Performability Analysis of Fork-Join Queueing Systems

Fork-join queueing systems offer a natural modelling paradigm for parallel processing systems and for assembly operations in automated manufacturing. The analysis of fork-join queueing systems has been an important subject of research in recent years. Existing analysis methodologies-both exact and approximate-assume that the servers are failure-free. In this study, we consider fork-join queueing systems in the presence of server failures and compute the cumulative distribution of performability with respect to the response time of such systems. For this, we employ a computational methodology that uses a recent technique based on randomization. We compare the performability of three different fork-join queueing models proposed in the literature: the distributed model, the centralized splitting model, and the split-merge model. The numerical results show that the centralized splitting model offers the highest levels of performability, followed by the distributed splitting and split-merge models.

Potential herblayer production and grazing effects in anthropogenic savanna-grasslands in the moist tropical forests of the Western Ghats of India

The moist tropical forests of the Western Ghats of India are pockmarked with savanna-grasslands created and managed by local agricultural communities. A sample of such savanna-grasslands with differing growing conditions was studied in terms of peak above-ground biomass, monthly growth, and cumulative production under different clipping treatments. The herblayer was found to be dominated by perennial C4 grasses, with Eulalia trispicata, Arundinella metzii and Themeda triandra being common to all sites. Peak biomass ranged between 3.3-5.9 t/ha at sites most favourable for grass production. Across these sites, peak biomass was found to be inversely related to the number of rainy days during the growing season, suggesting that growth may be light-limited. This hypothesis is supported by the observation that growth is most rapid immediately after the easing of the monsoon. Single clips early in the growing season had no negative or a slightly positive effect on production, but mid-season single clips or continuous frequent clipping reduced production by as much as 40%. The results suggest that, while indiscriminate grazing may certainly be deleterious, it is possible to obtain sustained high yields from forest lands managed for grass production without totally excluding grazing.

Stochastic dynamics modeling of the protein sequence length distribution in genomes: implications for microbial evolution

In this paper, we report an analysis of the protein sequence length distribution for 13 bacteria, four archaea and one eukaryote whose genomes have been completely sequenced, The frequency distribution of protein sequence length for all the 18 organisms are remarkably similar, independent of genome size and can be described in terms of a lognormal probability distribution function. A simple stochastic model based on multiplicative processes has been proposed to explain the sequence length distribution. The stochastic model supports the random-origin hypothesis of protein sequences in genomes. Distributions of large proteins deviate from the overall lognormal behavior. Their cumulative distribution follows a power-law analogous to Pareto's law used to describe the income distribution of the wealthy. The protein sequence length distribution in genomes of organisms has important implications for microbial evolution and applications. (C) 1999 Elsevier Science B.V. All rights reserved.

Lamb wave based identification and parameter estimation of corrosion in metallic plate structure using a circular PWAS array

A circular array of Piezoelectric Wafer Active Sensor (PWAS) has been employed to detect surface damages like corrosion using lamb waves. The array consists of a number of small PWASs of 10 mm diameter and 1 mm thickness. The advantage of a circular array is its compact arrangement and large area of coverage for monitoring with small area of physical access. Growth of corrosion is monitored in a laboratory-scale set-up using the PWAS array and the nature of reflected and transmitted Lamb wave patterns due to corrosion is investigated. The wavelet time-frequency maps of the sensor signals are employed and a damage index is plotted against the damage parameters and varying frequency of the actuation signal (a windowed sine signal). The variation of wavelet coefficient for different growth of corrosion is studied. Wavelet coefficient as function of time gives an insight into the effect of corrosion in time-frequency scale. We present here a method to eliminate the time scale effect which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the corrosion with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed for varying damage sizes and the results appear promising.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Ultrasonic Lamb wave based monitoring of corrosion type of damage in plate using a circular array of piezoelectric transducers

