Network Simulations (network + simulation)

Distribution by Scientific Domains

Kinds of Network Simulations

  • neural network simulation

  • Selected Abstracts

    Thermodynamic study of capillary pressure curves based on free energy minimization

    GEOFLUIDS (ELECTRONIC), Issue 3 2001
    Y. Deng
    Abstract This paper presents a new method for pore level network simulation of the distribution of two immiscible phases in a permeable medium. The method requires that the Helmholtz free energy of the system , the medium and the two phases contained within the pore space , be a minimum at all saturation states. We describe the method here and show some typical results from a computer algorithm that implements it. The results include (i) an explanation of the ,scanning' behaviour of capillary pressure curves based wholly on the free energy minimization, (ii) predictions of capillary pressure at arbitrary wetting states, including negative capillary pressures, and (iii) illustrations of how the minimized free energy changes along the scanning curves. The method also predicts the known dependency of the capillary pressure on the pore size distribution and interfacial tension. The current work is restricted to two-dimensional networks, but the free energy minimization appears to be generalizable to three dimensions and to more than two fluid phases. Moreover, functions generated through the minimization, specifically contact areas between the medium surface and the phases, appear to have applications predicting other multiphase petrophysical properties. [source]

    A functional hypothesis for adult hippocampal neurogenesis: Avoidance of catastrophic interference in the dentate gyrus

    HIPPOCAMPUS, Issue 3 2006
    Laurenz Wiskott
    Abstract The dentate gyrus is part of the hippocampal memory system and special in that it generates new neurons throughout life. Here we discuss the question of what the functional role of these new neurons might be. Our hypothesis is that they help the dentate gyrus to avoid the problem of catastrophic interference when adapting to new environments. We assume that old neurons are rather stable and preserve an optimal encoding learned for known environments while new neurons are plastic to adapt to those features that are qualitatively new in a new environment. A simple network simulation demonstrates that adding new plastic neurons is indeed a successful strategy for adaptation without catastrophic interference. © 2006 Wiley-Liss, Inc. [source]

    A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips

    P. Földesy
    This paper describes procedures to build custom-tailored behavioural models of cellular neural networks (CNNs), and acompanion tool to run these models. The main property of the CNNs is the emerging behaviour, i.e. new phenomena arise from the interactions of thousands of identical cells. The existence of these phenomena need is to be checked during the design phase, which requires a full network simulation and therefore constitutes a very time-consuming step of circuit verification. To solve this task as a modelling problem, we introduce a new behavioural model optimization technique. Starting from a user-defined set of block models, the proposed framework produces an optimized selection which is used to build up a full-chip model. The optimization goal is the minimization of the simulation CPU time and the maximization of the time domain precision. A dedicated environment has been developed for efficient numerical simulation; this environment is briefly described in the paper. Two case studies are also presented to demonstrate the effectivity of the technique. Copyright © 2002 John Wiley & Sons, Ltd. [source]

    Development, characterisation and 1000 Suns outdoor tests of GaAs monolithic interconnected module (MIM) receivers

    R. Loeckenhoff
    Abstract Monolithic interconnected modules (MIMs) are large area, high voltage PV devices which perform well at very high light intensities. They are therefore well suited for the assembly of dense array receivers. The latter can be employed in solar concentrator systems such as parabolic dishes at a concentration ratio of 1000 Suns or more. This paper reports on progress in the development and testing of GaAs MIMs and of water-cooled dense array receivers assembled from MIMs. The MIMs are electrically protected by integrated bypass diodes and, under indoor laboratory tests, reach an efficiency of 20·0% at 1000 Suns and 22·9% at 200 Suns. Several dense array receivers have been assembled, one of which was tested outdoors at 1-Sun and at concentration ratios of several hundred Suns and up to slightly above 1000 Suns using the PETAL solar dish facility in Sede Boqer, Israel. In addition to I,V curve measurements, the high-concentration tests included measurements that quantified the light intensity distribution over the dense array. Deformations in some of the I,V plots were observed for intensity distributions that departed substantially from perfect uniformity. The shapes of these plots were successfully reproduced by an electronic network simulation of the inhomogeneously illuminated receiver. 1-Sun I,V curve measurements and visual inspections performed before and after exposure of the module to concentrated sunlight revealed no indications of degradation. Copyright © 2007 John Wiley & Sons, Ltd. [source]

