69 resultados para NETWORK MODEL


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Two prospective controllers of hand movements in catching-both based on required velocity control-were simulated. Under certain conditions, this required velocity control led to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint model. Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.

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In a multiagent system where norms are used to regulate the actions agents ought to execute, some agents may decide not to abide by the norms if this can benefit them. Norm enforcement mechanisms are designed to counteract these benefits and thus the motives for not abiding by the norms. In this work we propose a distributed mechanism through which agents in the multiagent system that do not abide by the norms can be ostracised by their peers. An ostracised agent cannot interact anymore and looses all benefits from future interactions. We describe a model for multiagent systems structured as networks of agents, and a behavioural model for the agents in such systems. Furthermore, we provide analytical results which show that there exists an upper bound to the number of potential norm violations when all the agents exhibit certain behaviours. We also provide experimental results showing that both stricter enforcement behaviours and larger percentage of agents exhibiting these behaviours reduce the number of norm violations, and that the network topology influences the number of norm violations. These experiments have been executed under varying scenarios with different values for the number of agents, percentage of enforcers, percentage of violators, network topology, and agent behaviours. Finally, we give examples of applications where the enforcement techniques we provide could be used.

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This paper describes a data model for content representation of temporal media in an IP based sensor network. The model is formed by introducing the idea of semantic-role from linguistics into the underlying concepts of formal event representation with the aim of developing a common event model. The architecture of a prototype system for a multi camera surveillance system, based on the proposed model is described. The important aspects of the proposed model are its expressiveness, its ability to model content of temporal media, and its suitability for use with a natural language interface. It also provides a platform for temporal information fusion, as well as organizing sensor annotations by help of ontologies.

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Introduction: Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8).

Aims: In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany).

Results: We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies.

Conclusion: Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far.

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This paper addresses the problem of optimally locating intermodal freight terminals in Serbia. To solve this problem and determine the effects of the resulting scenarios, two modeling approaches were combined. The first approach is based on multiple-assignment hub-network design, and the second is based on simulation. The multiple-assignment p-hub network location model was used to determine the optimal location of intermodal terminals. Simulation was used as a tool to estimate intermodal transport flow volumes, due to the unreliability and unavailability of specific statistical data, and as a method for quantitatively analyzing the economic, time, and environmental effects of different scenarios of intermodal terminal development. The results presented here represent a summary, with some extension, of the research realized in the IMOD-X project (Intermodal Solutions for Competitive Transport in Serbia).

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This paper contributes to and expands on the Nakagami-m phase model. It derives exact, closed-form expressions for both the phase cumulative distribution function and its inverse. In addition, empirical first- and second-order statistics obtained from measurements conducted in a body-area network scenario were used to fit the phase probability density function, the phase cumulative distribution function, and the phase crossing rate expressions. Remarkably, the unlikely shapes of the phase statistics, as predicted by the theoretical formulations, are actually encountered in practice.

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Variations in the phase angle difference between a remote 11kV connected wind farm and the centre of Belfast during a typical working day are investigated in the paper. The results obtained using phasor measurement units (PMUs) are compared with the data generated using a PSS/E simulator configured to model the N.Ireland network. The study investigates the effect of changes in the load demand and the wind farm output power on the phase angles at various locations on the network. The paper finally describes how a major system disturbance on the All-Ireland network was monitored and analysed using PMUs located at Queen's University, Belfast and University College Dublin. ©2007 IEEE.

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A hydrolyzable model network comprising interconnected star polymers was prepared by the sequential group transfer polymerization of methyl methacrylate and the acid-labile diacetal-based dimethacrylate crosslinker bis[(2-methacryloyloxy)ethoxymethyl] ether. in contrast to other polymer networks previously synthesized by our group, all the branching points of this polymer network were found to hydrolyze under mildly acidic conditions, giving a linear copolymer with the theoretically expected molecular weight and composition. The ease of hydrolysis of this polymer network renders it a good candidate for use in the biomedical field. The characterization of the synthesized network, its linear and star polymer precursors and the hydrolysis products of the network and its precursors, by a variety of techniques, established the successful synthesis and hydrolysis of this well-defined polymer nanostructure.

