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Sample records for network simulator ns2

  1. 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

  2. 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 ns-2 network simulator is one of the most widely used tools by researchers to investigate the characteristics of wireless sensor networks. Academic papers focus on results and rarely include details of how ns-2 simulations are implemented...

  3. Positioning system in wireless sensor networks using NS-2

    CSIR Research Space (South Africa)

    Abu-Mahfouz, Adnan M

    2012-10-01

    Full Text Available The practical difficulties of setting up a wireless sensor network (WSN) and analysing its performance have made simulation essential for the study of WSNs. The ns-2 network simulator is one of the most widely used tools by researchers...

  4. Localisation system in wireless sensor networks using ns-2

    CSIR Research Space (South Africa)

    Abu-Mahfouz, Adnan M

    2012-04-01

    Full Text Available -1 /************************************************************************** ********** * * File: readme.asn * * Author: Adnan Abu-Mahfouz * * Date: March 2012 * * Description: Localisation system in wireless sensor networks using ns-2... *************************************************************************** *********/ /************************************************************************** *************************************************************************** *****/ 1. Introduction: ns-2 contains several flexible features that encourage researchers to use ns-2 to investigate the characteristics of wireless sensor networks (WSNs). However, to implement and evaluate localisation algorithms, the current ns- 2...

  5. Ad Hoc on-Demand Distance Vector (AODV Routing Protocol Performance Evaluation on Hybrid Ad Hoc Network: Comparison of Result of Ns-2 Simulation and Implementation on Testbed using PDA

    Directory of Open Access Journals (Sweden)

    Riri Sari

    2010-10-01

    Full Text Available In Mobile Ad hoc NETwork (MANET, node supplemented with wireless equipment has the capacity to manage and organise autonomously, without the presence of network infrastructures. Hybrid ad hoc network, enable several nodes to move freely (mobile to create instant communication. Independent from infrastructure. They could access the Local Area Network (LAN or the Internet. Functionalities of ad hoc network very much dependent on the routing protocol that determines the routing around node. Ad hoc On-demand Distance Vector (AODV is one of routing protocols in ad hoc network which has a reactive characteristic. This protocol is the most common protocol being researched and used. In this Research, AODV protocol investigation was conducted by developing a testbed using Personal Computer, several Laptops (the Linux Red Hat operation system 9.0 and Fedora Core 2, and Personal Digital Assistant (PDA. This research also made a complete package by mean of cross compilation for PDA iPAQ. In general, results obtained from the simulation of AODV protocol using Network Simulator NS-2 are packet delivery ratio 99.89%, end-to-end delay of 0.14 seconds and routing overhead of 1,756.61 byte per second. Afterwards results from simulation were compared to results from testbed. Results obtained from testbed are as follows: the packet delivery ratio is 99.57%, the end-to-end delay is 1.004 seconds and the routing overhead is 1,360.36 byte per second.

  6. Implementation of WirelessHART in the NS-2 Simulator and Validation of Its Correctness

    Directory of Open Access Journals (Sweden)

    Pouria Zand

    2014-05-01

    Full Text Available One of the first standards in the wireless sensor networks domain,WirelessHART (HART (Highway Addressable Remote Transducer, was introduced to address industrial process automation and control requirements. This standard can be used as a reference point to evaluate other wireless protocols in the domain of industrial monitoring and control. This makes it worthwhile to set up a reliable WirelessHART simulator in order to achieve that reference point in a relatively easy manner. Moreover, it offers an alternative to expensive testbeds for testing and evaluating the performance of WirelessHART. This paper explains our implementation of WirelessHART in the NS-2 network simulator. According to our knowledge, this is the first implementation that supports the WirelessHART network manager, as well as the whole stack (all OSI (Open Systems Interconnection model layers of the WirelessHART standard. It also explains our effort to validate the correctness of our implementation, namely through the validation of the implementation of the WirelessHART stack protocol and of the network manager. We use sniffed traffic from a realWirelessHART testbed installed in the Idrolab plant for these validations. This confirms the validity of our simulator. Empirical analysis shows that the simulated results are nearly comparable to the results obtained from real networks. We also demonstrate the versatility and usability of our implementation by providing some further evaluation results in diverse scenarios. For example, we evaluate the performance of the WirelessHART network by applying incremental interference in a multi-hop network.

  7. Molecular dynamic simulation of complex NS2B-NS3 DENV2 ...

    African Journals Online (AJOL)

    Several vaccines have been developed against the disease, but they only ... a two component NS2B-NS3 protease that cleaves viral precursor proteins, and ... The results provide conformational changes of enzyme-inhibitor complex that is ...

  8. Network Simulation

    CERN Document Server

    Fujimoto, Richard

    2006-01-01

    "Network Simulation" presents a detailed introduction to the design, implementation, and use of network simulation tools. Discussion topics include the requirements and issues faced for simulator design and use in wired networks, wireless networks, distributed simulation environments, and fluid model abstractions. Several existing simulations are given as examples, with details regarding design decisions and why those decisions were made. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the

  9. Miracle: The Multi-Interface Cross-Layer Extension of ns2

    Directory of Open Access Journals (Sweden)

    Guerra Federico

    2010-01-01

    Full Text Available We present Miracle, a novel framework which extends ns2 to facilitate the simulation and the design of beyond 4G networks. Miracle enhances ns2 by providing an efficient and embedded engine for handling cross-layer messages and, at the same time, enabling the coexistence of multiple modules within each layer of the protocol stack. We also present a novel framework developed as an extension of Miracle called Miracle PHY and MAC. This framework facilitates the development of more realistic Channel, PHY and MAC modules, considering features currently lacking in most state-of-the-art simulators, while at the same time giving a strong emphasis on code modularity, interoperability and reusability. Finally, we provide an overview of the wireless technologies implemented in Miracle, discussing in particular the models for the IEEE 802.11, UMTS and WiMAX standards and for Underwater Acoustic Networks. We observe that, thanks to Miracle and its extensions, it is possible to carefully simulate complex network architectures at all the OSI layers, from the physical reception model to standard applications and system management schemes. This allows to have a comprehensive view of all the interactions among network components, which play an important role in many research areas, such as cognitive networking and cross-layer design.

  10. Simulasi Kinerja Jaringan Nirkabel IEEE-802.11a dan IEEE-802.11g Menggunakan NS-2

    Directory of Open Access Journals (Sweden)

    Helm Fitriawan

    2014-03-01

    Full Text Available Wireless network uses transmission media based on radio waves. This type of networks is mainly useddue to its efficiency and mobility in data exchanging. This paper reports the modeling and simulation of wirelessnetworks based on Cisco Aironet 1130ag access point devices with IEEE 802.11a and IEEE 802.11g standards. Themodeling and simulation are performed using network simulator version 2 (NS-2 that is installed on operationsystem Linux Ubuntu v.10.10. The NS-2 is commonly used and works well in numerous types of network simulation. From simulation, we obtain quality of service parameters by employing several simulation scenarios in terms ofnumber of nodes, distances, and packet data sizes. It can be concluded from simulation results that the IEEE 802.11gnetworks transfer data with better quality than those of IEEE 802.11a networks.  Furthermore, the IEEE 802.11gnetworks provide a higher throughput, with smaller amount of delay and packet loss percentage compared to thoseof IEEE 802.11a networks.

  11. 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.

  12. CAISSON: Interconnect Network Simulator

    Science.gov (United States)

    Springer, Paul L.

    2006-01-01

    Cray response to HPCS initiative. Model future petaflop computer interconnect. Parallel discrete event simulation techniques for large scale network simulation. Built on WarpIV engine. Run on laptop and Altix 3000. Can be sized up to 1000 simulated nodes per host node. Good parallel scaling characteristics. Flexible: multiple injectors, arbitration strategies, queue iterators, network topologies.

  13. Message network simulation

    OpenAIRE

    Shih, Kuo-Tung

    1990-01-01

    Approved for public release, distribution is unlimited This thesis presents a computer simulation of a multinode data communication network using a virtual network model to determine the effects of various system parameters on overall network performance. Lieutenant Commander, Republic of China (Taiwan) Navy

  14. 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...

  15. Performance Evaluation of AODV Routing Protocol in VANET with NS2

    Directory of Open Access Journals (Sweden)

    Divya Rathi

    2017-03-01

    Full Text Available In intelligent transportation systems, the collaboration between vehicles and the road side units is essential to bring these systems to realization. The emerging Vehicular Ad Hoc Network (VANET is becoming more and more important as it provides intelligent transportation application, comfort, safety, entertainment for people in vehicles. In order to provide stable routes and to get good performance in VANET, there is a need of proper routing protocols must be designed. In this paper, we are working with the very well-known ad-hoc on-demand distance vector (AODV routing protocol. The existing Routing protocol AODV-L which is based on the Link expiration time is extended to propose a more reliable AODV-AD which is based on multichannel MAC protocol. For the performance evaluation of routing protocols, a simulation tool ‘NS2’ has been used. Simulation results show that the proposed AODV-AD protocol can achieves better performances in forms of high Route stability, Packet Delivery ratio and packet loss rate than traditional AODV-L and traditional AODV.

  16. NS simulator for beginners

    CERN Document Server

    Altman, Eitan

    2012-01-01

    NS-2 is an open-source discrete event network simulator which is widely used by both the research community as well as by the people involved in the standardization protocols of IETF. The goal of this book is twofold: on one hand to learn how to use the NS-2 simulator, and on the other hand, to become acquainted with and to understand the operation of some of the simulated objects using NS-2 simulations. The book is intended to help students, engineers or researchers who need not have much background in programming or who want to learn through simple examples how to analyse some simulated obje

  17. Role of nonstructural protein NS2A in flavivirus assembly

    NARCIS (Netherlands)

    Leung, J.Y.; Pijlman, G.P.; Kondratieva, N.; Hyde, J.; Mackenzie, J.M.; Khromykh, A.A.

