A unified view of the apriori-based algorithms for frequent episode discovery

Frequent episode discovery framework is a popular framework in temporal data mining with many applications. Over the years, many different notions of frequencies of episodes have been proposed along with different algorithms for episode discovery. In this paper, we present a unified view of all the apriori-based discovery methods for serial episodes under these different notions of frequencies. Specifically, we present a unified view of the various frequency counting algorithms. We propose a generic counting algorithm such that all current algorithms are special cases of it. This unified view allows one to gain insights into different frequencies, and we present quantitative relationships among different frequencies. Our unified view also helps in obtaining correctness proofs for various counting algorithms as we show here. It also aids in understanding and obtaining the anti-monotonicity properties satisfied by the various frequencies, the properties exploited by the candidate generation step of any apriori-based method. We also point out how our unified view of counting helps to consider generalization of the algorithm to count episodes with general partial orders.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Dependence of Protein Adsorption on Wetting Behavior of UHMWPE-HA-Al2O3-CNT Hybrid Biocomposites

Ultrahigh-molecular-weight polyethylene (UHMWPE) is used as an articulating surface in total hip and knee joint replacement. In order to enhance long-term durability/wear resistance properties, UHMWPE-based polymer-ceramic hybrid composites are being developed. Surface properties such as wettability and protein adsorption alter with reinforcement or with change in surface chemistry. From this perspective, the wettability and protein adsorption behavior of compression-molded UHMWPE-hydroxyapatite (HA)-aluminum oxide (Al2O3)-carbon nanotube (CNT) composites were analyzed in conjunction with surface roughness. The combined effect of Al2O3 and CNT shows enhancement of the contact angle by similar to 37A degrees compared with the surface of the UHMWPE matrix reinforced with HA. In reference to unreinforced UHMWPE, protein adsorption density also increased by similar to 230% for 2 wt.%HA-5 wt.%Al2O3-2 wt.%CNT addition to UHMWPE. An important conclusion is that the polar and dispersion components of the surface free energy play a significant role in wetting and protein adsorption than do the total free energy or chemistry of the surface. The results of this study have major implications for the biocompatibility of these newly developed biocomposites.

Ag@AgI, Core@Shell Structure in Agarose Matrix as Hybrid: Synthesis, Characterization, and Antimicrobial Activity

A novel in situ core@shell structure consisting of nanoparticles of Ag (Ag Nps) and AgI in agarose matrix (Ag@ AgI/agarose) has been synthesized as a hybrid, in order to have an efficient antibacterial agent for repetitive usage with no toxicity. The synthesized core@shell structure is very well characterized by XRD, UV-visible, photoluminescence, and TEM. A detailed antibacterial studies including repetitive cycles are carried out on Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus) bacteria in saline water, both in dark and on exposure to visible light. The hybrid could be recycled for the antibacterial activity and is nontoxic toward human cervical cancer cells (HeLa cells). The water insoluble Ag@AgI in agarose matrix forms a good coating on quartz, having good mechanical strength. EPR and TEM studies are carried out on the Ag@AgI/agarose and the bacteria, respectively, to elucidate a possible mechanism for killing of the bacteria.

Tunable device properties of free-standing inorganic/organic flexible hybrid structures obtained by exfoliation

We report the fabrication of free-standing flexible inorganic/organic hybrid structures by exfoliating ZnO nanostructured films from the flat indium tin oxide (ITO)/silicon/sapphire substrates using poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS). Strong interaction between ZnO and PEDOT: PSS and the thermomechanical response of PEDOT: PSS are the key issues for the exfoliation to prevail. The performance of the free-standing hybrid structures as rectifiers and photodetectors is better as compared to ITO supported hybrid structures. It is also shown that device properties of hybrid structures can be tuned by using different electrode materials. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4729550]

beta-Turn Analogues in Model a ss-Hybrid Peptides: Structural Characterization of Peptides Containing ss 2,2Ac6c and ss 3,3Ac6c Residues

The effect of gem-dialkyl substituents on the backbone conformations of beta-amino acid residues in peptides has been investigated by using four model peptides: Boc-Xxx-beta 2,2Ac6c(1-aminomethylcyclohexanecarboxylic acid)-NHMe (Xxx=Leu (1), Phe (2); Boc=tert-butyloxycarbonyl) and Boc-Xxx-beta 3,3Ac6c(1-aminocyclohexaneacetic acid)-NHMe (Xxx=Leu (3), Phe (4)). Tetrasubstituted carbon atoms restrict the ranges of stereochemically allowed conformations about flanking single bonds. The crystal structure of Boc-Leu-beta 2,2Ac6c-NHMe (1) established a C11 hydrogen-bonded turn in the a beta-hybrid sequence. The observed torsion angles (a(similar to-60 degrees, similar to-30 degrees), beta(similar to-90 degrees, similar to 60 degrees, similar to-90 degrees)) corresponded to a C11 helical turn, which was a backbone-expanded analogue of the type III beta turn in aa sequences. The crystal structure of the peptide Boc-Phe-beta 3,3Ac6c-NHMe (4) established a C11 hydrogen-bonded turn with distinctly different backbone torsion angles (a(similar to-60 degrees, similar to 120 degrees), beta(similar to 60 degrees, ?60 degrees, similar to-60 degrees)), which corresponded to a backbone-expanded analogue of the type II beta turn observed in aa sequences. In peptide 4, the two molecules in the asymmetric unit adopted backbone torsion angles of opposite signs. In one of the molecules, the Phe residue adopted an unfavorable backbone conformation, with the energetic penalty being offset by a favorable aromatic interaction between proximal molecules in the crystal. NMR spectroscopy studies provided evidence for the maintenance of folded structures in solution in these a beta-hybrid sequences.

Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography

We have developed an efficient fully three-dimensional (3D) reconstruction algorithm for diffuse optical tomography (DOT). The 3D DOT, a severely ill-posed problem, is tackled through a pseudodynamic (PD) approach wherein an ordinary differential equation representing the evolution of the solution on pseudotime is integrated that bypasses an explicit inversion of the associated, ill-conditioned system matrix. One of the most computationally expensive parts of the iterative DOT algorithm, the reevaluation of the Jacobian in each of the iterations, is avoided by using the adjoint-Broyden update formula to provide low rank updates to the Jacobian. In addition, wherever feasible, we have also made the algorithm efficient by integrating along the quadratic path provided by the perturbation equation containing the Hessian. These algorithms are then proven by reconstruction, using simulated and experimental data and verifying the PD results with those from the popular Gauss-Newton scheme. The major findings of this work are as follows: (i) the PD reconstructions are comparatively artifact free, providing superior absorption coefficient maps in terms of quantitative accuracy and contrast recovery; (ii) the scaling of computation time with the dimension of the measurement set is much less steep with the Jacobian update formula in place than without it; and (iii) an increase in the data dimension, even though it renders the reconstruction problem less ill conditioned and thus provides relatively artifact-free reconstructions, does not necessarily provide better contrast property recovery. For the latter, one should also take care to uniformly distribute the measurement points, avoiding regions close to the source so that the relative strength of the derivatives for measurements away from the source does not become insignificant. (c) 2012 Optical Society of America

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Structural characterization of backbone-expanded helices in hybrid peptides: (αγ) n and (αβ) n sequences with unconstrained β and γ homologues of L-Val

Learning your αβγ's: The diversity of hydrogen-bonding patterns in backbone-expanded hybrid helices is shown by crystal-structure determination of several oligomeric peptides (see scheme; C=gray; H=white; O=red; N=blue). C 12 helices were observed in the αγ peptide series for n=2-8. In comparison, the αα peptide and αβ peptide sequences show C 10 and mixed C 14/C 15 helices, respectively. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

Substrate integrated Lead-Carbon hybrid ultracapacitor with flooded, absorbent glass mat and silica-gel electrolyte configurations

Lead-Carbon hybrid ultracapacitors (Pb-C HUCs) with flooded, absorbent-glass-mat (AGM) and silica-gel sulphuric acid electrolyte configurations are developed and performance tested. Pb-C HUCs comprise substrate-integrated PbO2 (SI-PbO2) as positive electrodes and high surface-area carbon with graphite-sheet substrate as negative electrodes. The electrode and silica-gel electrolyte materials are characterized by XRD, XPS, SEM, TEM, Rheometry, BET surface area, and FTIR spectroscopy in conjunction with electrochemistry. Electrochemical performance of SI-PbO2 and carbon electrodes is studied using cyclic voltammetry with constant-current charge and discharge techniques by assembling symmetric electrical-double-layer capacitors and hybrid Pb-C HUCs with a dynamic Pb(porous)/PbSO4 reference electrode. The specific capacitance values for 2 V Pb-C HUCs are found to be 166 F/g, 102 F/g and 152 F/g with a faradaic efficiency of 98%, 92% and 88% for flooded, AGM and gel configurations, respectively.

Hydrothermal synthesis of a monoclinic VO2 nanotube-graphene hybrid for use as cathode material in lithium ion batteries

The hydrothermal reaction of a mixture of a colloidal dispersion of graphite oxide and ammonium vanadate yielded a hybrid made of graphene and a nanotubular metastable monoclinic polymorph of VO2, known as VO2(B). The formation of VO2(B) nanotubes is accompanied by the reduction of graphite oxide. Initially the partially scrolled graphite oxide layers act as templates for the crystallization of VO2(B) in the tubular morphology. This is followed by the reduction of graphite oxide to graphene resulting in a hybrid in which VO2(B) nanotubes are dispersed in graphene. Electron microscopic studies of the hybrid reveal that the VO2(B) nanotubes are wrapped by and trapped between graphene sheets. The hybrid shows potential to be a high capacity cathode material for lithium ion batteries. It exhibits a high capacity (similar to 450 mAh/g) and cycling stability. The high capacity of the hybrid is attributed to the interaction between the graphene sheets and the VO2(B) tubes which improves the charge-transfer. The graphene matrix prevents the aggregation of the VO2(B) nanotubes leading to high cycling stability. (C) 2012 Elsevier Ltd. All rights reserved.