In this paper we propose a concept and report experimental results based on a circular array of Piezoelectric Wafer Active Sensors (PWASs) for rapid localization and parametric identification of corrosion type damage in metallic plates. Implementation of this circular array of PWASs combines the use of ultrasonic Lamb wave propagation technique and an algorithm based on symmetry breaking in the signal pattern to locate and monitor the growth of a corrosion pit on a metallic plate. Wavelet time-frequency maps of the sensor signals are employed to obtain an insight regarding the effect of corrosion growth on the Lamb wave transmission in time-frequency scale. We present here a method to eliminate the time scale, which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the damage with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed from the wavelet coefficients for varying damage sizes and the results appear promising. Damage index is plotted against the damage parameters for frequency sweep of the excitation signal (a windowed sine signal). Results of corrosion damage are compared with circular holes of various sizes to demonstrate the applicability of present method to different types of damage. (C) 2011 Elsevier Ltd. All rights reserved.

Modulation of Catalytic Activity in Multi-Domain Protein Tyrosine Phosphatases

Signaling mechanisms involving protein tyrosine phosphatases govern several cellular and developmental processes. These enzymes are regulated by several mechanisms which include variation in the catalytic turnover rate based on redox stimuli, subcellular localization or protein-protein interactions. In the case of Receptor Protein Tyrosine Phosphatases (RPTPs) containing two PTP domains, phosphatase activity is localized in their membrane-proximal (D1) domains, while the membrane-distal (D2) domain is believed to play a modulatory role. Here we report our analysis of the influence of the D2 domain on the catalytic activity and substrate specificity of the D1 domain using two Drosophila melanogaster RPTPs as a model system. Biochemical studies reveal contrasting roles for the D2 domain of Drosophila Leukocyte antigen Related (DLAR) and Protein Tyrosine Phosphatase on Drosophila chromosome band 99A (PTP99A). While D2 lowers the catalytic activity of the D1 domain in DLAR, the D2 domain of PTP99A leads to an increase in the catalytic activity of its D1 domain. Substrate specificity, on the other hand, is cumulative, whereby the individual specificities of the D1 and D2 domains contribute to the substrate specificity of these two-domain enzymes. Molecular dynamics simulations on structural models of DLAR and PTP99A reveal a conformational rationale for the experimental observations. These studies reveal that concerted structural changes mediate inter-domain communication resulting in either inhibitory or activating effects of the membrane distal PTP domain on the catalytic activity of the membrane proximal PTP domain.

Novel auditory motivated subband temporal envelope based fundamental frequency estimation algorithm

We address the problem of estimating the fundamental frequency of voiced speech. We present a novel solution motivated by the importance of amplitude modulation in sound processing and speech perception. The new algorithm is based on a cumulative spectrum computed from the temporal envelope of various subbands. We provide theoretical analysis to derive the new pitch estimator based on the temporal envelope of the bandpass speech signal. We report extensive experimental performance for synthetic as well as natural vowels for both realworld noisy and noise-free data. Experimental results show that the new technique performs accurate pitch estimation and is robust to noise. We also show that the technique is superior to the autocorrelation technique for pitch estimation.

V(2)O(5)-Anchored Carbon Nanotubes for Enhanced Electrochemical Energy Storage

Functionalized multiwalled carbon nanotubes (CNTs) are coated with a 4-5 nm thin layer of V(2)O(5) by controlled hydrolysis of vanadium alkoxide. The resulting V(2)O(5)/CNT composite has been investigated for electrochemical activity with lithium ion, and the capacity value shows both faradaic and capacitive (nonfaradaic) contributions. At high rate (1 C), the capacitive behavior dominates the intercalation as 2/3 of the overall capacity value out of 2700 C/g is capacitive, while the remaining is due to Li-ion intercalation. These numbers are in agreement with the Trasatti plots and are corroborated by X-ray photoelectron spectroscopy (XPS) studies on the V(2)O(5)/CNTs electrode, which show 85% of vanadium in the +4 oxidation state after the discharge at 1 C rate. The cumulative high-capacity value is attributed to the unique property of the nano V(2)O(5)/CNTs composite, which provides a short diffusion path for Lit-ions and an easy access to vanadium redox centers besides the high conductivity of CNTs. The composite architecture exhibits both high power density and high energy density, stressing the benefits of using carbon substrates to design high performance supercapacitor electrodes.