    2008-01-01

    Flavivirus nonstructural (NS) proteins are involved in RNA replication and modulation of the host antiviral response; however, evidence is mounting that some NS proteins also have essential roles in virus assembly. Kunjin virus (KUN) NS2A is a small, hydrophobic, transmembrane protein that is part

  18. Mutagenesis of Dengue Virus Protein NS2A Revealed a Novel Domain Responsible for Virus-Induced Cytopathic Effect and Interactions between NS2A and NS2B Transmembrane Segments.

    Science.gov (United States)

    Wu, Ren-Huang; Tsai, Ming-Han; Tsai, Kuen-Nan; Tian, Jia Ni; Wu, Jian-Sung; Wu, Su-Ying; Chern, Jyh-Haur; Chen, Chun-Hong; Yueh, Andrew

    2017-06-15

    The NS2A protein of dengue virus (DENV) has eight predicted transmembrane segments (pTMS1 to -8) and participates in RNA replication, virion assembly, and host antiviral response. However, the roles of specific amino acid residues within the pTMS regions of NS2A during the viral life cycle are not clear. Here, we explore the function of DENV NS2A by introducing a series of alanine substitutions into the N-terminal half (pTMS1 to -4) of the protein in the context of a DENV infectious clone or subgenomic replicon. Six NS2A mutants (NM5, -7, -9, and -17 to -19) around pTMS1 and -2 displayed a novel phenotype showing a >1,000-fold reduction in virus yield, an absence of plaque formation despite wild-type-like replicon activity, and infectious-virus-like particle yields. HEK-293 cells infected with the six NS2A mutant viruses failed to cause a virus-induced cytopathic effect (CPE) by MitoCapture staining, cell proliferation, and lactate dehydrogenase release assays. Sequencing analyses of pseudorevertant viruses derived from lethal-mutant viruses revealed two consensus reversion mutations, leucine to phenylalanine at codon 181 (L181F) within pTMS7 of NS2A and isoleucine to threonine at codon 114 (I114T) within NS2B. The introduction of an NS2A-L181F mutation into the lethal (NM15, -16, -25, and -33) and CPE-defective (NM7, -9, and -19) mutants substantially rescued virus infectivity and virus-induced CPE, respectively, whereas the NS2B-L114T mutation rescued the NM16, -25, and -33 mutants. In conclusion, the results revealed the essential roles of the N-terminal half of NS2A in RNA replication and virus-induced CPE. Intramolecular interactions between pTMSs of NS2A and intermolecular interactions between the NS2A and NS2B proteins were also implicated. IMPORTANCE The characterization of the N-terminal (current study) and C-terminal halves of DENV NS2A is the most comprehensive mutagenesis study to date to investigate the function of NS2A during the flaviviral life cycle

  19. 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.

  20. Simulating synchronization in neuronal networks

    Science.gov (United States)

    Fink, Christian G.

    2016-06-01

    We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

  1. Bitcoin network simulator data explotation

    OpenAIRE

    Berini Sarrias, Martí

    2015-01-01

    This project starts with a brief introduction to the concepts of Bitcoin and blockchain, followed by the description of the di erent known attacks to the Bitcoin network. Once reached this point, the basic structure of the Bitcoin network simulator is presented. The main objective of this project is to help in the security assessment of the Bitcoin network. To accomplish that, we try to identify useful metrics, explain them and implement them in the corresponding simulator modules, aiming to ...

  2. Mosquito densonucleosis virus non-structural protein NS2 is necessary for a productive infection

    International Nuclear Information System (INIS)

    Azarkh, Eugene; Robinson, Erin; Hirunkanokpun, Supanee; Afanasiev, Boris; Kittayapong, Pattamaporn; Carlson, Jonathan; Corsini, Joe

    2008-01-01

    Mosquito densonucleosis viruses synthesize two non-structural proteins, NS1 and NS2. While NS1 has been studied relatively well, little is known about NS2. Antiserum was raised against a peptide near the N-terminus of NS2, and used to conduct Western blot analysis and immuno-fluorescence assays. Western blots revealed a prominent band near the expected size (41 kDa). Immuno-fluorescence studies of mosquito cells transfected with AeDNV indicate that NS2 has a wider distribution pattern than does NS1, and the distribution pattern appears to be a function of time post-infection. Nuclear localization of NS2 requires intact C-terminus but does not require additional viral proteins. Mutations ranging from complete NS2 knock-out to a single missense amino acid substitution in NS2 can significantly reduce viral replication and production of viable progeny

  3. Wireless network simulation - Your window on future network performance

    NARCIS (Netherlands)

    Fledderus, E.

    2005-01-01

    The paper describes three relevant perspectives on current wireless simulation practices. In order to obtain the key challenges for future network simulations, the characteristics of "beyond 3G" networks are described, including their impact on simulation.

  4. Simulating Real-Time Aspects of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Christian Nastasi

    2010-01-01

    Full Text Available Wireless Sensor Networks (WSNs technology has been mainly used in the applications with low-frequency sampling and little computational complexity. Recently, new classes of WSN-based applications with different characteristics are being considered, including process control, industrial automation and visual surveillance. Such new applications usually involve relatively heavy computations and also present real-time requirements as bounded end-to- end delay and guaranteed Quality of Service. It becomes then necessary to employ proper resource management policies, not only for communication resources but also jointly for computing resources, in the design and development of such WSN-based applications. In this context, simulation can play a critical role, together with analytical models, for validating a system design against the parameters of Quality of Service demanded for. In this paper, we present RTNS, a publicly available free simulation tool which includes Operating System aspects in wireless distributed applications. RTNS extends the well-known NS-2 simulator with models of the CPU, the Real-Time Operating System and the application tasks, to take into account delays due to the computation in addition to the communication. We demonstrate the benefits of RTNS by presenting our simulation study for a complex WSN-based multi-view vision system for real-time event detection.

  5. Detergent-resistant membrane association of NS2 and E2 during hepatitis C virus replication.

    Science.gov (United States)

    Shanmugam, Saravanabalaji; Saravanabalaji, Dhanaranjani; Yi, MinKyung

    2015-04-01

    Previously, we demonstrated that the efficiency of hepatitis C virus (HCV) E2-p7 processing regulates p7-dependent NS2 localization to putative virus assembly sites near lipid droplets (LD). In this study, we have employed subcellular fractionations and membrane flotation assays to demonstrate that NS2 associates with detergent-resistant membranes (DRM) in a p7-dependent manner. However, p7 likely plays an indirect role in this process, since only the background level of p7 was detectable in the DRM fractions. Our data also suggest that the p7-NS2 precursor is not involved in NS2 recruitment to the DRM, despite its apparent targeting to this location. Deletion of NS2 specifically inhibited E2 localization to the DRM, indicating that NS2 regulates this process. Treatment of cells with methyl-β-cyclodextrin (MβCD) significantly reduced the DRM association of Core, NS2, and E2 and reduced infectious HCV production. Since disruption of the DRM localization of NS2 and E2, either due to p7 and NS2 defects, respectively, or by MβCD treatment, inhibited infectious HCV production, these proteins' associations with the DRM likely play an important role during HCV assembly. Interestingly, we detected the HCV replication-dependent accumulation of ApoE in the DRM fractions. Taking into consideration the facts that ApoE was shown to be a major determinant for infectious HCV particle production at the postenvelopment step and that the HCV Core protein strongly associates with the DRM, recruitment of E2 and ApoE to the DRM may allow the efficient coordination of Core particle envelopment and postenvelopment events at the DRM to generate infectious HCV production. The biochemical nature of HCV assembly sites is currently unknown. In this study, we investigated the correlation between NS2 and E2 localization to the detergent-resistant membranes (DRM) and HCV particle assembly. We determined that although NS2's DRM localization is dependent on p7, p7 was not targeted to these

  6. Gelatin nanoparticles enhance delivery of hepatitis C virus recombinant NS2 gene.

    Science.gov (United States)

    Sabet, Salwa; George, Marina A; El-Shorbagy, Haidan M; Bassiony, Heba; Farroh, Khaled Y; Youssef, Tareq; Salaheldin, Taher A

    2017-01-01

    Development of an effective non-viral vaccine against hepatitis C virus infection is of a great importance. Gelatin nanoparticles (Gel.NPs) have an attention and promising approach as a viable carrier for delivery of vaccine, gene, drug and other biomolecules in the body. The present study aimed to develop stable Gel.NPs conjugated with nonstructural protein 2 (NS2) gene of Hepatitis C Virus genotype 4a (HCV4a) as a safe and an efficient vaccine delivery system. Gel.NPs were synthesized and characterized (size: 150±2 nm and zeta potential +17.6 mv). NS2 gene was successfully cloned and expressed into E. coli M15 using pQE-30 vector. Antigenicity of the recombinant NS2 protein was confirmed by Western blotting to verify the efficiency of NS2 as a possible vaccine. Then NS2 gene was conjugated to gelatin nanoparticles and a successful conjugation was confirmed by labeling and imaging using Confocal Laser Scanning Microscope (CLSM). Interestingly, the transformation of the conjugated NS2/Gel.NPs complex into E. coli DH5-α was 50% more efficient than transformation with the gene alone. In addition, conjugated NS2/Gel.NPs with ratio 1:100 (w/w) showed higher transformation efficiency into E. coli DH5-α than the other ratios (1:50 and 2:50). Gel.NPs effectively enhanced the gene delivery in bacterial cells without affecting the structure of NS2 gene and could be used as a safe, easy, rapid, cost-effective and non-viral vaccine delivery system for HCV.

