WorldWideScience

Sample records for network model validation

  1. Validating neural-network refinements of nuclear mass models

    Science.gov (United States)

    Utama, R.; Piekarewicz, J.

    2018-01-01

    Background: Nuclear astrophysics centers on the role of nuclear physics in the cosmos. In particular, nuclear masses at the limits of stability are critical in the development of stellar structure and the origin of the elements. Purpose: We aim to test and validate the predictions of recently refined nuclear mass models against the newly published AME2016 compilation. Methods: The basic paradigm underlining the recently refined nuclear mass models is based on existing state-of-the-art models that are subsequently refined through the training of an artificial neural network. Bayesian inference is used to determine the parameters of the neural network so that statistical uncertainties are provided for all model predictions. Results: We observe a significant improvement in the Bayesian neural network (BNN) predictions relative to the corresponding "bare" models when compared to the nearly 50 new masses reported in the AME2016 compilation. Further, AME2016 estimates for the handful of impactful isotopes in the determination of r -process abundances are found to be in fairly good agreement with our theoretical predictions. Indeed, the BNN-improved Duflo-Zuker model predicts a root-mean-square deviation relative to experiment of σrms≃400 keV. Conclusions: Given the excellent performance of the BNN refinement in confronting the recently published AME2016 compilation, we are confident of its critical role in our quest for mass models of the highest quality. Moreover, as uncertainty quantification is at the core of the BNN approach, the improved mass models are in a unique position to identify those nuclei that will have the strongest impact in resolving some of the outstanding questions in nuclear astrophysics.

  2. Validation of protein models by a neural network approach

    Directory of Open Access Journals (Sweden)

    Fantucci Piercarlo

    2008-01-01

    Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

  3. Validation & verification of a Bayesian network model for aircraft vulnerability

    CSIR Research Space (South Africa)

    Schietekat, Sunelle

    2016-09-01

    Full Text Available on the African Very Long Baseline Interferometry (VLBI) Network (AVN) project where she was based at Hartebeesthoek Radio Astronomy Observatory (HartRAO). Sunelle is certified as an Associate Systems Engineering Professional (ASEP) at INCOSE. Alta de Waal...

  4. Parameter Estimation and Model Validation of Nonlinear Dynamical Networks

    Energy Technology Data Exchange (ETDEWEB)

    Abarbanel, Henry [Univ. of California, San Diego, CA (United States); Gill, Philip [Univ. of California, San Diego, CA (United States)

    2015-03-31

    In the performance period of this work under a DOE contract, the co-PIs, Philip Gill and Henry Abarbanel, developed new methods for statistical data assimilation for problems of DOE interest, including geophysical and biological problems. This included numerical optimization algorithms for variational principles, new parallel processing Monte Carlo routines for performing the path integrals of statistical data assimilation. These results have been summarized in the monograph: “Predicting the Future: Completing Models of Observed Complex Systems” by Henry Abarbanel, published by Spring-Verlag in June 2013. Additional results and details have appeared in the peer reviewed literature.

  5. Modeling users' activity on twitter networks: validation of Dunbar's number.

    Directory of Open Access Journals (Sweden)

    Bruno Gonçalves

    Full Text Available Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100-200 stable relationships. Thus, the 'economy of attention' is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior.

  6. Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

    Directory of Open Access Journals (Sweden)

    Tommi Aho

    2010-05-01

    Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

  7. U-tube steam generator empirical model development and validation using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Chong, K.T.; Atiya, A.

    1992-01-01

    Empirical modeling techniques that use model structures motivated from neural networks research have proven effective in identifying complex process dynamics. A recurrent multilayer perception (RMLP) network was developed as a nonlinear state-space model structure along with a static learning algorithm for estimating the parameter associated with it. The methods developed were demonstrated by identifying two submodels of a U-tube steam generator (UTSG), each valid around an operating power level. A significant drawback of this approach is the long off-line training times required for the development of even a simplified model of a UTSG. Subsequently, a dynamic gradient descent-based learning algorithm was developed as an accelerated alternative to train an RMLP network for use in empirical modeling of power plants. The two main advantages of this learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm were demonstrated via the case study of a simple steam boiler power plant. In this paper, the dynamic gradient descent-based learning algorithm is used for the development and validation of a complete UTSG empirical model

  8. Modelling and Initial Validation of the DYMO Routing Protocol for Mobile Ad-Hoc Networks

    DEFF Research Database (Denmark)

    Espensen, Kristian Asbjørn Leth; Kjeldsen, Mads Keblov; Kristensen, Lars Michael

    2008-01-01

    A mobile ad-hoc network (MANET) is an infrastructureless network established by a set of mobile devices using wireless communication. The Dynamic MANET On-demand (DYMO) protocol is a routing protocol for multi-hop communication in MANETs currently under development by the Internet Engineering Task...... Force (IETF). This paper presents a Coloured Petri Net (CPN) model of the mandatory parts of the DYMO protocol, and shows how scenario-based state space exploration has been used to validate key properties of the protocol. Our CPN modelling and verification work has spanned two revisions of the DYMO...... protocol specification and have had direct impact on the most recent version of the protocol specification....

  9. Validation of a Novel Traditional Chinese Medicine Pulse Diagnostic Model Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Anson Chui Yan Tang

    2012-01-01

    Full Text Available In view of lacking a quantifiable traditional Chinese medicine (TCM pulse diagnostic model, a novel TCM pulse diagnostic model was introduced to quantify the pulse diagnosis. Content validation was performed with a panel of TCM doctors. Criterion validation was tested with essential hypertension. The gold standard was brachial blood pressure measured by a sphygmomanometer. Two hundred and sixty subjects were recruited (139 in the normotensive group and 121 in the hypertensive group. A TCM doctor palpated pulses at left and right cun, guan, and chi points, and quantified pulse qualities according to eight elements (depth, rate, regularity, width, length, smoothness, stiffness, and strength on a visual analog scale. An artificial neural network was used to develop a pulse diagnostic model differentiating essential hypertension from normotension. Accuracy, specificity, and sensitivity were compared among various diagnostic models. About 80% accuracy was attained among all models. Their specificity and sensitivity varied, ranging from 70% to nearly 90%. It suggested that the novel TCM pulse diagnostic model was valid in terms of its content and diagnostic ability.

  10. Using a small scale wireless sensor network for model validation. Two case studies

    Energy Technology Data Exchange (ETDEWEB)

    Lengfeld, Katharina; Ament, Felix [Hamburg Univ. (Germany). Meteorological Inst.; Zacharias, Stefan [Deutscher Wetterdienst, Freiburg im Breisgau (Germany)

    2013-10-15

    In this paper, the potential of a network consisting of low cost weather stations for validating microscale model simulations and for forcing surface-atmosphere-transfer-schemes is investigated within two case studies. Transfer schemes often do not account for small scale variabilities of the earth surface, because measurements of the atmospheric conditions do not exist in such a high spatial resolution to force the models. To overcome this issue, in this study a small scale network of meteorological stations is used to derive measurements in high spatial and temporal resolution. The observations carried out during the measurement campaign are compared to air temperature and specific humidity simulations of the mesoscale atmospheric model FOOT3DK (Flow Over Orographically-Structured Terrain - 3 Dimensional Model (Koelner Version)). This comparison indicates that FOOT3DK simulates either air temperature or specific humidity satisfactorily for each station at the lowest model level, depending on the dominating land use class within each grid cell. The influence of heterogeneous forcing and vegetation on heat flux modelling is studied using the soil-vegetation-atmosphere transfer scheme TERRA. The observations of the measurement campaign are used as input for four different runs with homogeneous and heterogeneous forcing and vegetation. Heterogeneous vegetation reduces the bias between the grid cells, heterogeneous forcing reduces the random error for each grid cell. (orig.)

  11. Validation Study of CODES Dragonfly Network Model with Theta Cray XC System

    Energy Technology Data Exchange (ETDEWEB)

    Mubarak, Misbah [Argonne National Lab. (ANL), Argonne, IL (United States); Ross, Robert B. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-05-31

    This technical report describes the experiments performed to validate the MPI performance measurements reported by the CODES dragonfly network simulation with the Theta Cray XC system at the Argonne Leadership Computing Facility (ALCF).

  12. Validation Techniques of network harmonic models based on switching of a series linear component and measuring resultant harmonic increments

    DEFF Research Database (Denmark)

    Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth

    2007-01-01

    In this paper two methods of validation of transmission network harmonic models are introduced. The methods were developed as a result of the work presented in [1]. The first method allows calculating the transfer harmonic impedance between two nodes of a network. Switching a linear, series network......, as for example a transmission line. Both methods require that harmonic measurements performed at two ends of the disconnected element are precisely synchronized....... are used for calculation of the transfer harmonic impedance between the nodes. The determined transfer harmonic impedance can be used to validate a computer model of the network. The second method is an extension of the fist one. It allows switching a series element that contains a shunt branch...

  13. Validation of artificial neural network models for predicting biochemical markers associated with male infertility.

    Science.gov (United States)

    Vickram, A S; Kamini, A Rao; Das, Raja; Pathy, M Ramesh; Parameswari, R; Archana, K; Sridharan, T B

    2016-08-01

    Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg(2+), Ca(2+), K(+), and Na(+). Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres. AAS: absorption spectroscopy; AI: artificial intelligence; ANN: artificial neural networks; ART: assisted reproductive technology; BPNN: back propagation neural network model; DT: decision tress; MLP: multilayer perceptron; PESA: percutaneous

  14. Validation and quantification of uncertainty in coupled climate models using network analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bracco, Annalisa [Georgia Inst. of Technology, Atlanta, GA (United States)

    2015-08-10

    We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets

  15. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

    Science.gov (United States)

    Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

    2017-01-01

    Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

  16. Groundwater Model Validation

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed E. Hassan

    2006-01-24

    Models have an inherent uncertainty. The difficulty in fully characterizing the subsurface environment makes uncertainty an integral component of groundwater flow and transport models, which dictates the need for continuous monitoring and improvement. Building and sustaining confidence in closure decisions and monitoring networks based on models of subsurface conditions require developing confidence in the models through an iterative process. The definition of model validation is postulated as a confidence building and long-term iterative process (Hassan, 2004a). Model validation should be viewed as a process not an end result. Following Hassan (2004b), an approach is proposed for the validation process of stochastic groundwater models. The approach is briefly summarized herein and detailed analyses of acceptance criteria for stochastic realizations and of using validation data to reduce input parameter uncertainty are presented and applied to two case studies. During the validation process for stochastic models, a question arises as to the sufficiency of the number of acceptable model realizations (in terms of conformity with validation data). Using a hierarchical approach to make this determination is proposed. This approach is based on computing five measures or metrics and following a decision tree to determine if a sufficient number of realizations attain satisfactory scores regarding how they represent the field data used for calibration (old) and used for validation (new). The first two of these measures are applied to hypothetical scenarios using the first case study and assuming field data consistent with the model or significantly different from the model results. In both cases it is shown how the two measures would lead to the appropriate decision about the model performance. Standard statistical tests are used to evaluate these measures with the results indicating they are appropriate measures for evaluating model realizations. The use of validation

  17. Validation of Tilt Gain under Realistic Path Loss Model and Network Scenario

    DEFF Research Database (Denmark)

    Nguyen, Huan Cong; Rodriguez, Ignacio; Sørensen, Troels Bundgaard

    2013-01-01

    Despite being a simple and commonly-applied radio optimization technique, the impact on practical network performance from base station antenna downtilt is not well understood. Most published studies based on empirical path loss models report tilt angles and performance gains that are far higher...... than practical experience suggests. We motivate in this paper, based on a practical LTE scenario, that the discrepancy partly lies in the path loss model, and shows that a more detailed semi-deterministic model leads to both lower gains in terms of SINR, outage probability and downlink throughput...... settings, including the use of electrical and/or mechanical antenna downtilt, and therefore it is possible to find multiple optimum tilt profiles in a practical case. A broader implication of this study is that care must be taken when using the 3GPP model to evaluate advanced adaptive antenna techniques...

  18. A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

    Science.gov (United States)

    David, Hamilton P; Carey, Cayelan C.; Arvola, Lauri; Arzberger, Peter; Brewer, Carol A.; Cole, Jon J; Gaiser, Evelyn; Hanson, Paul C.; Ibelings, Bas W; Jennings, Eleanor; Kratz, Tim K; Lin, Fang-Pang; McBride, Christopher G.; de Motta Marques, David; Muraoka, Kohji; Nishri, Ami; Qin, Boqiang; Read, Jordan S.; Rose, Kevin C.; Ryder, Elizabeth; Weathers, Kathleen C.; Zhu, Guangwei; Trolle, Dennis; Brookes, Justin D

    2014-01-01

    A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

  19. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  20. Construct Validation of Wenger's Support Network Typology.

    Science.gov (United States)

    Szabo, Agnes; Stephens, Christine; Allen, Joanne; Alpass, Fiona

    2016-10-07

    The study aimed to validate Wenger's empirically derived support network typology of responses to the Practitioner Assessment of Network Type (PANT) in an older New Zealander population. The configuration of network types was tested across ethnic groups and in the total sample. Data (N = 872, Mage = 67 years, SDage = 1.56 years) from the 2006 wave of the New Zealand Health, Work and Retirement study were analyzed using latent profile analysis. In addition, demographic differences among the emerging profiles were tested. Competing models were evaluated based on a range of fit criteria, which supported a five-profile solution. The "locally integrated," "community-focused," "local self-contained," "private-restricted," and "friend- and family-dependent" network types were identified as latent profiles underlying the data. There were no differences between Māori and non-Māori in final profile configurations. However, Māori were more likely to report integrated network types. Findings confirm the validity of Wenger's network types. However, the level to which participants endorse accessibility of family, frequency of interactions, and community engagement can be influenced by sample and contextual characteristics. Future research using the PANT items should empirically verify and derive the social support network types, rather than use a predefined scoring system. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  2. Validation of HEDR models

    International Nuclear Information System (INIS)

    Napier, B.A.; Simpson, J.C.; Eslinger, P.W.; Ramsdell, J.V. Jr.; Thiede, M.E.; Walters, W.H.

    1994-05-01

    The Hanford Environmental Dose Reconstruction (HEDR) Project has developed a set of computer models for estimating the possible radiation doses that individuals may have received from past Hanford Site operations. This document describes the validation of these models. In the HEDR Project, the model validation exercise consisted of comparing computational model estimates with limited historical field measurements and experimental measurements that are independent of those used to develop the models. The results of any one test do not mean that a model is valid. Rather, the collection of tests together provide a level of confidence that the HEDR models are valid

  3. The Internet addiction components model and personality: establishing construct validity via a nomological network

    OpenAIRE

    Kuss, DJ; Shorter, GW; Van Rooij, AJ; Van de Mheen, D; Griffiths, MD

    2014-01-01

    There is growing concern over excessive and sometimes problematic Internet use. Drawing upon the framework of the components model of addiction (Griffiths, 2005), Internet addiction appears as behavioural addiction characterised by the following symptoms: salience, withdrawal, tolerance, mood modification, relapse and conflict. A number of factors have been associated with an increased risk for Internet addiction, including personality traits. The overall aim of this study was to establish th...

  4. Model Validation Status Review

    International Nuclear Information System (INIS)

    E.L. Hardin

    2001-01-01

    The primary objective for the Model Validation Status Review was to perform a one-time evaluation of model validation associated with the analysis/model reports (AMRs) containing model input to total-system performance assessment (TSPA) for the Yucca Mountain site recommendation (SR). This review was performed in response to Corrective Action Request BSC-01-C-01 (Clark 2001, Krisha 2001) pursuant to Quality Assurance review findings of an adverse trend in model validation deficiency. The review findings in this report provide the following information which defines the extent of model validation deficiency and the corrective action needed: (1) AMRs that contain or support models are identified, and conversely, for each model the supporting documentation is identified. (2) The use for each model is determined based on whether the output is used directly for TSPA-SR, or for screening (exclusion) of features, events, and processes (FEPs), and the nature of the model output. (3) Two approaches are used to evaluate the extent to which the validation for each model is compliant with AP-3.10Q (Analyses and Models). The approaches differ in regard to whether model validation is achieved within individual AMRs as originally intended, or whether model validation could be readily achieved by incorporating information from other sources. (4) Recommendations are presented for changes to the AMRs, and additional model development activities or data collection, that will remedy model validation review findings, in support of licensing activities. The Model Validation Status Review emphasized those AMRs that support TSPA-SR (CRWMS M and O 2000bl and 2000bm). A series of workshops and teleconferences was held to discuss and integrate the review findings. The review encompassed 125 AMRs (Table 1) plus certain other supporting documents and data needed to assess model validity. The AMRs were grouped in 21 model areas representing the modeling of processes affecting the natural and

  5. Model Validation Status Review

    Energy Technology Data Exchange (ETDEWEB)

    E.L. Hardin

    2001-11-28

    The primary objective for the Model Validation Status Review was to perform a one-time evaluation of model validation associated with the analysis/model reports (AMRs) containing model input to total-system performance assessment (TSPA) for the Yucca Mountain site recommendation (SR). This review was performed in response to Corrective Action Request BSC-01-C-01 (Clark 2001, Krisha 2001) pursuant to Quality Assurance review findings of an adverse trend in model validation deficiency. The review findings in this report provide the following information which defines the extent of model validation deficiency and the corrective action needed: (1) AMRs that contain or support models are identified, and conversely, for each model the supporting documentation is identified. (2) The use for each model is determined based on whether the output is used directly for TSPA-SR, or for screening (exclusion) of features, events, and processes (FEPs), and the nature of the model output. (3) Two approaches are used to evaluate the extent to which the validation for each model is compliant with AP-3.10Q (Analyses and Models). The approaches differ in regard to whether model validation is achieved within individual AMRs as originally intended, or whether model validation could be readily achieved by incorporating information from other sources. (4) Recommendations are presented for changes to the AMRs, and additional model development activities or data collection, that will remedy model validation review findings, in support of licensing activities. The Model Validation Status Review emphasized those AMRs that support TSPA-SR (CRWMS M&O 2000bl and 2000bm). A series of workshops and teleconferences was held to discuss and integrate the review findings. The review encompassed 125 AMRs (Table 1) plus certain other supporting documents and data needed to assess model validity. The AMRs were grouped in 21 model areas representing the modeling of processes affecting the natural and

  6. Validation of simulation models

    DEFF Research Database (Denmark)

    Rehman, Muniza; Pedersen, Stig Andur

    2012-01-01

    In philosophy of science, the interest for computational models and simulations has increased heavily during the past decades. Different positions regarding the validity of models have emerged but the views have not succeeded in capturing the diversity of validation methods. The wide variety...

  7. Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

    Science.gov (United States)

    Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

    2018-04-17

    The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

  8. Network Security Validation Using Game Theory

    Science.gov (United States)

    Papadopoulou, Vicky; Gregoriades, Andreas

    Non-functional requirements (NFR) such as network security recently gained widespread attention in distributed information systems. Despite their importance however, there is no systematic approach to validate these requirements given the complexity and uncertainty characterizing modern networks. Traditionally, network security requirements specification has been the results of a reactive process. This however, limited the immunity property of the distributed systems that depended on these networks. Security requirements specification need a proactive approach. Networks' infrastructure is constantly under attack by hackers and malicious software that aim to break into computers. To combat these threats, network designers need sophisticated security validation techniques that will guarantee the minimum level of security for their future networks. This paper presents a game-theoretic approach to security requirements validation. An introduction to game theory is presented along with an example that demonstrates the application of the approach.

  9. HEDR model validation plan

    International Nuclear Information System (INIS)

    Napier, B.A.; Gilbert, R.O.; Simpson, J.C.; Ramsdell, J.V. Jr.; Thiede, M.E.; Walters, W.H.

    1993-06-01

    The Hanford Environmental Dose Reconstruction (HEDR) Project has developed a set of computational ''tools'' for estimating the possible radiation dose that individuals may have received from past Hanford Site operations. This document describes the planned activities to ''validate'' these tools. In the sense of the HEDR Project, ''validation'' is a process carried out by comparing computational model predictions with field observations and experimental measurements that are independent of those used to develop the model

  10. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  11. Innovation, Product Development, and New Business Models in Networks: How to come from case studies to a valid and operational theory

    DEFF Research Database (Denmark)

    Rasmussen, Erik Stavnsager; Jørgensen, Jacob Høj; Goduscheit, René Chester

    2007-01-01

    We have in the research project NEWGIBM (New Global ICT based Business Models) during 2005 and 2006 closely cooperated with a group of firms. The focus in the project has been development of new business models (and innovation) in close cooperation with multiple partners. These partners have been...... customers, suppliers, R&D partners, and others. The methodological problem is thus, how to come from e.g. one in-depth case study to a more formalized theory or model on how firms can develop new projects and be innovative in a network. The paper is structured so that it starts with a short presentation...... of the two key concepts in our research setting and theoretical models: Innovation and networks. It is not our intention in this paper to present a lengthy discussion of the two concepts, but a short presentation is necessary to understand the validity and interpretation discussion later in the paper. Next...

  12. Experimental Testing and Model Validation of a Decoupled-Phase On-Load Tap Changer Transformer in an Active Network

    DEFF Research Database (Denmark)

    Zecchino, Antonio; Hu, Junjie; Coppo, Massimiliano

    2016-01-01

    Due to the increasing penetration of single-phase small generation units and electric vehicles connected to distribution grids, system operators are facing challenges related to local unbalanced voltage rise or drop issues, which may lead to a violation of the allowed voltage band. To address...... this problem, distribution transformers with on-load tapping capability are under development. This paper presents model and experimental validation of a 35 kVA three-phase power distribution transformer with independent on-load tap changer control capability on each phase. With the purpose of investigating...... to reproduce the main feature of an unbalanced grid. The experimental activities are recreated in by carrying out dynamics simulation studies, aiming at validating the implemented models of both the transformer as well as the other grid components. Phase-neutral voltages’ deviations are limited, proving...

  13. A Validated Set of MIDAS V5 Task Network Model Scenarios to Evaluate Nextgen Closely Spaced Parallel Operations Concepts

    Science.gov (United States)

    Gore, Brian Francis; Hooey, Becky Lee; Haan, Nancy; Socash, Connie; Mahlstedt, Eric; Foyle, David C.

    2013-01-01

    The Closely Spaced Parallel Operations (CSPO) scenario is a complex, human performance model scenario that tested alternate operator roles and responsibilities to a series of off-nominal operations on approach and landing (see Gore, Hooey, Mahlstedt, Foyle, 2013). The model links together the procedures, equipment, crewstation, and external environment to produce predictions of operator performance in response to Next Generation system designs, like those expected in the National Airspaces NextGen concepts. The task analysis that is contained in the present report comes from the task analysis window in the MIDAS software. These tasks link definitions and states for equipment components, environmental features as well as operational contexts. The current task analysis culminated in 3300 tasks that included over 1000 Subject Matter Expert (SME)-vetted, re-usable procedural sets for three critical phases of flight; the Descent, Approach, and Land procedural sets (see Gore et al., 2011 for a description of the development of the tasks included in the model; Gore, Hooey, Mahlstedt, Foyle, 2013 for a description of the model, and its results; Hooey, Gore, Mahlstedt, Foyle, 2013 for a description of the guidelines that were generated from the models results; Gore, Hooey, Foyle, 2012 for a description of the models implementation and its settings). The rollout, after landing checks, taxi to gate and arrive at gate illustrated in Figure 1 were not used in the approach and divert scenarios exercised. The other networks in Figure 1 set up appropriate context settings for the flight deck.The current report presents the models task decomposition from the tophighest level and decomposes it to finer-grained levels. The first task that is completed by the model is to set all of the initial settings for the scenario runs included in the model (network 75 in Figure 1). This initialization process also resets the CAD graphic files contained with MIDAS, as well as the embedded

  14. Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Rasoul Sali

    2013-01-01

    Full Text Available Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12. A hybrid model of genetic algorithm (GA and artificial neural networks (ANNs was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale and the GHQ score as a response variable. In this model, GA is used in order to set some parameter of ANN for achieving more accurate results. Results. For each stressful life event, the number is defined as weight. Among all stressful life events, death of parents, spouse, or siblings is the most important and impactful stressor in the studied population. Sensitivity of 83% and specificity of 81% were obtained for the cut point 100. Conclusion. The SLE-revised (SLE-R questionnaire despite simplicity is a high-performance screening tool for investigating the stress level of life events and its management in both community and primary care settings. The SLE-R questionnaire is user-friendly and easy to be self-administered. This questionnaire allows the individuals to be aware of their own health status.

  15. Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

    Energy Technology Data Exchange (ETDEWEB)

    Hadhri, Mahdi; Ouafi, Abderazzak El; Barka, Noureddine [University of Quebec, Rimouski (Canada)

    2017-02-15

    This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process.

  16. Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

    International Nuclear Information System (INIS)

    Hadhri, Mahdi; Ouafi, Abderazzak El; Barka, Noureddine

    2017-01-01

    This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process

  17. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  18. Validation and Adaptation of Router and Switch Models

    NARCIS (Netherlands)

    Boltjes, B.; Fernandez Diaz, I.; Kock, B.A.; Langeveld, R.J.G.M.; Schoenmaker, G.

    2003-01-01

    This paper describes validating OPNET models of key devices for the next generation IP-based tactical network of the Royal Netherlands Army (RNLA). The task of TNO-FEL is to provide insight in scalability and performance of future deployed networks. Because validated models ol key Cisco equipment

  19. Security Property Validation of the Sensor Network Encryption Protocol (SNEP

    Directory of Open Access Journals (Sweden)

    Salekul Islam

    2015-07-01

    Full Text Available Since wireless sensor networks (WSNs have been designed to be deployed in an unsecured, public environment, secured communication is really vital for their wide-spread use. Among all of the communication protocols developed for WSN, the Security Protocols for Sensor Networks (SPINS is exceptional, as it has been designed with security as a goal. SPINS is composed of two building blocks: Secure Network Encryption Protocol (SNEP and the “micro” version of the Timed Efficient Streaming Loss-tolerant Authentication (TESLA, named μTESLA. From the inception of SPINS, a number of efforts have been made to validate its security properties. In this paper, we have validated the security properties of SNEP by using an automated security protocol validation tool, named AVISPA. Using the protocol specification language, HLPSL, we model two combined scenarios—node to node key agreement and counter exchange protocols—followed by data transmission. Next, we validate the security properties of these combined protocols, using different AVISPA back-ends. AVISPA reports the models we have developed free from attacks. However, by analyzing the key distribution sub-protocol, we find one threat of a potential DoS attack that we have demonstrated by modeling in AVISPA. Finally, we propose a modification, and AVISPA reports this modified version free from the potential DoS attack.

  20. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  1. Validating Animal Models

    Directory of Open Access Journals (Sweden)

    Nina Atanasova

    2015-06-01

    Full Text Available In this paper, I respond to the challenge raised against contemporary experimental neurobiology according to which the field is in a state of crisis because of the multiple experimental protocols employed in different laboratories and strengthening their reliability that presumably preclude the validity of neurobiological knowledge. I provide an alternative account of experimentation in neurobiology which makes sense of its experimental practices. I argue that maintaining a multiplicity of experimental protocols and strengthening their reliability are well justified and they foster rather than preclude the validity of neurobiological knowledge. Thus, their presence indicates thriving rather than crisis of experimental neurobiology.

  2. Developing a model for validation and prediction of bank customer ...

    African Journals Online (AJOL)

    Credit risk is the most important risk of banks. The main approaches of the bank to reduce credit risk are correct validation using the final status and the validation model parameters. High fuel of bank reserves and lost or outstanding facilities of banks indicate the lack of appropriate validation models in the banking network.

  3. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  4. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  5. RMBNToolbox: random models for biochemical networks

    Directory of Open Access Journals (Sweden)

    Niemi Jari

    2007-05-01

    Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

  6. Validating Dart Model

    Directory of Open Access Journals (Sweden)

    Mazur Jolanta

    2014-12-01

    Full Text Available The primary objective of the study was to quantitatively test the DART model, which despite being one of the most popular representations of co-creation concept was so far studied almost solely with qualitative methods. To this end, the researchers developed a multiple measurement scale and employed it in interviewing managers. The statistical evidence for adequacy of the model was obtained through CFA with AMOS software. The findings suggest that the DART model may not be an accurate representation of co-creation practices in companies. From the data analysis it was evident that the building blocks of DART had too much of conceptual overlap to be an effective framework for quantitative analysis. It was also implied that the phenomenon of co-creation is so rich and multifaceted that it may be more adequately captured by a measurement model where co-creation is conceived as a third-level factor with two layers of intermediate latent variables.

  7. Validation through model testing

    International Nuclear Information System (INIS)

    1995-01-01

    Geoval-94 is the third Geoval symposium arranged jointly by the OECD/NEA and the Swedish Nuclear Power Inspectorate. Earlier symposia in this series took place in 1987 and 1990. In many countries, the ongoing programmes to site and construct deep geological repositories for high and intermediate level nuclear waste are close to realization. A number of studies demonstrates the potential barrier function of the geosphere, but also that there are many unresolved issues. A key to these problems are the possibilities to gain knowledge by model testing with experiments and to increase confidence in models used for prediction. The sessions cover conclusions from the INTRAVAL-project, experiences from integrated experimental programs and underground research laboratories as well as the integration between performance assessment and site characterisation. Technical issues ranging from waste and buffer interactions with the rock to radionuclide migration in different geological media is addressed. (J.S.)

  8. Perpetual Model Validation

    Science.gov (United States)

    2017-03-01

    25]. This inference process is carried out by a tool referred to as Hynger (Hybrid iNvariant GEneratoR), overviewed in Figure 4, which is a MATLAB ...initially on memory access patterns. A monitoring module will check, at runtime that the observed memory access pattern matches the pattern the software is...necessary. By using the developed approach, a model may be derived from initial tests or simulations , which will then be formally checked at runtime

  9. GPM ground validation via commercial cellular networks: an exploratory approach

    Science.gov (United States)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko

    2016-04-01

    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  10. How to model wireless mesh networks topology

    International Nuclear Information System (INIS)

    Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M

    2013-01-01

    The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches

  11. Validation process of simulation model

    International Nuclear Information System (INIS)

    San Isidro, M. J.

