WorldWideScience

Sample records for network extensible simulator

  1. Optimization of a hydrometric network extension using specific flow, kriging and simulated annealing

    Science.gov (United States)

    Chebbi, Afef; Kebaili Bargaoui, Zoubeida; Abid, Nesrine; da Conceição Cunha, Maria

    2017-12-01

    In hydrometric stations, water levels are continuously observed and discharge rating curves are constantly updated to achieve accurate river levels and discharge observations. An adequate spatial distribution of hydrological gauging stations presents a lot of interest in linkage with the river regime characterization, water infrastructures design, water resources management and ecological survey. Due to the increase of riverside population and the associated flood risk, hydrological networks constantly need to be developed. This paper suggests taking advantage of kriging approaches to improve the design of a hydrometric network. The context deals with the application of an optimization approach using ordinary kriging and simulated annealing (SA) in order to identify the best locations to install new hydrometric gauges. The task at hand is to extend an existing hydrometric network in order to estimate, at ungauged sites, the average specific annual discharge which is a key basin descriptor. This methodology is developed for the hydrometric network of the transboundary Medjerda River in the North of Tunisia. A Geographic Information System (GIS) is adopted to delineate basin limits and centroids. The latter are adopted to assign the location of basins in kriging development. Scenarios where the size of an existing 12 stations network is alternatively increased by 1, 2, 3, 4 and 5 new station(s) are investigated using geo-regression and minimization of the variance of kriging errors. The analysis of the optimized locations from a scenario to another shows a perfect conformity with respect to the location of the new sites. The new locations insure a better spatial coverage of the study area as seen with the increase of both the average and the maximum of inter-station distances after optimization. The optimization procedure selects the basins that insure the shifting of the mean drainage area towards higher specific discharges.

  2. Simulated Associating Polymer Networks

    Science.gov (United States)

    Billen, Joris

    Telechelic associating polymer networks consist of polymer chains terminated by endgroups that have a different chemical composition than the polymer backbone. When dissolved in a solution, the endgroups cluster together to form aggregates. At low temperature, a strongly connected reversible network is formed and the system behaves like a gel. Telechelic networks are of interest since they are representative for biopolymer networks (e.g. F-actin) and are widely used in medical applications (e.g. hydrogels for tissue engineering, wound dressings) and consumer products (e.g. contact lenses, paint thickeners). In this thesis such systems are studied by means of a molecular dynamics/Monte Carlo simulation. At first, the system in rest is studied by means of graph theory. The changes in network topology upon cooling to the gel state, are characterized. Hereto an extensive study of the eigenvalue spectrum of the gel network is performed. As a result, an in-depth investigation of the eigenvalue spectra for spatial ER, scale-free, and small-world networks is carried out. Next, the gel under the application of a constant shear is studied, with a focus on shear banding and the changes in topology under shear. Finally, the relation between the gel transition and percolation is discussed.

  3. Packet Tracer network simulator

    CERN Document Server

    Jesin, A

    2014-01-01

    A practical, fast-paced guide that gives you all the information you need to successfully create networks and simulate them using Packet Tracer.Packet Tracer Network Simulator is aimed at students, instructors, and network administrators who wish to use this simulator to learn how to perform networking instead of investing in expensive, specialized hardware. This book assumes that you have a good amount of Cisco networking knowledge, and it will focus more on Packet Tracer rather than networking.

  4. OSPF-TE Extensions for Green Routing in Optical Networks

    DEFF Research Database (Denmark)

    Wang, Jiayuan; Ricciardi, S.; Fagertun, Anna Manolova

    2012-01-01

    This paper proposes extensions to the OSPF-TE protocol to enable green routing in GMPLS-controlled optical networks. Simulation results show a remarkable reduction in CO2 emissions by preferring network elements powered by green energy sources in the connection routing....

  5. EXTENSION OPERATOR AND NEURON NETWORK

    OpenAIRE

    LUIZ CARLOS C PEDROZA

    1997-01-01

    Na tese se desenvolve a teoria do Operador de extensão (OPEX) e utiliza-se desta para compreender melhor algumas questões relativas a teoria de Redes Neurais(RN). A abordagem de Redes Neurais pela ótica do Operador de Extensão possibilita também um melhoramento no algoritmo de retropropagação de erro usado no treinamento supervisionado das Redes Neurais. In this thesis, theory of Extension Operator is developed and used to understand some questions related to ...

  6. Airport Network Flow Simulator

    Science.gov (United States)

    1978-10-01

    The Airport Network Flow Simulator is a FORTRAN IV simulation of the flow of air traffic in the nation's 600 commercial airports. It calculates for any group of selected airports: (a) the landing and take-off (Type A) delays; and (b) the gate departu...

  7. Improved Extension Neural Network and Its Applications

    Directory of Open Access Journals (Sweden)

    Yu Zhou

    2014-01-01

    Full Text Available Extension neural network (ENN is a new neural network that is a combination of extension theory and artificial neural network (ANN. The learning algorithm of ENN is based on supervised learning algorithm. One of important issues in the field of classification and recognition of ENN is how to achieve the best possible classifier with a small number of labeled training data. Training data selection is an effective approach to solve this issue. In this work, in order to improve the supervised learning performance and expand the engineering application range of ENN, we use a novel data selection method based on shadowed sets to refine the training data set of ENN. Firstly, we use clustering algorithm to label the data and induce shadowed sets. Then, in the framework of shadowed sets, the samples located around each cluster centers (core data and the borders between clusters (boundary data are selected as training data. Lastly, we use selected data to train ENN. Compared with traditional ENN, the proposed improved ENN (IENN has a better performance. Moreover, IENN is independent of the supervised learning algorithms and initial labeled data. Experimental results verify the effectiveness and applicability of our proposed work.

  8. Shipboard Calibration Network Extension Utilizing COTS Products

    Science.gov (United States)

    2014-09-01

    are generated by TCP when performing congestion control . TCP performs congestion control in the network, as defined in RFC 2581, to mitigate the...Available: https://www.wireshark.org/about.html. [22] Network Working Group. (1999, April). TCP congestion control . [Online]. Available: http...Identification TCP Transport Control Protocol VNC Virtual Network Computing WLAN Wireless Local Area Network xvi THIS PAGE INTENTIONALLY

  9. OpenFlow Extensions for Programmable Quantum Networks

    Science.gov (United States)

    2017-06-19

    systems connected via classical communication channels. These networks differ from standard classical networks by their use of quantum physical phenomena...apply our framework to a physical multinode quantum network after more testing is completed in our emulated environment. Approved for public...ARL-TR-8043 JUN 2017 US Army Research Laboratory OpenFlow Extensions for Programmable Quantum Networks by Venkat Dasari

  10. GNS3 network simulation guide

    CERN Document Server

    Welsh, Chris

    2013-01-01

    GNS3 Network Simulation Guide is an easy-to-follow yet comprehensive guide which is written in a tutorial format helping you grasp all the things you need for accomplishing your certification or simulation goal. If you are a networking professional who wants to learn how to simulate networks using GNS3, this book is ideal for you. The introductory examples within the book only require minimal networking knowledge, but as the book progresses onto more advanced topics, users will require knowledge of TCP/IP and routing.

  11. Twitter Chats: Connect, Foster, and Engage Internal Extension Networks

    Science.gov (United States)

    Seger, Jamie; Hill, Paul; Stafne, Eric; Swadley, Emy

    2017-01-01

    The eXtension Educational Technology Learning Network (EdTechLN) has found Twitter to be an effective form of informal communication for routinely engaging network members. Twitter chats provide Extension professionals an opportunity to reach and engage one other. As the EdTechLN's experimentation with Twitter chats has demonstrated, the use of…

  12. Topology Design for Directional Range Extension Networks with Antenna Blockage

    Science.gov (United States)

    2016-11-01

    Topology Design for Directional Range Extension Networks with Antenna Blockage Thomas Shake MIT Lincoln Laboratory shake@ll.mit.edu Abstract...associated electronics into small aircraft to perform such range extension. In particular, the paper examines trade-offs in network topology design...aircraft, and the topology characteristics of the aerial relay network. The analysis suggests that low-degree air topologies such as rings and strings

  13. Simulation of Stimuli-Responsive Polymer Networks

    Directory of Open Access Journals (Sweden)

    Thomas Gruhn

    2013-11-01

    Full Text Available The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.

  14. Optimizing the network topology of block copolymer liquid crystal elastomers for enhanced extensibility and toughness

    Science.gov (United States)

    Nowak, Christian; Escobedo, Fernando A.

    2017-08-01

    Molecular simulations are used to study the effect of synthesis conditions on the tensile response of liquid-crystalline elastomers formed by block copolymer chains. Remarkably, it is found that despite the significant presence of trapped entanglements, these networks can exhibit the sawtooth tensile response previously predicted for ideal unentangled networks. It is also found that the monomer concentration during crosslinking can be tuned to limit the extent of entanglements and inhomogeneities while also maximizing network extensibility. It is predicted that networks synthesized at a "critical" concentration will have the greatest toughness.

  15. Poverty Simulations: Building Relationships among Extension, Schools, and the Community

    Science.gov (United States)

    Franck, Karen L.; Barnes, Shelly; Harrison, Julie

    2016-01-01

    Poverty simulations can be effective experiential learning tools for educating community members about the impact of poverty on families. The project described here includes survey results from three simulations with community leaders and teachers. This project illustrated how such workshops can help Extension professionals extend their reach and…

  16. Routing protocol extension for resilient GMPLS multi-domain networks

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Ruepp, Sarah Renée; Romeral, Ricardo

    2010-01-01

    This paper evaluates the performance of multi-domain networks under the Generalized Multi-Protocol Label Switching control framework in case of a single inter-domain link failure. We propose and evaluate a routing protocol extension for the Border Gateway Protocol, which allows domains to obtain...

  17. A Collaborative Extensible User Environment for Simulation and Knowledge Management

    Energy Technology Data Exchange (ETDEWEB)

    Freedman, Vicky L.; Lansing, Carina S.; Porter, Ellen A.; Schuchardt, Karen L.; Guillen, Zoe C.; Sivaramakrishnan, Chandrika; Gorton, Ian

    2015-06-01

    In scientific simulation, scientists use measured data to create numerical models, execute simulations and analyze results from advanced simulators executing on high performance computing platforms. This process usually requires a team of scientists collaborating on data collection, model creation and analysis, and on authorship of publications and data. This paper shows that scientific teams can benefit from a user environment called Akuna that permits subsurface scientists in disparate locations to collaborate on numerical modeling and analysis projects. The Akuna user environment is built on the Velo framework that provides both a rich client environment for conducting and analyzing simulations and a Web environment for data sharing and annotation. Akuna is an extensible toolset that integrates with Velo, and is designed to support any type of simulator. This is achieved through data-driven user interface generation, use of a customizable knowledge management platform, and an extensible framework for simulation execution, monitoring and analysis. This paper describes how the customized Velo content management system and the Akuna toolset are used to integrate and enhance an effective collaborative research and application environment. The extensible architecture of Akuna is also described and demonstrates its usage for creation and execution of a 3D subsurface simulation.

  18. OPTIC NERVE MENINGOCELE SIMULATING EXTRAOCULAR EXTENSION OF CHOROIDAL MELANOMA.

    Science.gov (United States)

    Sioufi, Kareem; Say, Emil Anthony T; Gray, Hilary M; Shields, Carol L

    2017-01-01

    To report a case of optic nerve meningocele simulating massive, recurrent extraocular extension of choroidal melanoma. Case report. A 53-year-old white man with choroidal melanoma in his left eye of 7.3-mm thickness was treated with plaque radiotherapy and transpupillary thermotherapy. On 1-year follow-up examination, visual acuity was 20/20 in the right eye and 20/30 in the left eye. The regressed choroidal melanoma scar in the left eye measured 1.5 mm in thickness with stable margins. The optic disk was normal. Ultrasonography demonstrated regressed echogenic choroidal scar, with an echolucent multilobulated retrobulbar mass, suspicious for extraocular extension. On magnetic resonance imaging, the retrobulbar mass corresponded to a distended and kinked optic nerve sheath, filled with extensive subarachnoid fluid and normal-size optic nerve with apposition against the posterior globe. There was no extraocular extension of tumor. Similar but less distended right optic nerve sheath was documented, consistent with optic nerve sheath meningocele in both eyes. Observation was advised and the findings remained stable. Optic nerve sheath meningocele is a benign dilatation of the optic nerve sheath that can simulate orbital tumor or extraocular extension of intraocular tumor. Magnetic resonance imaging can reliably differentiate these conditions.

  19. Extension of Pairwise Broadcast Clock Synchronization for Multicluster Sensor Networks

    Directory of Open Access Journals (Sweden)

    Bruce W. Suter

    2008-01-01

    Full Text Available Time synchronization is crucial for wireless sensor networks (WSNs in performing a number of fundamental operations such as data coordination, power management, security, and localization. The Pairwise Broadcast Synchronization (PBS protocol was recently proposed to minimize the number of timing messages required for global network synchronization, which enables the design of highly energy-efficient WSNs. However, PBS requires all nodes in the network to lie within the communication ranges of two leader nodes, a condition which might not be available in some applications. This paper proposes an extension of PBS to the more general class of sensor networks. Based on the hierarchical structure of the network, an energy-efficient pair selection algorithm is proposed to select the best pairwise synchronization sequence to reduce the overall energy consumption. It is shown that in a multicluster networking environment, PBS requires a far less number of timing messages than other well-known synchronization protocols and incurs no loss in synchronization accuracy. Moreover, the proposed scheme presents significant energy savings for densely deployed WSNs.

  20. Chaotic Extension Neural Network-Based Fault Diagnosis Method for Solar Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Kuo-Nan Yu

    2014-01-01

    Full Text Available At present, the solar photovoltaic system is extensively used. However, once a fault occurs, it is inspected manually, which is not economical. In order to remedy the defect of unavailable fault diagnosis at any irradiance and temperature in the literature with chaos synchronization based intelligent fault diagnosis for photovoltaic systems proposed by Hsieh et al., this study proposed a chaotic extension fault diagnosis method combined with error back propagation neural network to overcome this problem. It used the nn toolbox of matlab 2010 for simulation and comparison, measured current irradiance and temperature, and used the maximum power point tracking (MPPT for chaotic extraction of eigenvalue. The range of extension field was determined by neural network. Finally, the voltage eigenvalue obtained from current temperature and irradiance was used for the fault diagnosis. Comparing the diagnostic rates with the results by Hsieh et al., this scheme can obtain better diagnostic rates when the irradiances or the temperatures are changed.

  1. Introduction to Network Simulator NS2

    CERN Document Server

    Issariyakul, Teerawat

    2008-01-01

    A beginners' guide for network simulator NS2, an open-source discrete event simulator designed mainly for networking research. It presents two fundamental NS2 concepts: how objects are assembled to create a network and how a packet flows from one object to another

  2. Trace Replay and Network Simulation Tool

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.

  3. SDL-based network performance simulation

    Science.gov (United States)

    Yang, Yang; Lu, Yang; Lin, Xiaokang

    2005-11-01

    Specification and description language (SDL) is an object-oriented formal language defined as a standard by ITU-T. Though SDL is mainly used in describing communication protocols, it is an efficient way to simulate the network performance with SDL tools according to our experience. This paper presents our methodology of SDL-based network performance simulation in such aspects as the simulation platform, the simulation modes and the integrated simulation environment. Note that Telelogic Tau 4.3 SDL suite is used here as the simulation environment though our methodology isn't limited to the software. Finally the SDL-based open shortest path first (OSPF) performance simulation in the wireless private network is illustrated as an example of our methodology, which indicates that SDL is indeed an efficient language in the area of the network performance simulation.

  4. Introduction to Network Simulator NS2

    CERN Document Server

    Issariyakul, Teerawat

    2012-01-01

    "Introduction to Network Simulator NS2" is a primer providing materials for NS2 beginners, whether students, professors, or researchers for understanding the architecture of Network Simulator 2 (NS2) and for incorporating simulation modules into NS2. The authors discuss the simulation architecture and the key components of NS2 including simulation-related objects, network objects, packet-related objects, and helper objects. The NS2 modules included within are nodes, links, SimpleLink objects, packets, agents, and applications. Further, the book covers three helper modules: timers, ra

  5. 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.

  6. Hierarchical Network Design Using Simulated Annealing

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Clausen, Jens

    2002-01-01

    networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub...

  7. Vectorized algorithms for spiking neural network simulation.

    Science.gov (United States)

    Brette, Romain; Goodman, Dan F M

    2011-06-01

    High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

  8. A user oriented active network simulator

    Science.gov (United States)

    Rao, K. S.; Swamy, M. N. S.

    1980-07-01

    A digital computer simulator for the frequency response and tolerance analysis of an electrical network comprising RLCM elements, ideal operational amplifiers and controlled sources is presented in this tutorial paper. The simulator is based on 'tableau approach'. Reordering of the sparse tableau matrix is done using Markowitz Criterion and the diagonal pivots are chosen for simplicity. The simulator also employs dynamic allocation for maximum utilization of memory and faster turn around time. Three networks are simulated and their results are presented in this paper. A network in which the operational amplifiers are assumed to have single pole behaviour is also analyzed.

  9. Extension of a human visual system model for display simulation

    Science.gov (United States)

    Marchessoux, Cédric; Rombaut, Alexis; Kimpe, Tom; Vermeulen, Brecht; Demeester, Piet

    2008-02-01

    In the context of medical display validation, a simulation chain has been developed to facilitate display design and image quality validation. One important part is the human visual observer model to quantify the quality perception of the simulated images. Since several years, multiple research groups are modeling the various aspects of human perception to integrate them in a complete Human Visual System (HVS) and developing visible image difference metrics. In our framework, the JNDmetrix is used. It reflects the human subjective assessment of images or video fidelity. Nevertheless, the system is limited and not suitable for our accurate simulations. There is a limitation to RGB 8 bits integer images and the model takes into account display parameters like gamma, black offset, ambient light... It needs to be extended. The solutions proposed to extend the HVS model are: precision enhancement to overcome the 8 bit limit, color space conversion between XYZ and RGB and adaptation to the display parameters. The preprocessing does not introduce any kind of perceived distortion caused for example by precision enhancement. With this extension the model is used in a daily basis in the display simulation chain.

  10. Program Aids Simulation Of Neural Networks

    Science.gov (United States)

    Baffes, Paul T.

    1990-01-01

    Computer program NETS - Tool for Development and Evaluation of Neural Networks - provides simulation of neural-network algorithms plus software environment for development of such algorithms. Enables user to customize patterns of connections between layers of network, and provides features for saving weight values of network, providing for more precise control over learning process. Consists of translating problem into format using input/output pairs, designing network configuration for problem, and finally training network with input/output pairs until acceptable error reached. Written in C.

  11. Experimental demonstration of OSPF-TE extensions in muiti-domain OBS networks connected by GMPLS network

    Science.gov (United States)

    Tian, Chunlei; Yin, Yawei; Wu, Jian; Lin, Jintong

    2008-11-01

    The interworking network of Generalized Multi-Protocol Label Switching (GMPLS) and Optical Burst Switching (OBS) is attractive network architecture for the future IP/DWDM network nowadays. In this paper, OSPF-TE extensions for multi-domain Optical Burst Switching networks connected by GMPLS controlled WDM network are proposed, the corresponding experimental results such as the advertising latency are also presented by using an OBS network testbed. The experimental results show that it works effectively on the OBS/GMPLS networks.

  12. Extensions to Dynamic System Simulation of Fissile Solution Systems

    Energy Technology Data Exchange (ETDEWEB)

    Klein, Steven Karl [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bernardin, John David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kimpland, Robert Herbert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Spernjak, Dusan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-08-24

    Previous reports have documented the results of applying dynamic system simulation (DSS) techniques to model a variety of fissile solution systems. The SUPO (Super Power) aqueous homogeneous reactor (AHR) was chosen as the benchmark for comparison of model results to experimental data for steadystate operation.1 Subsequently, DSS was applied to additional AHR to verify results obtained for SUPO and extend modeling to prompt critical excursions, ramp reactivity insertions of various magnitudes and rate, and boiling operations in SILENE and KEWB (Kinetic Experiment Water Boiler).2 Additional models for pressurized cores (HRE: Homogeneous Reactor Experiment), annular core geometries, and accelerator-driven subcritical systems (ADAHR) were developed and results reported.3 The focus of each of these models is core dynamics; neutron kinetics, thermal hydraulics, radiolytic gas generation and transport are coupled to examine the time-based evolution of these systems from start-up through transition to steady-state. A common characteristic of these models is the assumption that (a) core cooling system inlet temperature and flow and (b) plenum gas inlet pressure and flow are held constant; no external (to core) component operations that may result in dynamic change to these parameters are considered. This report discusses extension of models to include explicit reference to cooling structures and radiolytic gas handling. The accelerator-driven subcritical generic system model described in References 3 and 4 is used as a basis for this extension.

  13. Hand Recognition Using Thermal Image and Extension Neural Network

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2012-01-01

    Full Text Available Hand recognition is one of the popular biometry methods for access control systems. In this paper, a new scheme for personal recognition using thermal images of the hand and an extension neural network (ENN is presented. The features of the recognition system are extracted from gray level hand images, which are taken by an infrared camera. The main advantage of the thermal image is that it can reduce errors and noise in the features extracted stage, which is most important to increase the accuracy of recognition systems. Moreover, a new recognition method based on the ENN is proposed to perform the core functions of the hand recognition system. The proposed ENN-based recognition method also permits rapid adaptive processing for a new pattern, as it only tunes the boundaries of classified features or adds a new neural node. It is feasible to implement the proposed method on a Microcomputer for a portable personal recognition device. From the tested examples, the proposed method has a significantly high degree of recognition accuracy and shows good tolerance to errors added.

  14. Buffer Management Simulation in ATM Networks

    Science.gov (United States)

    Yaprak, E.; Xiao, Y.; Chronopoulos, A.; Chow, E.; Anneberg, L.

    1998-01-01

    This paper presents a simulation of a new dynamic buffer allocation management scheme in ATM networks. To achieve this objective, an algorithm that detects congestion and updates the dynamic buffer allocation scheme was developed for the OPNET simulation package via the creation of a new ATM module.

  15. Network simulations of optical illusions

    Science.gov (United States)

    Shinbrot, Troy; Lazo, Miguel Vivar; Siu, Theo

    We examine a dynamical network model of visual processing that reproduces several aspects of a well-known optical illusion, including subtle dependencies on curvature and scale. The model uses a genetic algorithm to construct the percept of an image, and we show that this percept evolves dynamically so as to produce the illusions reported. We find that the perceived illusions are hardwired into the model architecture and we propose that this approach may serve as an archetype to distinguish behaviors that are due to nature (i.e. a fixed network architecture) from those subject to nurture (that can be plastically altered through learning).

  16. Network Simulation of Technical Architecture

    National Research Council Canada - National Science Library

    Cave, William

    1998-01-01

    ..., and development of the Army Battle Command System (ABCS). PSI delivered a hierarchical iconic modeling facility that can be used to structure and restructure both models and scenarios, interactively, while simulations are running...

  17. Extension of Generalized Fluid System Simulation Program's Fluid Property Database

    Science.gov (United States)

    Patel, Kishan

    2011-01-01

    This internship focused on the development of additional capabilities for the General Fluid Systems Simulation Program (GFSSP). GFSSP is a thermo-fluid code used to evaluate system performance by a finite volume-based network analysis method. The program was developed primarily to analyze the complex internal flow of propulsion systems and is capable of solving many problems related to thermodynamics and fluid mechanics. GFSSP is integrated with thermodynamic programs that provide fluid properties for sub-cooled, superheated, and saturation states. For fluids that are not included in the thermodynamic property program, look-up property tables can be provided. The look-up property tables of the current release version can only handle sub-cooled and superheated states. The primary purpose of the internship was to extend the look-up tables to handle saturated states. This involves a) generation of a property table using REFPROP, a thermodynamic property program that is widely used, and b) modifications of the Fortran source code to read in an additional property table containing saturation data for both saturated liquid and saturated vapor states. Also, a method was implemented to calculate the thermodynamic properties of user-fluids within the saturation region, given values of pressure and enthalpy. These additions required new code to be written, and older code had to be adjusted to accommodate the new capabilities. Ultimately, the changes will lead to the incorporation of this new capability in future versions of GFSSP. This paper describes the development and validation of the new capability.

  18. Implementation of quantum key distribution network simulation module in the network simulator NS-3

    Science.gov (United States)

    Mehic, Miralem; Maurhart, Oliver; Rass, Stefan; Voznak, Miroslav

    2017-10-01

    As the research in quantum key distribution (QKD) technology grows larger and becomes more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. Due to the specificity of the QKD link which requires optical and Internet connection between the network nodes, to deploy a complete testbed containing multiple network hosts and links to validate and verify a certain network algorithm or protocol would be very costly. Network simulators in these circumstances save vast amounts of money and time in accomplishing such a task. The simulation environment offers the creation of complex network topologies, a high degree of control and repeatable experiments, which in turn allows researchers to conduct experiments and confirm their results. In this paper, we described the design of the QKD network simulation module which was developed in the network simulator of version 3 (NS-3). The module supports simulation of the QKD network in an overlay mode or in a single TCP/IP mode. Therefore, it can be used to simulate other network technologies regardless of QKD.

  19. The Airport Network Flow Simulator.

    Science.gov (United States)

    1976-05-01

    The impact of investment at an individual airport is felt through-out the National Airport System by reduction of delays at other airports in the the system. A GPSS model was constructed to simulate the propagation of delays through a nine-airport sy...

  20. Networked Learning for Agricultural Extension: A Framework for Analysis and Two Cases

    Science.gov (United States)

    Kelly, Nick; Bennett, John McLean; Starasts, Ann

    2017-01-01

    Purpose: This paper presents economic and pedagogical motivations for adopting information and communications technology (ICT)- mediated learning networks in agricultural education and extension. It proposes a framework for networked learning in agricultural extension and contributes a theoretical and case-based rationale for adopting the…

  1. Dynamic simulation of regulatory networks using SQUAD

    Directory of Open Access Journals (Sweden)

    Xenarios Ioannis

    2007-11-01

    Full Text Available Abstract Background The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. Results We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. Conclusion The simulation of regulatory networks aims at predicting the behavior of a whole system when subject

  2. Transport network extensions for accessibility analysis in geographic information systems

    NARCIS (Netherlands)

    Jong, Tom de; Tillema, T.

    2005-01-01

    In many developed countries high quality digital transport networks are available for GIS based analysis. Partly this is due to the requirements of route planning software for internet and car navigation systems. Properties of these networks consist among others of road quality attributes,

  3. Network analysis of knowledge building on rural extension in Colombia

    National Research Council Canada - National Science Library

    Holmes Rodríguez; Carlos Julián Ramírez-Gómez; Norman Aguilar-Gallegos; Jorge Aguilar-Ávila

    2016-01-01

    Based on the analysis of scientific papers published on rural extension in Colombia since 2010, an interpretive descriptive study was conducted to identify the level of collaboration between authors...

  4. Maximizing Interconnectedness and Availability in Directional Airborne RangeExtension Networks

    Science.gov (United States)

    2017-10-25

    surveyed advances in directional networking , noting much work in topology management , medium access control algorithms, aircraft-based directional... networks . Other issues, such as topology management and spectrum management , also require further research and development to enable high-quality...Maximizing Interconnectedness and Availability in Directional Airborne Range Extension Networks Thomas Shake, Rahul Amin MIT Lincoln Laboratory

  5. Efficient simulation of a tandem Jackson network

    NARCIS (Netherlands)

    Kroese, Dirk; Nicola, V.F.

    2002-01-01

    The two-node tandem Jackson network serves as a convenient reference model for the analysis and testing of different methodologies and techniques in rare event simulation. In this paper we consider a new approach to efficiently estimate the probability that the content of the second buffer exceeds

  6. Parameter estimation in channel network flow simulation

    Directory of Open Access Journals (Sweden)

    Han Longxi

    2008-03-01

    Full Text Available Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.

  7. SELENE - Self-Forming Extensible Lunar EVA Network Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Lunar EVA network will exhibit a wide range of connectivity levels due to the challenging communications environment and mission dynamics. Disruption-Tolerant...

  8. Connect the dot: Computing feed-links for network extension

    Directory of Open Access Journals (Sweden)

    Boris Aronov

    2011-12-01

    Full Text Available Road network analysis can require distance from points that are not on the network themselves. We study the algorithmic problem of connecting a point inside a face (region of the road network to its boundary while minimizing the detour factor of that point to any point on the boundary of the face. We show that the optimal single connection (feed-link can be computed in O(lambda_7(n log n time, where n is the number of vertices that bounds the face and lambda_7(n is the slightly superlinear maximum length of a Davenport-Schinzel sequence of order 7 on n symbols. We also present approximation results for placing more feed-links, deal with the case that there are obstacles in the face of the road network that contains the point to be connected, and present various related results.

  9. SELENE - Self-Forming Extensible Lunar EVA Network Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall objective of this research effort (Phase I and Phase II) by Scientific Systems Company, Inc. and BBN Technologies is to develop the SELENE network --...

  10. Maximum Interconnectedness and Availability for Directional Airborne Range Extension Networks

    Science.gov (United States)

    2016-08-29

    affecting the design and management of the network topology [2][3]. In particular, such blockages can cause significant periods of unavailability of the...a standard definition in graph theoretic and networking literature that is related to, but different from, the metric we consider. August 29, 2016...of their flightpaths are assumed to be small compared to the distance between the aircraft. A representative node layout is illustrated in Fig. 5

  11. Realistic computer network simulation for network intrusion detection dataset generation

    Science.gov (United States)

    Payer, Garrett

    2015-05-01

    The KDD-99 Cup dataset is dead. While it can continue to be used as a toy example, the age of this dataset makes it all but useless for intrusion detection research and data mining. Many of the attacks used within the dataset are obsolete and do not reflect the features important for intrusion detection in today's networks. Creating a new dataset encompassing a large cross section of the attacks found on the Internet today could be useful, but would eventually fall to the same problem as the KDD-99 Cup; its usefulness would diminish after a period of time. To continue research into intrusion detection, the generation of new datasets needs to be as dynamic and as quick as the attacker. Simply examining existing network traffic and using domain experts such as intrusion analysts to label traffic is inefficient, expensive, and not scalable. The only viable methodology is simulation using technologies including virtualization, attack-toolsets such as Metasploit and Armitage, and sophisticated emulation of threat and user behavior. Simulating actual user behavior and network intrusion events dynamically not only allows researchers to vary scenarios quickly, but enables online testing of intrusion detection mechanisms by interacting with data as it is generated. As new threat behaviors are identified, they can be added to the simulation to make quicker determinations as to the effectiveness of existing and ongoing network intrusion technology, methodology and models.

  12. Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

    Science.gov (United States)

    Shen, Lin; Wu, Jingheng; Yang, Weitao

    2016-10-11

    Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.

  13. Simulating Autonomous Telecommunication Networks for Space Exploration

    Science.gov (United States)

    Segui, John S.; Jennings, Esther H.

    2008-01-01

    Currently, most interplanetary telecommunication systems require human intervention for command and control. However, considering the range from near Earth to deep space missions, combined with the increase in the number of nodes and advancements in processing capabilities, the benefits from communication autonomy will be immense. Likewise, greater mission science autonomy brings the need for unscheduled, unpredictable communication and network routing. While the terrestrial Internet protocols are highly developed their suitability for space exploration has been questioned. JPL has developed the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to help characterize network designs and protocols. The results will allow future mission planners to better understand the trade offs of communication protocols. This paper discusses various issues with interplanetary network and simulation results of interplanetary networking protocols.

  14. An overview of the fire and fuels extension to the forest vegetation simulator

    Science.gov (United States)

    Sarah J. Beukema; Elizabeth D. Reinhardt; Werner A. Kurz; Nicholas L. Crookston

    2000-01-01

    The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) has been developed to assess the risk, behavior, and impact of fire in forest ecosystems. This extension to the widely-used stand-dynamics model FVS simulates the dynamics of snags and surface fuels as they are affected by stand management (of trees or fuels), live tree growth and mortality,...

  15. Composite Extension Finite Fields for Low Overhead Network Coding

    DEFF Research Database (Denmark)

    Heide, Janus; Roetter, Daniel Enrique Lucani

    2015-01-01

    packet. This work advocates the use of multiple composite extension finite fields to address these challenges. The key of our approach is to design a series of finite fields where increasingly larger fields are based on a previous smaller field. For example, the design of a field with 256 elements F2222...

  16. Large Amplitude Oscillatory Extension of Soft Polymeric Networks

    DEFF Research Database (Denmark)

    Bejenariu, Anca Gabriela; Rasmussen, Henrik K.; Skov, Anne Ladegaard

    2010-01-01

    sing a filament stretching rheometer (FSR) surrounded by a thermostatic chamber and equipped with a micrometric laser it is possible to measure large amplitude oscillatory elongation (LAOE) on elastomeric based networks with no base flow as in the LAOE method for polymer melts. Poly...

  17. Real-time security extensions for EPCglobal networks case study for the pharmaceutical industry

    CERN Document Server

    Schapranow, Matthieu-P

    2014-01-01

    This book reviews the design of real-time security extensions for EPCglobal networks based on in-memory technology, presents authentication protocols for devices with low computational resources and outlines steps for implementing history-based access control.

  18. Cooperative Coverage Extension in Land Mobile Satellite Networks

    OpenAIRE

    Cocco, Giuseppe; Alagha, Nader; Ibars, Christian

    2014-01-01

    This chapter is dedicated to the application of cooperative relaying in heterogeneous land mobile satellite (LMS) systems. Vehicular terminals are considered. We focus on a Urban scenario, an environment characterized by intermittent satellite reception due to the shadowing effect of surrounding buildings. We study benefits and limits of the cooperative approach adopting a network model that is at the same time tractable and of practical interest.We derive an analytical lower boun...

  19. Modeling and Simulation Network Data Standards

    Science.gov (United States)

    2011-09-30

    12.1 Open Shortest Path First ( OSPF ) Protocol commonly used to find the shortest path between two nodes. User defined. 12.2 Border Gateway Protocol...Element Definition 12.7 Request for Comments – 1256 (RFC-1256) Router discovery protocol. 13.0 OSPF Sub-elements define OSPF parameters 13.1...resolution network analysis simulation tool OSPF open shortest path first OV operational view PEO-I Program Executive Office - Information

  20. Resilience Simulation for Water, Power & Road Networks

    Science.gov (United States)

    Clark, S. S.; Seager, T. P.; Chester, M.; Eisenberg, D. A.; Sweet, D.; Linkov, I.

    2014-12-01

    The increasing frequency, scale, and damages associated with recent catastrophic events has called for a shift in focus from evading losses through risk analysis to improving threat preparation, planning, absorption, recovery, and adaptation through resilience. However, neither underlying theory nor analytic tools have kept pace with resilience rhetoric. As a consequence, current approaches to engineering resilience analysis often conflate resilience and robustness or collapse into a deeper commitment to the risk analytic paradigm proven problematic in the first place. This research seeks a generalizable understanding of resilience that is applicable in multiple disciplinary contexts. We adopt a unique investigative perspective by coupling social and technical analysis with human subjects research to discover the adaptive actions, ideas and decisions that contribute to resilience in three socio-technical infrastructure systems: electric power, water, and roadways. Our research integrates physical models representing network objects with examination of the knowledge systems and social interactions revealed by human subjects making decisions in a simulated crisis environment. To ensure a diversity of contexts, we model electric power, water, roadway and knowledge networks for Phoenix AZ and Indianapolis IN. We synthesize this in a new computer-based Resilient Infrastructure Simulation Environment (RISE) to allow individuals, groups (including students) and experts to test different network design configurations and crisis response approaches. By observing simulated failures and best performances, we expect a generalizable understanding of resilience may emerge that yields a measureable understanding of the sensing, anticipating, adapting, and learning processes that are essential to resilient organizations.

  1. Simulation of developing human neuronal cell networks.

    Science.gov (United States)

    Lenk, Kerstin; Priwitzer, Barbara; Ylä-Outinen, Laura; Tietz, Lukas H B; Narkilahti, Susanna; Hyttinen, Jari A K

    2016-08-30

    Microelectrode array (MEA) is a widely used technique to study for example the functional properties of neuronal networks derived from human embryonic stem cells (hESC-NN). With hESC-NN, we can investigate the earliest developmental stages of neuronal network formation in the human brain. In this paper, we propose an in silico model of maturating hESC-NNs based on a phenomenological model called INEX. We focus on simulations of the development of bursts in hESC-NNs, which are the main feature of neuronal activation patterns. The model was developed with data from developing hESC-NN recordings on MEAs which showed increase in the neuronal activity during the investigated six measurement time points in the experimental and simulated data. Our simulations suggest that the maturation process of hESC-NN, resulting in the formation of bursts, can be explained by the development of synapses. Moreover, spike and burst rate both decreased at the last measurement time point suggesting a pruning of synapses as the weak ones are removed. To conclude, our model reflects the assumption that the interaction between excitatory and inhibitory neurons during the maturation of a neuronal network and the spontaneous emergence of bursts are due to increased connectivity caused by the forming of new synapses.

  2. On the Coverage Extension and Capacity Enhancement of Inband Relay Deployments in LTE-Advanced Networks

    Directory of Open Access Journals (Sweden)

    Abdallah Bou Saleh

    2010-01-01

    Full Text Available Decode-and-forward relaying is a promising enhancement to existing radio access networks and is currently being standardized in 3GPP to be part of the LTE-Advanced release 10. Two inband operation modes of relay nodes are to be supported, namely Type 1 and Type 1b. Relay nodes promise to offer considerable gain for system capacity or coverage depending on the deployment prioritization. However, the performance of relays, as any other radio access point, significantly depends on the propagation characteristics of the deployment environment. Hence, in this paper, we investigate the performance of Type 1 and Type 1b inband relaying within the LTE-Advanced framework in different propagation scenarios in terms of both coverage extension capabilities and capacity enhancements. A comparison between Type 1 and Type 1b relay nodes is as well presented to study the effect of the relaying overhead on the system performance in inband relay node deployments. System level simulations show that Type 1 and Type 1b inband relay deployments offer low to very high gains depending on the deployment environment. As well, it is shown that the effect of the relaying overhead is minimal on coverage extension whereas it is more evident on system throughput.

  3. New Power Quality Analysis Method Based on Chaos Synchronization and Extension Neural Network

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2014-10-01

    Full Text Available A hybrid method comprising a chaos synchronization (CS-based detection scheme and an Extension Neural Network (ENN classification algorithm is proposed for power quality monitoring and analysis. The new method can detect minor changes in signals of the power systems. Likewise, prominent characteristics of system signal disturbance can be extracted by this technique. In the proposed approach, the CS-based detection method is used to extract three fundamental characteristics of the power system signal and an ENN-based clustering scheme is then applied to detect the state of the signal, i.e., normal, voltage sag, voltage swell, interruption or harmonics. The validity of the proposed method is demonstrated by means of simulations given the use of three different chaotic systems, namely Lorenz, New Lorenz and Sprott. The simulation results show that the proposed method achieves a high detection accuracy irrespective of the chaotic system used or the presence of noise. The proposed method not only achieves higher detection accuracy than existing methods, but also has low computational cost, an improved robustness toward noise, and improved scalability. As a result, it provides an ideal solution for the future development of hand-held power quality analyzers and real-time detection devices.

  4. Spiking network simulation code for petascale computers

    Science.gov (United States)

    Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M.; Plesser, Hans E.; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

    2014-01-01

    Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today. PMID:25346682

  5. Spiking network simulation code for petascale computers.

    Science.gov (United States)

    Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M; Plesser, Hans E; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

    2014-01-01

    Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today.

  6. THE MEANING EXTENSION OF XIANG AND ITS POLYSEMY NETWORK

    Directory of Open Access Journals (Sweden)

    Mei-hsiu Chen

    2010-12-01

    Full Text Available Based on the idea that cognitive processes play an important role in linguistic analysis, this paper focuses on two main issues. The first issue is concerned with the nature of the intertwined relations of the various meanings of the Chinese polysemous word xiang and how these different meanings are extended from the original meaning found in ancient Chinese texts. The relations between these meanings can be accounted for in terms of five cognitive processes: generalization, extendability across motive states, profile, metaphor, and change in the position of the perspective point, all of which constitute links within the semantic network of xiang. The second issue is concerned with why xiang has two opposite meanings, i.e., goal marker and source marker. It is proposed that the two opposite meanings result from a change in the position of the perspective point in a given schema. That is, by changing the perspective point from that of the starting point of the movement of the Figure to the endpoint of the movement, the Figure, which moves from the starting point to the endpoint, is changed from being seen as leaving the observer to being seen as getting closer to the observer.

  7. C Library for Simulated Evolution of Biological Networks

    OpenAIRE

    Chandran, Deepak; Sauro, Herbert M.

    2010-01-01

    Simulated evolution of biological networks can be used to generate functional networks as well as investigate hypotheses regarding natural evolution. A handful of studies have shown how simulated evolution can be used for studying the functional space spanned by biochemical networks, studying natural evolution, or designing new synthetic networks. If there was a method for easily performing such studies, it can allow the community to further experiment with simulated evolution and explore all...

  8. Motorway Network Simulation Using Bluetooth Data

    Directory of Open Access Journals (Sweden)

    Karakikes Ioannis

    2016-09-01

    Full Text Available This paper describes a systematic calibration process of a Vissim model, based on data derived from BT detectors. It also provides instructions how to calibrate and validate a highway network model based upon a case study and establishes an example for practitioners that are interested in designing highway networks with micro simulation tools. Within this case study, a 94,5 % proper calibration to all segments was achieved First, an overview of the systematic calibration approach that will be followed is presented. A description of the given datasets follows. Finally, model’s systematic calibration and validation based on BT data from segments under free flow conditions is thoroughly explained. The delivered calibrated Vissim model acts as a test bed, which in combination with other analysis tools can be used for potential future exploitation regarding transportation related purposes.

  9. Learning in innovation networks: Some simulation experiments

    Science.gov (United States)

    Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas

    2007-05-01

    According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.

  10. Mobile-ip Aeronautical Network Simulation Study

    Science.gov (United States)

    Ivancic, William D.; Tran, Diepchi T.

