Large-Scale Elastic Net Regularized Linear Classification SVMs and Logistic Regression

Elastic Net Regularizers have shown much promise in designing sparse classifiers for linear classification. In this work, we propose an alternating optimization approach to solve the dual problems of elastic net regularized linear classification Support Vector Machines (SVMs) and logistic regression (LR). One of the sub-problems turns out to be a simple projection. The other sub-problem can be solved using dual coordinate descent methods developed for non-sparse L2-regularized linear SVMs and LR, without altering their iteration complexity and convergence properties. Experiments on very large datasets indicate that the proposed dual coordinate descent - projection (DCD-P) methods are fast and achieve comparable generalization performance after the first pass through the data, with extremely sparse models.

CONVERGENCE ANALYSIS OF THE LOWEST ORDER WEAKLY PENALIZED ADAPTIVE DISCONTINUOUS GALERKIN METHODS

In this article, we prove convergence of the weakly penalized adaptive discontinuous Galerkin methods. Unlike other works, we derive the contraction property for various discontinuous Galerkin methods only assuming the stabilizing parameters are large enough to stabilize the method. A central idea in the analysis is to construct an auxiliary solution from the discontinuous Galerkin solution by a simple post processing. Based on the auxiliary solution, we define the adaptive algorithm which guides to the convergence of adaptive discontinuous Galerkin methods.

Optimal Trajectory Generation for Convergence to a Rectilinear Path

This paper presents a strategy to determine the shortest path of a fixed-wing Miniature Air Vehicle (MAV), constrained by a bounded turning rate, to eventually fly along a given straight line, starting from an arbitrary but known initial position and orientation. Unlike the work available in the literature that solves the problem using the Pontryagin's Minimum Principle (PMP) the trajectory generation algorithm presented here considers a geometrical approach which is intuitive and easy to understand. This also computes the explicit solution for the length of the optimal path as a function of the initial configuration. Further, using a 6-DOF model of a MAV the generated optimal path is tracked by an autopilot consisting of proportional-integral-derivative (PID) controllers. The simulation results show the path generation and tracking for different cases.

Fabrication of large-area PbSe films at the organic-aqueous interface and their near-infrared photoresponse

An organic-aqueous interfacial reaction at room temperature has been employed to synthesize large-area self-assembled films consisting of PbSe single crystallites. The use of the films for the low-cost fabrication of IR-photodetectors has been explored. (111)-oriented single crystallites of PbSe self-assemble to form robust large-area films. The near-infrared photoresponse of the film measured at room temperature showed large responsivity and gain owing to trap-associated mechanisms. Low-cost, mild reaction conditions and tunability of the nature of deposits make the present strategy useful for synthesizing large-area films of functional materials for possible opto-electronic applications.

Strategy for Enhancing the Dielectric Constant of Organic Semiconductors Without Sacrificing Charge Carrier Mobility and Solubility

Current organic semiconductors for organic photovoltaics (OPV) have relative dielectric constants (relative permittivities, epsilon(r)) in the range of 2-4. As a consequence, Coulombically bound electron-hole pairs (excitons) are produced upon absorption of light, giving rise to limited power conversion efficiencies. We introduce a strategy to enhance epsilon(r) of well-known donors and acceptors without breaking conjugation, degrading charge carrier mobility or altering the transport gap. The ability of ethylene glycol (EG) repeating units to rapidly reorient their dipoles with the charge redistributions in the environment was proven via density functional theory (DFT) calculations. Fullerene derivatives functionalized with triethylene glycol side chains were studied for the enhancement of epsilon(r) together with poly(p-phenylene vinylene) and diketo-pyrrolopyrrole based polymers functionalized with similar side chains. The polymers showed a doubling of epsilon(r) with respect to their reference polymers in identical backbone. Fullerene derivatives presented enhancements up to 6 compared with phenyl-C-61-butyric acid methyl ester (PCBM) as the reference. Importantly, the applied modifications did not affect the mobility of electrons and holes and provided excellent solubility in common organic solvents.

Breeding in bamboo: a novel anuran reproductive strategy discovered in Rhacophorid frogs of the Western Ghats, India

Amphibians exhibit extraordinarily diverse sets of reproductive strategies among vertebrates. Understanding life history strategies in an evolutionary framework is lacking for many amphibian species in the tropics. Here, we report a novel reproductive mode where adult frogs enter hollow internodes of bamboo via a small opening, deposit direct developing eggs, and provide parental care. This behaviour is observed in two species of the frog genus Raorchestes. The first description of this unique life history and details of nest site characteristics and embryo development are provided along with ecological comparisons. Evolution of novel reproductive modes and parental care are discussed in context of natural selection. Dearth of natural history information on amphibians in the Western Ghats and much of the South-East Asian region is highlighted with suggestions for further studies.(c) 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 114, 1-11.

Room Temperature Growth of Ultrathin Au Nanowires with High Areal Density over Large Areas by in Situ Functionalization of Substrate

Although ultrathin Au nanowires (similar to 2 nm diameter) are expected to demonstrate several interesting properties, their extreme fragility has hampered their use in potential applications. One way to improve the stability is to grow them on substrates; however, there is no general method to grow these wires over large areas. The existing methods suffer from poor coverage and associated formation of larger nanoparticles on the substrate. Herein, we demonstrate a room temperature method for growth of these nanowires with high coverage over large areas by in situ functionalization of the substrate. Using control experiments, we demonstrate that an in situ functionalization of the substrate is the key step in controlling the areal density of the wires on the substrate. We show that this strategy works for a variety of substrates ranging like graphene, borosil glass, Kapton, and oxide supports. We present initial results on catalysis using the wires grown on alumina and silica beads and also extend the method to lithography-free device fabrication. This method is general and may be extended to grow ultrathin Au nanowires on a variety of substrates for other applications.