    1998-01-01

    It is presented a methodology on empirical validation about any detailed simulation model. This king of validation it is always related with an experimental case. The empirical validation has a residual sense, because the conclusions are based on comparisons between simulated outputs and experimental measurements. This methodology will guide us to detect the fails of the simulation model. Furthermore, it can be used a guide in the design of posterior experiments. Three steps can be well differentiated: Sensitivity analysis. It can be made with a DSA, differential sensitivity analysis, and with a MCSA, Monte-Carlo sensitivity analysis. Looking the optimal domains of the input parameters. It has been developed a procedure based on the Monte-Carlo methods and Cluster techniques, to find the optimal domains of these parameters. Residual analysis. This analysis has been made on the time domain and on the frequency domain, it has been used the correlation analysis and spectral analysis. As application of this methodology, it is presented the validation carried out on a thermal simulation model on buildings, Esp., studying the behavior of building components on a Test Cell of LECE of CIEMAT. (Author) 17 refs

  12. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  13. Network modelling methods for FMRI.

    Science.gov (United States)

    Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

    2011-01-15

    There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

  14. Verification and validation of models

    International Nuclear Information System (INIS)

    Herbert, A.W.; Hodgkinson, D.P.; Jackson, C.P.; Lever, D.A.; Robinson, P.C.

    1986-12-01

    The numerical accuracy of the computer models for groundwater flow and radionuclide transport that are to be used in repository safety assessment must be tested, and their ability to describe experimental data assessed: they must be verified and validated respectively. Also appropriate ways to use the codes in performance assessments, taking into account uncertainties in present data and future conditions, must be studied. These objectives are being met by participation in international exercises, by developing bench-mark problems, and by analysing experiments. In particular the project has funded participation in the HYDROCOIN project for groundwater flow models, the Natural Analogues Working Group, and the INTRAVAL project for geosphere models. (author)

  15. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  16. A soil moisture network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, N.; Jensen, Karsten Høgh

    2012-01-01

    network was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS...... between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved soil moisture (R2 of 0.49) as well as initial soil......). Based on these findings, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies...

  17. Enhanced data validation strategy of air quality monitoring network.

    Science.gov (United States)

    Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

    2018-01-01

    Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

  18. PEMFC modeling and experimental validation

    Energy Technology Data Exchange (ETDEWEB)

    Vargas, J.V.C. [Federal University of Parana (UFPR), Curitiba, PR (Brazil). Dept. of Mechanical Engineering], E-mail: jvargas@demec.ufpr.br; Ordonez, J.C.; Martins, L.S. [Florida State University, Tallahassee, FL (United States). Center for Advanced Power Systems], Emails: ordonez@caps.fsu.edu, martins@caps.fsu.edu

    2009-07-01

    In this paper, a simplified and comprehensive PEMFC mathematical model introduced in previous studies is experimentally validated. Numerical results are obtained for an existing set of commercial unit PEM fuel cells. The model accounts for pressure drops in the gas channels, and for temperature gradients with respect to space in the flow direction, that are investigated by direct infrared imaging, showing that even at low current operation such gradients are present in fuel cell operation, and therefore should be considered by a PEMFC model, since large coolant flow rates are limited due to induced high pressure drops in the cooling channels. The computed polarization and power curves are directly compared to the experimentally measured ones with good qualitative and quantitative agreement. The combination of accuracy and low computational time allow for the future utilization of the model as a reliable tool for PEMFC simulation, control, design and optimization purposes. (author)

  19. Context discovery using attenuated Bloom codes: model description and validation

    NARCIS (Netherlands)

    Liu, F.; Heijenk, Geert

    A novel approach to performing context discovery in ad-hoc networks based on the use of attenuated Bloom filters is proposed in this report. In order to investigate the performance of this approach, a model has been developed. This document describes the model and its validation. The model has been

  20. Modeling, validation, and simulation of massive self-organizing wireless sensor networks with cross-layer optimization and congestion mitigation techniques

    NARCIS (Netherlands)

    Boltjes, B.; Oever, J. van den; Zhang, S.

    2008-01-01

    TNO has formulated the ambition of founding a basis for the development of flexible multi-data source and multi-application (ad hoc) sensor networks. These networks are envisioned on a scale that is beyond networks for specific and separate sensor networks. These separate networks need in the future

  1. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  2. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  3. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  4. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

    Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

  5. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  6. Verifying and Validating Simulation Models

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-02-23

    This presentation is a high-level discussion of the Verification and Validation (V&V) of computational models. Definitions of V&V are given to emphasize that “validation” is never performed in a vacuum; it accounts, instead, for the current state-of-knowledge in the discipline considered. In particular comparisons between physical measurements and numerical predictions should account for their respective sources of uncertainty. The differences between error (bias), aleatoric uncertainty (randomness) and epistemic uncertainty (ignorance, lack-of- knowledge) are briefly discussed. Four types of uncertainty in physics and engineering are discussed: 1) experimental variability, 2) variability and randomness, 3) numerical uncertainty and 4) model-form uncertainty. Statistical sampling methods are available to propagate, and analyze, variability and randomness. Numerical uncertainty originates from the truncation error introduced by the discretization of partial differential equations in time and space. Model-form uncertainty is introduced by assumptions often formulated to render a complex problem more tractable and amenable to modeling and simulation. The discussion concludes with high-level guidance to assess the “credibility” of numerical simulations, which stems from the level of rigor with which these various sources of uncertainty are assessed and quantified.

  7. Comparison and validation of community structures in complex networks

    Science.gov (United States)

    Gustafsson, Mika; Hörnquist, Michael; Lombardi, Anna

    2006-07-01

    The issue of partitioning a network into communities has attracted a great deal of attention recently. Most authors seem to equate this issue with the one of finding the maximum value of the modularity, as defined by Newman. Since the problem formulated this way is believed to be NP-hard, most effort has gone into the construction of search algorithms, and less to the question of other measures of community structures, similarities between various partitionings and the validation with respect to external information. Here we concentrate on a class of computer generated networks and on three well-studied real networks which constitute a bench-mark for network studies; the karate club, the US college football teams and a gene network of yeast. We utilize some standard ways of clustering data (originally not designed for finding community structures in networks) and show that these classical methods sometimes outperform the newer ones. We discuss various measures of the strength of the modular structure, and show by examples features and drawbacks. Further, we compare different partitions by applying some graph-theoretic concepts of distance, which indicate that one of the quality measures of the degree of modularity corresponds quite well with the distance from the true partition. Finally, we introduce a way to validate the partitionings with respect to external data when the nodes are classified but the network structure is unknown. This is here possible since we know everything of the computer generated networks, as well as the historical answer to how the karate club and the football teams are partitioned in reality. The partitioning of the gene network is validated by use of the Gene Ontology database, where we show that a community in general corresponds to a biological process.

  8. Geochemistry Model Validation Report: External Accumulation Model

    International Nuclear Information System (INIS)

    Zarrabi, K.

    2001-01-01

    The purpose of this Analysis and Modeling Report (AMR) is to validate the External Accumulation Model that predicts accumulation of fissile materials in fractures and lithophysae in the rock beneath a degrading waste package (WP) in the potential monitored geologic repository at Yucca Mountain. (Lithophysae are voids in the rock having concentric shells of finely crystalline alkali feldspar, quartz, and other materials that were formed due to entrapped gas that later escaped, DOE 1998, p. A-25.) The intended use of this model is to estimate the quantities of external accumulation of fissile material for use in external criticality risk assessments for different types of degrading WPs: U.S. Department of Energy (DOE) Spent Nuclear Fuel (SNF) codisposed with High Level Waste (HLW) glass, commercial SNF, and Immobilized Plutonium Ceramic (Pu-ceramic) codisposed with HLW glass. The scope of the model validation is to (1) describe the model and the parameters used to develop the model, (2) provide rationale for selection of the parameters by comparisons with measured values, and (3) demonstrate that the parameters chosen are the most conservative selection for external criticality risk calculations. To demonstrate the applicability of the model, a Pu-ceramic WP is used as an example. The model begins with a source term from separately documented EQ6 calculations; where the source term is defined as the composition versus time of the water flowing out of a breached waste package (WP). Next, PHREEQC, is used to simulate the transport and interaction of the source term with the resident water and fractured tuff below the repository. In these simulations the primary mechanism for accumulation is mixing of the high pH, actinide-laden source term with resident water; thus lowering the pH values sufficiently for fissile minerals to become insoluble and precipitate. In the final section of the model, the outputs from PHREEQC, are processed to produce mass of accumulation

  9. Validating module network learning algorithms using simulated data.

    Science.gov (United States)

    Michoel, Tom; Maere, Steven; Bonnet, Eric; Joshi, Anagha; Saeys, Yvan; Van den Bulcke, Tim; Van Leemput, Koenraad; van Remortel, Piet; Kuiper, Martin; Marchal, Kathleen; Van de Peer, Yves

    2007-05-03

    In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Despite the demonstrated success of such algorithms in uncovering biologically relevant regulatory relations, further developments in the area are hampered by a lack of tools to compare the performance of alternative module network learning strategies. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators. We show that data simulators such as SynTReN are very well suited for the purpose of developing, testing and improving module network

  10. Interpreting social network metrics in healthcare organisations: a review and guide to validating small networks.

    Science.gov (United States)

    Dunn, Adam G; Westbrook, Johanna I

    2011-04-01

    Social network analysis is an increasingly popular sociological method used to describe and understand the social aspects of communication patterns in the health care sector. The networks studied in this area are special because they are small, and for these sizes, the metrics calculated during analysis are sensitive to the number of people in the network and the density of observed communication. Validation is of particular value in controlling for these factors and in assisting in the accurate interpretation of network findings, yet such approaches are rarely applied. Our aim in this paper was to bring together published case studies to demonstrate how a proposed validation technique provides a basis for standardised comparison of networks within and across studies. A validation is performed for three network studies comprising ten networks, where the results are compared within and across the studies in relation to a standard baseline. The results confirm that hierarchy, centralisation and clustering metrics are highly sensitive to changes in size or density. Amongst the three case studies, we found support for some conclusions and contrary evidence for others. This validation approach is a tool for identifying additional features and verifying the conclusions reached in observational studies of small networks. We provide a methodological basis from which to perform intra-study and inter-study comparisons, for the purpose of introducing greater rigour to the use of social network analysis in health care applications. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. Model-Based Method for Sensor Validation

    Science.gov (United States)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  12. Validation of Bosch' Mobile Communication NetworkArchitecture with SPIN

    NARCIS (Netherlands)

    Ruys, T.C.; Langerak, Romanus

    This paper discusses validation projects carried out for the Mobile Communication Division of Robert Bosch GmbH. We verified parts of their Mobile Communication Network (MCNet), a communication system which is to be used in infotainment systems of future cars. The protocols of the MCNet have been

  13. The QKD network: model and routing scheme

    Science.gov (United States)

    Yang, Chao; Zhang, Hongqi; Su, Jinhai

    2017-11-01

    Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.

  14. Developing Personal Network Business Models

    DEFF Research Database (Denmark)

    Saugstrup, Dan; Henten, Anders

    2006-01-01

    The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...

  15. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  16. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  17. Neural networks for sensor validation and plant-wide monitoring

    International Nuclear Information System (INIS)

    Eryurek, E.

    1991-08-01

    The feasibility of using neural networks to characterize one or more variables as a function of other than related variables has been studied. Neural network or parallel distributed processing is found to be highly suitable for the development of relationships among various parameters. A sensor failure detection is studied, and it is shown that neural network models can be used to estimate the sensor readings during the absence of a sensor. (author). 4 refs.; 3 figs

  18. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  19. Bayesian network modelling of upper gastrointestinal bleeding

    Science.gov (United States)

    Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri

    2013-09-01

    Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.

  20. A model of coauthorship networks

    Science.gov (United States)

    Zhou, Guochang; Li, Jianping; Xie, Zonglin

    2017-10-01

    A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property

  1. On traffic modelling in GPRS networks

    DEFF Research Database (Denmark)

    Madsen, Tatiana Kozlova; Schwefel, Hans-Peter; Prasad, Ramjee

    2005-01-01

    Optimal design and dimensioning of wireless data networks, such as GPRS, requires the knowledge of traffic characteristics of different data services. This paper presents an in-detail analysis of an IP-level traffic measurements taken in an operational GPRS network. The data measurements reported...... here are done at the Gi interface. The aim of this paper is to reveal some key statistics of GPRS data applications and to validate if the existing traffic models can adequately describe traffic volume and inter-arrival time distribution for different services. Additionally, we present a method of user...

  2. Feature selection for anomaly–based network intrusion detection using cluster validity indices

    CSIR Research Space (South Africa)

    Naidoo, T

    2015-09-01

    Full Text Available for Anomaly–Based Network Intrusion Detection Using Cluster Validity Indices Tyrone Naidoo_, Jules–Raymond Tapamoy, Andre McDonald_ Modelling and Digital Science, Council for Scientific and Industrial Research, South Africa 1tnaidoo2@csir.co.za 3...

  3. Telecommunications network modelling, planning and design

    CERN Document Server

    Evans, Sharon

    2003-01-01

    Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

  4. The application of self-validation to wireless sensor networks

    International Nuclear Information System (INIS)

    Collett, Michael A; Cox, Maurice G; Esward, Trevor J; Harris, Peter M; Duta, Mihaela; Henry, Manus P

    2008-01-01

    Self-validation is a valuable tool for extending the operating range of sensing systems and making them more robust. Wireless sensor networks suffer many limitations meaning that their efficacy could be greatly improved by self-validation techniques. We present two independently developed data analysis techniques and demonstrate that they can be applied to a wireless sensor network. Using an acoustic ranging application we demonstrate an improvement of more than ten-fold in the uncertainty of a single measurement where multiple sensor readings are appropriately combined. We also demonstrate that of the two methods for determining a largest consistent subset one is more rigorous in dealing with correlation, and the other more suited to time-series data

  5. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  6. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  7. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  8. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  9. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  10. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  11. Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

    Science.gov (United States)

    Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

    2014-12-01

    Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

  12. Validation of models with multivariate output

    International Nuclear Information System (INIS)

    Rebba, Ramesh; Mahadevan, Sankaran

    2006-01-01

    This paper develops metrics for validating computational models with experimental data, considering uncertainties in both. A computational model may generate multiple response quantities and the validation experiment might yield corresponding measured values. Alternatively, a single response quantity may be predicted and observed at different spatial and temporal points. Model validation in such cases involves comparison of multiple correlated quantities. Multiple univariate comparisons may give conflicting inferences. Therefore, aggregate validation metrics are developed in this paper. Both classical and Bayesian hypothesis testing are investigated for this purpose, using multivariate analysis. Since, commonly used statistical significance tests are based on normality assumptions, appropriate transformations are investigated in the case of non-normal data. The methodology is implemented to validate an empirical model for energy dissipation in lap joints under dynamic loading

  13. Modeling and control of magnetorheological fluid dampers using neural networks

    Science.gov (United States)

    Wang, D. H.; Liao, W. H.

    2005-02-01

    Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.

  14. Dynamic thermo-hydraulic model of district cooling networks

    International Nuclear Information System (INIS)

    Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd

    2016-01-01

    Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.

  15. Delay and Disruption Tolerant Networking MACHETE Model

    Science.gov (United States)

    Segui, John S.; Jennings, Esther H.; Gao, Jay L.

    2011-01-01

    To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity

  16. Feature Extraction for Structural Dynamics Model Validation

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield

    2016-01-13

    As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

  17. Model Validation in Ontology Based Transformations

    Directory of Open Access Journals (Sweden)

    Jesús M. Almendros-Jiménez

    2012-10-01

    Full Text Available Model Driven Engineering (MDE is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM has been proposed as a profile for UML models of the Web Ontology Language (OWL. In this context, transformations of UML models can be mapped into ODM/OWL transformations. On the other hand, model validation is a crucial task in model transformation. Meta-modeling permits to give a syntactic structure to source and target models. However, semantic requirements have to be imposed on source and target models. A given transformation will be sound when source and target models fulfill the syntactic and semantic requirements. In this paper, we present an approach for model validation in ODM based transformations. Adopting a logic programming based transformational approach we will show how it is possible to transform and validate models. Properties to be validated range from structural and semantic requirements of models (pre and post conditions to properties of the transformation (invariants. The approach has been applied to a well-known example of model transformation: the Entity-Relationship (ER to Relational Model (RM transformation.

  18. A broad view of model validation

    International Nuclear Information System (INIS)

    Tsang, C.F.

    1989-10-01

    The safety assessment of a nuclear waste repository requires the use of models. Such models need to be validated to ensure, as much as possible, that they are a good representation of the actual processes occurring in the real system. In this paper we attempt to take a broad view by reviewing step by step the modeling process and bringing out the need to validating every step of this process. This model validation includes not only comparison of modeling results with data from selected experiments, but also evaluation of procedures for the construction of conceptual models and calculational models as well as methodologies for studying data and parameter correlation. The need for advancing basic scientific knowledge in related fields, for multiple assessment groups, and for presenting our modeling efforts in open literature to public scrutiny is also emphasized. 16 refs

  19. A improved Network Security Situation Awareness Model

    Directory of Open Access Journals (Sweden)

    Li Fangwei

    2015-08-01

    Full Text Available In order to reflect the situation of network security assessment performance fully and accurately, a new network security situation awareness model based on information fusion was proposed. Network security situation is the result of fusion three aspects evaluation. In terms of attack, to improve the accuracy of evaluation, a situation assessment method of DDoS attack based on the information of data packet was proposed. In terms of vulnerability, a improved Common Vulnerability Scoring System (CVSS was raised and maked the assessment more comprehensive. In terms of node weights, the method of calculating the combined weights and optimizing the result by Sequence Quadratic Program (SQP algorithm which reduced the uncertainty of fusion was raised. To verify the validity and necessity of the method, a testing platform was built and used to test through evaluating 2000 DAPRA data sets. Experiments show that the method can improve the accuracy of evaluation results.

  20. Establishing model credibility involves more than validation

    International Nuclear Information System (INIS)

    Kirchner, T.

    1991-01-01

    One widely used definition of validation is that the quantitative test of the performance of a model through the comparison of model predictions to independent sets of observations from the system being simulated. The ability to show that the model predictions compare well with observations is often thought to be the most rigorous test that can be used to establish credibility for a model in the scientific community. However, such tests are only part of the process used to establish credibility, and in some cases may be either unnecessary or misleading. Naylor and Finger extended the concept of validation to include the establishment of validity for the postulates embodied in the model and the test of assumptions used to select postulates for the model. Validity of postulates is established through concurrence by experts in the field of study that the mathematical or conceptual model contains the structural components and mathematical relationships necessary to adequately represent the system with respect to the goals for the model. This extended definition of validation provides for consideration of the structure of the model, not just its performance, in establishing credibility. Evaluation of a simulation model should establish the correctness of the code and the efficacy of the model within its domain of applicability. (24 refs., 6 figs.)

  1. A last updating evolution model for online social networks

    Science.gov (United States)

    Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

    2013-05-01

    As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

  2. Validating agent based models through virtual worlds.

    Energy Technology Data Exchange (ETDEWEB)

    Lakkaraju, Kiran; Whetzel, Jonathan H.; Lee, Jina; Bier, Asmeret Brooke; Cardona-Rivera, Rogelio E.; Bernstein, Jeremy Ray Rhythm

    2014-01-01

    As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior

  3. Validating User Flows to Protect Software Defined Network Environments

    Directory of Open Access Journals (Sweden)

    Ihsan H. Abdulqadder

    2018-01-01

    Full Text Available Software Defined Network is a promising network paradigm which has led to several security threats in SDN applications that involve user flows, switches, and controllers in the network. Threats as spoofing, tampering, information disclosure, Denial of Service, flow table overloading, and so on have been addressed by many researchers. In this paper, we present novel SDN design to solve three security threats: flow table overloading is solved by constructing a star topology-based architecture, unsupervised hashing method mitigates link spoofing attack, and fuzzy classifier combined with L1-ELM running on a neural network for isolating anomaly packets from normal packets. For effective flow migration Discrete-Time Finite-State Markov Chain model is applied. Extensive simulations using OMNeT++ demonstrate the performance of our proposed approach, which is better at preserving holding time than are other state-of-the-art works from the literature.

  4. Base Flow Model Validation, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The innovation is the systematic "building-block" validation of CFD/turbulence models employing a GUI driven CFD code (RPFM) and existing as well as new data sets to...

  5. Network model of security system

    Directory of Open Access Journals (Sweden)

    Adamczyk Piotr

    2016-01-01

    Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.

  6. Model validation: Correlation for updating

    Indian Academy of Sciences (India)

    In this paper, a review is presented of the various methods which ... to make a direct and objective comparison of specific dynamic properties, measured ..... stiffness matrix is available from the analytical model, is that of reducing or condensing.

  7. Validating EHR clinical models using ontology patterns.

    Science.gov (United States)

    Martínez-Costa, Catalina; Schulz, Stefan

    2017-12-01

    Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Verification and validation for waste disposal models

    International Nuclear Information System (INIS)

    1987-07-01

    A set of evaluation criteria has been developed to assess the suitability of current verification and validation techniques for waste disposal methods. A survey of current practices and techniques was undertaken and evaluated using these criteria with the items most relevant to waste disposal models being identified. Recommendations regarding the most suitable verification and validation practices for nuclear waste disposal modelling software have been made

  9. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  10. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

  11. Tracer travel time and model validation

    International Nuclear Information System (INIS)

    Tsang, Chin-Fu.

    1988-01-01

    The performance assessment of a nuclear waste repository demands much more in comparison to the safety evaluation of any civil constructions such as dams, or the resource evaluation of a petroleum or geothermal reservoir. It involves the estimation of low probability (low concentration) of radionuclide transport extrapolated 1000's of years into the future. Thus models used to make these estimates need to be carefully validated. A number of recent efforts have been devoted to the study of this problem. Some general comments on model validation were given by Tsang. The present paper discusses some issues of validation in regards to radionuclide transport. 5 refs

  12. Target-Centric Network Modeling

    DEFF Research Database (Denmark)

    Mitchell, Dr. William L.; Clark, Dr. Robert M.

    In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

  13. Validating the passenger traffic model for Copenhagen

    DEFF Research Database (Denmark)

    Overgård, Christian Hansen; VUK, Goran

    2006-01-01

    The paper presents a comprehensive validation procedure for the passenger traffic model for Copenhagen based on external data from the Danish national travel survey and traffic counts. The model was validated for the years 2000 to 2004, with 2004 being of particular interest because the Copenhagen...... matched the observed traffic better than those of the transit assignment model. With respect to the metro forecasts, the model over-predicts metro passenger flows by 10% to 50%. The wide range of findings from the project resulted in two actions. First, a project was started in January 2005 to upgrade...

  14. Disruption Tolerant Networking Flight Validation Experiment on NASA's EPOXI Mission

    Science.gov (United States)

    Wyatt, Jay; Burleigh, Scott; Jones, Ross; Torgerson, Leigh; Wissler, Steve

    2009-01-01

    In October and November of 2008, the Jet Propulsion Laboratory installed and tested essential elements of Delay/Disruption Tolerant Networking (DTN) technology on the Deep Impact spacecraft. This experiment, called Deep Impact Network Experiment (DINET), was performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. During DINET some 300 images were transmitted from the JPL nodes to the spacecraft. Then they were automatically forwarded from the spacecraft back to the JPL nodes, exercising DTN's bundle origination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days. All transmitted bundles were successfully received, without corruption. The DINET experiment demonstrated DTN readiness for operational use in space missions. This activity was part of a larger NASA space DTN development program to mature DTN to flight readiness for a wide variety of mission types by the end of 2011. This paper describes the DTN protocols, the flight demo implementation, validation metrics which were created for the experiment, and validation results.

  15. Statistically validated network of portfolio overlaps and systemic risk.

    Science.gov (United States)

    Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien

    2016-12-21

    Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007-2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).

  16. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

    OpenAIRE

    Li, Jibin; Lau, Joseph T. F.; Mo, Phoenix K. H.; Su, Xuefen; Wu, Anise M. S.; Tang, Jie; Qin, Zuguo

    2016-01-01

    Background Online social networking use has been integrated into adolescents? daily life and the intensity of online social networking use may have important consequences on adolescents? well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. Methods A total of 910 students who were social networking...

  17. BIOMOVS: an international model validation study

    International Nuclear Information System (INIS)

    Haegg, C.; Johansson, G.

    1988-01-01

    BIOMOVS (BIOspheric MOdel Validation Study) is an international study where models used for describing the distribution of radioactive and nonradioactive trace substances in terrestrial and aquatic environments are compared and tested. The main objectives of the study are to compare and test the accuracy of predictions between such models, explain differences in these predictions, recommend priorities for future research concerning the improvement of the accuracy of model predictions and act as a forum for the exchange of ideas, experience and information. (author)

  18. BIOMOVS: An international model validation study

    International Nuclear Information System (INIS)

    Haegg, C.; Johansson, G.

    1987-01-01

    BIOMOVS (BIOspheric MOdel Validation Study) is an international study where models used for describing the distribution of radioactive and nonradioactive trace substances in terrestrial and aquatic environments are compared and tested. The main objectives of the study are to compare and test the accuracy of predictions between such models, explain differences in these predictions, recommend priorities for future research concerning the improvement of the accuracy of model predictions and act as a forum for the exchange of ideas, experience and information. (orig.)

  19. Model validation: a systemic and systematic approach

    International Nuclear Information System (INIS)

    Sheng, G.; Elzas, M.S.; Cronhjort, B.T.

    1993-01-01

    The term 'validation' is used ubiquitously in association with the modelling activities of numerous disciplines including social, political natural, physical sciences, and engineering. There is however, a wide range of definitions which give rise to very different interpretations of what activities the process involves. Analyses of results from the present large international effort in modelling radioactive waste disposal systems illustrate the urgent need to develop a common approach to model validation. Some possible explanations are offered to account for the present state of affairs. The methodology developed treats model validation and code verification in a systematic fashion. In fact, this approach may be regarded as a comprehensive framework to assess the adequacy of any simulation study. (author)

  20. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Neural Network Based Model of an Industrial Oil-Fired Boiler System ...

    African Journals Online (AJOL)

    A two-layer feed-forward neural network with Hyperbolic tangent sigmoid ... The neural network model when subjected to test, using the validation input data; ... Proportional Integral Derivative (PID) Controller is used to control the neural ...

  2. Ground-water models: Validate or invalidate

    Science.gov (United States)

    Bredehoeft, J.D.; Konikow, Leonard F.

    1993-01-01

    The word validation has a clear meaning to both the scientific community and the general public. Within the scientific community the validation of scientific theory has been the subject of philosophical debate. The philosopher of science, Karl Popper, argued that scientific theory cannot be validated, only invalidated. Popper’s view is not the only opinion in this debate; however, many scientists today agree with Popper (including the authors). To the general public, proclaiming that a ground-water model is validated carries with it an aura of correctness that we do not believe many of us who model would claim. We can place all the caveats we wish, but the public has its own understanding of what the word implies. Using the word valid with respect to models misleads the public; verification carries with it similar connotations as far as the public is concerned. Our point is this: using the terms validation and verification are misleading, at best. These terms should be abandoned by the ground-water community.

  3. Creating, generating and comparing random network models with NetworkRandomizer.

    Science.gov (United States)

    Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni

    2016-01-01

    Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.

  4. Model parameter updating using Bayesian networks

    International Nuclear Information System (INIS)

    Treml, C.A.; Ross, Timothy J.

    2004-01-01

    This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

  5. Runoff Modelling in Urban Storm Drainage by Neural Networks

    DEFF Research Database (Denmark)

    Rasmussen, Michael R.; Brorsen, Michael; Schaarup-Jensen, Kjeld

    1995-01-01

    A neural network is used to simulate folw and water levels in a sewer system. The calibration of th neural network is based on a few measured events and the network is validated against measureed events as well as flow simulated with the MOUSE model (Lindberg and Joergensen, 1986). The neural...... network is used to compute flow or water level at selected points in the sewer system, and to forecast the flow from a small residential area. The main advantages of the neural network are the build-in self calibration procedure and high speed performance, but the neural network cannot be used to extract...... knowledge of the runoff process. The neural network was found to simulate 150 times faster than e.g. the MOUSE model....

  6. Model performance analysis and model validation in logistic regression

    Directory of Open Access Journals (Sweden)

    Rosa Arboretti Giancristofaro

    2007-10-01

    Full Text Available In this paper a new model validation procedure for a logistic regression model is presented. At first, we illustrate a brief review of different techniques of model validation. Next, we define a number of properties required for a model to be considered "good", and a number of quantitative performance measures. Lastly, we describe a methodology for the assessment of the performance of a given model by using an example taken from a management study.

  7. Continuum Model for River Networks

    Science.gov (United States)

    Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.

    1995-07-01

    The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.

  8. A discussion on validation of hydrogeological models

    International Nuclear Information System (INIS)

    Carrera, J.; Mousavi, S.F.; Usunoff, E.J.; Sanchez-Vila, X.; Galarza, G.

    1993-01-01

    Groundwater flow and solute transport are often driven by heterogeneities that elude easy identification. It is also difficult to select and describe the physico-chemical processes controlling solute behaviour. As a result, definition of a conceptual model involves numerous assumptions both on the selection of processes and on the representation of their spatial variability. Validating a numerical model by comparing its predictions with actual measurements may not be sufficient for evaluating whether or not it provides a good representation of 'reality'. Predictions will be close to measurements, regardless of model validity, if these are taken from experiments that stress well-calibrated model modes. On the other hand, predictions will be far from measurements when model parameters are very uncertain, even if the model is indeed a very good representation of the real system. Hence, we contend that 'classical' validation of hydrogeological models is not possible. Rather, models should be viewed as theories about the real system. We propose to follow a rigorous modeling approach in which different sources of uncertainty are explicitly recognized. The application of one such approach is illustrated by modeling a laboratory uranium tracer test performed on fresh granite, which was used as Test Case 1b in INTRAVAL. (author)

  9. Structural system identification: Structural dynamics model validation

    Energy Technology Data Exchange (ETDEWEB)

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  10. Applications of autoassociative neural networks for signal validation in accident management

    International Nuclear Information System (INIS)

    Fantoni, P.; Mazzola, A.