    2001-01-01

    NASA is interested in applying mobile Internet protocol (mobile-ip) technologies to its space and aeronautics programs. In particular, mobile-ip will play a major role in the Advanced Aeronautic Transportation Technology (AATT), the Weather Information Communication (WINCOMM), and the Small Aircraft Transportation System (SATS) aeronautics programs. This report presents the results of a simulation study of mobile-ip for an aeronautical network. The study was performed to determine the performance of the transmission control protocol (TCP) in a mobile-ip environment and to gain an understanding of how long delays, handoffs, and noisy channels affect mobile-ip performance.

  11. Artificial neural network simulator for SOFC performance prediction

    Science.gov (United States)

    Arriagada, Jaime; Olausson, Pernilla; Selimovic, Azra

    This paper describes the development of a novel modelling tool for evaluation of solid oxide fuel cell (SOFC) performance. An artificial neural network (ANN) is trained with a reduced amount of data generated by a validated cell model, and it is then capable of learning the generic functional relationship between inputs and outputs of the system. Once the network is trained, the ANN-driven simulator can predict different operational parameters of the SOFC (i.e. gas flows, operational voltages, current density, etc.) avoiding the detailed description of the fuel cell processes. The highly parallel connectivity within the ANN further reduces the computational time. In a real case, the necessary data for training the ANN simulator would be extracted from experiments. This simulator could be suitable for different applications in the fuel cell field, such as, the construction of performance maps and operating point optimisation and analysis. All this is performed with minimum time demand and good accuracy. This intelligent model together with the operational conditions may provide useful insight into SOFC operating characteristics and improved means of selecting operating conditions, reducing costs and the need for extensive experiments.

  12. Statistical analysis of CSP plants by simulating extensive meteorological series

    Science.gov (United States)

    Pavón, Manuel; Fernández, Carlos M.; Silva, Manuel; Moreno, Sara; Guisado, María V.; Bernardos, Ana

    2017-06-01

    The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.

  13. Double and multiple knockout simulations for genome-scale metabolic network reconstructions.

    Science.gov (United States)

    Goldstein, Yaron Ab; Bockmayr, Alexander

    2015-01-01

    Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results. A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC.

  14. Universality and Realistic Extensions to the Semi-Analytic Simulation Principle in GNSS Signal Processing

    OpenAIRE

    O. Jakubov; P. Kacmarik; kovar, P.; F. Vejrazka

    2012-01-01

    Semi-analytic simulation principle in GNSS signal processing bypasses the bit-true operations at high sampling frequency. Instead, signals at the output branches of the integrate&dump blocks are successfully modeled, thus making extensive Monte Carlo simulations feasible. Methods for simulations of code and carrier tracking loops with BPSK, BOC signals have been introduced in the literature. Matlab toolboxes were designed and published. In this paper, we further extend the applicability o...

  15. The design of a network emulation and simulation laboratory

    CSIR Research Space (South Africa)

    Von Solms, S

    2015-07-01

    Full Text Available The development of the Network Emulation and Simulation Laboratory is motivated by the drive to contribute to the enhancement of the security and resilience of South Africa's critical information infrastructure. The goal of the Network Emulation...

  16. Double and multiple knockout simulations for genome-scale metabolic network reconstructions

    OpenAIRE

    Goldstein, Yaron AB; Bockmayr, Alexander

    2015-01-01

    Background Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. Results We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perfor...

  17. The design and implementation of a network simulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2013-11-01

    Full Text Available of the NS. A discussion on the various aspects of the NS is discussed subsequently. A. Topology It can be seen from Figure 1 that the developed NS comprises of multiple network sections, namely Internal User Networks/Local Area Networks (LANs) connected...]. This will provide a realistic platform which is isolated, more controlled and more predictable than implementation across live networks [4]. In this paper we discuss the development of such a network simulation environment, called a network simulator (NS...

  18. Characterization of Background Traffic in Hybrid Network Simulation

    National Research Council Canada - National Science Library

    Lauwens, Ben; Scheers, Bart; Van de Capelle, Antoine

    2006-01-01

    .... Two approaches are common: discrete event simulation and fluid approximation. A discrete event simulation generates a huge amount of events for a full-blown battlefield communication network resulting in a very long runtime...

  19. A contractile actomyosin network linked to adherens junctions by Canoe/afadin helps drive convergent extension

    Science.gov (United States)

    Sawyer, Jessica K.; Choi, Wangsun; Jung, Kuo-Chen; He, Li; Harris, Nathan J.; Peifer, Mark

    2011-01-01

    Integrating individual cell movements to create tissue-level shape change is essential to building an animal. We explored mechanisms of adherens junction (AJ):cytoskeleton linkage and roles of the linkage regulator Canoe/afadin during Drosophila germband extension (GBE), a convergent-extension process elongating the body axis. We found surprising parallels between GBE and a quite different morphogenetic movement, mesoderm apical constriction. Germband cells have an apical actomyosin network undergoing cyclical contractions. These coincide with a novel cell shape change—cell extension along the anterior–posterior (AP) axis. In Canoe's absence, GBE is disrupted. The apical actomyosin network detaches from AJs at AP cell borders, reducing coordination of actomyosin contractility and cell shape change. Normal GBE requires planar polarization of AJs and the cytoskeleton. Canoe loss subtly enhances AJ planar polarity and dramatically increases planar polarity of the apical polarity proteins Bazooka/Par3 and atypical protein kinase C. Changes in Bazooka localization parallel retraction of the actomyosin network. Globally reducing AJ function does not mimic Canoe loss, but many effects are replicated by global actin disruption. Strong dose-sensitive genetic interactions between canoe and bazooka are consistent with them affecting a common process. We propose a model in which an actomyosin network linked at AP AJs by Canoe and coupled to apical polarity proteins regulates convergent extension. PMID:21613546

  20. GMPLS control plane extensions in support of flex-grid enabled elastic optical networks

    DEFF Research Database (Denmark)

    Turus, Ioan; Fagertun, Anna Manolova; Dittmann, Lars

    2013-01-01

    of generalized labels format and enable enhancements for the wavelength selection procedures. OSPF-TE enables the creation of spectrum databases based on novel LSA sub-TLV attributes capable of advertising spectrum status. Based on the implemented extensions, we propose and evaluate advanced distributed spectrum...... allocation schemes and strategies for dynamic routing algorithms in support of flex-grid optical networks....

  1. Creating real network with expected degree distribution: A statistical simulation

    OpenAIRE

    WenJun Zhang; GuangHua Liu

    2012-01-01

    The degree distribution of known networks is one of the focuses in network analysis. However, its inverse problem, i.e., to create network from known degree distribution has not yet been reported. In present study, a statistical simulation algorithm was developed to create real network with expected degree distribution. It is aniteration procedure in which a real network, with the least deviation of actual degree distribution to expected degree distribution, was created. Random assignment was...

  2. A simulation study of TaMAC protocol using network simulator 2.

    Science.gov (United States)

    Ullah, Sana; Kwak, Kyung Sup

    2012-10-01

    A Wireless Body Area Network (WBAN) is expected to play a significant role in future healthcare system. It interconnects low-cost and intelligent sensor nodes in, on, or around a human body to serve a variety of medical applications. It can be used to diagnose and treat patients with chronic diseases such as hypertensions, diabetes, and cardiovascular diseases. The lightweight sensor nodes integrated in WBAN require low-power operation, which can be achieved using different optimization techniques. We introduce a Traffic-adaptive MAC protocol (TaMAC) for WBAN that supports dual wakeup mechanisms for normal, emergency, and on-demand traffic. In this letter, the TaMAC protocol is simulated using a well-known Network Simulator 2 (NS-2). The problem of multiple emergency nodes is solved using both wakeup radio and CSMA/CA protocol. The power consumption, delay, and throughput performance are closely compared with beacon-enabled IEEE 802.15.4 MAC protocol using extensive simulations.

  3. Information diversity in structure and dynamics of simulated neuronal networks.

    Science.gov (United States)

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Nykter, Matti; Kesseli, Juha; Ruohonen, Keijo; Yli-Harja, Olli; Linne, Marja-Leena

    2011-01-01

    Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviors are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses. We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.

  4. Information Diversity in Structure and Dynamics of Simulated Neuronal Networks

    Directory of Open Access Journals (Sweden)

    Tuomo eMäki-Marttunen

    2011-06-01

    Full Text Available Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance (NCD. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviours are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses.We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.

  5. Simulation Of Networking Protocols On Software Emulated Network Stack

    Directory of Open Access Journals (Sweden)

    Hrushikesh Nimkar

    2015-08-01

    Full Text Available With the increasing number and complexity of network based applications the need to easy configuration development and integration of network applications has taken a high precedence. Trivial activities such as configuration can be carried out efficiently if network services are software based rather than hardware based. Project aims at enabling the network engineers to easily include network functionalities into hisher configuration and define hisher own network stack without using the kernel network stack. Having thought of this we have implemented two functionalities UPNP and MDNS. The multicast Domain Name System MDNS resolves host names to IP addresses within small ad-hoc networks and without having need of special DNS server and its configuration. MDNS application provides every host with functionality to register itself to the router make a multicast DNS request and its resolution. To make adding network devices and networked programs to a network as easy as it is to plug in a piece of hardware into a PC we make use of UPnP. The devices and programs find out about the network setup and other networked devices and programs through discovery and advertisements of services and configure themselves accordingly. UPNP application provides every host with functionality of discovering services of other hosts and serving requests on demand. To implement these applications we have used snabbswitch framework which an open source virtualized ethernet networking stack.

  6. The Virtual Research and Extension Communication Network (VRECN): An Interactive Learning and Communication Network for Research and Extension Personnel. Concept Paper for the Food & Agriculture Organisation of the United Nations (FAO).

    Science.gov (United States)

    Richardson, Don

    A Virtual Research and Extension Communication Network (VRECN) is a set of networked electronic tools facilitating improvement in communication processes and information sharing among stakeholders involved in agricultural development. In developing countries, research and extension personnel within a ministry of agriculture, in consultation and…

  7. Simulation and Evaluation of Ethernet Passive Optical Network

    Directory of Open Access Journals (Sweden)

    Salah A. Jaro Alabady

    2013-05-01

    Full Text Available      This paper studies simulation and evaluation of Ethernet Passive Optical Network (EPON system, IEEE802.3ah based OPTISM 3.6 simulation program. The simulation program is used in this paper to build a typical ethernet passive optical network, and to evaluate the network performance when using the (1580, 1625 nm wavelength instead of (1310, 1490 nm that used in Optical Line Terminal (OLT and Optical Network Units (ONU's in system architecture of Ethernet passive optical network at different bit rate and different fiber optic length. The results showed enhancement in network performance by increase the number of nodes (subscribers connected to the network, increase the transmission distance, reduces the received power and reduces the Bit Error Rate (BER.   

  8. Understanding Farmers Information Network Implication For Effective Extension Delivery In Akwa Ibom State

    Directory of Open Access Journals (Sweden)

    Odoemelam

    2015-01-01

    Full Text Available ABSTRACT Appropriateness of information is a critical factor needed to stimulate the right knowledge and attitude of farmers towards sustainable transformation of agriculture. The study investigated the information network that exists among rural communities in Akwa-Ibom States and its implication for effective extension delivery. Even though AKADEPAkwa-Ibom State Agricultural Development Programmes are highly involved in the dissemination process it is important to analyze the information networks of the farmers to improve exchange of information with the following specific objectives identify the different wealth groups in the study area ascertain the information networks that exists in the area analyze the different information types and assess the strength and weakness of the information sources. Data were generated through Focus Group Discussion and Participatory Observation employing different methodologies like wealth ranking information diagram and linkage matrix analysis using Likerts scale type. Data generated were analyzed with simple descriptive statistics and means. Major results show that in wealth ranking two groups of respondents were identified the female households with mean score between 1.9 and male headed household with mean score of 2.00 2.99. on information network farmer to farmer with 21 market 14 church 15 were highest source of their information network. On perceived weakness and strength of the information network the information quality frequency of use timeliness of information flow and link up of information were adequate while reliability of information was not adequate. The results show that intra community information flow was suitable and accessible to rich farmers while inaccessible and often irrelevant to poor farmers. Therefore in the face of threat to food insecurity prevalent in the country it is important to put in place a platform that will afford farmers to ask questions and get substantive responses

  9. Extension of the IsaViz software for the representation of metabolic and regulatory networks

    OpenAIRE

    Diogo Fernando Veiga; Pedro de Stege Cecconello; José Eduardo De Lucca; Luismar Marques Porto

    2005-01-01

    In this work we developed an extension of IsaViz software, a RDF (Resource Description Framework) authoring tool, designed to be a graphical environment to build models of metabolic and regulatory networks. This environment, called Metabolic IsaViz, was linked to a genomic library of types and was modeled on the basis of ontologies. Biochemical pathways included data at sequence level (e.g., the amino acid sequence of enzymes), besides kinetic and thermodynamic parameters for the reactions. M...

  10. Graphical user interface for wireless sensor networks simulator

    Science.gov (United States)

    Paczesny, Tomasz; Paczesny, Daniel; Weremczuk, Jerzy

    2008-01-01

    Wireless Sensor Networks (WSN) are currently very popular area of development. It can be suited in many applications form military through environment monitoring, healthcare, home automation and others. Those networks, when working in dynamic, ad-hoc model, need effective protocols which must differ from common computer networks algorithms. Research on those protocols would be difficult without simulation tool, because real applications often use many nodes and tests on such a big networks take much effort and costs. The paper presents Graphical User Interface (GUI) for simulator which is dedicated for WSN studies, especially in routing and data link protocols evaluation.

  11. A Flexible System for Simulating Aeronautical Telecommunication Network

    Science.gov (United States)

    Maly, Kurt; Overstreet, C. M.; Andey, R.

    1998-01-01

    At Old Dominion University, we have built Aeronautical Telecommunication Network (ATN) Simulator with NASA being the fund provider. It provides a means to evaluate the impact of modified router scheduling algorithms on the network efficiency, to perform capacity studies on various network topologies and to monitor and study various aspects of ATN through graphical user interface (GUI). In this paper we describe briefly about the proposed ATN model and our abstraction of this model. Later we describe our simulator architecture highlighting some of the design specifications, scheduling algorithms and user interface. At the end, we have provided the results of performance studies on this simulator.

  12. Parallel discrete-event simulation of FCFS stochastic queueing networks

    Science.gov (United States)

    Nicol, David M.

    1988-01-01

    Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

  13. A neural network simulation package in CLIPS

    Science.gov (United States)

    Bhatnagar, Himanshu; Krolak, Patrick D.; Mcgee, Brenda J.; Coleman, John

    1990-01-01

    The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems.

  14. The Virtual Brain: a simulator of primate brain network dynamics.

    Science.gov (United States)

    Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

    2013-01-01

    We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

  15. Coverage extension and balancing the transmitted power of the moving relay node at LTE-A cellular network.

    Science.gov (United States)

    Aldhaibani, Jaafar A; Yahya, Abid; Ahmad, R Badlishah

    2014-01-01

    The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain.

  16. Toward Designing a Quantum Key Distribution Network Simulation Model

    Directory of Open Access Journals (Sweden)

    Miralem Mehic

    2016-01-01

    Full Text Available As research in quantum key distribution network technologies grows larger and more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. In this paper, we described the design of simplified simulation environment of the quantum key distribution network with multiple links and nodes. In such simulation environment, we analyzed several routing protocols in terms of the number of sent routing packets, goodput and Packet Delivery Ratio of data traffic flow using NS-3 simulator.

  17. Interfacing Network Simulations and Empirical Data

    Science.gov (United States)

    2009-05-01

    appropriate. The quadratic assignment procedure ( QAP ) (Krackhardt, 1987) could be used to compare the correlation between networks; however, the...Social roles and the evolution of networks in extreme and isolated environments. Mathematical Sociology, 27: 89-121. Krackhardt, D. (1987). QAP

  18. A Network Contention Model for the Extreme-scale Simulator

    Energy Technology Data Exchange (ETDEWEB)

    Engelmann, Christian [ORNL; Naughton III, Thomas J [ORNL

    2015-01-01

    The Extreme-scale Simulator (xSim) is a performance investigation toolkit for high-performance computing (HPC) hardware/software co-design. It permits running a HPC application with millions of concurrent execution threads, while observing its performance in a simulated extreme-scale system. This paper details a newly developed network modeling feature for xSim, eliminating the shortcomings of the existing network modeling capabilities. The approach takes a different path for implementing network contention and bandwidth capacity modeling using a less synchronous and accurate enough model design. With the new network modeling feature, xSim is able to simulate on-chip and on-node networks with reasonable accuracy and overheads.

  19. A GIS Tool for simulating Nitrogen transport along schematic Network

    Science.gov (United States)

    Tavakoly, A. A.; Maidment, D. R.; Yang, Z.; Whiteaker, T.; David, C. H.; Johnson, S.

    2012-12-01

    An automated method called the Arc Hydro Schematic Processor has been developed for water process computation on schematic networks formed from the NHDPlus and similar GIS river networks. The sechemtaic network represents the hydrologic feature on the ground and is a network of links and nodes. SchemaNodes show hydrologic features, such as catchments or stream junctions. SchemaLinks prescripe the connections between nodes. The schematic processor uses the schematic network to pass informatin through a watershed and move water or pollutants dwonstream. In addition, the schematic processor has a capability to use additional programming applied to the passed and/or received values and manipulating data trough network. This paper describes how the schemtic processor can be used to simulate nitrogen transport and transformation on river networks. For this purpose the nitrogen loads is estimated on the NHDPlus river network using the Schematic Processor coupled with the river routing model for the Texas Gulf Coast Hydrologic Region.

  20. WDM Systems and Networks Modeling, Simulation, Design and Engineering

    CERN Document Server

    Ellinas, Georgios; Roudas, Ioannis

    2012-01-01

    WDM Systems and Networks: Modeling, Simulation, Design and Engineering provides readers with the basic skills, concepts, and design techniques used to begin design and engineering of optical communication systems and networks at various layers. The latest semi-analytical system simulation techniques are applied to optical WDM systems and networks, and a review of the various current areas of optical communications is presented. Simulation is mixed with experimental verification and engineering to present the industry as well as state-of-the-art research. This contributed volume is divided into three parts, accommodating different readers interested in various types of networks and applications. The first part of the book presents modeling approaches and simulation tools mainly for the physical layer including transmission effects, devices, subsystems, and systems), whereas the second part features more engineering/design issues for various types of optical systems including ULH, access, and in-building system...

  1. Extension of the IsaViz software for the representation of metabolic and regulatory networks

    Directory of Open Access Journals (Sweden)

    Diogo Fernando Veiga

    2005-06-01

    Full Text Available In this work we developed an extension of IsaViz software, a RDF (Resource Description Framework authoring tool, designed to be a graphical environment to build models of metabolic and regulatory networks. This environment, called Metabolic IsaViz, was linked to a genomic library of types and was modeled on the basis of ontologies. Biochemical pathways included data at sequence level (e.g., the amino acid sequence of enzymes, besides kinetic and thermodynamic parameters for the reactions. Models created with Metabolic IsaViz could be exported to pathways simulators through SBML (Systems Biology Markup Language, which allowed to analyze the pathway dynamics of target chemicals.A determinação de vias metabólicas e regulatórias de microrganismos é essencial para estudos pós-sequenciamento de DNA, com aplicações diretas em várias áreas da biotecnologia, em especial em engenharia metabólica. Neste trabalho desenvolvemos uma extensão do software IsaViz, editor de grafos RDF (Resource Description Framework, com a finalidade de criar um ambiente gráfico para a construção de modelos de vias metabólicas e regulatórias. Este ambiente, o Metabolic IsaViz, foi integrado a uma biblioteca de tipos genômicos, modelada com base em ontologias, sendo que as vias bioquímicas podem incluir dados ao nível de seqüência (como a seqüência de aminoácidos das enzimas, além de parâmetros cinéticos e termodinâmicos. Os modelos criados com o Metabolic IsaViz podem ser exportados para simuladores de vias metabólicas através da linguagem SBML (Systems Biology Markup Language para análise da formação de metabólitos de interesse.

  2. Simulated evolution of signal transduction networks.

    Directory of Open Access Journals (Sweden)

    Mohammad Mobashir

    Full Text Available Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.

  3. Modified network simulation model with token method of bus access

    Directory of Open Access Journals (Sweden)

    L.V. Stribulevich

    2013-08-01

    Full Text Available Purpose. To study the characteristics of the local network with the marker method of access to the bus its modified simulation model was developed. Methodology. Defining characteristics of the network is carried out on the developed simulation model, which is based on the state diagram-layer network station with the mechanism of processing priorities, both in steady state and in the performance of control procedures: the initiation of a logical ring, the entrance and exit of the station network with a logical ring. Findings. A simulation model, on the basis of which can be obtained the dependencies of the application the maximum waiting time in the queue for different classes of access, and the reaction time usable bandwidth on the data rate, the number of network stations, the generation rate applications, the number of frames transmitted per token holding time, frame length was developed. Originality. The technique of network simulation reflecting its work in the steady condition and during the control procedures, the mechanism of priority ranking and handling was proposed. Practical value. Defining network characteristics in the real-time systems on railway transport based on the developed simulation model.

  4. Neural networks analysis on SSME vibration simulation data

    Science.gov (United States)

    Lo, Ching F.; Wu, Kewei

    1993-01-01

    The neural networks method is applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME to supplement the statistical method utilized in the prototype system. The investigation of neural networks analysis is conducted using SSME vibration data from a NASA developed numerical simulator. The limited application of neural networks to the HPFTP has also shown the effectiveness in diagnosing the anomalies of turbopump vibrations.

  5. EVALUATING AUSTRALIAN FOOTBALL LEAGUE PLAYER CONTRIBUTIONS USING INTERACTIVE NETWORK SIMULATION

    Directory of Open Access Journals (Sweden)

    Jonathan Sargent

    2013-03-01

    Full Text Available This paper focuses on the contribution of Australian Football League (AFL players to their team's on-field network by simulating player interactions within a chosen team list and estimating the net effect on final score margin. A Visual Basic computer program was written, firstly, to isolate the effective interactions between players from a particular team in all 2011 season matches and, secondly, to generate a symmetric interaction matrix for each match. Negative binomial distributions were fitted to each player pairing in the Geelong Football Club for the 2011 season, enabling an interactive match simulation model given the 22 chosen players. Dynamic player ratings were calculated from the simulated network using eigenvector centrality, a method that recognises and rewards interactions with more prominent players in the team network. The centrality ratings were recorded after every network simulation and then applied in final score margin predictions so that each player's match contribution-and, hence, an optimal team-could be estimated. The paper ultimately demonstrates that the presence of highly rated players, such as Geelong's Jimmy Bartel, provides the most utility within a simulated team network. It is anticipated that these findings will facilitate optimal AFL team selection and player substitutions, which are key areas of interest to coaches. Network simulations are also attractive for use within betting markets, specifically to provide information on the likelihood of a chosen AFL team list "covering the line".

  6. Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

    Science.gov (United States)

    DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.

    2017-01-01

    Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.

  7. Designing laboratory wind simulations using artificial neural networks

    Science.gov (United States)

    Križan, Josip; Gašparac, Goran; Kozmar, Hrvoje; Antonić, Oleg; Grisogono, Branko

    2015-05-01

    While experiments in boundary layer wind tunnels remain to be a major research tool in wind engineering and environmental aerodynamics, designing the modeling hardware required for a proper atmospheric boundary layer (ABL) simulation can be costly and time consuming. Hence, possibilities are sought to speed-up this process and make it more time-efficient. In this study, two artificial neural networks (ANNs) are developed to determine an optimal design of the Counihan hardware, i.e., castellated barrier wall, vortex generators, and surface roughness, in order to simulate the ABL flow developing above urban, suburban, and rural terrains, as previous ANN models were created for one terrain type only. A standard procedure is used in developing those two ANNs in order to further enhance best-practice possibilities rather than to improve existing ANN designing methodology. In total, experimental results obtained using 23 different hardware setups are used when creating ANNs. In those tests, basic barrier height, barrier castellation height, spacing density, and height of surface roughness elements are the parameters that were varied to create satisfactory ABL simulations. The first ANN was used for the estimation of mean wind velocity, turbulent Reynolds stress, turbulence intensity, and length scales, while the second one was used for the estimation of the power spectral density of velocity fluctuations. This extensive set of studied flow and turbulence parameters is unmatched in comparison to the previous relevant studies, as it includes here turbulence intensity and power spectral density of velocity fluctuations in all three directions, as well as the Reynolds stress profiles and turbulence length scales. Modeling results agree well with experiments for all terrain types, particularly in the lower ABL within the height range of the most engineering structures, while exhibiting sensitivity to abrupt changes and data scattering in profiles of wind-tunnel results. The

  8. Evaluating Australian football league player contributions using interactive network simulation.

    Science.gov (United States)

    Sargent, Jonathan; Bedford, Anthony

    2013-01-01

    This paper focuses on the contribution of Australian Football League (AFL) players to their team's on-field network by simulating player interactions within a chosen team list and estimating the net effect on final score margin. A Visual Basic computer program was written, firstly, to isolate the effective interactions between players from a particular team in all 2011 season matches and, secondly, to generate a symmetric interaction matrix for each match. Negative binomial distributions were fitted to each player pairing in the Geelong Football Club for the 2011 season, enabling an interactive match simulation model given the 22 chosen players. Dynamic player ratings were calculated from the simulated network using eigenvector centrality, a method that recognises and rewards interactions with more prominent players in the team network. The centrality ratings were recorded after every network simulation and then applied in final score margin predictions so that each player's match contribution-and, hence, an optimal team-could be estimated. The paper ultimately demonstrates that the presence of highly rated players, such as Geelong's Jimmy Bartel, provides the most utility within a simulated team network. It is anticipated that these findings will facilitate optimal AFL team selection and player substitutions, which are key areas of interest to coaches. Network simulations are also attractive for use within betting markets, specifically to provide information on the likelihood of a chosen AFL team list "covering the line ". Key pointsA simulated interaction matrix for Australian Rules football players is proposedThe simulations were carried out by fitting unique negative binomial distributions to each player pairing in a sideEigenvector centrality was calculated for each player in a simulated matrix, then for the teamThe team centrality measure adequately predicted the team's winning marginA player's net effect on margin could hence be estimated by replacing him in

  9. Slow update stochastic simulation algorithms for modeling complex biochemical networks.

    Science.gov (United States)

    Ghosh, Debraj; De, Rajat K

    2017-10-30

    The stochastic simulation algorithm (SSA) based modeling is a well recognized approach to predict the stochastic behavior of biological networks. The stochastic simulation of large complex biochemical networks is a challenge as it takes a large amount of time for simulation due to high update cost. In order to reduce the propensity update cost, we proposed two algorithms: slow update exact stochastic simulation algorithm (SUESSA) and slow update exact sorting stochastic simulation algorithm (SUESSSA). We applied cache-based linear search (CBLS) in these two algorithms for improving the search operation for finding reactions to be executed. Data structure used for incorporating CBLS is very simple and the cost of maintaining this during propensity update operation is very low. Hence, time taken during propensity updates, for simulating strongly coupled networks, is very fast; which leads to reduction of total simulation time. SUESSA and SUESSSA are not only restricted to elementary reactions, they support higher order reactions too. We used linear chain model and colloidal aggregation model to perform a comparative analysis of the performances of our methods with the existing algorithms. We also compared the performances of our methods with the existing ones, for large biochemical networks including B cell receptor and FcϵRI signaling networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. PyNN: A Common Interface for Neuronal Network Simulators

    Science.gov (United States)

    Davison, Andrew P.; Brüderle, Daniel; Eppler, Jochen; Kremkow, Jens; Muller, Eilif; Pecevski, Dejan; Perrinet, Laurent; Yger, Pierre

    2008-01-01

    Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN. PMID:19194529

  11. PyNN: a common interface for neuronal network simulators

    Directory of Open Access Journals (Sweden)

    Andrew P Davison

    2009-01-01

    Full Text Available Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware. PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization, and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN.

  12. Extension to HiRLoc Algorithm for Localization Error Computation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Swati Saxena

    2013-09-01

    Full Text Available Wireless sensor networks (WSNs have gained importance in recent years as this support a large spectrum of applications such as automotive, health, military, environmental, home and office. Various algorithms have been proposed for making this technology more adaptive the existing algorithms address issues such as safety, security, power consumption, lifetime and localization. This paper presents an extension to HiRLoc algorithm and highlights its benefits. Extended HiRLoc significantly reduce the average localization error by suggesting a new method directional antenna based scheme.

  13. Developed hydraulic simulation model for water pipeline networks

    Directory of Open Access Journals (Sweden)

    A. Ayad

    2013-03-01

    Full Text Available A numerical method that uses linear graph theory is presented for both steady state, and extended period simulation in a pipe network including its hydraulic components (pumps, valves, junctions, etc.. The developed model is based on the Extended Linear Graph Theory (ELGT technique. This technique is modified to include new network components such as flow control valves and tanks. The technique also expanded for extended period simulation (EPS. A newly modified method for the calculation of updated flows improving the convergence rate is being introduced. Both benchmarks, ad Actual networks are analyzed to check the reliability of the proposed method. The results reveal the finer performance of the proposed method.

  14. OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation.

    Science.gov (United States)

    Eastman, Peter; Friedrichs, Mark S; Chodera, John D; Radmer, Randall J; Bruns, Christopher M; Ku, Joy P; Beauchamp, Kyle A; Lane, Thomas J; Wang, Lee-Ping; Shukla, Diwakar; Tye, Tony; Houston, Mike; Stich, Timo; Klein, Christoph; Shirts, Michael R; Pande, Vijay S

    2013-01-08

    OpenMM is a software toolkit for performing molecular simulations on a range of high performance computing architectures. It is based on a layered architecture: the lower layers function as a reusable library that can be invoked by any application, while the upper layers form a complete environment for running molecular simulations. The library API hides all hardware-specific dependencies and optimizations from the users and developers of simulation programs: they can be run without modification on any hardware on which the API has been implemented. The current implementations of OpenMM include support for graphics processing units using the OpenCL and CUDA frameworks. In addition, OpenMM was designed to be extensible, so new hardware architectures can be accommodated and new functionality (e.g., energy terms and integrators) can be easily added.

  15. Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system.

    Science.gov (United States)

    Ma, Xiaofeng; Kohashi, Tsunehiko; Carlson, Bruce A

    2013-07-01

    Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

  16. Condition monitoring of oil-impregnated paper bushings using extension neural network, Gaussian mixture and hidden Markov models

    CSIR Research Space (South Africa)

    Miya, WS

    2008-10-01

    Full Text Available In this paper, a comparison between Extension Neural Network (ENN), Gaussian Mixture Model (GMM) and Hidden Markov model (HMM) is conducted for bushing condition monitoring. The monitoring process is a two-stage implementation of a classification...

  17. Extension of PENELOPE to protons: simulation of nuclear reactions and benchmark with Geant4.

    Science.gov (United States)

    Sterpin, E; Sorriaux, J; Vynckier, S

    2013-11-01

    Describing the implementation of nuclear reactions in the extension of the Monte Carlo code (MC) PENELOPE to protons (PENH) and benchmarking with Geant4. PENH is based on mixed-simulation mechanics for both elastic and inelastic electromagnetic collisions (EM). The adopted differential cross sections for EM elastic collisions are calculated using the eikonal approximation with the Dirac-Hartree-Fock-Slater atomic potential. Cross sections for EM inelastic collisions are computed within the relativistic Born approximation, using the Sternheimer-Liljequist model of the generalized oscillator strength. Nuclear elastic and inelastic collisions were simulated using explicitly the scattering analysis interactive dialin database for (1)H and ICRU 63 data for (12)C, (14)N, (16)O, (31)P, and (40)Ca. Secondary protons, alphas, and deuterons were all simulated as protons, with the energy adapted to ensure consistent range. Prompt gamma emission can also be simulated upon user request. Simulations were performed in a water phantom with nuclear interactions switched off or on and integral depth-dose distributions were compared. Binary-cascade and precompound models were used for Geant4. Initial energies of 100 and 250 MeV were considered. For cases with no nuclear interactions simulated, additional simulations in a water phantom with tight resolution (1 mm in all directions) were performed with FLUKA. Finally, integral depth-dose distributions for a 250 MeV energy were computed with Geant4 and PENH in a homogeneous phantom with, first, ICRU striated muscle and, second, ICRU compact bone. For simulations with EM collisions only, integral depth-dose distributions were within 1%/1 mm for doses higher than 10% of the Bragg-peak dose. For central-axis depth-dose and lateral profiles in a phantom with tight resolution, there are significant deviations between Geant4 and PENH (up to 60%/1 cm for depth-dose distributions). The agreement is much better with FLUKA, with deviations within

  18. Importance of simulation tools for the planning of optical network

    Science.gov (United States)

    Martins, Indayara B.; Martins, Yara; Rudge, Felipe; Moschimı, Edson

    2015-10-01

    The main proposal of this work is to show the importance of using simulation tools to project optical networks. The simulation method supports the investigation of several system and network parameters, such as bit error rate, blocking probability as well as physical layer issues, such as attenuation, dispersion, and nonlinearities, as these are all important to evaluate and validate the operability of optical networks. The work was divided into two parts: firstly, physical layer preplanning was proposed for the distribution of amplifiers and compensating for the attenuation and dispersion effects in span transmission; in this part, we also analyzed the quality of the transmitted signal. In the second part, an analysis of the transport layer was completed, proposing wavelength distribution planning, according to the total utilization of each link. The main network parameters used to evaluate the transport and physical layer design were delay (latency), blocking probability, and bit error rate (BER). This work was carried out with commercially available simulation tools.

  19. Simulating Social Networks of Online Communities: Simulation as a Method for Sociability Design

    Science.gov (United States)

    Ang, Chee Siang; Zaphiris, Panayiotis

    We propose the use of social simulations to study and support the design of online communities. In this paper, we developed an Agent-Based Model (ABM) to simulate and study the formation of social networks in a Massively Multiplayer Online Role Playing Game (MMORPG) guild community. We first analyzed the activities and the social network (who-interacts-with-whom) of an existing guild community to identify its interaction patterns and characteristics. Then, based on the empirical results, we derived and formalized the interaction rules, which were implemented in our simulation. Using the simulation, we reproduced the observed social network of the guild community as a means of validation. The simulation was then used to examine how various parameters of the community (e.g. the level of activity, the number of neighbors of each agent, etc) could potentially influence the characteristic of the social networks.

  20. Meeting the memory challenges of brain-scale network simulation

    Directory of Open Access Journals (Sweden)

    Susanne eKunkel

    2012-01-01

    Full Text Available The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10^5 neurons with up to 10^9 synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are one or two orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been studied in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Bluegene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of a neuronal simulator as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place.

  1. Computational Aspects of Sensor Network Protocols (Distributed Sensor Network Simulator

    Directory of Open Access Journals (Sweden)

    Vasanth Iyer

    2009-08-01

    Full Text Available In this work, we model the sensor networks as an unsupervised learning and clustering process. We classify nodes according to its static distribution to form known class densities (CCPD. These densities are chosen from specific cross-layer features which maximizes lifetime of power-aware routing algorithms. To circumvent computational complexities of a power-ware communication STACK we introduce path-loss models at the nodes only for high density deployments. We study the cluster heads and formulate the data handling capacity for an expected deployment and use localized probability models to fuse the data with its side information before transmission. So each cluster head has a unique Pmax but not all cluster heads have the same measured value. In a lossless mode if there are no faults in the sensor network then we can show that the highest probability given by Pmax is ambiguous if its frequency is ≤ n/2 otherwise it can be determined by a local function. We further show that the event detection at the cluster heads can be modelled with a pattern 2m and m, the number of bits can be a correlated pattern of 2 bits and for a tight lower bound we use 3-bit Huffman codes which have entropy < 1. These local algorithms are further studied to optimize on power, fault detection and to maximize on the distributed routing algorithm used at the higher layers. From these bounds in large network, it is observed that the power dissipation is network size invariant. The performance of the routing algorithms solely based on success of finding healthy nodes in a large distribution. It is also observed that if the network size is kept constant and the density of the nodes is kept closer then the local pathloss model effects the performance of the routing algorithms. We also obtain the maximum intensity of transmitting nodes for a given category of routing algorithms for an outage constraint, i.e., the lifetime of sensor network.

  2. Power Aware Simulation Framework for Wireless Sensor Networks and Nodes

    Directory of Open Access Journals (Sweden)

    Daniel Weber

    2008-07-01

    Full Text Available The constrained resources of sensor nodes limit analytical techniques and cost-time factors limit test beds to study wireless sensor networks (WSNs. Consequently, simulation becomes an essential tool to evaluate such systems.We present the power aware wireless sensors (PAWiS simulation framework that supports design and simulation of wireless sensor networks and nodes. The framework emphasizes power consumption capturing and hence the identification of inefficiencies in various hardware and software modules of the systems. These modules include all layers of the communication system, the targeted class of application itself, the power supply and energy management, the central processing unit (CPU, and the sensor-actuator interface. The modular design makes it possible to simulate heterogeneous systems. PAWiS is an OMNeT++ based discrete event simulator written in C++. It captures the node internals (modules as well as the node surroundings (network, environment and provides specific features critical to WSNs like capturing power consumption at various levels of granularity, support for mobility, and environmental dynamics as well as the simulation of timing effects. A module library with standardized interfaces and a power analysis tool have been developed to support the design and analysis of simulation models. The performance of the PAWiS simulator is comparable with other simulation environments.

  3. Simulating public private networks as evolving systems

    NARCIS (Netherlands)

    Deljoo, A.; Janssen, M.F.W.H.A.; Klievink, A.J.

    2013-01-01

    Public-private service networks (PPSN) consist of social and technology components. Development of PPSN is ill-understood as these are dependent on a complex mix of interactions among stakeholders and their technologies and is influenced by contemporary developments. The aim of this paper is to

  4. Adaptive Importance Sampling Simulation of Queueing Networks

    NARCIS (Netherlands)

    de Boer, Pieter-Tjerk; Nicola, V.F.; Rubinstein, N.; Rubinstein, Reuven Y.

    2000-01-01

    In this paper, a method is presented for the efficient estimation of rare-event (overflow) probabilities in Jackson queueing networks using importance sampling. The method differs in two ways from methods discussed in most earlier literature: the change of measure is state-dependent, i.e., it is a

  5. Queueing networks : Rare events and fast simulations

    NARCIS (Netherlands)

    Miretskiy, D.I.

    2009-01-01

    This monograph focuses on rare events. Even though they are extremely unlikely, they can still occur and then could have significant consequences. We mainly consider rare events in queueing networks. More precisely, we are interested in the probability of collecting some large number of jobs in the

  6. Universality and Realistic Extensions to the Semi-Analytic Simulation Principle in GNSS Signal Processing

    Directory of Open Access Journals (Sweden)

    O. Jakubov

    2012-06-01

    Full Text Available Semi-analytic simulation principle in GNSS signal processing bypasses the bit-true operations at high sampling frequency. Instead, signals at the output branches of the integrate&dump blocks are successfully modeled, thus making extensive Monte Carlo simulations feasible. Methods for simulations of code and carrier tracking loops with BPSK, BOC signals have been introduced in the literature. Matlab toolboxes were designed and published. In this paper, we further extend the applicability of the approach. Firstly, we describe any GNSS signal as a special instance of linear multi-dimensional modulation. Thereby, we state universal framework for classification of differently modulated signals. Using such description, we derive the semi-analytic models generally. Secondly, we extend the model for realistic scenarios including delay in the feed back, slowly fading multipath effects, finite bandwidth, phase noise, and a combination of these. Finally, a discussion on connection of this semi-analytic model and position-velocity-time estimator is delivered, as well as comparison of theoretical and simulated characteristics, produced by a prototype simulator developed at CTU in Prague.

  7. Simulating activation propagation in social networks using the graph theory

    Directory of Open Access Journals (Sweden)

    František Dařena

    2010-01-01

    Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

  8. SiGNet: A signaling network data simulator to enable signaling network inference.

    Directory of Open Access Journals (Sweden)

    Elizabeth A Coker

    Full Text Available Network models are widely used to describe complex signaling systems. Cellular wiring varies in different cellular contexts and numerous inference techniques have been developed to infer the structure of a network from experimental data of the network's behavior. To objectively identify which inference strategy is best suited to a specific network, a gold standard network and dataset are required. However, suitable datasets for benchmarking are difficult to find. Numerous tools exist that can simulate data for transcriptional networks, but these are of limited use for the study of signaling networks. Here, we describe SiGNet (Signal Generator for Networks: a Cytoscape app that simulates experimental data for a signaling network of known structure. SiGNet has been developed and tested against published experimental data, incorporating information on network architecture, and the directionality and strength of interactions to create biological data in silico. SiGNet is the first tool to simulate biological signaling data, enabling an accurate and systematic assessment of inference strategies. SiGNet can also be used to produce preliminary models of key biological pathways following perturbation.

  9. Integrated Circuit For Simulation Of Neural Network

    Science.gov (United States)

    Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

    1988-01-01

    Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

  10. Software for Brain Network Simulations: A Comparative Study

    Science.gov (United States)

    Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

    2017-01-01

    Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with

  11. Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks.

    Science.gov (United States)

    Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

    2016-01-01

    Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building.

  12. High precision and convenient extension simulation platform for satellite attitude and orbit system

    Science.gov (United States)

    Cui, Hongzheng; Han, Chao; Chen, Pei; Luo, Qinqin

    2012-01-01

    In this paper, a high precision and convenient extension simulation platform for satellite attitude and orbit system is developed, to demonstrate the satellite attitude and orbit system for given space mission, and test the new underdeveloped algorithms for attitude/orbit dynamics, attitude determination, orbit navigation, and attitude/orbit control. The simulation platform is based on Matlab/Simulink software, using the technique of Simulink modeling, importing C/Fortran code in Matlab/Simulink, and embedded Matlab function, with beautiful reusability, inheritability and expansibility. The paper orderly presents the background behind the development of the platform, the platform design architecture and capability, the validity of the platform, the inheritability and expansibility of the platform, the platform implementation example for Chinese weather satellite (FY-3), and the future development for the platform.

  13. HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

    Directory of Open Access Journals (Sweden)

    Luca Marchetti

    2017-01-01

    Full Text Available HSimulator is a multithread simulator for mass-action biochemical reaction systems placed in a well-mixed environment. HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA. HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. Benchmarks show that HSimulator is often considerably faster than the other considered simulators. The software, running on Java v6.0 or higher, offers a simulation GUI for modeling and visually exploring biological processes and a Javadoc-documented Java library to support the development of custom applications. HSimulator is released under the COSBI Shared Source license agreement (COSBI-SSLA.