    Prediction of biodegradation from the atom-type electrotopological state indices

    Jarmo Huuskonen
    Abstract A group contribution method based on atom-type electrotopological state indices for predicting the biodegradation of a diverse set of 241 organic chemicals is presented. Multiple linear regression and artificial neural networks were used to build the models using a training set of 172 compounds, for which the approximate time for ultimate biodegradation was estimated from the results of a survey of an expert panel. Derived models were validated by using a leave-25%-out method and against two test sets of 12 and 57 chemicals not included in the training set. The squared correlation coefficient (r2) for a linear model with 15 structural parameters was 0.76 for the training set and 0.68 for the test set of 12 molecules. The model predicted correctly the biodegradation of 48 chemicals in the test set of 57 molecules, for which biodegradability was presented as rapid or slow. The use of artificial neural networks gave better prediction for both test sets when the same set of parameters was tested as inputs in neural network simulations. The predictions of rapidly biodegradable chemicals were more accurate than the predictions of slowly bio-degradable chemicals for both the regression and neural network models. [source]

    A Possible Role for Gap Junctions in Generation of Very Fast EEG Oscillations Preceding the Onset of, and Perhaps Initiating, Seizures

    EPILEPSIA, Issue 2 2001
    Roger D. Traub
    Summary: ,Purpose: We propose an experimentally and clinically testable hypothesis, concerning the origin of very fast (>,70 Hz) EEG oscillations that sometimes precede the onset of focal seizures. These oscillations are important, as they may play a causal role in the initiation of seizures. Methods: Subdural EEG recordings were obtained from children with focal cortical dysplasias and intractable seizures. Intra- and extracellular recordings were performed in rat hippocampal slices, with induction of population activity, as follows: (a) bath-applied tetramethylamine (an intracellular alkalinizing agent, that opens gap junctions); (b) bath-applied carbachol, a cholinergic agonist; and (c) focal pressure ejection of hypertonic K+ solution. Detailed network simulations were performed, the better to understand the cellular mechanisms underlying oscillations. A major feature of the simulations was inclusion of axon,axon gap junctions between principal neurons, as supported by recent experimental data. Results: Very fast oscillations were found in children before seizure onset, but also superimposed on bursts during the seizure, and on interictal bursts. In slice experiments, very fast oscillations had previously been seen on interictal-like bursts; we now show such oscillations before, between, and after epileptiform bursts. Very fast oscillations were also seen superimposed on gamma (30,70 Hz) oscillations induced by carbachol or hypertonic K+, and in the latter case, very fast oscillations became continuous when chemical synapses were blocked. Simulations replicate these data, when axonal gap junctions are included. Conclusions: Electrical coupling between principal neurons, perhaps via axonal gap junctions, could underlie very fast population oscillations, in seizure-prone brain, but possibly also in normal brain. The anticonvulsant potential of gap-junction blockers such as carbenoxolone, now in clinical use for treatment of ulcer disease, should be considered. [source]

    Energy Group optimization for forward and inverse problems in nuclear engineering: application to downwell-logging problems