    1994-01-01

    The OECD Halden Reactor Project has been working for several years with computer based systems for determination on plant status including early fault detection and signal validation. The method here presented explores the possibility to use a neural network approach to validate important process signals during normal and abnormal plant conditions. In BWR plants, signal validation has two important applications: reliable thermal limits calculation and reliable inputs to other computerized systems that support the operator during accident scenarious. This work shows how a properly trained autoassociative neural network can promptly detect faulty process signal measurements and produce a best estimate of the actual process value. Noise has been artificially added to the input to evaluate the network ability to respond in a very low signal to noise ratio environment. Training and test datasets have been simulated by the real time transient simulator code APROS. Future development addresses the validation of the model through the use of real data from the plant. (author). 5 refs, 17 figs

  11. Bayesian network modeling of operator's state recognition process

    International Nuclear Information System (INIS)

    Hatakeyama, Naoki; Furuta, Kazuo

    2000-01-01

    Nowadays we are facing a difficult problem of establishing a good relation between humans and machines. To solve this problem, we suppose that machine system need to have a model of human behavior. In this study we model the state cognition process of a PWR plant operator as an example. We use a Bayesian network as an inference engine. We incorporate the knowledge hierarchy in the Bayesian network and confirm its validity using the example of PWR plant operator. (author)

  12. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  13. Validation of a metabolic network for Saccharomyces cerevisiae using mixed substrate studies.

    Science.gov (United States)

    Vanrolleghem, P A; de Jong-Gubbels, P; van Gulik, W M; Pronk, J T; van Dijken, J P; Heijnen, S

    1996-01-01

    Setting up a metabolic network model for respiratory growth of Saccharomyces cerevisiae requires the estimation of only two (energetic) stoichiometric parameters: (1) the operational PO ratio and (2) a growth-related maintenance factor k. It is shown, both theoretically and practically, how chemostat cultivations with different mixtures of two substrates allow unique values to be given to these unknowns of the proposed metabolic model. For the yeast and model considered, an effective PO ratio of 1.09 mol of ATP/mol of O (95% confidence interval 1.07-1.11) and a k factor of 0.415 mol of ATP/C-mol of biomass (0.385-0.445) were obtained from biomass substrate yield data on glucose/ethanol mixtures. Symbolic manipulation software proved very valuable in this study as it supported the proof of theoretical identifiability and significantly reduced the necessary computations for parameter estimation. In the transition from 100% glucose to 100% ethanol in the feed, four metabolic regimes occur. Switching between these regimes is determined by cessation of an irreversible reaction and initiation of an alternative reaction. Metabolic network predictions of these metabolic switches compared well with activity measurements of key enzymes. As a second validation of the network, the biomass yield of S. cerevisiae on acetate was also compared to the network prediction. An excellent agreement was found for a network in which acetate transport was modeled with a proton symport, while passive diffusion of acetate gave significantly higher yield predictions.

  14. Validating the Use of Deep Learning Neural Networks for Correction of Large Hydrometric Datasets

    Science.gov (United States)

    Frazier, N.; Ogden, F. L.; Regina, J. A.; Cheng, Y.

    2017-12-01

    Collection and validation of Earth systems data can be time consuming and labor intensive. In particular, high resolution hydrometric data, including rainfall and streamflow measurements, are difficult to obtain due to a multitude of complicating factors. Measurement equipment is subject to clogs, environmental disturbances, and sensor drift. Manual intervention is typically required to identify, correct, and validate these data. Weirs can become clogged and the pressure transducer may float or drift over time. We typically employ a graphical tool called Time Series Editor to manually remove clogs and sensor drift from the data. However, this process is highly subjective and requires hydrological expertise. Two different people may produce two different data sets. To use this data for scientific discovery and model validation, a more consistent method is needed to processes this field data. Deep learning neural networks have proved to be excellent mechanisms for recognizing patterns in data. We explore the use of Recurrent Neural Networks (RNN) to capture the patterns in the data over time using various gating mechanisms (LSTM and GRU), network architectures, and hyper-parameters to build an automated data correction model. We also explore the required amount of manually corrected training data required to train the network for reasonable accuracy. The benefits of this approach are that the time to process a data set is significantly reduced, and the results are 100% reproducible after training is complete. Additionally, we train the RNN and calibrate a physically-based hydrological model against the same portion of data. Both the RNN and the model are applied to the remaining data using a split-sample methodology. Performance of the machine learning is evaluated for plausibility by comparing with the output of the hydrological model, and this analysis identifies potential periods where additional investigation is warranted.

  15. Advanced training simulator models. Implementation and validation

    International Nuclear Information System (INIS)

    Borkowsky, Jeffrey; Judd, Jerry; Belblidia, Lotfi; O'farrell, David; Andersen, Peter

    2008-01-01

    Modern training simulators are required to replicate plant data for both thermal-hydraulic and neutronic response. Replication is required such that reactivity manipulation on the simulator properly trains the operator for reactivity manipulation at the plant. This paper discusses advanced models which perform this function in real-time using the coupled code system THOR/S3R. This code system models the all fluids systems in detail using an advanced, two-phase thermal-hydraulic a model. The nuclear core is modeled using an advanced, three-dimensional nodal method and also by using cycle-specific nuclear data. These models are configured to run interactively from a graphical instructor station or handware operation panels. The simulator models are theoretically rigorous and are expected to replicate the physics of the plant. However, to verify replication, the models must be independently assessed. Plant data is the preferred validation method, but plant data is often not available for many important training scenarios. In the absence of data, validation may be obtained by slower-than-real-time transient analysis. This analysis can be performed by coupling a safety analysis code and a core design code. Such a coupling exists between the codes RELAP5 and SIMULATE-3K (S3K). RELAP5/S3K is used to validate the real-time model for several postulated plant events. (author)

  16. Research on the model of home networking

    Science.gov (United States)

    Yun, Xiang; Feng, Xiancheng

    2007-11-01

    It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

  17. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  18. Energy modelling in sensor networks

    Science.gov (United States)

    Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

    2007-06-01

    Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

  19. Validation of a phytoremediation computer model

    Energy Technology Data Exchange (ETDEWEB)

    Corapcioglu, M Y; Sung, K; Rhykerd, R L; Munster, C; Drew, M [Texas A and M Univ., College Station, TX (United States)

    1999-01-01

    The use of plants to stimulate remediation of contaminated soil is an effective, low-cost cleanup method which can be applied to many different sites. A phytoremediation computer model has been developed to simulate how recalcitrant hydrocarbons interact with plant roots in unsaturated soil. A study was conducted to provide data to validate and calibrate the model. During the study, lysimeters were constructed and filled with soil contaminated with 10 [mg kg[sub -1

  20. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

    2015-01-01

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation

  1. Fracture network created by 3D printer and its validation using CT images

    Science.gov (United States)

    Suzuki, A.; Watanabe, N.; Li, K.; Horne, R. N.

    2017-12-01

    Understanding flow mechanisms in fractured media is essential for geoscientific research and geological development industries. This study used 3D printed fracture networks in order to control the properties of fracture distributions inside the sample. The accuracy and appropriateness of creating samples by the 3D printer was investigated by using a X-ray CT scanner. The CT scan images suggest that the 3D printer is able to reproduce complex three-dimensional spatial distributions of fracture networks. Use of hexane after printing was found to be an effective way to remove wax for the post-treatment. Local permeability was obtained by the cubic law and used to calculate the global mean. The experimental value of the permeability was between the arithmetic and geometric means of the numerical results, which is consistent with conventional studies. This methodology based on 3D printed fracture networks can help validate existing flow modeling and numerical methods.

  2. Fracture network created by 3-D printer and its validation using CT images

    Science.gov (United States)

    Suzuki, Anna; Watanabe, Noriaki; Li, Kewen; Horne, Roland N.

    2017-07-01

    Understanding flow mechanisms in fractured media is essential for geoscientific research and geological development industries. This study used 3-D printed fracture networks in order to control the properties of fracture distributions inside the sample. The accuracy and appropriateness of creating samples by the 3-D printer was investigated by using a X-ray CT scanner. The CT scan images suggest that the 3-D printer is able to reproduce complex three-dimensional spatial distributions of fracture networks. Use of hexane after printing was found to be an effective way to remove wax for the posttreatment. Local permeability was obtained by the cubic law and used to calculate the global mean. The experimental value of the permeability was between the arithmetic and geometric means of the numerical results, which is consistent with conventional studies. This methodology based on 3-D printed fracture networks can help validate existing flow modeling and numerical methods.

  3. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  4. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  5. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

    Science.gov (United States)

    Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

    2018-01-01

    Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

  6. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

    Directory of Open Access Journals (Sweden)

    B. N. Holben

    2018-01-01

    Full Text Available Over the past 24 years, the AErosol RObotic NETwork (AERONET program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

  7. A novel Direct Small World network model

    Directory of Open Access Journals (Sweden)

    LIN Tao

    2016-10-01

    Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.

  8. A methodology for PSA model validation

    International Nuclear Information System (INIS)

    Unwin, S.D.

    1995-09-01

    This document reports Phase 2 of work undertaken by Science Applications International Corporation (SAIC) in support of the Atomic Energy Control Board's Probabilistic Safety Assessment (PSA) review. A methodology is presented for the systematic review and evaluation of a PSA model. These methods are intended to support consideration of the following question: To within the scope and depth of modeling resolution of a PSA study, is the resultant model a complete and accurate representation of the subject plant? This question was identified as a key PSA validation issue in SAIC's Phase 1 project. The validation methods are based on a model transformation process devised to enhance the transparency of the modeling assumptions. Through conversion to a 'success-oriented' framework, a closer correspondence to plant design and operational specifications is achieved. This can both enhance the scrutability of the model by plant personnel, and provide an alternative perspective on the model that may assist in the identification of deficiencies. The model transformation process is defined and applied to fault trees documented in the Darlington Probabilistic Safety Evaluation. A tentative real-time process is outlined for implementation and documentation of a PSA review based on the proposed methods. (author). 11 refs., 9 tabs., 30 refs

  9. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

    Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

    1994-01-01

    An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

  10. Validation of the STAFF-5 computer model

    International Nuclear Information System (INIS)

    Fletcher, J.F.; Fields, S.R.

    1981-04-01

    STAFF-5 is a dynamic heat-transfer-fluid-flow stress model designed for computerized prediction of the temperature-stress performance of spent LWR fuel assemblies under storage/disposal conditions. Validation of the temperature calculating abilities of this model was performed by comparing temperature calculations under specified conditions to experimental data from the Engine Maintenance and Dissassembly (EMAD) Fuel Temperature Test Facility and to calculations performed by Battelle Pacific Northwest Laboratory (PNL) using the HYDRA-1 model. The comparisons confirmed the ability of STAFF-5 to calculate representative fuel temperatures over a considerable range of conditions, as a first step in the evaluation and prediction of fuel temperature-stress performance

  11. A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

    International Nuclear Information System (INIS)

    Mott, J.E.; King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D.

    1992-01-01

    The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system

  12. A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

    Energy Technology Data Exchange (ETDEWEB)

    Mott, J.E. [Advanced Modeling Techniques Corp., Idaho Falls, ID (United States); King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D. [Argonne National Lab., Idaho Falls, ID (United States)

    1992-03-06

    The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system.

  13. SPR Hydrostatic Column Model Verification and Validation.

    Energy Technology Data Exchange (ETDEWEB)

    Bettin, Giorgia [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lord, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rudeen, David Keith [Gram, Inc. Albuquerque, NM (United States)

    2015-10-01

    A Hydrostatic Column Model (HCM) was developed to help differentiate between normal "tight" well behavior and small-leak behavior under nitrogen for testing the pressure integrity of crude oil storage wells at the U.S. Strategic Petroleum Reserve. This effort was motivated by steady, yet distinct, pressure behavior of a series of Big Hill caverns that have been placed under nitrogen for extended period of time. This report describes the HCM model, its functional requirements, the model structure and the verification and validation process. Different modes of operation are also described, which illustrate how the software can be used to model extended nitrogen monitoring and Mechanical Integrity Tests by predicting wellhead pressures along with nitrogen interface movements. Model verification has shown that the program runs correctly and it is implemented as intended. The cavern BH101 long term nitrogen test was used to validate the model which showed very good agreement with measured data. This supports the claim that the model is, in fact, capturing the relevant physical phenomena and can be used to make accurate predictions of both wellhead pressure and interface movements.

  14. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  15. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  16. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  17. Network bandwidth utilization forecast model on high bandwidth networks

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-03-30

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  18. Grand canonical validation of the bipartite international trade network

    Science.gov (United States)

    Straka, Mika J.; Caldarelli, Guido; Saracco, Fabio

    2017-08-01

    Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

  19. Grand canonical validation of the bipartite international trade network.

    Science.gov (United States)

    Straka, Mika J; Caldarelli, Guido; Saracco, Fabio

    2017-08-01

    Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

  20. Super capacitor modeling with artificial neural network (ANN)

    Energy Technology Data Exchange (ETDEWEB)

    Marie-Francoise, J.N.; Gualous, H.; Berthon, A. [Universite de Franche-Comte, Lab. en Electronique, Electrotechnique et Systemes (L2ES), UTBM, INRETS (LRE T31) 90 - Belfort (France)

    2004-07-01

    This paper presents super-capacitors modeling using Artificial Neural Network (ANN). The principle consists on a black box nonlinear multiple inputs single output (MISO) model. The system inputs are temperature and current, the output is the super-capacitor voltage. The learning and the validation of the ANN model from experimental charge and discharge of super-capacitor establish the relationship between inputs and output. The learning and the validation of the ANN model use experimental results of 2700 F, 3700 F and a super-capacitor pack. Once the network is trained, the ANN model can predict the super-capacitor behaviour with temperature variations. The update parameters of the ANN model are performed thanks to Levenberg-Marquardt method in order to minimize the error between the output of the system and the predicted output. The obtained results with the ANN model of super-capacitor and experimental ones are in good agreement. (authors)

  1. Natural analogues and radionuclide transport model validation

    International Nuclear Information System (INIS)

    Lever, D.A.

    1987-08-01

    In this paper, some possible roles for natural analogues are discussed from the point of view of those involved with the development of mathematical models for radionuclide transport and with the use of these models in repository safety assessments. The characteristic features of a safety assessment are outlined in order to address the questions of where natural analogues can be used to improve our understanding of the processes involved and where they can assist in validating the models that are used. Natural analogues have the potential to provide useful information about some critical processes, especially long-term chemical processes and migration rates. There is likely to be considerable uncertainty and ambiguity associated with the interpretation of natural analogues, and thus it is their general features which should be emphasized, and models with appropriate levels of sophistication should be used. Experience gained in modelling the Koongarra uranium deposit in northern Australia is drawn upon. (author)

  2. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  3. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  4. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  5. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

    2010-01-01

    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  6. External validation of EPIWIN biodegradation models.

    Science.gov (United States)

    Posthumus, R; Traas, T P; Peijnenburg, W J G M; Hulzebos, E M

    2005-01-01

    The BIOWIN biodegradation models were evaluated for their suitability for regulatory purposes. BIOWIN includes the linear and non-linear BIODEG and MITI models for estimating the probability of rapid aerobic biodegradation and an expert survey model for primary and ultimate biodegradation estimation. Experimental biodegradation data for 110 newly notified substances were compared with the estimations of the different models. The models were applied separately and in combinations to determine which model(s) showed the best performance. The results of this study were compared with the results of other validation studies and other biodegradation models. The BIOWIN models predict not-readily biodegradable substances with high accuracy in contrast to ready biodegradability. In view of the high environmental concern of persistent chemicals and in view of the large number of not-readily biodegradable chemicals compared to the readily ones, a model is preferred that gives a minimum of false positives without a corresponding high percentage false negatives. A combination of the BIOWIN models (BIOWIN2 or BIOWIN6) showed the highest predictive value for not-readily biodegradability. However, the highest score for overall predictivity with lowest percentage false predictions was achieved by applying BIOWIN3 (pass level 2.75) and BIOWIN6.

  7. Neural Network Based Models for Fusion Applications

    Science.gov (United States)

    Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

    2017-10-01

    Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-­network (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.

  8. Spinal Cord Injury Model System Information Network

    Science.gov (United States)

    ... the UAB-SCIMS More The UAB-SCIMS Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network as a resource to promote knowledge in the ...

  9. Eight challenges for network epidemic models

    Directory of Open Access Journals (Sweden)

    Lorenzo Pellis

    2015-03-01

    Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

  10. Validation of a phytoremediation computer model

    International Nuclear Information System (INIS)

    Corapcioglu, M.Y.; Sung, K.; Rhykerd, R.L.; Munster, C.; Drew, M.

    1999-01-01

    The use of plants to stimulate remediation of contaminated soil is an effective, low-cost cleanup method which can be applied to many different sites. A phytoremediation computer model has been developed to simulate how recalcitrant hydrocarbons interact with plant roots in unsaturated soil. A study was conducted to provide data to validate and calibrate the model. During the study, lysimeters were constructed and filled with soil contaminated with 10 [mg kg -1 ] TNT, PBB and chrysene. Vegetated and unvegetated treatments were conducted in triplicate to obtain data regarding contaminant concentrations in the soil, plant roots, root distribution, microbial activity, plant water use and soil moisture. When given the parameters of time and depth, the model successfully predicted contaminant concentrations under actual field conditions. Other model parameters are currently being evaluated. 15 refs., 2 figs

  11. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  12. Entropy Characterization of Random Network Models

    Directory of Open Access Journals (Sweden)

    Pedro J. Zufiria

    2017-06-01

    Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

  13. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  14. Introducing Synchronisation in Deterministic Network Models

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

    2006-01-01

    The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

  15. Towards policy relevant environmental modeling: contextual validity and pragmatic models

    Science.gov (United States)

    Miles, Scott B.

    2000-01-01

    "What makes for a good model?" In various forms, this question is a question that, undoubtedly, many people, businesses, and institutions ponder with regards to their particular domain of modeling. One particular domain that is wrestling with this question is the multidisciplinary field of environmental modeling. Examples of environmental models range from models of contaminated ground water flow to the economic impact of natural disasters, such as earthquakes. One of the distinguishing claims of the field is the relevancy of environmental modeling to policy and environment-related decision-making in general. A pervasive view by both scientists and decision-makers is that a "good" model is one that is an accurate predictor. Thus, determining whether a model is "accurate" or "correct" is done by comparing model output to empirical observations. The expected outcome of this process, usually referred to as "validation" or "ground truthing," is a stamp on the model in question of "valid" or "not valid" that serves to indicate whether or not the model will be reliable before it is put into service in a decision-making context. In this paper, I begin by elaborating on the prevailing view of model validation and why this view must change. Drawing from concepts coming out of the studies of science and technology, I go on to propose a contextual view of validity that can overcome the problems associated with "ground truthing" models as an indicator of model goodness. The problem of how we talk about and determine model validity has much to do about how we perceive the utility of environmental models. In the remainder of the paper, I argue that we should adopt ideas of pragmatism in judging what makes for a good model and, in turn, developing good models. From such a perspective of model goodness, good environmental models should facilitate communication, convey—not bury or "eliminate"—uncertainties, and, thus, afford the active building of consensus decisions, instead

  16. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  17. Concepts of Model Verification and Validation

    International Nuclear Information System (INIS)

    Thacker, B.H.; Doebling, S.W.; Hemez, F.M.; Anderson, M.C.; Pepin, J.E.; Rodriguez, E.A.

    2004-01-01

    Model verification and validation (VandV) is an enabling methodology for the development of computational models that can be used to make engineering predictions with quantified confidence. Model VandV procedures are needed by government and industry to reduce the time, cost, and risk associated with full-scale testing of products, materials, and weapon systems. Quantifying the confidence and predictive accuracy of model calculations provides the decision-maker with the information necessary for making high-consequence decisions. The development of guidelines and procedures for conducting a model VandV program are currently being defined by a broad spectrum of researchers. This report reviews the concepts involved in such a program. Model VandV is a current topic of great interest to both government and industry. In response to a ban on the production of new strategic weapons and nuclear testing, the Department of Energy (DOE) initiated the Science-Based Stockpile Stewardship Program (SSP). An objective of the SSP is to maintain a high level of confidence in the safety, reliability, and performance of the existing nuclear weapons stockpile in the absence of nuclear testing. This objective has challenged the national laboratories to develop high-confidence tools and methods that can be used to provide credible models needed for stockpile certification via numerical simulation. There has been a significant increase in activity recently to define VandV methods and procedures. The U.S. Department of Defense (DoD) Modeling and Simulation Office (DMSO) is working to develop fundamental concepts and terminology for VandV applied to high-level systems such as ballistic missile defense and battle management simulations. The American Society of Mechanical Engineers (ASME) has recently formed a Standards Committee for the development of VandV procedures for computational solid mechanics models. The Defense Nuclear Facilities Safety Board (DNFSB) has been a proponent of model

  18. A validated physical model of greenhouse climate

    International Nuclear Information System (INIS)

    Bot, G.P.A.

    1989-01-01

    In the greenhouse model the momentaneous environmental crop growth factors are calculated as output, together with the physical behaviour of the crop. The boundary conditions for this model are the outside weather conditions; other inputs are the physical characteristics of the crop, of the greenhouse and of the control system. The greenhouse model is based on the energy, water vapour and CO 2 balances of the crop-greenhouse system. While the emphasis is on the dynamic behaviour of the greenhouse for implementation in continuous optimization, the state variables temperature, water vapour pressure and carbondioxide concentration in the relevant greenhouse parts crop, air, soil and cover are calculated from the balances over these parts. To do this in a proper way, the physical exchange processes between the system parts have to be quantified first. Therefore the greenhouse model is constructed from submodels describing these processes: a. Radiation transmission model for the modification of the outside to the inside global radiation. b. Ventilation model to describe the ventilation exchange between greenhouse and outside air. c. The description of the exchange of energy and mass between the crop and the greenhouse air. d. Calculation of the thermal radiation exchange between the various greenhouse parts. e. Quantification of the convective exchange processes between the greenhouse air and respectively the cover, the heating pipes and the soil surface and between the cover and the outside air. f. Determination of the heat conduction in the soil. The various submodels are validated first and then the complete greenhouse model is verified

  19. Model checking mobile ad hoc networks

    NARCIS (Netherlands)

    Ghassemi, Fatemeh; Fokkink, Wan

    2016-01-01

    Modeling arbitrary connectivity changes within mobile ad hoc networks (MANETs) makes application of automated formal verification challenging. We use constrained labeled transition systems as a semantic model to represent mobility. To model check MANET protocols with respect to the underlying

  20. Validated predictive modelling of the environmental resistome.

    Science.gov (United States)

    Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

    2015-06-01

    Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

  1. Validity of information security policy models

    Directory of Open Access Journals (Sweden)

    Joshua Onome Imoniana

    Full Text Available Validity is concerned with establishing evidence for the use of a method to be used with a particular set of population. Thus, when we address the issue of application of security policy models, we are concerned with the implementation of a certain policy, taking into consideration the standards required, through attribution of scores to every item in the research instrument. En today's globalized economic scenarios, the implementation of information security policy, in an information technology environment, is a condition sine qua non for the strategic management process of any organization. Regarding this topic, various studies present evidences that, the responsibility for maintaining a policy rests primarily with the Chief Security Officer. The Chief Security Officer, in doing so, strives to enhance the updating of technologies, in order to meet all-inclusive business continuity planning policies. Therefore, for such policy to be effective, it has to be entirely embraced by the Chief Executive Officer. This study was developed with the purpose of validating specific theoretical models, whose designs were based on literature review, by sampling 10 of the Automobile Industries located in the ABC region of Metropolitan São Paulo City. This sampling was based on the representativeness of such industries, particularly with regards to each one's implementation of information technology in the region. The current study concludes, presenting evidence of the discriminating validity of four key dimensions of the security policy, being such: the Physical Security, the Logical Access Security, the Administrative Security, and the Legal & Environmental Security. On analyzing the Alpha of Crombach structure of these security items, results not only attest that the capacity of those industries to implement security policies is indisputable, but also, the items involved, homogeneously correlate to each other.

  2. Polarographic validation of chemical speciation models

    International Nuclear Information System (INIS)

    Duffield, J.R.; Jarratt, J.A.

    2001-01-01

    It is well established that the chemical speciation of an element in a given matrix, or system of matrices, is of fundamental importance in controlling the transport behaviour of the element. Therefore, to accurately understand and predict the transport of elements and compounds in the environment it is a requirement that both the identities and concentrations of trace element physico-chemical forms can be ascertained. These twin requirements present the analytical scientist with considerable challenges given the labile equilibria, the range of time scales (from nanoseconds to years) and the range of concentrations (ultra-trace to macro) that may be involved. As a result of this analytical variability, chemical equilibrium modelling has become recognised as an important predictive tool in chemical speciation analysis. However, this technique requires firm underpinning by the use of complementary experimental techniques for the validation of the predictions made. The work reported here has been undertaken with the primary aim of investigating possible methodologies that can be used for the validation of chemical speciation models. However, in approaching this aim, direct chemical speciation analyses have been made in their own right. Results will be reported and analysed for the iron(II)/iron(III)-citrate proton system (pH 2 to 10; total [Fe] = 3 mmol dm -3 ; total [citrate 3- ] 10 mmol dm -3 ) in which equilibrium constants have been determined using glass electrode potentiometry, speciation is predicted using the PHREEQE computer code, and validation of predictions is achieved by determination of iron complexation and redox state with associated concentrations. (authors)

  3. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  4. Assessment model validity document FARF31

    International Nuclear Information System (INIS)

    Elert, Mark; Gylling Bjoern; Lindgren, Maria

    2004-08-01

    The prime goal of model validation is to build confidence in the model concept and that the model is fit for its intended purpose. In other words: Does the model predict transport in fractured rock adequately to be used in repository performance assessments. Are the results reasonable for the type of modelling tasks the model is designed for. Commonly, in performance assessments a large number of realisations of flow and transport is made to cover the associated uncertainties. Thus, the flow and transport including radioactive chain decay are preferably calculated in the same model framework. A rather sophisticated concept is necessary to be able to model flow and radionuclide transport in the near field and far field of a deep repository, also including radioactive chain decay. In order to avoid excessively long computational times there is a need for well-based simplifications. For this reason, the far field code FARF31 is made relatively simple, and calculates transport by using averaged entities to represent the most important processes. FARF31 has been shown to be suitable for the performance assessments within the SKB studies, e.g. SR 97. Among the advantages are that it is a fast, simple and robust code, which enables handling of many realisations with wide spread in parameters in combination with chain decay of radionuclides. Being a component in the model chain PROPER, it is easy to assign statistical distributions to the input parameters. Due to the formulation of the advection-dispersion equation in FARF31 it is possible to perform the groundwater flow calculations separately.The basis for the modelling is a stream tube, i.e. a volume of rock including fractures with flowing water, with the walls of the imaginary stream tube defined by streamlines. The transport within the stream tube is described using a dual porosity continuum approach, where it is assumed that rock can be divided into two distinct domains with different types of porosity

  5. Modelling and validation of electromechanical shock absorbers

    Science.gov (United States)

    Tonoli, Andrea; Amati, Nicola; Girardello Detoni, Joaquim; Galluzzi, Renato; Gasparin, Enrico

    2013-08-01

    Electromechanical vehicle suspension systems represent a promising substitute to conventional hydraulic solutions. However, the design of electromechanical devices that are able to supply high damping forces without exceeding geometric dimension and mass constraints is a difficult task. All these challenges meet in off-road vehicle suspension systems, where the power density of the dampers is a crucial parameter. In this context, the present paper outlines a particular shock absorber configuration where a suitable electric machine and a transmission mechanism are utilised to meet off-road vehicle requirements. A dynamic model is used to represent the device. Subsequently, experimental tests are performed on an actual prototype to verify the functionality of the damper and validate the proposed model.

  6. Neural networks for sensor validation and plant monitoring

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Eryurek, E.; Mathai, G.

    1990-01-01

    Sensor and process monitoring in power plants require the estimation of one or more process variables. Neural network paradigms are suitable for establishing general nonlinear relationships among a set of plant variables. Multiple-input multiple-output autoassociative networks can follow changes in plant-wide behavior. The backpropagation algorithm has been applied for training feedforward networks. A new and enhanced algorithm for training neural networks (BPN) has been developed and implemented in a VAX workstation. Operational data from the Experimental Breeder Reactor-II (EBR-II) have been used to study the performance of BPN. Several results of application to the EBR-II are presented

  7. A Simplified Network Model for Travel Time Reliability Analysis in a Road Network

    Directory of Open Access Journals (Sweden)

    Kenetsu Uchida

    2017-01-01

    Full Text Available This paper proposes a simplified network model which analyzes travel time reliability in a road network. A risk-averse driver is assumed in the simplified model. The risk-averse driver chooses a path by taking into account both a path travel time variance and a mean path travel time. The uncertainty addressed in this model is that of traffic flows (i.e., stochastic demand flows. In the simplified network model, the path travel time variance is not calculated by considering all travel time covariance between two links in the network. The path travel time variance is calculated by considering all travel time covariance between two adjacent links in the network. Numerical experiments are carried out to illustrate the applicability and validity of the proposed model. The experiments introduce the path choice behavior of a risk-neutral driver and several types of risk-averse drivers. It is shown that the mean link flows calculated by introducing the risk-neutral driver differ as a whole from those calculated by introducing several types of risk-averse drivers. It is also shown that the mean link flows calculated by the simplified network model are almost the same as the flows calculated by using the exact path travel time variance.

  8. Atmospheric corrosion: statistical validation of models

    International Nuclear Information System (INIS)

    Diaz, V.; Martinez-Luaces, V.; Guineo-Cobs, G.