  14. GAIA - a generalizable, extensible structure for integrating games, models and social networking to support decision makers

    Science.gov (United States)

    Paxton, L. J.; Schaefer, R. K.; Nix, M.; Fountain, G. H.; Weiss, M.; Swartz, W. H.; Parker, C. L.; MacDonald, L.; Ihde, A. G.; Simpkins, S.; GAIA Team

    2011-12-01

    In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions embodied in real-world decision making to water scarcity and water resources. We have developed a generalizable, extensible facility we call "GAIA" - Global Assimilation of Information for Action - and applied it to different problem sets. We describe the use of the "Green Country Model" and other gaming/simulation tools to address the impacts of climate and climate disruption issues at the intersection of science, economics, policy, and society. There is a long history in the Defense community of using what are known as strategic simulations or "wargames" to model the complex interactions between the environment, people, resources, infrastructure and the economy in a competitive environment. We describe in this paper, work that we have done on understanding how this heritage can be repurposed to help us explore how the complex interplay between climate disruption and our socio/political and economic structures will affect our future. Our focus here is on a fundamental and growing issue - water and water availability. We consider water and the role of "virtual water" in the system. Various "actors" are included in the simulations. While these simulations cannot definitively predict what will happen, they do illuminate non-linear feedbacks between, for example, treaty agreement, the environment, the economy, and the government. These simulations can be focused on the global, regional, or local environment. We note that these simulations are not "zero sum" games - there need not be a winner and a loser. They are, however, competitive influence games: they represent the tools that a nation, state, faction or group has at its disposal to influence policy (diplomacy), finances, industry (economy), infrastructure, information, etc to achieve their particular goals. As in the real world the problem is competitive - not everyone shares the same

  15. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System...... Identification, Prediction, Simulation and Control of a dynamic, non-linear and noisy process. Further, the difficulties to control a practical non-linear laboratory process in a satisfactory way by using a traditional controller are overcomed by using a trained neural network to perform non-linear System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...

  16. Network bursts in cortical neuronal cultures: 'noise - versus pacemaker'- driven neural network simulations

    NARCIS (Netherlands)

    Gritsun, T.; Stegenga, J.; le Feber, Jakob; Rutten, Wim

    2009-01-01

    In this paper we address the issue of spontaneous bursting activity in cortical neuronal cultures and explain what might cause this collective behavior using computer simulations of two different neural network models. While the common approach to acivate a passive network is done by introducing

  17. High Fidelity Simulations of Large-Scale Wireless Networks

    Energy Technology Data Exchange (ETDEWEB)

    Onunkwo, Uzoma [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benz, Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-11-01

    The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

  18. Dynamic thermal simulation on retrofitting scenarios for semi-extensive sheep farms

    Directory of Open Access Journals (Sweden)

    Maria E. Menconi

    2014-10-01

    Full Text Available Sheep and goat have a high adaptability to different climatic conditions. Nevertheless, even in extensive farming, these species benefit from the presence of structures that can mitigate stress from heat, cold and humidity changes. These shelters are used at night or for limited periods during the year. These are characterised by a low engineering and make extensive use of recycled material. Interesting innovation in rural areas could be represented by the re-development of these buildings in order to improve their internal microclimate. This work develops a thermal dynamic simulation model aimed at identifying the best solution to retrofit the envelope of existing livestock buildings. In this paper, three different solutions have been tested: insulation of vertical surfaces, insulation of roof and window type. Eight different materials have been considered for roof and vertical surfaces and four for the different kind of window glazing, analysing the building microclimate responses. As a reference building to compare the different solutions adopted has been chosen an extensive sheep farm located in the Italian Apennines. The results suggest that the best solution is to insulate the roof. The other elements offer negligible results in term of improving the internal microclimate conditions. For coating the roof it can also be considered a good response of all the analysed insulating materials, in order to increase the period of maintaining the temperature of comfort and not exceeding its critical values within the building.

  19. Stochastic Simulation of Biomolecular Networks in Dynamic Environments.

    Science.gov (United States)

    Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G

    2016-06-01

    Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.

  20. Stochastic Simulation of Biomolecular Networks in Dynamic Environments.

    Directory of Open Access Journals (Sweden)

    Margaritis Voliotis

    2016-06-01

    Full Text Available Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.

  1. SELANSI: a toolbox for Simulation of Stochastic Gene Regulatory Networks.

    Science.gov (United States)

    Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

    2017-10-11

    Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding chemical master equation (CME) with a partial integral differential equation (PIDE) that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es.

  2. Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

    Energy Technology Data Exchange (ETDEWEB)

    Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

    2009-09-01

    This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

  3. Local Community Detection in Complex Networks Based on Maximum Cliques Extension

    Directory of Open Access Journals (Sweden)

    Meng Fanrong

    2014-01-01

    Full Text Available Detecting local community structure in complex networks is an appealing problem that has attracted increasing attention in various domains. However, most of the current local community detection algorithms, on one hand, are influenced by the state of the source node and, on the other hand, cannot effectively identify the multiple communities linked with the overlapping nodes. We proposed a novel local community detection algorithm based on maximum clique extension called LCD-MC. The proposed method firstly finds the set of all the maximum cliques containing the source node and initializes them as the starting local communities; then, it extends each unclassified local community by greedy optimization until a certain objective is satisfied; finally, the expected local communities will be obtained until all maximum cliques are assigned into a community. An empirical evaluation using both synthetic and real datasets demonstrates that our algorithm has a superior performance to some of the state-of-the-art approaches.

  4. Synthesis of recurrent neural networks for dynamical system simulation.

    Science.gov (United States)

    Trischler, Adam P; D'Eleuterio, Gabriele M T

    2016-08-01

    We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Social Network Mixing Patterns In Mergers & Acquisitions - A Simulation Experiment

    Directory of Open Access Journals (Sweden)

    Robert Fabac

    2011-01-01

    Full Text Available In the contemporary world of global business and continuously growing competition, organizations tend to use mergers and acquisitions to enforce their position on the market. The future organization’s design is a critical success factor in such undertakings. The field of social network analysis can enhance our uderstanding of these processes as it lets us reason about the development of networks, regardless of their origin. The analysis of mixing patterns is particularly useful as it provides an insight into how nodes in a network connect with each other. We hypothesize that organizational networks with compatible mixing patterns will be integrated more successfully. After conducting a simulation experiment, we suggest an integration model based on the analysis of network assortativity. The model can be a guideline for organizational integration, such as occurs in mergers and acquisitions.

  6. In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks.

    Science.gov (United States)

    Liu, Gang; Neelamegham, Sriram

    2008-04-15

    We present In silico Biochemical Reaction Network Analysis (IBRENA), a software package which facilitates multiple functions including cellular reaction network simulation and sensitivity analysis (both forward and adjoint methods), coupled with principal component analysis, singular-value decomposition and model reduction. The software features a graphical user interface that aids simulation and plotting of in silico results. While the primary focus is to aid formulation, testing and reduction of theoretical biochemical reaction networks, the program can also be used for analysis of high-throughput genomic and proteomic data. The software package, manual and examples are available at http://www.eng.buffalo.edu/~neel/ibrena

  7. Aggregated Representation of Distribution Networks for Large-Scale Transmission Network Simulations

    DEFF Research Database (Denmark)

    Göksu, Ömer; Altin, Müfit; Sørensen, Poul Ejnar

    2014-01-01

    As a common practice of large-scale transmission network analysis the distribution networks have been represented as aggregated loads. However, with increasing share of distributed generation, especially wind and solar power, in the distribution networks, it became necessary to include the distri......As a common practice of large-scale transmission network analysis the distribution networks have been represented as aggregated loads. However, with increasing share of distributed generation, especially wind and solar power, in the distribution networks, it became necessary to include...... the distributed generation within those analysis. In this paper a practical methodology to obtain aggregated behaviour of the distributed generation is proposed. The methodology, which is based on the use of the IEC standard wind turbine models, is applied on a benchmark distribution network via simulations....

  8. Artificial Neural Network Metamodels of Stochastic Computer Simulations

    Science.gov (United States)

    1994-08-10

    23 Haddock, J. and O’Keefe, R., "Using Artificial Intelligence to Facilitate Manufacturing Systems Simulation," Computers & Industrial Engineering , Vol...Feedforward Neural Networks," Computers & Industrial Engineering , Vol. 21, No. 1- 4, (1991), pp. 247-251. 87 Proceedings of the 1992 Summer Computer...Using Simulation Experiments," Computers & Industrial Engineering , Vol. 22, No. 2 (1992), pp. 195-209. 119 Kuei, C. and Madu, C., "Polynomial

  9. Flow MRI simulation in complex 3D geometries: Application to the cerebral venous network.

    Science.gov (United States)

    Fortin, Alexandre; Salmon, Stéphanie; Baruthio, Joseph; Delbany, Maya; Durand, Emmanuel

    2018-02-05

    Develop and evaluate a complete tool to include 3D fluid flows in MRI simulation, leveraging from existing software. Simulation of MR spin flow motion is of high interest in the study of flow artifacts and angiography. However, at present, only a few simulators include this option and most are restricted to static tissue imaging. An extension of JEMRIS, one of the most advanced high performance open-source simulation platforms to date, was developed. The implementation of a Lagrangian description of the flow allows simulating any MR experiment, including both static tissues and complex flow data from computational fluid dynamics. Simulations of simple flow models are compared with real experiments on a physical flow phantom. A realistic simulation of 3D flow MRI on the cerebral venous network is also carried out. Simulations and real experiments are in good agreement. The generality of the framework is illustrated in 2D and 3D with some common flow artifacts (misregistration and inflow enhancement) and with the three main angiographic techniques: phase contrast velocimetry (PC), time-of-flight, and contrast-enhanced imaging MRA. The framework provides a versatile and reusable tool for the simulation of any MRI experiment including physiological fluids and arbitrarily complex flow motion. © 2018 International Society for Magnetic Resonance in Medicine.

  10. Transmission network expansion planning with simulation optimization

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Toole, G. Loren [Los Alamos National Laboratory

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  11. PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS.

    Science.gov (United States)

    Chen, Feng; Wang, Shuang; Jiang, Xiaoqian; Ding, Sijie; Lu, Yao; Kim, Jihoon; Sahinalp, S Cenk; Shimizu, Chisato; Burns, Jane C; Wright, Victoria J; Png, Eileen; Hibberd, Martin L; Lloyd, David D; Yang, Hai; Telenti, Amalio; Bloss, Cinnamon S; Fox, Dov; Lauter, Kristin; Ohno-Machado, Lucila

    2017-03-15

    We introduce PRINCESS, a privacy-preserving international collaboration framework for analyzing rare disease genetic data that are distributed across different continents. PRINCESS leverages Software Guard Extensions (SGX) and hardware for trustworthy computation. Unlike a traditional international collaboration model, where individual-level patient DNA are physically centralized at a single site, PRINCESS performs a secure and distributed computation over encrypted data, fulfilling institutional policies and regulations for protected health information. To demonstrate PRINCESS' performance and feasibility, we conducted a family-based allelic association study for Kawasaki Disease, with data hosted in three different continents. The experimental results show that PRINCESS provides secure and accurate analyses much faster than alternative solutions, such as homomorphic encryption and garbled circuits (over 40 000× faster). https://github.com/achenfengb/PRINCESS_opensource. shw070@ucsd.edu. Supplementary data are available at Bioinformatics online.

  12. Improving a Computer Networks Course Using the Partov Simulation Engine

    Science.gov (United States)

    Momeni, B.; Kharrazi, M.

    2012-01-01

    Computer networks courses are hard to teach as there are many details in the protocols and techniques involved that are difficult to grasp. Employing programming assignments as part of the course helps students to obtain a better understanding and gain further insight into the theoretical lectures. In this paper, the Partov simulation engine and…

  13. A Neural Network Model for Dynamics Simulation | Bholoa ...

    African Journals Online (AJOL)

    University of Mauritius Research Journal. Journal Home · ABOUT · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2009) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. A Neural Network Model for Dynamics Simulation. Ajeevsing ...

  14. Fracture Network Modeling and GoldSim Simulation Support

    OpenAIRE

    杉田 健一郎; Dershowiz, W.

    2003-01-01

    During Heisei-14, Golder Associates provided support for JNC Tokai through data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aspo Task Force on Modelling of Groundwater Flow and Transport, and analysis of repository safety assessment technologies including cell networks for evaluation of the disturbed rock zone (DRZ) and total systems performance assessment (TSPA).

  15. Latitudinal extension of low-latitude scintillations measured with a network of GPS receivers

    Directory of Open Access Journals (Sweden)

    C. E. Valladares

    2004-09-01

    Full Text Available A latitudinal-distributed network of GPS receivers has been operating within Colombia, Peru and Chile with sufficient latitudinal span to measure the absolute total electron content (TEC at both crests of the equatorial anomaly. The network also provides the latitudinal extension of GPS scintillations and TEC depletions. The GPS-based information has been supplemented with density profiles collected with the Jicamarca digisonde and JULIA power maps to investigate the background conditions of the nighttime ionosphere that prevail during the formation and the persistence of plasma depletions. This paper presents case-study events in which the latitudinal extension of GPS scintillations, the maximum latitude of TEC depletion detections, and the altitude extension of radar plumes are correlated with the location and extension of the equatorial anomaly. Then it shows the combined statistics of GPS scintillations, TEC depletions, TEC latitudinal profiles, and bottomside density profiles collected between September 2001 and June 2002. It is demonstrated that multiple sights of TEC depletions from different stations can be used to estimate the drift of the background plasma, the tilt of the plasma plumes, and in some cases even the approximate time and location of the depletion onset. This study corroborates the fact that TEC depletions and radar plumes coincide with intense levels of GPS scintillations. Bottomside radar traces do not seem to be associated with GPS scintillations. It is demonstrated that scintillations/depletions can occur when the TEC latitude profiles are symmetric, asymmetric or highly asymmetric; this is during the absence of one crest. Comparison of the location of the northern crest of the equatorial anomaly and the maximum latitude of scintillations reveals that for 90% of the days, scintillations are confined within the boundaries of the 50% decay limit of the anomaly crests. The crests of the anomaly are the regions where the

  16. Distributed Sensor Network Software Development Testing through Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Brennan, Sean M. [Univ. of New Mexico, Albuquerque, NM (United States)

    2003-12-01

    The distributed sensor network (DSN) presents a novel and highly complex computing platform with dif culties and opportunities that are just beginning to be explored. The potential of sensor networks extends from monitoring for threat reduction, to conducting instant and remote inventories, to ecological surveys. Developing and testing for robust and scalable applications is currently practiced almost exclusively in hardware. The Distributed Sensors Simulator (DSS) is an infrastructure that allows the user to debug and test software for DSNs independent of hardware constraints. The exibility of DSS allows developers and researchers to investigate topological, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, and to defeat those algorithms through simulated failure. The user speci es the topology, the environment, the application, and any number of arbitrary failures; DSS provides the virtual environmental embedding.

  17. Numerical simulations of contrail-to-cirrus transition – Part 1: An extensive parametric study

    Directory of Open Access Journals (Sweden)

    S. Unterstrasser

    2010-02-01

    Full Text Available Simulations of contrail-to-cirrus transition over up to 6 h were performed using a LES-model. The sensitivity of microphysical, optical and geometric contrail properties to relative humidity RHi, temperature T and vertical wind shear s was investigated in an extensive parametric study. The dominant parameter for contrail evolution is relative humidity. Substantial spreading is only visible for RHi≳120%. Vertical wind shear has a smaller effect on optical properties than human observers might expect from the visual impression. Our model shows that after a few hours the water vapour removed by falling ice crystals from the contrail layer can be several times higher than the ice mass that is actually present in the contrail at any instance.

  18. Simulation of Attacks for Security in Wireless Sensor Network.

    Science.gov (United States)

    Diaz, Alvaro; Sanchez, Pablo

    2016-11-18

    The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node's software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work.

  19. Simulation of Two High Pressure Distribution Network Operation in one-Network Connection

    Directory of Open Access Journals (Sweden)

    Perju Sorin

    2014-09-01

    Full Text Available The programs developed by the water supply system operators in view of metering the branches and reducing the potable water losses from the distribution network pipes lead to the performance reassessment of these networks. As a result the energetic consumption of the pumping stations should meet the accepted limits. An essential role in the evaluation of the operation parameters of the network performance is played by hydraulic modeling, by means of which the network performance simulation can be done in different scenarios. The present article describes the concept of two high-pressure network coupling. These networks are supplied by two repumping stations, in which the water flows were drastically reduced due to the present situation

  20. Brian: a simulator for spiking neural networks in Python

    Directory of Open Access Journals (Sweden)

    Dan F M Goodman

    2008-11-01

    Full Text Available Brian is a new simulator for spiking neural networks, written in Python (http://brian.di.ens.fr. It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.

  1. Socialising Health Burden Through Different Network Topologies: A Simulation Study.

    Science.gov (United States)

    Peacock, Adrian; Cheung, Anthony; Kim, Peter; Poon, Simon K

    2017-01-01

    An aging population and the expectation of premium quality health services combined with the increasing economic burden of the healthcare system requires a paradigm shift toward patient oriented healthcare. The guardian angel theory described by Szolovits [1] explores the notion of enlisting patients as primary providers of information and motivation to patients with similar clinical history through social connections. In this study, an agent based model was developed to simulate to explore how individuals are affected through their levels of intrinsic positivity. Ring, point-to-point (paired buddy), and random networks were modelled, with individuals able to send messages to each other given their levels of variables positivity and motivation. Of the 3 modelled networks it is apparent that the ring network provides the most equal, collective improvement in positivity and motivation for all users. Further study into other network topologies should be undertaken in the future.

  2. Molecular Simulations of Actomyosin Network Self-Assembly and Remodeling

    Science.gov (United States)

    Komianos, James; Popov, Konstantin; Papoian, Garegin; Papoian Lab Team

    Actomyosin networks are an integral part of the cytoskeleton of eukaryotic cells and play an essential role in determining cellular shape and movement. Actomyosin network growth and remodeling in vivo is based on a large number of chemical and mechanical processes, which are mutually coupled and spatially and temporally resolved. To investigate the fundamental principles behind the self-organization of these networks, we have developed a detailed mechanochemical, stochastic model of actin filament growth dynamics, at a single-molecule resolution, where the nonlinear mechanical rigidity of filaments and their corresponding deformations under internally and externally generated forces are taken into account. Our work sheds light on the interplay between the chemical and mechanical processes governing the cytoskeletal dynamics, and also highlights the importance of diffusional and active transport phenomena. Our simulations reveal how different actomyosin micro-architectures emerge in response to varying the network composition. Support from NSF Grant CHE-1363081.

  3. SIMULATION OF WIRELESS SENSOR NETWORK WITH HYBRID TOPOLOGY

    Directory of Open Access Journals (Sweden)

    J. Jaslin Deva Gifty

    2016-03-01

    Full Text Available The design of low rate Wireless Personal Area Network (WPAN by IEEE 802.15.4 standard has been developed to support lower data rates and low power consuming application. Zigbee Wireless Sensor Network (WSN works on the network and application layer in IEEE 802.15.4. Zigbee network can be configured in star, tree or mesh topology. The performance varies from topology to topology. The performance parameters such as network lifetime, energy consumption, throughput, delay in data delivery and sensor field coverage area varies depending on the network topology. In this paper, designing of hybrid topology by using two possible combinations such as star-tree and star-mesh is simulated to verify the communication reliability. This approach is to combine all the benefits of two network model. The parameters such as jitter, delay and throughput are measured for these scenarios. Further, MAC parameters impact such as beacon order (BO and super frame order (SO for low power consumption and high channel utilization, has been analysed for star, tree and mesh topology in beacon disable mode and beacon enable mode by varying CBR traffic loads.

  4. Hybrid neural network bushing model for vehicle dynamics simulation

    Energy Technology Data Exchange (ETDEWEB)

    Sohn, Jeong Hyun [Pukyong National University, Busan (Korea, Republic of); Lee, Seung Kyu [Hyosung Corporation, Changwon (Korea, Republic of); Yoo, Wan Suk [Pusan National University, Busan (Korea, Republic of)

    2008-12-15

    Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers

  5. Modeling and simulation of the USAVRE network and radiology operations

    Science.gov (United States)

    Martinez, Ralph; Bradford, Daniel Q.; Hatch, Jay; Sochan, John; Chimiak, William J.

    1998-07-01

    The U.S. Army Medical Command, lead by the Brooke Army Medical Center, has embarked on a visionary project. The U.S. Army Virtual Radiology Environment (USAVRE) is a CONUS-based network that connects all the Army's major medical centers and Regional Medical Commands (RMC). The purpose of the USAVRE is to improve the quality, access, and cost of radiology services in the Army via the use of state-of-the-art medical imaging, computer, and networking technologies. The USAVRE contains multimedia viewing workstations; database archive systems are based on a distributed computing environment using Common Object Request Broker Architecture (CORBA) middleware protocols. The underlying telecommunications network is an ATM-based backbone network that connects the RMC regional networks and PACS networks at medical centers and RMC clinics. This project is a collaborative effort between Army, university, and industry centers with expertise in teleradiology and Global PACS applications. This paper describes a model and simulation of the USAVRE for performance evaluation purposes. As a first step the results of a Technology Assessment and Requirements Analysis (TARA) -- an analysis of the workload in Army radiology departments, their equipment and their staffing. Using the TARA data and other workload information, we have developed a very detailed analysis of the workload and workflow patterns of our Medical Treatment Facilities. We are embarking on modeling and simulation strategies, which will form the foundation for the VRE network. The workload analysis is performed for each radiology modality in a RMC site. The workload consists of the number of examinations per modality, type of images per exam, number of images per exam, and size of images. The frequency for store and forward cases, second readings, and interactive consultation cases are also determined. These parameters are translated into the model described below. The model for the USAVRE is hierarchical in nature

  6. A new snow-vegetation interaction extension for the Water Balance Simulation Model (WaSiM)

    Science.gov (United States)

    Förster, Kristian; Meißl, Gertraud; Marke, Thomas; Pohl, Stefan; Garvelmann, Jakob; Schulla, Jörg; Strasser, Ulrich

    2017-04-01

    The water balance in forested mountainous catchments is strongly influenced by the interaction of snow and vegetation. Especially coniferous forest canopies have a large storage capacity for snow, exceeding the one for rain by one order of magnitude. The snow intercepted by the trees is exposed to increased turbulence. Hence, the sublimation of intercepted snow can amount to a significant fraction of total precipitation and therefore represents an important component of the water balance in forested environments. The current version of the Water Balance Simulation Model (WaSiM 9.09.01) has been extended to consider snow hydrological processes in forest canopies with: (i) modified micro-meteorological conditions in the forest canopy, (ii) snow interception, melt unload, and sublimation of intercepted snow, and (iii) energy balance snowmelt computation on the ground, considering the modified micro-meteorological conditions. The study presents a detailed description of the new snow-vegetation extension in WaSiM. Internal state variables of the model have been compared to inside-forest measurements (meteorological variables and snow cover dynamics) from a low-cost sensor network established in the 9.2 km2 large alpine catchment of the Brixenbach, Tyrol/Austria. Results show the improvements achieved with the extended model version for forested areas in temperate mountain environments subject to seasonal snow cover.

  7. Agent-Based Simulation Analysis for Network Formation

    OpenAIRE

    神原, 李佳; 林田, 智弘; 西﨑, 一郎; 片桐, 英樹

    2009-01-01

    In the mathematical models for network formation by Bala and Goyal(2000), it is shown that a star network is the strict Nash equilibrium. However, the result of the experiments in a laboratory using human subjects by Berninghaus et al.(2007) basing on the model of Bala and Goyal indicates that players reach a strict Nash equilibrium and deviate it. In this paper, an agent-based simulation model in which artificial adaptive agents have mechanisms of decision making and learning based on nueral...

  8. Correlated EEG Signals Simulation Based on Artificial Neural Networks.

    Science.gov (United States)

    Tomasevic, Nikola M; Neskovic, Aleksandar M; Neskovic, Natasa J

    2017-08-01

    In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence). In order to acquire the EEG recordings, the measurement campaign was carried out on a healthy awake adult having no cognitive, physical or mental load. For the evaluation of the proposed approach, comprehensive quantitative and qualitative statistical analysis was performed considering probability distribution, correlation properties and spectral characteristics of generated EEG processes. The obtained results clearly indicated the satisfactory agreement with the measurement data.

  9. Code generation: a strategy for neural network simulators.

    Science.gov (United States)

    Goodman, Dan F M

    2010-10-01

    We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).

  10. Design and Simulation Analysis for Integrated Vehicle Chassis-Network Control System Based on CAN Network

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2016-01-01

    Full Text Available Due to the different functions of the system used in the vehicle chassis control, the hierarchical control strategy also leads to many kinds of the network topology structure. According to the hierarchical control principle, this research puts forward the integrated control strategy of the chassis based on supervision mechanism. The purpose is to consider how the integrated control architecture affects the control performance of the system after the intervention of CAN network. Based on the principle of hierarchical control and fuzzy control, a fuzzy controller is designed, which is used to monitor and coordinate the ESP, AFS, and ARS. And the IVC system is constructed with the upper supervisory controller and three subcontrol systems on the Simulink platform. The network topology structure of IVC is proposed, and the IVC communication matrix based on CAN network communication is designed. With the common sensors and the subcontrollers as the CAN network independent nodes, the network induced delay and packet loss rate on the system control performance are studied by simulation. The results show that the simulation method can be used for designing the communication network of the vehicle.

  11. Artificial neural network based approach to EEG signal simulation.

    Science.gov (United States)

    Tomasevic, Nikola M; Neskovic, Aleksandar M; Neskovic, Natasa J

    2012-06-01

    In this paper a new approach to the electroencephalogram (EEG) signal simulation based on the artificial neural networks (ANN) is proposed. The aim was to simulate the spontaneous human EEG background activity based solely on the experimentally acquired EEG data. Therefore, an EEG measurement campaign was conducted on a healthy awake adult in order to obtain an adequate ANN training data set. As demonstration of the performance of the ANN based approach, comparisons were made against autoregressive moving average (ARMA) filtering based method. Comprehensive quantitative and qualitative statistical analysis showed clearly that the EEG process obtained by the proposed method was in satisfactory agreement with the one obtained by measurements.

  12. Molecular dynamics simulation of gas models of Lennard-Jones type interactions: Extensivity associated with interaction range and external noise

    Science.gov (United States)

    Kadijani, M. Nouri; Abbasi, H.; Nezamipour, S.

    2017-06-01

    Statistics of a two-dimensional gas model interacting through a Lennard-Jones type potential, is considered. The goal is to examine the extensivity of internal energy in respect to the potential range and external white noise through molecular dynamics simulation. Accordingly a molecular dynamics simulation model is designed that provides reasonable evidence, in this respect. It is shown that for the long range potential the internal energy scales according to non-extensive thermodynamics expectation and the criteria is specified. Besides, for the short range case we demonstrate that the external noise drastically modifies the statistics of gas and makes the internal energy non-extensive. The relation between the non-extensive parameter, q, and the relaxation time and the noise intensity is obtained.

  13. Frequency and motivational state: evolutionary simulations suggest an adaptive function for network oscillations

    NARCIS (Netherlands)

    Heerebout, B.T.; Phaf, R.H.; Taatgen, N.A.; van Rijn, H.

    2009-01-01

    Evolutionary simulations of foraging agents, controlled by artificial neural networks, unexpectedly yielded oscillating node activations in the networks. The agents had to navigate a virtual environment to collect food while avoiding predation. Between generations their neural networks were

  14. A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

    Science.gov (United States)

    Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

    2016-09-01

    Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

  15. A simulated annealing approach for redesigning a warehouse network problem

    Science.gov (United States)

    Khairuddin, Rozieana; Marlizawati Zainuddin, Zaitul; Jiun, Gan Jia

    2017-09-01

    Now a day, several companies consider downsizing their distribution networks in ways that involve consolidation or phase-out of some of their current warehousing facilities due to the increasing competition, mounting cost pressure and taking advantage on the economies of scale. Consequently, the changes on economic situation after a certain period of time require an adjustment on the network model in order to get the optimal cost under the current economic conditions. This paper aimed to develop a mixed-integer linear programming model for a two-echelon warehouse network redesign problem with capacitated plant and uncapacitated warehouses. The main contribution of this study is considering capacity constraint for existing warehouses. A Simulated Annealing algorithm is proposed to tackle with the proposed model. The numerical solution showed the model and method of solution proposed was practical.

  16. Computer simulation of randomly cross-linked polymer networks

    CERN Document Server

    Williams, T P

    2002-01-01

    In this work, Monte Carlo and Stochastic Dynamics computer simulations of mesoscale model randomly cross-linked networks were undertaken. Task parallel implementations of the lattice Monte Carlo Bond Fluctuation model and Kremer-Grest Stochastic Dynamics bead-spring continuum model were designed and used for this purpose. Lattice and continuum precursor melt systems were prepared and then cross-linked to varying degrees. The resultant networks were used to study structural changes during deformation and relaxation dynamics. The effects of a random network topology featuring a polydisperse distribution of strand lengths and an abundance of pendant chain ends, were qualitatively compared to recent published work. A preliminary investigation into the effects of temperature on the structural and dynamical properties was also undertaken. Structural changes during isotropic swelling and uniaxial deformation, revealed a pronounced non-affine deformation dependant on the degree of cross-linking. Fractal heterogeneiti...

  17. NCC Simulation Model: Simulating the operations of the network control center, phase 2

    Science.gov (United States)

    Benjamin, Norman M.; Paul, Arthur S.; Gill, Tepper L.

    1992-12-01

    The simulation of the network control center (NCC) is in the second phase of development. This phase seeks to further develop the work performed in phase one. Phase one concentrated on the computer systems and interconnecting network. The focus of phase two will be the implementation of the network message dialogues and the resources controlled by the NCC. These resources are requested, initiated, monitored and analyzed via network messages. In the NCC network messages are presented in the form of packets that are routed across the network. These packets are generated, encoded, decoded and processed by the network host processors that generate and service the message traffic on the network that connects these hosts. As a result, the message traffic is used to characterize the work done by the NCC and the connected network. Phase one of the model development represented the NCC as a network of bi-directional single server queues and message generating sources. The generators represented the external segment processors. The served based queues represented the host processors. The NCC model consists of the internal and external processors which generate message traffic on the network that links these hosts. To fully realize the objective of phase two it is necessary to identify and model the processes in each internal processor. These processes live in the operating system of the internal host computers and handle tasks such as high speed message exchanging, ISN and NFE interface, event monitoring, network monitoring, and message logging. Inter process communication is achieved through the operating system facilities. The overall performance of the host is determined by its ability to service messages generated by both internal and external processors.

  18. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  19. Neural network stochastic simulation applied for quantifying uncertainties

    Directory of Open Access Journals (Sweden)

    N Foudil-Bey

    2016-09-01

    Full Text Available Generally the geostatistical simulation methods are used to generate several realizations of physical properties in the sub-surface, these methods are based on the variogram analysis and limited to measures correlation between variables at two locations only. In this paper, we propose a simulation of properties based on supervised Neural network training at the existing drilling data set. The major advantage is that this method does not require a preliminary geostatistical study and takes into account several points. As a result, the geological information and the diverse geophysical data can be combined easily. To do this, we used a neural network with multi-layer perceptron architecture like feed-forward, then we used the back-propagation algorithm with conjugate gradient technique to minimize the error of the network output. The learning process can create links between different variables, this relationship can be used for interpolation of the properties on the one hand, or to generate several possible distribution of physical properties on the other hand, changing at each time and a random value of the input neurons, which was kept constant until the period of learning. This method was tested on real data to simulate multiple realizations of the density and the magnetic susceptibility in three-dimensions at the mining camp of Val d'Or, Québec (Canada.

  20. [Simulation of lung motions using an artificial neural network].

    Science.gov (United States)

    Laurent, R; Henriet, J; Salomon, M; Sauget, M; Nguyen, F; Gschwind, R; Makovicka, L

    2011-04-01

    A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. The first results are promising: an average accuracy of 1mm is obtained for a spatial resolution of 1 × 1 × 2.5mm(3). We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs. Copyright © 2010 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

  1. Pore scale simulations for the extension of the Darcy-Forchheimer law to shear thinning fluids

    Science.gov (United States)

    Tosco, Tiziana; Marchisio, Daniele; Lince, Federica; Boccardo, Gianluca; Sethi, Rajandrea

    2014-05-01

    results of flow simulations show the superposition of two contributions to pressure drops: one, strictly related to the non-Newtonian properties of the fluid, dominates at low Reynolds numbers, while a quadratic one, arising at higher Reynolds numbers, is dependent only on the porous medium properties. The results suggest that, for Newtonian flow, the porous medium can be fully described by two macroscopic parameters, namely permeability K and inertial coefficient β. Conversely, for non-Newtonian flow, an additional parameter is required, represented by the shift factor α, which depends on the properties of both porous medium and fluid, which is not easy to be determined in laboratory tests, but can be in turn calculated from 2D or 3D pore-scale flow simulations, following the approach which was adopted in this work. References 1. Sorbie, K.S. Polymer-improved oil recovery; Blackie ; CRC Press: Glasgow, Boca Raton, Fla., 1991. 2. Xue, D.; Sethi, R. Viscoelastic gels of guar and xanthan gum mixtures provide long-term stabilization of iron micro- and nanoparticles. J Nanopart Res 2012, 14(11). 3. Bird, R.B.; Armstrong, R.C.; Hassager, O. Dynamics of polymeric liquids. Volume 1. Fluid mechanics; John Wiley and Sons Inc.: New York - NY, 1977. 4. Tosco, T.; Marchisio, D.L.; Lince, F.; Sethi, R. Extension of the Darcy-Forchheimer Law for Shear-Thinning Fluids and Validation via Pore-Scale Flow Simulations. Transport in Porous Media 2013, 96(1), 1-20.

  2. Performance Evaluation and Design Considerations of Electrically Activated Drain Extension Tunneling GNRFET: A Quantum Simulation Study

    Science.gov (United States)

    Ghoreishi, Seyed Saleh; Yousefi, Reza; Taghavi, Neda

    2017-11-01

    In this paper, a tunneling graphene nanoribbon field effect transistor with electrically activated drain extension, namely, EA-T-GNRFET, is proposed. The proposed structure includes a side gate at the drain side with a constant voltage and length of 0.4 V and 15 nm, respectively. Simulations are performed based on the non-equilibrium Green's function method coupled with the Poisson equation in the mode space representation. This side gate creates an additional step in potential profile at the drain side, which increases and decreases the width of tunneling barrier and leakage current, respectively. Furthermore, the proposed structure has lower drain induced barrier thinning, lower sub-threshold swing (SS) and higher I ON/ I OFF ratio than the conventional structure. Also, other characteristics of the device such as switching delay ( τ ), power delay product (PDP) and unity-gain frequency ( f t) are improved in the proposed device. These advantages make EA-T-GNRFET more suitable for digital and analog applications.

  3. A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

    Science.gov (United States)

    Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

    2015-01-01

    We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701

  4. Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

    OpenAIRE

    Diogo Santos; José Pinto; Rossetti, Rosaldo J. F.; Eugénio Oliveira

    2016-01-01

    Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO - Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models - particul...

  5. Ekofisk chalk: core measurements, stochastic reconstruction, network modeling and simulation

    Energy Technology Data Exchange (ETDEWEB)

    Talukdar, Saifullah

    2002-07-01

    This dissertation deals with (1) experimental measurements on petrophysical, reservoir engineering and morphological properties of Ekofisk chalk, (2) numerical simulation of core flood experiments to analyze and improve relative permeability data, (3) stochastic reconstruction of chalk samples from limited morphological information, (4) extraction of pore space parameters from the reconstructed samples, development of network model using pore space information, and computation of petrophysical and reservoir engineering properties from network model, and (5) development of 2D and 3D idealized fractured reservoir models and verification of the applicability of several widely used conventional up scaling techniques in fractured reservoir simulation. Experiments have been conducted on eight Ekofisk chalk samples and porosity, absolute permeability, formation factor, and oil-water relative permeability, capillary pressure and resistivity index are measured at laboratory conditions. Mercury porosimetry data and backscatter scanning electron microscope images have also been acquired for the samples. A numerical simulation technique involving history matching of the production profiles is employed to improve the relative permeability curves and to analyze hysteresis of the Ekofisk chalk samples. The technique was found to be a powerful tool to supplement the uncertainties in experimental measurements. Porosity and correlation statistics obtained from backscatter scanning electron microscope images are used to reconstruct microstructures of chalk and particulate media. The reconstruction technique involves a simulated annealing algorithm, which can be constrained by an arbitrary number of morphological parameters. This flexibility of the algorithm is exploited to successfully reconstruct particulate media and chalk samples using more than one correlation functions. A technique based on conditional simulated annealing has been introduced for exact reproduction of vuggy

  6. Network Flow Simulation of Fluid Transients in Rocket Propulsion Systems

    Science.gov (United States)

    Bandyopadhyay, Alak; Hamill, Brian; Ramachandran, Narayanan; Majumdar, Alok

    2011-01-01

    Fluid transients, also known as water hammer, can have a significant impact on the design and operation of both spacecraft and launch vehicle propulsion systems. These transients often occur at system activation and shutdown. The pressure rise due to sudden opening and closing of valves of propulsion feed lines can cause serious damage during activation and shutdown of propulsion systems. During activation (valve opening) and shutdown (valve closing), pressure surges must be predicted accurately to ensure structural integrity of the propulsion system fluid network. In the current work, a network flow simulation software (Generalized Fluid System Simulation Program) based on Finite Volume Method has been used to predict the pressure surges in the feed line due to both valve closing and valve opening using two separate geometrical configurations. The valve opening pressure surge results are compared with experimental data available in the literature and the numerical results compared very well within reasonable accuracy (simulation results are compared with the results of Method of Characteristics. Most rocket engines experience a longitudinal acceleration, known as "pogo" during the later stage of engine burn. In the shutdown example problem, an accumulator has been used in the feed system to demonstrate the "pogo" mitigation effects in the feed system of propellant. The simulation results using GFSSP compared very well with the results of Method of Characteristics.

  7. OMNeT++-Based Cross-Layer Simulator for Content Transmission over Wireless Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Massin R

    2010-01-01

    Full Text Available Flexbility and deployment simplicity are among the numerous advantages of wireless links when compared to standard wired communications. However, challenges do remain high for wireless communications, in particular due to the wireless medium inherent unreliability, and to the desired flexibility, which entails complex protocol procedures. In that context simulation is an important tool to understand and design the protocols that manage the wireless networks. This paper introduces a new simulation framework based on the OMNeT++ simulator whose goal is to enable the study of data and multimedia content transmission over hybrid wired/wireless ad hoc networks, as well as the design of innovative radio access schemes. To achieve this goal, the complete protocol stack from the application to the physical layer is simulated, and the real bits and bytes of the messages transferred on the radio channel are exchanged. To ensure that this framework is reusable and extensible in future studies and projects, a modular software and protocol architecture has been defined. Although still in progress, our work has already provided some valuable results concerning cross layer HARQ/MAC protocol performance and video transmission over the wireless channel, as illustrated by results examples.

  8. Efficiently passing messages in distributed spiking neural network simulation.

    Science.gov (United States)

    Thibeault, Corey M; Minkovich, Kirill; O'Brien, Michael J; Harris, Frederick C; Srinivasa, Narayan

    2013-01-01

    Efficiently passing spiking messages in a neural model is an important aspect of high-performance simulation. As the scale of networks has increased so has the size of the computing systems required to simulate them. In addition, the information exchange of these resources has become more of an impediment to performance. In this paper we explore spike message passing using different mechanisms provided by the Message Passing Interface (MPI). A specific implementation, MVAPICH, designed for high-performance clusters with Infiniband hardware is employed. The focus is on providing information about these mechanisms for users of commodity high-performance spiking simulators. In addition, a novel hybrid method for spike exchange was implemented and benchmarked.

  9. An artifical neural network for detection of simulated dental caries

    Energy Technology Data Exchange (ETDEWEB)

    Kositbowornchai, S. [Khon Kaen Univ. (Thailand). Dept. of Oral Diagnosis; Siriteptawee, S.; Plermkamon, S.; Bureerat, S. [Khon Kaen Univ. (Thailand). Dept. of Mechanical Engineering; Chetchotsak, D. [Khon Kaen Univ. (Thailand). Dept. of Industrial Engineering

    2006-08-15

    Objects: A neural network was developed to diagnose artificial dental caries using images from a charged-coupled device (CCD)camera and intra-oral digital radiography. The diagnostic performance of this neural network was evaluated against a gold standard. Materials and methods: The neural network design was the Learning Vector Quantization (LVQ) used to classify a tooth surface as sound or as having dental caries. The depth of the dental caries was indicated on a graphic user interface (GUI) screen developed by Matlab programming. Forty-nine images of both sound and simulated dental caries, derived from a CCD camera and by digital radiography, were used to 'train' an artificial neural network. After the 'training' process, a separate test-set comprising 322 unseen images was evaluated. Tooth sections and microscopic examinations were used to confirm the actual dental caries status.The performance of neural network was evaluated using diagnostic test. Results: The sensitivity (95%CI)/specificity (95%CI) of dental caries detection by the CCD camera and digital radiography were 0.77(0.68-0.85)/0.85(0.75-0.92) and 0.81(0.72-0.88)/0.93(0.84-0.97), respectively. The accuracy of caries depth-detection by the CCD camera and digital radiography was 58 and 40%, respectively. Conclusions: The model neural network used in this study could be a prototype for caries detection but should be improved for classifying caries depth. Our study suggests an artificial neural network can be trained to make the correct interpretations of dental caries. (orig.)

  10. Biochemical Network Stochastic Simulator (BioNetS: software for stochastic modeling of biochemical networks

    Directory of Open Access Journals (Sweden)

    Elston Timothy C

    2004-03-01

    Full Text Available Abstract Background Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. Results We have developed the software package Biochemical Network Stochastic Simulator (BioNetS for efficientlyand accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solvesthe appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://www.biospice.org. BioNetS also can be run as a stand alone package. All the required files are accessible from http://x.amath.unc.edu/BioNetS. Conclusions We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.

