30 resultados para Network System

em University of Queensland eSpace - Australia


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The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.

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Currently, wireless technology is revolutionizing the way we share information and communicate. The demands for mobility have made wireless technology the primary source for voice communication. Code-division multiple-access (CDMA) is a very popular spread spectrum application due to its claims of low transmission power, higher system capacity, ability to mitigate multipath fading and user interference. In that case, frequency-hopping code-division multiple access (FH-CDMA) has received considerable attention over the past few years. This technique will allow a better performance over a fading channel, message privacy, and immunity to narrowband interference. This paper addresses the characteristics of FH-CDMA in WPAN networks, with an emphasis on frequency-hopped Bluetooth systems. A performance evaluation of FH-CDMA is discussed and simulated. The analysis shows the interaction between the designed parameters and their effect on the network system. Most specifically, the FH-CDMA scheme provides frequency and temporal diversity to combat the effects of interference.

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Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.

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Mechanically skinned skeletal muscle fibres from rat and toad were exposed to the permeabilizing agents beta-escin and saponin. The effects of these agents on the sealed transverse tubular system (t-system) and sarcoplasmic reticulum (SR) were examined by looking at changes in the magnitude of the force responses to t-system depolarization, the time course of the fluorescence of fura-2 trapped in the sealed t-system, and changes in the magnitude of caffeine-induced contractures following SR loading with Ca2+ under defined conditions. In the presence of 2 mu g ml(-1) beta-escin and saponin, the response to t-system depolarization was not completely abolished, decreasing to a plateau, and a large proportion of fura-2 remained in the sealed t-system. At 10 mu g ml(-1), both agents abolished the ability of both rat and toad preparations to respond to t-system depolarization after 3 min of exposure, but a significant amount of fura-2 remained in sealed t-tubules even after exposure to 100 mu g ml(-1) beta-escin and saponin for 10 min. beta-Escin took longer than saponin to reduce the t-system depolarizations and fura-2 content of the sealed t-system to a similar level. The ability of the SR to load Ca2+ was reduced to a lower level after treatment with beta-escin than saponin. This direct effect on the SR occurred at much lower concentrations for rat (2 mu g ml(-1) beta-escin and 10 mu g ml(-1) saponin) than toad (10 mu g ml(-1) beta-escin and 150 mu g ml(-1) saponin). The reverse order in sensitivities to beta-escin and saponin of t-system and SR membranes indicates that the mechanisms of action of beta-escin and saponin are different in the two types of membrane. In conclusion, this study shows that: (1) beta-escin has a milder action on the surface membrane than saponin; (2) beta-escin is a more potent modifier of SR function; (3) simple permeabilization of membranes is not sufficient to explain the effects of beta-escin and saponin on muscle membranes; and (4) the t-system network within muscle fibres is not a homogeneous compartment.

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In primates, the observation of meaningful, goaldirected actions engages a network of cortical areas located within the premotor and inferior parietal lobules. Current models suggest that activity within these regions arises relatively automatically during passive action observation without the need for topdown control. Here we used functional magnetic resonance imaging to determine whether cortical activit)' associated with action observation is modulated by the strategic allocation of selective attention. Normal observers viewed movie clips of reach-to-grasp actions while performing an easy or difficult visual discrimination at the fovea. A wholebrain analysis was performed to determine the effects of attentional load on neural responses to observed hand actions. Our results suggest that cortical areas involved in action observation are significantiy modulated by attentional load. These findings have important implications for recent attempts to link the human action-observation system to response properties of "mirror neurons" in monkeys.

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Mental rotation involves the creation and manipulation of internal images, with the later being particularly useful cognitive capacities when applied to high-level mathematical thinking and reasoning. Many neuroimaging studies have demonstrated mental rotation to be mediated primarily by the parietal lobes, particularly on the right side. Here, we use fMRI to show for the first time that when performing 3-dimensional mental rotations, mathematically gifted male adolescents engage a qualitatively different brain network than those of average math ability, one that involves bilateral activation of the parietal lobes and frontal cortex, along with heightened activation of the anterior cingulate. Reliance on the processing characteristics of this uniquely bilateral system and the interplay of these anterior/posterior regions may be contributors to their mathematical precocity.

