Buffer losses vs. deadline violations for ABR traffic in an ATM switch: A computational approach

The B‐ISDN will carry a variety of traffic types: the Variable Bit Rate traffic (VBR), of which compressed video is an example, Continuous Bit Rate traffic (CBR), of which telemetry is an example, Data traffic, and Available Bit Rate traffic (ABR) that represents aggregate data traffic with very limited guarantees on quality. Of these, VBR and CBR have timing constraints and need synchronous bandwidth; data traffic is relatively delay insensitive. In this paper, we consider the VBR, Data and ABR traffic types and obtain the cumulative distribution function (cdf) of the queueing delay experienced by a burst of ABR traffic in the output buffer of an ATM switch. The cdf is used to trade off buffer loss probabilities against deadline violation probabilities through adjusting the buffer size and (delay) deadline values. Large buffers result in low losses but queueing delays can become excessive and cause a high level of deadline violations. Both losses and violations are detrimental and an operating point must be chosen to achieve a balance. In this paper we study the nature of the trade off. We develop a stochastic Petri net model assuming periodic burst arrivals for VBR and Poisson arrival processes for the Data and ABR traffic types at the burst level, and solve the model analytically (numerically) using a decomposition approach. This decomposition, along with the inherent decomposability of the tagged customer approach for obtaining the cdf opens up a possibility of carrying out fast computations using a parallel machine for selecting the operating point each time that a call is admitted. This revised version was published online in June 2006 with corrections to the Cover Date.     

Assessment of the validity of maturity metrics for predicting the volatile composition of Concord grape juice

Total soluble solids (TSS) are typically used as the sole metric for maturity of Concord grapes. However, the reliability of TSS in predicting the aroma composition of finished juice for grapes sourced from multiple sites has not been investigated. This study sought to determine the validity of TSS in predicting the aroma composition of the juice while also investigating other potentially useful indicators, including pH, titratable acidity (TA), and TSS:TA ratio. Grapes were harvested from 9 sites in the Lake Erie Concord Grape Belt and stratified from north to south and east to west. The key aroma compounds methyl anthranilate ("grapey") and trans-2-hexenal ("herbaceous") were quantified along with several other odorants. It was observed that while TSS was a robust predictor of monomeric anthocyanin content across sites, it was a poor predictor of aroma compounds in the finished juice. Conversely, pH, TA, and TSS:TA ratio were all significantly correlated with methyl anthranilate and trans-2-hexenal concentrations (P < 0.05) in samples equal to or exceeding 15 Brix, the industry minimum for grape maturity. These results indicate that parameters related to acidity are better predictors of aroma composition than TSS, which may aid in efforts to minimize herbaceous off-aromas and optimize the aroma composition of the finished juice.     

A novel classifier for multivariate instance using graph class signatures

Applications like identifying different customers from their unique buying behaviours, determining ratingsof a product given by users based on different sets of features, etc. require classification using class-specific subsets of features. Most of the existing state-of-the-art classifiers for multivariate data use complete feature set for classification regardless of the different class labels. Decision tree classifier can produce class-wise subsets of features. However, none of these classifiers model the relationship between features which may enhance classification accuracy. We call the class-specific subsets of features and the features’ interrelationships as class signatures. In this work, we propose to map the original input space of multivariate data to the feature space characterized by connected graphs as graphs can easily model entities, their attributes, and relationships among attributes. Mostly, entities are modeled using graphs, where graphs occur naturally, for example, chemical compounds. However, graphs do not occur naturally in multivariate data. Thus, extracting class signatures from multivariate data is a challenging task. We propose some feature selection heuristics to obtain class-specific prominent subgraph signatures. We also propose two variants of class signatures based classifier namely: 1) maximum matching signature (gMM), and 2) score and size of matched signatures (gSM). The effectiveness of the proposed approach on real-world and synthetic datasets has been studied and compared with other established classifiers. Experimental results confirm the ascendancy of the proposed class signatures based classifier on most of the datasets.     

Transthoracic Ventricular Defibrillation in the Dog with Truncated and Untruncated Exponential Stimuli

From 10 560 transthoracic fibrillation-defibrillation episodes in large anesthetized dogs, the effectiveness of 88 types of untruncated and truncated exponential waveforms in reversing ventricular fibrillation was evaluated. The study involved waveforms which could be generated with stored energy levels (in the simple capacitor-switch sense) of 60, 90, 120, and 180 J and initial current levels of 10, 20, 30, 40, 60, 80, and 100 A. The 10-A waveforms were untruncated or truncated at final current values of 5, 7.5, and 9 A. The 20-, 30-, and 40-A waveforms were untruncated or truncated at 5, 10, and 15 A. The 60-, 80-, and l00-A waveforms were untruncated or truncated at the 15-A level.     