  7. Hepatitis C virus NS2 protein activates cellular cyclic AMP-dependent pathways

    International Nuclear Information System (INIS)

    Kim, Kyoung Mi; Kwon, Shi-Nae; Kang, Ju-Il; Lee, Song Hee; Jang, Sung Key; Ahn, Byung-Yoon; Kim, Yoon Ki

    2007-01-01

    Chronic infection of the hepatitis C virus (HCV) leads to liver cirrhosis and cancer. The mechanism leading to viral persistence and hepatocellular carcinoma, however, has not been fully understood. In this study, we show that the HCV infection activates cellular cAMP-dependent pathways. Expression of a luciferase reporter gene controlled by a basic promoter with the cAMP response element (CRE) was significantly elevated in human hepatoma Huh-7 cells infected with the HCV JFH1. Analysis with viral subgenomic replicons indicated that the HCV NS2 protein is responsible for the effect. Furthermore, the level of cellular transcripts whose stability is known to be regulated by cAMP was specifically reduced in cells harboring NS2-expressing replicons. These results allude to the HCV NS2 protein having a novel function of regulating cellular gene expression and proliferation through the cAMP-dependent pathway

  8. 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.

  9. Program Helps Simulate Neural Networks

    Science.gov (United States)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  10. DESARROLLO DE UN SOFTWARE BASADO EN JAVA CAPAZ DE INTERPRETAR TRAZAS DE ARCHIVOS GENERADOS POR NS-2

    Directory of Open Access Journals (Sweden)

    Fredy Pachón Barbera

    2013-09-01

    Full Text Available En la simulación de una red de datos, se trata de evaluar, investigar y/o analizar su comportamiento  en un ambiente real, siempre buscando la optimización los recursos. El análisis de la información es un punto clave para conocer fortalezas y debilidades de la red simulada. El objetivo de este artículo es mostrar el desarrollo de una herramienta de interpretación de trazas generadas por NS-2 basado en el lenguaje de programación Java  y las variables estadísticas que se tuvieron en cuenta para la implementación, con el fin de facilitar el análisis de redes simuladas con la herramienta network simluator. Finalmente se logra la construcción del software, logrando determinar los cálculos de jitter, throughput y bytes enviados por cada nodo, a partir de las trazas generadas por NS-2.

  11. Simulations of biopolymer networks under shear

    NARCIS (Netherlands)

    Huisman, Elisabeth Margaretha

    2011-01-01

    In this thesis we present a new method to simulate realistic three-dimensional networks of biopolymers under shear. These biopolymer networks are important for the structural functions of cells and tissues. We use the method to analyze these networks under shear, and consider the elastic modulus,

  12. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  13. Splitting Strategy for Simulating Genetic Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Xiong You

    2014-01-01

    Full Text Available The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions.

  14. Network Modeling and Simulation A Practical Perspective

    CERN Document Server

    Guizani, Mohsen; Khan, Bilal

    2010-01-01

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

  15. Interfacing Network Simulations and Empirical Data

    Science.gov (United States)

    2009-05-01

    contraceptive innovations in the Cameroon. He found that real-world adoption rates did not follow simulation models when the network relationships were...Analysis of the Coevolution of Adolescents ’ Friendship Networks, Taste in Music, and Alcohol Consumption. Methodology, 2: 48-56. Tichy, N.M., Tushman

  16. Naringenin and quercetin--potential anti-HCV agents for NS2 protease targets.

    Science.gov (United States)

    Lulu, S Sajitha; Thabitha, A; Vino, S; Priya, A Mohana; Rout, Madhusmita

    2016-01-01

    Nonstructural proteins of hepatitis C virus had drawn much attention for the scientific fraternity in drug discovery due to its important role in the disease. 3D structure of the protein was predicted using molecular modelling protocol. Docking studies of 10 medicinal plant compounds and three drugs available in the market (control) with NS2 protease were employed by using rigid docking approach of AutoDock 4.2. Among the molecules tested for docking study, naringenin and quercetin revealed minimum binding energy of - 7.97 and - 7.95 kcal/mol with NS2 protease. All the ligands were docked deeply within the binding pocket region of the protein. The docking study results showed that these compounds are potential inhibitors of the target; and also all these docked compounds have good inhibition constant, vdW+Hbond+desolv energy with best RMSD value.

  17. Stochastic Simulation of Biomolecular Reaction Networks Using the Biomolecular Network Simulator Software

    National Research Council Canada - National Science Library

    Frazier, John; Chusak, Yaroslav; Foy, Brent

    2008-01-01

    .... The software uses either exact or approximate stochastic simulation algorithms for generating Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks...

  18. Development and Characterization of a High Sensitivity Segmented Fast Neutron Spectrometer (FaNS-2).

    Science.gov (United States)

    Langford, T J; Beise, E J; Breuer, H; Heimbach, C R; Ji, G; Nico, J S

    2016-01-01

    We present the development of a segmented fast neutron spectrometer (FaNS-2) based upon plastic scintillator and 3 He proportional counters. It was designed to measure both the flux and spectrum of fast neutrons in the energy range of few MeV to 1 GeV. FaNS-2 utilizes capture-gated spectroscopy to identify neutron events and reject backgrounds. Neutrons deposit energy in the plastic scintillator before capturing on a 3 He nucleus in the proportional counters. Segmentation improves neutron energy reconstruction while the large volume of scintillator increases sensitivity to low neutron fluxes. A main goal of its design is to study comparatively low neutron fluxes, such as cosmogenic neutrons at the Earth's surface, in an underground environment, or from low-activity neutron sources. In this paper, we present details of its design and construction as well as its characterization with a calibrated 252 Cf source and monoenergetic neutron fields of 2.5 MeV and 14 MeV. Detected monoenergetic neutron spectra are unfolded using a Singular Value Decomposition method, demonstrating a 5% energy resolution at 14 MeV. Finally, we discuss plans for measuring the surface and underground cosmogenic neutron spectra with FaNS-2.

  19. 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).

  20. 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......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

  1. 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...

  2. Reprocessing process simulation network; PRONET

    International Nuclear Information System (INIS)

    Mitsui, T.; Takada, H.; Kamishima, N.; Tsukamoto, T.; Harada, N.; Fujita, N.; Gonda, K.

    1991-01-01

    The effectiveness of simulation technology and its wide application to nuclear fuel reprocessing plants has been recognized recently. The principal aim of applying simulation is to predict the process behavior accurately based on the quantitative relations among substances in physical and chemical phenomena. Mitsubishi Heavy Industries Ltd. has engaged positively in the development and the application study of this technology. All the software products of its recent activities were summarized in the integrated form named 'PRONET'. The PRONET is classified into two independent software groups from the viewpoint of computer system. One is off-line Process Simulation Group, and the other is Dynamic Real-time Simulator Group. The former is called 'PRONET System', and the latter is called 'PRONET Simulator'. These have several subsystems with the prefix 'MR' meaning Mitsubishi Reprocessing Plant. Each MR subsystem is explained in this report. The technical background, the objective of the PRONET, the system and the function of the PRONET, and the future application to an on-line real-time simulator and the development of MR EXPERT are described. (K.I.)

  3. 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.

  4. 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...

  5. Toward the laboratory identification of the not-so-simple NS2 neutral and anion isomers

    Science.gov (United States)

    Fortenberry, Ryan C.; Thackston, Russell; Francisco, Joseph S.; Lee, Timothy J.

    2017-08-01

    The NS2 radical is a simple arrangement of atoms with a complex electronic structure. This molecule was first reported by Hassanzadeh and Andrew's group [J. Am. Chem. Soc. 114, 83 (1992)] through Ar matrix isolation experiments. In the quarter century since this seminal work was published, almost nothing has been reported about nitrogen disulfide even though NS2 is isovalent with the common NO2. The present study aims to shed new insight into possible challenges with the characterization of this radical. No less than three potential energy surfaces all intersect in the C2v region of the SNS radical isomer. A type-C Renner-Teller molecule is present for the linear 2Πu state where the potential energy surface is fully contained within the 2.05 kcal/mol lower energy X ˜ 2A1 state. A C2v, 1 2B1 state is present in this same region, but a double excitation is required to access this state from the X ˜ 2A1 state of SNS. Additionally, a 1 2A' NSS isomer is also present but with notable differences in the geometry from the global minimum. Consequently, the rovibronic spectrum of these NS2 isomers is quite complicated. While the present theory and previous Ar matrix experiments agree well on isotopic shifts, they differ notably for the absolute fundamental vibrational frequency transitions. These differences are likely a combination of matrix shifts and issues associated with the neglect of non-adiabatic coupling in the computations. In either case, it is clear that high-resolution gas phase experimental observations will be complicated to sort. The present computations should aid in their analysis.