Fracture analysis of concrete using singular fractal functions with lattice beam network and confirmation with acoustic emission study

In the present study singular fractal functions (SFF) were used to generate stress-strain plots for quasibrittle material like concrete and cement mortar and subsequently stress-strain plot of cement mortar obtained using SFF was used for modeling fracture process in concrete. The fracture surface of concrete is rough and irregular. The fracture surface of concrete is affected by the concrete's microstructure that is influenced by water cement ratio, grade of cement and type of aggregate 11-41. Also the macrostructural properties such as the size and shape of the specimen, the initial notch length and the rate of loading contribute to the shape of the fracture surface of concrete. It is known that concrete is a heterogeneous and quasi-brittle material containing micro-defects and its mechanical properties strongly relate to the presence of micro-pores and micro-cracks in concrete 11-41. The damage in concrete is believed to be mainly due to initiation and development of micro-defects with irregularity and fractal characteristics. However, repeated observations at various magnifications also reveal a variety of additional structures that fall between the `micro' and the `macro' and have not yet been described satisfactorily in a systematic manner [1-11,15-17]. The concept of singular fractal functions by Mosolov was used to generate stress-strain plot of cement concrete, cement mortar and subsequently the stress-strain plot of cement mortar was used in two-dimensional lattice model [28]. A two-dimensional lattice model was used to study concrete fracture by considering softening of matrix (cement mortar). The results obtained from simulations with lattice model show softening behavior of concrete and fairly agrees with the experimental results. The number of fractured elements are compared with the acoustic emission (AE) hits. The trend in the cumulative fractured beam elements in the lattice fracture simulation reasonably reflected the trend in the recorded AE measurements. In other words, the pattern in which AE hits were distributed around the notch has the same trend as that of the fractured elements around the notch which is in support of lattice model. (C) 2011 Elsevier Ltd. All rights reserved.

Studies on hydrogen-bonds .4. proposed working criteria for assessing qualitative strength of hydrogen-bonds

The data obtained in the earlier parts of this series for the donor and acceptor end parameters of N-H. O and O-H. O hydrogen bonds have been utilised to obtain a qualitative working criterion to classify the hydrogen bonds into three categories: “very good” (VG), “moderately good” (MG) and weak (W). The general distribution curves for all the four parameters are found to be nearly of the Gaussian type. Assuming that the VG hydrogen bonds lie between 0 and ± la, MG hydrogen bonds between ± 1s̀ and ± 2s̀, W hydrogen bonds beyond ± 2s̀ (where s̀ is the standard deviation), suitable cut-off limits for classifying the hydrogen bonds in the three categories have been derived. These limits are used to get VG and MG ranges for the four parameters 1 and θ (at the donor end) and ± and ± (at the acceptor end). The qualitative strength of a hydrogen bond is decided by the cumulative application of the criteria to all the four parameters. The criterion has been further applied to some practical examples in conformational studies such as α-helix and can be used for obtaining suitable location of hydrogen atoms to form good hydrogen bonds. An empirical approach to the energy of hydrogen bonds in the three categories has also been presented.

Minor mergers and their impact on the kinematics of old and young stellar populations in disk galaxies

By means of N-body simulations we investigate the impact of minor mergers on the angular momentum and dynamical properties of the merger remnant. Our simulations cover a range of initial orbital characteristics and gas-to-stellar mass fractions (from 0 to 20%), and include star formation and supernova feedback. We confirm and extend previous results by showing that the specific angular momentum of the stellar component always decreases independently of the orbital parameters or morphology of the satellite, and that the decrease in the rotation velocity of the primary galaxy is accompanied by a change in the anisotropy of the orbits. However, the decrease affects only the old stellar population, and not the new population formed from gas during the merging process. This means that the merging process induces an increasing difference in the rotational support of the old and young stellar components, with the old one lagging with respect to the new. Even if our models are not intended specifically to reproduce the Milky Way and its accretion history, we find that, under certain conditions, the modeled rotational lag found is compatible with that observed in the Milky Way disk, thus indicating that minor mergers can be a viable way to produce it. The lag can increase with the vertical distance from the disk midplane, but only if the satellite is accreted along a direct orbit, and in all cases the main contribution to the lag comes from stars originally in the primary disk rather than from stars in the satellite galaxy. We also discuss the possibility of creating counter-rotating stars in the remnant disk, their fraction as a function of the vertical distance from the galaxy midplane, and the cumulative effect of multiple mergers on their creation.