    Elsa Aristodemou
    ABSTRACT Simulating radiation transport of neutral particles (neutrons and ,-ray photons) within subsurface formations has been an area of research in the nuclear well-logging community since the 1960s, with many researchers exploiting existing computational tools already available within the nuclear reactor community. Deterministic codes became a popular tool, with the radiation transport equation being solved using a discretization of phase-space of the problem (energy, angle, space and time). The energy discretization in such codes is based on the multigroup approximation, or equivalently the discrete finite-difference energy approximation. One of the uncertainties, therefore, of simulating radiation transport problems, has become the multigroup energy structure. The nuclear reactor community has tackled the problem by optimizing existing nuclear cross-sectional libraries using a variety of group-collapsing codes, whilst the nuclear well-logging community has relied, until now, on libraries used in the nuclear reactor community. However, although the utilization of such libraries has been extremely useful in the past, it has also become clear that a larger number of energy groups were available than was necessary for the well-logging problems. It was obvious, therefore, that a multigroup energy structure specific to the needs of the nuclear well-logging community needed to be established. This would have the benefit of reducing computational time (the ultimate aim of this work) for both the stochastic and deterministic calculations since computational time increases with the number of energy groups. We, therefore, present in this study two methodologies that enable the optimization of any multigroup neutron,, energy structure. Although we test our theoretical approaches on nuclear well-logging synthetic data, the methodologies can be applied to other radiation transport problems that use the multigroup energy approximation. The first approach considers the effect of collapsing the neutron groups by solving the forward transport problem directly using the deterministic code EVENT, and obtaining neutron and ,-ray fluxes deterministically for the different group-collapsing options. The best collapsing option is chosen as the one which minimizes the effect on the ,-ray spectrum. During this methodology, parallel processing is implemented to reduce computational times. The second approach uses the uncollapsed output from neural network simulations in order to estimate the new, collapsed fluxes for the different collapsing cases. Subsequently, an inversion technique is used which calculates the properties of the subsurface, based on the collapsed fluxes. The best collapsing option is chosen as the one that predicts the subsurface properties with a minimal error. The fundamental difference between the two methodologies relates to their effect on the generated ,-rays. The first methodology takes the generation of ,-rays fully into account by solving the transport equation directly. The second methodology assumes that the reduction of the neutron groups has no effect on the ,-ray fluxes. It does, however, utilize an inversion scheme to predict the subsurface properties reliably, and it looks at the effect of collapsing the neutron groups on these predictions. Although the second procedure is favoured because of (a) the speed with which a solution can be obtained and (b) the application of an inversion scheme, its results need to be validated against a physically more stringent methodology. A comparison of the two methodologies is therefore given. [source]

    Computational constraints between retrieving the past and predicting the future, and the CA3-CA1 differentiation

    HIPPOCAMPUS, Issue 5 2004
    Alessandro Treves
    Abstract The differentiation between the CA3 and CA1 fields of the mammalian hippocampus is one of the salient traits that set it apart from the organization of the homologue medial wall in reptiles and birds. CA3 is widely thought to function as an autoassociator, but what do we need CA1 for? Based on evidence for a specific role of CA1 in temporal processing, I have explored the hypothesis that the differentiation between CA3 and CA1 may help solve a computational conflict. The conflict is between pattern completion, or integrating current sensory information on the basis of memory, and prediction, or moving from one pattern to the next in a stored sequence. CA3 would take care of the former, while CA1 would concentrate on the latter. I have found the hypothesis to be only weakly supported by neural network simulations. The conflict indeed exists, but two mechanisms that would relate more directly to a functional CA3-CA1 differentiation were found unable to produce genuine prediction. Instead, a simple mechanism based on firing frequency adaptation in pyramidal cells was found to be sufficient for prediction, with the degree of adaptation as the crucial parameter balancing retrieval with prediction. The differentiation between the architectures of CA3 and CA1 has a minor but significant, and positive, effect on this balance. In particular, for a fixed anticipatory interval in the model, it increases significantly the information content of hippocampal outputs. There may therefore be just a simple quantitative advantage in differentiating the connectivity of the two fields. Moreover, different degrees of adaptation in CA3 and CA1 cells were not found to lead to better performance, further undermining the notion of a functional dissociation. © 2004 Wiley-Liss, Inc. [source]

    An Empirical and Computational Investigation of Perceiving and Remembering Event Temporal Relations

    Shulan Lu
    Abstract Events have beginnings, ends, and often overlap in time. A major question is how perceivers come to parse a stream of multimodal information into meaningful units and how different event boundaries may vary event processing. This work investigates the roles of these three types of event boundaries in constructing event temporal relations. Predictions were made based on how people would err according to the beginning state, end state, and overlap heuristic hypotheses. Participants viewed animated events that include all the logical possibilities of event temporal relations, and then made temporal relation judgments. The results showed that people make use of the overlap between events and take into account the ends and beginnings, but they weight ends more than beginnings. Neural network simulations showed a self-organized distinction when learning temporal relations between events with overlap versus those without. [source]