    2003-01-01

    In this paper we discuss two different methods for validation of regression models, applied to corrosion data. One of them is based on the correlation coefficient and the other one is the statistical test of lack of fit. Both methods are used here to analyse fitting of bi logarithmic model in order to predict corrosion for very low carbon steel substrates in rural and urban-industrial atmospheres in Uruguay. Results for parameters A and n of the bi logarithmic model are reported here. For this purpose, all repeated values were used instead of using average values as usual. Modelling is carried out using experimental data corresponding to steel substrates under the same initial meteorological conditions ( in fact, they are put in the rack at the same time). Results of correlation coefficient are compared with the lack of it tested at two different signification levels (α=0.01 and α=0.05). Unexpected differences between them are explained and finally, it is possible to conclude, at least in the studied atmospheres, that the bi logarithmic model does not fit properly the experimental data. (Author) 18 refs

  9. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

  10. Experimental validation of models for Plasma Focus devices

    International Nuclear Information System (INIS)

    Rodriguez Palomino, Luis; Gonzalez, Jose; Clausse, Alejandro

    2003-01-01

    Plasma Focus(PF) Devices are thermonuclear pulsators that produce short pulsed radiation (X-ray, charged particles and neutrons). Since Filippov and Mather, investigations have been used to study plasma properties. Nowadays the interest about PF is focused in technology applications, related to the use of these devices as pulsed neutron sources. In the numerical calculus the Inter institutional PLADEMA (PLAsmas DEnsos MAgnetizados) network is developing three models. Each one is useful in different engineering stages of the Plasma Focus design. One of the main objectives in this work is a comparative study on the influence of the different parameters involved in each models. To validate these results, several experimental measurements under different geometry and initial conditions were performed. (author)

  11. Network structure exploration via Bayesian nonparametric models

    International Nuclear Information System (INIS)

    Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

    2015-01-01

    Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

  12. SDG and qualitative trend based model multiple scale validation

    Science.gov (United States)

    Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

    2017-09-01

    Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

  13. The meaning and validation of social support networks for close family of persons with advanced cancer

    Directory of Open Access Journals (Sweden)

    Sjolander Catarina

    2012-09-01

    Full Text Available Abstract Background To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study’s empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Methods Seventeen family members with a relative who 8–14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. Results The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. Conclusions The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could

  14. The meaning and validation of social support networks for close family of persons with advanced cancer.

    Science.gov (United States)

    Sjolander, Catarina; Ahlstrom, Gerd

    2012-09-17

    To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study's empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Seventeen family members with a relative who 8-14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could encourage nurses and other health-care professionals to focus on family members

  15. Unit testing, model validation, and biological simulation.

    Science.gov (United States)

    Sarma, Gopal P; Jacobs, Travis W; Watts, Mark D; Ghayoomie, S Vahid; Larson, Stephen D; Gerkin, Richard C

    2016-01-01

    The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

  16. Contaminant transport model validation: The Oak Ridge Reservation

    International Nuclear Information System (INIS)

    Lee, R.R.; Ketelle, R.H.

    1988-09-01

    In the complex geologic setting on the Oak Ridge Reservation, hydraulic conductivity is anisotropic and flow is strongly influenced by an extensive and largely discontinuous fracture network. Difficulties in describing and modeling the aquifer system prompted a study to obtain aquifer property data to be used in a groundwater flow model validation experiment. Characterization studies included the performance of an extensive suite of aquifer test within a 600-square-meter area to obtain aquifer property values to describe the flow field in detail. Following aquifer test, a groundwater tracer test was performed under ambient conditions to verify the aquifer analysis. Tracer migration data in the near-field were used in model calibration to predict tracer arrival time and concentration in the far-field. Despite the extensive aquifer testing, initial modeling inaccurately predicted tracer migration direction. Initial tracer migration rates were consistent with those predicted by the model; however, changing environmental conditions resulted in an unanticipated decay in tracer movement. Evaluation of the predictive accuracy of groundwater flow and contaminant transport models on the Oak Ridge Reservation depends on defining the resolution required, followed by field testing and model grid definition at compatible scales. The use of tracer tests, both as a characterization method and to verify model results, provides the highest level of resolution of groundwater flow characteristics. 3 refs., 4 figs

  17. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  18. Validating Farmers' Indigenous Social Networks for Local Seed Supply in Central Rift Valley of Ethiopia

    NARCIS (Netherlands)

    Seboka, B.; Deressa, A.

    2000-01-01

    Indigenous social networks of Ethiopian farmers participate in seed exchange based on mutual interdependence and trust. A government-imposed extension program must validate the role of local seed systems in developing a national seed industry

  19. Feature selection for anomaly–based network intrusion detection using cluster validity indices

    CSIR Research Space (South Africa)

    Naidoo, Tyrone

    2015-09-01

    Full Text Available data, which is rarely available in operational networks. It uses normalized cluster validity indices as an objective function that is optimized over the search space of candidate feature subsets via a genetic algorithm. Feature sets produced...

  20. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  1. Using consensus bayesian network to model the reactive oxygen species regulatory pathway.

    Directory of Open Access Journals (Sweden)

    Liangdong Hu

    Full Text Available Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data directly. Although large numbers of bayesian network learning algorithms have been developed, when applying them to learn bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn bayesian networks contain too few microarray data. In this paper, we propose a consensus bayesian network which is constructed by combining bayesian networks from relevant literatures and bayesian networks learned from microarray data. It would have a higher accuracy than the bayesian networks learned from one database. In the experiment, we validated the bayesian network combination algorithm on several classic machine learning databases and used the consensus bayesian network to model the Escherichia coli's ROS pathway.

  2. HIV lipodystrophy case definition using artificial neural network modelling

    DEFF Research Database (Denmark)

    Ioannidis, John P A; Trikalinos, Thomas A; Law, Matthew

    2003-01-01

    OBJECTIVE: A case definition of HIV lipodystrophy has recently been developed from a combination of clinical, metabolic and imaging/body composition variables using logistic regression methods. We aimed to evaluate whether artificial neural networks could improve the diagnostic accuracy. METHODS......: The database of the case-control Lipodystrophy Case Definition Study was split into 504 subjects (265 with and 239 without lipodystrophy) used for training and 284 independent subjects (152 with and 132 without lipodystrophy) used for validation. Back-propagation neural networks with one or two middle layers...... were trained and validated. Results were compared against logistic regression models using the same information. RESULTS: Neural networks using clinical variables only (41 items) achieved consistently superior performance than logistic regression in terms of specificity, overall accuracy and area under...

  3. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    . The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

  4. MAAP4 model and validation status

    International Nuclear Information System (INIS)

    Plys, M.G.; Paik, C.Y.; Henry, R.E.; Wu, Chunder; Suh, K.Y.; Sung Jin Lee; McCartney, M.A.; Wang, Zhe

    1993-01-01

    The MAAP 4 code for integrated severe accident analysis is intended to be used for Level 1 and Level 2 probabilistic safety assessment and severe accident management evaluations for current and advanced light water reactors. MAAP 4 can be used to determine which accidents lead to fuel damage and which are successfully terminated which accidents lead to fuel damage and which are successfully terminated before or after fuel damage (a level 1 application). It can also be used to determine which sequences result in fission product release to the environment and provide the time history of such releases (a level 2 application). The MAAP 4 thermal-hydraulic and fission product models and their validation are discussed here. This code is the newest version of MAAP offered by the Electric Power Research Institute (EPRI) and it contains substantial mechanistic improvements over its predecessor, MAAP 3.0B

  5. Port Hamiltonian modeling of Power Networks

    NARCIS (Netherlands)

    van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R

    2012-01-01

    In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all

  6. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...

  7. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  8. Network interconnections: an architectural reference model

    NARCIS (Netherlands)

    Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.

    1985-01-01

    One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for

  9. Performance modeling of network data services

    Energy Technology Data Exchange (ETDEWEB)

    Haynes, R.A.; Pierson, L.G.

    1997-01-01

    Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.

  10. Validating modeled turbulent heat fluxes across large freshwater surfaces

    Science.gov (United States)

    Lofgren, B. M.; Fujisaki-Manome, A.; Gronewold, A.; Anderson, E. J.; Fitzpatrick, L.; Blanken, P.; Spence, C.; Lenters, J. D.; Xiao, C.; Charusambot, U.

    2017-12-01

    Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the Great Lakes. Validation and improvement of bulk flux algorithms to simulate these turbulent heat fluxes are critical for accurate prediction of hydrodynamics, water levels, weather, and climate over the region. Here we consider five heat flux algorithms from several model systems; the Finite-Volume Community Ocean Model, the Weather Research and Forecasting model, and the Large Lake Thermodynamics Model, which are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system, but interface at the lake surface. The heat flux algorithms were isolated from each model and driven by meteorological data from over-lake stations in the Great Lakes Evaporation Network. The simulation results were compared with eddy covariance flux measurements at the same stations. All models show the capacity to the seasonal cycle of the turbulent heat fluxes. Overall, the Coupled Ocean Atmosphere Response Experiment algorithm in FVCOM has the best agreement with eddy covariance measurements. Simulations with the other four algorithms are overall improved by updating the parameterization of roughness length scales of temperature and humidity. Agreement between modelled and observed fluxes notably varied with geographical locations of the stations. For example, at the Long Point station in Lake Erie, observed fluxes are likely influenced by the upwind land surface while the simulations do not take account of the land surface influence, and therefore the agreement is worse in general.

  11. Discrete fracture modelling for the Stripa tracer validation experiment predictions

    International Nuclear Information System (INIS)

    Dershowitz, W.; Wallmann, P.

    1992-02-01

    Groundwater flow and transport through three-dimensional networks of discrete fractures was modeled to predict the recovery of tracer from tracer injection experiments conducted during phase 3 of the Stripa site characterization and validation protect. Predictions were made on the basis of an updated version of the site scale discrete fracture conceptual model used for flow predictions and preliminary transport modelling. In this model, individual fractures were treated as stochastic features described by probability distributions of geometric and hydrologic properties. Fractures were divided into three populations: Fractures in fracture zones near the drift, non-fracture zone fractures within 31 m of the drift, and fractures in fracture zones over 31 meters from the drift axis. Fractures outside fracture zones are not modelled beyond 31 meters from the drift axis. Transport predictions were produced using the FracMan discrete fracture modelling package for each of five tracer experiments. Output was produced in the seven formats specified by the Stripa task force on fracture flow modelling. (au)

  12. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

    2017-01-01

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes

  13. Network models in economics and finance

    CERN Document Server

    Pardalos, Panos; Rassias, Themistocles

    2014-01-01

    Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis  that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

  14. Modeling Marine Electromagnetic Survey with Radial Basis Function Networks

    Directory of Open Access Journals (Sweden)

    Agus Arif

    2014-11-01

    Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.

  15. Neural Network Models for Free Radical Polymerization of Methyl Methacrylate

    International Nuclear Information System (INIS)

    Curteanu, S.; Leon, F.; Galea, D.

    2003-01-01

    In this paper, a neural network modeling of the batch bulk methyl methacrylate polymerization is performed. To obtain conversion, number and weight average molecular weights, three neural networks were built. Each was a multilayer perception with one or two hidden layers. The choice of network topology, i.e. the number of hidden layers and the number of neurons in these layers, was based on achieving a compromise between precision and complexity. Thus, it was intended to have an error as small as possible at the end of back-propagation training phases, while using a network with reduced complexity. The performances of the networks were evaluated by comparing network predictions with training data, validation data (which were not uses for training), and with the results of a mechanistic model. The accurate predictions of neural networks for monomer conversion, number average molecular weight and weight average molecular weight proves that this modeling methodology gives a good representation and generalization of the batch bulk methyl methacrylate polymerization. (author)

  16. Validation of A Global Hydrological Model

    Science.gov (United States)

    Doell, P.; Lehner, B.; Kaspar, F.; Vassolo, S.

    due to the precipitation mea- surement errors. Even though the explicit modeling of wetlands and lakes leads to a much improved modeling of both the vertical water balance and the lateral transport of water, not enough information is included in WGHM to accurately capture the hy- drology of these water bodies. Certainly, the reliability of model results is highest at the locations at which WGHM was calibrated. The validation indicates that reliability for cells inside calibrated basins is satisfactory if the basin is relatively homogeneous. Analyses of the few available stations outside of calibrated basins indicate a reason- ably high model reliability, particularly in humid regions.

  17. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  18. Citizen science networks in natural history and the collective validation of biodiversity data.

    Science.gov (United States)

    Turnhout, Esther; Lawrence, Anna; Turnhout, Sander

    2016-06-01

    Biodiversity data are in increasing demand to inform policy and management. A substantial portion of these data is generated in citizen science networks. To ensure the quality of biodiversity data, standards and criteria for validation have been put in place. We used interviews and document analysis from the United Kingdom and The Netherlands to examine how data validation serves as a point of connection between the diverse people and practices in natural history citizen science networks. We found that rather than a unidirectional imposition of standards, validation was performed collectively. Specifically, it was enacted in ongoing circulations of biodiversity records between recorders and validators as they jointly negotiated the biodiversity that was observed and the validity of the records. These collective validation practices contributed to the citizen science character or natural history networks and tied these networks together. However, when biodiversity records were included in biodiversity-information initiatives on different policy levels and scales, the circulation of records diminished. These initiatives took on a more extractive mode of data use. Validation ceased to be collective with important consequences for the natural history networks involved and citizen science more generally. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

  19. Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks

    DEFF Research Database (Denmark)

    Yan, Ying; Dittmann, Lars

    2011-01-01

    In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...... by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....

  20. Synergistic effects in threshold models on networks

    Science.gov (United States)

    Juul, Jonas S.; Porter, Mason A.

    2018-01-01

    Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

  1. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  2. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  3. Methods and procedures for the verification and validation of artificial neural networks

    CERN Document Server

    Taylor, Brian J

    2006-01-01

    Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. This volume introduces some of the methods and techniques used for the verification and validation of neural networks and adaptive systems.

  4. Towards reproducible descriptions of neuronal network models.

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2009-08-01

    Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.

  5. Improved Maximum Parsimony Models for Phylogenetic Networks.

    Science.gov (United States)

    Van Iersel, Leo; Jones, Mark; Scornavacca, Celine

    2018-05-01

    Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

  6. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  7. A proposed best practice model validation framework for banks

    Directory of Open Access Journals (Sweden)

    Pieter J. (Riaan de Jongh

    2017-06-01

    Full Text Available Background: With the increasing use of complex quantitative models in applications throughout the financial world, model risk has become a major concern. The credit crisis of 2008–2009 provoked added concern about the use of models in finance. Measuring and managing model risk has subsequently come under scrutiny from regulators, supervisors, banks and other financial institutions. Regulatory guidance indicates that meticulous monitoring of all phases of model development and implementation is required to mitigate this risk. Considerable resources must be mobilised for this purpose. The exercise must embrace model development, assembly, implementation, validation and effective governance. Setting: Model validation practices are generally patchy, disparate and sometimes contradictory, and although the Basel Accord and some regulatory authorities have attempted to establish guiding principles, no definite set of global standards exists. Aim: Assessing the available literature for the best validation practices. Methods: This comprehensive literature study provided a background to the complexities of effective model management and focussed on model validation as a component of model risk management. Results: We propose a coherent ‘best practice’ framework for model validation. Scorecard tools are also presented to evaluate if the proposed best practice model validation framework has been adequately assembled and implemented. Conclusion: The proposed best practice model validation framework is designed to assist firms in the construction of an effective, robust and fully compliant model validation programme and comprises three principal elements: model validation governance, policy and process.

  8. Aerosol modelling and validation during ESCOMPTE 2001

    Science.gov (United States)

    Cousin, F.; Liousse, C.; Cachier, H.; Bessagnet, B.; Guillaume, B.; Rosset, R.

    The ESCOMPTE 2001 programme (Atmospheric Research. 69(3-4) (2004) 241) has resulted in an exhaustive set of dynamical, radiative, gas and aerosol observations (surface and aircraft measurements). A previous paper (Atmospheric Research. (2004) in press) has dealt with dynamics and gas-phase chemistry. The present paper is an extension to aerosol formation, transport and evolution. To account for important loadings of primary and secondary aerosols and their transformation processes in the ESCOMPTE domain, the ORISAM aerosol module (Atmospheric Environment. 35 (2001) 4751) was implemented on-line in the air-quality Meso-NH-C model. Additional developments have been introduced in ORganic and Inorganic Spectral Aerosol Module (ORISAM) to improve the comparison between simulations and experimental surface and aircraft field data. This paper discusses this comparison for a simulation performed during one selected day, 24 June 2001, during the Intensive Observation Period IOP2b. Our work relies on BC and OCp emission inventories specifically developed for ESCOMPTE. This study confirms the need for a fine resolution aerosol inventory with spectral chemical speciation. BC levels are satisfactorily reproduced, thus validating our emission inventory and its processing through Meso-NH-C. However, comparisons for reactive species generally denote an underestimation of concentrations. Organic aerosol levels are rather well simulated though with a trend to underestimation in the afternoon. Inorganic aerosol species are underestimated for several reasons, some of them have been identified. For sulphates, primary emissions were introduced. Improvement was obtained too for modelled nitrate and ammonium levels after introducing heterogeneous chemistry. However, no modelling of terrigeneous particles is probably a major cause for nitrates and ammonium underestimations. Particle numbers and size distributions are well reproduced, but only in the submicrometer range. Our work points out

  9. An information search model for online social Networks - MOBIRSE

    Directory of Open Access Journals (Sweden)

    Miguel Angel Niño Zambrano

    2015-09-01

    Full Text Available Online Social Networks (OSNs have been gaining great importance among Internet users in recent years.  These are sites where it is possible to meet people, publish, and share content in a way that is both easy and free of charge. As a result, the volume of information contained in these websites has grown exponentially, and web search has consequently become an important tool for users to easily find information relevant to their social networking objectives. Making use of ontologies and user profiles can make these searches more effective. This article presents a model for Information Retrieval in OSNs (MOBIRSE based on user profile and ontologies which aims to improve the relevance of retrieved information on these websites. The social network Facebook was chosen for a case study and as the instance for the proposed model. The model was validated using measures such as At-k Precision and Kappa statistics, to assess its efficiency.

  10. Use of artificial neural networks for transport energy demand modeling

    International Nuclear Information System (INIS)

    Murat, Yetis Sazi; Ceylan, Halim

    2006-01-01

    The paper illustrates an artificial neural network (ANN) approach based on supervised neural networks for the transport energy demand forecasting using socio-economic and transport related indicators. The ANN transport energy demand model is developed. The actual forecast is obtained using a feed forward neural network, trained with back propagation algorithm. In order to investigate the influence of socio-economic indicators on the transport energy demand, the ANN is analyzed based on gross national product (GNP), population and the total annual average veh-km along with historical energy data available from 1970 to 2001. Comparing model predictions with energy data in testing period performs the model validation. The projections are made with two scenarios. It is obtained that the ANN reflects the fluctuation in historical data for both dependent and independent variables. The results obtained bear out the suitability of the adopted methodology for the transport energy-forecasting problem

  11. Geochemistry Model Validation Report: Material Degradation and Release Model

    Energy Technology Data Exchange (ETDEWEB)

    H. Stockman

    2001-09-28

    The purpose of this Analysis and Modeling Report (AMR) is to validate the Material Degradation and Release (MDR) model that predicts degradation and release of radionuclides from a degrading waste package (WP) in the potential monitored geologic repository at Yucca Mountain. This AMR is prepared according to ''Technical Work Plan for: Waste Package Design Description for LA'' (Ref. 17). The intended use of the MDR model is to estimate the long-term geochemical behavior of waste packages (WPs) containing U. S . Department of Energy (DOE) Spent Nuclear Fuel (SNF) codisposed with High Level Waste (HLW) glass, commercial SNF, and Immobilized Plutonium Ceramic (Pu-ceramic) codisposed with HLW glass. The model is intended to predict (1) the extent to which criticality control material, such as gadolinium (Gd), will remain in the WP after corrosion of the initial WP, (2) the extent to which fissile Pu and uranium (U) will be carried out of the degraded WP by infiltrating water, and (3) the chemical composition and amounts of minerals and other solids left in the WP. The results of the model are intended for use in criticality calculations. The scope of the model validation report is to (1) describe the MDR model, and (2) compare the modeling results with experimental studies. A test case based on a degrading Pu-ceramic WP is provided to help explain the model. This model does not directly feed the assessment of system performance. The output from this model is used by several other models, such as the configuration generator, criticality, and criticality consequence models, prior to the evaluation of system performance. This document has been prepared according to AP-3.10Q, ''Analyses and Models'' (Ref. 2), and prepared in accordance with the technical work plan (Ref. 17).

  12. Geochemistry Model Validation Report: Material Degradation and Release Model

    International Nuclear Information System (INIS)

    Stockman, H.

    2001-01-01

    The purpose of this Analysis and Modeling Report (AMR) is to validate the Material Degradation and Release (MDR) model that predicts degradation and release of radionuclides from a degrading waste package (WP) in the potential monitored geologic repository at Yucca Mountain. This AMR is prepared according to ''Technical Work Plan for: Waste Package Design Description for LA'' (Ref. 17). The intended use of the MDR model is to estimate the long-term geochemical behavior of waste packages (WPs) containing U. S . Department of Energy (DOE) Spent Nuclear Fuel (SNF) codisposed with High Level Waste (HLW) glass, commercial SNF, and Immobilized Plutonium Ceramic (Pu-ceramic) codisposed with HLW glass. The model is intended to predict (1) the extent to which criticality control material, such as gadolinium (Gd), will remain in the WP after corrosion of the initial WP, (2) the extent to which fissile Pu and uranium (U) will be carried out of the degraded WP by infiltrating water, and (3) the chemical composition and amounts of minerals and other solids left in the WP. The results of the model are intended for use in criticality calculations. The scope of the model validation report is to (1) describe the MDR model, and (2) compare the modeling results with experimental studies. A test case based on a degrading Pu-ceramic WP is provided to help explain the model. This model does not directly feed the assessment of system performance. The output from this model is used by several other models, such as the configuration generator, criticality, and criticality consequence models, prior to the evaluation of system performance. This document has been prepared according to AP-3.10Q, ''Analyses and Models'' (Ref. 2), and prepared in accordance with the technical work plan (Ref. 17)

  13. Comparison between a generalized Newtonian model and a network-type multiscale model for hemodynamic behavior in the aortic arch: Validation with 4D MRI data for a case study.

    Science.gov (United States)

    Menut, Marine; Boussel, Loïc; Escriva, Xavier; Bou-Saïd, Benyebka; Walter-Le Berre, Hélène; Marchesse, Yann; Millon, Antoine; Della Schiava, Nellie; Lermusiaux, Patrick; Tichy, John

    2018-05-17

    Blood is a complex fluid in which the presence of the various constituents leads to significant changes in its rheological properties. Thus, an appropriate non-Newtonian model is advisable; and we choose a Modified version of the rheological model of Phan-Thien and Tanner (MPTT). The different parameters of this model, derived from the rheology of polymers, allow characterization of the non-Newtonian nature of blood, taking into account the behavior of red blood cells in plasma. Using the MPTT model that we implemented in the open access software OpenFOAM, numerical simulations have been performed on blood flow in the thoracic aorta for a healthy patient. We started from a patient-specific model which was constructed from medical images. Exiting flow boundary conditions have been developped, based on a 3-element Windkessel model to approximate physiological conditions. The parameters of the Windkessel model were calibrated with in vivo measurements of flow rate and pressure. The influence of the selected viscosity of red blood cells on the flow and wall shear stress (WSS) was investigated. Results obtained from this model were compared to those of the Newtonian model, and to those of a generalized Newtonian model, as well as to in vivo dynamic data from 4D MRI during a cardiac cycle. Upon evaluating the results, the MPTT model shows better agreement with the MRI data during the systolic and diastolic phases than the Newtonian or generalized Newtonian model, which confirms our interest in using a complex viscoelastic model. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Tool wear modeling using abductive networks

    Science.gov (United States)

    Masory, Oren

    1992-09-01

    A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.

  15. Statistical validation of normal tissue complication probability models

    NARCIS (Netherlands)

    Xu, Cheng-Jian; van der Schaaf, Arjen; van t Veld, Aart; Langendijk, Johannes A.; Schilstra, Cornelis

    2012-01-01

    PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage

  16. Modelling of virtual production networks

    Directory of Open Access Journals (Sweden)

    2011-03-01

    Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.

  17. A Network Disruption Modeling Tool

    National Research Council Canada - National Science Library

    Leinart, James

    1998-01-01

    Given that network disruption has been identified as a military objective and C2-attack has been identified as the mechanism to accomplish this objective, a target set must be acquired and priorities...

  18. Validation of the community radiative transfer model

    International Nuclear Information System (INIS)

    Ding Shouguo; Yang Ping; Weng Fuzhong; Liu Quanhua; Han Yong; Delst, Paul van; Li Jun; Baum, Bryan

    2011-01-01

    To validate the Community Radiative Transfer Model (CRTM) developed by the U.S. Joint Center for Satellite Data Assimilation (JCSDA), the discrete ordinate radiative transfer (DISORT) model and the line-by-line radiative transfer model (LBLRTM) are combined in order to provide a reference benchmark. Compared with the benchmark, the CRTM appears quite accurate for both clear sky and ice cloud radiance simulations with RMS errors below 0.2 K, except for clouds with small ice particles. In a computer CPU run time comparison, the CRTM is faster than DISORT by approximately two orders of magnitude. Using the operational MODIS cloud products and the European Center for Medium-range Weather Forecasting (ECMWF) atmospheric profiles as an input, the CRTM is employed to simulate the Atmospheric Infrared Sounder (AIRS) radiances. The CRTM simulations are shown to be in reasonably close agreement with the AIRS measurements (the discrepancies are within 2 K in terms of brightness temperature difference). Furthermore, the impact of uncertainties in the input cloud properties and atmospheric profiles on the CRTM simulations has been assessed. The CRTM-based brightness temperatures (BTs) at the top of the atmosphere (TOA), for both thin (τ 30) clouds, are highly sensitive to uncertainties in atmospheric temperature and cloud top pressure. However, for an optically thick cloud, the CRTM-based BTs are not sensitive to the uncertainties of cloud optical thickness, effective particle size, and atmospheric humidity profiles. On the contrary, the uncertainties of the CRTM-based TOA BTs resulting from effective particle size and optical thickness are not negligible in an optically thin cloud.

  19. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  20. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  1. Implementing network constraints in the EMPS model

    Energy Technology Data Exchange (ETDEWEB)

    Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

    2010-02-15

    This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

  2. Role models for complex networks

    Science.gov (United States)

    Reichardt, J.; White, D. R.

    2007-11-01

    We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

  3. Development of a Conservative Model Validation Approach for Reliable Analysis

    Science.gov (United States)

    2015-01-01

    CIE 2015 August 2-5, 2015, Boston, Massachusetts, USA [DRAFT] DETC2015-46982 DEVELOPMENT OF A CONSERVATIVE MODEL VALIDATION APPROACH FOR RELIABLE...obtain a conservative simulation model for reliable design even with limited experimental data. Very little research has taken into account the...3, the proposed conservative model validation is briefly compared to the conventional model validation approach. Section 4 describes how to account

  4. Validation of ecological state space models using the Laplace approximation

    DEFF Research Database (Denmark)

    Thygesen, Uffe Høgsbro; Albertsen, Christoffer Moesgaard; Berg, Casper Willestofte

    2017-01-01

    Many statistical models in ecology follow the state space paradigm. For such models, the important step of model validation rarely receives as much attention as estimation or hypothesis testing, perhaps due to lack of available algorithms and software. Model validation is often based on a naive...... for estimation in general mixed effects models. Implementing one-step predictions in the R package Template Model Builder, we demonstrate that it is possible to perform model validation with little effort, even if the ecological model is multivariate, has non-linear dynamics, and whether observations...... useful directions in which the model could be improved....

  5. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

    2017-10-01

    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  6. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  7. Homophyly/Kinship Model: Naturally Evolving Networks

    Science.gov (United States)

    Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

    2015-10-01

    It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

  8. Validation of a Global Hydrodynamic Flood Inundation Model

    Science.gov (United States)

    Bates, P. D.; Smith, A.; Sampson, C. C.; Alfieri, L.; Neal, J. C.

    2014-12-01

    In this work we present first validation results for a hyper-resolution global flood inundation model. We use a true hydrodynamic model (LISFLOOD-FP) to simulate flood inundation at 1km resolution globally and then use downscaling algorithms to determine flood extent and depth at 90m spatial resolution. Terrain data are taken from a custom version of the SRTM data set that has been processed specifically for hydrodynamic modelling. Return periods of flood flows along the entire global river network are determined using: (1) empirical relationships between catchment characteristics and index flood magnitude in different hydroclimatic zones derived from global runoff data; and (2) an index flood growth curve, also empirically derived. Bankful return period flow is then used to set channel width and depth, and flood defence impacts are modelled using empirical relationships between GDP, urbanization and defence standard of protection. The results of these simulations are global flood hazard maps for a number of different return period events from 1 in 5 to 1 in 1000 years. We compare these predictions to flood hazard maps developed by national government agencies in the UK and Germany using similar methods but employing detailed local data, and to observed flood extent at a number of sites including St. Louis, USA and Bangkok in Thailand. Results show that global flood hazard models can have considerable skill given careful treatment to overcome errors in the publicly available data that are used as their input.

  9. Validation of models in an imaging infrared simulation

    CSIR Research Space (South Africa)

    Willers, C

    2007-10-01

    Full Text Available threeprocessesfortransformingtheinformationbetweentheentities. Reality/ Problem Entity Conceptual Model Computerized Model Model Validation ModelVerification Model Qualification Computer Implementation Analysisand Modelling Simulationand Experimentation “Substantiationthata....C.Refsgaard ,ModellingGuidelines-terminology andguidingprinciples, AdvancesinWaterResources, Vol27,No1,January2004,?pp.71-82(12),Elsevier. et.al. [5]N.Oreskes,et.al.,Verification,Validation,andConfirmationof NumericalModelsintheEarthSciences,Science,Vol263, Number...

  10. Neural network tagging in a toy model

    International Nuclear Information System (INIS)

    Milek, Marko; Patel, Popat

    1999-01-01

    The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed

  11. An endogenous model of the credit network

    Science.gov (United States)

    He, Jianmin; Sui, Xin; Li, Shouwei

    2016-01-01

    In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.

  12. Modelling and designing electric energy networks

    International Nuclear Information System (INIS)

    Retiere, N.

    2003-11-01

    The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets

  13. Model Validation Using Coordinate Distance with Performance Sensitivity

    Directory of Open Access Journals (Sweden)

    Jiann-Shiun Lew

    2008-01-01

    Full Text Available This paper presents an innovative approach to model validation for a structure with significant parameter variations. Model uncertainty of the structural dynamics is quantified with the use of a singular value decomposition technique to extract the principal components of parameter change, and an interval model is generated to represent the system with parameter uncertainty. The coordinate vector, corresponding to the identified principal directions, of the validation system is computed. The coordinate distance between the validation system and the identified interval model is used as a metric for model validation. A beam structure with an attached subsystem, which has significant parameter uncertainty, is used to demonstrate the proposed approach.

  14. Queueing Models for Mobile Ad Hoc Networks

    NARCIS (Netherlands)

    de Haan, Roland

    2009-01-01

    This thesis presents models for the performance analysis of a recent communication paradigm: \\emph{mobile ad hoc networking}. The objective of mobile ad hoc networking is to provide wireless connectivity between stations in a highly dynamic environment. These dynamics are driven by the mobility of

  15. Modeling GMPLS and Optical MPLS Networks

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann; Wessing, Henrik

    2003-01-01

    . The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...

  16. Cyber threat model for tactical radio networks

    Science.gov (United States)

    Kurdziel, Michael T.

