless Systems: Performance Evaluation and Benchmarking

Energy harvesting sensor (EHS) nodes provide an attractive and green solution to the problem of limited lifetime of wireless sensor networks (WSNs). Unlike a conventional node that uses a non-rechargeable battery and dies once it runs out of energy, an EHS node can harvest energy from the environment and replenish its rechargeable battery. We consider hybrid WSNs that comprise of both EHS and conventional nodes; these arise when legacy WSNs are upgraded or due to EHS deployment cost issues. We compare conventional and hybrid WSNs on the basis of a new and insightful performance metric called k-outage duration, which captures the inability of the nodes to transmit data either due to lack of sufficient battery energy or wireless fading. The metric overcomes the problem of defining lifetime in networks with EHS nodes, which never die but are occasionally unable to transmit due to lack of sufficient battery energy. It also accounts for the effect of wireless channel fading on the ability of the WSN to transmit data. We develop two novel, tight, and computationally simple bounds for evaluating the k-outage duration. Our results show that increasing the number of EHS nodes has a markedly different effect on the k-outage duration than increasing the number of conventional nodes.

Design of substrate-integrated lead-carbon hybrid ultracapacitor and experimental validation

Suitability of substrate-integrated lead-carbon hybrid ultracapacitors for low-power back-up applications is studied. A practical application that provides 30 W power back-up to low-power medical gadgets for use in grid-power-deficient rural areas is presented. An ultracapacitor bank is designed for this application and the sizing calculations are provided. Experimental validation and results are also discussed.

Conflict-tolerant specifications for hybrid systems

We propose a framework for developing and reasoning about hybrid systems that are comprised of a plant with multiple controllers, each of which controls the plant intermittently. The framework is based on the notion of a ``conflict tolerant'' specification for a controller, and provides a modular way of developing and reasoning about such systems. We propose a novel mechanism of defining conflict-tolerant specifications for general hybrid systems, using ``acceptor'' and ``advisor'' components. We also give a decision procedure for verifying whether a controller satisfies its conflict-tolerant specification, in the special case when the components are modeled using initialized rectangular hybrid automata.