Investigation of biodegradable and biocompatible castor oil poly(mannitol-citric-sebacate) polyester as a drug carrier

Castor oil-based poly(mannitol-citric sebacate) was synthesized by simple, catalyst-free melt condensation process using monomers having potential to be metabolized in vivo. The polymer was characterized using various techniques and the tensile and hydration properties of the polymers were also determined. The biocompatibility of the polymer was tested using human foreskin fibroblasts cells. The in vitro degradation studies show that the time for complete degradation of the polymer was more than 21 days. The usage of castor oil polyester as a drug carrier was analysed by doping the polymer with 5-fluorouracil model drug and the release rate was studied by varying the percentage loading of drugs and the pH of the PBS solution medium. The cumulative drug-release profiles exhibited a biphasic release with an initial burst release and cumulative 100% release within 42 h. To understand the role of the polymer as a drug carrier in the release behaviour, drug-release studies were conducted with another drug, isoniazid. The release behaviour of isoniazid drug from the same polymer matrix followed an nth order kinetic model and 100% cumulative release was achieved after 12 days. The variation in the release behaviour for two model drugs from the same polymer matrix suggests a strong interaction between the polymer and the drug molecule.

Prototype learning methods for online handwriting recognition

In this paper, we study different methods for prototype selection for recognizing handwritten characters of Tamil script. In the first method, cumulative pairwise- distances of the training samples of a given class are used to select prototypes. In the second method, cumulative distance to allographs of different orientation is used as a criterion to decide if the sample is representative of the group. The latter method is presumed to offset the possible orientation effect. This method still uses fixed number of prototypes for each of the classes. Finally, a prototype set growing algorithm is proposed, with a view to better model the differences in complexity of different character classes. The proposed algorithms are tested and compared for both writer independent and writer adaptation scenarios.

Influence fields: a quantitative framework for representation and analysis of active dendrites

Rathour RK, Narayanan R. Influence fields: a quantitative framework for representation and analysis of active dendrites. J Neurophysiol 107: 2313-2334, 2012. First published January 18, 2012; doi:10.1152/jn.00846.2011.-Neuronal dendrites express numerous voltage-gated ion channels (VGICs), typically with spatial gradients in their densities and properties. Dendritic VGICs, their gradients, and their plasticity endow neurons with information processing capabilities that are higher than those of neurons with passive dendrites. Despite this, frameworks that incorporate dendritic VGICs and their plasticity into neurophysiological and learning theory models have been far and few. Here, we develop a generalized quantitative framework to analyze the extent of influence of a spatially localized VGIC conductance on different physiological properties along the entire stretch of a neuron. Employing this framework, we show that the extent of influence of a VGIC conductance is largely independent of the conductance magnitude but is heavily dependent on the specific physiological property and background conductances. Morphologically, our analyses demonstrate that the influences of different VGIC conductances located on an oblique dendrite are confined within that oblique dendrite, thus providing further credence to the postulate that dendritic branches act as independent computational units. Furthermore, distinguishing between active and passive propagation of signals within a neuron, we demonstrate that the influence of a VGIC conductance is spatially confined only when propagation is active. Finally, we reconstruct functional gradients from VGIC conductance gradients using influence fields and demonstrate that the cumulative contribution of VGIC conductances in adjacent compartments plays a critical role in determining physiological properties at a given location. We suggest that our framework provides a quantitative basis for unraveling the roles of dendritic VGICs and their plasticity in neural coding, learning, and homeostasis.