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Group transfer polymerization (GTP) chemistry was employed for the preparation of polymethacrylate networks of controlled structure (quasi-model networks) of three different types: (a) regular quasi-model networks, in which all polymer chains were linked at their ends, leaving, in principle, no free chain ends, (b) crosslinked star polymer quasi-model networks, in which star polymers were interlinked via half of their chains, letting the other half free (dangling), and (c) shell-crosslinked polymer quasi-model networks, in which the outer part of the network contained polymer arms (dangling chains). Combination of hydrophilic and hydrophobic monomers led to amphiphilic networks whose aqueous swelling behavior was characterized gravimetrically.

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A hydrolyzable dimethacrylate cross-linker, 2-methyl-2,4-pentanediol dimethacrylate (MPDMA), was synhesized by the reaction of 2-methyl-2,4-pentanediol and methacryloyl chloride in the presence of triethylamine. This cross-linker was used to prepare a neat cross-linker network and three cross-linked star polymer model networks (CSPMNs) of methyl methacrylate (MMA), as well as star-shaped polymers of MMA, by group transfer polymerization (GTP). Gel permeation chromatography (GPC) in tetrahydrofuran (THF) confirmed the narrow molecular weight distributions (MWDs) of the linear polymer precursors, and demonstrated the increase in molecular weight (MW) on each successive addition of cross-linker or monomer. Characterization of the star polymers by static light scattering (SLS) in THF showed that star polymers with MPDMA cores bear a relatively small number of arms, between 7 and 35. All star polymers and polymer networks containing the MPDMA cross-linker were hydrolyzed at room temperature in neat trifluoroacetic acid to yield lower-MW products.

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An acid-labile dimethacrylate cross-linker, dimethyldi(methacryloyloxy-l-ethoxy)silane (DMDMAES), was synthesized by the reaction of 2-hydroxyethyl methacrylate (HEMA) and dichlorodimethylsilane in the presence of triethylamine. Group transfer polymerization (GTP) was employed to use this cross-linker in the preparation of six hydrolyzable polymer structures: one neat cross-linker network, one randomly cross-linked network of methyl methacrylate (MMA), two star-shaped polymers of MMA, and two cross-linked star polymer model networks (CSPMNs) of MMA. A nonhydrolyzable CSPMN of MMA, based on a stable cross-linker, was also synthesized. Gel permeation chromatography (GPC) in tetrahydrofuran (THF) confirmed the narrow molecular weight distributions (MWDs) of the linear polymer precursors and demonstrated the increase in molecular weight (MW) upon each successive addition of cross-linker or monomer. Characterization by static light scattering (SLS) and GPC showed that star polymers with DMDMAES cores bear a relatively small number of arms, around 7. All star polymers and polymer networks were hydrolyzed using hydrochloric acid in THF. While the MWs of the products from the hydrolysis of the star polymers, the neat cross-linker network, and the randomly cross-linked network were as expected, those from the CSPMNs were of a much higher than expected MW, indicating extensive star-star coupling.

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Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

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This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods. 

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This paper characterizes efficient networks in player and partner heterogeneity models for both the one-way flow and the two-way flow models. Player (partner) dependent network formation allows benefits and costs to be player (partner) heterogeneous which is an important extension for modeling social networks in the real world. Employing widely used assumptions, I show that efficient networks in the two way flow model are minimally connected and have star or derivative of star type architectures, whereas efficient networks in the one way flow model have wheel architectures.

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In this paper we investigate the received signal characteristics of on-body communications channels at 2.45 GHz. The hypothetical body area network configuration considered a transmitter node situated on the person’s left waist and receiving nodes positioned on the head, knee and wrist of the person’s right side. The on-body channel measurements were performed in both anechoic and reverberant environments while the person was moving. It was found that the recently proposed shadowed κ‒μ fading model provided an excellent fit to the measured data.