934 resultados para Random Scission
Resumo:
The mechano-chemical degradation of poly(methyl methacrylate) (PMMA), poly(ethyl methacrylate) (PEMA) and poly(n-butyl methacrylate) (PBMA) using ultrasound (US), ultraviolet (UV) radiation and a photoinitiator (benzoin) has been investigated. The degradation of the polymers was monitored using the reduction in number average molecular weight (M-n) and polydispersity (PDI). A degradation mechanism that included the decomposition of the initiator, generation of polymer radicals by the hydrogen abstraction of initiator radicals, reversible chain transfer between stable polymer and polymer radicals was proposed. The mechanism assumed mid-point chain scission due to US and random scission due to UV radiation. A series of experiments with different initial M-n of the polymers were performed and the results indicated that, irrespective of the initial PDI, the PDI during the sono-photooxidative degradation evolved to a steady state value of 1.6 +/- 0.05 for all the polymers. This steady state evolution of PDI was successfully predicted by the continuous distribution kinetics model. The rate coefficients of polymer scission due to US and UV exhibited a linear increase and decrease with the size of the alkyl group of the poly(alkyl methacrylate)s, respectively. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The thermal degradation of high density polyethylene has been modelled by the random breakage of polymer bonds, using a set of population balance equations. A model was proposed in which the population balances were lumped into representative sizes so that the experimentally determined molecular weight distribution of the original polymer could be used as the initial condition. This model was then compared to two different cases of the unlumped population balance which assumed unimolecular initial distributions of 100 and 500 monomer units, respectively. The model that utilised the experimentally determined molecular weight distribution was found to best describe the experimental data. The model fits suggested a second mechanism in addition to random breakage at slow reaction rates. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
Channel measurements and simulations have been carried out to observe the effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity. An in-house built MIMO-OFDM packet transmission demonstrator equipped with four transmitters and four receivers has been utilized to perform channel measurements at 5.2 GHz. Variations in the channel capacity dynamic range have been analysed for 1 to 10 pedestrians and different antenna arrays (2 × 2, 3 × 3 and 4 × 4). Results show a predicted 5.5 bits/s/Hz and a measured 1.5 bits/s/Hz increment in the capacity dynamic range with the number of pedestrian and the number of antennas in the transmitter and receiver array.
Resumo:
Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.
Resumo:
In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.
Resumo:
This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.
Resumo:
In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.
Resumo:
Quantitative studies of nascent entrepreneurs such as GEM and PSED are required to generate their samples by screening the adult population, usually by phone in developed economies. Phone survey research has recently been challenged by shifting patterns of ownership and response rates of landline versus mobile (cell) phones, particularly for younger respondents. This challenge is acutely intense for entrepreneurship which is a strongly age-dependent phenomenon. Although shifting ownership rates have received some attention, shifting response rates have remained largely unexplored. For the Australian GEM 2010 adult population study we conducted a dual-frame approach that allows comparison between samples of mobile and landline phones. We find a substantial response bias towards younger, male and metropolitan respondents for mobile phones – far greater than explained by ownership rates. We also found these response rate differences significantly biases the estimates of the prevalence of early stage entrepreneurship by both samples, even when each sample is weighted to match the Australian population.