  6. Purification and crystallization of dengue and West Nile virus NS2B–NS3 complexes

    Energy Technology Data Exchange (ETDEWEB)

    D’Arcy, Allan, E-mail: allan.darcy@novartis.com; Chaillet, Maxime; Schiering, Nikolaus; Villard, Frederic [Novartis Institutes of Biomedical Research, Protease Platform, Klybeckstrasse 144, CH 4002 Basel (Switzerland); Lim, Siew Pheng [Novartis Institutes of Tropical Diseases (Singapore); Lefeuvre, Peggy [Novartis Institutes of Biomedical Research, Protease Platform, Klybeckstrasse 144, CH 4002 Basel (Switzerland); Erbel, Paul [Novartis Institutes of Biomedical Research, Protease Platform, Klybeckstrasse 144, CH 4002 Basel (Switzerland); Novartis Institutes of Tropical Diseases (Singapore)

    2006-02-01

    Crystals of dengue serotype 2 and West Nile virus NS2B–NS3 protease complexes have been obtained and the crystals of both diffract to useful resolution. Sample homogeneity was essential for obtaining X-ray-quality crystals of the dengue protease. Controlled proteolysis produced a crystallizable fragment of the apo West Nile virus NS2B–NS3 and crystals were also obtained in the presence of a peptidic inhibitor. Both dengue and West Nile virus infections are an increasing risk to humans, not only in tropical and subtropical areas, but also in North America and parts of Europe. These viral infections are generally transmitted by mosquitoes, but may also be tick-borne. Infection usually results in mild flu-like symptoms, but can also cause encephalitis and fatalities. Approximately 2799 severe West Nile virus cases were reported this year in the United States, resulting in 102 fatalities. With this alarming increase in the number of West Nile virus infections in western countries and the fact that dengue virus already affects millions of people per year in tropical and subtropical climates, there is a real need for effective medicines. A possible therapeutic target to combat these viruses is the protease, which is essential for virus replication. In order to provide structural information to help to guide a lead identification and optimization program, crystallizations of the NS2B–NS3 protease complexes from both dengue and West Nile viruses have been initiated. Crystals that diffract to high resolution, suitable for three-dimensional structure determinations, have been obtained.

  7. Purification and crystallization of dengue and West Nile virus NS2B–NS3 complexes

    International Nuclear Information System (INIS)

    D’Arcy, Allan; Chaillet, Maxime; Schiering, Nikolaus; Villard, Frederic; Lim, Siew Pheng; Lefeuvre, Peggy; Erbel, Paul

    2006-01-01

    Crystals of dengue serotype 2 and West Nile virus NS2B–NS3 protease complexes have been obtained and the crystals of both diffract to useful resolution. Sample homogeneity was essential for obtaining X-ray-quality crystals of the dengue protease. Controlled proteolysis produced a crystallizable fragment of the apo West Nile virus NS2B–NS3 and crystals were also obtained in the presence of a peptidic inhibitor. Both dengue and West Nile virus infections are an increasing risk to humans, not only in tropical and subtropical areas, but also in North America and parts of Europe. These viral infections are generally transmitted by mosquitoes, but may also be tick-borne. Infection usually results in mild flu-like symptoms, but can also cause encephalitis and fatalities. Approximately 2799 severe West Nile virus cases were reported this year in the United States, resulting in 102 fatalities. With this alarming increase in the number of West Nile virus infections in western countries and the fact that dengue virus already affects millions of people per year in tropical and subtropical climates, there is a real need for effective medicines. A possible therapeutic target to combat these viruses is the protease, which is essential for virus replication. In order to provide structural information to help to guide a lead identification and optimization program, crystallizations of the NS2B–NS3 protease complexes from both dengue and West Nile viruses have been initiated. Crystals that diffract to high resolution, suitable for three-dimensional structure determinations, have been obtained

  8. Optical and EPR spectra of the thionitrosyl complex [Cr(OH2)5(NS)]2+

    DEFF Research Database (Denmark)

    Døssing, Anders Rørbæk; Dethlefsen, Johannes Wied

    2008-01-01

    . The optical data indicate that the NS ligand is a weaker p-acceptor than the NO ligand. The EPR parameters of [Cr(OH2)5(NS)]2+ were determined: giso, g¦ and g-: 1.96515, 1.92686(5) and 1.986860(8); Aiso(53Cr), A¦(53Cr) and A-(53Cr): 25.3´10-4, 38´10-4 and 18.5´10-4cm-1; Aiso(14N), A¦(14N) and A-(14N): 6...

  9. In Silico Screening, Alanine Mutation, and DFT Approaches for Identification of NS2B/NS3 Protease Inhibitors

    Directory of Open Access Journals (Sweden)

    R. Balajee

    2016-01-01

    Full Text Available To identify the ligand that binds to a target protein with high affinity is a nontrivial task in computer-assisted approaches. Antiviral drugs have been identified for NS2B/NS3 protease enzyme on the mechanism to cleave the viral protein using the computational tools. The consequence of the molecular docking, free energy calculations, and simulation protocols explores the better ligand. It provides in-depth structural insights with the catalytic triad of His51, Asp75, Ser135, and Gly133. The MD simulation was employed here to predict the stability of the complex. The alanine mutation has been performed and its stability was monitored by using the molecular dynamics simulation. The minimal RMSD value suggests that the derived complexes are close to equilibrium. The DFT outcome reveals that the HOMO-LUMO gap of Ligand19 is 2.86 kcal/mol. Among the considered ligands, Ligand19 shows the lowest gap and it is suggested that the HOMO of Ligand19 may transfer the electrons to the LUMO in the active regions. The calculated binding energy of Ligand19 using the DFT method is in good agreement with the docking studies. The pharmacological activity of ligand was performed and satisfies Lipinski rule of 5. Moreover, the computational results are compared with the available IC50 values of experimental results.

  10. Stochastic simulation of karst conduit networks

    Science.gov (United States)

    Pardo-Igúzquiza, Eulogio; Dowd, Peter A.; Xu, Chaoshui; Durán-Valsero, Juan José

    2012-01-01

    Karst aquifers have very high spatial heterogeneity. Essentially, they comprise a system of pipes (i.e., the network of conduits) superimposed on rock porosity and on a network of stratigraphic surfaces and fractures. This heterogeneity strongly influences the hydraulic behavior of the karst and it must be reproduced in any realistic numerical model of the karst system that is used as input to flow and transport modeling. However, the directly observed karst conduits are only a small part of the complete karst conduit system and knowledge of the complete conduit geometry and topology remains spatially limited and uncertain. Thus, there is a special interest in the stochastic simulation of networks of conduits that can be combined with fracture and rock porosity models to provide a realistic numerical model of the karst system. Furthermore, the simulated model may be of interest per se and other uses could be envisaged. The purpose of this paper is to present an efficient method for conditional and non-conditional stochastic simulation of karst conduit networks. The method comprises two stages: generation of conduit geometry and generation of topology. The approach adopted is a combination of a resampling method for generating conduit geometries from templates and a modified diffusion-limited aggregation method for generating the network topology. The authors show that the 3D karst conduit networks generated by the proposed method are statistically similar to observed karst conduit networks or to a hypothesized network model. The statistical similarity is in the sense of reproducing the tortuosity index of conduits, the fractal dimension of the network, the direction rose of directions, the Z-histogram and Ripley's K-function of the bifurcation points (which differs from a random allocation of those bifurcation points). The proposed method (1) is very flexible, (2) incorporates any experimental data (conditioning information) and (3) can easily be modified when

  11. Speeding Up Network Simulations Using Discrete Time

    OpenAIRE

    Lucas, Aaron; Armbruster, Benjamin

    2013-01-01

    We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the accuracy attained. We also discuss the choice of step size and do an analytical comparison of the computational costs. Our error bound concept comes from the theory of numerical methods for SDEs and the basic proof structure comes from the theory of numeri...

  12. 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.

  13. LANES - LOCAL AREA NETWORK EXTENSIBLE SIMULATOR

    Science.gov (United States)

    Gibson, J.

    1994-01-01

    The Local Area Network Extensible Simulator (LANES) provides a method for simulating the performance of high speed local area network (LAN) technology. LANES was developed as a design and analysis tool for networking on board the Space Station. The load, network, link and physical layers of a layered network architecture are all modeled. LANES models to different lower-layer protocols, the Fiber Distributed Data Interface (FDDI) and the Star*Bus. The load and network layers are included in the model as a means of introducing upper-layer processing delays associated with message transmission; they do not model any particular protocols. FDDI is an American National Standard and an International Organization for Standardization (ISO) draft standard for a 100 megabit-per-second fiber-optic token ring. Specifications for the LANES model of FDDI are taken from the Draft Proposed American National Standard FDDI Token Ring Media Access Control (MAC), document number X3T9.5/83-16 Rev. 10, February 28, 1986. This is a mature document describing the FDDI media-access-control protocol. Star*Bus, also known as the Fiber Optic Demonstration System, is a protocol for a 100 megabit-per-second fiber-optic star-topology LAN. This protocol, along with a hardware prototype, was developed by Sperry Corporation under contract to NASA Goddard Space Flight Center as a candidate LAN protocol for the Space Station. LANES can be used to analyze performance of a networking system based on either FDDI or Star*Bus under a variety of loading conditions. Delays due to upper-layer processing can easily be nullified, allowing analysis of FDDI or Star*Bus as stand-alone protocols. LANES is a parameter-driven simulation; it provides considerable flexibility in specifying both protocol an run-time parameters. Code has been optimized for fast execution and detailed tracing facilities have been included. LANES was written in FORTRAN 77 for implementation on a DEC VAX under VMS 4.6. It consists of two

  14. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

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

  15. Docking, synthesis and bioassay studies of imine derivatives as potential inhibitors for dengue NS2B/ NS3 serine protease

    Directory of Open Access Journals (Sweden)

    Neni Frimayanti

    2017-11-01

    Full Text Available Objective: To search imine derivatives as new active agents against dengue type 2 NS2B/NS3 using molecular docking, since there is no effective vaccine against flaviviral infections. Methods: In this research, molecular docking was performed for a series of imine derivatives and the information obtained from the docking studies was used to explore the binding modes of these imine derivatives with dengue type 2 NS2B/NS3 serine protease. A set of imine were synthesized and bioassay study of the inhibitory activities of these compounds was then performed. Results: The results indicated that MY8 and MY4 have the ability to inhibit DEN2 NS2B/NS3 proteolytic activity. Conclusions: These two compounds were chosen as the reference for the next stage in drug design as new inhibitor agents against NS2B/NS3.