    2014-05-01

    The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.

  17. Modeling documents with Generative Adversarial Networks

    OpenAIRE

    Glover, John

    2016-01-01

    This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

  18. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  19. Modeling trust context in networks

    CERN Document Server

    Adali, Sibel

    2013-01-01

    We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others.? In this brief, 'trust context' is defined as the system level description of how the trust evaluation process unfolds.Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout

  20. Influence of rainfall observation network on model calibration and application

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-01-01

    Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

  1. International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation

    DEFF Research Database (Denmark)

    Wendt, Fabian F.; Yu, Yi-Hsiang; Nielsen, Kim

    2017-01-01

    This is the first joint reference paper for the Ocean Energy Systems (OES) Task 10 Wave Energy Converter modeling verification and validation group. The group is established under the OES Energy Technology Network program under the International Energy Agency. OES was founded in 2001 and Task 10 ...

  2. Mathematical model of highways network optimization

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2017-12-01

    The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

  3. Validity of the Neuromuscular Recovery Scale: a measurement model approach.

    Science.gov (United States)

    Velozo, Craig; Moorhouse, Michael; Ardolino, Elizabeth; Lorenz, Doug; Suter, Sarah; Basso, D Michele; Behrman, Andrea L

    2015-08-01

    To determine how well the Neuromuscular Recovery Scale (NRS) items fit the Rasch, 1-parameter, partial-credit measurement model. Confirmatory factor analysis (CFA) and principal components analysis (PCA) of residuals were used to determine dimensionality. The Rasch, 1-parameter, partial-credit rating scale model was used to determine rating scale structure, person/item fit, point-measure item correlations, item discrimination, and measurement precision. Seven NeuroRecovery Network clinical sites. Outpatients (N=188) with spinal cord injury. Not applicable. NRS. While the NRS met 1 of 3 CFA criteria, the PCA revealed that the Rasch measurement dimension explained 76.9% of the variance. Ten of 11 items and 91% of the patients fit the Rasch model, with 9 of 11 items showing high discrimination. Sixty-nine percent of the ratings met criteria. The items showed a logical item-difficulty order, with Stand retraining as the easiest item and Walking as the most challenging item. The NRS showed no ceiling or floor effects and separated the sample into almost 5 statistically distinct strata; individuals with an American Spinal Injury Association Impairment Scale (AIS) D classification showed the most ability, and those with an AIS A classification showed the least ability. Items not meeting the rating scale criteria appear to be related to the low frequency counts. The NRS met many of the Rasch model criteria for construct validity. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  4. Causality within the Epileptic Network: An EEG-fMRI Study Validated by Intracranial EEG.

    Science.gov (United States)

    Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano

    2013-01-01

    Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

  5. Causality within the epileptic network: an EEG-fMRI study validated by intracranial EEG.

    Directory of Open Access Journals (Sweden)

    Anna Elisabetta eVaudano

    2013-11-01

    Full Text Available Accurate localization of the Seizure Onset Zone (SOZ is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical workup. However, fMRI maps related to interictal epileptiform activities (IED often show multiple regions of signal change, or networks, rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modelling (DCM applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of BOLD signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favoured a model corresponding to the left dorsolateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI, and psychophysiological interaction analysis (PPI; (b the failure of a first surgical intervention limited to the fronto-polar region; (c the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

  6. System Advisor Model: Flat Plate Photovoltaic Performance Modeling Validation Report

    Energy Technology Data Exchange (ETDEWEB)

    Freeman, Janine [National Renewable Energy Lab. (NREL), Golden, CO (United States); Whitmore, Jonathan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Kaffine, Leah [National Renewable Energy Lab. (NREL), Golden, CO (United States); Blair, Nate [National Renewable Energy Lab. (NREL), Golden, CO (United States); Dobos, Aron P. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    The System Advisor Model (SAM) is a free software tool that performs detailed analysis of both system performance and system financing for a variety of renewable energy technologies. This report provides detailed validation of the SAM flat plate photovoltaic performance model by comparing SAM-modeled PV system generation data to actual measured production data for nine PV systems ranging from 75 kW to greater than 25 MW in size. The results show strong agreement between SAM predictions and field data, with annualized prediction error below 3% for all fixed tilt cases and below 8% for all one axis tracked cases. The analysis concludes that snow cover and system outages are the primary sources of disagreement, and other deviations resulting from seasonal biases in the irradiation models and one axis tracking issues are discussed in detail.

  7. SDL-Based Protocol Validation for the Integrated Safety Communication Network in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Kim, Jung-hun; Kim, Dong-hoon; Lee, Dong-young; Park, Sung-woo

    2006-01-01

    The communication protocol in nuclear power plants needs to be validated systematically to avoid the critical situation that may be caused by its own faults. We establish the methodology to validate the protocol designed for the Integrated Safety Communication Networks (ISCN) of Korea Nuclear Instrumentation and Control System (KNICS). The ISCN protocol is specified using the formal description technique called the SDL. The validation of ISCN protocol is done via the Simulator and Validator, both of which are main functions provided by the SDL

  8. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma

    2004-12-01

    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  9. Sparsity in Model Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Zagorski, M.

    2011-01-01

    We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

  10. Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Pirmoradi

    2012-04-01

    Full Text Available Distillation is a complex and highly nonlinear industrial process. In general it is not always possible to obtain accurate first principles models for high-purity distillation columns. On the other hand the development of first principles models is usually time consuming and expensive. To overcome these problems, empirical models such as neural networks can be used. One major drawback of empirical models is that the prediction is valid only inside the data domain that is sufficiently covered by measurement data. Modeling distillation columns by means of neural networks is reported in literature by using recursive networks. The recursive networks are proper for modeling purpose, but such models have the problems of high complexity and high computational cost. The objective of this paper is to propose a simple and reliable model for distillation column. The proposed model uses feed forward neural networks which results in a simple model with less parameters and faster training time. Simulation results demonstrate that predictions of the proposed model in all regions are close to outputs of the dynamic model and the error in negligible. This implies that the model is reliable in all regions.

  11. Training and validation of the ATLAS pixel clustering neural networks

    CERN Document Server

    The ATLAS collaboration

    2018-01-01

    The high centre-of-mass energy of the LHC gives rise to dense environments, such as the core of high-pT jets, in which the charge clusters left by ionising particles in the silicon sensors of the pixel detector can merge, compromising the tracking and vertexing efficiency. To recover optimal performance, a neural network-based approach is used to separate clusters originating from single and multiple particles and to estimate all hit positions within clusters. This note presents the training strategy employed and a set of benchmark performance measurements on a Monte Carlo sample of high-pT dijet events.

  12. Test-driven verification/validation of model transformations

    Institute of Scientific and Technical Information of China (English)

    László LENGYEL; Hassan CHARAF

    2015-01-01

    Why is it important to verify/validate model transformations? The motivation is to improve the quality of the trans-formations, and therefore the quality of the generated software artifacts. Verified/validated model transformations make it possible to ensure certain properties of the generated software artifacts. In this way, verification/validation methods can guarantee different requirements stated by the actual domain against the generated/modified/optimized software products. For example, a verified/ validated model transformation can ensure the preservation of certain properties during the model-to-model transformation. This paper emphasizes the necessity of methods that make model transformation verified/validated, discusses the different scenarios of model transformation verification and validation, and introduces the principles of a novel test-driven method for verifying/ validating model transformations. We provide a solution that makes it possible to automatically generate test input models for model transformations. Furthermore, we collect and discuss the actual open issues in the field of verification/validation of model transformations.

  13. A comprehensive model for piezoceramic actuators: modelling, validation and application

    International Nuclear Information System (INIS)

    Quant, Mario; Elizalde, Hugo; Flores, Abiud; Ramírez, Ricardo; Orta, Pedro; Song, Gangbing

    2009-01-01

    This paper presents a comprehensive model for piezoceramic actuators (PAs), which accounts for hysteresis, non-linear electric field and dynamic effects. The hysteresis model is based on the widely used general Maxwell slip model, while an enhanced electro-mechanical non-linear model replaces the linear constitutive equations commonly used. Further on, a linear second order model compensates the frequency response of the actuator. Each individual model is fully characterized from experimental data yielded by a specific PA, then incorporated into a comprehensive 'direct' model able to determine the output strain based on the applied input voltage, fully compensating the aforementioned effects, where the term 'direct' represents an electrical-to-mechanical operating path. The 'direct' model was implemented in a Matlab/Simulink environment and successfully validated via experimental results, exhibiting higher accuracy and simplicity than many published models. This simplicity would allow a straightforward inclusion of other behaviour such as creep, ageing, material non-linearity, etc, if such parameters are important for a particular application. Based on the same formulation, two other models are also presented: the first is an 'alternate' model intended to operate within a force-controlled scheme (instead of a displacement/position control), thus able to capture the complex mechanical interactions occurring between a PA and its host structure. The second development is an 'inverse' model, able to operate within an open-loop control scheme, that is, yielding a 'linearized' PA behaviour. The performance of the developed models is demonstrated via a numerical sample case simulated in Matlab/Simulink, consisting of a PA coupled to a simple mechanical system, aimed at shifting the natural frequency of the latter

  14. Preventing patient absenteeism: validation of a predictive overbooking model.

    Science.gov (United States)

    Reid, Mark W; Cohen, Samuel; Wang, Hank; Kaung, Aung; Patel, Anish; Tashjian, Vartan; Williams, Demetrius L; Martinez, Bibiana; Spiegel, Brennan M R

    2015-12-01

    To develop a model that identifies patients at high risk for missing scheduled appointments ("no-shows" and cancellations) and to project the impact of predictive overbooking in a gastrointestinal endoscopy clinic-an exemplar resource-intensive environment with a high no-show rate. We retrospectively developed an algorithm that uses electronic health record (EHR) data to identify patients who do not show up to their appointments. Next, we prospectively validated the algorithm at a Veterans Administration healthcare network clinic. We constructed a multivariable logistic regression model that assigned a no-show risk score optimized by receiver operating characteristic curve analysis. Based on these scores, we created a calendar of projected open slots to offer to patients and compared the daily performance of predictive overbooking with fixed overbooking and typical "1 patient, 1 slot" scheduling. Data from 1392 patients identified several predictors of no-show, including previous absenteeism, comorbid disease burden, and current diagnoses of mood and substance use disorders. The model correctly classified most patients during the development (area under the curve [AUC] = 0.80) and validation phases (AUC = 0.75). Prospective testing in 1197 patients found that predictive overbooking averaged 0.51 unused appointments per day versus 6.18 for typical booking (difference = -5.67; 95% CI, -6.48 to -4.87; P < .0001). Predictive overbooking could have increased service utilization from 62% to 97% of capacity, with only rare clinic overflows. Information from EHRs can accurately predict whether patients will no-show. This method can be used to overbook appointments, thereby maximizing service utilization while staying within clinic capacity.

  15. A Model of Network Porosity

    Science.gov (United States)

    2016-11-09

    Figure 1. We generally express such networks in terms of the services running in each enclave as well as the routing and firewall rules between the...compromise a server, they can compromise other devices in the same subnet or protected enclave. They probe attached firewalls and routers for open ports and...spam and malware filter would prevent this content from reaching its destination. Content filtering provides another layer of defense to other controls

  16. Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Young-Jae Song

    2009-07-01

    Full Text Available Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

  17. Thermal conductivity model for nanofiber networks

    Science.gov (United States)

    Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui

    2018-02-01

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  18. Thermal conductivity model for nanofiber networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA

    2018-02-28

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  19. A quantum-implementable neural network model

    Science.gov (United States)

    Chen, Jialin; Wang, Lingli; Charbon, Edoardo

    2017-10-01

    A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

  20. Combinatorial explosion in model gene networks

    Science.gov (United States)

    Edwards, R.; Glass, L.

    2000-09-01

    The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such

  1. Complex networks under dynamic repair model

    Science.gov (United States)

    Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

    2018-01-01

    Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

  2. Some considerations for validation of repository performance assessment models

    International Nuclear Information System (INIS)

    Eisenberg, N.

    1991-01-01

    Validation is an important aspect of the regulatory uses of performance assessment. A substantial body of literature exists indicating the manner in which validation of models is usually pursued. Because performance models for a nuclear waste repository cannot be tested over the long time periods for which the model must make predictions, the usual avenue for model validation is precluded. Further impediments to model validation include a lack of fundamental scientific theory to describe important aspects of repository performance and an inability to easily deduce the complex, intricate structures characteristic of a natural system. A successful strategy for validation must attempt to resolve these difficulties in a direct fashion. Although some procedural aspects will be important, the main reliance of validation should be on scientific substance and logical rigor. The level of validation needed will be mandated, in part, by the uses to which these models are put, rather than by the ideal of validation of a scientific theory. Because of the importance of the validation of performance assessment models, the NRC staff has engaged in a program of research and international cooperation to seek progress in this important area. 2 figs., 16 refs

  3. Performance modeling, stochastic networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi R

    2013-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan

  4. Network Modeling and Simulation A Practical Perspective

    CERN Document Server

    Guizani, Mohsen; Khan, Bilal

    2010-01-01

    Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strate

  5. Multiple-failure signal validation in nuclear power plants using artificial neural networks

    International Nuclear Information System (INIS)

    Fantoni, P.F.; Mazzola, A.

    1996-01-01

    The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

  6. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida

    2014-09-01

    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  7. Statistical Validation of Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)

    2012-09-01

    Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.

  8. Statistical validation of normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis

    2012-09-01

    To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China.

    Science.gov (United States)

    Li, Jibin; Lau, Joseph T F; Mo, Phoenix K H; Su, Xuefen; Wu, Anise M S; Tang, Jie; Qin, Zuguo

    2016-01-01

    Online social networking use has been integrated into adolescents' daily life and the intensity of online social networking use may have important consequences on adolescents' well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach's alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, psocial networking, social networking addiction, Internet addiction, and characteristics related to social networking use. The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population.

  10. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

    Science.gov (United States)

    Li, Jibin; Lau, Joseph T. F.; Mo, Phoenix K. H.; Su, Xuefen; Wu, Anise M. S.; Tang, Jie; Qin, Zuguo

    2016-01-01

    Background Online social networking use has been integrated into adolescents’ daily life and the intensity of online social networking use may have important consequences on adolescents’ well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. Methods A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Results Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach’s alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, psocial networking, social networking addiction, Internet addiction, and characteristics related to social networking use. Conclusions The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population. PMID:27798699

  11. Optimal transportation networks models and theory

    CERN Document Server

    Bernot, Marc; Morel, Jean-Michel

    2009-01-01

    The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.

  12. Flood routing modelling with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  13. Validation of measured poleward TEC gradient using multi-station GPS with Artificial Neural Network based TEC model in low latitude region for developing predictive capability of ionospheric scintillation

    Science.gov (United States)

    Sur, D.; Paul, A.

    2017-12-01

    The equatorial ionosphere shows sharp diurnal and latitudinal Total Electron Content (TEC) variations over a major part of the day. Equatorial ionosphere also exhibits intense post-sunset ionospheric irregularities. Accurate prediction of TEC in these low latitudes is not possible from standard ionospheric models. An Artificial Neural Network (ANN) based Vertical TEC (VTEC) model has been designed using TEC data in low latitude Indian longitude sector for accurate prediction of VTEC. GPS TEC data from the stations Calcutta (22.58°N, 88.38°E geographic, magnetic dip 32°), Baharampore (24.09°N, 88.25°E geographic, magnetic dip 35°) and Siliguri (26.72°N, 88.39°E geographic; magnetic dip 40°) are used as training dataset for the duration of January 2007-September 2011. Poleward VTEC gradients from northern EIA crest to region beyond EIA crest have been calculated from measured VTEC and compared with that obtained from ANN based VTEC model. TEC data from Calcutta and Siliguri are used to compute VTEC gradients during April 2013 and August-September 2013. It has been observed that poleward VTEC gradient computed from ANN based TEC model has shown good correlation with measured values during vernal and autumnal equinoxes of high solar activity periods of 2013. Possible correlation between measured poleward TEC gradients and post-sunset scintillations (S4 ≥ 0.4) from northern crest of EIA has been observed in this paper. From the observation, a suitable threshold poleward VTEC gradient has been proposed for possible occurrence of post-sunset scintillations at northern crest of EIA along 88°E longitude. Poleward VTEC gradients obtained from ANN based VTEC model are used to forecast possible ionospheric scintillation after post-sunset period using the threshold value. It has been observed that these predicted VTEC gradients obtained from ANN based VTEC model can forecast post-sunset L-band scintillation with an accuracy of 67% to 82% in this dynamic low latitude

  14. Linear approximation model network and its formation via ...

    Indian Academy of Sciences (India)

    To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

  15. Automated bony region identification using artificial neural networks: reliability and validation measurements

    Energy Technology Data Exchange (ETDEWEB)

    Gassman, Esther E.; Kallemeyn, Nicole A.; DeVries, Nicole A.; Shivanna, Kiran H. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States); Powell, Stephanie M. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Magnotta, Vincent A. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Ramme, Austin J. [University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Adams, Brian D. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Orthopaedics and Rehabilitation, Iowa City, IA (United States); Grosland, Nicole M. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Orthopaedics and Rehabilitation, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States)

    2008-04-15

    The objective was to develop tools for automating the identification of bony structures, to assess the reliability of this technique against manual raters, and to validate the resulting regions of interest against physical surface scans obtained from the same specimen. Artificial intelligence-based algorithms have been used for image segmentation, specifically artificial neural networks (ANNs). For this study, an ANN was created and trained to identify the phalanges of the human hand. The relative overlap between the ANN and a manual tracer was 0.87, 0.82, and 0.76, for the proximal, middle, and distal index phalanx bones respectively. Compared with the physical surface scans, the ANN-generated surface representations differed on average by 0.35 mm, 0.29 mm, and 0.40 mm for the proximal, middle, and distal phalanges respectively. Furthermore, the ANN proved to segment the structures in less than one-tenth of the time required by a manual rater. The ANN has proven to be a reliable and valid means of segmenting the phalanx bones from CT images. Employing automated methods such as the ANN for segmentation, eliminates the likelihood of rater drift and inter-rater variability. Automated methods also decrease the amount of time and manual effort required to extract the data of interest, thereby making the feasibility of patient-specific modeling a reality. (orig.)

  16. Automated bony region identification using artificial neural networks: reliability and validation measurements

    International Nuclear Information System (INIS)

    Gassman, Esther E.; Kallemeyn, Nicole A.; DeVries, Nicole A.; Shivanna, Kiran H.; Powell, Stephanie M.; Magnotta, Vincent A.; Ramme, Austin J.; Adams, Brian D.; Grosland, Nicole M.

    2008-01-01

    The objective was to develop tools for automating the identification of bony structures, to assess the reliability of this technique against manual raters, and to validate the resulting regions of interest against physical surface scans obtained from the same specimen. Artificial intelligence-based algorithms have been used for image segmentation, specifically artificial neural networks (ANNs). For this study, an ANN was created and trained to identify the phalanges of the human hand. The relative overlap between the ANN and a manual tracer was 0.87, 0.82, and 0.76, for the proximal, middle, and distal index phalanx bones respectively. Compared with the physical surface scans, the ANN-generated surface representations differed on average by 0.35 mm, 0.29 mm, and 0.40 mm for the proximal, middle, and distal phalanges respectively. Furthermore, the ANN proved to segment the structures in less than one-tenth of the time required by a manual rater. The ANN has proven to be a reliable and valid means of segmenting the phalanx bones from CT images. Employing automated methods such as the ANN for segmentation, eliminates the likelihood of rater drift and inter-rater variability. Automated methods also decrease the amount of time and manual effort required to extract the data of interest, thereby making the feasibility of patient-specific modeling a reality. (orig.)

  17. Validation of network communicability metrics for the analysis of brain structural networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

    Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

  18. Analytical model of a burst assembly algorithm for the VBR in the OBS networks

    International Nuclear Information System (INIS)

    Shargabi, M.A.A.; Mellah, H.; Abid, A.

    2008-01-01

    This paper presents a proposed analytical model for the number of bursts aggregated in a period of time in OBS networks. The model considers the case of VBR traffic with two different sending rates, which are SCR and PCR. The model is validated using extensive simulations. Where results from simulations are in total agreement with the results obtained by the proposed model. (author)

  19. Development and validation of a survey to measure features of clinical networks.

    Science.gov (United States)

    Brown, Bernadette Bea; Haines, Mary; Middleton, Sandy; Paul, Christine; D'Este, Catherine; Klineberg, Emily; Elliott, Elizabeth

    2016-09-30

    Networks of clinical experts are increasingly being implemented as a strategy to improve health care processes and outcomes and achieve change in the health system. Few are ever formally evaluated and, when this is done, not all networks are equally successful in their efforts. There is a need to formatively assess the strategic and operational management and leadership of networks to identify where functioning could be improved to maximise impact. This paper outlines the development and psychometric evaluation of an Internet survey to measure features of clinical networks and provides descriptive results from a sample of members of 19 diverse clinical networks responsible for evidence-based quality improvement across a large geographical region. Instrument development was based on: a review of published and grey literature; a qualitative study of clinical network members; a program logic framework; and consultation with stakeholders. The resulting domain structure was validated for a sample of 592 clinical network members using confirmatory factor analysis. Scale reliability was assessed using Cronbach's alpha. A summary score was calculated for each domain and aggregate level means and ranges are reported. The instrument was shown to have good construct validity across seven domains as demonstrated by a high level of internal consistency, and all Cronbach's α coefficients were equal to or above 0.75. In the survey sample of network members there was strong reported commitment and belief in network-led quality improvement initiatives, which were perceived to have improved quality of care (72.8 %) and patient outcomes (63.2 %). Network managers were perceived to be effective leaders and clinical co-chairs were perceived as champions for change. Perceived external support had the lowest summary score across the seven domains. This survey, which has good construct validity and internal reliability, provides a valid instrument to use in future research related to

  20. Modeling Security Aspects of Network

    Science.gov (United States)

    Schoch, Elmar

    With more and more widespread usage of computer systems and networks, dependability becomes a paramount requirement. Dependability typically denotes tolerance or protection against all kinds of failures, errors and faults. Sources of failures can basically be accidental, e.g., in case of hardware errors or software bugs, or intentional due to some kind of malicious behavior. These intentional, malicious actions are subject of security. A more complete overview on the relations between dependability and security can be found in [31]. In parallel to the increased use of technology, misuse also has grown significantly, requiring measures to deal with it.

  1. Validation of mentorship model for newly qualified professional ...

    African Journals Online (AJOL)

    Newly qualified professional nurses (NQPNs) allocated to community health care services require the use of validated model to practice independently. Validation was done to adapt and assess if the model is understood and could be implemented by NQPNs and mentors employed in community health care services.

  2. Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

    International Nuclear Information System (INIS)

    Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Palchykov, Vasyl; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; N Mantegna, Rosario

    2014-01-01

    Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets. (paper)

  3. Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

    Science.gov (United States)

    Li, Ming-Xia; Palchykov, Vasyl; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2014-08-01

    Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.

  4. Modeling and optimization of an electric power distribution network ...

    African Journals Online (AJOL)

    Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

  5. Cost model validation: a technical and cultural approach

    Science.gov (United States)

    Hihn, J.; Rosenberg, L.; Roust, K.; Warfield, K.

    2001-01-01

    This paper summarizes how JPL's parametric mission cost model (PMCM) has been validated using both formal statistical methods and a variety of peer and management reviews in order to establish organizational acceptance of the cost model estimates.

  6. An evolving network model with modular growth

    International Nuclear Information System (INIS)

    Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi

    2012-01-01

    In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)

  7. Knowledge-fused differential dependency network models for detecting significant rewiring in biological networks.

    Science.gov (United States)

    Tian, Ye; Zhang, Bai; Hoffman, Eric P; Clarke, Robert; Zhang, Zhen; Shih, Ie-Ming; Xuan, Jianhua; Herrington, David M; Wang, Yue

    2014-07-24

    Modeling biological networks serves as both a major goal and an effective tool of systems biology in studying mechanisms that orchestrate the activities of gene products in cells. Biological networks are context-specific and dynamic in nature. To systematically characterize the selectively activated regulatory components and mechanisms, modeling tools must be able to effectively distinguish significant rewiring from random background fluctuations. While differential networks cannot be constructed by existing knowledge alone, novel incorporation of prior knowledge into data-driven approaches can improve the robustness and biological relevance of network inference. However, the major unresolved roadblocks include: big solution space but a small sample size; highly complex networks; imperfect prior knowledge; missing significance assessment; and heuristic structural parameter learning. To address these challenges, we formulated the inference of differential dependency networks that incorporate both conditional data and prior knowledge as a convex optimization problem, and developed an efficient learning algorithm to jointly infer the conserved biological network and the significant rewiring across different conditions. We used a novel sampling scheme to estimate the expected error rate due to "random" knowledge. Based on that scheme, we developed a strategy that fully exploits the benefit of this data-knowledge integrated approach. We demonstrated and validated the principle and performance of our method using synthetic datasets. We then applied our method to yeast cell line and breast cancer microarray data and obtained biologically plausible results. The open-source R software package and the experimental data are freely available at http://www.cbil.ece.vt.edu/software.htm. Experiments on both synthetic and real data demonstrate the effectiveness of the knowledge-fused differential dependency network in revealing the statistically significant rewiring in biological

  8. Validation of Embedded System Verification Models

    NARCIS (Netherlands)

    Marincic, J.; Mader, Angelika H.; Wieringa, Roelf J.

    The result of a model-based requirements verification shows that the model of a system satisfies (or not) formalised system requirements. The verification result is correct only if the model represents the system adequately. No matter what modelling technique we use, what precedes the model

  9. Modeling of contact tracing in social networks

    Science.gov (United States)

    Tsimring, Lev S.; Huerta, Ramón

    2003-07-01

    Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.

  10. A Network Model of Credit Risk Contagion

    Directory of Open Access Journals (Sweden)

    Ting-Qiang Chen

    2012-01-01

    Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

  11. The International Trade Network: weighted network analysis and modelling

    International Nuclear Information System (INIS)

    Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K

    2008-01-01

    Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN

  12. IVIM: modeling, experimental validation and application to animal models

    International Nuclear Information System (INIS)

    Fournet, Gabrielle

    2016-01-01

    This PhD thesis is centered on the study of the IVIM ('Intravoxel Incoherent Motion') MRI sequence. This sequence allows for the study of the blood microvasculature such as the capillaries, arterioles and venules. To be sensitive only to moving groups of spins, diffusion gradients are added before and after the 180 degrees pulse of a spin echo (SE) sequence. The signal component corresponding to spins diffusing in the tissue can be separated from the one related to spins travelling in the blood vessels which is called the IVIM signal. These two components are weighted by f IVIM which represents the volume fraction of blood inside the tissue. The IVIM signal is usually modelled by a mono-exponential (ME) function and characterized by a pseudo-diffusion coefficient, D*. We propose instead a bi-exponential IVIM model consisting of a slow pool, characterized by F slow and D* slow corresponding to the capillaries as in the ME model, and a fast pool, characterized by F fast and D* fast, related to larger vessels such as medium-size arterioles and venules. This model was validated experimentally and more information was retrieved by comparing the experimental signals to a dictionary of simulated IVIM signals. The influence of the pulse sequence, the repetition time and the diffusion encoding time was also studied. Finally, the IVIM sequence was applied to the study of an animal model of Alzheimer's disease. (author) [fr

  13. Keystone Business Models for Network Security Processors

    OpenAIRE

    Arthur Low; Steven Muegge

    2013-01-01

    Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor...

  14. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  15. Decomposed Implicit Models of Piecewise - Linear Networks

    Directory of Open Access Journals (Sweden)

    J. Brzobohaty

    1992-05-01

    Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.

  16. Artificial Immune Networks: Models and Applications

    Directory of Open Access Journals (Sweden)

    Xian Shen

    2008-06-01

    Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.

  17. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  18. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  19. Network Design Models for Container Shipping

    DEFF Research Database (Denmark)

    Reinhardt, Line Blander; Kallehauge, Brian; Nielsen, Anders Nørrelund

    This paper presents a study of the network design problem in container shipping. The paper combines the network design and fleet assignment problem into a mixed integer linear programming model minimizing the overall cost. The major contributions of this paper is that the time of a vessel route...... is included in the calculation of the capacity and that a inhomogeneous fleet is modeled. The model also includes the cost of transshipment which is one of the major cost for the shipping companies. The concept of pseudo simple routes is introduced to expand the set of feasible routes. The linearization...

  20. Characterization and Modeling of Network Traffic

    DEFF Research Database (Denmark)

    Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

    2011-01-01

    -arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...

  1. Mashup Model and Verification Using Mashup Processing Network

    Science.gov (United States)

    Zahoor, Ehtesham; Perrin, Olivier; Godart, Claude

    Mashups are defined to be lightweight Web applications aggregating data from different Web services, built using ad-hoc composition and being not concerned with long term stability and robustness. In this paper we present a pattern based approach, called Mashup Processing Network (MPN). The idea is based on Event Processing Network and is supposed to facilitate the creation, modeling and the verification of mashups. MPN provides a view of how different actors interact for the mashup development namely the producer, consumer, mashup processing agent and the communication channels. It also supports modeling transformations and validations of data and offers validation of both functional and non-functional requirements, such as reliable messaging and security, that are key issues within the enterprise context. We have enriched the model with a set of processing operations and categorize them into data composition, transformation and validation categories. These processing operations can be seen as a set of patterns for facilitating the mashup development process. MPN also paves a way for realizing Mashup Oriented Architecture where mashups along with services are used as building blocks for application development.

  2. Phenomenological network models: Lessons for epilepsy surgery.

    Science.gov (United States)

    Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans

    2017-10-01

    The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

  3. Agent based modeling of energy networks

    International Nuclear Information System (INIS)

    Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

    2014-01-01

    Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

  4. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  5. Impacts of Sample Design for Validation Data on the Accuracy of Feedforward Neural Network Classification

    Directory of Open Access Journals (Sweden)

    Giles M. Foody

    2017-08-01

    Full Text Available Validation data are often used to evaluate the performance of a trained neural network and used in the selection of a network deemed optimal for the task at-hand. Optimality is commonly assessed with a measure, such as overall classification accuracy. The latter is often calculated directly from a confusion matrix showing the counts of cases in the validation set with particular labelling properties. The sample design used to form the validation set can, however, influence the estimated magnitude of the accuracy. Commonly, the validation set is formed with a stratified sample to give balanced classes, but also via random sampling, which reflects class abundance. It is suggested that if the ultimate aim is to accurately classify a dataset in which the classes do vary in abundance, a validation set formed via random, rather than stratified, sampling is preferred. This is illustrated with the classification of simulated and remotely-sensed datasets. With both datasets, statistically significant differences in the accuracy with which the data could be classified arose from the use of validation sets formed via random and stratified sampling (z = 2.7 and 1.9 for the simulated and real datasets respectively, for both p < 0.05%. The accuracy of the classifications that used a stratified sample in validation were smaller, a result of cases of an abundant class being commissioned into a rarer class. Simple means to address the issue are suggested.