  11. Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS

    Directory of Open Access Journals (Sweden)

    Christopher Bergmeir

    2012-01-01

    Full Text Available Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main features are (a encapsulation of the relevant SNNS parts in a C++ class, for sequential and parallel usage of different networks, (b accessibility of all of the SNNSalgorithmic functionality from R using a low-level interface, and (c a high-level interface for convenient, R-style usage of many standard neural network procedures. The package also includes functions for visualization and analysis of the models and the training procedures, as well as functions for data input/output from/to the original SNNSfile formats.

  12. Optimization of sustainable buildings envelopes for extensive sheep farming through the use of dynamic energy simulation

    Directory of Open Access Journals (Sweden)

    Maria Elena Menconi

    2013-09-01

    Full Text Available Extensive sheep farming can be seen as a marginal market, compared to other livestock and agricultural activities, taking into account only the economic absolute values. But for many rural marginal areas within the European Community member states, in particular for those located in the Mediterranean area on hills or mountains with high landscape value, extensive sheep farming is not only the longest practiced animal farming activity, but also the most interesting considering its adaptability to the territorial morphology and the restrictions that have been established over the years in terms of sustainable rural development practices. At the moment, most of the structures used in this type of farming are built using low cost and sometimes recycled, but often unsuitable, materials. Few specific studies have been carried out on this particular issue assuming, presumably, that the very low profit margins of these activities made impossible any restructuring. Taken this into account, the new Rural Development Plans that will be issued in 2014 will surely contain some measure dedicated to innovations in farming structures and technology towards facilitating the application of the principles of energy optimization. This is the framework in which the present research has developed. The software that has been applied to perform the energy optimization analysis is the dynamic energy simulation engine Energy Plus. A case study farm has been identified in the small village of Ceseggi (PG, situated in Central Italy. For the case study optimum thermo hygrometric conditions have been identified to ensure the welfare of animals and operators and it has been hypothesized the insertion of an ideal HVAC system to achieve them. Afterwards were evaluated the different energy requirements of the building while varying the insulation material used on the vertical surfaces. The greater goal is to verify which could be the best insulation material for vertical

  13. Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

    Science.gov (United States)

    Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

    2011-05-01

    Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.

  14. Computer Simulations of Bottlebrush Melts and Soft Networks

    Science.gov (United States)

    Cao, Zhen; Carrillo, Jan-Michael; Sheiko, Sergei; Dobrynin, Andrey

    We have studied dense bottlebrush systems in a melt and network state using a combination of the molecular dynamics simulations and analytical calculations. Our simulations show that the bottlebrush macromolecules in a melt behave as ideal chains with the effective Kuhn length bK. The bottlebrush induced bending rigidity is due to redistribution of the side chains upon backbone bending. Kuhn length of the bottlebrushes increases with increasing the side-chain degree of polymerization nsc as bK ~nsc0 . 46 . This model of bottlebrush macromolecules is extended to describe mechanical properties of bottlebrush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G0 ~nsc + 1 - 1 as long as the ratio of the Kuhn length to the size of the fully extended bottlebrush backbone between crosslinks, Rmax, is smaller than unity, bK /Rmax crosslinks. Nsf DMR-1409710 DMR-1436201.

  15. Quantum versus simulated annealing in wireless interference network optimization.

    Science.gov (United States)

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-16

    Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking-more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.

  16. Simulating dynamic and mixed-severity fire regimes: a process-based fire extension for LANDIS-II

    Science.gov (United States)

    Brian R. Sturtevant; Robert M. Scheller; Brian R. Miranda; Douglas. Shinneman; Alexandra. Syphard

    2009-01-01

    Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and...

  17. Leader neurons in leaky integrate and fire neural network simulations.

    Science.gov (United States)

    Zbinden, Cyrille

    2011-10-01

    In this paper, we highlight the topological properties of leader neurons whose existence is an experimental fact. Several experimental studies show the existence of leader neurons in population bursts of activity in 2D living neural networks (Eytan and Marom, J Neurosci 26(33):8465-8476, 2006; Eckmann et al., New J Phys 10(015011), 2008). A leader neuron is defined as a neuron which fires at the beginning of a burst (respectively network spike) more often than we expect by chance considering its mean firing rate. This means that leader neurons have some burst triggering power beyond a chance-level statistical effect. In this study, we characterize these leader neuron properties. This naturally leads us to simulate neural 2D networks. To build our simulations, we choose the leaky integrate and fire (lIF) neuron model (Gerstner and Kistler 2002; Cessac, J Math Biol 56(3):311-345, 2008), which allows fast simulations (Izhikevich, IEEE Trans Neural Netw 15(5):1063-1070, 2004; Gerstner and Naud, Science 326:379-380, 2009). The dynamics of our lIF model has got stable leader neurons in the burst population that we simulate. These leader neurons are excitatory neurons and have a low membrane potential firing threshold. Except for these two first properties, the conditions required for a neuron to be a leader neuron are difficult to identify and seem to depend on several parameters involved in the simulations themselves. However, a detailed linear analysis shows a trend of the properties required for a neuron to be a leader neuron. Our main finding is: A leader neuron sends signals to many excitatory neurons as well as to few inhibitory neurons and a leader neuron receives only signals from few other excitatory neurons. Our linear analysis exhibits five essential properties of leader neurons each with different relative importance. This means that considering a given neural network with a fixed mean number of connections per neuron, our analysis gives us a way of

  18. Analysis of sensor network observations during some simulated landslide experiments

    Science.gov (United States)

    Scaioni, M.; Lu, P.; Feng, T.; Chen, W.; Wu, H.; Qiao, G.; Liu, C.; Tong, X.; Li, R.

    2012-12-01

    A multi-sensor network was tested during some experiments on a landslide simulation platform established at Tongji University (Shanghai, P.R. China). Here landslides were triggered by means of artificial rainfall (see Figure 1). The sensor network currently incorporates contact sensors and two imaging systems. This represent a novel solution, because the spatial sensor network incorporate either contact sensors and remote sensors (video-cameras). In future, these sensors will be installed on two real ground slopes in Sichuan province (South-West China), where Wenchuan earthquake occurred in 2008. This earthquake caused the immediate activation of several landslide, while other area became unstable and still are a menace for people and properties. The platform incorporates the reconstructed scale slope, sensor network, communication system, database and visualization system. Some landslide simulation experiments allowed ascertaining which sensors could be more suitable to be deployed in Wenchuan area. The poster will focus on the analysis of results coming from down scale simulations. Here the different steps of the landslide evolution can be followed on the basis of sensor observations. This include underground sensors to detect the water table level and the pressure in the ground, a set of accelerometers and two inclinometers. In the first part of the analysis the full data series are investigated to look for correlations and common patterns, as well as to link them to the physical processes. In the second, 4 subsets of sensors located in neighbor positions are analyzed. The analysis of low- and high-speed image sequences allowed to track a dense field of displacement on the slope surface. These outcomes have been compared to the ones obtained from accelerometers for cross-validation. Images were also used for the photogrammetric reconstruction of the slope topography during the experiment. Consequently, volume computation and mass movements could be evaluated on

  19. COEL: A Cloud-based Reaction Network Simulator

    Directory of Open Access Journals (Sweden)

    Peter eBanda

    2016-04-01

    Full Text Available Chemical Reaction Networks (CRNs are a formalism to describe the macroscopic behavior of chemical systems. We introduce COEL, a web- and cloud-based CRN simulation framework that does not require a local installation, runs simulations on a large computational grid, provides reliable database storage, and offers a visually pleasing and intuitive user interface. We present an overview of the underlying software, the technologies, and the main architectural approaches employed. Some of COEL's key features include ODE-based simulations of CRNs and multicompartment reaction networks with rich interaction options, a built-in plotting engine, automatic DNA-strand displacement transformation and visualization, SBML/Octave/Matlab export, and a built-in genetic-algorithm-based optimization toolbox for rate constants.COEL is an open-source project hosted on GitHub (http://dx.doi.org/10.5281/zenodo.46544, which allows interested research groups to deploy it on their own sever. Regular users can simply use the web instance at no cost at http://coel-sim.org. The framework is ideally suited for a collaborative use in both research and education.

  20. A Network Scheduling Model for Distributed Control Simulation

    Science.gov (United States)

    Culley, Dennis; Thomas, George; Aretskin-Hariton, Eliot

    2016-01-01

    Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

  1. Simulation of heart rate variability model in a network

    Science.gov (United States)

    Cascaval, Radu C.; D'Apice, Ciro; D'Arienzo, Maria Pia

    2017-07-01

    We consider a 1-D model for the simulation of the blood flow in the cardiovascular system. As inflow condition we consider a model for the aortic valve. The opening and closing of the valve is dynamically determined by the pressure difference between the left ventricular and aortic pressures. At the outflow we impose a peripheral resistance model. To approximate the solution we use a numerical scheme based on the discontinuous Galerkin method. We also considering a variation in heart rate and terminal reflection coefficient due to monitoring of the pressure in the network.

  2. DC Collection Network Simulation for Offshore Wind Farms

    DEFF Research Database (Denmark)

    Vogel, Stephan; Rasmussen, Tonny Wederberg; El-Khatib, Walid Ziad

    2015-01-01

    The possibility to connect offshore wind turbines with a collection network based on Direct Current (DC), instead of Alternating Current (AC), gained attention in the scientific and industrial environment. There are many promising properties of DC components that could be beneficial such as......: smaller dimensions, less weight, fewer conductors, no reactive power considerations, and less overall losses due to the absence of proximity and skin effects. This work describes a study about the simulation of a Medium Voltage DC (MVDC) grid in an offshore wind farm. Suitable converter concepts...

  3. Coarse-graining stochastic biochemical networks: adiabaticity and fast simulations

    Energy Technology Data Exchange (ETDEWEB)

    Nemenman, Ilya [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Hengartner, Nick [Los Alamos National Laboratory

    2008-01-01

    We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscoplc, non-Poissonian fluctuations of the slow ones. Our approach, which is similar to the Born-Oppenhelmer approximation in quantum mechanics, follows from the stochastic path Integral representation of the cumulant generating function of reaction events. In applications with a small number of chemIcal reactions, It produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, Interpretable representation and can be used for coarse-grained numerical simulation schemes with a small computational complexity and yet high accuracy. As an example, we derive the coarse-grained description for a chain of biochemical reactions, and show that the coarse-grained and the microscopic simulations are in an agreement, but the coarse-gralned simulations are three orders of magnitude faster.

  4. A Multiparameter Network Reveals Extensive Divergence between C. elegans bHLH Transcription Factors

    DEFF Research Database (Denmark)

    Grove, C.; De Masi, Federico; Newburger, Daniel

    2009-01-01

    parameters remain undetermined. We comprehensively identify dimerization partners, spatiotemporal expression patterns, and DNA-binding specificities for the C. elegans bHLH family of TFs, and model these data into an integrated network. This network displays both specificity and promiscuity, as some b...

  5. Wireless Power Transfer Protocols in Sensor Networks: Experiments and Simulations

    Directory of Open Access Journals (Sweden)

    Sotiris Nikoletseas

    2017-04-01

    Full Text Available Rapid technological advances in the domain of Wireless Power Transfer pave the way for novel methods for power management in systems of wireless devices, and recent research works have already started considering algorithmic solutions for tackling emerging problems. In this paper, we investigate the problem of efficient and balanced Wireless Power Transfer in Wireless Sensor Networks. We employ wireless chargers that replenish the energy of network nodes. We propose two protocols that configure the activity of the chargers. One protocol performs wireless charging focused on the charging efficiency, while the other aims at proper balance of the chargers’ residual energy. We conduct detailed experiments using real devices and we validate the experimental results via larger scale simulations. We observe that, in both the experimental evaluation and the evaluation through detailed simulations, both protocols achieve their main goals. The Charging Oriented protocol achieves good charging efficiency throughout the experiment, while the Energy Balancing protocol achieves a uniform distribution of energy within the chargers.

  6. Quantum versus simulated annealing in wireless interference network optimization

    Science.gov (United States)

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-01

    Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.

  7. 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

  8. Network condition simulator for benchmarking sewer deterioration models.

    Science.gov (United States)

    Scheidegger, A; Hug, T; Rieckermann, J; Maurer, M

    2011-10-15

    An accurate description of aging and deterioration of urban drainage systems is necessary for optimal investment and rehabilitation planning. Due to a general lack of suitable datasets, network condition models are rarely validated, and if so with varying levels of success. We therefore propose a novel network condition simulator (NetCoS) that produces a synthetic population of sewer sections with a given condition-class distribution. NetCoS can be used to benchmark deterioration models and guide utilities in the selection of appropriate models and data management strategies. The underlying probabilistic model considers three main processes: a) deterioration, b) replacement policy, and c) expansions of the sewer network. The deterioration model features a semi-Markov chain that uses transition probabilities based on user-defined survival functions. The replacement policy is approximated with a condition-class dependent probability of replacing a sewer pipe. The model then simulates the course of the sewer sections from the installation of the first line to the present, adding new pipes based on the defined replacement and expansion program. We demonstrate the usefulness of NetCoS in two examples where we quantify the influence of incomplete data and inspection frequency on the parameter estimation of a cohort survival model and a Markov deterioration model. Our results show that typical available sewer inventory data with discarded historical data overestimate the average life expectancy by up to 200 years. Although NetCoS cannot prove the validity of a particular deterioration model, it is useful to reveal its possible limitations and shortcomings and quantifies the effects of missing or uncertain data. Future developments should include additional processes, for example to investigate the long-term effect of pipe rehabilitation measures, such as inliners. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Brainlab: a Python toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NeoCortical Simulator

    Directory of Open Access Journals (Sweden)

    Richard P Drewes

    2009-05-01

    Full Text Available Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading ``glue'' tool for managing all sorts of complex programmatictasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS environment in particular. Brainlab is an integrated model building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS (the NeoCortical Simulator.

  10. Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator.

    Science.gov (United States)

    Drewes, Rich; Zou, Quan; Goodman, Philip H

    2009-01-01

    Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading "glue" tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS.

  11. Climate and change: simulating flooding impacts on urban transport network

    Science.gov (United States)

    Pregnolato, Maria; Ford, Alistair; Dawson, Richard

    2015-04-01

    National-scale climate projections indicate that in the future there will be hotter and drier summers, warmer and wetter winters, together with rising sea levels. The frequency of extreme weather events is expected to increase, causing severe damage to the built environment and disruption of infrastructures (Dawson, 2007), whilst population growth and changed demographics are placing new demands on urban infrastructure. It is therefore essential to ensure infrastructure networks are robust to these changes. This research addresses these challenges by focussing on the development of probabilistic tools for managing risk by modelling urban transport networks within the context of extreme weather events. This paper presents a methodology to investigate the impacts of extreme weather events on urban environment, in particular infrastructure networks, through a combination of climate simulations and spatial representations. By overlaying spatial data on hazard thresholds from a flood model and a flood safety function, mitigated by potential adaptation strategies, different levels of disruption to commuting journeys on road networks are evaluated. The method follows the Catastrophe Modelling approach and it consists of a spatial model, combining deterministic loss models and probabilistic risk assessment techniques. It can be applied to present conditions as well as future uncertain scenarios, allowing the examination of the impacts alongside socio-economic and climate changes. The hazard is determined by simulating free surface water flooding, with the software CityCAT (Glenis et al., 2013). The outputs are overlapped to the spatial locations of a simple network model in GIS, which uses journey-to-work (JTW) observations, supplemented with speed and capacity information. To calculate the disruptive effect of flooding on transport networks, a function relating water depth to safe driving car speed has been developed by combining data from experimental reports (Morris et

  12. On the Universality of Resilience Patterns in Complex Networks: Limitations and Extensions

    CERN Document Server

    Tu, Chengyi; Grilli, Jacopo; Maritan, Amos

    2016-01-01

    Gao et al.\\cite{Gao2016} developed a theoretical framework that, under two main assumptions, separates the roles of dynamics and topology in multi-dimensional systems. Using their method, the multi-dimensional dynamical behavior obtained under different networks collapses onto a one dimensional universal resilience function. The two main conditions that are at the heart of Gao et al. elegant formalism are: $(i)$ The network determined by the the interaction between pairs of nodes, and described by a matrix $A$, has negligible degree correlations; $(ii)$ The node activities are uniform across nodes or both the drift and interaction functions ($F$ and $G$) can be considered linear.Moreover, Gao et al. limit their analysis to positive interactions networks. The authors finally claim that their formalism can be applied to very general system dynamical equations, and it represents a "Universal resilience patterns in complex networks". Here we show that: $a)$ the two assumptions are neither sufficient nor necessary...

  13. On the errors of spectral shallow-water limited-area model simulations using an extension technique

    Energy Technology Data Exchange (ETDEWEB)

    Simmel, M.; Harlander, U. [Leipzig Univ. (Germany). Inst. fuer Meteorologie (LIM)

    1999-08-01

    Although the spectral technique is frequently used for the horizontal discretization in global atmospheric models, it is not common in limited area models (LAMs) because of the nonperiodic boundary conditions. We apply the Haugen-Machenhauer extension technique to a regional three-layer shallow-water model based on double Fourier series. The method extends the time-dependent boundary fields into a zone outside the integration area in a way that periodic fields are obtained. The boundary fields necessary for the regional model simulations are calculated in advance by a global simulation performed. In contrast to other studies, we use exactly the same numerical model for the global and the regional simulation, respectively. The only difference between these simulations is the model domain. Therefore, a relatively objective measure for errors associated with the extension technique can be obtained. First, we compare an analytic stationary nonlinear and nonperiodic solution of the governing model equations with the spectral LAM solution. Secondly, we compare the time evolution of pressure and flow structures during a westerly flow across an asymmetric large-scale topography in the global and regional model domains. Both simulations show a good agreement between the regional and the global solutions. The rms-errors amount to about 2 m for the layer heights and 0.2 m s{sup -1} for the velocity components in the mountain flow case after a 48 h integration period. Finally, we repeat this simulation with models based on 2nd and 4th order finite differences, respectively, and compare the errors of the spectral model version with the errors of the grid point versions. We demonstrate that the high accuracy of global spectral methods can also be realized in the regional model by using the Haugen-Machenhauer extension technique. (orig.) 21 refs.

  14. Capacity Extension of Software Defined Data Center Networks With Jellyfish Topology

    DEFF Research Database (Denmark)

    Mehmeri, Victor; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso

    We present a performance analysis of Jellyfish topology with Software-Defined commodity switches for Data Center networks. Our results show up to a 2-fold performance gain when compared to a Spanning Tree Protocol implementation.......We present a performance analysis of Jellyfish topology with Software-Defined commodity switches for Data Center networks. Our results show up to a 2-fold performance gain when compared to a Spanning Tree Protocol implementation....

  15. INDEX: Incremental depth extension approach for protein-protein interaction networks alignment.

    Science.gov (United States)

    Mir, Abolfazl; Naghibzadeh, Mahmoud; Saadati, Nayyereh

    2017-12-01

    High-throughput methods have provided us with a large amount of data pertaining to protein-protein interaction networks. The alignment of these networks enables us to better understand biological systems. Given the fact that the alignment of networks is computationally intractable, it is important to introduce a more efficient and accurate algorithm which finds as large as possible similar areas among networks. This paper proposes a new algorithm named INDEX for the global alignment of protein-protein interaction networks. INDEX has multiple phases. First, it computes topological and biological scores of proteins and creates the initial alignment based on the proposed matching score strategy. Using networks topologies and aligned proteins, it then selects a set of high scoring proteins in each phase and extends new alignments around them until final alignment is obtained. Proposing a new alignment strategy, detailed consideration of matching scores, and growth of the alignment core has led INDEX to obtain a larger common connected subgraph with a much greater number of edges compared with previous methods. Regarding other measures such as edge correctness, symmetric substructure score, and runtime, the proposed algorithm performed considerably better than existing popular methods. Our results show that INDEX can be a promising method for identifying functionally conserved interactions. The INDEX executable file is available at https://github.com/a-mir/index/. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Ground Motion Simulations for Bursa Region (Turkey) Using Input Parameters derived from the Regional Seismic Network

    Science.gov (United States)

    Unal, B.; Askan, A.

    2014-12-01

    Earthquakes are among the most destructive natural disasters in Turkey and it is important to assess seismicity in different regions with the use of seismic networks. Bursa is located in Marmara Region, Northwestern Turkey and to the south of the very active North Anatolian Fault Zone. With around three million inhabitants and key industrial facilities of the country, Bursa is the fourth largest city in Turkey. Since most of the focus is on North Anatolian Fault zone, despite its significant seismicity, Bursa area has not been investigated extensively until recently. For reliable seismic hazard estimations and seismic design of structures, assessment of potential ground motions in this region is essential using both recorded and simulated data. In this study, we employ stochastic finite-fault simulation with dynamic corner frequency approach to model previous events as well to assess potential earthquakes in Bursa. To ensure simulations with reliable synthetic ground motion outputs, the input parameters must be carefully derived from regional data. In this study, using strong motion data collected at 33 stations in the region, site-specific parameters such as near-surface high frequency attenuation parameter and amplifications are obtained. Similarly, source and path parameters are adopted from previous studies that as well employ regional data. Initially, major previous events in the region are verified by comparing the records with the corresponding synthetics. Then simulations of scenario events in the region are performed. We present the results in terms of spatial distribution of peak ground motion parameters and time histories at selected locations.

  17. Neural network simulation of the industrial producer price index dynamical series

    OpenAIRE

    Soshnikov, L. E.

    2013-01-01

    This paper is devoted the simulation and forecast of dynamical series of the economical indicators. Multilayer perceptron and Radial basis function neural networks have been used. The neural networks model results are compared with the econometrical modeling.

  18. TopoGen: A Network Topology Generation Architecture with application to automating simulations of Software Defined Networks

    CERN Document Server

    Laurito, Andres; The ATLAS collaboration

    2017-01-01

    Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...

  19. TopoGen: A Network Topology Generation Architecture with application to automating simulations of Software Defined Networks

    CERN Document Server

    Laurito, Andres; The ATLAS collaboration

    2018-01-01

    Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...

  20. An extensive assessment of network alignment algorithms for comparison of brain connectomes.

    Science.gov (United States)

    Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

    2017-06-06

    Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

  1. Space Link Extension (SLE) Emulation for High-Throughput Network Communication

    Science.gov (United States)

    Murawski, Robert W.; Tchorowski, Nicole; Golden, Bert

    2014-01-01

    As the data rate requirements for space communications increases, significant stress is placed not only on the wireless satellite communication links, but also on the ground networks which forward data from end-users to remote ground stations. These wide area network (WAN) connections add delay and jitter to the end-to-end satellite communication link, effects which can have significant impacts on the wireless communication link. It is imperative that any ground communication protocol can react to these effects such that the ground network does not become a bottleneck in the communication path to the satellite. In this paper, we present our SCENIC Emulation Lab testbed which was developed to test the CCSDS SLE protocol implementations proposed for use on future NASA communication networks. Our results show that in the presence of realistic levels of network delay, high-throughput SLE communication links can experience significant data rate throttling. Based on our observations, we present some insight into why this data throttling happens, and trace the probable issue back to non-optimal blocking communication which is sup-ported by the CCSDS SLE API recommended practices. These issues were presented as well to the SLE implementation developers which, based on our reports, developed a new release for SLE which we show fixes the SLE blocking issue and greatly improves the protocol throughput. In this paper, we also discuss future developments for our end-to-end emulation lab and how these improvements can be used to develop and test future space communication technologies.

  2. Agricultural Extension, Collective Action and Innovation Systems: Lessons on Network Brokering from Peru and Mexico

    Science.gov (United States)

    Hellin, Jon

    2012-01-01

    Purpose: New approaches to extension service delivery are needed that stimulate increased agricultural production, contribute to collective action and which also foster the emergence of agricultural innovation systems. Research in Peru and Mexico explores some of these new approaches. Design/methodology/approach: In both countries, a qualitative…

  3. Enhancing network performance under single link failure with AS-disjoint BGP extension

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Romeral, S.; Ruepp, Sarah Renée

    2009-01-01

    In this paper we propose an enhancement of the BGP protocol for obtaining AS-disjoint paths in GMPLS multi-domain networks. We evaluate the benefits of having AS-disjoint paths under single inter-domain link failure for two main applications: routing of future connection requests during routing...... protocol re-convergence and applying multi-domain restoration as survivability mechanism in case of a single link failure. The proposed BGP modification is a simple and effective solution for disjoint path selection in connection-oriented multi-domain networks. Our results show that applying the proper...... failure notification method combined with our proposal reduces the blocking of new connection requests under protocol re-convergence. Furthermore. we show that our proposal is a valuable complementary process for increasing the network resilience....

  4. USE OF NEURAL NETWORK SIMULATION TO MONITOR PATIENTS UNDERGOING RADICAL PROSTATECTOMY

    National Research Council Canada - National Science Library

    I. V. Lukyanov; N. A. Demchenko

    2014-01-01

    .... Based on neural network simulation, the Department of Urology, Russian Medical Academy of Postgraduate Education, has developed an accounting prognostic system to monitor the postoperative course...

  5. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions

    DEFF Research Database (Denmark)

    Hutton, Brian; Salanti, Georgia; Caldwell, Deborah M

    2015-01-01

    The PRISMA statement is a reporting guideline designed to improve the completeness of reporting of systematic reviews and meta-analyses. Authors have used this guideline worldwide to prepare their reviews for publication. In the past, these reports typically compared 2 treatment alternatives....... With the evolution of systematic reviews that compare multiple treatments, some of them only indirectly, authors face novel challenges for conducting and reporting their reviews. This extension of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement was developed specifically...... to improve the reporting of systematic reviews incorporating network meta-analyses. A group of experts participated in a systematic review, Delphi survey, and face-to-face discussion and consensus meeting to establish new checklist items for this extension statement. Current PRISMA items were also clarified...

  6. The Virtual Brain: a simulator of primate brain network dynamics

    Directory of Open Access Journals (Sweden)

    Paula eSanz Leon

    2013-06-01

    Full Text Available We present TheVirtualBrain (TVB, a neuroinformatics platform for full brainnetwork simulations using biologically realistic connectivity. This simulationenvironment enables the model-based inference of neurophysiological mechanismsacross different brain scales that underlie the generation of macroscopicneuroimaging signals including functional MRI (fMRI, EEG and MEG. Researchersfrom different backgrounds can benefit from an integrative software platformincluding a supporting framework for data management (generation,organization, storage, integration and sharing and a simulation core writtenin Python. TVB allows the reproduction and evaluation of personalizedconfigurations of the brain by using individual subject data. Thispersonalization facilitates an exploration of the consequences of pathologicalchanges in the system, permitting to investigate potential ways to counteractsuch unfavorable processes. The architecture of TVB supports interaction withMATLAB packages, for example, the well known Brain Connectivity Toolbox. TVBcan be used in a client-server configuration, such that it can be remotelyaccessed through the Internet thanks to its web-basedHTML5, JS and WebGL graphical user interface. TVB is alsoaccessible as a standalone cross-platform Python library and application, andusers can interact with the scientific core through the scripting interfaceIDLE, enabling easy modeling, development and debugging of the scientifickernel. This second interface makes TVB extensible by combining it with otherlibraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to thedevelopment of TVB, the architecture and features of its major softwarecomponents as well as potential neuroscience applications.

  7. Model and simulation of Krause model in dynamic open network

    Science.gov (United States)

    Zhu, Meixia; Xie, Guangqiang

    2017-08-01

    The construction of the concept of evolution is an effective way to reveal the formation of group consensus. This study is based on the modeling paradigm of the HK model (Hegsekmann-Krause). This paper analyzes the evolution of multi - agent opinion in dynamic open networks with member mobility. The results of the simulation show that when the number of agents is constant, the interval distribution of the initial distribution will affect the number of the final view, The greater the distribution of opinions, the more the number of views formed eventually; The trust threshold has a decisive effect on the number of views, and there is a negative correlation between the trust threshold and the number of opinions clusters. The higher the connectivity of the initial activity group, the more easily the subjective opinion in the evolution of opinion to achieve rapid convergence. The more open the network is more conducive to the unity of view, increase and reduce the number of agents will not affect the consistency of the group effect, but not conducive to stability.

  8. Global 4-H Network: Laying the Groundwork for Global Extension Opportunities

    Science.gov (United States)

    Major, Jennifer; Miller, Rhonda

    2012-01-01

    A descriptive study examining 4-H programs in Africa, Asia, and Europe was conducted to provide understanding and direction in the establishment of a Global 4-H Network. Information regarding structure, organizational support, funding, and programming areas was gathered. Programs varied greatly by country, and many partnered with other 4-H…

  9. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    2004-01-01

    It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreases distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law depe...

  10. Energy Efficiency Evaluation of RSVP-TE Extensions for Survivable Translucent WSON Networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2012-01-01

    in communication networks is that connections must be protected against failures. The backup resources are normally connected and powered on, which also contributes to the energy budget. Using Shared Path Protection (SPP) minimizes the protection resources by efficient sharing of wavelengths, regenerators...

  11. Nose Fairing Modeling and Simulation to Support Trident II D5 Lifecycle Extension

    Science.gov (United States)

    2013-09-01

    closure segment impact at time of launch. Changes in the material properties of the model allow for a simulation of aging in the nose fairing to estimate...segment impact at time of launch. Changes in the material properties of the model allow for a simulation of aging in the nose fairing to estimate the...is consistent with standard veneer thicknesses and gives a total thickness of 0.45 inches of wood in the laminate. A final laminate thickness of

  12. A Network Traffic Generator Model for Fast Network-on-Chip Simulation

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael

    2005-01-01

    and effective Network-on-Chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns......For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...

  13. Network Traffic Generator Model for Fast Network-on-Chip Simulation

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Ang, Frederico; Olsen, Rasmus G.

    2008-01-01

    and effective Network-on-Chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns......For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...

  14. Simulation technologies in networking and communications selecting the best tool for the test

    CERN Document Server

    Pathan, Al-Sakib Khan; Khan, Shafiullah

    2014-01-01

    Simulation is a widely used mechanism for validating the theoretical models of networking and communication systems. Although the claims made based on simulations are considered to be reliable, how reliable they really are is best determined with real-world implementation trials.Simulation Technologies in Networking and Communications: Selecting the Best Tool for the Test addresses the spectrum of issues regarding the different mechanisms related to simulation technologies in networking and communications fields. Focusing on the practice of simulation testing instead of the theory, it presents

  15. Using elements of game engine architecture to simulate sensor networks for eldercare.

    Science.gov (United States)

    Godsey, Chad; Skubic, Marjorie

    2009-01-01

    When dealing with a real time sensor network, building test data with a known ground truth is a tedious and cumbersome task. In order to quickly build test data for such a network, a simulation solution is a viable option. Simulation environments have a close relationship with computer game environments, and therefore there is much to be learned from game engine design. In this paper, we present our vision for a simulated in-home sensor network and describe ongoing work on using elements of game engines for building the simulator. Validation results are included to show agreement on motion sensor simulation with the physical environment.

  16. statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data

    Directory of Open Access Journals (Sweden)

    Mark S. Handcock

    2007-12-01

    Full Text Available statnet is a suite of software packages for statistical network analysis. The packages implement recent advances in network modeling based on exponential-family random graph models (ERGM. The components of the package provide a comprehensive framework for ERGM-based network modeling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC algorithm. The coding is optimized for speed and robustness.

  17. Reservoir simulation with MUFITS code: Extension for double porosity reservoirs and flows in horizontal wells

    Science.gov (United States)

    Afanasyev, Andrey

    2017-04-01

    Numerical modelling of multiphase flows in porous medium is necessary in many applications concerning subsurface utilization. An incomplete list of those applications includes oil and gas fields exploration, underground carbon dioxide storage and geothermal energy production. The numerical simulations are conducted using complicated computer programs called reservoir simulators. A robust simulator should include a wide range of modelling options covering various exploration techniques, rock and fluid properties, and geological settings. In this work we present a recent development of new options in MUFITS code [1]. The first option concerns modelling of multiphase flows in double-porosity double-permeability reservoirs. We describe internal representation of reservoir models in MUFITS, which are constructed as a 3D graph of grid blocks, pipe segments, interfaces, etc. In case of double porosity reservoir, two linked nodes of the graph correspond to a grid cell. We simulate the 6th SPE comparative problem [2] and a five-spot geothermal production problem to validate the option. The second option concerns modelling of flows in porous medium coupled with flows in horizontal wells that are represented in the 3D graph as a sequence of pipe segments linked with pipe junctions. The well completions link the pipe segments with reservoir. The hydraulics in the wellbore, i.e. the frictional pressure drop, is calculated in accordance with Haaland's formula. We validate the option against the 7th SPE comparative problem [3]. We acknowledge financial support by the Russian Foundation for Basic Research (project No RFBR-15-31-20585). References [1] Afanasyev, A. MUFITS Reservoir Simulation Software (www.mufits.imec.msu.ru). [2] Firoozabadi A. et al. Sixth SPE Comparative Solution Project: Dual-Porosity Simulators // J. Petrol. Tech. 1990. V.42. N.6. P.710-715. [3] Nghiem L., et al. Seventh SPE Comparative Solution Project: Modelling of Horizontal Wells in Reservoir Simulation

  18. Simulation of one-dimensional blood flow in networks of human vessels using a novel TVD scheme.

    Science.gov (United States)

    Huang, P G; Muller, L O

    2015-05-01

    An extension of a total variation diminishing (TVD) scheme to solve one-dimensional (1D) blood flow for human circulation is proposed. This method is simple as it involves only a few modifications to existing shock-capturing TVD schemes. We have applied the method to a wide range of test cases including a complete simulation of the human vascular network. Excellent solutions have been demonstrated for problems involving varying and discontinuous mechanical properties of blood vessels. For 1D network simulations, the method has been shown to agree well with the reported computational results. Finally, the method has been demonstrated to compare favorably with in vivo experiments set up to study the impact of circle of Willis anomalies on flow patterns in the cerebral arterial system. Copyright © 2015 John Wiley & Sons, Ltd.

  19. The Extension of Wireless Mesh Networks Via Vertical Takeoff and Landing Unmanned Aerial Vehicles

    Science.gov (United States)

    2007-12-01

    Malaysian Maritime Enforcement Agency MOE Measures of Effectiveness MOP Measures of Performance MSL Mean Sea Level xvii NCW Network-centric warfare...real-time to local (Chiang Mai), theater ( Bangkok ), and global (Alameda, California) command and control (C2) centers. This fusion of information...1. 44 b. The Radio Environment Several issues affect the way the radio signal travels from one device to another: Radio energy attenuates

  20. Brain without mind: Computer simulation of neural networks with modifiable neuronal interactions

    Science.gov (United States)

    Clark, John W.; Rafelski, Johann; Winston, Jeffrey V.

    1985-07-01

    Aspects of brain function are examined in terms of a nonlinear dynamical system of highly interconnected neuron-like binary decision elements. The model neurons operate synchronously in discrete time, according to deterministic or probabilistic equations of motion. Plasticity of the nervous system, which underlies such cognitive collective phenomena as adaptive development, learning, and memory, is represented by temporal modification of interneuronal connection strengths depending on momentary or recent neural activity. A formal basis is presented for the construction of local plasticity algorithms, or connection-modification routines, spanning a large class. To build an intuitive understanding of the behavior of discrete-time network models, extensive computer simulations have been carried out (a) for nets with fixed, quasirandom connectivity and (b) for nets with connections that evolve under one or another choice of plasticity algorithm. From the former experiments, insights are gained concerning the spontaneous emergence of order in the form of cyclic modes of neuronal activity. In the course of the latter experiments, a simple plasticity routine (“brainwashing,” or “anti-learning”) was identified which, applied to nets with initially quasirandom connectivity, creates model networks which provide more felicitous starting points for computer experiments on the engramming of content-addressable memories and on learning more generally. The potential relevance of this algorithm to developmental neurobiology and to sleep states is discussed. The model considered is at the same time a synthesis of earlier synchronous neural-network models and an elaboration upon them; accordingly, the present article offers both a focused review of the dynamical properties of such systems and a selection of new findings derived from computer simulation.

  1. Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

    Science.gov (United States)

    Nathan R. De Jager; Patrick J. Drohan; Brian M. Miranda; Brian R. Sturtevant; Susan L. Stout; Alejandro A. Royo; Eric J. Gustafson; Mark C. Romanski

    2017-01-01

    Browsing ungulates alter forest productivity and vegetation succession through selective foraging onspecies that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit...

  2. Preliminary study for a numerical aerodynamic simulation facility. Phase 1: Extension

    Science.gov (United States)

    Lincoln, N. R.

    1978-01-01

    Functional requirements and preliminary design data were identified for use in the design of all system components and in the construction of a facility to perform aerodynamic simulation for airframe design. A skeleton structure of specifications for the flow model processor and monitor, the operating system, and the language and its compiler is presented.

  3. Millimeter-Wave Wireless LAN and Its Extension toward 5G Heterogeneous Networks

    Science.gov (United States)

    Sakaguchi, Kei; Mohamed, Ehab Mahmoud; Kusano, Hideyuki; Mizukami, Makoto; Miyamoto, Shinichi; Rezagah, Roya E.; Takinami, Koji; Takahashi, Kazuaki; Shirakata, Naganori; Peng, Hailan; Yamamoto, Toshiaki; Nanba, Shinobu

    Millimeter-wave (mmw) frequency bands, especially 60 GHz unlicensed band, are considered as a promising solution for gigabit short range wireless communication systems. IEEE standard 802.11ad, also known as WiGig, is standardized for the usage of the 60 GHz unlicensed band for wireless local area networks (WLANs). By using this mmw WLAN, multi-Gbps rate can be achieved to support bandwidth-intensive multimedia applications. Exhaustive search along with beamforming (BF) is usually used to overcome 60 GHz channel propagation loss and accomplish data transmissions in such mmw WLANs. Because of its short range transmission with a high susceptibility to path blocking, multiple number of mmw access points (APs) should be used to fully cover a typical target environment for future high capacity multi-Gbps WLANs. Therefore, coordination among mmw APs is highly needed to overcome packet collisions resulting from un-coordinated exhaustive search BF and to increase the total capacity of mmw WLANs. In this paper, we firstly give the current status of mmw WLANs with our developed WiGig AP prototype. Then, we highlight the great need for coordinated transmissions among mmw APs as a key enabler for future high capacity mmw WLANs. Two different types of coordinated mmw WLAN architecture are introduced. One is the distributed antenna type architecture to realize centralized coordination, while the other is an autonomous coordination with the assistance of legacy Wi-Fi signaling. Moreover, two heterogeneous network (HetNet) architectures are also introduced to efficiently extend the coordinated mmw WLANs to be used for future 5th Generation (5G) cellular networks.

  4. Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON.

    Science.gov (United States)

    Lytton, William W; Seidenstein, Alexandra H; Dura-Bernal, Salvador; McDougal, Robert A; Schürmann, Felix; Hines, Michael L

    2016-10-01

    Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256). We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin-Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment.

  5. Discrimination of Cylinders with Different Wall Thicknesses using Neural Networks and Simulated Dolphin Sonar Signals

    DEFF Research Database (Denmark)

    Andersen, Lars Nonboe; Au, Whitlow; Larsen, Jan

    1999-01-01

    This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness...

  6. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreses distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law......, and it is shown that while they allow for more flexibility in design and construction of structures supporting topological routing, their performances are comparable to the performance of the perfect square mesh. Finally suggestions for further research within the field are given....

  7. The extension of the Greek railway network, exemplified by the Athens - Thessaloniki route electrification; Der Ausbau des griechischen Eisenbahnnetzes am Beispiel der Elektrifizierung Athen - Thessaloniki

    Energy Technology Data Exchange (ETDEWEB)

    Protopappas, I. [ERGA OSE S.A., Railway System Directorate, Athens (Greece); Klinge, R.R. [Lahmeyer International GmbH, Athens (Greece). Branch Office Greece; Albert, R. [Lahmeyer International GmbH, Bad Vilbel (Germany). Geschaeftsbereich Transport

    2005-07-01

    An extended European high-speed route network will be implemented by 2020, with the extension of the Greek railway network playing an essential part. Various railway infrastructure improvement measures will be taken, and important routes will be electrified. Principal technical parameters of the overhead line, substations and SCADA system are given, and the project implementation is described. (orig.)

  8. Extension of life span by impaired glucose metabolism in Caenorhabditis elegans is accompanied by structural rearrangements of the transcriptomic network.

    Directory of Open Access Journals (Sweden)

    Steffen Priebe

    Full Text Available Glucose restriction mimicked by feeding the roundworm Caenorhabditis elegans with 2-deoxy-D-glucose (DOG - a glucose molecule that lacks the ability to undergo glycolysis - has been found to increase the life span of the nematodes considerably. To facilitate understanding of the molecular mechanisms behind this life extension, we analyzed transcriptomes of DOG-treated and untreated roundworms obtained by RNA-seq at different ages. We found that, depending on age, DOG changes the magnitude of the expression values of about 2 to 24 percent of the genes significantly, although our results reveal that the gross changes introduced by DOG are small compared to the age-induced changes. We found that 27 genes are constantly either up- or down-regulated by DOG over the whole life span, among them several members of the cytochrome P450 family. The monotonic change with age of the temporal expression patterns of the genes was investigated, leading to the result that 21 genes reverse their monotonic behaviour under impaired glycolysis. Put simply, the DOG-treatment reduces the gross transcriptional activity but increases the interconnectedness of gene expression. However, a detailed analysis of network parameters discloses that the introduced changes differ remarkably between individual signalling pathways. We found a reorganization of the hubs of the mTOR pathway when standard diet is replaced by DOG feeding. By constructing correlation based difference networks, we identified those signalling pathways that are most vigorously changed by impaired glycolysis. Taken together, we have found a number of genes and pathways that are potentially involved in the DOG-driven extension of life span of C. elegans. Furthermore, our results demonstrate how the network structure of ageing-relevant signalling pathways is reorganised under impaired glycolysis.