  16. Evaluasi Kinerja IEEE 802.11e HCCA untuk Dukungan QoS pada WLAN Menggunakan NS-2

    Directory of Open Access Journals (Sweden)

    Amry Daulat Gultom

    2014-06-01

    Full Text Available Wireless Local Area Network (WLAN digunakan oleh trafik multimedia yang seharusnya memerlukan persyaratan jaringan yang lebih baik terhadap delay, jitter dan packet losses. IEEE 802.11 Task Group E memperkenalkan perbaikan protokol MAC 802.11, yaitu Hybrid Coordination Function (HCF, yang terdiri dari dua mekanisme akses: Enhanced Distributed Channel Access (EDCA dan HCF Controlled Channel Access (HCCA yang memberikan dukungan Kualitas Layanan/Quality of Service (QoS bagi trafik multimedia. Tujuan dari penelitian ini adalah untuk memahami algoritma protokol MAC IEEE 802.11e HCCA pada jaringan WLAN, dan menganalisis kinerja protokol MAC 802.11e HCCA pada aplikasi multimedia dengan menggunakan metode simulasi pada NS-2. Metrik kinerja yang diukur adalah jitter dan throughput-nya. Hasil penelitian ini menunjukkan bahwa protokol MAC HCCA dapat memberikan jaminan QoS dibanding protokol MAC DCF, dimana jitter HCCA lebih stabil dari pada jitter DCF. Begitupula dengan throughput HCCA yang tidak berubah selama trafik berlangsung, tidak seperti pada DCF yang masih mengalami fluktuasi yang besar.

  17. NMR analysis of the dynamic exchange of the NS2B cofactor between open and closed conformations of the West Nile virus NS2B-NS3 protease.

    Directory of Open Access Journals (Sweden)

    Xun-Cheng Su

    Full Text Available BACKGROUND: The two-component NS2B-NS3 proteases of West Nile and dengue viruses are essential for viral replication and established targets for drug development. In all crystal structures of the proteases to date, the NS2B cofactor is located far from the substrate binding site (open conformation in the absence of inhibitor and lining the substrate binding site (closed conformation in the presence of an inhibitor. METHODS: In this work, nuclear magnetic resonance (NMR spectroscopy of isotope and spin-labeled samples of the West Nile virus protease was used to investigate the occurrence of equilibria between open and closed conformations in solution. FINDINGS: In solution, the closed form of the West Nile virus protease is the predominant conformation irrespective of the presence or absence of inhibitors. Nonetheless, dissociation of the C-terminal part of the NS2B cofactor from the NS3 protease (open conformation occurs in both the presence and the absence of inhibitors. Low-molecular-weight inhibitors can shift the conformational exchange equilibria so that over 90% of the West Nile virus protease molecules assume the closed conformation. The West Nile virus protease differs from the dengue virus protease, where the open conformation is the predominant form in the absence of inhibitors. CONCLUSION: Partial dissociation of NS2B from NS3 has implications for the way in which the NS3 protease can be positioned with respect to the host cell membrane when NS2B is membrane associated via N- and C-terminal segments present in the polyprotein. In the case of the West Nile virus protease, discovery of low-molecular-weight inhibitors that act by breaking the association of the NS2B cofactor with the NS3 protease is impeded by the natural affinity of the cofactor to the NS3 protease. The same strategy can be more successful in the case of the dengue virus NS2B-NS3 protease.

  18. Neural Network Emulation of Reionization Simulations

    Science.gov (United States)

    Schmit, Claude J.; Pritchard, Jonathan R.

    2018-05-01

    Next generation radio experiments such as LOFAR, HERA and SKA are expected to probe the Epoch of Reionization and claim a first direct detection of the cosmic 21cm signal within the next decade. One of the major challenges for these experiments will be dealing with enormous incoming data volumes. Machine learning is key to increasing our data analysis efficiency. We consider the use of an artificial neural network to emulate 21cmFAST simulations and use it in a Bayesian parameter inference study. We then compare the network predictions to a direct evaluation of the EoR simulations and analyse the dependence of the results on the training set size. We find that the use of a training set of size 100 samples can recover the error contours of a full scale MCMC analysis which evaluates the model at each step.

  19. Enabling parallel simulation of large-scale HPC network systems

    International Nuclear Information System (INIS)

    Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; Carns, Philip

    2016-01-01

    Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks used in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations

  20. Mesoscopic Simulations of Crosslinked Polymer Networks

    Science.gov (United States)

    Megariotis, Grigorios; Vogiatzis, Georgios G.; Schneider, Ludwig; Müller, Marcus; Theodorou, Doros N.

    2016-08-01

    A new methodology and the corresponding C++ code for mesoscopic simulations of elastomers are presented. The test system, crosslinked ds-1’4-polyisoprene’ is simulated with a Brownian Dynamics/kinetic Monte Carlo algorithm as a dense liquid of soft, coarse-grained beads, each representing 5-10 Kuhn segments. From the thermodynamic point of view, the system is described by a Helmholtz free-energy containing contributions from entropic springs between successive beads along a chain, slip-springs representing entanglements between beads on different chains, and non-bonded interactions. The methodology is employed for the calculation of the stress relaxation function from simulations of several microseconds at equilibrium, as well as for the prediction of stress-strain curves of crosslinked polymer networks under deformation.

  1. Model-based Compositional Design of Networked Control Systems

    Science.gov (United States)

    2013-12-01

    with event scheduling. In particular, the C++ source code for the ns-2 simulator scheduler is modi - fied to implement the time synchronization mechanism...pump: Security attacks and defenses for a diabetes therapy system. In: 2011 13th IEEE International Conference In e-Health Networking Applications and

  2. Dengue Virus NS2B/NS3 Protease Inhibitors Exploiting the Prime Side.

    Science.gov (United States)

    Lin, Kuan-Hung; Ali, Akbar; Rusere, Linah; Soumana, Djade I; Kurt Yilmaz, Nese; Schiffer, Celia A

    2017-05-15

    The mosquito-transmitted dengue virus (DENV) infects millions of people in tropical and subtropical regions. Maturation of DENV particles requires proper cleavage of the viral polyprotein, including processing of 8 of the 13 substrate cleavage sites by dengue virus NS2B/NS3 protease. With no available direct-acting antiviral targeting DENV, NS2/NS3 protease is a promising target for inhibitor design. Current design efforts focus on the nonprime side of the DENV protease active site, resulting in highly hydrophilic and nonspecific scaffolds. However, the prime side also significantly modulates DENV protease binding affinity, as revealed by engineering the binding loop of aprotinin, a small protein with high affinity for DENV protease. In this study, we designed a series of cyclic peptides interacting with both sides of the active site as inhibitors of dengue virus protease. The design was based on two aprotinin loops and aimed to leverage both key specific interactions of substrate sequences and the entropic advantage driving aprotinin's high affinity. By optimizing the cyclization linker, length, and amino acid sequence, the tightest cyclic peptide achieved a K i value of 2.9 μM against DENV3 wild-type (WT) protease. These inhibitors provide proof of concept that both sides of DENV protease active site can be exploited to potentially achieve specificity and lower hydrophilicity in the design of inhibitors targeting DENV. IMPORTANCE Viruses of the flaviviral family, including DENV and Zika virus transmitted by Aedes aegypti , continue to be a threat to global health by causing major outbreaks in tropical and subtropical regions, with no available direct-acting antivirals for treatment. A better understanding of the molecular requirements for the design of potent and specific inhibitors against flaviviral proteins will contribute to the development of targeted therapies for infections by these viruses. The cyclic peptides reported here as DENV protease inhibitors

  3. Supersymmetric non-singular fractional D2-branes and NS-NS 2-branes

    International Nuclear Information System (INIS)

    Cvetic, M.; Gibbons, G.W.; Lue, H.; Pope, C.N.

    2001-01-01

    We obtain regular deformed D2-brane solutions with fractional D2-branes arising as wrapped D4-branes. The space transverse to the D2-brane is a complete Ricci-flat 7-manifold of G 2 holonomy, which is asymptotically conical with principal orbits that are topologically CP 3 or the flag manifold SU(3)/(U(1)xU(1)). We obtain the solution by first constructing an L 2 normalisable harmonic 3-form. We also review a previously-obtained regular deformed D2-brane whose transverse space is a different 7-manifold of G 2 holonomy, with principal orbits that are topologically S 3 xS 3 . This describes D2-branes with fractional NS-NS 2-branes coming from the wrapping of 5-branes, which is supported by a non-normalisable harmonic 3-form on the 7-manifold. We prove that both types of solutions are supersymmetric, preserving 1/16 of the maximal supersymmetry and hence that they are dual to N=1 three-dimensional gauge theories. In each case, the spectrum for minimally-coupled scalars is discrete, indicating confinement in the infrared region of the dual gauge theories. We examine resolutions of other branes, and obtain necessary conditions for their regularity. The resolution of many of these seems to lie beyond supergravity. In the process of studying these questions, we construct new explicit examples of complete Ricci-flat metrics

  4. CALIDAD DE SERVICIO EN REDES IPv4 Y SU SIMULACIÓN EN NS-2

    Directory of Open Access Journals (Sweden)

    Jaime Andrés Vallejo Avellaneda

    2012-05-01

    Full Text Available Se evalúan algunas características presentadas a la hora de garantizar calidad de servicio como son el ancho de banda y la pérdida de paquetes, sobre una topología de red que involucra tres tipos de tráfico (CBR, Pareto y Exponencial.  Se implementan cinco configuraciones diferentes en el simulador de redes NS2, donde el primero corresponde a un caso sin QoS, con una capacidad de canal  que es suficientemente grande para trasmitir los tres tipos de tráfico, mientras que en las siguientes cuatro configuraciones la capacidad se reduce a un menor tamaño y se estudian  diferentes casos de calidad de servicio.Para observar el comportamiento de los tráficos se implementa inicialmente una red sin QoS con dos tipos de encolamiento y posteriormente se realiza una configuración que implementa QoS mediante los modelos IntServ y DiffServ.Los resultados obtenidos de estas simulaciones son graficados y comparados con el fin de determinar el comportamiento más adecuado en redes IP.