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Individuals with Autism Spectrum Disorder (ASD) are generally thought to have impaired attentional and executive function upon which all their cognitive and behaviour functions are based. Mental Rotation is a recognized visuo-spatial task, involving spatial working memory, known to involve activation in the fronto-parietal networks. To elucidate the functioning of fronto-parietal networks in ASD, the aim of this study was to use fMRI techniques with a mental rotation task, to characterize the underlying functional neural system. Sixteen male participants (seven highfunctioning autism or Asperger's syndrome; nine ageand performance IQ-matched controls) underwent fMRI. Participants were presented with 18 baseline and 18 rotation trials, with stimuli rotated 3- dimensionaUy (45°-180°). Data were acquired on a 3- Tesla scanner. The most widely accepted area reported to be involved in processing of visuo-spatial information. Posterior Parietal Cortex, was found to be activated in both groups, however, the ASD group showed decreased activation in cortical and subcortical frontal structures that are highly interconnected, including lateral and medial Brodmann area 6, frontal eye fields, caudate, dorsolateral prefrontal cortex and anterior cingulate. The suggested connectivity between these regions indicates that one or more circuits are impaired as a result of the disorder. In future it is hoped that we are able to identify the possible point of origin of this dysfunction, or indeed if the entire network is dysfunctional.

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FILTER is an innovative, CSIRO developed system for treating effluent using high rate land application and subsequent effluent recapture via a closely spaced, subsurface drainage network. We report on the summer performance of a FILTER system established in a subtropical environment on a relatively impermeable swelling clay soil underlain by a deep regional water table. Using secondary treated sewage effluent, the FILTER system produced effluent of tertiary nutrient standards (less than or equal to5 mg/L TN; less than or equal to1 mg/L TP), with salinity levels suitable for subsequent irrigation reuse (EC less than or equal to2.5 dS/m). Removal of faecal coliforms was considerably less effective. The hydraulic loading rate achieved was about two and a half times larger than conventional irrigation demand, but this was associated with high deep percolation losses (e 3 mm/day). Comparisons are made with the original FILTER system developed and tested by Jayawardane et al. in temperate Australia. Suggestions are made for modifications to, and further testing of FILTER in a subtropical environment.

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Complex chemical reactions in the gas phase can be decomposed into a network of elementary (e.g., unimolecular and bimolecular) steps which may involve multiple reactant channels, multiple intermediates, and multiple products. The modeling of such reactions involves describing the molecular species and their transformation by reaction at a detailed level. Here we focus on a detailed modeling of the C(P-3)+allene (C3H4) reaction, for which molecular beam experiments and theoretical calculations have previously been performed. In our previous calculations, product branching ratios for a nonrotating isomerizing unimolecular system were predicted. We extend the previous calculations to predict absolute unimolecular rate coefficients and branching ratios using microcanonical variational transition state theory (mu-VTST) with full energy and angular momentum resolution. Our calculation of the initial capture rate is facilitated by systematic ab initio potential energy surface calculations that describe the interaction potential between carbon and allene as a function of the angle of attack. Furthermore, the chemical kinetic scheme is enhanced to explicitly treat the entrance channels in terms of a predicted overall input flux and also to allow for the possibility of redissociation via the entrance channels. Thus, the computation of total bimolecular reaction rates and partial capture rates is now possible. (C) 2002 American Institute of Physics.