  9. Unified Approach to Modeling and Simulation of Space Communication Networks and Systems

    Science.gov (United States)

    Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth

    2010-01-01

    Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks

  10. Changes in support networks in late middle age: the extension of gender and educational differences.

    Science.gov (United States)

    Fischer, Claude S; Beresford, Lauren

    2015-01-01

    This paper tests whether differences by gender and by educational attainment in contact with friends and family and in support expected from friends and family narrow or widen in late middle age. The data are drawn from about 4,800 members of the Wisconsin Longitudinal Survey who answered questions about their frequency of contact with social ties and expectations of 3 kinds of help in both 1993, when they were in their early 50s, and again in 2004. Using lagged dependent variable models, we find that between their 50s and 60s women's network advantages over men and college graduates' network advantages over high school graduates in frequency of social contact widened. The same was roughly true as well for expectations of social support, although here the divergences depended partly on the type of the support: Women gained relative to men in "talk" support and in help from nonkin if ill, but lost ground in financial support. The college-educated gained ground in all sorts of support from nonkin. These results reinforce concern that late middle age is a period when men and the less educated become yet more disadvantaged in social support, making attention to connectedness yet more critical. © The Author 2014. 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.

  11. Understanding the Dynamics of MOOC Discussion Forums with Simulation Investigation for Empirical Network Analysis (SIENA)

    Science.gov (United States)

    Zhang, Jingjing; Skryabin, Maxim; Song, Xiongwei

    2016-01-01

    This study attempts to make inferences about the mechanisms that drive network change over time. It adopts simulation investigation for empirical network analysis to examine the patterns and evolution of relationships formed in the context of a massive open online course (MOOC) discussion forum. Four network effects--"homophily,"…

  12. Linking Simulation with Formal Verification and Modeling of Wireless Sensor Network in TLA+

    Science.gov (United States)

    Martyna, Jerzy

    In this paper, we present the results of the simulation of a wireless sensor network based on the flooding technique and SPIN protocols. The wireless sensor network was specified and verified by means of the TLA+ specification language [1]. For a model of wireless sensor network built this way simulation was carried with the help of specially constructed software tools. The obtained results allow us to predict the behaviour of the wireless sensor network in various topologies and spatial densities. Visualization of the output data enable precise examination of some phenomenas in wireless sensor networks, such as a hidden terminal, etc.

  13. Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

    Directory of Open Access Journals (Sweden)

    Diogo Santos

    2016-06-01

    Full Text Available Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO - Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models - particularly for the case of the Porto urban network, in Portugal. With this goal in mind, a comparison between different altitude information retrieval approaches is made and a simple tool to annotate network models with altitude data is proposed. The work starts by describing the methodological approach followed during research and development, then describing and analysing its main findings. This description includes an in-depth explanation of the proposed tool. Lastly, this work reviews some related work to the subject.

  14. Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.

    Directory of Open Access Journals (Sweden)

    Zsófia Kallus

    Full Text Available Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.

  15. Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.

    Science.gov (United States)

    Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

    2015-01-01

    Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.

  16. Molecular Dynamics Simulations of Polymer Networks Undergoing Sequential Cross-Linking and Scission Reactions

    DEFF Research Database (Denmark)

    Rottach, Dana R.; Curro, John G.; Budzien, Joanne

    2007-01-01

    The effects of sequential cross-linking and scission of polymer networks formed in two states of strain are investigated using molecular dynamics simulations. Two-stage networks are studied in which a network formed in the unstrained state (stage 1) undergoes additional cross-linking in a uniaxia......The effects of sequential cross-linking and scission of polymer networks formed in two states of strain are investigated using molecular dynamics simulations. Two-stage networks are studied in which a network formed in the unstrained state (stage 1) undergoes additional cross......, a fraction (quantified by the stress transfer function ) of the second-stage cross-links contribute to the effective first-stage cross-link density. The stress transfer functions extracted from the MD simulations of the reacting networks are found to be in very...

  17. Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Stochastic reaction networks (SRNs) is a class of continuous-time Markov chains intended to describe, from the kinetic point of view, the time-evolution of chemical systems in which molecules of different chemical species undergo a finite set of reaction channels. This talk is based on articles [4, 5, 6], where we are interested in the following problem: given a SRN, X, defined though its set of reaction channels, and its initial state, x0, estimate E (g(X(T))); that is, the expected value of a scalar observable, g, of the process, X, at a fixed time, T. This problem lead us to define a series of Monte Carlo estimators, M, such that, with high probability can produce values close to the quantity of interest, E (g(X(T))). More specifically, given a user-selected tolerance, TOL, and a small confidence level, η, find an estimator, M, based on approximate sampled paths of X, such that, P (|E (g(X(T))) − M| ≤ TOL) ≥ 1 − η; even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.

  18. Interaction prediction between groundwater and quarry extension using discrete choice models and artificial neural networks

    CERN Document Server

    Barthélemy, Johan; Collier, Louise; Hallet, Vincent; Moriamé, Marie; Sartenaer, Annick

    2016-01-01

    Groundwater and rock are intensively exploited in the world. When a quarry is deepened the water table of the exploited geological formation might be reached. A dewatering system is therefore installed so that the quarry activities can continue, possibly impacting the nearby water catchments. In order to recommend an adequate feasibility study before deepening a quarry, we propose two interaction indices between extractive activity and groundwater resources based on hazard and vulnerability parameters used in the assessment of natural hazards. The levels of each index (low, medium, high, very high) correspond to the potential impact of the quarry on the regional hydrogeology. The first index is based on a discrete choice modelling methodology while the second is relying on an artificial neural network. It is shown that these two complementary approaches (the former being probabilistic while the latter fully deterministic) are able to predict accurately the level of interaction. Their use is finally illustrate...

  19. Queueing Models and Stability of Message Flows in Distributed Simulators of Open Queueing Networks

    OpenAIRE

    Gupta, Manish; Kumar, Anurag; Shorey, Rajeev

    1996-01-01

    In this paper we study message flow processes in distributed simulators of open queueing networks. We develop and study queueing models for distributed simulators with maximum lookahead sequencing. We characterize the external arrival process, and the message feedback process in the simulator of a simple queueing network with feedback. We show that a certain natural modelling construct for the arrival process is exactly correct, whereas an obvious model for the feedback process is wrong; we t...

  20. Origin of an extensive network of non-tectonic synclines in Eocene limestones of the Western Desert, Egypt

    Science.gov (United States)

    Tewksbury, Barbara J.; Tarabees, Elhamy A.; Mehrtens, Charlotte J.

    2017-12-01

    Satellite images of the Western Desert of Egypt display conspicuous sinuous color patterning that previous workers have interpreted as erosional flutes formed by catastrophic flooding. Our work with high resolution satellite imagery shows that the patterning is not erosional but, rather, the result of a network of thousands of narrow synclines in the Eocene bedrock capping the Limestone Plateau. Synclines form as isolated, 200-400 meter-wide downwarps in otherwise flat-lying strata. Limb dips are shallow, and doubly plunging hinges form multiple basin closures along syncline lengths. Anticlines form ;accidentally; in inter-syncline areas where two adjacent synclines lie close together. Synclines have two dominant orientations, WNW-ESE and NNW-SSE, parallel to two prominent joint and fault sets, and synclines branch, merge, and change orientation along their lengths. Synclines are all at the same scale with neither larger structures nor parasitic structures and are best described as non-tectonic sag synclines. An Egypt-wide inventory reveals that these synclines are both confined to Eocene limestones and developed, albeit it sporadically, over nearly 100,000 km2. The syncline network predates plateau gravels of the Katkut Formation, which have been interpreted as Oligocene or early Miocene in age, and the network is cut by faults related to Western Desert extension associated with Red Sea rifting. The mechanism that caused sag of overlying layers is not clear. Modern karst collapse, subsurface dissolution of evaporites, and collapse of paleokarst are all unlikely mechanisms given the timing of formation and the underlying stratigraphy. Silica diagenesis and downslope mobilization of underlying shales are possibilities, although uncertainty about the origin of silica in the limestones, plus the consistency of syncline orientations over large areas, make these models problematic. Hypogene karst, perhaps related to aggressive fluids associated with basaltic intrusions

  1. Analysis and extension of the Furter equation, and its application in the simulation of saline extractive distillation columns

    Directory of Open Access Journals (Sweden)

    Ernesto O. Timmermann

    Full Text Available ABSTRACT Simulation of saline extractive distillation columns is a difficult task owing to the high nonlinearity of the rigorous models that represent these systems. The use of simple models to obtain initial estimates of equilibrium compositions may improve the stability and rate of convergence. One of the simplest models to study the vapor-liquid equilibrium of binary liquid mixtures + salt systems is the Furter equation. This model was analyzed in the present work by means of the incorporation of activity coefficient models in the ratio of relative volatility. This approach allowed systematic extensions of the Furter equation and a brief review of the theoretical basis of the original equation. As a result of these extensions, two simple equations were proposed and tested with experimental data from 20 systems, including binary liquid mixtures + salt systems and binary liquid mixtures + ionic liquid systems. Finally, one of these proposed equations was incorporated into the GKTM software in order to assess the utility of these simple models in the simulation of saline extractive distillation columns. The obtained results showed a significant improvement over the previous algorithm.

  2. Imagining the future: The core episodic simulation network dissociates as a function of timecourse and the amount of simulated information.

    Science.gov (United States)

    Thakral, Preston P; Benoit, Roland G; Schacter, Daniel L

    2017-05-01

    Neuroimaging data indicate that episodic memory (i.e., remembering specific past experiences) and episodic simulation (i.e., imagining specific future experiences) are associated with enhanced activity in a common set of neural regions, often referred to as the core network. This network comprises the hippocampus, parahippocampal cortex, lateral and medial parietal cortex, lateral temporal cortex, and medial prefrontal cortex. Evidence for a core network has been taken as support for the idea that episodic memory and episodic simulation are supported by common processes. Much remains to be learned about how specific core network regions contribute to specific aspects of episodic simulation. Prior neuroimaging studies of episodic memory indicate that certain regions within the core network are differentially sensitive to the amount of information recollected (e.g., the left lateral parietal cortex). In addition, certain core network regions dissociate as a function of their timecourse of engagement during episodic memory (e.g., transient activity in the posterior hippocampus and sustained activity in the left lateral parietal cortex). In the current study, we assessed whether similar dissociations could be observed during episodic simulation. We found that the left lateral parietal cortex modulates as a function of the amount of simulated details. Of particular interest, while the hippocampus was insensitive to the amount of simulated details, we observed a temporal dissociation within the hippocampus: transient activity occurred in relatively posterior portions of the hippocampus and sustained activity occurred in anterior portions. Because the posterior hippocampal and lateral parietal findings parallel those observed during episodic memory, the present results add to the evidence that episodic memory and episodic simulation are supported by common processes. Critically, the present study also provides evidence that regions within the core network support

  3. A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors.

    Science.gov (United States)

    Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L; Nicolau, Alex; Veidenbaum, Alexander V

    2009-01-01

    Neural network simulators that take into account the spiking behavior of neurons are useful for studying brain mechanisms and for various neural engineering applications. Spiking Neural Network (SNN) simulators have been traditionally simulated on large-scale clusters, super-computers, or on dedicated hardware architectures. Alternatively, Compute Unified Device Architecture (CUDA) Graphics Processing Units (GPUs) can provide a low-cost, programmable, and high-performance computing platform for simulation of SNNs. In this paper we demonstrate an efficient, biologically realistic, large-scale SNN simulator that runs on a single GPU. The SNN model includes Izhikevich spiking neurons, detailed models of synaptic plasticity and variable axonal delay. We allow user-defined configuration of the GPU-SNN model by means of a high-level programming interface written in C++ but similar to the PyNN programming interface specification. PyNN is a common programming interface developed by the neuronal simulation community to allow a single script to run on various simulators. The GPU implementation (on NVIDIA GTX-280 with 1 GB of memory) is up to 26 times faster than a CPU version for the simulation of 100K neurons with 50 Million synaptic connections, firing at an average rate of 7 Hz. For simulation of 10 Million synaptic connections and 100K neurons, the GPU SNN model is only 1.5 times slower than real-time. Further, we present a collection of new techniques related to parallelism extraction, mapping of irregular communication, and network representation for effective simulation of SNNs on GPUs. The fidelity of the simulation results was validated on CPU simulations using firing rate, synaptic weight distribution, and inter-spike interval analysis. Our simulator is publicly available to the modeling community so that researchers will have easy access to large-scale SNN simulations.

  4. Rational Extension of the Ribosome Biogenesis Pathway Using Network-Guided Genetics

    Science.gov (United States)

    Li, Zhihua; Lee, Insuk; Moradi, Emily; Hung, Nai-Jung; Johnson, Arlen W.; Marcotte, Edward M.

    2009-01-01

    Biogenesis of ribosomes is an essential cellular process conserved across all eukaryotes and is known to require >170 genes for the assembly, modification, and trafficking of ribosome components through multiple cellular compartments. Despite intensive study, this pathway likely involves many additional genes. Here, we employ network-guided genetics—an approach for associating candidate genes with biological processes that capitalizes on recent advances in functional genomic and proteomic studies—to computationally identify additional ribosomal biogenesis genes. We experimentally evaluated >100 candidate yeast genes in a battery of assays, confirming involvement of at least 15 new genes, including previously uncharacterized genes (YDL063C, YIL091C, YOR287C, YOR006C/TSR3, YOL022C/TSR4). We associate the new genes with specific aspects of ribosomal subunit maturation, ribosomal particle association, and ribosomal subunit nuclear export, and we identify genes specifically required for the processing of 5S, 7S, 20S, 27S, and 35S rRNAs. These results reveal new connections between ribosome biogenesis and mRNA splicing and add >10% new genes—most with human orthologs—to the biogenesis pathway, significantly extending our understanding of a universally conserved eukaryotic process. PMID:19806183

  5. Rational extension of the ribosome biogenesis pathway using network-guided genetics.

    Directory of Open Access Journals (Sweden)

    Zhihua Li

    2009-10-01

    Full Text Available Biogenesis of ribosomes is an essential cellular process conserved across all eukaryotes and is known to require >170 genes for the assembly, modification, and trafficking of ribosome components through multiple cellular compartments. Despite intensive study, this pathway likely involves many additional genes. Here, we employ network-guided genetics-an approach for associating candidate genes with biological processes that capitalizes on recent advances in functional genomic and proteomic studies-to computationally identify additional ribosomal biogenesis genes. We experimentally evaluated >100 candidate yeast genes in a battery of assays, confirming involvement of at least 15 new genes, including previously uncharacterized genes (YDL063C, YIL091C, YOR287C, YOR006C/TSR3, YOL022C/TSR4. We associate the new genes with specific aspects of ribosomal subunit maturation, ribosomal particle association, and ribosomal subunit nuclear export, and we identify genes specifically required for the processing of 5S, 7S, 20S, 27S, and 35S rRNAs. These results reveal new connections between ribosome biogenesis and mRNA splicing and add >10% new genes-most with human orthologs-to the biogenesis pathway, significantly extending our understanding of a universally conserved eukaryotic process.

  6. 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....

  7. Stochastic simulation of HIV population dynamics through complex network modelling

    NARCIS (Netherlands)

    Sloot, P. M. A.; Ivanov, S. V.; Boukhanovsky, A. V.; van de Vijver, D. A. M. C.; Boucher, C. A. B.

    We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and

  8. Stochastic simulation of HIV population dynamics through complex network modelling

    NARCIS (Netherlands)

    Sloot, P.M.A.; Ivanov, S.V.; Boukhanovsky, A.V.; van de Vijver, D.A.M.C.; Boucher, C.A.B.

    2008-01-01

    We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and

  9. Validation of Mobility Simulations via Measurement Drive Tests in an Operational Network

    DEFF Research Database (Denmark)

    Gimenez, Lucas Chavarria; Barbera, Simone; Polignano, Michele

    2015-01-01

    Simulations play a key role in validating new concepts in cellular networks, since most of the features proposed and introduced into the standards are typically first studied by means of simulations. In order to increase the trustworthiness of the simulation results, proper models and settings must...... to reality. The presented study is based on drive tests measurements and explicit simulations of an operator network in the city of Aalborg (Denmark) – modelling a real 3D environment and using a commonly accepted dynamic system level simulation methodology. In short, the presented results show...

  10. Extension of the Viscous Collision Limiting Direct Simulation Monte Carlo Technique to Multiple Species

    Science.gov (United States)

    Liechty, Derek S.; Burt, Jonathan M.

    2016-01-01

    There are many flows fields that span a wide range of length scales where regions of both rarefied and continuum flow exist and neither direct simulation Monte Carlo (DSMC) nor computational fluid dynamics (CFD) provide the appropriate solution everywhere. Recently, a new viscous collision limited (VCL) DSMC technique was proposed to incorporate effects of physical diffusion into collision limiter calculations to make the low Knudsen number regime normally limited to CFD more tractable for an all-particle technique. This original work had been derived for a single species gas. The current work extends the VCL-DSMC technique to gases with multiple species. Similar derivations were performed to equate numerical and physical transport coefficients. However, a more rigorous treatment of determining the mixture viscosity is applied. In the original work, consideration was given to internal energy non-equilibrium, and this is also extended in the current work to chemical non-equilibrium.

  11. ns-2 extension to simulate localization system in wireless sensor networks

    CSIR Research Space (South Africa)

    Abu-Mahfouz, Adnan M

    2011-09-01

    Full Text Available the entire structure is presented for the sake of completeness, not all the classes and files need to be modified to implement a new scheme. Only the classes and files shaded in yellow in Fig. 1, Fig. 2 and Fig. 3 need to be customized. Fig. 1 shows... command ?set lreq [new Agent/LocRec]? will create a new object of class LocReqAgent. A. Class Hierarchy The Doxygen documentation system [13] was used to illustrate the class hierarchy of the new classes as shown in Fig. 2. For the sake...

  12. How Crime Spreads Through Imitation in Social Networks: A Simulation Model

    Science.gov (United States)

    Punzo, Valentina

    In this chapter an agent-based model for investigating how crime spreads through social networks is presented. Some theoretical issues related to the sociological explanation of crime are tested through simulation. The agent-based simulation allows us to investigate the relative impact of some mechanisms of social influence on crime, within a set of controlled simulated experiments.

  13. Experimental Evaluation of Simulation Abstractions for Wireless Sensor Network MAC Protocols

    NARCIS (Netherlands)

    Halkes, G.P.; Langendoen, K.G.

    2010-01-01

    The evaluation ofMAC protocols forWireless Sensor Networks (WSNs) is often performed through simulation. These simulations necessarily abstract away from reality inmany ways. However, the impact of these abstractions on the results of the simulations has received only limited attention. Moreover,

  14. Hybrid Network Simulation for the ATLAS Trigger and Data Acquisition (TDAQ) System

    CERN Document Server

    Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel; Foguelman, Daniel Jacob

    2015-01-01

    The poster shows the ongoing research in the ATLAS TDAQ group in collaboration with the University of Buenos Aires in the area of hybrid data network simulations. he Data Network and Processing Cluster filters data in real-time, achieving a rejection factor in the order of 40000x and has real-time latency constrains. The dataflow between the processing units (TPUs) and Readout System (ROS) presents a “TCP Incast”-type network pathology which TCP cannot handle it efficiently. A credits system is in place which limits rate of queries and reduces latency. This large computer network, and the complex dataflow has been modelled and simulated using a PowerDEVS, a DEVS-based simulator. The simulation has been validated and used to produce what-if scenarios in the real network. Network Simulation with Hybrid Flows: Speedups and accuracy, combined • For intensive network traffic, Discrete Event simulation models (packet-level granularity) soon becomes prohibitive: Too high computing demands. • Fluid Flow simul...

  15. Insights and issues with simulating terrestrial DOC loading of Arctic river networks

    Science.gov (United States)

    Kicklighter, David W.; Hayes, Daniel J.; McClelland, James W.; Peterson, Bruce J.; McGuire, A. David; Melillo, Jerry M.

    2013-01-01

    Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.

  16. POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

    Energy Technology Data Exchange (ETDEWEB)

    Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

    2016-03-01

    This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

  17. Modulation of neuroblastoma disease pathogenesis by an extensive network of epigenetically regulated microRNAs.

    Science.gov (United States)

    Das, S; Bryan, K; Buckley, P G; Piskareva, O; Bray, I M; Foley, N; Ryan, J; Lynch, J; Creevey, L; Fay, J; Prenter, S; Koster, J; van Sluis, P; Versteeg, R; Eggert, A; Schulte, J H; Schramm, A; Mestdagh, P; Vandesompele, J; Speleman, F; Stallings, R L

    2013-06-13

    RNA epigenome and identify a remarkable network of miRNA/mRNA interactions that significantly contribute to neuroblastoma disease pathogenesis.

  18. Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

    Science.gov (United States)

    Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

    2017-01-01

    Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

  19. Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

    Directory of Open Access Journals (Sweden)

    Henry D Priest

    Full Text Available Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

  20. On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues.

    Science.gov (United States)

    Wang, Wei; Huang, Li; Liang, Xuedong

    2018-01-06

    This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks' statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies.

  1. The role of simulation in the design of a neural network chip

    Science.gov (United States)

    Desai, Utpal; Roppel, Thaddeus A.; Padgett, Mary L.

    1993-01-01

    An iterative, simulation-based design procedure for a neural network chip is introduced. For this design procedure, the goal is to produce a chip layout for a neural network in which the weights are determined by transistor gate width-to-length ratios. In a given iteration, the current layout is simulated using the circuit simulator SPICE, and layout adjustments are made based on conventional gradient-decent methods. After the iteration converges, the chip is fabricated. Monte Carlo analysis is used to predict the effect of statistical fabrication process variations on the overall performance of the neural network chip.

  2. Simulation of Foam Divot Weight on External Tank Utilizing Least Squares and Neural Network Methods

    Science.gov (United States)

    Chamis, Christos C.; Coroneos, Rula M.

    2007-01-01

    Simulation of divot weight in the insulating foam, associated with the external tank of the U.S. space shuttle, has been evaluated using least squares and neural network concepts. The simulation required models based on fundamental considerations that can be used to predict under what conditions voids form, the size of the voids, and subsequent divot ejection mechanisms. The quadratic neural networks were found to be satisfactory for the simulation of foam divot weight in various tests associated with the external tank. Both linear least squares method and the nonlinear neural network predicted identical results.

  3. CoSimulating Communication Networks and Electrical System for Performance Evaluation in Smart Grid

    Directory of Open Access Journals (Sweden)

    Hwantae Kim

    2018-01-01

    Full Text Available In smart grid research domain, simulation study is the first choice, since the analytic complexity is too high and constructing a testbed is very expensive. However, since communication infrastructure and the power grid are tightly coupled with each other in the smart grid, a well-defined combination of simulation tools for the systems is required for the simulation study. Therefore, in this paper, we propose a cosimulation work called OOCoSim, which consists of OPNET (network simulation tool and OpenDSS (power system simulation tool. By employing the simulation tool, an organic and dynamic cosimulation can be realized since both simulators operate on the same computing platform and provide external interfaces through which the simulation can be managed dynamically. In this paper, we provide OOCoSim design principles including a synchronization scheme and detailed descriptions of its implementation. To present the effectiveness of OOCoSim, we define a smart grid application model and conduct a simulation study to see the impact of the defined application and the underlying network system on the distribution system. The simulation results show that the proposed OOCoSim can successfully simulate the integrated scenario of the power and network systems and produce the accurate effects of the networked control in the smart grid.

  4. Feasibility study for a generalized gate logic software simulator

    Science.gov (United States)

    Mcgough, J. G.

    1983-01-01

    Unit-delay simulation, event driven simulation, zero-delay simulation, simulation techniques, 2-valued versus multivalued logic, network initialization, gate operations and alternate network representations, parallel versus serial mode simulation fault modelling, extension of multiprocessor systems, and simulation timing are discussed. Functional level networks, gate equivalent circuits, the prototype BDX-930 network model, fault models, identifying detected faults for BGLOSS are discussed. Preprocessor tasks, postprocessor tasks, executive tasks, and a library of bliss coded macros for GGLOSS are also discussed.

  5. Reproducing and Extending Real Testbed Evaluation of GeoNetworking Implementation in Simulated Networks

    OpenAIRE

    Tao, Ye; Tsukada, Manabu; LI, Xin; Kakiuchi, Masatoshi; Esaki, Hiroshi

    2016-01-01

    International audience; Vehicular Ad-hoc Network (VANET) is a type of Mobile Ad-hoc Network (MANET) which is specialized for vehicle communication. GeoNetworking is a new standardized network layer protocol for VANET which employs geolocation based routing. However, conducting large scale experiments in GeoNetworking softwares is extremely difficult, since it requires many extra factors such as vehicles, stuff, place, terrain, etc. In this paper, we propose a method to reproduce realistic res...

  6. Credibility and validation of simulation models for tactical IP networks

    NARCIS (Netherlands)

    Boltjes, B.; Thiele, F.; Diaz, I.F.

    2007-01-01

    The task of TNO is to provide predictions of the scalability and performance of the new all-IP tactical networks of the Royal Netherlands Army (RNLA) that are likely to be fielded. The inherent properties of fielded tactical networks, such as low bandwidth and Quality of Service (QoS) policies

  7. Evaluation and Simulation of Common Video Conference Traffics in Communication Networks

    Directory of Open Access Journals (Sweden)

    Farhad faghani

    2014-01-01

    Full Text Available Multimedia traffics are the basic traffics in data communication networks. Especially Video conferences are the most desirable traffics in huge networks(wired, wireless, …. Traffic modeling can help us to evaluate the real networks. So, in order to have good services in data communication networks which provide multimedia services, QoS will be very important .In this research we tried to have an exact traffic model design and simulation to overcome QoS challenges. Also, we predict bandwidth by Kalman filter in Ethernet networks.

  8. Permanent Set of Cross-Linking Networks: Comparison of Theory with Molecular Dynamics Simulations

    DEFF Research Database (Denmark)

    Rottach, Dana R.; Curro, John G.; Budzien, Joanne

    2006-01-01

    The permanent set of cross-linking networks is studied by molecular dynamics. The uniaxial stress for a bead-spring polymer network is investigated as a function of strain and cross-link density history, where cross-links are introduced in unstrained and strained networks. The permanent set...... is found from the strain of the network after it returns to the state-of-ease where the stress is zero. The permanent set simulations are compared with theory using the independent network hypothesis, together with the various theoretical rubber elasticity theories: affine, phantom, constrained junction...

  9. 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.

  10. Simulation of mixed switched-capacitor/digital networks with signal-driven switches

    Science.gov (United States)

    Suyama, Ken; Tsividis, Yannis P.; Fang, San-Chin

    1990-12-01

    The simulation of mixed switched-capacitor/digital (SC/D) networks containing capacitors, independent and linear-dependent voltage sources, switches controlled either by periodic or nonperiodic Boolean signals, latched comparators, and logic gates is considered. A unified linear switched-capacitor network (SCN) and mixed SC/D network simulator, SWITCAP2, and its applications to several widely used and novel nonlinear SCNs are discussed. The switches may be controlled by periodic waveforms and by nonperiodic waveforms from the outputs of comparators and logic gates. The signal-dependent modification of network topology through the comparators, logic gates, and signal-driven switches makes the modeling of various nonlinear switched-capacitor circuits possible. Simulation results for a pulse-code modulation (PCM) voice encoder, a sigma-delta modulator, a neural network, and a phase-locked loop (PLL) are presented to demonstrate the flexibility of the approach.

  11. Enterprise Networks for Competences Exchange: A Simulation Model

    Science.gov (United States)

    Remondino, Marco; Pironti, Marco; Pisano, Paola

    A business process is a set of logically related tasks performed to achieve a defined business and related to improving organizational processes. Process innovation can happen at various levels: incrementally, redesign of existing processes, new processes. The knowledge behind process innovation can be shared, acquired, changed and increased by the enterprises inside a network. An enterprise can decide to exploit innovative processes it owns, thus potentially gaining competitive advantage, but risking, in turn, that other players could reach the same technological levels. Or it could decide to share it, in exchange for other competencies or money. These activities could be the basis for a network formation and/or impact the topology of an existing network. In this work an agent based model is introduced (E3), aiming to explore how a process innovation can facilitate network formation, affect its topology, induce new players to enter the market and spread onto the network by being shared or developed by new players.

  12. Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks

    Science.gov (United States)

    Vestergaard, Christian L.; Génois, Mathieu

    2015-01-01

    Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling. PMID:26517860

  13. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

    National Research Council Canada - National Science Library

    Cheung, Kit; Schultz, Simon R; Luk, Wayne

    2015-01-01

    NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs...

  14. Accelerated Gillespie Algorithm for Gas–Grain Reaction Network Simulations Using Quasi-steady-state Assumption

    Science.gov (United States)

    Chang, Qiang; Lu, Yang; Quan, Donghui

    2017-12-01

    Although the Gillespie algorithm is accurate in simulating gas–grain reaction networks, so far its computational cost is so expensive that it cannot be used to simulate chemical reaction networks that include molecular hydrogen accretion or the chemical evolution of protoplanetary disks. We present an accelerated Gillespie algorithm that is based on a quasi-steady-state assumption with the further approximation that the population distribution of transient species depends only on the accretion and desorption processes. The new algorithm is tested against a few reaction networks that are simulated by the regular Gillespie algorithm. We found that the less likely it is that transient species are formed and destroyed on grain surfaces, the more accurate the new method is. We also apply the new method to simulate reaction networks that include molecular hydrogen accretion. The results show that surface chemical reactions involving molecular hydrogen are not important for the production of surface species under standard physical conditions of dense molecular clouds.

  15. ABCDecision: A Simulation Platform for Access Selection Algorithms in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Guy Pujolle

    2010-01-01

    Full Text Available We present a simulation platform for access selection algorithms in heterogeneous wireless networks, called “ABCDecision”. The simulator implements the different parts of an Always Best Connected (ABC system, including Access Technology Selector (ATS, Radio Access Networks (RANs, and users. After describing the architecture of the simulator, we show an overview of the existing decision algorithms for access selection. Then we propose a new selection algorithm in heterogeneous networks and we run a set of simulations to evaluate the performance of the proposed algorithm in comparison with the existing ones. The performance results, in terms of the occupancy rate, show that our algorithm achieves a load balancing distribution between networks by taking into consideration the capacities of the available cells.

  16. An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network.

    Science.gov (United States)

    Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong

    2016-01-01

    As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

  17. An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network.

    Directory of Open Access Journals (Sweden)

    Wen Zhou

    Full Text Available As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

  18. An introduction to network modeling and simulation for the practicing engineer

    CERN Document Server

    Burbank, Jack; Ward, Jon

    2011-01-01

    This book provides the practicing engineer with a concise listing of commercial and open-source modeling and simulation tools currently available including examples of implementing those tools for solving specific Modeling and Simulation examples. Instead of focusing on the underlying theory of Modeling and Simulation and fundamental building blocks for custom simulations, this book compares platforms used in practice, and gives rules enabling the practicing engineer to utilize available Modeling and Simulation tools. This book will contain insights regarding common pitfalls in network Modeling and Simulation and practical methods for working engineers.

  19. Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

    DEFF Research Database (Denmark)

    Christiansen, Niels H.; Voie, Per Erlend Torbergsen; Winther, Ole

    2014-01-01

    platform is designed and tested. The purpose of setting up the network is to reduce calculation time in a fatigue life analysis. Therefore, the networks trained on different error functions are compared with respect to accuracy of rain flow counts of stress cycles over a number of time series simulations......Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure...... for regression is the mean square error. This paper looks into the possibility of improving the performance of neural networks by selecting or defining error functions that are tailor-made for a specific objective. A neural network trained to simulate tension forces in an anchor chain on a floating offshore...

  20. Application of Neural Network and Simulation Modeling to Evaluate Russian Banks’ Performance

    OpenAIRE

    Sharma, Satish; Shebalkov, Mikhail

    2013-01-01

    This paper presents an application of neural network and simulation modeling to analyze and predict the performance of 883 Russian Banks over the period 2000-2010. Correlation analysis was performed to obtain key financial indicators which reflect the leverage, liquidity, profitability and size of Banks. Neural network was trained over the entire dataset, and then simulation modeling was performed generating values which are distributed with Largest Extreme Value and Loglogistic distributions...

  1. FNCS: A Framework for Power System and Communication Networks Co-Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Ciraci, Selim; Daily, Jeffrey A.; Fuller, Jason C.; Fisher, Andrew R.; Marinovici, Laurentiu D.; Agarwal, Khushbu

    2014-04-13

    This paper describes the Fenix framework that uses a federated approach for integrating power grid and communication network simulators. Compared existing approaches, Fenix al- lows co-simulation of both transmission and distribution level power grid simulators with the communication network sim- ulator. To reduce the performance overhead of time synchro- nization, Fenix utilizes optimistic synchronization strategies that make speculative decisions about when the simulators are going to exchange messages. GridLAB-D (a distribution simulator), PowerFlow (a transmission simulator), and ns-3 (a telecommunication simulator) are integrated with the frame- work and are used to illustrate the enhanced performance pro- vided by speculative multi-threading on a smart grid applica- tion. Our speculative multi-threading approach achieved on average 20% improvement over the existing synchronization methods

  2. Less Developed Countries Energy System Network Simulator, LDC-ESNS: a brief description

    Energy Technology Data Exchange (ETDEWEB)

    Reisman, A; Malone, R

    1978-04-01

    Prepared for the Brookhaven National Laboratory Developing Countries Energy Program, this report describes the Less Developed Countries Energy System Network Simulator (LDC-ESNS), a tool which provides a quantitative representation of the energy system of an LDC. The network structure of the energy supply and demand system, the model inputs and outputs, and the possible uses of the model for analysis are described.

  3. Reliability assessment of restructured power systems using reliability network equivalent and pseudo-sequential simulation techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Yi; Wang, Peng; Goel, Lalit [Nanyang Technological University, School of Electrical and Electronics Engineering, Block S1, Nanyang Avenue, Singapore 639798 (Singapore); Billinton, Roy; Karki, Rajesh [Department of Electrical Engineering, University of Saskatchewan, Saskatoon (Canada)

    2007-10-15

    This paper presents a technique to evaluate reliability of a restructured power system with a bilateral market. The proposed technique is based on the combination of the reliability network equivalent and pseudo-sequential simulation approaches. The reliability network equivalent techniques have been implemented in the Monte Carlo simulation procedure to reduce the computational burden of the analysis. Pseudo-sequential simulation has been used to increase the computational efficiency of the non-sequential simulation method and to model the chronological aspects of market trading and system operation. Multi-state Markov models for generation and transmission systems are proposed and implemented in the simulation. A new load shedding scheme is proposed during generation inadequacy and network congestion to minimize the load curtailment. The IEEE reliability test system (RTS) is used to illustrate the technique. (author)

  4. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    Science.gov (United States)

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  5. Human metabolic network: reconstruction, simulation, and applications in systems biology.

    Science.gov (United States)

    Wu, Ming; Chan, Christina

    2012-03-02

    Metabolism is crucial to cell growth and proliferation. Deficiency or alterations in metabolic functions are known to be involved in many human diseases. Therefore, understanding the human metabolic system is important for the study and treatment of complex diseases. Current reconstructions of the global human metabolic network provide a computational platform to integrate genome-scale information on metabolism. The platform enables a systematic study of the regulation and is applicable to a wide variety of cases, wherein one could rely on in silico perturbations to predict novel targets, interpret systemic effects, and identify alterations in the metabolic states to better understand the genotype-phenotype relationships. In this review, we describe the reconstruction of the human metabolic network, introduce the constraint based modeling approach to analyze metabolic networks, and discuss systems biology applications to study human physiology and pathology. We highlight the challenges and opportunities in network reconstruction and systems modeling of the human metabolic system.

  6. Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

    Science.gov (United States)

    Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

    2017-02-01

    There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  7. How Network Properties Affect One's Ability to Obtain Benefits: A Network Simulation

    Science.gov (United States)

    Trefalt, Špela

    2014-01-01

    Networks and the social capital that they carry enable people to get things done, to prosper in their careers, and to feel supported. To develop an effective network, one needs to know more than how to make connections with strangers at a reception; understanding the consequences of network properties on one's ability to obtain benefits is…

  8. Research on Risk Evaluation of Transnational Power Networking Projects Based on the Matter-Element Extension Theory and Granular Computing

    Directory of Open Access Journals (Sweden)

    Jinying Li

    2017-10-01

    Full Text Available In project management, risk assessment is crucial for stakeholders to identify the risk factors during the whole life cycle of the project. A risk evaluation index system of a transnational networking project, which provides an effective way for the grid integration of clean electricity and the sustainable development of the power industry, is constructed in this paper. Meanwhile, a combination of granular computing and order relation analysis (G1 method is applied to determine the weight of each indicator and the matter-element extension evaluation model is also employed to seek the global optimal decision during the risk assessment. Finally, a case study is given to validate the index system and evaluation model established in this paper by assessing two different investment schemes of a transnational high voltage direct current (HVDC transmission project. The result shows that the comprehensive risk level of Scheme 1 is “Low” and the level of Scheme 2 is “General”, which means Scheme 1 is better for the stakeholders from the angle of risk control. The main practical significance of this paper lies in that it can provide a reference and decision support for the government’s power sectors, investment companies and other stakeholders when carrying out related activities.

  9. Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network.

    Science.gov (United States)

    Groth, Detlef

    2017-04-01

    Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later

  10. D-LiTE: A platform for evaluating DASH performance over a simulated LTE network

    OpenAIRE

    Quinlan, Jason J.; Raca, Darijo; Zahran, Ahmed H.; Khalid, Ahmed; Ramakrishnan, K. K.; Sreenan, Cormac J.

    2015-01-01

    In this demonstration we present a platform that encompasses all of the components required to realistically evaluate the performance of Dynamic Adaptive Streaming over HTTP (DASH) over a real-time NS-3 simulated network. Our platform consists of a network-attached storage server with DASH video clips and a simulated LTE network which utilises the NS-3 LTE module provided by the LENA project. We stream to clients running an open-source player with a choice of adaptation algorithms. By providi...

  11. ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks

    Directory of Open Access Journals (Sweden)

    David R. Hunter

    2008-12-01

    Full Text Available We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs: estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.

  12. Optimizing targeted vaccination across cyber-physical networks: an empirically based mathematical simulation study

    DEFF Research Database (Denmark)

    Mones, Enys; Stopczynski, Arkadiusz; Pentland, Alex 'Sandy'

    2018-01-01

    . If interruption of disease transmission is the goal, targeting requires knowledge of underlying person-to-person contact networks. Digital communication networks may reflect not only virtual but also physical interactions that could result in disease transmission, but the precise overlap between these cyber...... and physical networks has never been empirically explored in real-life settings. Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person......-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. We show that individuals selected on the basis of their closeness centrality within cyber networks (what we...

  13. Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center.

    Science.gov (United States)

    Shi, Xiaobo; Li, Wei; Song, Jeungeun; Hossain, M Shamim; Mizanur Rahman, Sk Md; Alelaiwi, Abdulhameed

    2016-10-01

    With the development of IoT (Internet of Thing), big data analysis and cloud computing, traditional medical information system integrates with these new technologies. The establishment of cloud-based smart healthcare application gets more and more attention. In this paper, semi-physical simulation technology is applied to cloud-based smart healthcare system. The Body sensor network (BSN) of system transmit has two ways of data collection and transmission. The one is using practical BSN to collect data and transmitting it to the data center. The other is transmitting real medical data to practical data center by simulating BSN. In order to transmit real medical data to practical data center by simulating BSN under semi-physical simulation environment, this paper designs an OPNET packet structure, defines a gateway node model between simulating BSN and practical data center and builds a custom protocol stack. Moreover, this paper conducts a large amount of simulation on the real data transmission through simulation network connecting with practical network. The simulation result can provides a reference for parameter settings of fully practical network and reduces the cost of devices and personnel involved.

  14. Increasing Learner Retention in a Simulated Learning Network using Indirect Social Interaction

    NARCIS (Netherlands)

    Koper, Rob

    2004-01-01

    Please refer to original publication: Koper, E.J.R. (2005). Increasing Learner Retention in a Simulated Learning Network Using Indirect Social Interaction. Journal of Artificial Societies and Social Simulation vol. 8, no. 2. http://jasss.soc.surrey.ac.uk/8/2/5.html Software is only stored to ensure

  15. Digitalization and networking of analog simulators and portal images.

    Science.gov (United States)

    Pesznyák, Csilla; Zaránd, Pál; Mayer, Arpád

    2007-03-01

    Many departments have analog simulators and irradiation facilities (especially cobalt units) without electronic portal imaging. Import of the images into the R&V (Record & Verify) system is required. Simulator images are grabbed while portal films scanned by using a laser scanner and both converted into DICOM RT (Digital Imaging and Communications in Medicine Radiotherapy) images. Image intensifier output of a simulator and portal films are converted to DICOM RT images and used in clinical practice. The simulator software was developed in cooperation at the authors' hospital. The digitalization of analog simulators is a valuable updating in clinical use replacing screen-film technique. Film scanning and digitalization permit the electronic archiving of films. Conversion into DICOM RT images is a precondition of importing to the R&V system.

  16. Development of a pore network simulation model to study nonaqueous phase liquid dissolution

    Science.gov (United States)

    Dillard, Leslie A.; Blunt, Martin J.

    2000-01-01

    A pore network simulation model was developed to investigate the fundamental physics of nonequilibrium nonaqueous phase liquid (NAPL) dissolution. The network model is a lattice of cubic chambers and rectangular tubes that represent pore bodies and pore throats, respectively. Experimental data obtained by Powers [1992] were used to develop and validate the model. To ensure the network model was representative of a real porous medium, the pore size distribution of the network was calibrated by matching simulated and experimental drainage and imbibition capillary pressure-saturation curves. The predicted network residual styrene blob-size distribution was nearly identical to the observed distribution. The network model reproduced the observed hydraulic conductivity and produced relative permeability curves that were representative of a poorly consolidated sand. Aqueous-phase transport was represented by applying the equation for solute flux to the network tubes and solving for solute concentrations in the network chambers. Complete mixing was found to be an appropriate approximation for calculation of chamber concentrations. Mass transfer from NAPL blobs was represented using a corner diffusion model. Predicted results of solute concentration versus Peclet number and of modified Sherwood number versus Peclet number for the network model compare favorably with experimental data for the case in which NAPL blob dissolution was negligible. Predicted results of normalized effluent concentration versus pore volume for the network were similar to the experimental data for the case in which NAPL blob dissolution occurred with time.