  6. Artificial Neural Network L* from different magnetospheric field models

    Science.gov (United States)

    Yu, Y.; Koller, J.; Zaharia, S. G.; Jordanova, V. K.

    2011-12-01

    The third adiabatic invariant L* plays an important role in modeling and understanding the radiation belt dynamics. The popular way to numerically obtain the L* value follows the recipe described by Roederer [1970], which is, however, slow and computational expensive. This work focuses on a new technique, which can compute the L* value in microseconds without losing much accuracy: artificial neural networks. Since L* is related to the magnetic flux enclosed by a particle drift shell, global magnetic field information needed to trace the drift shell is required. A series of currently popular empirical magnetic field models are applied to create the L* data pool using 1 million data samples which are randomly selected within a solar cycle and within the global magnetosphere. The networks, trained from the above L* data pool, can thereby be used for fairly efficient L* calculation given input parameters valid within the trained temporal and spatial range. Besides the empirical magnetospheric models, a physics-based self-consistent inner magnetosphere model (RAM-SCB) developed at LANL is also utilized to calculate L* values and then to train the L* neural network. This model better predicts the magnetospheric configuration and therefore can significantly improve the L*. The above neural network L* technique will enable, for the first time, comprehensive solar-cycle long studies of radiation belt processes. However, neural networks trained from different magnetic field models can result in different L* values, which could cause mis-interpretation of radiation belt dynamics, such as where the source of the radiation belt charged particle is and which mechanism is dominant in accelerating the particles. Such a fact calls for attention to cautiously choose a magnetospheric field model for the L* calculation.

  7. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  8. Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

    DEFF Research Database (Denmark)

    Huang, Qian; Huang, Yue-Cai; Ko, King-Tim

    2011-01-01

    . This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing......A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...

  9. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale.

    Science.gov (United States)

    Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D; Sinatra, Maria

    2017-06-01

    Aim Research into social networking addiction has greatly increased over the last decade. However, the number of validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship between attachment styles and SNS addiction. Methods A total of 769 participants were recruited to this study. Confirmatory factor analysis (CFA) and multigroup analyses were applied to assess construct validity of the Italian version of the BSMAS. Reliability analyses comprised the average variance extracted, the standard error of measurement, and the factor determinacy coefficient. Results Indices obtained from the CFA showed the Italian version of the BSMAS to have an excellent fit of the model to the data, thus confirming the single-factor structure of the instrument. Measurement invariance was established at configural, metric, and strict invariances across age groups, and at configural and metric levels across gender groups. Internal consistency was supported by several indicators. In addition, the theoretical associations between SNS addiction and attachment styles were generally supported. Conclusion This study provides evidence that the Italian version of the BSMAS is a psychometrically robust tool that can be used in future Italian research into social networking addiction.

  10. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

  11. A Unified Access Model for Interconnecting Heterogeneous Wireless Networks

    Science.gov (United States)

    2015-05-01

    validation of the proposed network design for unified network access, and it lays the foundation for implementing a Software - Defined Networking ( SDN ...York (NY): Springer; 2014. Chapter 2, Software - defined networking ; p. 19–32. 5. Sharma S, Staessens D, Colle D, Pickavet M, Demeester P. A...demonstration of fast failure recovery in software defined networking . In: Korakis T, Zink M, Ott, M, editors. Testbeds and research infrastructure

  12. Constitutive modelling of composite biopolymer networks.

    Science.gov (United States)

    Fallqvist, B; Kroon, M

    2016-04-21

    The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Empirical model development and validation with dynamic learning in the recurrent multilayer perception

    International Nuclear Information System (INIS)

    Parlos, A.G.; Chong, K.T.; Atiya, A.F.

    1994-01-01

    A nonlinear multivariable empirical model is developed for a U-tube steam generator using the recurrent multilayer perceptron network as the underlying model structure. The recurrent multilayer perceptron is a dynamic neural network, very effective in the input-output modeling of complex process systems. A dynamic gradient descent learning algorithm is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over static learning algorithms. In developing the U-tube steam generator empirical model, the effects of actuator, process,and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response. Extensive model validation studies indicate that the empirical model can substantially generalize (extrapolate), though online learning becomes necessary for tracking transients significantly different than the ones included in the training set and slowly varying U-tube steam generator dynamics. In view of the satisfactory modeling accuracy and the associated short development time, neural networks based empirical models in some cases appear to provide a serious alternative to first principles models. Caution, however, must be exercised because extensive on-line validation of these models is still warranted

  14. Modelling students' knowledge organisation: Genealogical conceptual networks

    Science.gov (United States)

    Koponen, Ismo T.; Nousiainen, Maija

    2018-04-01

    Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks.

  15. The concept of validation of numerical models for consequence analysis

    International Nuclear Information System (INIS)

    Borg, Audun; Paulsen Husted, Bjarne; Njå, Ove

    2014-01-01

    Numerical models such as computational fluid dynamics (CFD) models are increasingly used in life safety studies and other types of analyses to calculate the effects of fire and explosions. The validity of these models is usually established by benchmark testing. This is done to quantitatively measure the agreement between the predictions provided by the model and the real world represented by observations in experiments. This approach assumes that all variables in the real world relevant for the specific study are adequately measured in the experiments and in the predictions made by the model. In this paper the various definitions of validation for CFD models used for hazard prediction are investigated to assess their implication for consequence analysis in a design phase. In other words, how is uncertainty in the prediction of future events reflected in the validation process? The sources of uncertainty are viewed from the perspective of the safety engineer. An example of the use of a CFD model is included to illustrate the assumptions the analyst must make and how these affect the prediction made by the model. The assessments presented in this paper are based on a review of standards and best practice guides for CFD modeling and the documentation from two existing CFD programs. Our main thrust has been to assess how validation work is performed and communicated in practice. We conclude that the concept of validation adopted for numerical models is adequate in terms of model performance. However, it does not address the main sources of uncertainty from the perspective of the safety engineer. Uncertainty in the input quantities describing future events, which are determined by the model user, outweighs the inaccuracies in the model as reported in validation studies. - Highlights: • Examine the basic concept of validation applied to models for consequence analysis. • Review standards and guides for validation of numerical models. • Comparison of the validation

  16. A Model of Network Porosity

    Science.gov (United States)

    2016-02-04

    of complex systems [1]. Although the ODD protocol was originally intended for individual-based or agent-based models ( ABM ), we adopt this protocol for...applies to information transfer between air-gapped systems . Trust relationships between devices (e.g. a trust relationship created by a domain controller...prevention systems , and data leakage protection systems . 2.2 ATTACKER The model specifies an attacker who gains access to internal enclaves by

  17. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

    Directory of Open Access Journals (Sweden)

    Sarah R. Haile

    2017-12-01

    Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

  18. Modeling and optimization of potable water network

    Energy Technology Data Exchange (ETDEWEB)

    Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)

    2000-07-01

    Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.

  19. Modelling dendritic ecological networks in space: An integrated network perspective

    Science.gov (United States)

    Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

  20. Models for Validation of Prior Learning (VPL)

    DEFF Research Database (Denmark)

    Ehlers, Søren

    The national policies for the education/training of adults are in the 21st century highly influenced by proposals which are formulated and promoted by The European Union (EU) as well as other transnational players and this shift in policy making has consequences. One is that ideas which in the past...... would have been categorized as utopian can become realpolitik. Validation of Prior Learning (VPL) was in Europe mainly regarded as utopian while universities in the United States of America (USA) were developing ways to obtain credits to those students which was coming with experiences from working life....

  1. PREDIKSI FOREX MENGGUNAKAN MODEL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. Hadapiningradja Kusumodestoni

    2015-11-01

    Full Text Available ABSTRAK Prediksi adalah salah satu teknik yang paling penting dalam menjalankan bisnis forex. Keputusan dalam memprediksi adalah sangatlah penting, karena dengan prediksi dapat membantu mengetahui nilai forex di waktu tertentu kedepan sehingga dapat mengurangi resiko kerugian. Tujuan dari penelitian ini dimaksudkan memprediksi bisnis fores menggunakan model neural network dengan data time series per 1 menit untuk mengetahui nilai akurasi prediksi sehingga dapat mengurangi resiko dalam menjalankan bisnis forex. Metode penelitian pada penelitian ini meliputi metode pengumpulan data kemudian dilanjutkan ke metode training, learning, testing menggunakan neural network. Setelah di evaluasi hasil penelitian ini menunjukan bahwa penerapan algoritma Neural Network mampu untuk memprediksi forex dengan tingkat akurasi prediksi 0.431 +/- 0.096 sehingga dengan prediksi ini dapat membantu mengurangi resiko dalam menjalankan bisnis forex. Kata kunci: prediksi, forex, neural network.

  2. Artificial neural network cardiopulmonary modeling and diagnosis

    Science.gov (United States)

    Kangas, Lars J.; Keller, Paul E.

    1997-01-01

    The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.

  3. A Neural Networks Based Operation Guidance System for Procedure Presentation and Validation

    International Nuclear Information System (INIS)

    Seung, Kun Mo; Lee, Seung Jun; Seong, Poong Hyun

    2006-01-01

    In this paper, a neural network based operator support system is proposed to reduce operator's errors in abnormal situations in nuclear power plants (NPPs). There are many complicated situations, in which regular and suitable operations should be done by operators accordingly. In order to regulate and validate operators' operations, it is necessary to develop an operator support system which includes computer based procedures with the functions for operation validation. Many computerized procedures systems (CPS) have been recently developed. Focusing on the human machine interface (HMI) design and procedures' computerization, most of CPSs used various methodologies to enhance system's convenience, reliability and accessibility. Other than only showing procedures, the proposed system integrates a simple CPS and an operation validation system (OVS) by using artificial neural network (ANN) for operational permission and quantitative evaluation

  4. Green Network Planning Model for Optical Backbones

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Jensen, Michael

    2010-01-01

    on the environment in general. In network planning there are existing planning models focused on QoS provisioning, investment minimization or combinations of both and other parameters. But there is a lack of a model for designing green optical backbones. This paper presents novel ideas to be able to define......Communication networks are becoming more essential for our daily lives and critically important for industry and governments. The intense growth in the backbone traffic implies an increment of the power demands of the transmission systems. This power usage might have a significant negative effect...

  5. A Model for Telestrok Network Evaluation

    DEFF Research Database (Denmark)

    Storm, Anna; Günzel, Franziska; Theiss, Stephan

    2011-01-01

    analysis lacking, current telestroke reimbursement by third-party payers is limited to special contracts and not included in the regular billing system. Based on a systematic literature review and expert interviews with health care economists, third-party payers and neurologists, a Markov model...... was developed from the third-party payer perspective. In principle, it enables telestroke networks to conduct cost-effectiveness studies, because the majority of the required data can be extracted from health insurance companies’ databases and the telestroke network itself. The model presents a basis...

  6. Data acquisition in modeling using neural networks and decision trees

    Directory of Open Access Journals (Sweden)

    R. Sika

    2011-04-01

    Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too

  7. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Daan Nieboer

    Full Text Available External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting.We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1 the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2 the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury.The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples and heterogeneous in scenario 2 (in 17%-39% of simulated samples. Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2.The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

  8. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  9. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  10. Experimental Validation of Flow Force Models for Fast Switching Valves

    DEFF Research Database (Denmark)

    Bender, Niels Christian; Pedersen, Henrik Clemmensen; Nørgård, Christian

    2017-01-01

    This paper comprises a detailed study of the forces acting on a Fast Switching Valve (FSV) plunger. The objective is to investigate to what extend different models are valid to be used for design purposes. These models depend on the geometry of the moving plunger and the properties of the surroun......This paper comprises a detailed study of the forces acting on a Fast Switching Valve (FSV) plunger. The objective is to investigate to what extend different models are valid to be used for design purposes. These models depend on the geometry of the moving plunger and the properties...... to compare and validate different models, where an effort is directed towards capturing the fluid squeeze effect just before material on material contact. The test data is compared with simulation data relying solely on analytic formulations. The general dynamics of the plunger is validated...

  11. Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks

    CERN Document Server

    Santi, Paolo

    2012-01-01

    Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and

  12. Validation of elk resource selection models with spatially independent data

    Science.gov (United States)

    Priscilla K. Coe; Bruce K. Johnson; Michael J. Wisdom; John G. Cook; Marty Vavra; Ryan M. Nielson

    2011-01-01

    Knowledge of how landscape features affect wildlife resource use is essential for informed management. Resource selection functions often are used to make and validate predictions about landscape use; however, resource selection functions are rarely validated with data from landscapes independent of those from which the models were built. This problem has severely...

  13. A Practical Approach to Validating a PD Model

    NARCIS (Netherlands)

    Medema, L.; Koning, de R.; Lensink, B.W.

    2009-01-01

    The capital adequacy framework Basel II aims to promote the adoption of stronger risk management practices by the banking industry. The implementation makes validation of credit risk models more important. Lenders therefore need a validation methodology to convince their supervisors that their

  14. A practical approach to validating a PD model

    NARCIS (Netherlands)

    Medema, Lydian; Koning, Ruud H.; Lensink, Robert; Medema, M.

    The capital adequacy framework Basel II aims to promote the adoption of stronger risk management practices by the banking industry. The implementation makes validation of credit risk models more important. Lenders therefore need a validation methodology to convince their supervisors that their

  15. Amendment to Validated dynamic flow model

    DEFF Research Database (Denmark)

    Knudsen, Torben

    2011-01-01

    The purpose of WP2 is to establish flow models relating the wind speed at turbines in a farm. Until now, active control of power reference has not been included in these models as only data with standard operation has been available. In this report the first data series with power reference excit...... turbine in undisturbed flow. For this data set both the multiplicative model and in particular the simple first order transfer function model can predict the down wind wind speed from upwind wind speed and loading.......The purpose of WP2 is to establish flow models relating the wind speed at turbines in a farm. Until now, active control of power reference has not been included in these models as only data with standard operation has been available. In this report the first data series with power reference...

  16. Modeling Renewable Penertration Using a Network Economic Model

    Science.gov (United States)

    Lamont, A.

    2001-03-01

    This paper evaluates the accuracy of a network economic modeling approach in designing energy systems having renewable and conventional generators. The network approach models the system as a network of processes such as demands, generators, markets, and resources. The model reaches a solution by exchanging prices and quantity information between the nodes of the system. This formulation is very flexible and takes very little time to build and modify models. This paper reports an experiment designing a system with photovoltaic and base and peak fossil generators. The level of PV penetration as a function of its price and the capacities of the fossil generators were determined using the network approach and using an exact, analytic approach. It is found that the two methods agree very closely in terms of the optimal capacities and are nearly identical in terms of annual system costs.

  17. Security Modeling on the Supply Chain Networks

    Directory of Open Access Journals (Sweden)

    Marn-Ling Shing

    2007-10-01

    Full Text Available In order to keep the price down, a purchaser sends out the request for quotation to a group of suppliers in a supply chain network. The purchaser will then choose a supplier with the best combination of price and quality. A potential supplier will try to collect the related information about other suppliers so he/she can offer the best bid to the purchaser. Therefore, confidentiality becomes an important consideration for the design of a supply chain network. Chen et al. have proposed the application of the Bell-LaPadula model in the design of a secured supply chain network. In the Bell-LaPadula model, a subject can be in one of different security clearances and an object can be in one of various security classifications. All the possible combinations of (Security Clearance, Classification pair in the Bell-LaPadula model can be thought as different states in the Markov Chain model. This paper extends the work done by Chen et al., provides more details on the Markov Chain model and illustrates how to use it to monitor the security state transition in the supply chain network.

  18. An evolving model of online bipartite networks

    Science.gov (United States)

    Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang

    2013-12-01

    Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.

  19. An autocatalytic network model for stock markets

    Science.gov (United States)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2015-02-01

    The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

  20. Synchronous versus asynchronous modeling of gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

    2008-09-01

    In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

  1. A validated physical model of greenhouse climate.

    NARCIS (Netherlands)

    Bot, G.P.A.

    1989-01-01

    In the greenhouse model the momentaneous environmental crop growth factors are calculated as output, together with the physical behaviour of the crop. The boundary conditions for this model are the outside weather conditions; other inputs are the physical characteristics of the crop, of the

  2. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    Directory of Open Access Journals (Sweden)

    Qi Yuan(Alan

    2010-01-01

    Full Text Available Abstract The problem of uncovering transcriptional regulation by transcription factors (TFs based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ( status and Estrogen Receptor negative ( status, respectively.

  3. Development of Artificial Neural Network Model of Crude Oil Distillation Column

    Directory of Open Access Journals (Sweden)

    Ali Hussein Khalaf

    2016-02-01

    Full Text Available Artificial neural network in MATLAB simulator is used to model Baiji crude oil distillation unit based on data generated from aspen-HYSYS simulator. Thirteen inputs, six outputs and over 1487 data set are used to model the actual unit. Nonlinear autoregressive network with exogenous inputs (NARXand back propagation algorithm are used for training. Seventy percent of data are used for training the network while the remaining  thirty percent are used for testing  and validating the network to determine its prediction accuracy. One hidden layer and 34 hidden neurons are used for the proposed network with MSE of 0.25 is obtained. The number of neuron are selected based on less MSE for the network. The model founded to predict the optimal operating conditions for different objective functions within the training limit since ANN models are poor extrapolators. They are usually only reliable within the range of data that they had been trained for.

  4. Development of Artificial Neural Network Model of Crude Oil Distillation Column

    Directory of Open Access Journals (Sweden)

    Duraid F. Ahmed

    2016-02-01

    Full Text Available Artificial neural network in MATLAB simulator is used to model Baiji crude oil distillation unit based on data generated from aspen-HYSYS simulator. Thirteen inputs, six outputs and over 1487 data set are used to model the actual unit. Nonlinear autoregressive network with exogenous inputs (NARX and back propagation algorithm are used for training. Seventy percent of data are used for training the network while the remaining thirty percent are used for testing and validating the network to determine its prediction accuracy. One hidden layer and 34 hidden neurons are used for the proposed network with MSE of 0.25 is obtained. The number of neuron are selected based on less MSE for the network. The model founded to predict the optimal operating conditions for different objective functions within the training limit since ANN models are poor extrapolators. They are usually only reliable within the range of data that they had been trained for.

  5. Applied to neuro-fuzzy models for signal validation in Angra 1 nuclear power plant

    International Nuclear Information System (INIS)

    Oliveira, Mauro Vitor de

    1999-06-01

    This work develops two models of signal validation in which the analytical redundancy of the monitored signals from an industrial plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire region of operation in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  6. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor

    International Nuclear Information System (INIS)

    Oliveira, Mauro V.; Schirru, Roberto

    2000-01-01

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  7. Statistical Validation of Engineering and Scientific Models: Background

    International Nuclear Information System (INIS)

    Hills, Richard G.; Trucano, Timothy G.

    1999-01-01

    A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made

  8. Validity of microgravity simulation models on earth

    DEFF Research Database (Denmark)

    Regnard, J; Heer, M; Drummer, C

    2001-01-01

    Many studies have used water immersion and head-down bed rest as experimental models to simulate responses to microgravity. However, some data collected during space missions are at variance or in contrast with observations collected from experimental models. These discrepancies could reflect...... incomplete knowledge of the characteristics inherent to each model. During water immersion, the hydrostatic pressure lowers the peripheral vascular capacity and causes increased thoracic blood volume and high vascular perfusion. In turn, these changes lead to high urinary flow, low vasomotor tone, and a high...

  9. Keystone Business Models for Network Security Processors

    Directory of Open Access Journals (Sweden)

    Arthur Low

    2013-07-01

    Full Text Available Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor” models nor the silicon intellectual-property licensing (“IP-licensing” models allow small technology companies to successfully compete. This article describes an alternative approach that produces an ongoing stream of novel network security processors for niche markets through continuous innovation by both large and small companies. This approach, referred to here as the "business ecosystem model for network security processors", includes a flexible and reconfigurable technology platform, a “keystone” business model for the company that maintains the platform architecture, and an extended ecosystem of companies that both contribute and share in the value created by innovation. New opportunities for business model innovation by participating companies are made possible by the ecosystem model. This ecosystem model builds on: i the lessons learned from the experience of the first author as a senior integrated circuit architect for providers of public-key cryptography solutions and as the owner of a semiconductor startup, and ii the latest scholarly research on technology entrepreneurship, business models, platforms, and business ecosystems. This article will be of interest to all technology entrepreneurs, but it will be of particular interest to owners of small companies that provide security solutions and to specialized security professionals seeking to launch their own companies.

  10. Modeling and Simulation Network Data Standards

    Science.gov (United States)

    2011-09-30

    approaches . 2.3. JNAT. JNAT is a Web application that provides connectivity and network analysis capability. JNAT uses propagation models and low-fidelity...COMBATXXI Movement Logger Data Output Dictionary. Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal...B-8 Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal Transverse Mercator (UTM) Heading

  11. The Kuramoto model in complex networks

    Science.gov (United States)

    Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

  12. An architectural model for network interconnection

    NARCIS (Netherlands)

    van Sinderen, Marten J.; Vissers, C.A.; Kalin, T.

    1983-01-01

    This paper presents a technique of successive decomposition of a common users' activity to illustrate the problems of network interconnection. The criteria derived from this approach offer a structuring principle which is used to develop an architectural model that embeds heterogeneous subnetworks

  13. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  14. A Model of Mental State Transition Network

    Science.gov (United States)

    Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

    Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

  15. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.

  16. Verification and Validation of Tropospheric Model/Database

    National Research Council Canada - National Science Library

    Junho, choi

    1998-01-01

    A verification and validation of tropospheric models and databases has been performed based on ray tracing algorithm, statistical analysis, test on real time system operation, and other technical evaluation process...

  17. Modeling Insurgent Network Structure and Dynamics

    Science.gov (United States)

    Gabbay, Michael; Thirkill-Mackelprang, Ashley

    2010-03-01

    We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.

  18. Base Flow Model Validation, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The program focuses on turbulence modeling enhancements for predicting high-speed rocket base flows. A key component of the effort is the collection of high-fidelity...

  19. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China.

    Directory of Open Access Journals (Sweden)

    Jibin Li

    Full Text Available Online social networking use has been integrated into adolescents' daily life and the intensity of online social networking use may have important consequences on adolescents' well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS and validate it among junior middle school students in China.A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods.Two factors, Social Function Use Intensity (SFUI and Entertainment Function Use Intensity (EFUI, were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach's alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, p<0.001. As expected, the SNAIS and its subscale scores were correlated significantly with emotional connection to social networking, social networking addiction, Internet addiction, and characteristics related to social networking use.The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population.

  20. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  1. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  2. Large-Scale Recurrent Neural Network Based Modelling of Gene Regulatory Network Using Cuckoo Search-Flower Pollination Algorithm.

    Science.gov (United States)

    Mandal, Sudip; Khan, Abhinandan; Saha, Goutam; Pal, Rajat K

    2016-01-01

    The accurate prediction of genetic networks using computational tools is one of the greatest challenges in the postgenomic era. Recurrent Neural Network is one of the most popular but simple approaches to model the network dynamics from time-series microarray data. To date, it has been successfully applied to computationally derive small-scale artificial and real-world genetic networks with high accuracy. However, they underperformed for large-scale genetic networks. Here, a new methodology has been proposed where a hybrid Cuckoo Search-Flower Pollination Algorithm has been implemented with Recurrent Neural Network. Cuckoo Search is used to search the best combination of regulators. Moreover, Flower Pollination Algorithm is applied to optimize the model parameters of the Recurrent Neural Network formalism. Initially, the proposed method is tested on a benchmark large-scale artificial network for both noiseless and noisy data. The results obtained show that the proposed methodology is capable of increasing the inference of correct regulations and decreasing false regulations to a high degree. Secondly, the proposed methodology has been validated against the real-world dataset of the DNA SOS repair network of Escherichia coli. However, the proposed method sacrifices computational time complexity in both cases due to the hybrid optimization process.

  3. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

    This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

  4. Propagating semantic information in biochemical network models

    Directory of Open Access Journals (Sweden)

    Schulz Marvin

    2012-01-01

    Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

  5. Communicating systems with UML 2 modeling and analysis of network protocols

    CERN Document Server

    Barrera, David Garduno

    2013-01-01

    This book gives a practical approach to modeling and analyzing communication protocols using UML 2. Network protocols are always presented with a point of view focusing on partial mechanisms and starting models. This book aims at giving the basis needed for anybody to model and validate their own protocols. It follows a practical approach and gives many examples for the description and analysis of well known basic network mechanisms for protocols.The book firstly shows how to describe and validate the main protocol issues (such as synchronization problems, client-server interactions, layer

  6. Biological dosimetry by the triage dicentric chromosome assay - Further validation of international networking

    Energy Technology Data Exchange (ETDEWEB)

    Wilkins, Ruth C., E-mail: Ruth.Wilkins@hc-sc.gc.ca [Health Canada, Ottawa, ON K1A 0K9 (Canada); Romm, Horst; Oestreicher, Ursula [Bundesamt fur Strahlenschutz, 38226 Salzgitter (Germany); Marro, Leonora [Health Canada, Ottawa, ON K1A 0K9 (Canada); Yoshida, Mitsuaki A. [Biological Dosimetry Section, Dept. of Dose Assessment, Research Center for Radiation Emergency Medicine, NIRS, 4-9-1 Anagawa, Inage-ku, Chiba 263-8555 (Japan); Department Radiation Biology, Institute of Radiation Emergency Medicine, Hirosaki University Graduate School of Health Sciences, 66-1 Hon-cho, Hirosaki, Aomori 036-8564 (Japan); Suto, Y. [Biological Dosimetry Section, Dept. of Dose Assessment, Research Center for Radiation Emergency Medicine, NIRS, 4-9-1 Anagawa, Inage-ku, Chiba 263-8555 (Japan); Prasanna, Pataje G.S. [National Cancer Institute, Division of Cancer Treatment and Diagnosis, Radiation Research Program, 6130 Executive Blvd., MSC 7440, Bethesda, MD 20892-7440 (United States)

    2011-09-15

    Biological dosimetry is an essential tool for estimating radiation doses received to personnel when physical dosimetry is not available or inadequate. The current preferred biodosimetry method is based on the measurement of radiation-specific dicentric chromosomes in exposed individuals' peripheral blood lymphocytes. However, this method is labor-, time- and expertise-demanding. Consequently, for mass casualty applications, strategies have been developed to increase its throughput. One such strategy is to develop validated cytogenetic biodosimetry laboratory networks, both national and international. In a previous study, the dicentric chromosome assay (DCA) was validated in our cytogenetic biodosimetry network involving five geographically dispersed laboratories. A complementary strategy to further enhance the throughput of the DCA among inter-laboratory networks is to use a triage DCA where dose assessments are made by truncating the labor-demanding and time-consuming metaphase spread analysis to 20 - 50 metaphase spreads instead of routine 500 - 1000 metaphase spread analysis. Our laboratory network also validated this triage DCA, however, these dose estimates were made using calibration curves generated in each laboratory from the blood samples irradiated in a single laboratory. In an emergency situation, dose estimates made using pre-existing calibration curves which may vary according to radiation type and dose rate and therefore influence the assessed dose. Here, we analyze the effect of using a pre-existing calibration curve on assessed dose among our network laboratories. The dose estimates were made by analyzing 1000 metaphase spreads as well as triage quality scoring and compared to actual physical doses applied to the samples for validation. The dose estimates in the laboratory partners were in good agreement with the applied physical doses and determined to be adequate for guidance in the treatment of acute radiation syndrome.

  7. Preliminary validation of a Monte Carlo model for IMRT fields

    International Nuclear Information System (INIS)

    Wright, Tracy; Lye, Jessica; Mohammadi, Mohammad

    2011-01-01

    Full text: A Monte Carlo model of an Elekta linac, validated for medium to large (10-30 cm) symmetric fields, has been investigated for small, irregular and asymmetric fields suitable for IMRT treatments. The model has been validated with field segments using radiochromic film in solid water. The modelled positions of the multileaf collimator (MLC) leaves have been validated using EBT film, In the model, electrons with a narrow energy spectrum are incident on the target and all components of the linac head are included. The MLC is modelled using the EGSnrc MLCE component module. For the validation, a number of single complex IMRT segments with dimensions approximately 1-8 cm were delivered to film in solid water (see Fig, I), The same segments were modelled using EGSnrc by adjusting the MLC leaf positions in the model validated for 10 cm symmetric fields. Dose distributions along the centre of each MLC leaf as determined by both methods were compared. A picket fence test was also performed to confirm the MLC leaf positions. 95% of the points in the modelled dose distribution along the leaf axis agree with the film measurement to within 1%/1 mm for dose difference and distance to agreement. Areas of most deviation occur in the penumbra region. A system has been developed to calculate the MLC leaf positions in the model for any planned field size.

  8. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  9. Modeling Multistandard Wireless Networks in OPNET

    DEFF Research Database (Denmark)

    Zakrzewska, Anna; Berger, Michael Stübert; Ruepp, Sarah Renée

    2011-01-01

    Future wireless communication is emerging towards one heterogeneous platform. In this new environment wireless access will be provided by multiple radio technologies that are cooperating and complementing one another. The paper investigates the possibilities of developing such a multistandard sys...... system using OPNET Modeler. A network model consisting of LTE interworking with WLAN and WiMAX is considered from the radio resource management perspective. In particular, implementing a joint packet scheduler across multiple systems is discussed more in detail....

  10. Modelling dendritic ecological networks in space: anintegrated network perspective

    Science.gov (United States)

    Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within

  11. Unified Model for Generation Complex Networks with Utility Preferential Attachment

    International Nuclear Information System (INIS)

    Wu Jianjun; Gao Ziyou; Sun Huijun

    2006-01-01

    In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.

  12. Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks

    Science.gov (United States)

    Zhelavskaya, I. S.; Shprits, Y.; Spasojevic, M.