Gum arabic as a phytochemical construct for the stabilization of gold nanoparticles: in vivo pharmacokinetics and X-ray-contrast-imaging studies

Gold nanoparticles (AuNPs) have exceptional stability against oxidation and therefore will play a significant role in the advancement of clinically useful diagnostic and therapeutic nanomedicines. Despite the huge potential for a new generation of AuNP-based nanomedicinal products, nontoxic AuNP constructs and formulations that can be readily administered site-specifically through the intravenous mode, for diagnostic imaging by computed tomography (CT) or for therapy via various modalities, are still rare. Herein, we report results encompassing: 1) the synthesis and stabilization of AuNPs within the nontoxic phytochemical gum-arabic matrix (GA-AuNPs); 2) detailed in vitro analysis and in vivo pharmacokinetics studies of GA-AuNPs in pigs to gain insight into the organ-specific localization of this new generation of AuNP vector, and 3) X-ray CT contrast measurements of GA-AuNP vectors for potential utility in molecular imaging. Our results demonstrate that naturally occurring GA can be used as a nontoxic phytochemical construct in the production of readily administrable biocompatible AuNPs for diagnostic and therapeutic applications in nanomedicine.     

Effect of organoclay on the gas barrier properties of natural rubber nanocomposites

Natural rubber nanocomposites have been prepared with organically modified montmorillonite clay. The nanocomposites have been characterized by X‐ray diffractometry and transmission electron microscopy. The gas‐barrier properties of the nanocomposites have been studied for three different gases viz., oxygen, nitrogen, and CO₂ gases. The natural rubber–organoclay composites exhibit outstanding gas‐barrier properties compared to the neat rubber. Various models have been applied to predict the decrease in permeability in nanocomposites. All other models except Bharadwaj model give low values of calculated aspect ratio. Dynamic mechanical analysis has been carried out to investigate the role of the constrained region on the permeability of the nanocomposites. The permeability decrease of the organoclay nanocomposites is found to have good qualitative correlation with the volume of the constrained region. POLYM. COMPOS.,, 2012. © 2012 Society of Plastics Engineers     

Preparation and characterisation of Tl2Pu(MoO4)3 and Tl4Pu(MoO4)4 in Tl-Pu-Mo-O system by X-ray and thermal methods

The quaternary Tl-Pu-Mo-O system was investigated for the first time and two new quaternary compounds Tl₂Pu(MoO₄)₃ and Tl₄Pu(MoO₄)₄ were synthesized by solid state reactions of Tl₂MoO₄ with Pu(MoO₄)₂ in 1:1 and 2:1 molar proportions at 773 K and 823 K, respectively. X-ray powder diffraction data of these compounds were indexed on orthorhombic system. Thermogravimetric (TG) curves of Tl₂Pu(MoO₄)₃ and Tl₄Pu(MoO₄)₄ were recorded in air and no significant weight changes were observed up to 973 K and 1033 K, respectively. Differential thermal analysis (DTA) curves of Tl₂Pu(MoO₄)₃ and Tl₄Pu(MoO₄)₄ showed endothermic peaks due to the melting of the compounds at 838 K and 1013 K, respectively. Non-isothermal kinetics of decomposition of Tl₂Pu(MoO₄)₃ and Tl₄Pu(MoO₄)₄ in air was studied using thermogravimetric technique. Tl₂Pu(MoO₄)₃ and Tl₄Pu(MoO₄)₄ when heated up to 1673 K decomposed to Tl₂O and MoO₃ in the gaseous form, giving solid PuO₂ as an end product. The reactions followed unimolecular nucleation and growth mechanism with activation energies of 106 kJ/mol and 157 kJ/mol, respectively.     

Thermal expansion studies on Th(MoO4)2, Na2Th(MoO4)3 and Na4Th(MoO4)4

Thermal expansion behavior of Th(MoO₄)₂, Na₂Th(MoO₄)₃ and Na₄Th(MoO₄)₄ was studied under vacuum in the temperature range of 298–1123 K by high temperature X-ray diffractometer. Th(MoO₄)₂ was synthesized by reacting ThO₂ with 2 mol of MoO₃, at 1073 K in air and Na₂Th(MoO₄)₃ and Na₄Th(MoO₄)₄ were prepared by reacting Th(MoO₄)₂ with 1 and 2 mol of Na₂MoO₄, respectively at 873 K in air. The XRD data of Th(MoO₄)₂ was indexed on orthorhombic system where as XRD data of Na₂Th(MoO₄)₃ and Na₄Th(MoO₄)₄ were indexed on tetragonal system. The lattice parameters and cell volume of all the three compounds, fit into polynomial expression with respect to temperature, showed positive thermal expansion (PTE) up to 1123 K. The average value of thermal expansion coefficients for Th(MoO₄)₂, Na₂Th(MoO₄)₃ and Na₄Th(MoO₄)₄ were determined from the high temperature data.