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Insulin stimulates glucose transport in fat and muscle cells by triggering exocytosis of the glucose transporter GLUT4. To define the intracellular trafficking of GLUT4, we have studied the internalization of an epitope-tagged version of GLUT4 from the cell surface. GLUT4 rapidly traversed the endosomal system en route to a perinuclear location. This perinuclear GLUT4 compartment did not colocalize with endosomal markers (endosomal antigen I protein, transferrin) or TGN38, but showed significant overlap with the TGN target (t)-soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) Syntaxins 6 and 16. These results were confirmed by vesicle immunoisolation. Consistent with a role for Syntaxins 6 and 16 in GLUT4 trafficking we found that their expression was up-regulated significantly during adipocyte differentiation and insulin stimulated their movement to the cell surface. GLUT4 trafficking between endosomes and trans-Golgi network was regulated via an acidic targeting motif in the carboxy terminus of GLUT4, because a mutant lacking this motif was retained in endosomes. We conclude that GLUT4 is rapidly transported from the cell surface to a subdomain of the trans-Golgi network that is enriched in the t-SNAREs Syntaxins 6 and 16 and that an acidic targeting motif in the C-terminal tail of GLUT4 plays an important role in this process.

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The paper presents a computational system based upon formal principles to run spatial models for environmental processes. The simulator is named SimuMap because it is typically used to simulate spatial processes over a mapped representation of terrain. A model is formally represented in SimuMap as a set of coupled sub-models. The paper considers the situation where spatial processes operate at different time levels, but are still integrated. An example of such a situation commonly occurs in watershed hydrology where overland flow and stream channel flow have very different flow rates but are highly related as they are subject to the same terrain runoff processes. SimuMap is able to run a network of sub-models that express different time-space derivatives for water flow processes. Sub-models may be coded generically with a map algebra programming language that uses a surface data model. To address the problem of differing time levels in simulation, the paper: (i) reviews general approaches for numerical solvers, (ii) considers the constraints that need to be enforced to use more adaptive time steps in discrete time specified simulations, and (iii) scaling transfer rates in equations that use different time bases for time-space derivatives. A multistep scheme is proposed for SimuMap. This is presented along with a description of its visual programming interface, its modelling formalisms and future plans. (C) 2003 Elsevier Ltd. All rights reserved.

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A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

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One of the great challenges in biology is to understand how particular complex morphological and physiological characters originated in specific evolutionary lineages. In this article, we address the origin of the vertebrate hypothalamic-pituitary-peripheral gland (H-P-PG) endocrine system, a complex network of specialized tissues, ligands and receptors. Analysis of metazoan nucleotide and protein sequences reveals a patchwork pattern of H-P-PG gene conservation between vertebrates and closely related invertebrates (ascidians). This is consistent with a model of how the vertebrate H-P-PG endocrine system could have emerged in relatively few steps by gene family expansion and by regulatory and structural modifications to genes that are present in a chordate ancestor. Some of these changes might have resulted in new connections between metabolic or signaling pathways, such as the bridging of 'synthesis islands' to form an efficient system for steroid hormone synthesis.

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The phase equilibria in the Fe-Zn-O system in the range 900-1580degreesC in air have been experimentally studied using equilibration and quenching techniques. The compositions of the phases at equilibrium were determined using electron probe X-ray microanalysis (EPMA). The ferrous and ferric bulk iron concentrations were measured with a wet chemical analysis using the ammonium metavanadate technique. X-ray powder diffraction analysis (XRD) was used to characterise the phases. Iron oxide dissolved in zincite was found to be present principally in the ferric form. The XRD analysis and the composition measurements both indicate that zincite is the only phase stable in the ZnO-rich area in the range of conditions investigated. The solubility of the iron oxide in zincite rapidly increases at temperatures above 1200degreesC; the morphology of the zincite crystals also sharply changes between 1200 and 1300degreesC from rounded to plate-like crystals. The plate-like zincite forms a refractory network-the type of microstructure beneficial to the Imperial Smelting Process (ISP) sinter performance. The software program FactSage with a thermodynamically optimised database was used to predict phase equilibria in the Fe-Zn-O system.