  17. Numerical simulation of fibrous biomaterials with randomly distributed fiber network structure.

    Science.gov (United States)

    Jin, Tao; Stanciulescu, Ilinca

    2016-08-01

    This paper presents a computational framework to simulate the mechanical behavior of fibrous biomaterials with randomly distributed fiber networks. A random walk algorithm is implemented to generate the synthetic fiber network in 2D used in simulations. The embedded fiber approach is then adopted to model the fibers as embedded truss elements in the ground matrix, which is essentially equivalent to the affine fiber kinematics. The fiber-matrix interaction is partially considered in the sense that the two material components deform together, but no relative movement is considered. A variational approach is carried out to derive the element residual and stiffness matrices for finite element method (FEM), in which material and geometric nonlinearities are both included. Using a data structure proposed to record the network geometric information, the fiber network is directly incorporated into the FEM simulation without significantly increasing the computational cost. A mesh sensitivity analysis is conducted to show the influence of mesh size on various simulation results. The proposed method can be easily combined with Monte Carlo (MC) simulations to include the influence of the stochastic nature of the network and capture the material behavior in an average sense. The computational framework proposed in this work goes midway between homogenizing the fiber network into the surrounding matrix and accounting for the fully coupled fiber-matrix interaction at the segment length scale, and can be used to study the connection between the microscopic structure and the macro-mechanical behavior of fibrous biomaterials with a reasonable computational cost.

  18. A simulated annealing heuristic for maximum correlation core/periphery partitioning of binary networks.

    Science.gov (United States)

    Brusco, Michael; Stolze, Hannah J; Hoffman, Michaela; Steinley, Douglas

    2017-01-01

    A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In this paper, we present a computationally efficient simulated annealing algorithm for maximum correlation core/periphery partitioning of binary networks. The algorithm is evaluated using simulated networks consisting of up to 2000 actors and spanning a variety of densities for the intra-core, intra-periphery, and inter-core-periphery components of the network. Core/periphery analyses of problem solving, trust, and information sharing networks for the frontline employees and managers of a consumer packaged goods manufacturer are provided to illustrate the use of the model.

  19. Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

    Science.gov (United States)

    Zeng, Y.

    2017-09-01

    Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

  20. Molecular simulation of flow-enhanced nucleation in n-eicosane melts under steady shear and uniaxial extension

    Science.gov (United States)

    Nicholson, David A.; Rutledge, Gregory C.

    2016-12-01

    Non-equilibrium molecular dynamics is used to study crystal nucleation of n-eicosane under planar shear and, for the first time, uniaxial extension. A method of analysis based on the mean first-passage time is applied to the simulation results in order to determine the effect of the applied flow field type and strain rate on the steady-state nucleation rate and a characteristic growth rate, as well as the effects on kinetic parameters associated with nucleation: the free energy barrier, critical nucleus size, and monomer attachment pre-factor. The onset of flow-enhanced nucleation (FEN) occurs at a smaller critical strain rate in extension as compared to shear. For strain rates larger than the critical rate, a rapid increase in the nucleation rate is accompanied by decreases in the free energy barrier and critical nucleus size, as well as an increase in chain extension. These observations accord with a mechanism in which FEN is caused by an increase in the driving force for crystallization due to flow-induced entropy reduction. At high applied strain rates, the free energy barrier, critical nucleus size, and degree of stretching saturate, while the monomer attachment pre-factor and degree of orientational order increase steadily. This trend is indicative of a significant diffusive contribution to the nucleation rate under intense flows that is correlated with the degree of global orientational order in a nucleating system. Both flow fields give similar results for all kinetic quantities with respect to the reduced strain rate, which we define as the ratio of the applied strain rate to the critical rate. The characteristic growth rate increases with increasing strain rate, and shows a correspondence with the nucleation rate that does not depend on the type of flow field applied. Additionally, a structural analysis of the crystalline clusters indicates that the flow field suppresses the compaction and crystalline ordering of clusters, leading to the formation of

  1. Molecular simulation of flow-enhanced nucleation in n-eicosane melts under steady shear and uniaxial extension.

    Science.gov (United States)

    Nicholson, David A; Rutledge, Gregory C

    2016-12-28

    Non-equilibrium molecular dynamics is used to study crystal nucleation of n-eicosane under planar shear and, for the first time, uniaxial extension. A method of analysis based on the mean first-passage time is applied to the simulation results in order to determine the effect of the applied flow field type and strain rate on the steady-state nucleation rate and a characteristic growth rate, as well as the effects on kinetic parameters associated with nucleation: the free energy barrier, critical nucleus size, and monomer attachment pre-factor. The onset of flow-enhanced nucleation (FEN) occurs at a smaller critical strain rate in extension as compared to shear. For strain rates larger than the critical rate, a rapid increase in the nucleation rate is accompanied by decreases in the free energy barrier and critical nucleus size, as well as an increase in chain extension. These observations accord with a mechanism in which FEN is caused by an increase in the driving force for crystallization due to flow-induced entropy reduction. At high applied strain rates, the free energy barrier, critical nucleus size, and degree of stretching saturate, while the monomer attachment pre-factor and degree of orientational order increase steadily. This trend is indicative of a significant diffusive contribution to the nucleation rate under intense flows that is correlated with the degree of global orientational order in a nucleating system. Both flow fields give similar results for all kinetic quantities with respect to the reduced strain rate, which we define as the ratio of the applied strain rate to the critical rate. The characteristic growth rate increases with increasing strain rate, and shows a correspondence with the nucleation rate that does not depend on the type of flow field applied. Additionally, a structural analysis of the crystalline clusters indicates that the flow field suppresses the compaction and crystalline ordering of clusters, leading to the formation of

  2. Modeling radio link performance in UMTS W-CDMA network simulations

    DEFF Research Database (Denmark)

    Klingenbrunn, Thomas; Mogensen, Preben Elgaard

    2000-01-01

    This article presents a method to model the W-CDMA radio receiver performance, which is usable in network simulation tools for third generation mobile cellular systems. The method represents a technique to combine link level simulations with network level simulations. The method is derived from [1......], which defines a stochastic mapping function from a Signal-to-Interference Ratio into a Bit-Error-Rate for a TDMA system. However, in order to work in a W-CDMA based system, the fact that the Multiple-Access Interference in downlink consists of both Gaussian inter-cell interference and orthogonal intra...

  3. A versatile framework for simulating the dynamic mechanical structure of cytoskeletal networks

    CERN Document Server

    Freedman, Simon L; Hocky, Glen M; Dinner, Aaron R

    2016-01-01

    Computer simulations can aid in our understanding of how collective materials properties emerge from interactions between simple constituents. Here, we introduce a coarse- grained model of networks of actin filaments, myosin motors, and crosslinking proteins that enables simulation at biologically relevant time and length scales. We demonstrate that the model, with a consistent parameterization, qualitatively and quantitatively captures a suite of trends observed experimentally, including the statistics of filament fluctuations, mechanical responses to shear, motor motilities, and network rearrangements. The model can thus serve as a platform for interpretation and design of cytoskeletal materials experiments, as well as for further development of simulations incorporating active elements.

  4. STOMP: A Software Architecture for the Design and Simulation UAV-Based Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Jones, E D; Roberts, R S; Hsia, T C S

    2002-10-28

    This paper presents the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture and framework for simulating, controlling and communicating with unmanned air vehicles (UAVs) servicing large distributed sensor networks. STOMP provides hardware-in-the-loop capability enabling real UAVs and sensors to feedback state information, route data and receive command and control requests while interacting with other real or virtual objects thereby enhancing support for simulation of dynamic and complex events.

  5. Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

    Directory of Open Access Journals (Sweden)

    Ufa Ruslan A.

    2015-01-01

    Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

  6. Simulation, State Estimation and Control of Nonlinear Superheater Attemporator using Neural Networks

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Sørensen, O.

    2000-01-01

    This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model......-by-sample linearizations and state estimates provided by the observer network. Simulation studies show that the nonlinear observer-based control loop performs better than a similar control loop based on a linear observer....... of the process, then another network is trained to act as a combined state and parameter estimator for the process. The observer network incorporates smoothing of the parameter estimates in the form of regularization. A pole placement controller is designed which takes advantage of the sample...

  7. Simulation, State Estimation and Control of Nonlinear Superheater Attemporator using Neural Networks

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Sørensen, O.

    1999-01-01

    This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model......-by-sample linearizations and state estimates provided by the observer network. Simulation studies show that the nonlinear observer-based control loop performs better than a similar control loop based on a linear observer....... of the process, then another network is trained to act as a combined state and parameter estimator for the process. The observer network incorporates smoothing of the parameter estimates in the form of regularization. A pole placement controller is designed which takes advantage of the sample...

  8. A Model to Simulate Multimodality in a Mesoscopic Dynamic Network Loading Framework

    Directory of Open Access Journals (Sweden)

    Massimo Di Gangi

    2017-01-01

    Full Text Available A dynamic network loading (DNL model using a mesoscopic approach is proposed to simulate a multimodal transport network considering en-route change of the transport modes. The classic mesoscopic approach, where packets of users belonging to the same mode move following a path, is modified to take into account multiple modes interacting with each other, simultaneously and on the same multimodal network. In particular, to simulate modal change, functional aspects of multimodal arcs have been developed; those arcs are properly located on the network where modal change occurs and users are packed (or unpacked in a new modal resource that moves up to destination or to another multimodal arc. A test on a simple network reproducing a real situation is performed in order to show model peculiarities; some indicators, used to describe performances of the considered transport system, are shown.

  9. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  10. High Fidelity Simulations of Large-Scale Wireless Networks (Plus-Up)

    Energy Technology Data Exchange (ETDEWEB)

    Onunkwo, Uzoma [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-11-01

    Sandia has built a strong reputation in scalable network simulation and emulation for cyber security studies to protect our nation’s critical information infrastructures. Georgia Tech has preeminent reputation in academia for excellence in scalable discrete event simulations, with strong emphasis on simulating cyber networks. Many of the experts in this field, such as Dr. Richard Fujimoto, Dr. George Riley, and Dr. Chris Carothers, have strong affiliations with Georgia Tech. The collaborative relationship that we intend to immediately pursue is in high fidelity simulations of practical large-scale wireless networks using ns-3 simulator via Dr. George Riley. This project will have mutual benefits in bolstering both institutions’ expertise and reputation in the field of scalable simulation for cyber-security studies. This project promises to address high fidelity simulations of large-scale wireless networks. This proposed collaboration is directly in line with Georgia Tech’s goals for developing and expanding the Communications Systems Center, the Georgia Tech Broadband Institute, and Georgia Tech Information Security Center along with its yearly Emerging Cyber Threats Report. At Sandia, this work benefits the defense systems and assessment area with promise for large-scale assessment of cyber security needs and vulnerabilities of our nation’s critical cyber infrastructures exposed to wireless communications.

  11. Efficient Heuristics for Simulating Population Overflow in Parallel Networks

    NARCIS (Netherlands)

    Zaburnenko, T.S.; Nicola, V.F.

    2006-01-01

    In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for costly optimization involved in other

  12. Simulation of traffic capacity of inland waterway network

    NARCIS (Netherlands)

    Chen, L.; Mou, J.; Ligteringen, H.

    2013-01-01

    The inland waterborne transportation is viewed as an economic, safe and environmentally friendly alternative to the congested road network. The traffic capacity are the critical indicator of the inland shipping performance. Actually, interacted under the complicated factors, it is challenging to

  13. Numerical simulation with finite element and artificial neural network ...

    Indian Academy of Sciences (India)

    Further, this database after the neural network training; is used to analyse measured material properties of different test pieces. The ANN predictions are reconfirmed with contact type finite element analysis for an arbitrary selected test sample. The methodology evolved in this work can be extended to predict material ...

  14. MULTI-LEVEL NETWORK RESILIENCE: TRAFFIC ANALYSIS, ANOMALY DETECTION AND SIMULATION

    Directory of Open Access Journals (Sweden)

    Angelos Marnerides

    2011-06-01

    Full Text Available Traffic analysis and anomaly detection have been extensively used to characterize network utilization as well as to identify abnormal network traffic such as malicious attacks. However, so far, techniques for traffic analysis and anomaly detection have been carried out independently, relying on mechanisms and algorithms either in edge or in core networks alone. In this paper we propose the notion of multi-level network resilience, in order to provide a more robust traffic analysis and anomaly detection architecture, combining mechanisms and algorithms operating in a coordinated fashion both in the edge and in the core networks. This work is motivated by the potential complementarities between the research being developed at IIT Madras and Lancaster University. In this paper we describe the current work being developed at IIT Madras and Lancaster on traffic analysis and anomaly detection, and outline the principles of a multi-level resilience architecture.

  15. Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah; Ross, Robert; Carns, Philip

    2016-05-15

    As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.

  16. COMPLEX NETWORK SIMULATION OF FOREST NETWORK SPATIAL PATTERN IN PEARL RIVER DELTA

    Directory of Open Access Journals (Sweden)

    Y. Zeng

    2017-09-01

    Full Text Available Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network’s power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network’s degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network’s main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc. for networking a standard and base datum.

  17. Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation

    Directory of Open Access Journals (Sweden)

    Chunqing Li

    2012-01-01

    Full Text Available The computer simulation of the membrane bioreactor MBR has become the research focus of the MBR simulation. In order to compensate for the defects, for example, long test period, high cost, invisible equipment seal, and so forth, on the basis of conducting in-depth study of the mathematical model of the MBR, combining with neural network theory, this paper proposed a three-dimensional simulation system for MBR wastewater treatment, with fast speed, high efficiency, and good visualization. The system is researched and developed with the hybrid programming of VC++ programming language and OpenGL, with a multifactor linear regression model of affecting MBR membrane fluxes based on neural network, applying modeling method of integer instead of float and quad tree recursion. The experiments show that the three-dimensional simulation system, using the above models and methods, has the inspiration and reference for the future research and application of the MBR simulation technology.

  18. A case for spiking neural network simulation based on configurable multiple-FPGA systems.

    Science.gov (United States)

    Yang, Shufan; Wu, Qiang; Li, Renfa

    2011-09-01

    Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.

  19. Simulating dynamic plastic continuous neural networks by finite elements.

    Science.gov (United States)

    Joghataie, Abdolreza; Torghabehi, Omid Oliyan

    2014-08-01

    We introduce dynamic plastic continuous neural network (DPCNN), which is comprised of neurons distributed in a nonlinear plastic medium where wire-like connections of neural networks are replaced with the continuous medium. We use finite element method to model the dynamic phenomenon of information processing within the DPCNNs. During the training, instead of weights, the properties of the continuous material at its different locations and some properties of neurons are modified. Input and output can be vectors and/or continuous functions over lines and/or areas. Delay and feedback from neurons to themselves and from outputs occur in the DPCNNs. We model a simple form of the DPCNN where the medium is a rectangular plate of bilinear material, and the neurons continuously fire a signal, which is a function of the horizontal displacement.

  20. Runtime Performance and Virtual Network Control Alternatives in VM-Based High-Fidelity Network Simulations

    Science.gov (United States)

    2012-12-01

    network emulation systems have been proposed, such as V-eM (Apostolopoulos and Hasapis 2006), DieCast (Gupta et al. 2008), VENICE (Liu, Raju, and...Proceedings of the 2006 3rd Symposium on Networked Systems Design and Implementation (NSDI’06), San Jose, CA, USA. Gupta, D., et al. 2008. “ DieCast

  1. Representing Dynamic Social Networks in Discrete Event Social Simulation

    Science.gov (United States)

    2010-12-01

    notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not...and applying social network change detection methods (SNCD) to model output. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...society. The action choice component of the conceptual model is based on the theory of planned behavior ( TPB ) (I. Ajzen 1991). The TPB states that an

  2. Analysis and Simulation of Hybrid Models for Reaction Networks

    OpenAIRE

    Kreim, Michael

    2014-01-01

    The dynamics of biochemical reaction networks can be described by a variety of models, like the Reaction Rate equation (RRE), the Chemical Master equation (CME) or the Fokker-Planck equation (FPE). In this thesis, the behaviour of these different models is analysed. It is shown that the FPE can be motivated as an approximation of the CME and convergence is proven. Furthermore, two hybrid models are constructed by combining different approaches and convergence properties are proven and discussed.

  3. Simulators for the Internet of Things

    OpenAIRE

    LAHARNAR, BORIS

    2016-01-01

    The thesis delivers an extensive review of free and open-source simulation tools useful for IoT simulation. The work deals with free simulators and other tools and sources applicable to simulation of IoT use cases. Roughly 80 tools and other sources were reviewed. Different application domain simulators were enlisted (smart home, connected vehicles, smart city, smart grid, UAV...), network simulators, WSN simulators, discrete event simulators, virtualization tools, emulators and simulators of...

  4. Simulating market dynamics : Interactions between consumer psychology and social networks

    NARCIS (Netherlands)

    Janssen, M.A; Jager, W.

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. in a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation

  5. Credible Mobile and Ad Hoc Network Simulation-Based Studies

    Science.gov (United States)

    2006-10-26

    once duplicate (orange) Received the same packet twice 2-duplicates ( pink ) Received the same packet at least three times 4-duplicates (red) Received...mobility tool generators in NS-2 simulator. Version 1.0, beta, 2004. [6] S. Bajaj, L. Breslau, D. Estrin, K. Fall, S. Floyd , P. Haldar, M. Hand- ley, A

  6. Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

    Science.gov (United States)

    Knight, James C.; Tully, Philip J.; Kaplan, Bernhard A.; Lansner, Anders; Furber, Steve B.

    2016-01-01

    SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 × 104 neurons and 5.1 × 107 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45× more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models. PMID:27092061

  7. Large-scale simulations of plastic neural networks on neuromorphic hardware

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-04-01

    Full Text Available SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 20000 neurons and 51200000 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

  8. A Simulation Study for Emergency/Disaster Management by Applying Complex Networks Theory

    Directory of Open Access Journals (Sweden)

    Li Jin

    2014-04-01

    Full Text Available Earthquakes, hurricanes, flooding and terrorist attacks pose a severe threat to our society. What’s more, when such a disaster happens, it can spread in a wide range with ubiquitous presence of a large-scale networked system. Therefore, the emergency/disaster management faces new challenges that the decision-makers have extra difficulties in perceiving the disaster dynamic spreading processes under this networked environment. This study tries to use the complex networks theory to tackle this complexity and the result shows the theory is a promising approach to support disaster/emergency management by focusing on simulation experiments of small world networks and scale free networks. The theory can be used to capture and describe the evolution mechanism, evolution discipline and overall behavior of a networked system. In particular, the complex networks theory is very strong at analyzing the complexity and dynamical changes of a networked system, which can improve the situation awareness after a disaster has occurred and help perceive its dynamic process, which is very important for high-quality decision making. In addition, this study also shows the use of the complex networks theory can build a visualized process to track the dynamic spreading of a disaster in a networked system.

  9. Experimental Evaluation of Simulation Abstractions for Wireless Sensor Network MAC Protocols

    Directory of Open Access Journals (Sweden)

    G. P. Halkes

    2010-01-01

    Full Text Available The evaluation of MAC protocols for Wireless Sensor Networks (WSNs is often performed through simulation. These simulations necessarily abstract away from reality in many ways. However, the impact of these abstractions on the results of the simulations has received only limited attention. Moreover, many studies on the accuracy of simulation have studied either the physical layer and per link effects or routing protocol effects. To the best of our knowledge, no other work has focused on the study of the simulation abstractions with respect to MAC protocol performance. In this paper, we present the results of an experimental study of two often used abstractions in the simulation of WSN MAC protocols. We show that a simple SNR-based reception model can provide quite accurate results for metrics commonly used to evaluate MAC protocols. Furthermore, we provide an analysis of what the main sources of deviation are and thereby how the simulations can be improved to provide even better results.

  10. Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

    CERN Document Server

    Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

    2016-01-01

    We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

  11. Brownian dynamics simulation of insulin microsphere formation from break-up of a fractal network.

    Science.gov (United States)

    Li, Wei; Gunton, J D; Khan, Siddique J; Schoelz, J K; Chakrabarti, A

    2011-01-14

    Motivated by a recent experiment on insulin microsphere formation where polyethylene glycol (PEG) is used as the precipitating agent, we have developed a simple theoretical model that can predict the formation of a fractal network of insulin monomers and the subsequent break-up of the fractal network into microsphere aggregates. In our approach the effect of PEG on insulin is modeled via a standard depletion attraction mechanism via the Asakura-Oosawa model. We show that even in the context of this simple model, it is possible to mimic important aspects of the insulin experiment in a brownian dynamics simulation. We simulate the effect of changing temperature in our model by changing the well depth of the Asakura-Oosawa potential. A fractal network is observed in a "deep quench" of the system, followed by a "heating" that results in a break-up of the network and subsequent formation of microspheres.

  12. Application of artificial neural networks to identify equilibration in computer simulations

    Science.gov (United States)

    Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

    2017-11-01

    Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

  13. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-04-01

    Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

  14. Live tree carbon stock equivalence of fire and fuels extension to the Forest Vegetation Simulator and Forest Inventory and Analysis approaches

    Science.gov (United States)

    James E. Smith; Coeli M. Hoover

    2017-01-01

    The carbon reports in the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) provide two alternate approaches to carbon estimates for live trees (Rebain 2010). These are (1) the FFE biomass algorithms, which are volumebased biomass equations, and (2) the Jenkins allometric equations (Jenkins and others 2003), which are diameter based. Here, we...

  15. Simulation and Modeling of a New Medium Access Control Scheme for Multi-Beam Directional Networking

    Science.gov (United States)

    2017-03-03

    implement our protocol in both simula- tion and a new Extendable Mobile Ad -hoc Network Emula- tor (EMANE) model that allows for real-time, high fidelity...issues, where the amount of data passed between the servers is too high, and 2) computation issues, where calculating the interference on the packets...developed a custom discrete event simulator in C++, and a new Ex- tendable Mobile Ad -hoc Network Emulator (EMANE) [10] model. These tools are used to both

  16. Simulated Annealing in Optimization of Energy Production in a Water Supply Network

    OpenAIRE

    Almeida Samora, Irene; Franca, Mário J.; Schleiss, Anton; Helena M. Ramos

    2016-01-01

    In water supply systems, the potential exists for micro-hydropower that uses the pressure excess in the networks to produce electricity. However, because urban drinking water networks are complex systems in which flows and pressure vary constantly, identification of the ideal locations for turbines is not straightforward, and assessment implies the need for simulation. In this paper, an optimization algorithm is proposed to provide a selection of optimal locations for the installation of a gi...

  17. Attaining Realistic Simulations of Mobile Ad-hoc Networks

    Science.gov (United States)

    2010-06-01

    Lastly every MANET faces higher security risks either through malicious or poorly configured nodes. The fact that MANET traffic is dependent on...are being developed and advertised as secure and reliable but the simulation models are unable to provide an accurate depiction of how the new...use of the Institute of Telematics techniques that alter propagation models within NS-2 and generate the resulting model in LaTeX [20]. These models

  18. Large-scale lattice-Boltzmann simulations over lambda networks

    Science.gov (United States)

    Saksena, R.; Coveney, P. V.; Pinning, R.; Booth, S.

    Amphiphilic molecules are of immense industrial importance, mainly due to their tendency to align at interfaces in a solution of immiscible species, e.g., oil and water, thereby reducing surface tension. Depending on the concentration of amphiphiles in the solution, they may assemble into a variety of morphologies, such as lamellae, micelles, sponge and cubic bicontinuous structures exhibiting non-trivial rheological properties. The main objective of this work is to study the rheological properties of very large, defect-containing gyroidal systems (of up to 10243 lattice sites) using the lattice-Boltzmann method. Memory requirements for the simulation of such large lattices exceed that available to us on most supercomputers and so we use MPICH-G2/MPIg to investigate geographically distributed domain decomposition simulations across HPCx in the UK and TeraGrid in the US. Use of MPICH-G2/MPIg requires the port-forwarder to work with the grid middleware on HPCx. Data from the simulations is streamed to a high performance visualisation resource at UCL (London) for rendering and visualisation. Lighting the Blue Touchpaper for UK e-Science - Closing Conference of ESLEA Project March 26-28 2007 The George Hotel, Edinburgh, UK

  19. Proposal for an extension to the procedure for the qualification and selection of network operators for the provision of outgoing fixed-line telephone calls

    CERN Document Server

    2004-01-01

    This document concerns a proposal for a three-year extension to the procedure for the qualification and selection of network operators for the provision of outgoing fixed-line telephone calls. The Finance Committee is invited to agree to the continuation of the procedure approved by the Finance Committee (CERN/FC/4407) for the selection of network operators for the provision of outgoing fixed-line telephone calls for a three-year period within an annual ceiling of 800 000 Swiss francs, bringing the total amount for the period to a maximum of 2 400 000 Swiss francs.

  20. Compensatory plasticity in the action observation network: virtual lesions of STS enhance anticipatory simulation of seen actions

    National Research Council Canada - National Science Library

    Avenanti, Alessio; Annella, Laura; Candidi, Matteo; Urgesi, Cosimo; Aglioti, Salvatore M

    2013-01-01

    .... Such motor facilitation indexes the anticipatory simulation of observed (implied) actions and likely reflects computations occurring in the parietofrontal nodes of a cortical network subserving action perception...

  1. Multiscale methodology for bone remodelling simulation using coupled finite element and neural network computation.

    Science.gov (United States)

    Hambli, Ridha; Katerchi, Houda; Benhamou, Claude-Laurent

    2011-02-01

    The aim of this paper is to develop a multiscale hierarchical hybrid model based on finite element analysis and neural network computation to link mesoscopic scale (trabecular network level) and macroscopic (whole bone level) to simulate the process of bone remodelling. As whole bone simulation, including the 3D reconstruction of trabecular level bone, is time consuming, finite element calculation is only performed at the macroscopic level, whilst trained neural networks are employed as numerical substitutes for the finite element code needed for the mesoscale prediction. The bone mechanical properties are updated at the macroscopic scale depending on the morphological and mechanical adaptation at the mesoscopic scale computed by the trained neural network. The digital image-based modelling technique using μ-CT and voxel finite element analysis is used to capture volume elements representative of 2 mm³ at the mesoscale level of the femoral head. The input data for the artificial neural network are a set of bone material parameters, boundary conditions and the applied stress. The output data are the updated bone properties and some trabecular bone factors. The current approach is the first model, to our knowledge, that incorporates both finite element analysis and neural network computation to rapidly simulate multilevel bone adaptation.

  2. The Framework for Simulation of Bioinspired Security Mechanisms against Network Infrastructure Attacks

    Directory of Open Access Journals (Sweden)

    Andrey Shorov

    2014-01-01

    Full Text Available The paper outlines a bioinspired approach named “network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed prosedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine nessesary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

  3. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

    Directory of Open Access Journals (Sweden)

    Kit eCheung

    2016-01-01

    Full Text Available NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs. Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimised performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP rule for learning. A 6-FPGA system can simulate a network of up to approximately 600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.

  4. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

    Science.gov (United States)

    Cheung, Kit; Schultz, Simon R; Luk, Wayne

    2015-01-01

    NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.

  5. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

    Science.gov (United States)

    Cheung, Kit; Schultz, Simon R.; Luk, Wayne

    2016-01-01

    NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

  6. PAX: A mixed hardware/software simulation platform for spiking neural networks.

    Science.gov (United States)

    Renaud, S; Tomas, J; Lewis, N; Bornat, Y; Daouzli, A; Rudolph, M; Destexhe, A; Saïghi, S

    2010-09-01

    Many hardware-based solutions now exist for the simulation of bio-like neural networks. Less conventional than software-based systems, these types of simulators generally combine digital and analog forms of computation. In this paper we present a mixed hardware-software platform, specifically designed for the simulation of spiking neural networks, using conductance-based models of neurons and synaptic connections with dynamic adaptation rules (Spike-Timing-Dependent Plasticity). The neurons and networks are configurable, and are computed in 'biological real time' by which we mean that the difference between simulated time and simulation time is guaranteed lower than 50 mus. After presenting the issues and context involved in the design and use of hardware-based spiking neural networks, we describe the analog neuromimetic integrated circuits which form the core of the platform. We then explain the organization and computation principles of the modules within the platform, and present experimental results which validate the system. Designed as a tool for computational neuroscience, the platform is exploited in collaborative research projects together with neurobiology and computer science partners. Copyright 2010 Elsevier Ltd. All rights reserved.

  7. A SIMULATION OF THE PENICILLIN G PRODUCTION BIOPROCESS APPLYING NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    A.J.G. da Cruz

    1997-12-01

    Full Text Available The production of penicillin G by Penicillium chrysogenum IFO 8644 was simulated employing a feedforward neural network with three layers. The neural network training procedure used an algorithm combining two procedures: random search and backpropagation. The results of this approach were very promising, and it was observed that the neural network was able to accurately describe the nonlinear behavior of the process. Besides, the results showed that this technique can be successfully applied to control process algorithms due to its long processing time and its flexibility in the incorporation of new data

  8. Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

    Science.gov (United States)

    Hou, Rui; Wu, Jiawen; Du, Helen S.

    2017-03-01

    To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

  9. Building a Community of Practice for Researchers: The International Network for Simulation-Based Pediatric Innovation, Research and Education.

    Science.gov (United States)

    Cheng, Adam; Auerbach, Marc; Calhoun, Aaron; Mackinnon, Ralph; Chang, Todd P; Nadkarni, Vinay; Hunt, Elizabeth A; Duval-Arnould, Jordan; Peiris, Nicola; Kessler, David

    2017-11-08

    The scope and breadth of simulation-based research is growing rapidly; however, few mechanisms exist for conducting multicenter, collaborative research. Failure to foster collaborative research efforts is a critical gap that lies in the path of advancing healthcare simulation. The 2017 Research Summit hosted by the Society for Simulation in Healthcare highlighted how simulation-based research networks can produce studies that positively impact the delivery of healthcare. In 2011, the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE) was formed to facilitate multicenter, collaborative simulation-based research with the aim of developing a community of practice for simulation researchers. Since its formation, the network has successfully completed and published numerous collaborative research projects. In this article, we describe INSPIRE's history, structure, and internal processes with the goal of highlighting the community of practice model for other groups seeking to form a simulation-based research network.

  10. A simulation model for aligning smart home networks and deploying smart objects

    DEFF Research Database (Denmark)

    Lynggaard, Per

    Smart homes use sensor based networks to capture activities and offer learned services to the user. These smart home networks are challenging because they mainly use wireless communication at frequencies that are shared with other services and equipments. One of the major challenges...... is the interferences produced by WiFi access points in smart home networks which are expensive to overcome in terms of battery energy. Currently, different method exists to handle this. However, they use complex mechanisms such as sharing frequencies, sharing time slots, and spatial reuse of frequencies. This paper...... introduces a unique concept which saves battery energy and lowers the interference level by simulating the network alignment and assign the necessary amount of transmit power to each individual network node and finally, deploy the smart objects. The needed transmit powers are calculated by the presented...

  11. Statistics of interacting networks with extreme preferred degrees: Simulation results and theoretical approaches

    Science.gov (United States)

    Liu, Wenjia; Schmittmann, Beate; Zia, R. K. P.

    2012-02-01

    Network studies have played a central role for understanding many systems in nature - e.g., physical, biological, and social. So far, much of the focus has been the statistics of networks in isolation. Yet, many networks in the world are coupled to each other. Recently, we considered this issue, in the context of two interacting social networks. In particular, We studied networks with two different preferred degrees, modeling, say, introverts vs. extroverts, with a variety of ``rules for engagement.'' As a first step towards an analytically accessible theory, we restrict our attention to an ``extreme scenario'': The introverts prefer zero contacts while the extroverts like to befriend everyone in the society. In this ``maximally frustrated'' system, the degree distributions, as well as the statistics of cross-links (between the two groups), can depend sensitively on how a node (individual) creates/breaks its connections. The simulation results can be reasonably well understood in terms of an approximate theory.

  12. Agent-based simulations of emotion spreading in online social networks

    CERN Document Server

    Šuvakov, Milovan; Schweitzer, Frank; Tadić, Bosiljka

    2012-01-01

    Quantitative analysis of empirical data from online social networks reveals group dynamics in which emotions are involved (\\v{S}uvakov et al). Full understanding of the underlying mechanisms, however, remains a challenging task. Using agent-based computer simulations, in this paper we study dynamics of emotional communications in online social networks. The rules that guide how the agents interact are motivated, and the realistic network structure and some important parameters are inferred from the empirical dataset of \\texttt{MySpace} social network. Agent's emotional state is characterized by two variables representing psychological arousal---reactivity to stimuli, and valence---attractiveness or aversiveness, by which common emotions can be defined. Agent's action is triggered by increased arousal. High-resolution dynamics is implemented where each message carrying agent's emotion along the network link is identified and its effect on the recipient agent is considered as continuously aging in time. Our res...

  13. Method of construction of rational corporate network using the simulation model

    Directory of Open Access Journals (Sweden)

    V.N. Pakhomovа

    2013-06-01

    Full Text Available Purpose. Search for new options of the transition from Ethernet technology. Methodology. Physical structuring of the Fast Ethernet network based on hubs and logical structuring of Fast Ethernet network using commutators. Organization of VLAN based on ports grouping and in accordance with the standard IEEE 802 .1Q. Findings. The options for improving of the Ethernet network are proposed. According to the Fast Ethernet and VLAN technologies on the simulation models in packages NetCraker and Cisco Packet Traker respectively. Origiality. The technique of designing of local area network using the VLAN technology is proposed. Practical value.Each of the options of "Dniprozaliznychproekt" network improving has its advantages. Transition from the Ethernet to Fast Ethernet technology is simple and economical, it requires only one commutator, when the VLAN organization requires at least two. VLAN technology, however, has the following advantages: reducing the load on the network, isolation of the broadcast traffic, change of the logical network structure without changing its physical structure, improving the network security. The transition from Ethernet to the VLAN technology allows you to separate the physical topology from the logical one, and the format of the ÌEEE 802.1Q standard frames allows you to simplify the process of virtual networks implementation to enterprises.

  14. Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Yang Sun

    2018-01-01

    Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.

  15. Versatile Networks of Simulated Spiking Neurons Displaying Winner-Take-All Behavior

    Directory of Open Access Journals (Sweden)

    Yanqing eChen

    2013-03-01

    Full Text Available We describe simulations of large-scale networks of excitatory and inhibitory spiking neurons that can generate dynamically stable winner-take-all (WTA behavior. The network connectivity is a variant of center-surround architecture that we call center-annular-surround (CAS. In this architecture each neuron is excited by nearby neighbors and inhibited by more distant neighbors in an annular-surround region. The neural units of these networks simulate conductance-based spiking neurons that interact via mechanisms susceptible to both short-term synaptic plasticity and STDP. We show that such CAS networks display robust WTA behavior unlike the center-surround networks and other control architectures that we have studied. We find that a large-scale network of spiking neurons with separate populations of excitatory and inhibitory neurons can give rise to smooth maps of sensory input. In addition, we show that a humanoid Brain-Based-Device (BBD under the control of a spiking WTA neural network can learn to reach to target positions in its visual field, thus demonstrating the acquisition of sensorimotor coordination.

  16. High power fuel cell simulator based on artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Chavez-Ramirez, Abraham U.; Munoz-Guerrero, Roberto [Departamento de Ingenieria Electrica, CINVESTAV-IPN. Av. Instituto Politecnico Nacional No. 2508, D.F. CP 07360 (Mexico); Duron-Torres, S.M. [Unidad Academica de Ciencias Quimicas, Universidad Autonoma de Zacatecas, Campus Siglo XXI, Edif. 6 (Mexico); Ferraro, M.; Brunaccini, G.; Sergi, F.; Antonucci, V. [CNR-ITAE, Via Salita S. Lucia sopra Contesse 5-98126 Messina (Italy); Arriaga, L.G. [Centro de Investigacion y Desarrollo Tecnologico en Electroquimica S.C., Parque Tecnologico Queretaro, Sanfandila, Pedro Escobedo, Queretaro (Mexico)

    2010-11-15

    Artificial Neural Network (ANN) has become a powerful modeling tool for predicting the performance of complex systems with no well-known variable relationships due to the inherent properties. A commercial Polymeric Electrolyte Membrane fuel cell (PEMFC) stack (5 kW) was modeled successfully using this tool, increasing the number of test into the 7 inputs - 2 outputs-dimensional spaces in the shortest time, acquiring only a small amount of experimental data. Some parameters could not be measured easily on the real system in experimental tests; however, by receiving the data from PEMFC, the ANN could be trained to learn the internal relationships that govern this system, and predict its behavior without any physical equations. Confident accuracy was achieved in this work making possible to import this tool to complex systems and applications. (author)

  17. Enhancing the NS-2 Network Simulator for Near Real-Time Control Feedback and Distributed Simulation

    Science.gov (United States)

    2009-03-21

    visualization of the simulation as it executes. 12 III. Command Feedback Design and Implementation U ser -simulator interaction is the key driver of this...TCL script. As the TCL script is parsed, a SocketListener object is created within C++. The SocketLis- tener object creates a new Boost::Thread [4] and

  18. Some issues related to simulation of the tracking and communications computer network

    Science.gov (United States)

    Lacovara, Robert C.

    1989-01-01

    The Communications Performance and Integration branch of the Tracking and Communications Division has an ongoing involvement in the simulation of its flight hardware for Space Station Freedom. Specifically, the communication process between central processor(s) and orbital replaceable units (ORU's) is simulated with varying degrees of fidelity. The results of investigations into three aspects of this simulation effort are given. The most general area involves the use of computer assisted software engineering (CASE) tools for this particular simulation. The second area of interest is simulation methods for systems of mixed hardware and software. The final area investigated is the application of simulation methods to one of the proposed computer network protocols for space station, specifically IEEE 802.4.

  19. The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

    Science.gov (United States)

    Kunkel, Susanne; Schenck, Wolfram

    2017-01-01

    NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling. PMID:28701946

  20. The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code.

    Science.gov (United States)

    Kunkel, Susanne; Schenck, Wolfram

    2017-01-01

    NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

  1. ezBioNet: A modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2012-10-01

    To achieve robustness against living environments, a living organism is composed of complicated regulatory mechanisms ranging from gene regulations to signal transduction. If such life phenomena are to be understand, an integrated analysis tool that should have modeling and simulation functions for biological reactions, as well as new experimental methods for measuring biological phenomena, is fundamentally required. We have designed and implemented modeling and simulation software (ezBioNet) for analyzing biological reaction networks. The software can simultaneously perform an integrated modeling of various responses occurring in cells, ranging from gene expressions to signaling processes. To support massive analysis of biological networks, we have constructed a server-side simulation system (VCellSim) that can perform ordinary differential equations (ODE) analysis, sensitivity analysis, and parameter estimates. ezBioNet integrates the BioModel database by connecting the european bioinformatics institute (EBI) servers through Web services APIs and supports the handling of systems biology markup language (SBML) files. In addition, we employed eclipse RCP (rich client platform) which is a powerful modularity framework allowing various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool, as well as a simulation system, to understand the control mechanism by monitoring the change of each component in a biological network. A researcher may perform the kinetic modeling and execute the simulation. The simulation result can be managed and visualized on ezBioNet, which is freely available at http://ezbionet.cbnu.ac.kr.

  2. The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

    Directory of Open Access Journals (Sweden)

    Susanne Kunkel

    2017-06-01

    Full Text Available NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

  3. Transforming network simulation data to semantic data for network attack planning

    CSIR Research Space (South Africa)

    Chan, Ke Fai Peter

    2017-03-01

    Full Text Available to the Web Ontology Language (OWL) 2.0 eXtensible Markup Language (XML) format, which can be read, merged, and reasoned by ontology tools such as Protégé. Using the Web Ontology Language Application Program Interface (OWL API), it was possible to merge...

  4. Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

    Science.gov (United States)

    Christensen, Claire Petra

    Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author

  5. Design and Study of Cognitive Network Physical Layer Simulation Platform

    Directory of Open Access Journals (Sweden)

    Yongli An

    2014-01-01

    Full Text Available Cognitive radio technology has received wide attention for its ability to sense and use idle frequency. IEEE 802.22 WRAN, the first to follow the standard in cognitive radio technology, is featured by spectrum sensing and wireless data transmission. As far as wireless transmission is concerned, the availability and implementation of a mature and robust physical layer algorithm are essential to high performance. For the physical layer of WRAN using OFDMA technology, this paper proposes a synchronization algorithm and at the same time provides a public platform for the improvement and verification of that new algorithm. The simulation results show that the performance of the platform is highly close to the theoretical value.

  6. Interfacing Space Communications and Navigation Network Simulation with Distributed System Integration Laboratories (DSIL)

    Science.gov (United States)

    Jennings, Esther H.; Nguyen, Sam P.; Wang, Shin-Ywan; Woo, Simon S.

    2008-01-01

    NASA's planned Lunar missions will involve multiple NASA centers where each participating center has a specific role and specialization. In this vision, the Constellation program (CxP)'s Distributed System Integration Laboratories (DSIL) architecture consist of multiple System Integration Labs (SILs), with simulators, emulators, testlabs and control centers interacting with each other over a broadband network to perform test and verification for mission scenarios. To support the end-to-end simulation and emulation effort of NASA' exploration initiatives, different NASA centers are interconnected to participate in distributed simulations. Currently, DSIL has interconnections among the following NASA centers: Johnson Space Center (JSC), Kennedy Space Center (KSC), Marshall Space Flight Center (MSFC) and Jet Propulsion Laboratory (JPL). Through interconnections and interactions among different NASA centers, critical resources and data can be shared, while independent simulations can be performed simultaneously at different NASA locations, to effectively utilize the simulation and emulation capabilities at each center. Furthermore, the development of DSIL can maximally leverage the existing project simulation and testing plans. In this work, we describe the specific role and development activities at JPL for Space Communications and Navigation Network (SCaN) simulator using the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to simulate communications effects among mission assets. Using MACHETE, different space network configurations among spacecrafts and ground systems of various parameter sets can be simulated. Data that is necessary for tracking, navigation, and guidance of spacecrafts such as Crew Exploration Vehicle (CEV), Crew Launch Vehicle (CLV), and Lunar Relay Satellite (LRS) and orbit calculation data are disseminated to different NASA centers and updated periodically using the High Level Architecture (HLA). In

  7. Modeling a Large Data Acquisition Network in a Simulation Framework

    CERN Document Server

    Colombo, Tommaso; The ATLAS collaboration

    2015-01-01

    The ATLAS detector at CERN records particle collision “events” delivered by the Large Hadron Collider. Its data-acquisition system is a distributed software system that identifies, selects, and stores interesting events in near real-time, with an aggregate throughput of several 10 GB/s. It is a distributed software system executed on a farm of roughly 2000 commodity worker nodes communicating via TCP/IP on an Ethernet network. Event data fragments are received from the many detector readout channels and are buffered, collected together, analyzed and either stored permanently or discarded. This system, and data-acquisition systems in general, are sensitive to the latency of the data transfer from the readout buffers to the worker nodes. Challenges affecting this transfer include the many-to-one communication pattern and the inherently bursty nature of the traffic. In this paper we introduce the main performance issues brought about by this workload, focusing in particular on the so-called TCP incast pathol...