  5. Computer Aided Screening of Phytochemicals from Garcinia against the Dengue NS2B/NS3 Protease.

    Science.gov (United States)

    Qamar, Tahir Ul; Mumtaz, Arooj; Ashfaq, Usman Ali; Azhar, Samia; Fatima, Tabeer; Hassan, Muhammad; Hussain, Syed Sajid; Akram, Waheed; Idrees, Sobia

    2014-01-01

    Dengue virus NS2/NS3 protease because of its ability to cleave viral proteins is considered as an attractive target to screen antiviral agents. Medicinal plants contain a variety of phytochemicals that can be used as drug against different diseases and infections. Therefore, this study was designed to uncover possible phytochemical of different classes (Aromatic, Carbohydrates, Lignin, Saponins, Steroids, Tannins, Terpenoids, Xanthones) that could be used as inhibitors against the NS2B/NS3 protease of DENV. With the help of molecular docking, Garcinia phytochemicals found to be bound deeply inside the active site of DENV NS2B/NS3 protease among all tested phytochemicals and had interactions with catalytic triad (His51, Asp75, Ser135). Thus, it can be concluded from the study that these Gracinia phytochemicals could serve as important inhibitors to inhibit the viral replication inside the host cell. Further in-vitro investigations require confirming their efficacy.

  6. Analysis of Time Delay Simulation in Networked Control System

    OpenAIRE

    Nyan Phyo Aung; Zaw Min Naing; Hla Myo Tun

    2016-01-01

    The paper presents a PD controller for the Networked Control Systems (NCS) with delay. The major challenges in this networked control system (NCS) are the delay of the data transmission throughout the communication network. The comparative performance analysis is carried out for different delays network medium. In this paper, simulation is carried out on Ac servo motor control system using CAN Bus as communication network medium. The True Time toolbox of MATLAB is used for simulation to analy...

  7. 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.

  8. 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.

  9. Primitive chain network simulations of probe rheology.

    Science.gov (United States)

    Masubuchi, Yuichi; Amamoto, Yoshifumi; Pandey, Ankita; Liu, Cheng-Yang

    2017-09-27

    Probe rheology experiments, in which the dynamics of a small amount of probe chains dissolved in immobile matrix chains is discussed, have been performed for the development of molecular theories for entangled polymer dynamics. Although probe chain dynamics in probe rheology is considered hypothetically as single chain dynamics in fixed tube-shaped confinement, it has not been fully elucidated. For instance, the end-to-end relaxation of probe chains is slower than that for monodisperse melts, unlike the conventional molecular theories. In this study, the viscoelastic and dielectric relaxations of probe chains were calculated by primitive chain network simulations. The simulations semi-quantitatively reproduced the dielectric relaxation, which reflects the effect of constraint release on the end-to-end relaxation. Fair agreement was also obtained for the viscoelastic relaxation time. However, the viscoelastic relaxation intensity was underestimated, possibly due to some flaws in the model for the inter-chain cross-correlations between probe and matrix chains.

  10. Chain networking revealed by molecular dynamics simulation

    Science.gov (United States)

    Zheng, Yexin; Tsige, Mesfin; Wang, Shi-Qing

    Based on Kremer-Grest model for entangled polymer melts, we demonstrate how the response of a polymer glass depends critically on the chain length. After quenching two melts of very different chain lengths (350 beads per chain and 30 beads per chain) into deeply glassy states, we subject them to uniaxial extension. Our MD simulations show that the glass of long chains undergoes stable necking after yielding whereas the system of short chains is unable to neck and breaks up after strain localization. During ductile extension of the polymer glass made of long chain significant chain tension builds up in the load-bearing strands (LBSs). Further analysis is expected to reveal evidence of activation of the primary structure during post-yield extension. These results lend support to the recent molecular model 1 and are the simulations to demonstrate the role of chain networking. This work is supported, in part, by a NSF Grant (DMR-EAGER-1444859)

  11. Modeling And Simulation Of Multimedia Communication Networks

    Science.gov (United States)

    Vallee, Richard; Orozco-Barbosa, Luis; Georganas, Nicolas D.

    1989-05-01

    In this paper, we present a simulation study of a browsing system involving radiological image servers. The proposed IEEE 802.6 DQDB MAN standard is designated as the computer network to transfer radiological images from file servers to medical workstations, and to simultaneously support real time voice communications. Storage and transmission of original raster scanned images and images compressed according to pyramid data structures are considered. Different types of browsing as well as various image sizes and bit rates in the DQDB MAN are also compared. The elapsed time, measured from the time an image request is issued until the image is displayed on the monitor, is the parameter considered to evaluate the system performance. Simulation results show that image browsing can be supported by the DQDB MAN.

  12. Event-based simulation of networks with pulse delayed coupling

    Science.gov (United States)

    Klinshov, Vladimir; Nekorkin, Vladimir

    2017-10-01

    Pulse-mediated interactions are common in networks of different nature. Here we develop a general framework for simulation of networks with pulse delayed coupling. We introduce the discrete map governing the dynamics of such networks and describe the computation algorithm for its numerical simulation.

  13. Application of the random phase approximation to some atoms with ns2 ground state configurations

    International Nuclear Information System (INIS)

    Wright, L.A.

    1975-01-01

    Atomic bound state properties such as excitation energies and oscillator strengths were calculated by the Random Phase Approximation (RPA), also known as the Time Dependent Hartree-Fock Approximation (TDHFA). The RPA is equivalent to describing excited states as the creation of particle-hole pairs and the application to atoms is important for two reasons: the wide range of densities in an atom will cause the physical interpretation and mathematical approximations to be much different than with a uniform density system, such as an electron gas; this method could detect the existence of collective states in atoms similar to those responsible for the giant dipole resonances in nuclei. The method is shown to be superior to the H-F method in three basic ways: (1) The RPA contains explicit correlations between the excited and ground states. These are not included in the H-F theory. One can apply this method to large atoms since only these correlations are explicitly included. (2) The RPA calculates excitation energies directly without recourse to highly correlated ground state wavefunctions. This is in contrast to the method of configuration mixing which is known to have slow convergence properties. (3) Oscillator strengths and photoionization cross sections can be calculated by finding the eigenvectors corresponding excitation energy eigenvalues. The strength of the RPA is that the excitation energies and oscillator strengths, which are relative quantities, are calculated directly. The results for the oscillator strengths show an improvement of up to 45 percent over the H-F values and an improvement over the RPA done with Hartree wavefunctions by as much as 65 percent. The work was limited to atoms with an ns 2 ground state configuration. These atoms were He, Be, Mg and Ca

  14. Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo.

    Science.gov (United States)

    Yuan, Shuofeng; Chan, Jasper Fuk-Woo; den-Haan, Helena; Chik, Kenn Ka-Heng; Zhang, Anna Jinxia; Chan, Chris Chung-Sing; Poon, Vincent Kwok-Man; Yip, Cyril Chik-Yan; Mak, Winger Wing-Nga; Zhu, Zheng; Zou, Zijiao; Tee, Kah-Meng; Cai, Jian-Piao; Chan, Kwok-Hung; de la Peña, Jorge; Pérez-Sánchez, Horacio; Cerón-Carrasco, José Pedro; Yuen, Kwok-Yung

    2017-09-01

    Zika virus (ZIKV) infection may be associated with severe complications in fetuses and adults, but treatment options are limited. We performed an in silico structure-based screening of a large chemical library to identify potential ZIKV NS2B-NS3 protease inhibitors. Clinically approved drugs belonging to different drug classes were selected among the 100 primary hit compounds with the highest predicted binding affinities to ZIKV NS2B-NS3-protease for validation studies. ZIKV NS2B-NS3 protease inhibitory activity was validated in most of the selected drugs and in vitro anti-ZIKV activity was identified in two of them (novobiocin and lopinavir-ritonavir). Molecular docking and molecular dynamics simulations predicted that novobiocin bound to ZIKV NS2B-NS3-protease with high stability. Dexamethasone-immunosuppressed mice with disseminated ZIKV infection and novobiocin treatment had significantly (P < 0.05) higher survival rate (100% vs 0%), lower mean blood and tissue viral loads, and less severe histopathological changes than untreated controls. This structure-based drug discovery platform should facilitate the identification of additional enzyme inhibitors of ZIKV. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Assessment of Drug Binding Potential of Pockets in the NS2B/NS3 Dengue Virus Protein

    Science.gov (United States)

    Amelia, F.; Iryani; Sari, P. Y.; Parikesit, A. A.; Bakri, R.; Toepak, E. P.; Tambunan, U. S. F.