Effects of large-scale deforestation on precipitation in the monsoon regions: Remote versus local effects

In this paper, using idealized climate model simulations, we investigate the biogeophysical effects of large-scale deforestation on monsoon regions. We find that the remote forcing from large-scale deforestation in the northern middle and high latitudes shifts the Intertropical Convergence Zone southward. This results in a significant decrease in precipitation in the Northern Hemisphere monsoon regions (East Asia, North America, North Africa, and South Asia) and moderate precipitation increases in the Southern Hemisphere monsoon regions (South Africa, South America, and Australia). The magnitude of the monsoonal precipitation changes depends on the location of deforestation, with remote effects showing a larger influence than local effects. The South Asian Monsoon region is affected the most, with 18% decline in precipitation over India. Our results indicate that any comprehensive assessment of afforestation/reforestation as climate change mitigation strategies should carefully evaluate the remote effects on monsoonal precipitation alongside the large local impacts on temperatures.

Bayesian parameter identification in dynamic state space models using modified measurement equations

When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Fault Tolerance on Large Scale Systems using Adaptive Process Replication

Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. At such low MTBFs, employing periodic checkpointing alone will result in low efficiency because of the high number of application failures resulting in large amount of lost work due to rollbacks. In such scenarios, it is highly necessary to have proactive fault tolerance mechanisms that can help avoid significant number of failures. In this work, we have developed a mechanism for proactive fault tolerance using partial replication of a set of application processes. Our fault tolerance framework adaptively changes the set of replicated processes periodically based on failure predictions to avoid failures. We have developed an MPI prototype implementation, PAREP-MPI that allows changing the replica set. We have shown that our strategy involving adaptive process replication significantly outperforms existing mechanisms providing up to 20 percent improvement in application efficiency even for exascale systems.

Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems

Generalized spatial modulation (GSM) uses n(t) transmit antenna elements but fewer transmit radio frequency (RF) chains, n(rf). Spatial modulation (SM) and spatial multiplexing are special cases of GSM with n(rf) = 1 and n(rf) = n(t), respectively. In GSM, in addition to conveying information bits through n(rf) conventional modulation symbols (for example, QAM), the indices of the n(rf) active transmit antennas also convey information bits. In this paper, we investigate GSM for large-scale multiuser MIMO communications on the uplink. Our contributions in this paper include: 1) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and 2) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR). The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of 10(-3). Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.

REPERTOIRE OF PROTEIN KINASES ENCODED IN THE GENOME OF ZEBRAFISH SHOWS REMARKABLY LARGE POPULATION OF PIM KINASES

In recent times, zebrafish has garnered lot of popularity as model organism to study human cancers. Despite high evolutionary divergence from humans, zebrafish develops almost all types of human tumors when induced. However, mechanistic details of tumor formation have remained largely unknown. Present study is aimed at analysis of repertoire of kinases in zebrafish proteome to provide insights into various cellular components. Annotation using highly sensitive remote homology detection methods revealed ``substantial expansion'' of Ser/Thr/Tyr kinase family in zebrafish compared to humans, constituting over 3% of proteome. Subsequent classification of kinases into subfamilies revealed presence of large number of CAMK group of kinases, with massive representation of PIM kinases, important for cell cycle regulation and growth. Extensive sequence comparison between human and zebrafish PIM kinases revealed high conservation of functionally important residues with a few organism specific variations. There are about 300 PIM kinases in zebrafish kinome, while human genome codes for only about 500 kinases altogether. PIM kinases have been implicated in various human cancers and are currently being targeted to explore their therapeutic potentials. Hence, in depth analysis of PIM kinases in zebrafish has opened up new avenues of research to verify the model organism status of zebrafish.

Impact Time Guidance for Large Heading Errors Using Sliding Mode Control

In this paper, sliding mode control-based impact time guidance laws are proposed. Even for large heading angle errors and negative initial closing speeds, the desired impact time is achieved by enforcing a sliding mode on a switching surface designed by using the concepts of collision course and estimated time-to-go. Unlike existing guidance laws, the proposed guidance strategy achieves impact time successfully even when the estimated interception time is greater than the desired impact time. Simulation results are also presented.

Stabilization of a Tetrahedral (Mn5+O4) Chromophore in Ternary Barium Oxides as a Strategy toward Development of New Turquoise/Green-Colored Pigments

An experimental investigation of the stabilization of the turquoise-colored chrornophore (Mn5+O4) in various oxide hosts, viz., A(3)(VO4)(2) (A = Ba, Sr, Ca), YVO4, and Ba2MO4 (M = Ti, Si), has been carried out. The results reveal that substitution of Mn5+O4 occurs in Ba-3(VO4)(2) forming the entire solid solution series Ba-3(V1-x MnxO4)(2) (0 < x <= 1.0), while with the corresponding strontium derivative, only up to about 10% of Mn5+O4 substitution is possible. Ca-3(VO4)(2) and YVO4 do not stabilize Mn5+O4 at all. With Ba2MO4 (M = Ti, Si), we could prepare only partially substituted materials, Ba2M1-xMn5+O4+x/2 for x up to 0.15, that are turquoise-colored. We rationalize the results that a large stabilization of the O 2p-valence band states occurs in the presence of the electropositive barium that renders the Mn5+ oxidation state accessible in oxoanion compounds containing PO43-, VO43-, etc. By way of proof-of-concept, we synthesized new turquoise-colored Mn5+O4 materials, Ba-5(BO3)(MnO4)(2)Cl and Ba-5(BO3)(PO4)(MnO4)Cl, based on the apatite-Ba-5(PO4)(3)Cl-structure.