  8. Simulation and Noise Analysis of Multimedia Transmission in Optical CDMA Computer Networks

    Directory of Open Access Journals (Sweden)

    Nasaruddin Nasaruddin

    2013-09-01

    Full Text Available This paper simulates and analyzes noise of multimedia transmission in a flexible optical code division multiple access (OCDMA computer network with different quality of service (QoS requirements. To achieve multimedia transmission in OCDMA, we have proposed strict variable-weight optical orthogonal codes (VW-OOCs, which can guarantee the smallest correlation value of one by the optimal design. In developing multimedia transmission for computer network, a simulation tool is essential in analyzing the effectiveness of various transmissions of services. In this paper, implementation models are proposed to analyze the multimedia transmission in the representative of OCDMA computer networks by using MATLAB simulink tools. Simulation results of the models are discussed including spectrums outputs of transmitted signals, superimposed signals, received signals, and eye diagrams with and without noise. Using the proposed models, multimedia OCDMA computer network using the strict VW-OOC is practically evaluated. Furthermore, system performance is also evaluated by considering avalanche photodiode (APD noise and thermal noise. The results show that the system performance depends on code weight, received laser power, APD noise, and thermal noise which should be considered as important parameters to design and implement multimedia transmission in OCDMA computer networks.

  9. An enhanced simulated annealing routing algorithm for semi-diagonal torus network

    Science.gov (United States)

    Adzhar, Noraziah; Salleh, Shaharuddin

    2017-09-01

    Multiprocessor is another great technology that helps in advancing human civilization due to high demands for solving complex problems. A multiprocessing system can have a lot of replicated processor-memory pairs (henceforth regard as net) or also called as processing nodes. Each of these nodes is connected to each other through interconnection networks and passes message using a standard message passing mechanism. In this paper, we present a routing algorithm based on enhanced simulated annealing technique to provide the connection between nodes in a semi-diagonal torus (SD-Torus) network. This network is both symmetric and regular; thus, make it very beneficial in the implementation process. The main objective is to maximize the number of established connection between nodes in this SD-Torus network. In order to achieve this objective, each node must be connected in its shortest way as possible. We start our algorithm by designing shortest path algorithm based on Dijkstra’s method. While this algorithm guarantees to find the shortest path for each single net, if it exists, each routed net will form obstacle for later paths. This increases the complexity to route later nets and makes routing longer than optimal, or sometimes impossible to complete. The solution is further refined by re-routing all nets in different orders using simulated annealing method. Through simulation program, our proposed algorithm succeeded in performing complete routing up to 81 nodes with 40 nets in 9×9 SD-Torus network size.

  10. Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

    Science.gov (United States)

    Calvin, Nicholas T; J McDowell, J

    2015-11-01

    For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Simulation and Noise Analysis of Multimedia Transmission in Optical CDMA Computer Networks

    Directory of Open Access Journals (Sweden)

    Nasaruddin

    2009-11-01

    Full Text Available This paper simulates and analyzes noise of multimedia transmission in a flexible optical code division multiple access (OCDMA computer network with different quality of service (QoS requirements. To achieve multimedia transmission in OCDMA, we have proposed strict variable-weight optical orthogonal codes (VW-OOCs, which can guarantee the smallest correlation value of one by the optimal design. In developing multimedia transmission for computer network, a simulation tool is essential in analyzing the effectiveness of various transmissions of services. In this paper, implementation models are proposed to analyze the multimedia transmission in the representative of OCDMA computer networks by using MATLAB simulink tools. Simulation results of the models are discussed including spectrums outputs of transmitted signals, superimposed signals, received signals, and eye diagrams with and without noise. Using the proposed models, multimedia OCDMA computer network using the strict VW-OOC is practically evaluated. Furthermore, system performance is also evaluated by considering avalanche photodiode (APD noise and thermal noise. The results show that the system performance depends on code weight, received laser power, APD noise, and thermal noise which should be considered as important parameters to design and implement multimedia transmission in OCDMA computer networks.

  12. Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

    Directory of Open Access Journals (Sweden)

    Joshua Rodewald

    2016-10-01

    Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

  13. Lattice Boltzmann simulation of fluid flow in fracture networks with rough, self-affine surfaces.

    Science.gov (United States)

    Madadi, Mahyar; Sahimi, Muhammad

    2003-02-01

    Using the lattice Boltzmann method, we study fluid flow in a two-dimensional (2D) model of fracture network of rock. Each fracture in a square network is represented by a 2D channel with rough, self-affine internal surfaces. Various parameters of the model, such as the connectivity and the apertures of the fractures, the roughness profile of their surface, as well as the Reynolds number for flow of the fluid, are systematically varied in order to assess their effect on the effective permeability of the fracture network. The distribution of the fractures' apertures is approximated well by a log-normal distribution, which is consistent with experimental data. Due to the roughness of the fractures' surfaces, and the finite size of the networks that can be used in the simulations, the fracture network is anisotropic. The anisotropy increases as the connectivity of the network decreases and approaches the percolation threshold. The effective permeability K of the network follows the power law K approximately (beta), where is the average aperture of the fractures in the network and the exponent beta may depend on the roughness exponent. A crossover from linear to nonlinear flow regime is obtained at a Reynolds number Re approximately O(1), but the precise numerical value of the crossover Re depends on the roughness of the fractures' surfaces.

  14. Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

    Science.gov (United States)

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

    2016-01-01

    It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

  15. Simulation and evaluation of urban rail transit network based on multi-agent approach

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2013-03-01

    Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

  16. Distributed Particle Swarm Optimization and Simulated Annealing for Energy-efficient Coverage in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2007-05-01

    Full Text Available The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, we focus on energy-efficient coverage with distributed particle swarm optimization and simulated annealing. First, the energy-efficient coverage problem is formulated with sensing coverage and energy consumption models. We consider the network composed of stationary and mobile nodes. Second, coverage and energy metrics are presented to evaluate the coverage rate and energy consumption of a wireless sensor network, where a grid exclusion algorithm extracts the coverage state and Dijkstra’s algorithm calculates the lowest cost path for communication. Then, a hybrid algorithm optimizes the energy consumption, in which particle swarm optimization and simulated annealing are combined to find the optimal deployment solution in a distributed manner. Simulated annealing is performed on multiple wireless sensor nodes, results of which are employed to correct the local and global best solution of particle swarm optimization. Simulations of wireless sensor node deployment verify that coverage performance can be guaranteed, energy consumption of communication is conserved after deployment optimization and the optimization performance is boosted by the distributed algorithm. Moreover, it is demonstrated that energy efficiency of wireless sensor networks is enhanced by the proposed optimization algorithm in target tracking applications.

  17. Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

    Science.gov (United States)

    Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

    2011-01-01

    Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

  18. Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2017-01-01

    Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

  19. Simulation of emotions of agents in virtual environments using neural networks

    NARCIS (Netherlands)

    van Kesteren, A.-J.; van Kesteren, A.J.; op den Akker, Hendrikus J.A.; Poel, Mannes; Jokinen, K.; Heylen, Dirk K.J.; Nijholt, Antinus

    2000-01-01

    A distributed architecture for a system simulating the emotional state of an agent acting in a virtual environment is presented. The system is an implementation of an event appraisal model of emotional behaviour and uses neural networks to learn how the emotional state should be influenced by the

  20. Neural networks simulation of a discrete model of continious effects of irrelevant stimuli

    NARCIS (Netherlands)

    Molenaar, P.C.M.

    1990-01-01

    Presents a general simulation method based on minimal neural network representations of nonmathematical, structural models of information processes. The time-dependent behavior of each component in a given structural model is represented by a simple, noncommittal equation that does not affect the

  1. Use of a neural network to extract a missile flight model for simulation purposes

    Science.gov (United States)

    Pascale, Danny; Volckaert, Guy

    1996-03-01

    A neural network is used to extract the flight model of guided, short to medium range, tripod and shoulder-fired missile systems which is then integrated into a training simulator. The simulator uses injected video to replace the optical sight and is fitted with a multi-axis positioning system which senses the gunner's movement. The movement creates an image shift and affects the input data to the missile control algorithm. Accurate flight dynamics are a key to efficient training, particularly in the case of closed loop guided systems. However, flight model data is not always available, either because it is proprietary, or because it is too complex to embed in a real time simulator. A solution is to reverse engineer the flight model by analyzing the missile's response when submitted to typical input conditions. Training data can be extracted from either recorded video or from a combination of weapon and missile positioning data. The video camera can be located either on the weapon or attached to a through-sight adapter. No knowledge of the missile flight transfer function is used in the process. The data is fed to a three-layer back-propagation type neural network. The network is configured within a standard spreadsheet application and is optimized with the built-in solver functions. The structure of the network, the selected inputs and outputs, as well as training data, output data after training, and output data when embedded in the simulator are presented.

  2. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks

    Science.gov (United States)

    Slepoy, Alexander; Thompson, Aidan P.; Plimpton, Steven J.

    2008-05-01

    The time evolution of species concentrations in biochemical reaction networks is often modeled using the stochastic simulation algorithm (SSA) [Gillespie, J. Phys. Chem. 81, 2340 (1977)]. The computational cost of the original SSA scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [Gibson and Bruck, J. Phys. Chem. A 104, 1876 (2000)]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure. While applicable to kinetic Monte Carlo simulations in general, we describe the algorithm in the context of biochemical simulations and demonstrate its competitive performance on small- and medium-size networks, as well as its superior constant-time performance on very large networks, which are becoming necessary to represent the increasing complexity of biochemical data for pathways that mediate cell function.

  3. A hybrid Genetic and Simulated Annealing Algorithm for Chordal Ring implementation in large-scale networks

    DEFF Research Database (Denmark)

    Riaz, M. Tahir; Gutierrez Lopez, Jose Manuel; Pedersen, Jens Myrup

    2011-01-01

    of the networks. There have been many use of evolutionary algorithms to solve the problems which are in combinatory complexity nature, and extremely hard to solve by exact approaches. Both Genetic and Simulated annealing algorithms are similar in using controlled stochastic method to search the solution...

  4. Largenet2: an object-oriented programming library for simulating large adaptive networks.

    Science.gov (United States)

    Zschaler, Gerd; Gross, Thilo

    2013-01-15

    The largenet2 C++ library provides an infrastructure for the simulation of large dynamic and adaptive networks with discrete node and link states. The library is released as free software. It is available at http://biond.github.com/largenet2. Largenet2 is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. gerd@biond.org

  5. Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics

    DEFF Research Database (Denmark)

    Papaleo, Elena

    2015-01-01

    that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome...... simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations....

  6. An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

    Science.gov (United States)

    Leon, Barbara D.; Heller, Paul R.

    1987-05-01

    A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system

  7. Cellular neural network modelling of soft tissue dynamics for surgical simulation.

    Science.gov (United States)

    Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

    2017-07-20

    Currently, the mechanical dynamics of soft tissue deformation is achieved by numerical time integrations such as the explicit or implicit integration; however, the explicit integration is stable only under a small time step, whereas the implicit integration is computationally expensive in spite of the accommodation of a large time step. This paper presents a cellular neural network method for stable simulation of soft tissue deformation dynamics. The non-rigid motion equation is formulated as a cellular neural network with local connectivity of cells, and thus the dynamics of soft tissue deformation is transformed into the neural dynamics of the cellular neural network. Results show that the proposed method can achieve good accuracy at a small time step. It still remains stable at a large time step, while maintaining the computational efficiency of the explicit integration. The proposed method can achieve stable soft tissue deformation with efficiency of explicit integration for surgical simulation.

  8. Simulating Local Area Network Protocols with the General Purpose Simulation System (GPSS)

    Science.gov (United States)

    1990-03-01

    because of insufficient buffer capacity ), and the mean transmitter and receiver utilisations. Figure 11 shows that the buffer overflow probability is...made. (1) Infinite buffer capacity at each station (2) 1 M bit/s data rate (3) Network of 50 stations equally spaced over a 2000 m length ring (4

  9. Fractional Diffusion Emulates a Human Mobility Network during a Simulated Disease Outbreak

    Directory of Open Access Journals (Sweden)

    Kyle B. Gustafson

    2017-04-01

    Full Text Available Mobility networks facilitate the growth of populations, the success of invasive species, and the spread of communicable diseases among social animals, including humans. Disease control and elimination efforts, especially during an outbreak, can be optimized by numerical modeling of disease dynamics on transport networks. This is especially true when incidence data from an emerging epidemic is sparse and unreliable. However, mobility networks can be complex, challenging to characterize, and expensive to simulate with agent-based models. We therefore studied a parsimonious model for spatiotemporal disease dynamics based on a fractional diffusion equation. We implemented new stochastic simulations of a prototypical influenza-like infection spreading through the United States' highly-connected air travel network. We found that the national-averaged infected fraction during an outbreak is accurately reproduced by a space-fractional diffusion equation consistent with the connectivity of airports. Fractional diffusion therefore seems to be a better model of network outbreak dynamics than a diffusive model. Our fractional reaction-diffusion method and the result could be extended to other mobility networks in a variety of applications for population dynamics.

  10. Building Model for the University of Mosul Computer Network Using OPNET Simulator

    Directory of Open Access Journals (Sweden)

    Modhar Modhar A. Hammoudi

    2013-04-01

    Full Text Available This paper aims at establishing a model in OPNET (Optimized Network Engineering Tool simulator for the University of Mosul computer network. The proposed network model was made up of two routers (Cisco 2600, core switch (Cisco6509, two servers, ip 32 cloud and 37 VLANs. These VLANs were connected to the core switch using fiber optic cables (1000BaseX. Three applications were added to test the network model. These applications were FTP (File Transfer Protocol, HTTP (Hyper Text Transfer Protocol and VoIP (Voice over Internet Protocol. The results showed that the proposed model had a positive efficiency on designing and managing the targeted network and can be used to view the data flow in it. Also, the simulation results showed that the maximum number of VoIP service users could be raised upto 5000 users when working under IP Telephony. This means that the ability to utilize VoIP service in this network can be maintained and is better when subjected to IP telephony scheme.

  11. Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

    Science.gov (United States)

    Davis, Paul; Boisvert, Benjamin

    2017-01-01

    The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

  12. Architecture for an integrated real-time air combat and sensor network simulation

    Science.gov (United States)

    Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara

    2007-04-01

    An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.

  13. Simulated Annealing Technique for Routing in a Rectangular Mesh Network

    Directory of Open Access Journals (Sweden)

    Noraziah Adzhar

    2014-01-01

    Full Text Available In the process of automatic design for printed circuit boards (PCBs, the phase following cell placement is routing. On the other hand, routing process is a notoriously difficult problem, and even the simplest routing problem which consists of a set of two-pin nets is known to be NP-complete. In this research, our routing region is first tessellated into a uniform Nx×Ny array of square cells. The ultimate goal for a routing problem is to achieve complete automatic routing with minimal need for any manual intervention. Therefore, shortest path for all connections needs to be established. While classical Dijkstra’s algorithm guarantees to find shortest path for a single net, each routed net will form obstacles for later paths. This will add complexities to route later nets and make its routing longer than the optimal path or sometimes impossible to complete. Today’s sequential routing often applies heuristic method to further refine the solution. Through this process, all nets will be rerouted in different order to improve the quality of routing. Because of this, we are motivated to apply simulated annealing, one of the metaheuristic methods to our routing model to produce better candidates of sequence.

  14. Teleradiology system analysis using a discrete event-driven block-oriented network simulator

    Science.gov (United States)

    Stewart, Brent K.; Dwyer, Samuel J., III

    1992-07-01

    Performance evaluation and trade-off analysis are the central issues in the design of communication networks. Simulation plays an important role in computer-aided design and analysis of communication networks and related systems, allowing testing of numerous architectural configurations and fault scenarios. We are using the Block Oriented Network Simulator (BONeS, Comdisco, Foster City, CA) software package to perform discrete, event- driven Monte Carlo simulations in capacity planning, tradeoff analysis and evaluation of alternate architectures for a high-speed, high-resolution teleradiology project. A queuing network model of the teleradiology system has been devise, simulations executed and results analyzed. The wide area network link uses a switched, dial-up N X 56 kbps inverting multiplexer where the number of digital voice-grade lines (N) can vary from one (DS-0) through 24 (DS-1). The proposed goal of such a system is 200 films (2048 X 2048 X 12-bit) transferred between a remote and local site in an eight hour period with a mean delay time less than five minutes. It is found that: (1) the DS-1 service limit is around 100 films per eight hour period with a mean delay time of 412 +/- 39 seconds, short of the goal stipulated above; (2) compressed video teleconferencing can be run simultaneously with image data transfer over the DS-1 wide area network link without impacting the performance of the described teleradiology system; (3) there is little sense in upgrading to a higher bandwidth WAN link like DS-2 or DS-3 for the current system; and (4) the goal of transmitting 200 films in an eight hour period with a mean delay time less than five minutes can be achieved simply if the laser printer interface is updated from the current DR-11W interface to a much faster SCSI interface.

  15. Simulating microinjection experiments in a novel model of the rat sleep-wake regulatory network.

    Science.gov (United States)

    Diniz Behn, Cecilia G; Booth, Victoria

    2010-04-01

    This study presents a novel mathematical modeling framework that is uniquely suited to investigating the structure and dynamics of the sleep-wake regulatory network in the brain stem and hypothalamus. It is based on a population firing rate model formalism that is modified to explicitly include concentration levels of neurotransmitters released to postsynaptic populations. Using this framework, interactions among primary brain stem and hypothalamic neuronal nuclei involved in rat sleep-wake regulation are modeled. The model network captures realistic rat polyphasic sleep-wake behavior consisting of wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep states. Network dynamics include a cyclic pattern of NREM sleep, REM sleep, and wake states that is disrupted by simulated variability of neurotransmitter release and external noise to the network. Explicit modeling of neurotransmitter concentrations allows for simulations of microinjections of neurotransmitter agonists and antagonists into a key wake-promoting population, the locus coeruleus (LC). Effects of these simulated microinjections on sleep-wake states are tracked and compared with experimental observations. Agonist/antagonist pairs, which are presumed to have opposing effects on LC activity, do not generally induce opposing effects on sleep-wake patterning because of multiple mechanisms for LC activation in the network. Also, different agents, which are presumed to have parallel effects on LC activity, do not induce parallel effects on sleep-wake patterning because of differences in the state dependence or independence of agonist and antagonist action. These simulation results highlight the utility of formal mathematical modeling for constraining conceptual models of the sleep-wake regulatory network.

  16. SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method.

    Science.gov (United States)

    Bernal, Javier; Torres-Jimenez, Jose

    2015-01-01

    SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.

  17. Efficient Constant-Time Complexity Algorithm for Stochastic Simulation of Large Reaction Networks.

    Science.gov (United States)

    Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado

    2017-01-01

    Exact stochastic simulation is an indispensable tool for a quantitative study of biochemical reaction networks. The simulation realizes the time evolution of the model by randomly choosing a reaction to fire and update the system state according to a probability that is proportional to the reaction propensity. Two computationally expensive tasks in simulating large biochemical networks are the selection of next reaction firings and the update of reaction propensities due to state changes. We present in this work a new exact algorithm to optimize both of these simulation bottlenecks. Our algorithm employs the composition-rejection on the propensity bounds of reactions to select the next reaction firing. The selection of next reaction firings is independent of the number reactions while the update of propensities is skipped and performed only when necessary. It therefore provides a favorable scaling for the computational complexity in simulating large reaction networks. We benchmark our new algorithm with the state of the art algorithms available in literature to demonstrate its applicability and efficiency.

  18. Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

    Directory of Open Access Journals (Sweden)

    Wang Chao

    2016-03-01

    Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

  19. Operator Splitting Method for Simulation of Dynamic Flows in Natural Gas Pipeline Networks

    CERN Document Server

    Dyachenko, Sergey A; Chertkov, Michael

    2016-01-01

    We develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.

  20. Simulation of Missile Autopilot with Two-Rate Hybrid Neural Network System

    Directory of Open Access Journals (Sweden)

    ASTROV, I.

    2007-04-01

    Full Text Available This paper proposes a two-rate hybrid neural network system, which consists of two artificial neural network subsystems. These neural network subsystems are used as the dynamic subsystems controllers.1 This is because such neuromorphic controllers are especially suitable to control complex systems. An illustrative example - two-rate neural network hybrid control of decomposed stochastic model of a rigid guided missile over different operating conditions - was carried out using the proposed two-rate state-space decomposition technique. This example demonstrates that this research technique results in simplified low-order autonomous control subsystems with various speeds of actuation, and shows the quality of the proposed technique. The obtained results show that the control tasks for the autonomous subsystems can be solved more qualitatively than for the original system. The simulation and animation results with use of software package Simulink demonstrate that this research technique would work for real-time stochastic systems.

  1. Operator splitting method for simulation of dynamic flows in natural gas pipeline networks

    Science.gov (United States)

    Dyachenko, Sergey A.; Zlotnik, Anatoly; Korotkevich, Alexander O.; Chertkov, Michael

    2017-12-01

    We develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.

  2. Simulation of unsteady flow and solute transport in a tidal river network

    Science.gov (United States)

    Zhan, X.

    2003-01-01

    A mathematical model and numerical method for water flow and solute transport in a tidal river network is presented. The tidal river network is defined as a system of open channels of rivers with junctions and cross sections. As an example, the Pearl River in China is represented by a network of 104 channels, 62 nodes, and a total of 330 cross sections with 11 boundary section for one of the applications. The simulations are performed with a supercomputer for seven scenarios of water flow and/or solute transport in the Pearl River, China, with different hydrological and weather conditions. Comparisons with available data are shown. The intention of this study is to summarize previous works and to provide a useful tool for water environmental management in a tidal river network, particularly for the Pearl River, China.

  3. Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.

    Science.gov (United States)

    Stetz, Gabrielle; Verkhivker, Gennady M

    2015-01-01

    Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations

  4. How the ownership structures cause epidemics in financial markets: A network-based simulation model

    Science.gov (United States)

    Dastkhan, Hossein; Gharneh, Naser Shams

    2018-02-01

    Analysis of systemic risks and contagions is one of the main challenges of policy makers and researchers in the recent years. Network theory is introduced as a main approach in the modeling and simulation of financial and economic systems. In this paper, a simulation model is introduced based on the ownership network to analyze the contagion and systemic risk events. For this purpose, different network structures with different values for parameters are considered to investigate the stability of the financial system in the presence of different kinds of idiosyncratic and aggregate shocks. The considered network structures include Erdos-Renyi, core-periphery, segregated and power-law networks. Moreover, the results of the proposed model are also calculated for a real ownership network. The results show that the network structure has a significant effect on the probability and the extent of contagion in the financial systems. For each network structure, various values for the parameters results in remarkable differences in the systemic risk measures. The results of real case show that the proposed model is appropriate in the analysis of systemic risk and contagion in financial markets, identification of systemically important firms and estimation of market loss when the initial failures occur. This paper suggests a new direction in the modeling of contagion in the financial markets, in particular that the effects of new kinds of financial exposure are clarified. This paper's idea and analytical results may also be useful for the financial policy makers, portfolio managers and the firms to conduct their investment in the right direction.

  5. Extension and Validation of a Hybrid Particle-Finite Element Method for Hypervelocity Impact Simulation. Chapter 2

    Science.gov (United States)

    Fahrenthold, Eric P.; Shivarama, Ravishankar

    2004-01-01

    The hybrid particle-finite element method of Fahrenthold and Horban, developed for the simulation of hypervelocity impact problems, has been extended to include new formulations of the particle-element kinematics, additional constitutive models, and an improved numerical implementation. The extended formulation has been validated in three dimensional simulations of published impact experiments. The test cases demonstrate good agreement with experiment, good parallel speedup, and numerical convergence of the simulation results.

  6. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

    Directory of Open Access Journals (Sweden)

    Mikael eDjurfeldt

    2014-04-01

    Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  7. Numerical Simulation of Fluid Flow through Fractal-Based Discrete Fractured Network

    Directory of Open Access Journals (Sweden)

    Wendong Wang

    2018-01-01

    Full Text Available Abstract: In recent years, multi-stage hydraulic fracturing technologies have greatly facilitated the development of unconventional oil and gas resources. However, a quantitative description of the “complexity” of the fracture network created by the hydraulic fracturing is confronted with many unsolved challenges. Given the multiple scales and heterogeneity of the fracture system, this study proposes a “bifurcated fractal” model to quantitatively describe the distribution of induced hydraulic fracture networks. The construction theory is employed to generate hierarchical fracture patterns as a scaled numerical model. With the implementation of discrete fractal-fracture network modeling (DFFN, fluid flow characteristics in bifurcated fractal fracture networks are characterized. The effects of bifurcated fracture length, bifurcated tendency, and number of bifurcation stages are examined. A field example of the fractured horizontal well is introduced to calibrate the accuracy of the flow model. The proposed model can provide a more realistic representation of complex fracture networks around a fractured horizontal well, and offer the way to quantify the “complexity” of the fracture network in shale reservoirs. The simulation results indicate that the geometry of the bifurcated fractal fracture network model has a significant impact on production performance in the tight reservoir, and enhancing connectivity of each bifurcate fracture is the key to improve the stimulation performance. In practice, this work provides a novel and efficient workflow for complex fracture characterization and production prediction in naturally-fractured reservoirs of multi-stage fractured horizontal wells.

  8. Unified pipe network method for simulation of water flow in fractured porous rock

    Science.gov (United States)

    Ren, Feng; Ma, Guowei; Wang, Yang; Li, Tuo; Zhu, Hehua

    2017-04-01

    Rock masses are often conceptualized as dual-permeability media containing fractures or fracture networks with high permeability and porous matrix that is less permeable. In order to overcome the difficulties in simulating fluid flow in a highly discontinuous dual-permeability medium, an effective unified pipe network method is developed, which discretizes the dual-permeability rock mass into a virtual pipe network system. It includes fracture pipe networks and matrix pipe networks. They are constructed separately based on equivalent flow models in a representative area or volume by taking the advantage of the orthogonality of the mesh partition. Numerical examples of fluid flow in 2-D and 3-D domain including porous media and fractured porous media are presented to demonstrate the accuracy, robustness, and effectiveness of the proposed unified pipe network method. Results show that the developed method has good performance even with highly distorted mesh. Water recharge into the fractured rock mass with complex fracture network is studied. It has been found in this case that the effect of aperture change on the water recharge rate is more significant in the early stage compared to the fracture density change.

  9. USING THE RANDOM OF QUANTIZATION IN THE SIMULATION OF NETWORKED CONTROL SYSTEMS

    Directory of Open Access Journals (Sweden)

    V. K. Bitiukov

    2014-01-01

    Full Text Available Network control systems using a network channel for communication between the elements. This approach has several advantages: lower installation costs, ease of configuration, ease of diagnostics and maintenance. The use of networks in control systems poses new problems. The network characteristics make the analysis, modeling, and control of networked control systems more complex and challenging. In the simulation must consider the following factors: packet loss, packet random time over the network, the need for location records in a channel simultaneously multiple data packets with sequential transmission. Attempts to account at the same time all of these factors lead to a significant increase in the dimension of the mathematical model and, as a con-sequence, a significant computational challenges. Such models tend to have a wide application in research. However, for engineering calculations required mathematical models of small dimension, but at the same time having sufficient accuracy. Considered the networks channels with random delays and packet loss. Random delay modeled by appropriate distribution the Erlang. The probability of packet loss depends on the arrival rate of data packets in the transmission channel, and the parameters of the distribution Erlang. We propose a model of the channel in the form of a serial connection of discrete elements. Discrete elements produce independents quantization of the input signal. To change the probability of packet loss is proposed to use a random quantization input signal. Obtained a formula to determine the probability of packet loss during transmission.

  10. PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation.

    Science.gov (United States)

    Cao, Buwen; Luo, Jiawei; Liang, Cheng; Wang, Shulin; Ding, Pingjian

    2016-10-01

    Identifying overlapping protein complexes in protein-protein interaction (PPI) networks can provide insight into cellular functional organization and thus elucidate underlying cellular mechanisms. Recently, various algorithms for protein complexes detection have been developed for PPI networks. However, majority of algorithms primarily depend on network topological feature and/or gene expression profile, failing to consider the inherent biological meanings between protein pairs. In this paper, we propose a novel method to detect protein complexes using pseudo-clique extension based on fuzzy relation (PCE-FR). Our algorithm operates in three stages: it first forms the nonoverlapping protein substructure based on fuzzy relation and then expands each substructure by adding neighbor proteins to maximize the cohesive score. Finally, highly overlapped candidate protein complexes are merged to form the final protein complex set. Particularly, our algorithm employs the biological significance hidden in protein pairs to construct edge weight for protein interaction networks. The experiment results show that our method can not only outperform classical algorithms such as CFinder, ClusterONE, CMC, RRW, HC-PIN, and ProRank +, but also achieve ideal overall performance in most of the yeast PPI datasets in terms of composite score consisting of precision, accuracy, and separation. We further apply our method to a human PPI network from the HPRD dataset and demonstrate it is very effective in detecting protein complexes compared to other algorithms.

  11. Matching the reaction-diffusion simulation to dynamic [18F]FMISO PET measurements in tumors: extension to a flow-limited oxygen-dependent model.

    Science.gov (United States)

    Shi, Kuangyu; Bayer, Christine; Gaertner, Florian C; Astner, Sabrina T; Wilkens, Jan J; Nüsslin, Fridtjof; Vaupel, Peter; Ziegler, Sibylle I

    2017-02-01

    Positron-emission tomography (PET) with hypoxia specific tracers provides a noninvasive method to assess the tumor oxygenation status. Reaction-diffusion models have advantages in revealing the quantitative relation between in vivo imaging and the tumor microenvironment. However, there is no quantitative comparison of the simulation results with the real PET measurements yet. The lack of experimental support hampers further applications of computational simulation models. This study aims to compare the simulation results with a preclinical [18F]FMISO PET study and to optimize the reaction-diffusion model accordingly. Nude mice with xenografted human squamous cell carcinomas (CAL33) were investigated with a 2 h dynamic [18F]FMISO PET followed by immunofluorescence staining using the hypoxia marker pimonidazole and the endothelium marker CD 31. A large data pool of tumor time-activity curves (TAC) was simulated for each mouse by feeding the arterial input function (AIF) extracted from experiments into the model with different configurations of the tumor microenvironment. A measured TAC was considered to match a simulated TAC when the difference metric was below a certain, noise-dependent threshold. As an extension to the well-established Kelly model, a flow-limited oxygen-dependent (FLOD) model was developed to improve the matching between measurements and simulations. The matching rate between the simulated TACs of the Kelly model and the mouse PET data ranged from 0 to 28.1% (on average 9.8%). By modifying the Kelly model to an FLOD model, the matching rate between the simulation and the PET measurements could be improved to 41.2-84.8% (on average 64.4%). Using a simulation data pool and a matching strategy, we were able to compare the simulated temporal course of dynamic PET with in vivo measurements. By modifying the Kelly model to a FLOD model, the computational simulation was able to approach the dynamic [18F]FMISO measurements in the investigated tumors.

  12. A vascular image registration method based on network structure and circuit simulation.

    Science.gov (United States)

    Chen, Li; Lian, Yuxi; Guo, Yi; Wang, Yuanyuan; Hatsukami, Thomas S; Pimentel, Kristi; Balu, Niranjan; Yuan, Chun

    2017-05-02

    Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods.

  13. Simulating urban growth by emphasis on connective routes network (case study: Bojnourd city

    Directory of Open Access Journals (Sweden)

    Mehdi Saadat Novin

    2017-06-01

    Full Text Available Development of urban construction and ever-increasing growth of population lead to landuse changes especially in agricultural lands, which play an important role in providing human food. According to this issue, a proper landuse planning is required to protecting and preserving the valuable agricultural lands and environment, in today’s world. The prediction of urban growth can help in understanding the potential impacts on a region’s water resource, economy and people. One of the effective parameters in development of cities is connective routes network and their different types and qualities that play an important role in decreasing or increasing the growth of the city. On the other hand, the type of the connective routes network is an important factor for the speed and quality of development. In this paper, two different scenarios were used to simulate landuse changes and analyzing their results. In first scenario, modeling is based on the effective parameters in urban growth without classification of connective routes network. In the second scenario, effective parameters in urban growth were considered and connective routes were classified in 6 different classes with different weights in order to examine their effect on urban development. Simulation of landuse has been carried out for 2020–2050. The results clearly showed the effect of the connective routes network classification in output maps so that the effect of the first and second main routes network in development, is conspicuous.

  14. Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer.

    Science.gov (United States)

    ElKalaawy, Nesma; Wassal, Amr

    2015-03-01

    Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Simulated apoptosis/neurogenesis regulates learning and memory capabilities of adaptive neural networks.

    Science.gov (United States)

    Chambers, R Andrew; Potenza, Marc N; Hoffman, Ralph E; Miranker, Willard

    2004-04-01

    Characterization of neuronal death and neurogenesis in the adult brain of birds, humans, and other mammals raises the possibility that neuronal turnover represents a special form of neuroplasticity associated with stress responses, cognition, and the pathophysiology and treatment of psychiatric disorders. Multilayer neural network models capable of learning alphabetic character representations via incremental synaptic connection strength changes were used to assess additional learning and memory effects incurred by simulation of coordinated apoptotic and neurogenic events in the middle layer. Using a consistent incremental learning capability across all neurons and experimental conditions, increasing the number of middle layer neurons undergoing turnover increased network learning capacity for new information, and increased forgetting of old information. Simulations also showed that specific patterns of neural turnover based on individual neuronal connection characteristics, or the temporal-spatial pattern of neurons chosen for turnover during new learning impacts new learning performance. These simulations predict that apoptotic and neurogenic events could act together to produce specific learning and memory effects beyond those provided by ongoing mechanisms of connection plasticity in neuronal populations. Regulation of rates as well as patterns of neuronal turnover may serve an important function in tuning the informatic properties of plastic networks according to novel informational demands. Analogous regulation in the hippocampus may provide for adaptive cognitive and emotional responses to novel and stressful contexts, or operate suboptimally as a basis for psychiatric disorders. The implications of these elementary simulations for future biological and neural modeling research on apoptosis and neurogenesis are discussed.

  16. Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

    Science.gov (United States)

    Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

    2016-09-01

    The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

  17. Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation.

    Science.gov (United States)

    Anderson, William S; Kudela, Pawel; Weinberg, Seth; Bergey, Gregory K; Franaszczuk, Piotr J

    2009-03-01

    A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of the evolving bursting activity, as well as effects due to network stimulation. The model represents a cortical region of 1.6 mm x 1.6mm, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. There are a total of 65,536 modeled single compartment neurons that operate according to a version of Hodgkin-Huxley dynamics. The intercellular wiring is based on histological studies and our previous modeling efforts. The bursting phase is characterized by a flat frequency spectrum. Stimulation pulses are applied to this modeled network, with an electric field provided by a 1mm radius circular electrode represented mathematically in the simulation. A phase dependence to the post-stimulation quiescence is demonstrated, with local relative maxima in efficacy occurring before or during the network depolarization phase in the underlying activity. Brief periods of network insensitivity to stimulation are also demonstrated. The phase dependence was irregular and did not reach statistical significance when averaged over the full 2.5s of simulated bursting investigated. This result provides comparison with previous in vivo studies which have also demonstrated increased efficacy of stimulation when pulses are applied at the peak of the local field potential during cortical after discharges. The network bursting is synchronous when comparing the different neuron classes represented up to an uncertainty of 10 ms. Studies performed with an excitatory chandelier cell component demonstrated increased synchronous bursting in the model, as predicted from

  18. An Efficient Neural Network Based Modeling Method for Automotive EMC Simulation

    Science.gov (United States)

    Frank, Florian; Weigel, Robert

    2011-09-01

    This paper presents a newly developed methodology for VHDL-AMS model integration into SPICE-based EMC simulations. To this end the VHDL-AMS model, which is available in a compiled version only, is characterized under typical loading conditions, and afterwards a neural network based technique is applied to convert characteristic voltage and current data into an equivalent circuit in SPICE syntax. After the explanation of the whole method and the presentation of a newly developed switched state space dynamic neural network model, the entire analysis process is demonstrated using a typical application from automotive industry.

  19. A Cut Cell Method for Simulating Spatial Models of Biochemical Reaction Networks in Arbitrary Geometries.

    Science.gov (United States)

    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C

    2010-01-01

    Cells use signaling networks consisting of multiple interacting proteins to respond to changes in their environment. In many situations, such as chemotaxis, spatial and temporal information must be transmitted through the network. Recent computational studies have emphasized the importance of cellular geometry in signal transduction, but have been limited in their ability to accurately represent complex cell morphologies. We present a finite volume method that addresses this problem. Our method uses Cartesian cut cells and is second order in space and time. We use our method to simulate several models of signaling systems in realistic cell morphologies obtained from live cell images and examine the effects of geometry on signal transduction.

  20. Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

    Science.gov (United States)

    Samareh, Jamshid A.; Wong, Jay Ming

    2014-01-01

    Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

  1. Analyses of systems and their behaviour in extraordinary situations as based on the latest results in network sciences and extensive empirical investigations; Netzwerkanalyse fuer ein antizipatives Katastrophenmanagement

    Energy Technology Data Exchange (ETDEWEB)

    Ammoser, H. [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Kuehnert, C. [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Imperial College, London (United Kingdom); Buzna, L. [Zilina Univ. (Slovakia). Dept. of Transportation Networks

    2006-07-01

    In the context of a DFG research project, scientists of Prof. Helbing's chair at the Institute of Transport and Economics deal with the dynamics of disasters, being experienced in the modelling of complex systems and in the simulation of emergency scenarios. The analyses of systems and their behaviour in extraordinary events are based on the latest results of network sciences and on numerous empirical investigations. The results shall be used for precaution measures and innovations in disaster recovery. (orig.)

  2. DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Marília Gonçalves Dutra da Silva

    2016-04-01

    Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

  3. Simulation of A 90o Differential Phase Shifter for Korean VLBI Network 129 GHz Band Polarizer

    Directory of Open Access Journals (Sweden)

    Moon-Hee Chung

    2010-09-01

    Full Text Available A simulation for the design of a 90o differential phase shifter aimed toward Korean VLBI Network (KVN 129 GHz band polarizer is described in this paper. A dual-circular polarizer for KVN 129 GHz band consists of a 90o differential phase shifter and an orthomode transducer. The differential phase shifter is made up of a square waveguide with two opposite walls loaded with corrugations. Three-dimensional electromagnetic simulation has been performed to predict the 90o differential phase shifter’s characteristics. The simulation for the differential phase shifter shows that the phase shift is 90o ± 3.3o across 108-160 GHz and the return losses of two orthogonal modes are better than -30 dB within the design frequency band. According to the simulation results the calculated performance is quite encouraging for KVN 129 GHz band application.

  4. Efficient Uplink Modeling for Dynamic System-Level Simulations of Cellular and Mobile Networks

    Directory of Open Access Journals (Sweden)

    Lobinger Andreas

    2010-01-01

    Full Text Available A novel theoretical framework for uplink simulations is proposed. It allows investigations which have to cover a very long (real- time and which at the same time require a certain level of accuracy in terms of radio resource management, quality of service, and mobility. This is of particular importance for simulations of self-organizing networks. For this purpose, conventional system level simulators are not suitable due to slow simulation speeds far beyond real-time. Simpler, snapshot-based tools are lacking the aforementioned accuracy. The runtime improvements are achieved by deriving abstract theoretical models for the MAC layer behavior. The focus in this work is long term evolution, and the most important uplink effects such as fluctuating interference, power control, power limitation, adaptive transmission bandwidth, and control channel limitations are considered. Limitations of the abstract models will be discussed as well. Exemplary results are given at the end to demonstrate the capability of the derived framework.

  5. Methods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists

    Directory of Open Access Journals (Sweden)

    Brenton J Prettejohn

    2011-03-01

    Full Text Available Many simulations of networks in computational neuroscience assume completely homogenous random networks of the Erd"{o}s-R'{e}nyi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the `scale-free' and `small-world' properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks.

  6. Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks

    Directory of Open Access Journals (Sweden)

    Biao Xiong

    2017-01-01

    Full Text Available The effectiveness of military supply chain networks is an important reference for logistics decision-making, and it is crucial to evaluate it scientifically and accurately. This paper highlights the problem from the perspective of dynamic and discrete networks. A topological structure model with the characteristics of dynamic and discreteness is used to describe the structure of military supply chain networks (MSCNs. In order to provide a platform for evaluating the effectiveness, simulation algorithms based on topological structure models for MSCNs are presented. Considering military and economic factors, evaluation metrics including supply capability and supply efficiency are proposed. By applying the model and algorithms to a POL supply network in a theater, we obtain the values of supply capability and efficiency metrics in a dynamic environment. We also identify an optimal solution from multiple feasible solutions to help decision-makers to make scientific and rational decisions by using exploratory analysis method. The results show that new evaluation metrics can capture important effectiveness requirements for military supply networks positively. We also find the proposed method in this paper can solve the problem of evaluating the effectiveness of dynamic and discrete network effectiveness evaluation in a feasible and effective manner.

  7. Usage of link-level performance indicators for HSDPA network-level simulations in E-UMTS

    NARCIS (Netherlands)

    Brouwer, Frank; de Bruin, I.C.C.; Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Correia, Américo

    2004-01-01

    The paper describes integration of HSDPA (high-speed downlink packet access) link-level simulation results into network-level simulations for enhanced UMTS. The link-level simulations model all physical layer features depicted in the 3GPP standards. These include: generation of transport blocks;

  8. Catastrophic approach to satellite imagery utilization on network-based flight simulators

    Science.gov (United States)

    Levin, Eugene; Ternovskiy, Igor V.