    2018-04-01

    Every year an endemic dengue fever estimated to affect over 390 million cases in over 128 countries occurs. However, the antigen types which stimulate the human immune response are variable, as a result, neither effective vaccines nor antiviral treatments have been successfully developed for this disease. The NS2B/NS3 protease of the dengue virus (DENV) responsible for viral replication is a potential drug target. The ligand-enzyme binding site determination is a key role in the success of virtual screening of new inhibitors. The NS2B/NS3 protease of DENV (PDB ID: 2FOM) has two pockets consisting of 37 (Pocket 1) and 27 (Pocket 2) amino acid residues in each pocket. In this research, we characterized the amino acid residues for binding sites in NS3/NS2B based on the hydrophobicity, the percentage of charged residues, volume, depth, ΔGbinding, hydrogen bonding and bond length. The hydrophobic percentages of both pockets are high, 59 % (Pocket 1) and 41% (Pocket 2) and the percentage of charged residues in Pocket 1 and 2 are 22% and 48%, and the pocket volume is less than 700 Å3. An interaction analysis using molecular docking showed that interaction between the ligand complex and protein in Pocket 1 is more negative than Pocket 2. As a result, Pocket 1 is the better potential target for a ligand to inhibit the action of NS2B/NS3 DENV.

  16. 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...

  17. Programmable multi-node quantum network design and simulation

    Science.gov (United States)

    Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

    2016-05-01

    Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

  18. Integrated workflows for spiking neuronal network simulations

    Directory of Open Access Journals (Sweden)

    Ján eAntolík

    2013-12-01

    Full Text Available The increasing availability of computational resources is enabling more detailed, realistic modelling in computational neuroscience, resulting in a shift towards more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeller's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modellers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity.To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualisation into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organised configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualisation stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modelling studies by relieving the user from manual handling of the flow of metadata between the individual

  19. 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...

  20. BioNessie - a grid enabled biochemical networks simulation environment

    OpenAIRE

    Liu, X.; Jiang, J.; Ajayi, O.; Gu, X.; Gilbert, D.; Sinnott, R.O.

    2008-01-01

    The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations.

  1. The design and implementation of a network simulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2013-11-01

    Full Text Available these events and their effects can enable researchers to identify these threats and find ways to counter them. In this paper we present the design of a network simulation platform which can enable researchers to study dynamic behaviour of networks, network...

  2. Small-angle X-Ray analysis of macromolecular structure: the structure of protein NS2 (NEP) in solution

    Science.gov (United States)

    Shtykova, E. V.; Bogacheva, E. N.; Dadinova, L. A.; Jeffries, C. M.; Fedorova, N. V.; Golovko, A. O.; Baratova, L. A.; Batishchev, O. V.

    2017-11-01

    A complex structural analysis of nuclear export protein NS2 (NEP) of influenza virus A has been performed using bioinformatics predictive methods and small-angle X-ray scattering data. The behavior of NEP molecules in a solution (their aggregation, oligomerization, and dissociation, depending on the buffer composition) has been investigated. It was shown that stable associates are formed even in a conventional aqueous salt solution at physiological pH value. For the first time we have managed to get NEP dimers in solution, to analyze their structure, and to compare the models obtained using the method of the molecular tectonics with the spatial protein structure predicted by us using the bioinformatics methods. The results of the study provide a new insight into the structural features of nuclear export protein NS2 (NEP) of the influenza virus A, which is very important for viral infection development.

  3. Accelerator and feedback control simulation using neural networks

    International Nuclear Information System (INIS)

    Nguyen, D.; Lee, M.; Sass, R.; Shoaee, H.

    1991-05-01

    Unlike present constant model feedback system, neural networks can adapt as the dynamics of the process changes with time. Using a process model, the ''Accelerator'' network is first trained to simulate the dynamics of the beam for a given beam line. This ''Accelerator'' network is then used to train a second ''Controller'' network which performs the control function. In simulation, the networks are used to adjust corrector magnetics to control the launch angle and position of the beam to keep it on the desired trajectory when the incoming beam is perturbed. 4 refs., 3 figs

  4. 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.   

  5. Network simulation of nonstationary ionic transport through liquid junctions

    International Nuclear Information System (INIS)

    Castilla, J.; Horno, J.

    1993-01-01

    Nonstationary ionic transport across the liquid junctions has been studied using Network Thermodynamics. A network model for the time-dependent Nernst-Plack-Poisson system of equation is proposed. With this network model and the electrical circuit simulation program PSPICE, the concentrations, charge density, and electrical potentials, at short times, have been simulated for the binary system NaCl/NaCl. (Author) 13 refs

  6. Identification of novel small molecule inhibitors against NS2B/NS3 serine protease from Zika virus

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hyun; Ren, Jinhong; Nocadello, Salvatore; Rice, Amy J.; Ojeda, Isabel; Light, Samuel; Minasov, George; Vargas, Jason; Nagarathnam, Dhanapalan; Anderson, Wayne F.; Johnson, Michael E. (UIC); (NWU); (Novalex); (DNSK)

    2016-12-26

    Zika flavivirus infection during pregnancy appears to produce higher risk of microcephaly, and also causes multiple neurological problems such as Guillain–Barré syndrome. The Zika virus is now widespread in Central and South America, and is anticipated to become an increasing risk in the southern United States. With continuing global travel and the spread of the mosquito vector, the exposure is expected to accelerate, but there are no currently approved treatments against the Zika virus. The Zika NS2B/NS3 protease is an attractive drug target due to its essential role in viral replication. Our studies have identified several compounds with inhibitory activity (IC50) and binding affinity (KD) of ~5–10 μM against the Zika NS2B-NS3 protease from testing 71 HCV NS3/NS4A inhibitors that were initially discovered by high-throughput screening of 40,967 compounds. Competition surface plasmon resonance studies and mechanism of inhibition analyses by enzyme kinetics subsequently determined the best compound to be a competitive inhibitor with a Ki value of 9.5 μM. We also determined the X-ray structure of the Zika NS2B-NS3 protease in a “pre-open conformation”, a conformation never observed before for any flavivirus proteases. This provides the foundation for new structure-based inhibitor design.

  7. Biological transportation networks: Modeling and simulation

    KAUST Repository

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

    2015-01-01

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

  8. Toward Designing a Quantum Key Distribution Network Simulation Model

    OpenAIRE

    Miralem Mehic; Peppino Fazio; Miroslav Voznak; Erik Chromy

    2016-01-01

    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 ...

  9. Cooperative Media Streaming Using Adaptive Network Compression

    DEFF Research Database (Denmark)

    Møller, Janus Heide; Sørensen, Jesper Hemming; Krigslund, Rasmus

    2008-01-01

    as an adaptive hybrid between LC and MDC. In order to facilitate the use of MDC-CC, a new overlay network approach is proposed, using tree of meshes. A control system for managing description distribution and compression in a small mesh is implemented in the discrete event simulator NS-2. The two traditional...... approaches, MDC and LC, are used as references for the performance evaluation of the proposed scheme. The system is simulated in a heterogeneous network environment, where packet errors are introduced. Moreover, a test is performed at different network loads. Performance gain is shown over both LC and MDC....

  10. BioNSi: A Discrete Biological Network Simulator Tool.

    Science.gov (United States)

    Rubinstein, Amir; Bracha, Noga; Rudner, Liat; Zucker, Noga; Sloin, Hadas E; Chor, Benny

    2016-08-05

    Modeling and simulation of biological networks is an effective and widely used research methodology. The Biological Network Simulator (BioNSi) is a tool for modeling biological networks and simulating their discrete-time dynamics, implemented as a Cytoscape App. BioNSi includes a visual representation of the network that enables researchers to construct, set the parameters, and observe network behavior under various conditions. To construct a network instance in BioNSi, only partial, qualitative biological data suffices. The tool is aimed for use by experimental biologists and requires no prior computational or mathematical expertise. BioNSi is freely available at http://bionsi.wix.com/bionsi , where a complete user guide and a step-by-step manual can also be found.

  11. 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.

  12. 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.

  13. 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.

  14. A framework for visualization of battlefield network behavior

    Science.gov (United States)

    Perzov, Yury; Yurcik, William

    2006-05-01

    An extensible network simulation application was developed to study wireless battlefield communications. The application monitors node mobility and depicts broadcast and unicast traffic as expanding rings and directed links. The network simulation was specially designed to support fault injection to show the impact of air strikes on disabling nodes. The application takes standard ns-2 trace files as an input and provides for performance data output in different graphical forms (histograms and x/y plots). Network visualization via animation of simulation output can be saved in AVI format that may serve as a basis for a real-time battlefield awareness system.

  15. 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.

  16. 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.

  17. 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...

  18. Trends in ns 2np 0 [M(CO)] q+ complexes: From germanium to element 114 (Uuq)

    Science.gov (United States)

    Gourlaouen, C.; Parisel, O.; Piquemal, J.-P.

    2009-02-01

    The present contribution reports investigations on the metal-ligand bond lengths and interaction energies in selected carbon monoxide complexes of metal cations sharing the ns2np0 valence configuration. 1- and 4-component DFT geometry optimizations have been performed for cations ranging from Ge2+ to Uuq2+, the dication of element 114 (Ununquadium). The nature of the bonding has been studied by means of energy decomposition analysis. The magnitude of the relativistic effects is shown to evolve slowly and to become predominant for Uuq for the molecular properties investigated.

  19. Ranking important nodes in complex networks by simulated annealing

    International Nuclear Information System (INIS)

    Sun Yu; Yao Pei-Yang; Shen Jian; Zhong Yun; Wan Lu-Jun

    2017-01-01

    In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented. First, the concept of an importance sequence (IS) to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks. (paper)

  20. 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.

  1. 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".

  2. Mesoscopic simulations of crosslinked polymer networks

    NARCIS (Netherlands)

    Megariotis, G.; Vogiatzis, G.G.; Schneider, L.; Müller, M.; Theodorou, D.N.

