Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.

Morphological Effects of G-Quadruplex Stabilization Using a Small Molecule in Zebrafish

Zebrafish (Danio rerio) embryos are transparent and advantageous for studying early developmental changes due to ex utero development, making them an appropriate model for studying gene expression changes as a result of molecular targeting. Zebrafish embryos were injected with a previously reported G-quadruplex selective ligand, and the phenotypic changes were recorded. We report marked discrepancies in the development of intersegmental vessels. In silico analysis determined that the putative G-quadruplex motif occur in the upstream promoter region of the Cdh5 (N-cadherin) gene. A real-time polymerase chain reaction-based investigation indicated that in zebrafish, CDH-2 (ZN-cad) was significantly downregulated in the ligand-treated embryos. Biophysical characterization of the interaction of the ligand with the G-quadruplex motif found in this promoter yielded strong binding and stabilization of the G-quadruplex with this ligand. Hence, we report for the first time the phenotypic impact of G-quadruplex targeting with a ligand in a vertebrate organism. This study has unveiled not only G-quadruplex targeting in non-human animal species but also the potential that G-quadruplexes can provide a ready tool for understanding the phenotypic effects of targeting certain important genes involved in differentiation and developmental processes in a living eukaryotic organism.

Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding

H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

On the Parameterized Complexity of the Maximum Edge 2-Coloring Problem

We investigate the parameterized complexity of the following edge coloring problem motivated by the problem of channel assignment in wireless networks. For an integer q >= 2 and a graph G, the goal is to find a coloring of the edges of G with the maximum number of colors such that every vertex of the graph sees at most q colors. This problem is NP-hard for q >= 2, and has been well-studied from the point of view of approximation. Our main focus is the case when q = 2, which is already theoretically intricate and practically relevant. We show fixed-parameter tractable algorithms for both the standard and the dual parameter, and for the latter problem, the result is based on a linear vertex kernel.

Morphological Evolution in Air-Stable Metallic Iron Nanostructures and Their Magnetic Study

Iron nanostructures with morphology ranging from discrete nanoparticles to nearly monodisperse hierarchical nanostructures have been successfully synthesized using solvated metal atom dispersion (SMAD) method. Such a morphological evolution was realized by tuning the molar ratio of ligand to metal. Surface energy minimization in confluence with strong magnetic interactions and ligand-based stabilization results in the formation of nanospheres of iron. The as-prepared amorphous iron nanostructures exhibit remarkably high coercivity in comparison to the discrete nanoparticles and bulk counterpart. Annealing the as-prepared amorphous Fe nanostructures under anaerobic conditions affords air-stable carbon-encapsulated Fe(0) and Fe3C nanostructures with retention of the morphology. The resulting nanostructures were thoroughly analyzed by powder X-ray diffraction (PXRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), and Raman spectroscopy. TGA brought out that Fe3C nanostructures are more robust toward oxidation than those of a-Fe. Finally, detailed magnetic studies were carried out by superconducting quantum interference device (SQUID) magnetometer and it was found that the magnetic properties remain conserved even upon exposure of the annealed samples to ambient conditions for months.

On the Communication Complexity of Secret Key Generation in the Multiterminal Source Model

Communication complexity refers to the minimum rate of public communication required for generating a maximal-rate secret key (SK) in the multiterminal source model of Csiszar and Narayan. Tyagi recently characterized this communication complexity for a two-terminal system. We extend the ideas in Tyagi's work to derive a lower bound on communication complexity in the general multiterminal setting. In the important special case of the complete graph pairwise independent network (PIN) model, our bound allows us to determine the exact linear communication complexity, i.e., the communication complexity when the communication and SK are restricted to be linear functions of the randomness available at the terminals.

Sphere to ring morphological transformation in drying nanofluid droplets in a contact-free environment

Understanding the transients of buckling in drying colloidal suspensions is pivotal for producing new functional microstructures with tunable morphologies. Here, we report first observations and elucidate the buckling instability induced morphological transition (sphere to ring structure) in an acoustically levitated, heated nanosuspension droplet using dynamic energy balance. Droplet deformation featuring the formation of symmetric cavities is initiated by capillary pressure that is two to three orders of magnitude greater than the acoustic radiation pressure, thus indicating that the standing pressure field has no influence on the buckling front kinetics. With an increase in heat flux, the growth rate of surface cavities and their post-buckled volume increase while the buckling time period reduces, thereby altering the buckling pathway and resulting in distinct precipitate structures. However, irrespective of the heating rate, the volumetric droplet deformation exhibits a linear time dependence and the droplet vaporization is observed to deviate from the classical D-2-law.

Efficient QR Decomposition Using Low Complexity Column-wise Givens Rotation (CGR)

QR decomposition (QRD) is a widely used Numerical Linear Algebra (NLA) kernel with applications ranging from SONAR beamforming to wireless MIMO receivers. In this paper, we propose a novel Givens Rotation (GR) based QRD (GR QRD) where we reduce the computational complexity of GR and exploit higher degree of parallelism. This low complexity Column-wise GR (CGR) can annihilate multiple elements of a column of a matrix simultaneously. The algorithm is first realized on a Two-Dimensional (2 D) systolic array and then implemented on REDEFINE which is a Coarse Grained run-time Reconfigurable Architecture (CGRA). We benchmark the proposed implementation against state-of-the-art implementations to report better throughput, convergence and scalability.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

On the Parameterized Complexity of Finding Separators with Non-Hereditary Properties