    2017-12-01

    We present a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural-network-based Upper hybrid Resonance Determination) algorithm for the period of October 1, 2012 - July 1, 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2 ≤ L ≤ 6 and all local times. We validate and test the model by measuring its performance on independent datasets withheld from the training set and by comparing the model predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in-situ observations by using machine learning techniques.

  13. Validation of the simulator neutronics model

    International Nuclear Information System (INIS)

    Gregory, M.V.

    1984-01-01

    The neutronics model in the SRP reactor training simulator computes the variation with time of the neutron population in the reactor core. The power output of a reactor is directly proportional to the neutron population, thus in a very real sense the neutronics model determines the response of the simulator. The geometrical complexity of the reactor control system in SRP reactors requires the neutronics model to provide a detailed, 3D representation of the reactor core. Existing simulator technology does not allow such a detailed representation to run in real-time in a minicomputer environment, thus an entirely different approach to the problem was required. A prompt jump method has been developed in answer to this need

  14. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

    A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

  15. Traffic modelling validation of advanced driver assistance systems

    NARCIS (Netherlands)

    Tongeren, R. van; Gietelink, O.J.; Schutter, B. de; Verhaegen, M.

    2007-01-01

    This paper presents a microscopic traffic model for the validation of advanced driver assistance systems. This model describes single-lane traffic and is calibrated with data from a field operational test. To illustrate the use of the model, a Monte Carlo simulation of single-lane traffic scenarios

  16. Application of parameters space analysis tools for empirical model validation

    Energy Technology Data Exchange (ETDEWEB)

    Paloma del Barrio, E. [LEPT-ENSAM UMR 8508, Talence (France); Guyon, G. [Electricite de France, Moret-sur-Loing (France)

    2004-01-01

    A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. Both steps, as well as the underlying methods, have been presented in the first part of the paper. In this part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building. Sensitivity analysis tools have been first used to identify the parts of the model that can be really tested on the available data. A preliminary diagnosis is then supplied by principal components analysis. Useful information for model behaviour improvement has been finally obtained by optimisation techniques. This example of application shows how model parameters space analysis is a powerful tool for empirical validation. In particular, diagnosis possibilities are largely increased in comparison with residuals analysis techniques. (author)

  17. Quantitative system validation in model driven design

    DEFF Research Database (Denmark)

    Hermanns, Hilger; Larsen, Kim Guldstrand; Raskin, Jean-Francois

    2010-01-01

    The European STREP project Quasimodo1 develops theory, techniques and tool components for handling quantitative constraints in model-driven development of real-time embedded systems, covering in particular real-time, hybrid and stochastic aspects. This tutorial highlights the advances made, focus...

  18. Control of uncertain systems by feedback linearization with neural networks augmentation. Part II. Controller validation by numerical simulation

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2010-09-01

    Full Text Available The paper was conceived in two parts. Part I, previously published in this journal, highlighted the main steps of adaptive output feedback control for non-affine uncertain systems, having a known relative degree. The main paradigm of this approach was the feedback linearization (dynamic inversion with neural network augmentation. Meanwhile, based on new contributions of the authors, a new paradigm, that of robust servomechanism problem solution, has been added to the controller architecture. The current Part II of the paper presents the validation of the controller hereby obtained by using the longitudinal channel of a hovering VTOL-type aircraft as mathematical model.

  19. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...

  20. A Networks Approach to Modeling Enzymatic Reactions.

    Science.gov (United States)

    Imhof, P

    2016-01-01

    Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

  1. Model-Driven Approach for Body Area Network Application Development.

    Science.gov (United States)

    Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

    2016-05-12

    This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

  2. Model-Driven Approach for Body Area Network Application Development

    Science.gov (United States)

    Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

    2016-01-01

    This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application. PMID:27187394

  3. Model-Driven Approach for Body Area Network Application Development

    Directory of Open Access Journals (Sweden)

    Algimantas Venčkauskas

    2016-05-01

    Full Text Available This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS. We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

  4. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...

  5. Fractional virus epidemic model on financial networks

    Directory of Open Access Journals (Sweden)

    Balci Mehmet Ali

    2016-01-01

    Full Text Available In this study, we present an epidemic model that characterizes the behavior of a financial network of globally operating stock markets. Since the long time series have a global memory effect, we represent our model by using the fractional calculus. This model operates on a network, where vertices are the stock markets and edges are constructed by the correlation distances. Thereafter, we find an analytical solution to commensurate system and use the well-known differential transform method to obtain the solution of incommensurate system of fractional differential equations. Our findings are confirmed and complemented by the data set of the relevant stock markets between 2006 and 2016. Rather than the hypothetical values, we use the Hurst Exponent of each time series to approximate the fraction size and graph theoretical concepts to obtain the variables.

  6. Modelling for the Stripa site characterization and validation drift inflow: prediction of flow through fractured rock

    International Nuclear Information System (INIS)

    Herbert, A.; Gale, J.; MacLeod, R.; Lanyon, G.

    1991-12-01

    We present our approach to predicting flow through a fractured rock site; the site characterization and validation region in the Stripa mine. Our approach is based on discrete fracture network modelling using the NAPSAC computer code. We describe the conceptual models and assumptions that we have used to interpret the geometry and flow properties of the fracture networks, from measurements at the site. These are used to investigate large scale properties of the network and we show that for flows on scales larger than about 10 m, porous medium approximation should be used. The porous medium groundwater flow code CFEST is used to predict the large scale flows through the mine and the SCV region. This, in turn, is used to provide boundary conditions for more detailed models, which predict the details of flow, using a discrete fracture network model, on scales of less than 10 m. We conclude that a fracture network approach is feasible and that it provides a better understanding of details of flow than conventional porous medium approaches and a quantification of the uncertainty associated with predictive flow modelling characterised from field measurement in fractured rock. (au)

  7. Entanglement effects in model polymer networks

    Science.gov (United States)

    Everaers, R.; Kremer, K.

    The influence of topological constraints on the local dynamics in cross-linked polymer melts and their contribution to the elastic properties of rubber elastic systems are a long standing problem in statistical mechanics. Polymer networks with diamond lattice connectivity (Everaers and Kremer 1995, Everaers and Kremer 1996a) are idealized model systems which isolate the effect of topology conservation from other sources of quenched disorder. We study their behavior in molecular dynamics simulations under elongational strain. In our analysis we compare the measured, purely entropic shear moduli G to the predictions of statistical mechanical models of rubber elasticity, making extensive use of the microscopic structural and topological information available in computer simulations. We find (Everaers and Kremer 1995) that the classical models of rubber elasticity underestimate the true change in entropy in a deformed network significantly, because they neglect the tension along the contour of the strands which cannot relax due to entanglements (Everaers and Kremer (in preparation)). This contribution and the fluctuations in strained systems seem to be well described by the constrained mode model (Everaers 1998) which allows to treat the crossover from classical rubber elasticity to the tube model for polymer networks with increasing strand length within one transparant formalism. While this is important for the description of the effects we try to do a first quantitative step towards their explanation by topological considerations. We show (Everaers and Kremer 1996a) that for the comparatively short strand lengths of our diamond networks the topology contribution to the shear modulus is proportional to the density of entangled mesh pairs with non-zero Gauss linking number. Moreover, the prefactor can be estimated consistently within a rather simple model developed by Vologodskii et al. and by Graessley and Pearson, which is based on the definition of an entropic

  8. Ensuring the Validity of the Micro Foundation in DSGE Models

    DEFF Research Database (Denmark)

    Andreasen, Martin Møller

    & Primiceri (American Economic Review, forth- coming) and Fernández-Villaverde & Rubio-Ramírez (Review of Economic Studies, 2007) do not satisfy these sufficient conditions, or any other known set of conditions ensuring finite values for the objective functions. Thus, the validity of the micro foundation......The presence of i) stochastic trends, ii) deterministic trends, and/or iii) stochastic volatil- ity in DSGE models may imply that the agents' objective functions attain infinite values. We say that such models do not have a valid micro foundation. The paper derives sufficient condi- tions which...... ensure that the objective functions of the households and the firms are finite even when various trends and stochastic volatility are included in a standard DSGE model. Based on these conditions we test the validity of the micro foundation in six DSGE models from the literature. The models of Justiniano...

  9. Northern emporia and maritime networks. Modelling past communication using archaeological network analysis

    DEFF Research Database (Denmark)

    Sindbæk, Søren Michael

    2015-01-01

    preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...

  10. Functional Validation of Heteromeric Kainate Receptor Models.

    Science.gov (United States)

    Paramo, Teresa; Brown, Patricia M G E; Musgaard, Maria; Bowie, Derek; Biggin, Philip C

    2017-11-21

    Kainate receptors require the presence of external ions for gating. Most work thus far has been performed on homomeric GluK2 but, in vivo, kainate receptors are likely heterotetramers. Agonists bind to the ligand-binding domain (LBD) which is arranged as a dimer of dimers as exemplified in homomeric structures, but no high-resolution structure currently exists of heteromeric kainate receptors. In a full-length heterotetramer, the LBDs could potentially be arranged either as a GluK2 homomer alongside a GluK5 homomer or as two GluK2/K5 heterodimers. We have constructed models of the LBD dimers based on the GluK2 LBD crystal structures and investigated their stability with molecular dynamics simulations. We have then used the models to make predictions about the functional behavior of the full-length GluK2/K5 receptor, which we confirmed via electrophysiological recordings. A key prediction and observation is that lithium ions bind to the dimer interface of GluK2/K5 heteromers and slow their desensitization. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  11. Performance modeling, loss networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi

    2009-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I

  12. Validation of limited sampling models (LSM) for estimating AUC in therapeutic drug monitoring - is a separate validation group required?

    NARCIS (Netherlands)

    Proost, J. H.

    Objective: Limited sampling models (LSM) for estimating AUC in therapeutic drug monitoring are usually validated in a separate group of patients, according to published guidelines. The aim of this study is to evaluate the validation of LSM by comparing independent validation with cross-validation

  13. Sequence-based model of gap gene regulatory network.

    Science.gov (United States)

    Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

    2014-01-01

    The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

  14. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  15. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

  16. Building Modelling Methodologies for Virtual District Heating and Cooling Networks

    Energy Technology Data Exchange (ETDEWEB)

    Saurav, Kumar; Choudhury, Anamitra R.; Chandan, Vikas; Lingman, Peter; Linder, Nicklas

    2017-10-26

    District heating and cooling systems (DHC) are a proven energy solution that has been deployed for many years in a growing number of urban areas worldwide. They comprise a variety of technologies that seek to develop synergies between the production and supply of heat, cooling, domestic hot water and electricity. Although the benefits of DHC systems are significant and have been widely acclaimed, yet the full potential of modern DHC systems remains largely untapped. There are several opportunities for development of energy efficient DHC systems, which will enable the effective exploitation of alternative renewable resources, waste heat recovery, etc., in order to increase the overall efficiency and facilitate the transition towards the next generation of DHC systems. This motivated the need for modelling these complex systems. Large-scale modelling of DHC-networks is challenging, as it has several components interacting with each other. In this paper we present two building methodologies to model the consumer buildings. These models will be further integrated with network model and the control system layer to create a virtual test bed for the entire DHC system. The model is validated using data collected from a real life DHC system located at Lulea, a city on the coast of northern Sweden. The test bed will be then used for simulating various test cases such as peak energy reduction, overall demand reduction etc.

  17. Validation of nuclear models used in space radiation shielding applications

    International Nuclear Information System (INIS)

    Norman, Ryan B.; Blattnig, Steve R.

    2013-01-01

    A program of verification and validation has been undertaken to assess the applicability of models to space radiation shielding applications and to track progress as these models are developed over time. In this work, simple validation metrics applicable to testing both model accuracy and consistency with experimental data are developed. The developed metrics treat experimental measurement uncertainty as an interval and are therefore applicable to cases in which epistemic uncertainty dominates the experimental data. To demonstrate the applicability of the metrics, nuclear physics models used by NASA for space radiation shielding applications are compared to an experimental database consisting of over 3600 experimental cross sections. A cumulative uncertainty metric is applied to the question of overall model accuracy, while a metric based on the median uncertainty is used to analyze the models from the perspective of model development by examining subsets of the model parameter space.

  18. Network evolution model for supply chain with manufactures as the core

    Science.gov (United States)

    Jiang, Dali; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

    2018-01-01

    Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model. PMID:29370201

  19. Network evolution model for supply chain with manufactures as the core.

    Science.gov (United States)

    Fang, Haiyang; Jiang, Dali; Yang, Tinghong; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

    2018-01-01

    Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

  20. Network evolution model for supply chain with manufactures as the core.

    Directory of Open Access Journals (Sweden)

    Haiyang Fang

    Full Text Available Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

  1. Mapping and modeling of physician collaboration network.

    Science.gov (United States)

    Uddin, Shahadat; Hamra, Jafar; Hossain, Liaquat

    2013-09-10

    Effective provisioning of healthcare services during patient hospitalization requires collaboration involving a set of interdependent complex tasks, which needs to be carried out in a synergistic manner. Improved patients' outcome during and after hospitalization has been attributed to how effective different health services provisioning groups carry out their tasks in a coordinated manner. Previous studies have documented the underlying relationships between collaboration among physicians on the effective outcome in delivering health services for improved patient outcomes. However, there are very few systematic empirical studies with a focus on the effect of collaboration networks among healthcare professionals and patients' medical condition. On the basis of the fact that collaboration evolves among physicians when they visit a common hospitalized patient, in this study, we first propose an approach to map collaboration network among physicians from their visiting information to patients. We termed this network as physician collaboration network (PCN). Then, we use exponential random graph (ERG) models to explore the microlevel network structures of PCNs and their impact on hospitalization cost and hospital readmission rate. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks such as PCN. It simplifies a complex structure down to a combination of basic parameters such as 2-star, 3-star, and triangle. By applying our proposed mapping approach and ERG modeling technique to the electronic health insurance claims dataset of a very large Australian health insurance organization, we construct and model PCNs. We notice that the 2-star (subset of 3 nodes in which 1 node is connected to each of the other 2 nodes) parameter of ERG has significant impact on hospitalization cost. Further, we identify that triangle (subset of 3 nodes in which each node is connected to

  2. Validity and Reliability in the Assessment of the Vulnerability of Social Networks

    Directory of Open Access Journals (Sweden)

    Orantes-Jiménez Sandra Dinora

    2014-08-01

    Full Text Available Nowadays, measuring the impact and effectiveness of Social Networks is important for people who use them in an individual manner, due to social or academic interests, as well as for companies that use them to evaluate or promote their products and businesses. Particularly, it is necessary to monitor and evaluate qualitatively and quantitatively, if possible, this tool that is used for the dissemination of information of any kind. We have tried to create an instrument that aims to validate the reliability of social networks, taking Facebook our case study because it is one of the most widely used currently. This instrument is a tool that measures the "information vulnerability"; information that people decide to upload to the Internet as part of a social network. Regarding validity, a suitable solution focused on four factors was found: legality (self-regulation, social factors, psychological factors, and finally technology. It was concluded that the proposed mechanism can be a useful instrument that detects the information vulnerability storage in each social network.

  3. Composing, Analyzing and Validating Software Models

    Science.gov (United States)

    Sheldon, Frederick T.

    1998-10-01

    This research has been conducted at the Computational Sciences Division of the Information Sciences Directorate at Ames Research Center (Automated Software Engineering Grp). The principle work this summer has been to review and refine the agenda that were carried forward from last summer. Formal specifications provide good support for designing a functionally correct system, however they are weak at incorporating non-functional performance requirements (like reliability). Techniques which utilize stochastic Petri nets (SPNs) are good for evaluating the performance and reliability for a system, but they may be too abstract and cumbersome from the stand point of specifying and evaluating functional behavior. Therefore, one major objective of this research is to provide an integrated approach to assist the user in specifying both functionality (qualitative: mutual exclusion and synchronization) and performance requirements (quantitative: reliability and execution deadlines). In this way, the merits of a powerful modeling technique for performability analysis (using SPNs) can be combined with a well-defined formal specification language. In doing so, we can come closer to providing a formal approach to designing a functionally correct system that meets reliability and performance goals.

  4. Modeling In-Network Aggregation in VANETs

    NARCIS (Netherlands)

    Dietzel, Stefan; Kargl, Frank; Heijenk, Geert; Schaub, Florian

    2011-01-01

    The multitude of applications envisioned for vehicular ad hoc networks requires efficient communication and dissemination mechanisms to prevent network congestion. In-network data aggregation promises to reduce bandwidth requirements and enable scalability in large vehicular networks. However, most

  5. Different Epidemic Models on Complex Networks

    International Nuclear Information System (INIS)

    Zhang Haifeng; Small, Michael; Fu Xinchu

    2009-01-01

    Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals' relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each case. Finally, we present numerical simulations for each case to verify our results.

  6. Model validation and calibration based on component functions of model output

    International Nuclear Information System (INIS)

    Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

    2015-01-01

    The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

  7. A generalized and parameterized interference model for cognitive radio networks

    KAUST Repository

    Mahmood, Nurul Huda

    2011-06-01

    For meaningful co-existence of cognitive radios with primary system, it is imperative that the cognitive radio system is aware of how much interference it generates at the primary receivers. This can be done through statistical modeling of the interference as perceived at the primary receivers. In this work, we propose a generalized model for the interference generated by a cognitive radio network, in the presence of small and large scale fading, at a primary receiver located at the origin. We then demonstrate how this model can be used to estimate the impact of cognitive radio transmission on the primary receiver in terms of different outage probabilities. Finally, our analytical findings are validated through some selected computer-based simulations. © 2011 IEEE.

  8. Validation of model predictions of pore-scale fluid distributions during two-phase flow

    Science.gov (United States)

    Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

    2018-05-01

    Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

  9. Predicting the ungauged basin: Model validation and realism assessment

    Directory of Open Access Journals (Sweden)

    Tim evan Emmerik

    2015-10-01

    Full Text Available The hydrological decade on Predictions in Ungauged Basins (PUB led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of model outcome has not been discussed to a great extent. With this paper we aim to contribute to the discussion on how one can determine the value and validity of a hydrological model developed for an ungauged basin. As in many cases no local, or even regional, data are available, alternative methods should be applied. Using a PUB case study in a genuinely ungauged basin in southern Cambodia, we give several examples of how one can use different types of soft data to improve model design, calibrate and validate the model, and assess the realism of the model output. A rainfall-runoff model was coupled to an irrigation reservoir, allowing the use of additional and unconventional data. The model was mainly forced with remote sensing data, and local knowledge was used to constrain the parameters. Model realism assessment was done using data from surveys. This resulted in a successful reconstruction of the reservoir dynamics, and revealed the different hydrological characteristics of the two topographical classes. This paper does not present a generic approach that can be transferred to other ungauged catchments, but it aims to show how clever model design and alternative data acquisition can result in a valuable hydrological model for an ungauged catchment.

  10. The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

    International Nuclear Information System (INIS)

    Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

    2016-01-01

    Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

  11. Making Validated Educational Models Central in Preschool Standards.

    Science.gov (United States)

    Schweinhart, Lawrence J.

    This paper presents some ideas to preschool educators and policy makers about how to make validated educational models central in standards for preschool education and care programs that are available to all 3- and 4-year-olds. Defining an educational model as a coherent body of program practices, curriculum content, program and child, and teacher…

  12. Validation of ASTEC core degradation and containment models

    International Nuclear Information System (INIS)

    Kruse, Philipp; Brähler, Thimo; Koch, Marco K.

    2014-01-01

    Ruhr-Universitaet Bochum performed in a German funded project validation of in-vessel and containment models of the integral code ASTEC V2, jointly developed by IRSN (France) and GRS (Germany). In this paper selected results of this validation are presented. In the in-vessel part, the main point of interest was the validation of the code capability concerning cladding oxidation and hydrogen generation. The ASTEC calculations of QUENCH experiments QUENCH-03 and QUENCH-11 show satisfactory results, despite of some necessary adjustments in the input deck. Furthermore, the oxidation models based on the Cathcart–Pawel and Urbanic–Heidrick correlations are not suitable for higher temperatures while the ASTEC model BEST-FIT based on the Prater–Courtright approach at high temperature gives reliable enough results. One part of the containment model validation was the assessment of three hydrogen combustion models of ASTEC against the experiment BMC Ix9. The simulation results of these models differ from each other and therefore the quality of the simulations depends on the characteristic of each model. Accordingly, the CPA FRONT model, corresponding to the simplest necessary input parameters, provides the best agreement to the experimental data

  13. Validation of a multi-objective, predictive urban traffic model

    NARCIS (Netherlands)

    Wilmink, I.R.; Haak, P. van den; Woldeab, Z.; Vreeswijk, J.

    2013-01-01

    This paper describes the results of the verification and validation of the ecoStrategic Model, which was developed, implemented and tested in the eCoMove project. The model uses real-time and historical traffic information to determine the current, predicted and desired state of traffic in a

  14. Predicting the ungauged basin : Model validation and realism assessment

    NARCIS (Netherlands)

    Van Emmerik, T.H.M.; Mulder, G.; Eilander, D.; Piet, M.; Savenije, H.H.G.

    2015-01-01

    The hydrological decade on Predictions in Ungauged Basins (PUB) led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of

  15. Validating a Technology Enhanced Student-Centered Learning Model

    Science.gov (United States)

    Kang, Myunghee; Hahn, Jungsun; Chung, Warren

    2015-01-01

    The Technology Enhanced Student Centered Learning (TESCL) Model in this study presents the core factors that ensure the quality of learning in a technology-supported environment. Although the model was conceptually constructed using a student-centered learning framework and drawing upon previous studies, it should be validated through real-world…

  16. Validation of Power Requirement Model for Active Loudspeakers

    DEFF Research Database (Denmark)

    Schneider, Henrik; Madsen, Anders Normann; Bjerregaard, Ruben

    2015-01-01

    . There are however many advantages that could be harvested from such knowledge like size, cost and efficiency improvements. In this paper a recently proposed power requirement model for active loudspeakers is experimentally validated and the model is expanded to include the closed and vented type enclosures...

  17. Predicting the ungauged basin: model validation and realism assessment

    NARCIS (Netherlands)

    van Emmerik, Tim; Mulder, Gert; Eilander, Dirk; Piet, Marijn; Savenije, Hubert

    2015-01-01

    The hydrological decade on Predictions in Ungauged Basins (PUB) led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of

  18. Validation and comparison of dispersion models of RTARC DSS

    International Nuclear Information System (INIS)

    Duran, J.; Pospisil, M.

    2004-01-01

    RTARC DSS (Real Time Accident Release Consequences - Decision Support System) is a computer code developed at the VUJE Trnava, Inc. (Stubna, M. et al, 1993). The code calculations include atmospheric transport and diffusion, dose assessment, evaluation and displaying of the affected zones, evaluation of the early health effects, concentration and dose rate time dependence in the selected sites etc. The simulation of the protective measures (sheltering, iodine administration) is involved. The aim of this paper is to present the process of validation of the RTARC dispersion models. RTARC includes models for calculations of release for very short (Method Monte Carlo - MEMOC), short (Gaussian Straight-Line Model) and long distances (Puff Trajectory Model - PTM). Validation of the code RTARC was performed using the results of comparisons and experiments summarized in the Table 1.: 1. Experiments and comparisons in the process of validation of the system RTARC - experiments or comparison - distance - model. Wind tunnel experiments (Universitaet der Bundeswehr, Muenchen) - Area of NPP - Method Monte Carlo. INEL (Idaho National Engineering Laboratory) - short/medium - Gaussian model and multi tracer atmospheric experiment - distances - PTM. Model Validation Kit - short distances - Gaussian model. STEP II.b 'Realistic Case Studies' - long distances - PTM. ENSEMBLE comparison - long distances - PTM (orig.)

  19. Model Validation and Verification of Data Mining from the ...

    African Journals Online (AJOL)

    Michael Horsfall

    In this paper, we seek to present a hybrid method for Model Validation and Verification of Data Mining from the ... This model generally states the numerical value of knowledge .... procedures found in the field of software engineering should be ...

  20. Centralized Bayesian reliability modelling with sensor networks

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil; Sečkárová, Vladimíra

    2013-01-01

    Roč. 19, č. 5 (2013), s. 471-482 ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant - others:GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf

  1. Modelling Pollutant Dispersion in a Street Network

    Science.gov (United States)

    Salem, N. Ben; Garbero, V.; Salizzoni, P.; Lamaison, G.; Soulhac, L.

    2015-04-01

    This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.

  2. The Channel Network model and field applications

    International Nuclear Information System (INIS)

    Khademi, B.; Moreno, L.; Neretnieks, I.

    1999-01-01

    The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed

  3. Advances in dynamic network modeling in complex transportation systems

    CERN Document Server

    Ukkusuri, Satish V

    2013-01-01

    This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

  4. Distributed Bayesian Networks for User Modeling

    DEFF Research Database (Denmark)

    Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang

    2006-01-01

    The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used by such ada......The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...

  5. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  6. A network model for Ebola spreading.

    Science.gov (United States)

    Rizzo, Alessandro; Pedalino, Biagio; Porfiri, Maurizio

    2016-04-07

    The availability of accurate models for the spreading of infectious diseases has opened a new era in management and containment of epidemics. Models are extensively used to plan for and execute vaccination campaigns, to evaluate the risk of international spreadings and the feasibility of travel bans, and to inform prophylaxis campaigns. Even when no specific therapeutical protocol is available, as for the Ebola Virus Disease (EVD), models of epidemic spreading can provide useful insight to steer interventions in the field and to forecast the trend of the epidemic. Here, we propose a novel mathematical model to describe EVD spreading based on activity driven networks (ADNs). Our approach overcomes the simplifying assumption of homogeneous mixing, which is central to most of the mathematically tractable models of EVD spreading. In our ADN-based model, each individual is not bound to contact every other, and its network of contacts varies in time as a function of an activity potential. Our model contemplates the possibility of non-ideal and time-varying intervention policies, which are critical to accurately describe EVD spreading in afflicted countries. The model is calibrated from field data of the 2014 April-to-December spreading in Liberia. We use the model as a predictive tool, to emulate the dynamics of EVD in Liberia and offer a one-year projection, until December 2015. Our predictions agree with the current vision expressed by professionals in the field, who consider EVD in Liberia at its final stage. The model is also used to perform a what-if analysis to assess the efficacy of timely intervention policies. In particular, we show that an earlier application of the same intervention policy would have greatly reduced the number of EVD cases, the duration of the outbreak, and the infrastructures needed for the implementation of the intervention. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Modeling Network Transition Constraints with Hypergraphs

    DEFF Research Database (Denmark)

    Harrod, Steven

    2011-01-01

    Discrete time dynamic graphs are frequently used to model multicommodity flows or activity paths through constrained resources, but simple graphs fail to capture the interaction effects of resource transitions. The resulting schedules are not operationally feasible, and return inflated objective...... values. A directed hypergraph formulation is derived to address railway network sequencing constraints, and an experimental problem sample solved to estimate the magnitude of objective inflation when interaction effects are ignored. The model is used to demonstrate the value of advance scheduling...... of train paths on a busy North American railway....

  8. Mathematical model for spreading dynamics of social network worms

    International Nuclear Information System (INIS)

    Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin

    2012-01-01

    In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks

  9. Validation of heat transfer models for gap cooling

    International Nuclear Information System (INIS)

    Okano, Yukimitsu; Nagae, Takashi; Murase, Michio

    2004-01-01

    For severe accident assessment of a light water reactor, models of heat transfer in a narrow annular gap between overheated core debris and a reactor pressure vessel are important for evaluating vessel integrity and accident management. The authors developed and improved the models of heat transfer. However, validation was not sufficient for applicability of the gap heat flux correlation to the debris cooling in the vessel lower head and applicability of the local boiling heat flux correlations to the high-pressure conditions. Therefore, in this paper, we evaluated the validity of the heat transfer models and correlations by analyses for ALPHA and LAVA experiments where molten aluminum oxide (Al 2 O 3 ) at about 2700 K was poured into the high pressure water pool in a small-scale simulated vessel lower head. In the heating process of the vessel wall, the calculated heating rate and peak temperature agreed well with the measured values, and the validity of the heat transfer models and gap heat flux correlation was confirmed. In the cooling process of the vessel wall, the calculated cooling rate was compared with the measured value, and the validity of the nucleate boiling heat flux correlation was confirmed. The peak temperatures of the vessel wall in ALPHA and LAVA experiments were lower than the temperature at the minimum heat flux point between film boiling and transition boiling, so the minimum heat flux correlation could not be validated. (author)

  10. Towards a model-based development approach for wireless sensor-actuator network protocols

    DEFF Research Database (Denmark)

    Kumar S., A. Ajith; Simonsen, Kent Inge

    2014-01-01

    Model-Driven Software Engineering (MDSE) is a promising approach for the development of applications, and has been well adopted in the embedded applications domain in recent years. Wireless Sensor Actuator Networks consisting of resource constrained hardware and platformspecific operating system...... induced due to manual translations. With the use of formal semantics in the modeling approach, we can further ensure the correctness of the source model by means of verification. Also, with the use of network simulators and formal modeling tools, we obtain a verified and validated model to be used...

  11. Developing rural palliative care: validating a conceptual model.

    Science.gov (United States)

    Kelley, Mary Lou; Williams, Allison; DeMiglio, Lily; Mettam, Hilary

    2011-01-01

    The purpose of this research was to validate a conceptual model for developing palliative care in rural communities. This model articulates how local rural healthcare providers develop palliative care services according to four sequential phases. The model has roots in concepts of community capacity development, evolves from collaborative, generalist rural practice, and utilizes existing health services infrastructure. It addresses how rural providers manage challenges, specifically those related to: lack of resources, minimal community understanding of palliative care, health professionals' resistance, the bureaucracy of the health system, and the obstacles of providing services in rural environments. Seven semi-structured focus groups were conducted with interdisciplinary health providers in 7 rural communities in two Canadian provinces. Using a constant comparative analysis approach, focus group data were analyzed by examining participants' statements in relation to the model and comparing emerging themes in the development of rural palliative care to the elements of the model. The data validated the conceptual model as the model was able to theoretically predict and explain the experiences of the 7 rural communities that participated in the study. New emerging themes from the data elaborated existing elements in the model and informed the requirement for minor revisions. The model was validated and slightly revised, as suggested by the data. The model was confirmed as being a useful theoretical tool for conceptualizing the development of rural palliative care that is applicable in diverse rural communities.