    2001-11-01

    Presently, there are many technological and industrial efforts for development of virtual flight simulators, usually based on networked technologies. In order to solve the problems of real time availability and realistic quality of simulators, source data images and digital terrain models (DTM) should have some generalized structure, which supposes different imagery resolution and different amount of detail on each level of 3D simulation. One of the central problems is geotruthing of satellite imagery with realistic accuracy requirements with respect to DTM. Traditionally such geotruthing can be achieved by means of geo control points measurements. This process is labor intensive and requires special photogrammetric operator skills. In order to avoid such a process an algorithm of terrain and image models singularity's recognition based on Catastrophe theory is investigated in this paper. This approach does not require training but operates with direct comparison of the analytical manifolds from DTM with those actually extracted from the image. The technology described in this paper, the Catastrophe Approach, and algorithms of satellite imagery treatment may be implemented in a multi-level image pyramid flight simulators. Theoretical approaches and practical realization indicates that the Catastrophe Approach is easy- to-use for a final customer and can be implemented on-line to networked flight simulators.

  9. SIPSON--simulation of interaction between pipe flow and surface overland flow in networks.

    Science.gov (United States)

    Djordjević, S; Prodanović, D; Maksimović, C; Ivetić, M; Savić, D

    2005-01-01

    The new simulation model, named SIPSON, based on the Preissmann finite difference method and the conjugate gradient method, is presented in the paper. This model simulates conditions when the hydraulic capacity of a sewer system is exceeded, pipe flow is pressurized, the water flows out from the piped system to the streets, and the inlets cannot capture all the runoff. In the mathematical model, buried structures and pipelines, together with surface channels, make a horizontally and vertically looped network involving a complex interaction of flows. In this paper, special internal boundary conditions related to equivalent inlets are discussed. Procedures are described for the simulation of manhole cover loss, basement flooding, the representation of street geometry, and the distribution of runoff hydrographs between surface and underground networks. All these procedures are built into the simulation model. Relevant issues are illustrated on a set of examples, focusing on specific parameters and comparison with field measurements of flooding of the Motilal ki Chal catchment (Indore, India). Satisfactory agreement of observed and simulated hydrographs and maximum surface flooding levels is obtained. It is concluded that the presented approach is an improvement compared to the standard "virtual reservoir" approach commonly applied in most of the models.

  10. Simulation and optimization of a pulsating heat pipe using artificial neural network and genetic algorithm

    Science.gov (United States)

    Jokar, Ali; Godarzi, Ali Abbasi; Saber, Mohammad; Shafii, Mohammad Behshad

    2016-11-01

    In this paper, a novel approach has been presented to simulate and optimize the pulsating heat pipes (PHPs). The used pulsating heat pipe setup was designed and constructed for this study. Due to the lack of a general mathematical model for exact analysis of the PHPs, a method has been applied for simulation and optimization using the natural algorithms. In this way, the simulator consists of a kind of multilayer perceptron neural network, which is trained by experimental results obtained from our PHP setup. The results show that the complex behavior of PHPs can be successfully described by the non-linear structure of this simulator. The input variables of the neural network are input heat flux to evaporator (q″), filling ratio (FR) and inclined angle (IA) and its output is thermal resistance of PHP. Finally, based upon the simulation results and considering the heat pipe's operating constraints, the optimum operating point of the system is obtained by using genetic algorithm (GA). The experimental results show that the optimum FR (38.25 %), input heat flux to evaporator (39.93 W) and IA (55°) that obtained from GA are acceptable.

  11. Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

    Science.gov (United States)

    Li, Ming; Huang, Xiaobo; Kang, Zhan

    2015-08-01

    Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.

  12. Simulation of Neurocomputing Based on Photophobic Reactions of Euglena: Toward Microbe-Based Neural Network Computing

    Science.gov (United States)

    Ozasa, Kazunari; Aono, Masashi; Maeda, Mizuo; Hara, Masahiko

    In order to develop an adaptive computing system, we investigate microscopic optical feedback to a group of microbes (Euglena gracilis in this study) with a neural network algorithm, expecting that the unique characteristics of microbes, especially their strategies to survive/adapt against unfavorable environmental stimuli, will explicitly determine the temporal evolution of the microbe-based feedback system. The photophobic reactions of Euglena are extracted from experiments, and built in the Monte-Carlo simulation of a microbe-based neurocomputing. The simulation revealed a good performance of Euglena-based neurocomputing. Dynamic transition among the solutions is discussed from the viewpoint of feedback instability.

  13. Physical Properties and Hydrogen-Bonding Network of Water-Ethanol Mixtures from Molecular Dynamics Simulations.

    Science.gov (United States)

    Ghoufi, A; Artzner, F; Malfreyt, P

    2016-02-04

    While many numerical and experimental works were focused on water-ethanol mixtures at low ethanol concentration, this work reports predictions of a few physical properties (thermodynamical, interfacial, dynamical, and dielectrical properties) of water-ethanol mixture at high alcohol concentrations by means of molecular dynamics simulations. By using a standard force field a good agreement was found between experiment and molecular simulation. This was allowed us to explore the dynamics, structure, and interplay between both hydrogen-bonding networks of water and ethanol.

  14. Extension of the pulsed power supply network of ASDEX Upgrade by a set of compact modular generators

    Energy Technology Data Exchange (ETDEWEB)

    Kaesemann, C.-P., E-mail: c.p.kaesemann@ipp.mpg.de [Max-Planck-Institut fuer Plasmaphysik (IPP), EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Huart, M. [Max-Planck-Institut fuer Plasmaphysik (IPP), EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Lieshout, L. von [Imtech Vonk BV, Modem 30, NL-7741 MJ Coevorden (Netherlands); Habel, D. [Piller Germany GmbH and Co. KG, Abgunst 24, D-37520 Osterode (Harz) (Germany); Stobbe, F. [Max-Planck-Institut fuer Plasmaphysik (IPP), EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany)

    2011-10-15

    Some years ago, ASDEX Upgrade (AUG) examined its future power supply needs. The experimental program could make use of an extension of the IPP pulsed energy storage, both to allow new scenarios at higher plasma current to be investigated, as well as to allow longer plasma flat-top time. Studies performed in 2001 and 2002 by IPP and external collaborators showed that an attractive solution for this extension is a parallel connection of commercially available compact flywheel generators. Especially the main challenges of this system will be explained in the paper. Further on, the paper will present the parallel and stand-alone mode of operation, analyse the results of measurements obtained during commissioning, compare them to the calculated design values and report on the performance achieved during AUG plasma experiments and Additional Heating operation.

  15. Modeling and Simulation of Road Traffic Noise Using Artificial Neural Network and Regression.

    Science.gov (United States)

    Honarmand, M; Mousavi, S M

    2014-04-01

    Modeling and simulation of noise pollution has been done in a large city, where the population is over 2 millions. Two models of artificial neural network and regression were developed to predict in-city road traffic noise pollution with using the data of noise measurements and vehicle counts at three points of the city for a period of 12 hours. The MATLAB and DATAFIT softwares were used for simulation. The predicted results of noise level were compared with the measured noise levels in three stations. The values of normalized bias, sum of squared errors, mean of squared errors, root mean of squared errors, and squared correlation coefficient calculated for each model show the results of two models are suitable, and the predictions of artificial neural network are closer to the experimental data.

  16. Simulation tests of the optimization method of Hopfield and Tank using neural networks

    Science.gov (United States)

    Paielli, Russell A.

    1988-01-01

    The method proposed by Hopfield and Tank for using the Hopfield neural network with continuous valued neurons to solve the traveling salesman problem is tested by simulation. Several researchers have apparently been unable to successfully repeat the numerical simulation documented by Hopfield and Tank. However, as suggested to the author by Adams, it appears that the reason for those difficulties is that a key parameter value is reported erroneously (by four orders of magnitude) in the original paper. When a reasonable value is used for that parameter, the network performs generally as claimed. Additionally, a new method of using feedback to control the input bias currents to the amplifiers is proposed and successfully tested. This eliminates the need to set the input currents by trial and error.

  17. Prediction of Maximum Story Drift of MDOF Structures under Simulated Wind Loads Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Omar Payán-Serrano

    2017-05-01

    Full Text Available The aim of this paper is to investigate the prediction of maximum story drift of Multi-Degree of Freedom (MDOF structures subjected to dynamics wind load using Artificial Neural Networks (ANNs through the combination of several structural and turbulent wind parameters. The maximum story drift of 1600 MDOF structures under 16 simulated wind conditions are computed with the purpose of generating the data set for the networks training with the Levenberg–Marquardt method. The Shinozuka and Newmark methods are used to simulate the turbulent wind and dynamic response, respectively. In order to optimize the computational time required for the dynamic analyses, an array format based on the Shinozuka method is presented to perform the parallel computing. Finally, it is observed that the already trained ANNs allow for predicting adequately the maximum story drift with a correlation close to 99%.

  18. Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks

    DEFF Research Database (Denmark)

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.

    2012-01-01

    linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using...... numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from...... the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results...

  19. Acquiring Efficient Locomotion in a Simulated Quadruped through Evolving Random and Predefined Neural Networks

    DEFF Research Database (Denmark)

    Veenstra, Frank; Struck, Alexander; Krauledat, Matthias

    2015-01-01

    The acquisition and optimization of dynamically stable locomotion is important to engender fast and energy efficient locomotion in animals. Conventional optimization strategies tend to have difficulties in acquiring dynamically stable gaits in legged robots. In this paper, an evolving neural...... network (ENN) was implemented with the aim to optimize the locomotive behavior of a four-legged simulated robot. In the initial generation, individuals had neural networks (NNs) that were either predefined or randomly initialized. Additional investigations show that the efficiency of applying additional...... sensors to the simulated quadruped improved the performance of the ENN slightly. Promising results were seen in the evolutionary runs where the initial predefined NNs of the population contributed to slight movements of the limbs. This paper shows how a predefined ENNs linked to bio-inspired sensors can...

  20. An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

    Science.gov (United States)

    2014-01-01

    Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

  1. An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

    Science.gov (United States)

    He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

    2014-01-01

    Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation

  2. Simulation of complex fracture networks influenced by natural fractures in shale gas reservoir

    Directory of Open Access Journals (Sweden)

    Zhao Jinzhou

    2014-10-01

    Full Text Available When hydraulic fractures intersect with natural fractures, the geometry and complexity of a fracture network are determined by the initiation and propagation pattern which is affected by a number of factors. Based on the fracture mechanics, the criterion for initiation and propagation of a fracture was introduced to analyze the tendency of a propagating angle and factors affecting propagating pressure. On this basis, a mathematic model with a complex fracture network was established to investigate how the fracture network form changes with different parameters, including rock mechanics, in-situ stress distribution, fracture properties, and frac treatment parameters. The solving process of this model was accelerated by classifying the calculation nodes on the extending direction of the fracture by equal pressure gradients, and solving the geometrical parameters prior to the iteration fitting flow distribution. With the initiation and propagation criterion as the bases for the propagation of branch fractures, this method decreased the iteration times through eliminating the fitting of the fracture length in conventional 3D fracture simulation. The simulation results indicated that the formation with abundant natural fractures and smaller in-situ stress difference is sufficient conditions for fracture network development. If the pressure in the hydraulic fractures can be kept at a high level by temporary sealing or diversion, the branch fractures will propagate further with minor curvature radius, thus enlarging the reservoir stimulation area. The simulated shape of fracture network can be well matched with the field microseismic mapping in data point range and distribution density, validating the accuracy of this model.

  3. Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species with Application to DSMC Simulations

    Science.gov (United States)

    Liechty, Derek S.

    2014-01-01

    The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for near-equilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion.

  4. Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species With Application to DSMC Simulations

    Science.gov (United States)

    Liechty, Derek S.

    2013-01-01

    The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for nearequilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion of the heating and is then compared to the total heating measured in flight.

  5. Railway optimal network simulation for the development of regional transport-logistics system

    Directory of Open Access Journals (Sweden)

    Mikhail Borisovich Petrov

    2013-12-01

    Full Text Available The dependence of logistics on mineral fuel is a stable tendency of regions development, though when making strategic plans of logistics in the regions, it is necessary to provide the alternative possibilities of power-supply sources change together with population density, transport infrastructure peculiarities, and demographic changes forecast. On the example of timber processing complex of the Sverdlovsk region, the authors suggest the algorithm of decision of the optimal logistics infrastructure allocation. The problem of regional railway network organization at the stage of slow transition from the prolonged stagnation to the new development is carried out. The transport networks’ configurations of countries on the Pacific Rim, which successfully developed nowadays, are analyzed. The authors offer some results of regional transport network simulation on the basis of artificial intelligence method. These methods let to solve the task with incomplete data. The ways of the transport network improvement in the Sverdlovsk region are offered.

  6. Intelligent Controlling Simulation of Traffic Flow in a Small City Network

    Science.gov (United States)

    Fouladvand, M. Ebrahim; Shaebani, M. Reza; Sadjadi, Zeinab

    2004-11-01

    We propose a two dimensional probabilistic cellular automata for the description of traffic flow in a small city network composed of two intersections. The traffic in the network is controlled by a set of traffic lights which can be operated both in fixed-time and a traffic responsive manner. Vehicular dynamics is simulated and the total delay experienced by the traffic is evaluated within specified time intervals. We investigate both decentralized and centralized traffic responsive schemes and in particular discuss the implementation of the green-wave strategy. Our investigations prove that the network delay strongly depends on the signalisation strategy. We show that in some traffic conditions, the application of the green-wave scheme may destructively lead to the increment of the global delay.

  7. Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks

    Science.gov (United States)

    Orlov, Yu.; Fedorov, S.; Samuylov, A.; Gaidamaka, Yu.; Molchanov, D.

    2017-07-01

    The problem of channel quality estimation for devices in a wireless 5G network is formulated. As a performance metrics of interest we choose the signal-to-interference-plus-noise ratio, which depends essentially on the distance between the communicating devices. A model with a plurality of moving devices in a bounded three-dimensional space and a simulation algorithm to determine the distances between the devices for a given motion model are devised.

  8. Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

    Science.gov (United States)

    Hallgren, Kevin A; McCrady, Barbara S; Caudell, Thomas P; Witkiewitz, Katie; Tonigan, J Scott

    2017-11-01

    Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. Design and simulation of sensor networks for tracking Wifi users in outdoor urban environments

    Science.gov (United States)

    Thron, Christopher; Tran, Khoi; Smith, Douglas; Benincasa, Daniel

    2017-05-01

    We present a proof-of-concept investigation into the use of sensor networks for tracking of WiFi users in outdoor urban environments. Sensors are fixed, and are capable of measuring signal power from users' WiFi devices. We derive a maximum likelihood estimate for user location based on instantaneous sensor power measurements. The algorithm takes into account the effects of power control, and is self-calibrating in that the signal power model used by the location algorithm is adjusted and improved as part of the operation of the network. Simulation results to verify the system's performance are presented. The simulation scenario is based on a 1.5 km2 area of lower Manhattan, The self-calibration mechanism was verified for initial rms (root mean square) errors of up to 12 dB in the channel power estimates: rms errors were reduced by over 60% in 300 track-hours, in systems with limited power control. Under typical operating conditions with (without) power control, location rms errors are about 8.5 (5) meters with 90% accuracy within 9 (13) meters, for both pedestrian and vehicular users. The distance error distributions for smaller distances (issue of optimal sensor placement in the sensor network is also addressed. We specify a linear programming algorithm for determining sensor placement for networks with reduced number of sensors. In our test case, the algorithm produces a network with 18.5% fewer sensors with comparable accuracy estimation performance. Finally, we discuss future research directions for improving the accuracy and capabilities of sensor network systems in urban environments.

  10. Simulation of two-phase flow in horizontal fracture networks with numerical manifold method

    Science.gov (United States)

    Ma, G. W.; Wang, H. D.; Fan, L. F.; Wang, B.

    2017-10-01

    The paper presents simulation of two-phase flow in discrete fracture networks with numerical manifold method (NMM). Each phase of fluids is considered to be confined within the assumed discrete interfaces in the present method. The homogeneous model is modified to approach the mixed fluids. A new mathematical cover formation for fracture intersection is proposed to satisfy the mass conservation. NMM simulations of two-phase flow in a single fracture, intersection, and fracture network are illustrated graphically and validated by the analytical method or the finite element method. Results show that the motion status of discrete interface significantly depends on the ratio of mobility of two fluids rather than the value of the mobility. The variation of fluid velocity in each fracture segment and the driven fluid content are also influenced by the ratio of mobility. The advantages of NMM in the simulation of two-phase flow in a fracture network are demonstrated in the present study, which can be further developed for practical engineering applications.

  11. A discrete event simulation model for evaluating time delays in a pipeline network

    Energy Technology Data Exchange (ETDEWEB)

    Spricigo, Deisi; Muggiati, Filipe V.; Lueders, Ricardo; Neves Junior, Flavio [Federal University of Technology of Parana (UTFPR), Curitiba, PR (Brazil)

    2009-07-01

    Currently in the oil industry the logistic chain stands out as a strong candidate to obtain highest profit, since recent studies have pointed out to a cost reduction by adoption of better policies for distribution of oil derivatives, particularly those where pipelines are used to transport products. Although there are models to represent transfers of oil derivatives in pipelines, they are quite complex and computationally burden. In this paper, we are interested on models that are less detailed in terms of fluid dynamics but provide more information about operational decisions in a pipeline network. We propose a discrete event simulation model in ARENA that allows simulating a pipeline network based on average historical data. Time delays for transferring different products can be evaluated through different routes. It is considered that transport operations follow a historical behavior and average time delays can thus be estimated within certain bounds. Due to its stochastic nature, time quantities are characterized by average and dispersion measures. This allows comparing different operational scenarios for product transportation. Simulation results are compared to data obtained from a real world pipeline network and different scenarios of production and demand are analyzed. (author)

  12. Exact subthreshold integration with continuous spike times in discrete-time neural network simulations.

    Science.gov (United States)

    Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus

    2007-01-01

    Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

  13. Impact of Stoichiometry Representation on Simulation of Genotype-Phenotype Relationships in Metabolic Networks

    Science.gov (United States)

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.; Patil, Kiran R.

    2012-01-01

    Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in Saccharomyces cerevisiae. PMID:23133362

  14. A Mobility and Traffic Generation Framework for Modeling and Simulating Ad Hoc Communication Networks

    Directory of Open Access Journals (Sweden)

    Chris Barrett

    2004-01-01

    Full Text Available We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad~hoc networks. Three components of this framework, namely a mobility data generator (MDG, a graph structure generator (GSG and an occlusion modification tool (OMT allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG which generates packet transmission activities for transceivers and a packet activity simulator (PAS which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of

  15. Modeling languages for biochemical network simulation: reaction vs equation based approaches.

    Science.gov (United States)

    Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

    2010-01-01

    Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

  16. MEDYAN: Mechanochemical Simulations of Contraction and Polarity Alignment in Actomyosin Networks.

    Directory of Open Access Journals (Sweden)

    Konstantin Popov

    2016-04-01

    Full Text Available Active matter systems, and in particular the cell cytoskeleton, exhibit complex mechanochemical dynamics that are still not well understood. While prior computational models of cytoskeletal dynamics have lead to many conceptual insights, an important niche still needs to be filled with a high-resolution structural modeling framework, which includes a minimally-complete set of cytoskeletal chemistries, stochastically treats reaction and diffusion processes in three spatial dimensions, accurately and efficiently describes mechanical deformations of the filamentous network under stresses generated by molecular motors, and deeply couples mechanics and chemistry at high spatial resolution. To address this need, we propose a novel reactive coarse-grained force field, as well as a publicly available software package, named the Mechanochemical Dynamics of Active Networks (MEDYAN, for simulating active network evolution and dynamics (available at www.medyan.org. This model can be used to study the non-linear, far from equilibrium processes in active matter systems, in particular, comprised of interacting semi-flexible polymers embedded in a solution with complex reaction-diffusion processes. In this work, we applied MEDYAN to investigate a contractile actomyosin network consisting of actin filaments, alpha-actinin cross-linking proteins, and non-muscle myosin IIA mini-filaments. We found that these systems undergo a switch-like transition in simulations from a random network to ordered, bundled structures when cross-linker concentration is increased above a threshold value, inducing contraction driven by myosin II mini-filaments. Our simulations also show how myosin II mini-filaments, in tandem with cross-linkers, can produce a range of actin filament polarity distributions and alignment, which is crucially dependent on the rate of actin filament turnover and the actin filament's resulting super-diffusive behavior in the actomyosin-cross-linker system

  17. Selective adaptation in networks of heterogeneous populations: model, simulation, and experiment.

    Directory of Open Access Journals (Sweden)

    Avner Wallach

    2008-02-01

    Full Text Available Biological systems often change their responsiveness when subject to persistent stimulation, a phenomenon termed adaptation. In neural systems, this process is often selective, allowing the system to adapt to one stimulus while preserving its sensitivity to another. In some studies, it has been shown that adaptation to a frequent stimulus increases the system's sensitivity to rare stimuli. These phenomena were explained in previous work as a result of complex interactions between the various subpopulations of the network. A formal description and analysis of neuronal systems, however, is hindered by the network's heterogeneity and by the multitude of processes taking place at different time-scales. Viewing neural networks as populations of interacting elements, we develop a framework that facilitates a formal analysis of complex, structured, heterogeneous networks. The formulation developed is based on an analysis of the availability of activity dependent resources, and their effects on network responsiveness. This approach offers a simple mechanistic explanation for selective adaptation, and leads to several predictions that were corroborated in both computer simulations and in cultures of cortical neurons developing in vitro. The framework is sufficiently general to apply to different biological systems, and was demonstrated in two different cases.

  18. Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

    Science.gov (United States)

    Wang, Ting; Plecháč, Petr

    2017-12-01

    Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

  19. Network Performance Improvement under Epidemic Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2013-01-01

    In this paper we investigate epidemic failure spreading in large- scale GMPLS-controlled transport networks. By evaluating the effect of the epidemic failure spreading on the network, we design several strategies for cost-effective network performance improvement via differentiated repair times....... First we identify the most vulnerable and the most strategic nodes in the network. Then, via extensive simulations we show that strategic placement of resources for improved failure recovery has better performance than randomly assigning lower repair times among the network nodes. Our OPNET simulation...

  20. Modeling and simulation of network-on-chip systems with DEVS and DEUS.

    Science.gov (United States)

    Amoretti, Michele

    2014-01-01

    Networks on-chip (NoCs) provide enhanced performance, scalability, modularity, and design productivity as compared with previous communication architectures for VLSI systems on-chip (SoCs), such as buses and dedicated signal wires. Since the NoC design space is very large and high dimensional, evaluation methodologies rely heavily on analytical modeling and simulation. Unfortunately, there is no standard modeling framework. In this paper we illustrate how to design and evaluate NoCs by integrating the Discrete Event System Specification (DEVS) modeling framework and the simulation environment called DEUS. The advantage of such an approach is that both DEVS and DEUS support modularity-the former being a sound and complete modeling framework and the latter being an open, general-purpose platform, characterized by a steep learning curve and the possibility to simulate any system at any level of detail.

  1. Design and simulation of a nanoelectronic DG MOSFET current source using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Djeffal, F. [LEA, Department of Electronics, University of Batna 05000 (Algeria)], E-mail: faycaldzdz@hotmail.com; Dibi, Z. [LEA, Department of Electronics, University of Batna 05000 (Algeria)], E-mail: zohirdibi@univ-batna.dz; Hafiane, M.L.; Arar, D. [LEA, Department of Electronics, University of Batna 05000 (Algeria)

    2007-09-15

    The double gate (DG) MOSFET has received great attention in recent years owing to the inherent suppression of short channel effects (SCEs), excellent subthreshold slope (S), improved drive current (I{sub ds}) and transconductance (gm), volume inversion for symmetric devices and excellent scalability. Therefore, simulation tools which can be applied to design nanoscale transistors in the future require new theory and modeling techniques that capture the physics of quantum transport accurately and efficiently. In this sense, this work presents the applicability of the artificial neural networks (ANN) for the design and simulation of a nanoelectronic DG MOSFET current source. The latter is based on the 2D numerical Non-Equilibrium Green's Function (NEGF) simulation of the current-voltage characteristics of an undoped symmetric DG MOSFET. Our results are discussed in order to obtain some new and useful information about the ULSI technology.

  2. Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

    Science.gov (United States)

    Majumdar, Alok K.; Ravindran, S. S.

    2017-01-01

    Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

  3. Mesoscopic simulations of hydrophilic cross-linked polycarbonate polyurethane networks: structure and morphology.

    Science.gov (United States)

    Iype, E; Esteves, A C C; de With, G

    2016-06-14

    Polyurethane (PU) cross-linked networks are frequently used in biomedical and marine applications, e.g., as hydrophilic polymer coatings with antifouling or low-friction properties and have been reported to exhibit characteristic phase separation between soft and hard segments. Understanding this phase-separation behavior is critical to design novel hydrophilic polymer coatings. However, most of the studies on the structure and morphology of cross-linked coatings are experimental, which only assess the phase separation via indirect methods. Herein we present a mesoscopic simulation study of the network characteristics of model hydrophilic polymer networks, consisting of PU with and without methyl-polyethylene glycol (mPEG) dangling chains. The systems are analyzed using a number of tools, such as the radial distribution function, the cross-link point density distribution and the Voronoi volume distribution (of the cross-linking points). The combined results show that the cross-linked networks without dangling chains are rather homogeneous but contain a small amount of clustering of cross-linker molecules. A clear phase separation is observed when introducing the dangling chains. In spite of that, the amount of cross-linker molecules connected to dangling chains only, i.e., not connected to the main network, is relatively small, leading to about 3 wt% extractables. Thus, these cross-linked polymers consist of a phase-separated, yet highly connected network. This study provides valuable guidelines towards new self-healing hydrophilic coatings based on the molecular design of cross-linked networks in direct contact with water or aqueous fluids, e.g., as anti-fouling self-repairing coatings for marine applications.

  4. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

    Directory of Open Access Journals (Sweden)

    Régis Corinne

    2011-07-01

    Full Text Available Abstract Background The spread of infectious diseases crucially depends on the pattern of contacts between individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. However, there are few empirical studies available that provide estimates of the number and duration of contacts between social groups. Moreover, their space and time resolutions are limited, so that data are not explicit at the person-to-person level, and the dynamic nature of the contacts is disregarded. In this study, we aimed to assess the role of data-driven dynamic contact patterns between individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. Methods We considered high-resolution data about face-to-face interactions between the attendees at a conference, obtained from the deployment of an infrastructure based on radiofrequency identification (RFID devices that assessed mutual face-to-face proximity. The spread of epidemics along these interactions was simulated using an SEIR (Susceptible, Exposed, Infectious, Recovered model, using both the dynamic network of contacts defined by the collected data, and two aggregated versions of such networks, to assess the role of the data temporal aspects. Results We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation that retains only the topology of the contact network fails to reproduce the size of the epidemic. Conclusions These results have important implications for understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics. Please see related article BMC Medicine, 2011, 9:88

  5. Efficient stochastic simulation of chemical kinetics networks using a weighted ensemble of trajectories.

    Science.gov (United States)

    Donovan, Rory M; Sedgewick, Andrew J; Faeder, James R; Zuckerman, Daniel M

    2013-09-21

    We apply the "weighted ensemble" (WE) simulation strategy, previously employed in the context of molecular dynamics simulations, to a series of systems-biology models that range in complexity from a one-dimensional system to a system with 354 species and 3680 reactions. WE is relatively easy to implement, does not require extensive hand-tuning of parameters, does not depend on the details of the simulation algorithm, and can facilitate the simulation of extremely rare events. For the coupled stochastic reaction systems we study, WE is able to produce accurate and efficient approximations of the joint probability distribution for all chemical species for all time t. WE is also able to efficiently extract mean first passage times for the systems, via the construction of a steady-state condition with feedback. In all cases studied here, WE results agree with independent "brute-force" calculations, but significantly enhance the precision with which rare or slow processes can be characterized. Speedups over "brute-force" in sampling rare events via the Gillespie direct Stochastic Simulation Algorithm range from ~10(12) to ~10(18) for characterizing rare states in a distribution, and ~10(2) to ~10(4) for finding mean first passage times.

  6. A parallel program for numerical simulation of discrete fracture network and groundwater flow

    Science.gov (United States)

    Huang, Ting-Wei; Liou, Tai-Sheng; Kalatehjari, Roohollah

    2017-04-01

    The ability of modeling fluid flow in Discrete Fracture Network (DFN) is critical to various applications such as exploration of reserves in geothermal and petroleum reservoirs, geological sequestration of carbon dioxide and final disposal of spent nuclear fuels. Although several commerical or acdametic DFN flow simulators are already available (e.g., FracMan and DFNWORKS), challenges in terms of computational efficiency and three-dimensional visualization still remain, which therefore motivates this study for developing a new DFN and flow simulator. A new DFN and flow simulator, DFNbox, was written in C++ under a cross-platform software development framework provided by Qt. DFNBox integrates the following capabilities into a user-friendly drop-down menu interface: DFN simulation and clipping, 3D mesh generation, fracture data analysis, connectivity analysis, flow path analysis and steady-state grounwater flow simulation. All three-dimensional visualization graphics were developed using the free OpenGL API. Similar to other DFN simulators, fractures are conceptualized as random point process in space, with stochastic characteristics represented by orientation, size, transmissivity and aperture. Fracture meshing was implemented by Delaunay triangulation for visualization but not flow simulation purposes. Boundary element method was used for flow simulations such that only unknown head or flux along exterior and interection bounaries are needed for solving the flow field in the DFN. Parallel compuation concept was taken into account in developing DFNbox for calculations that such concept is possible. For example, the time-consuming seqential code for fracture clipping calculations has been completely replaced by a highly efficient parallel one. This can greatly enhance compuational efficiency especially on multi-thread platforms. Furthermore, DFNbox have been successfully tested in Windows and Linux systems with equally-well performance.

  7. Coherent Synchrotron Radiation A Simulation Code Based on the Non-Linear Extension of the Operator Splitting Method

    CERN Document Server

    Dattoli, Giuseppe

    2005-01-01

    The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. A code devoted to the analysis of this type of problems should be fast and reliable: conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problem in accelerators. The extension of these method to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators implemented numerically in C++. We show that the integration procedure is capable of reproducing the onset of an instability and effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, parametric studies a...

  8. Hierarchical assembly of block copolymer micelles into reversible networks: MC simulations

    Science.gov (United States)

    Wang, Zilu; Dormidontova, Elena

    2015-03-01

    The rapid development of nanoscience has considerably expanded the range of building blocks for complex self-assembled nanostructure formation, which show great potential for numerous advanced applications. We apply Monte Carlo simulations to gain understanding of molecular mechanism of self-assembly of nanostructures formed by diblock copolymer micelles interconnected by means of metal-ligand complexation. These systems exhibit interesting chemical and mechanical stimuli-responsive behavior and possess two levels of self-assembly: 1) self-assembly of diblock copolymers into micelles and 2) reversible inter-micelle bridging by coordination bonding between metal ions and ligands attached to the corona of nanoparticles, which is responsible for the network viscoelastic properties. Using MC simulations we investigate the effect of metal-ligand complexation on diblock-copolymer micelle formation and vice versa. We analyze the extent of intra- and inter-micelle loops and bridges formed by metal-ligand complexation in relation to the degree of crosslinking and elastic properties of the network. The effect of polymer concentration, hydrophilic block length, metal to oligomer ratio and type of complexation (2:1 or 3:1) on equilibrium properties of reversible networks will be discussed.

  9. Reading fiction and reading minds: the role of simulation in the default network

    Science.gov (United States)

    Bricker, Andrew B.; Dodell-Feder, David; Mitchell, Jason P.

    2016-01-01

    Research in psychology has suggested that reading fiction can improve individuals’ social-cognitive abilities. Findings from neuroscience show that reading and social cognition both recruit the default network, a network which is known to support our capacity to simulate hypothetical scenes, spaces and mental states. The current research tests the hypothesis that fiction reading enhances social cognition because it serves to exercise the default subnetwork involved in theory of mind. While undergoing functional neuroimaging, participants read literary passages that differed along two dimensions: (i) vivid vs abstract and (ii) social vs non-social. Analyses revealed distinct subnetworks of the default network respond to the two dimensions of interest: the medial temporal lobe subnetwork responded preferentially to vivid passages, with or without social content; the dorsomedial prefrontal cortex (dmPFC) subnetwork responded preferentially to passages with social and abstract content. Analyses also demonstrated that participants who read fiction most often also showed the strongest social cognition performance. Finally, mediation analysis showed that activity in the dmPFC subnetwork in response to the social content mediated this relation, suggesting that the simulation of social content in fiction plays a role in fiction’s ability to enhance readers’ social cognition. PMID:26342221

  10. Reconstruction of chalk pore networks from 2D backscatter electron micrographs using a simulated annealing technique

    Energy Technology Data Exchange (ETDEWEB)

    Talukdar, M.S.; Torsaeter, O. [Department of Petroleum Engineering and Applied Geophysics, Norwegian University of Science and Technology, Trondheim (Norway)

    2002-05-01

    We report the stochastic reconstruction of chalk pore networks from limited morphological information that may be readily extracted from 2D backscatter electron (BSE) images of the pore space. The reconstruction technique employs a simulated annealing (SA) algorithm, which can be constrained by an arbitrary number of morphological descriptors. Backscatter electron images of a high-porosity North Sea chalk sample are analyzed and the morphological descriptors of the pore space are determined. The morphological descriptors considered are the void-phase two-point probability function and lineal path function computed with or without the application of periodic boundary conditions (PBC). 2D and 3D samples have been reconstructed with different combinations of the descriptors and the reconstructed pore networks have been analyzed quantitatively to evaluate the quality of reconstructions. The results demonstrate that simulated annealing technique may be used to reconstruct chalk pore networks with reasonable accuracy using the void-phase two-point probability function and/or void-phase lineal path function. Void-phase two-point probability function produces slightly better reconstruction than the void-phase lineal path function. Imposing void-phase lineal path function results in slight improvement over what is achieved by using the void-phase two-point probability function as the only constraint. Application of periodic boundary conditions appears to be not critically important when reasonably large samples are reconstructed.

  11. IMPROVEMENT OF RECOGNITION QUALITY IN DEEP LEARNING NETWORKS BY SIMULATED ANNEALING METHOD

    Directory of Open Access Journals (Sweden)

    A. S. Potapov

    2014-09-01

    Full Text Available The subject of this research is deep learning methods, in which automatic construction of feature transforms is taken place in tasks of pattern recognition. Multilayer autoencoders have been taken as the considered type of deep learning networks. Autoencoders perform nonlinear feature transform with logistic regression as an upper classification layer. In order to verify the hypothesis of possibility to improve recognition rate by global optimization of parameters for deep learning networks, which are traditionally trained layer-by-layer by gradient descent, a new method has been designed and implemented. The method applies simulated annealing for tuning connection weights of autoencoders while regression layer is simultaneously trained by stochastic gradient descent. Experiments held by means of standard MNIST handwritten digit database have shown the decrease of recognition error rate from 1.1 to 1.5 times in case of the modified method comparing to the traditional method, which is based on local optimization. Thus, overfitting effect doesn’t appear and the possibility to improve learning rate is confirmed in deep learning networks by global optimization methods (in terms of increasing recognition probability. Research results can be applied for improving the probability of pattern recognition in the fields, which require automatic construction of nonlinear feature transforms, in particular, in the image recognition. Keywords: pattern recognition, deep learning, autoencoder, logistic regression, simulated annealing.

  12. Potential of commercial microwave link network derived rainfall for river runoff simulations

    Science.gov (United States)

    Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald

    2017-03-01

    Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

  13. Reading fiction and reading minds: the role of simulation in the default network.

    Science.gov (United States)

    Tamir, Diana I; Bricker, Andrew B; Dodell-Feder, David; Mitchell, Jason P

    2016-02-01

    Research in psychology has suggested that reading fiction can improve individuals' social-cognitive abilities. Findings from neuroscience show that reading and social cognition both recruit the default network, a network which is known to support our capacity to simulate hypothetical scenes, spaces and mental states. The current research tests the hypothesis that fiction reading enhances social cognition because it serves to exercise the default subnetwork involved in theory of mind. While undergoing functional neuroimaging, participants read literary passages that differed along two dimensions: (i) vivid vs abstract and (ii) social vs non-social. Analyses revealed distinct subnetworks of the default network respond to the two dimensions of interest: the medial temporal lobe subnetwork responded preferentially to vivid passages, with or without social content; the dorsomedial prefrontal cortex (dmPFC) subnetwork responded preferentially to passages with social and abstract content. Analyses also demonstrated that participants who read fiction most often also showed the strongest social cognition performance. Finally, mediation analysis showed that activity in the dmPFC subnetwork in response to the social content mediated this relation, suggesting that the simulation of social content in fiction plays a role in fiction's ability to enhance readers' social cognition. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Multi-Sensor Network for Landslides Simulation and Hazard Monitoring - Design and Deployment

    Science.gov (United States)

    Wu, H.; Qiao, G.; Lu, P.; Feng, T.; Tian, Y.; Fan, H.; Liu, S.; Liu, C.; Tong, X.; Wang, W.; Shen, Y.; Guan, Z.; Li, R.

    2011-08-01

    This paper describes a newly developed multi-sensor network system for landslide and hazard monitoring. Landslide hazard is one of the most destructive natural disasters, which has severely affected human safety, properties and infrastructures. We report the results of designing and deploying the multi-sensor network, based on the simulated landslide model, to monitor typical landslide areas and with a goal to predict landslide hazard and mitigate damages. The integration and deployment of the prototype sensor network were carried out in an experiment area at Tongji University in Shanghai. In order to simulate a real landslide, a contractible landslide body is constructed in the experiment area by 7m*1.5m. Then, some different kind of sensors, such as camera, GPS, crackmeter, accelerometer, laser scanning system, inclinometer, etc., are installed near or in the landslide body. After the sensors are powered, continuous sampling data will be generated. With the help of communication method, such as GPRS, and certain transport devices, such as iMesh and 3G router, all the sensor data will be transported to the server and stored in Oracle. These are the current results of an ongoing project of the center. Further research results will be updated and presented in the near future.

  15. MULTI-SENSOR NETWORK FOR LANDSLIDES SIMULATION AND HAZARD MONITORING - DESIGN AND DEPLOYMENT

    Directory of Open Access Journals (Sweden)

    H. Wu

    2012-08-01

    Full Text Available This paper describes a newly developed multi-sensor network system for landslide and hazard monitoring. Landslide hazard is one of the most destructive natural disasters, which has severely affected human safety, properties and infrastructures. We report the results of designing and deploying the multi-sensor network, based on the simulated landslide model, to monitor typical landslide areas and with a goal to predict landslide hazard and mitigate damages. The integration and deployment of the prototype sensor network were carried out in an experiment area at Tongji University in Shanghai. In order to simulate a real landslide, a contractible landslide body is constructed in the experiment area by 7m*1.5m. Then, some different kind of sensors, such as camera, GPS, crackmeter, accelerometer, laser scanning system, inclinometer, etc., are installed near or in the landslide body. After the sensors are powered, continuous sampling data will be generated. With the help of communication method, such as GPRS, and certain transport devices, such as iMesh and 3G router, all the sensor data will be transported to the server and stored in Oracle. These are the current results of an ongoing project of the center. Further research results will be updated and presented in the near future.

  16. Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

    Science.gov (United States)

    Conrads, Paul; Petkewich, Matthew D.; O'Reilly, Andrew M.; Telis, Pamela A.

    2015-01-01

    The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies.

  17. Exploiting Network Topology Information to Mitigate Ambiguities in VMP Localization

    DEFF Research Database (Denmark)

    Pedersen, Claus; Pedersen, Troels; Fleury, Bernard Henri

    2011-01-01

    We investigate an extension to the probabilistic model of a wireless sensor network (WSN) in the variational message passing localization algorithm. This extension exploits network topology information to mitigate ambiguities in WSN localization schemes. In a simulation case study we show...... that this extension in some cases improves the location estimates produced by the algorithm. The final version of the paper will present quantitative results from more extensive investigations that will document the extent of this improvement....

  18. On Improved Least Squares Regression and Artificial Neural Network Meta-Models for Simulation via Control Variates

    Science.gov (United States)

    2016-09-15

    neural network using applications across varied industries . Alam et al. [2] showed the factorial design did not perform as well as other designs (mentioned...composite design with a neural network using applications across varied industries . Alam et al. [2] showed the central composite design did not perform as...ON IMPROVED LEAST SQUARES REGRESSION & ARTIFICIAL NEURAL NETWORK META-MODELS FOR SIMULATION VIA CONTROL VARIATES DISSERTATION Michael P. Gibb

  19. Artificial neural network model for simulation of water distribution in sprinkle irrigation

    Directory of Open Access Journals (Sweden)

    Paulo L. de Menezes

    2015-09-01

    Full Text Available ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN to simulate sprinkler precipitation, using the values ​​of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs ranging from 0.92 to 0.97 and Willmott agreement index (d from 0.950 to 0.991, between the observed and simulated values for ten analysed trials. The ANN model shows promise in the simulation of precipitation in sprinkle irrigation systems.

  20. ChemChains: a platform for simulation and analysis of biochemical networks aimed to laboratory scientists

    Science.gov (United States)

    Helikar, Tomáš; Rogers, Jim A

    2009-01-01

    Background New mathematical models of complex biological structures and computer simulation software allow modelers to simulate and analyze biochemical systems in silico and form mathematical predictions. Due to this potential predictive ability, the use of these models and software has the possibility to compliment laboratory investigations and help refine, or even develop, new hypotheses. However, the existing mathematical modeling techniques and simulation tools are often difficult to use by laboratory biologists without training in high-level mathematics, limiting their use to trained modelers. Results We have developed a Boolean network-based simulation and analysis software tool, ChemChains, which combines the advantages of the parameter-free nature of logical models while providing the ability for users to interact with their models in a continuous manner, similar to the way laboratory biologists interact with laboratory data. ChemChains allows users to simulate models in an automatic fashion under tens of thousands of different external environments, as well as perform various mutational studies. Conclusion ChemChains combines the advantages of logical and continuous modeling and provides a way for laboratory biologists to perform in silico experiments on mathematical models easily, a necessary component of laboratory research in the systems biology era. PMID:19500393