We study the problem of finding small s-t separators that induce graphs having certain properties. It is known that finding a minimum clique s-t separator is polynomial-time solvable (Tarjan in Discrete Math. 55:221-232, 1985), while for example the problems of finding a minimum s-t separator that induces a connected graph or forms an independent set are fixed-parameter tractable when parameterized by the size of the separator (Marx et al. in ACM Trans. Algorithms 9(4): 30, 2013). Motivated by these results, we study properties that generalize cliques, independent sets, and connected graphs, and determine the complexity of finding separators satisfying these properties. We investigate these problems also on bounded-degree graphs. Our results are as follows: Finding a minimum c-connected s-t separator is FPT for c=2 and W1]-hard for any ca parts per thousand yen3. Finding a minimum s-t separator with diameter at most d is W1]-hard for any da parts per thousand yen2. Finding a minimum r-regular s-t separator is W1]-hard for any ra parts per thousand yen1. For any decidable graph property, finding a minimum s-t separator with this property is FPT parameterized jointly by the size of the separator and the maximum degree. Finding a connected s-t separator of minimum size does not have a polynomial kernel, even when restricted to graphs of maximum degree at most 3, unless .

Peculiar morphological transitions induced by nanoparticles in polymeric blends: retarded relaxation or altered interfacial tension?

Nanoparticles of different shapes can induce peculiar morphologies in binary polymer blends depending on their position. It is envisaged that the increased yield stress of the filled phase slows down the relaxation resulting in arresting the peculiar morphologies which otherwise is thermodynamically unfavourable due to the increased interfacial area. This essentially means that the highly irregular structures can be preserved even without altering the interfacial tension between the phases! On the other hand, in the case of interfacially adsorbed particles, the resulting solid-like interface can also preserve the irregular structures. These phenomenal transitions in filled blends are very different from the classical copolymer compatibilized polymer blends. Moreover, these irregular structures can further pave way in designing conducting polymer blends involving conducting nanoparticles and revisiting our understanding of the concept of double percolation!

Morphological and functional characterisation of the burrow systems of six earthworm species (Lumbricidae)

Earthworm burrow systems are generally described based on postulated behaviours associated with the three ecological types. In this study, we used X-ray tomography to obtain 3D information on the burrowing behaviour of six very common anecic (Aporrectodea nocturna and Lumbricus terrestris) and endogeic (Aporrectodea rosea, Allolobophora chlorotica, Aporrectodea caliginosa, Aporrectodea icterica) earthworm species, introduced into repacked soil cores for 6 weeks. A simple water infiltration test, the Beerkan method, was also used to assess some functional properties of these burrow systems. Endogeic worms make larger burrow systems, which are more highly branched, less continuous and of smaller diameter, than those of anecic worms. Among the anecic species, L. terrestris burrow systems are shorter (9.2 vs 21.2 m) with a higher number (14.5 vs 23.5) of less branched burrows (12.2 vs 20.2 branches m(-1)), which are also wider (7.78 vs 5.16 mm) than those of A. nocturna. In comparison, the burrow systems made by endogeic species appeared similar to each other. However, A. rosea burrows were short and narrow, whereas A. icterica had a longer burrow system (15.7 m), more intense bioturbation intensity (refilled macropores or soil lateral compaction around them) and thus a greater number of burrows. Regarding water infiltration, anecic burrow systems were far more efficient due to open burrows linking the top and bottom of the cores. For endogeic species, we observed a linear relationship between burrow length and the water infiltration rate (R (2) = 0.49, p < 0.01). Overall, the three main characteristics significantly influencing water infiltration were burrow length, burrow number and bioturbation volume. This last characteristic highlighted the effect of burrow refilling by casts.

Efficient Low Complexity Power Allocation Policies for Wireless Communication Systems Guaranteeing QoS

We consider near-optimal policies for a single user transmitting on a wireless channel which minimize average queue length under average power constraint. The power is consumed in transmission of data only. We consider the case when the power used in transmission is a linear function of the data transmitted. The transmission channel may experience multipath fading. Later, we also extend these results to the multiuser case. We show that our policies can be used in a system with energy harvesting sources at the transmitter. Next we consider data users which require minimum rate guarantees. Finally we consider the system which has both data and real time users. Our policies have low computational complexity, closed form expression for mean delays and require only the mean arrival rate with no queue length information.

Kernelization complexity of possible winner and coalitional manipulation problems in voting

In the POSSIBLE WINNER problem in computational social choice theory, we are given a set of partial preferences and the question is whether a distinguished candidate could be made winner by extending the partial preferences to linear preferences. Previous work has provided, for many common voting rules, fixed parameter tractable algorithms for the POSSIBLE WINNER problem, with number of candidates as the parameter. However, the corresponding kernelization question is still open and in fact, has been mentioned as a key research challenge 10]. In this paper, we settle this open question for many common voting rules. We show that the POSSIBLE WINNER problem for maximin, Copeland, Bucklin, ranked pairs, and a class of scoring rules that includes the Borda voting rule does not admit a polynomial kernel with the number of candidates as the parameter. We show however that the COALITIONAL MANIPULATION problem which is an important special case of the POSSIBLE WINNER problem does admit a polynomial kernel for maximin, Copeland, ranked pairs, and a class of scoring rules that includes the Borda voting rule, when the number of manipulators is polynomial in the number of candidates. A significant conclusion of our work is that the POSSIBLE WINNER problem is harder than the COALITIONAL MANIPULATION problem since the COALITIONAL MANIPULATION problem admits a polynomial kernel whereas the POSSIBLE WINNER problem does not admit a polynomial kernel. (C) 2015 Elsevier B.V. All rights reserved.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.