  12. Importance of Computer Model Validation in Pyroprocessing Technology Development

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Y. E.; Li, Hui; Yim, M. S. [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)

    2014-05-15

    In this research, we developed a plan for experimental validation of one of the computer models developed for ER process modeling, i. e., the ERAD code. Several candidate surrogate materials are selected for the experiment considering the chemical and physical properties. Molten salt-based pyroprocessing technology is being examined internationally as an alternative to treat spent nuclear fuel over aqueous technology. The central process in pyroprocessing is electrorefining(ER) which separates uranium from transuranic elements and fission products present in spent nuclear fuel. ER is a widely used process in the minerals industry to purify impure metals. Studies of ER by using actual spent nuclear fuel materials are problematic for both technical and political reasons. Therefore, the initial effort for ER process optimization is made by using computer models. A number of models have been developed for this purpose. But as validation of these models is incomplete and often times problematic, the simulation results from these models are inherently uncertain.

  13. The turbulent viscosity models and their experimental validation; Les modeles de viscosite turbulente et leur validation experimentale

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    This workshop on turbulent viscosity models and on their experimental validation was organized by the `convection` section of the French society of thermal engineers. From the 9 papers presented during this workshop, 8 deal with the modeling of turbulent flows inside combustion chambers, turbo-machineries or in other energy-related applications, and have been selected for ETDE. (J.S.)

  14. Complex networks-based energy-efficient evolution model for wireless sensor networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)

    2009-08-30

    Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

  15. Complex networks-based energy-efficient evolution model for wireless sensor networks

    International Nuclear Information System (INIS)

    Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun

    2009-01-01

    Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

  16. Analytical models approximating individual processes: a validation method.

    Science.gov (United States)

    Favier, C; Degallier, N; Menkès, C E

    2010-12-01

    Upscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. The validity of such approximations is generally tested only on a limited range of parameter sets. A more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. This method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. As a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models. Copyright © 2010 Elsevier Inc. All rights reserved.

  17. Field validation of the contaminant transport model, FEMA

    International Nuclear Information System (INIS)

    Wong, K.-F.V.

    1986-01-01

    The work describes the validation with field data of a finite element model of material transport through aquifers (FEMA). Field data from the Idaho Chemical Processing Plant, Idaho, USA and from the 58th Street landfill in Miami, Florida, USA are used. In both cases the model was first calibrated and then integrated over a span of eight years to check on the predictive capability of the model. Both predictive runs gave results that matched well with available data. (author)

  18. Results from the Savannah River Laboratory model validation workshop

    International Nuclear Information System (INIS)

    Pepper, D.W.

    1981-01-01

    To evaluate existing and newly developed air pollution models used in DOE-funded laboratories, the Savannah River Laboratory sponsored a model validation workshop. The workshop used Kr-85 measurements and meteorology data obtained at SRL during 1975 to 1977. Individual laboratories used models to calculate daily, weekly, monthly or annual test periods. Cumulative integrated air concentrations were reported at each grid point and at each of the eight sampler locations

  19. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

    Hu Hai-Bo; Chen Jun; Guo Jin-Li

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

  20. On-line validation of feedwater flow rate in nuclear power plants using neural networks

    International Nuclear Information System (INIS)

    Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.

    1994-01-01

    On-line calibration of feedwater flow rate measurement in nuclear power plants provides a continuous realistic value of feedwater flow rate. It also reduces the manpower required for periodic calibration needed due to the fouling and defouling of the venturi meter surface condition. This paper presents a method for on-line validation of feedwater flow rate in nuclear power plants. The method is an improvement of the previously developed method which is based on the use of a set of process variables dynamically related to the feedwater flow rate. The online measurements of this set of variables are used as inputs to a neural network to obtain an estimate of the feedwater flow rate reading. The difference between the on-line feedwater flow rate reading, and the neural network estimate establishes whether there is a need to apply a correction factor to the feedwater flow rate measurement for calculation of the actual reactor power. The method was applied to the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant. The venturi meters used for flow measurements are susceptible to frequent fouling that degrades their measurement accuracy. The fouling effects can cause an inaccuracy of up to 3% relative error in feedwater flow rate reading. A neural network, whose inputs were the readings of a set of reference instruments, was designed to predict both feedwater flow rates simultaneously. A multi-layer feedforward neural network employing the backpropagation algorithm was used. A number of neural network training tests were performed to obtain an optimum filtering technique of the input/output data of the neural networks. The result of the selection of the filtering technique was confirmed by numerous Fast Fourier Transform (FFT) tests. Training and testing were done on data from TMI-1 nuclear power plant. The results show that the neural network can predict the correct flow rates with an absolute relative error of less than 2%

  1. Contact Modelling in Resistance Welding, Part II: Experimental Validation

    DEFF Research Database (Denmark)

    Song, Quanfeng; Zhang, Wenqi; Bay, Niels

    2006-01-01

    Contact algorithms in resistance welding presented in the previous paper are experimentally validated in the present paper. In order to verify the mechanical contact algorithm, two types of experiments, i.e. sandwich upsetting of circular, cylindrical specimens and compression tests of discs...... with a solid ring projection towards a flat ring, are carried out at room temperature. The complete algorithm, involving not only the mechanical model but also the thermal and electrical models, is validated by projection welding experiments. The experimental results are in satisfactory agreement...

  2. Modeling the Effect of Bandwidth Allocation on Network Performance

    African Journals Online (AJOL)

    ... The proposed model showed improved performance for CDMA networks, but further increase in the bandwidth did not benefit the network; (iii) A reliability measure such as the spectral efficiency is therefore useful to redeem the limitation in (ii). Keywords: Coverage Capacity, CDMA, Mobile Network, Network Throughput ...

  3. Aeronautical telecommunications network advances, challenges, and modeling

    CERN Document Server

    Musa, Sarhan M

    2015-01-01

    Addresses the Challenges of Modern-Day Air Traffic Air traffic control (ATC) directs aircraft in the sky and on the ground to safety, while the Aeronautical Telecommunications Network (ATN) comprises all systems and phases that assist in aircraft departure and landing. The Aeronautical Telecommunications Network: Advances, Challenges, and Modeling focuses on the development of ATN and examines the role of the various systems that link aircraft with the ground. The book places special emphasis on ATC-introducing the modern ATC system from the perspective of the user and the developer-and provides a thorough understanding of the operating mechanism of the ATC system. It discusses the evolution of ATC, explaining its structure and how it works; includes design examples; and describes all subsystems of the ATC system. In addition, the book covers relevant tools, techniques, protocols, and architectures in ATN, including MIPv6, air traffic control (ATC), security of air traffic management (ATM), very-high-frequenc...

  4. Modelling dependable systems using hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

    2008-01-01

    A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

  5. Logic integer programming models for signaling networks.

    Science.gov (United States)

    Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

    2009-05-01

    We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

  6. Generalized model for k -core percolation and interdependent networks

    Science.gov (United States)

    Panduranga, Nagendra K.; Gao, Jianxi; Yuan, Xin; Stanley, H. Eugene; Havlin, Shlomo

    2017-09-01

    Cascading failures in complex systems have been studied extensively using two different models: k -core percolation and interdependent networks. We combine the two models into a general model, solve it analytically, and validate our theoretical results through extensive simulations. We also study the complete phase diagram of the percolation transition as we tune the average local k -core threshold and the coupling between networks. We find that the phase diagram of the combined processes is very rich and includes novel features that do not appear in the models studying each of the processes separately. For example, the phase diagram consists of first- and second-order transition regions separated by two tricritical lines that merge and enclose a two-stage transition region. In the two-stage transition, the size of the giant component undergoes a first-order jump at a certain occupation probability followed by a continuous second-order transition at a lower occupation probability. Furthermore, at certain fixed interdependencies, the percolation transition changes from first-order → second-order → two-stage → first-order as the k -core threshold is increased. The analytic equations describing the phase boundaries of the two-stage transition region are set up, and the critical exponents for each type of transition are derived analytically.

  7. Impact of Loss Synchronization on Reliable High Speed Networks: A Model Based Simulation

    Directory of Open Access Journals (Sweden)

    Suman Kumar

    2014-01-01

    Full Text Available Contemporary nature of network evolution demands for simulation models which are flexible, scalable, and easily implementable. In this paper, we propose a fluid based model for performance analysis of reliable high speed networks. In particular, this paper aims to study the dynamic relationship between congestion control algorithms and queue management schemes, in order to develop a better understanding of the causal linkages between the two. We propose a loss synchronization module which is user configurable. We validate our model through simulations under controlled settings. Also, we present a performance analysis to provide insights into two important issues concerning 10 Gbps high speed networks: (i impact of bottleneck buffer size on the performance of 10 Gbps high speed network and (ii impact of level of loss synchronization on link utilization-fairness tradeoffs. The practical impact of the proposed work is to provide design guidelines along with a powerful simulation tool to protocol designers and network developers.

  8. Hysteretic recurrent neural networks: a tool for modeling hysteretic materials and systems

    International Nuclear Information System (INIS)

    Veeramani, Arun S; Crews, John H; Buckner, Gregory D

    2009-01-01

    This paper introduces a novel recurrent neural network, the hysteretic recurrent neural network (HRNN), that is ideally suited to modeling hysteretic materials and systems. This network incorporates a hysteretic neuron consisting of conjoined sigmoid activation functions. Although similar hysteretic neurons have been explored previously, the HRNN is unique in its utilization of simple recurrence to 'self-select' relevant activation functions. Furthermore, training is facilitated by placing the network weights on the output side, allowing standard backpropagation of error training algorithms to be used. We present two- and three-phase versions of the HRNN for modeling hysteretic materials with distinct phases. These models are experimentally validated using data collected from shape memory alloys and ferromagnetic materials. The results demonstrate the HRNN's ability to accurately generalize hysteretic behavior with a relatively small number of neurons. Additional benefits lie in the network's ability to identify statistical information concerning the macroscopic material by analyzing the weights of the individual neurons

  9. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-01-01

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

  10. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-11-17

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  11. Validation of spectral gas radiation models under oxyfuel conditions

    Energy Technology Data Exchange (ETDEWEB)

    Becher, Johann Valentin

    2013-05-15

    Combustion of hydrocarbon fuels with pure oxygen results in a different flue gas composition than combustion with air. Standard computational-fluid-dynamics (CFD) spectral gas radiation models for air combustion are therefore out of their validity range in oxyfuel combustion. This thesis provides a common spectral basis for the validation of new spectral models. A literature review about fundamental gas radiation theory, spectral modeling and experimental methods provides the reader with a basic understanding of the topic. In the first results section, this thesis validates detailed spectral models with high resolution spectral measurements in a gas cell with the aim of recommending one model as the best benchmark model. In the second results section, spectral measurements from a turbulent natural gas flame - as an example for a technical combustion process - are compared to simulated spectra based on measured gas atmospheres. The third results section compares simplified spectral models to the benchmark model recommended in the first results section and gives a ranking of the proposed models based on their accuracy. A concluding section gives recommendations for the selection and further development of simplified spectral radiation models. Gas cell transmissivity spectra in the spectral range of 2.4 - 5.4 {mu}m of water vapor and carbon dioxide in the temperature range from 727 C to 1500 C and at different concentrations were compared in the first results section at a nominal resolution of 32 cm{sup -1} to line-by-line models from different databases, two statistical-narrow-band models and the exponential-wide-band model. The two statistical-narrow-band models EM2C and RADCAL showed good agreement with a maximal band transmissivity deviation of 3 %. The exponential-wide-band model showed a deviation of 6 %. The new line-by-line database HITEMP2010 had the lowest band transmissivity deviation of 2.2% and was therefore recommended as a reference model for the

  12. An adaptive wavelet-network model for forecasting daily total solar-radiation

    International Nuclear Information System (INIS)

    Mellit, A.; Benghanem, M.; Kalogirou, S.A.

    2006-01-01

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet-networks are feed-forward networks using wavelets as activation functions. Wavelet-networks have been used successfully in various engineering applications such as classification, identification and control problems. In this paper, the use of adaptive wavelet-network architecture in finding a suitable forecasting model for predicting the daily total solar-radiation is investigated. Total solar-radiation is considered as the most important parameter in the performance prediction of renewable energy systems, particularly in sizing photovoltaic (PV) power systems. For this purpose, daily total solar-radiation data have been recorded during the period extending from 1981 to 2001, by a meteorological station in Algeria. The wavelet-network model has been trained by using either the 19 years of data or one year of the data. In both cases the total solar radiation data corresponding to year 2001 was used for testing the model. The network was trained to accept and handle a number of unusual cases. Results indicate that the model predicts daily total solar-radiation values with a good accuracy of approximately 97% and the mean absolute percentage error is not more than 6%. In addition, the performance of the model was compared with different neural network structures and classical models. Training algorithms for wavelet-networks require smaller numbers of iterations when compared with other neural networks. The model can be used to fill missing data in weather databases. Additionally, the proposed model can be generalized and used in different locations and for other weather data, such as sunshine duration and ambient temperature. Finally, an application using the model for sizing a PV-power system is presented in order to confirm the validity of this model

  13. Validation techniques of agent based modelling for geospatial simulations

    Directory of Open Access Journals (Sweden)

    M. Darvishi

    2014-10-01

    Full Text Available One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS, biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI’s ArcGIS, OpenMap, GeoTools, etc for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

  14. Validation techniques of agent based modelling for geospatial simulations

    Science.gov (United States)

    Darvishi, M.; Ahmadi, G.

    2014-10-01

    One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

  15. Validation of intensive care unit-acquired infection surveillance in the Italian SPIN-UTI network.

    Science.gov (United States)

    Masia, M D; Barchitta, M; Liperi, G; Cantù, A P; Alliata, E; Auxilia, F; Torregrossa, V; Mura, I; Agodi, A

    2010-10-01

    Validity is one of the most critical factors concerning surveillance of nosocomial infections (NIs). This article describes the first validation study of the Italian Nosocomial Infections Surveillance in Intensive Care Units (ICUs) project (SPIN-UTI) surveillance data. The objective was to validate infection data and thus to determine the sensitivity, specificity, and positive and negative predictive values of NI data reported on patients in the ICUs participating in the SPIN-UTI network. A validation study was performed at the end of the surveillance period. All medical records including all clinical and laboratory data were reviewed retrospectively by the trained physicians of the validation team and a positive predictive value (PPV), a negative predictive value (NPV), sensitivity and specificity were calculated. Eight ICUs (16.3%) were randomly chosen from all 49 SPIN-UTI ICUs for the validation study. In total, the validation team reviewed 832 patient charts (27.3% of the SPIN-UTI patients). The PPV was 83.5% and the NPV was 97.3%. The overall sensitivity was 82.3% and overall specificity was 97.2%. Over- and under-reporting of NIs were related to misinterpretation of the case definitions and deviations from the protocol despite previous training and instructions. The results of this study are useful to identify methodological problems within a surveillance system and have been used to plan retraining for surveillance personnel and to design and implement the second phase of the SPIN-UTI project. Copyright 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

  16. Bayesian Recurrent Neural Network for Language Modeling.

    Science.gov (United States)

    Chien, Jen-Tzung; Ku, Yuan-Chu

    2016-02-01

    A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.

  17. Validation of Computer Models for Homeland Security Purposes

    International Nuclear Information System (INIS)

    Schweppe, John E.; Ely, James; Kouzes, Richard T.; McConn, Ronald J.; Pagh, Richard T.; Robinson, Sean M.; Siciliano, Edward R.; Borgardt, James D.; Bender, Sarah E.; Earnhart, Alison H.

    2005-01-01

    At Pacific Northwest National Laboratory, we are developing computer models of radiation portal monitors for screening vehicles and cargo. Detailed models of the radiation detection equipment, vehicles, cargo containers, cargos, and radioactive sources have been created. These are used to determine the optimal configuration of detectors and the best alarm algorithms for the detection of items of interest while minimizing nuisance alarms due to the presence of legitimate radioactive material in the commerce stream. Most of the modeling is done with the Monte Carlo code MCNP to describe the transport of gammas and neutrons from extended sources through large, irregularly shaped absorbers to large detectors. A fundamental prerequisite is the validation of the computational models against field measurements. We describe the first step of this validation process, the comparison of the models to measurements with bare static sources

  18. Thermal hydraulic model validation for HOR mixed core fuel management

    International Nuclear Information System (INIS)

    Gibcus, H.P.M.; Vries, J.W. de; Leege, P.F.A. de

    1997-01-01

    A thermal-hydraulic core management model has been developed for the Hoger Onderwijsreactor (HOR), a 2 MW pool-type university research reactor. The model was adopted for safety analysis purposes in the framework of HEU/LEU core conversion studies. It is applied in the thermal-hydraulic computer code SHORT (Steady-state HOR Thermal-hydraulics) which is presently in use in designing core configurations and for in-core fuel management. An elaborate measurement program was performed for establishing the core hydraulic characteristics for a variety of conditions. The hydraulic data were obtained with a dummy fuel element with special equipment allowing a.o. direct measurement of the true core flow rate. Using these data the thermal-hydraulic model was validated experimentally. The model, experimental tests, and model validation are discussed. (author)

  19. Validation of the newborn larynx modeling with aerodynamical experimental data.

    Science.gov (United States)

    Nicollas, R; Giordano, J; Garrel, R; Medale, M; Caminat, P; Giovanni, A; Ouaknine, M; Triglia, J M

    2009-06-01

    Many authors have studied adult's larynx modelization, but the mechanisms of newborn's voice production have very rarely been investigated. After validating a numerical model with acoustic data, studies were performed on larynges of human fetuses in order to validate this model with aerodynamical experiments. Anatomical measurements were performed and a simplified numerical model was built using Fluent((R)) with the vocal folds in phonatory position. The results obtained are in good agreement with those obtained by laser Doppler velocimetry (LDV) and high-frame rate particle image velocimetry (HFR-PIV), on an experimental bench with excised human fetus larynges. It appears that computing with first cry physiological parameters leads to a model which is close to those obtained in experiments with real organs.

  20. Swelling of polymer networks with topological constraints: Application of the Helmis-Heinrich-Straube model

    Directory of Open Access Journals (Sweden)

    B. Basterra-Beroiz

    2018-08-01

    Full Text Available For the first time since its formulation in 1986, the theoretical approach proposed by Helmis, Heinrich and Straube (HHS model, which considers the contribution of topological restrictions from entanglements to the swelling of polymer networks, is applied to experimental data. The main aspects and key equations are reviewed and their application is illustrated for unfilled rubber compounds. The HHS model is based on real networks and gives new perspectives to the interpretation of experimental swelling data for which the entanglement contributions are usually neglected by considering phantom network models. This investigation applies a reliable constrained-chain approach through a deformation-dependent tube model for defining the elastic contribution of swollen networks, which is one of the main limitations on the applicability of classical (affine Flory-Rehner and (non-affine phantom models. This short communication intends to provide a baseline for the application and validation of this modern approach for a broader class of rubber materials.

  1. Research on network information security model and system construction

    OpenAIRE

    Wang Haijun

    2016-01-01

    It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the...

  2. A Complex Network Approach to Distributional Semantic Models.

    Directory of Open Access Journals (Sweden)

    Akira Utsumi

    Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.

  3. Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

    Directory of Open Access Journals (Sweden)

    Masanao Sato

    Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

  4. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale

    OpenAIRE

    Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D.; Sinatra, Maria

    2017-01-01

    Aim: Research into social networking addiction has greatly increased over the last decade. However, the number of\\ud validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been\\ud validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of\\ud the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship\\ud between attachment styles and...

  5. Validation of the dynamic model for a pressurized water reactor

    International Nuclear Information System (INIS)

    Zwingelstein, Gilles.

    1979-01-01

    Dynamic model validation is a necessary procedure to assure that the developed empirical or physical models are satisfactorily representing the dynamic behavior of the actual plant during normal or abnormal transients. For small transients, physical models which represent isolated core, isolated steam generator and the overall pressurized water reactor are described. Using data collected during the step power changes that occured during the startup procedures, comparisons of experimental and actual transients are given at 30% and 100% of full power. The agreement between the transients derived from the model and those recorded on the plant indicates that the developed models are well suited for use for functional or control studies

  6. Development and validation of a mass casualty conceptual model.

    Science.gov (United States)

    Culley, Joan M; Effken, Judith A

    2010-03-01

    To develop and validate a conceptual model that provides a framework for the development and evaluation of information systems for mass casualty events. The model was designed based on extant literature and existing theoretical models. A purposeful sample of 18 experts validated the model. Open-ended questions, as well as a 7-point Likert scale, were used to measure expert consensus on the importance of each construct and its relationship in the model and the usefulness of the model to future research. Computer-mediated applications were used to facilitate a modified Delphi technique through which a panel of experts provided validation for the conceptual model. Rounds of questions continued until consensus was reached, as measured by an interquartile range (no more than 1 scale point for each item); stability (change in the distribution of responses less than 15% between rounds); and percent agreement (70% or greater) for indicator questions. Two rounds of the Delphi process were needed to satisfy the criteria for consensus or stability related to the constructs, relationships, and indicators in the model. The panel reached consensus or sufficient stability to retain all 10 constructs, 9 relationships, and 39 of 44 indicators. Experts viewed the model as useful (mean of 5.3 on a 7-point scale). Validation of the model provides the first step in understanding the context in which mass casualty events take place and identifying variables that impact outcomes of care. This study provides a foundation for understanding the complexity of mass casualty care, the roles that nurses play in mass casualty events, and factors that must be considered in designing and evaluating information-communication systems to support effective triage under these conditions.

  7. Verification and Validation of FAARR Model and Data Envelopment Analysis Models for United States Army Recruiting

    National Research Council Canada - National Science Library

    Piskator, Gene

    1998-01-01

    ...) model and to develop a Data Envelopment Analysis (DEA) modeling strategy. First, the FAARR model was verified using a simulation of a known production function and validated using sensitivity analysis and ex-post forecasts...

  8. Continuous validation of ASTEC containment models and regression testing

    International Nuclear Information System (INIS)

    Nowack, Holger; Reinke, Nils; Sonnenkalb, Martin

    2014-01-01

    The focus of the ASTEC (Accident Source Term Evaluation Code) development at GRS is primarily on the containment module CPA (Containment Part of ASTEC), whose modelling is to a large extent based on the GRS containment code COCOSYS (COntainment COde SYStem). Validation is usually understood as the approval of the modelling capabilities by calculations of appropriate experiments done by external users different from the code developers. During the development process of ASTEC CPA, bugs and unintended side effects may occur, which leads to changes in the results of the initially conducted validation. Due to the involvement of a considerable number of developers in the coding of ASTEC modules, validation of the code alone, even if executed repeatedly, is not sufficient. Therefore, a regression testing procedure has been implemented in order to ensure that the initially obtained validation results are still valid with succeeding code versions. Within the regression testing procedure, calculations of experiments and plant sequences are performed with the same input deck but applying two different code versions. For every test-case the up-to-date code version is compared to the preceding one on the basis of physical parameters deemed to be characteristic for the test-case under consideration. In the case of post-calculations of experiments also a comparison to experimental data is carried out. Three validation cases from the regression testing procedure are presented within this paper. The very good post-calculation of the HDR E11.1 experiment shows the high quality modelling of thermal-hydraulics in ASTEC CPA. Aerosol behaviour is validated on the BMC VANAM M3 experiment, and the results show also a very good agreement with experimental data. Finally, iodine behaviour is checked in the validation test-case of the THAI IOD-11 experiment. Within this test-case, the comparison of the ASTEC versions V2.0r1 and V2.0r2 shows how an error was detected by the regression testing

  9. Validation od computational model ALDERSON/EGSnrc for chest radiography

    International Nuclear Information System (INIS)

    Muniz, Bianca C.; Santos, André L. dos; Menezes, Claudio J.M.

    2017-01-01

    To perform dose studies in situations of exposure to radiation, without exposing individuals, the numerical dosimetry uses Computational Exposure Models (ECM). Composed essentially by a radioactive source simulator algorithm, a voxel phantom representing the human anatomy and a Monte Carlo code, the ECMs must be validated to determine the reliability of the physical array representation. The objective of this work is to validate the ALDERSON / EGSnrc MCE by through comparisons between the experimental measurements obtained with the ionization chamber and virtual simulations using Monte Carlo Method to determine the ratio of the input and output radiation dose. Preliminary results of these comparisons showed that the ECM reproduced the results of the experimental measurements performed with the physical phantom with a relative error of less than 10%, validating the use of this model for simulations of chest radiographs and estimates of radiation doses in tissues in the irradiated structures

  10. A practical guide for operational validation of discrete simulation models

    Directory of Open Access Journals (Sweden)

    Fabiano Leal

    2011-04-01

    Full Text Available As the number of simulation experiments increases, the necessity for validation and verification of these models demands special attention on the part of the simulation practitioners. By analyzing the current scientific literature, it is observed that the operational validation description presented in many papers does not agree on the importance designated to this process and about its applied techniques, subjective or objective. With the expectation of orienting professionals, researchers and students in simulation, this article aims to elaborate a practical guide through the compilation of statistical techniques in the operational validation of discrete simulation models. Finally, the guide's applicability was evaluated by using two study objects, which represent two manufacturing cells, one from the automobile industry and the other from a Brazilian tech company. For each application, the guide identified distinct steps, due to the different aspects that characterize the analyzed distributions

  11. Progress in Geant4 Electromagnetic Physics Modelling and Validation

    International Nuclear Information System (INIS)

    Apostolakis, J; Burkhardt, H; Ivanchenko, V N; Asai, M; Bagulya, A; Grichine, V; Brown, J M C; Chikuma, N; Cortes-Giraldo, M A; Elles, S; Jacquemier, J; Guatelli, S; Incerti, S; Kadri, O; Maire, M; Urban, L; Pandola, L; Sawkey, D; Toshito, T; Yamashita, T

    2015-01-01

    In this work we report on recent improvements in the electromagnetic (EM) physics models of Geant4 and new validations of EM physics. Improvements have been made in models of the photoelectric effect, Compton scattering, gamma conversion to electron and muon pairs, fluctuations of energy loss, multiple scattering, synchrotron radiation, and high energy positron annihilation. The results of these developments are included in the new Geant4 version 10.1 and in patches to previous versions 9.6 and 10.0 that are planned to be used for production for run-2 at LHC. The Geant4 validation suite for EM physics has been extended and new validation results are shown in this work. In particular, the effect of gamma-nuclear interactions on EM shower shape at LHC energies is discussed. (paper)

  12. Validation of statistical models for creep rupture by parametric analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)

    2012-01-15

    Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).

  13. Multiphysics modelling and experimental validation of high concentration photovoltaic modules

    International Nuclear Information System (INIS)

    Theristis, Marios; Fernández, Eduardo F.; Sumner, Mike; O'Donovan, Tadhg S.

    2017-01-01

    Highlights: • A multiphysics modelling approach for concentrating photovoltaics was developed. • An experimental campaign was conducted to validate the models. • The experimental results were in good agreement with the models. • The multiphysics modelling allows the concentrator’s optimisation. - Abstract: High concentration photovoltaics, equipped with high efficiency multijunction solar cells, have great potential in achieving cost-effective and clean electricity generation at utility scale. Such systems are more complex compared to conventional photovoltaics because of the multiphysics effect that is present. Modelling the power output of such systems is therefore crucial for their further market penetration. Following this line, a multiphysics modelling procedure for high concentration photovoltaics is presented in this work. It combines an open source spectral model, a single diode electrical model and a three-dimensional finite element thermal model. In order to validate the models and the multiphysics modelling procedure against actual data, an outdoor experimental campaign was conducted in Albuquerque, New Mexico using a high concentration photovoltaic monomodule that is thoroughly described in terms of its geometry and materials. The experimental results were in good agreement (within 2.7%) with the predicted maximum power point. This multiphysics approach is relatively more complex when compared to empirical models, but besides the overall performance prediction it can also provide better understanding of the physics involved in the conversion of solar irradiance into electricity. It can therefore be used for the design and optimisation of high concentration photovoltaic modules.

  14. Exact model reduction of combinatorial reaction networks

    Directory of Open Access Journals (Sweden)

    Fey Dirk

    2008-08-01

    Full Text Available Abstract Background Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models. Results We introduce methods that extend and complete the already introduced approach. For instance, we provide techniques to handle the formation of multi-scaffold complexes as well as receptor dimerization. Furthermore, we discuss a new modeling approach that allows the direct generation of exactly reduced model structures. The developed methods are used to reduce a model of EGF and insulin receptor crosstalk comprising 5,182 ordinary differential equations (ODEs to a model with 87 ODEs. Conclusion The methods, presented in this contribution, significantly enhance the available methods to exactly reduce models of combinatorial reaction networks.

  15. Neural Networks For Electrohydrodynamic Effect Modelling

    Directory of Open Access Journals (Sweden)

    Wiesław Wajs

    2004-01-01

    Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.

  16. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  17. Social network models predict movement and connectivity in ecological landscapes.

    Science.gov (United States)

    Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

    2011-11-29

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  18. Neural network models of categorical perception.

    Science.gov (United States)

    Damper, R I; Harnad, S R

    2000-05-01

    Studies of the categorical perception (CP) of sensory continua have a long and rich history in psychophysics. In 1977, Macmillan, Kaplan, and Creelman introduced the use of signal detection theory to CP studies. Anderson and colleagues simultaneously proposed the first neural model for CP, yet this line of research has been less well explored. In this paper, we assess the ability of neural-network models of CP to predict the psychophysical performance of real observers with speech sounds and artificial/novel stimuli. We show that a variety of neural mechanisms are capable of generating the characteristics of CP. Hence, CP may not be a special model of perception but an emergent property of any sufficiently powerful general learning system.

  19. Combination of Bayesian Network and Overlay Model in User Modeling

    Directory of Open Access Journals (Sweden)

    Loc Nguyen

    2009-12-01

    Full Text Available The core of adaptive system is user model containing personal information such as knowledge, learning styles, goals… which is requisite for learning personalized process. There are many modeling approaches, for example: stereotype, overlay, plan recognition… but they don’t bring out the solid method for reasoning from user model. This paper introduces the statistical method that combines Bayesian network and overlay modeling so that it is able to infer user’s knowledge from evidences collected during user’s learning process.

  20. Improving Perovskite Solar Cells: Insights From a Validated Device Model

    NARCIS (Netherlands)

    Sherkar, Tejas S.; Momblona, Cristina; Gil-Escrig, Lidon; Bolink, Henk J.; Koster, L. Jan Anton

    2017-01-01

    To improve the efficiency of existing perovskite solar cells (PSCs), a detailed understanding of the underlying device physics during their operation is essential. Here, a device model has been developed and validated that describes the operation of PSCs and quantitatively explains the role of