    2016-01-01

    A new methodology and the corresponding C++ code for mesoscopic simulations of elastomers are presented. The test system, crosslinked ds-1'4-polyisoprene' is simulated with a Brownian Dynamics/kinetic Monte Carlo algorithm as a dense liquid of soft, coarse-grained beads, each representing 5-10 Kuhn

  3. Optimization of blanking process using neural network simulation

    International Nuclear Information System (INIS)

    Hambli, R.

    2005-01-01

    The present work describes a methodology using the finite element method and neural network simulation in order to predict the optimum punch-die clearance during sheet metal blanking processes. A damage model is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. Numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling. The comparative study between the numerical results and the experimental ones shows the good agreement. (author)

  4. 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.

  5. Simulating individual-based models of epidemics in hierarchical networks

    NARCIS (Netherlands)

    Quax, R.; Bader, D.A.; Sloot, P.M.A.

    2009-01-01

    Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics

  6. Simulation studies of a wide area health care network.

    Science.gov (United States)

    McDaniel, J. G.

    1994-01-01

    There is an increasing number of efforts to install wide area health care networks. Some of these networks are being built to support several applications over a wide user base consisting primarily of medical practices, hospitals, pharmacies, medical laboratories, payors, and suppliers. Although on-line, multi-media telecommunication is desirable for some purposes such as cardiac monitoring, store-and-forward messaging is adequate for many common, high-volume applications. Laboratory test results and payment claims, for example, can be distributed using electronic messaging networks. Several network prototypes have been constructed to determine the technical problems and to assess the effectiveness of electronic messaging in wide area health care networks. Our project, Health Link, developed prototype software that was able to use the public switched telephone network to exchange messages automatically, reliably and securely. The network could be configured to accommodate the many different traffic patterns and cost constraints of its users. Discrete event simulations were performed on several network models. Canonical star and mesh networks, that were composed of nodes operating at steady state under equal loads, were modeled. Both topologies were found to support the throughput of a generic wide area health care network. The mean message delivery time of the mesh network was found to be less than that of the star network. Further simulations were conducted for a realistic large-scale health care network consisting of 1,553 doctors, 26 hospitals, four medical labs, one provincial lab and one insurer. Two network topologies were investigated: one using predominantly peer-to-peer communication, the other using client-server communication.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7949966

  7. A gene network simulator to assess reverse engineering algorithms.

    Science.gov (United States)

    Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio

    2009-03-01

    In the context of reverse engineering of biological networks, simulators are helpful to test and compare the accuracy of different reverse-engineering approaches in a variety of experimental conditions. A novel gene-network simulator is presented that resembles some of the main features of transcriptional regulatory networks related to topology, interaction among regulators of transcription, and expression dynamics. The simulator generates network topology according to the current knowledge of biological network organization, including scale-free distribution of the connectivity and clustering coefficient independent of the number of nodes in the network. It uses fuzzy logic to represent interactions among the regulators of each gene, integrated with differential equations to generate continuous data, comparable to real data for variety and dynamic complexity. Finally, the simulator accounts for saturation in the response to regulation and transcription activation thresholds and shows robustness to perturbations. It therefore provides a reliable and versatile test bed for reverse engineering algorithms applied to microarray data. Since the simulator describes regulatory interactions and expression dynamics as two distinct, although interconnected aspects of regulation, it can also be used to test reverse engineering approaches that use both microarray and protein-protein interaction data in the process of learning. A first software release is available at http://www.dei.unipd.it/~dicamill/software/netsim as an R programming language package.

  8. 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.

  9. 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.

  10. 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.

  11. Distributed dynamic simulations of networked control and building performance applications.

    Science.gov (United States)

    Yahiaoui, Azzedine

    2018-02-01

    The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper.

  12. Modeling and Simulation Network Data Standards

    Science.gov (United States)

    2011-09-30

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

  13. 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

  14. 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.

  15. 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.

  16. 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......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...... study of the networks themselves. With this end in view the following restrictions have been made: 1) Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. 2) Amongst numerous training algorithms, only the Recursive Prediction Error Method using...

  17. Artificial neural network simulation of battery performance

    Energy Technology Data Exchange (ETDEWEB)

    O`Gorman, C.C.; Ingersoll, D.; Jungst, R.G.; Paez, T.L.

    1998-12-31

    Although they appear deceptively simple, batteries embody a complex set of interacting physical and chemical processes. While the discrete engineering characteristics of a battery such as the physical dimensions of the individual components, are relatively straightforward to define explicitly, their myriad chemical and physical processes, including interactions, are much more difficult to accurately represent. Within this category are the diffusive and solubility characteristics of individual species, reaction kinetics and mechanisms of primary chemical species as well as intermediates, and growth and morphology characteristics of reaction products as influenced by environmental and operational use profiles. For this reason, development of analytical models that can consistently predict the performance of a battery has only been partially successful, even though significant resources have been applied to this problem. As an alternative approach, the authors have begun development of a non-phenomenological model for battery systems based on artificial neural networks. Both recurrent and non-recurrent forms of these networks have been successfully used to develop accurate representations of battery behavior. The connectionist normalized linear spline (CMLS) network has been implemented with a self-organizing layer to model a battery system with the generalized radial basis function net. Concurrently, efforts are under way to use the feedforward back propagation network to map the {open_quotes}state{close_quotes} of a battery system. Because of the complexity of battery systems, accurate representation of the input and output parameters has proven to be very important. This paper describes these initial feasibility studies as well as the current models and makes comparisons between predicted and actual performance.

  18. Dynamic Interactions for Network Visualization and Simulation

    Science.gov (United States)

    2009-03-01

    projects.htm, Site accessed January 5, 2009. 12. John S. Weir, Major, USAF, Mediated User-Simulator Interactive Command with Visualization ( MUSIC -V). Master’s...Computing Sciences in Colleges, December 2005). 14. Enrique Campos -Nanez, “nscript user manual,” Department of System Engineer- ing University of

  19. 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.

  20. Promoting Simulation Globally: Networking with Nursing Colleagues Across Five Continents.

    Science.gov (United States)

    Alfes, Celeste M; Madigan, Elizabeth A

    Simulation education is gaining momentum internationally and may provide the opportunity to enhance clinical education while disseminating evidence-based practice standards for clinical simulation and learning. There is a need to develop a cohesive leadership group that fosters support, networking, and sharing of simulation resources globally. The Frances Payne Bolton School of Nursing at Case Western Reserve University has had the unique opportunity to establish academic exchange programs with schools of nursing across five continents. Although the joint and mutual simulation activities have been extensive, each international collaboration has also provided insight into the innovations developed by global partners.

  1. 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.

  2. 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

  3. SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

    Science.gov (United States)

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

    2018-03-01

    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 with a partial integral differential equation 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. © The Author(s) 2017. Published by Oxford University Press.

  4. 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.

  5. Simulation Of Wireless Networked Control System Using TRUETIME And MATLAB

    Directory of Open Access Journals (Sweden)

    Nyan Phyo Aung

    2015-08-01

    Full Text Available Wireless networked control systems WNCS are attracting an increasing research interests in the past decade. Wireless networked control system WNCS is composed of a group of distributed sensors and actuators that communicate through wireless link which achieves distributed sensing and executing tasks. This is particularly relevant for the areas of communication control and computing where successful design of WNCS brings about new challenges to the researchers. The primary motivation of this survey paper is to examine the design issues and to provide directions for successful simulation and implementation of WNCS. The paper also as well reviews some simulation tools for such systems.

  6. Simulation of nonlinear random vibrations using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Paez, T.L.; Tucker, S.; O`Gorman, C.

    1997-02-01

    The simulation of mechanical system random vibrations is important in structural dynamics, but it is particularly difficult when the system under consideration is nonlinear. Artificial neural networks provide a useful tool for the modeling of nonlinear systems, however, such modeling may be inefficient or insufficiently accurate when the system under consideration is complex. This paper shows that there are several transformations that can be used to uncouple and simplify the components of motion of a complex nonlinear system, thereby making its modeling and random vibration simulation, via component modeling with artificial neural networks, a much simpler problem. A numerical example is presented.

  7. 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.

  8. Efficient Neural Network Modeling for Flight and Space Dynamics Simulation

    Directory of Open Access Journals (Sweden)

    Ayman Hamdy Kassem

    2011-01-01

    Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

  9. 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.

  10. Simulated annealing for tensor network states

    International Nuclear Information System (INIS)

    Iblisdir, S

    2014-01-01

    Markov chains for probability distributions related to matrix product states and one-dimensional Hamiltonians are introduced. With appropriate ‘inverse temperature’ schedules, these chains can be combined into a simulated annealing scheme for ground states of such Hamiltonians. Numerical experiments suggest that a linear, i.e., fast, schedule is possible in non-trivial cases. A natural extension of these chains to two-dimensional settings is next presented and tested. The obtained results compare well with Euclidean evolution. The proposed Markov chains are easy to implement and are inherently sign problem free (even for fermionic degrees of freedom). (paper)

  11. 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 study was performed, using the Common Open Research Emulator (CORE), to generate the necessary network simulation data. The simulation data was analysed, and then transformed into linked data. The result of the transformation is a data file that adheres...

  12. Computer simulation of randomly cross-linked polymer networks

    International Nuclear Information System (INIS)

    Williams, Timothy Philip

    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 heterogeneities were observed in the swollen model networks and were analysed by considering constituent substructures of varying size. The network connectivity determined the length scales at which the majority of the substructure unfolding process occurred. Simulated stress-strain curves and diffraction patterns for uniaxially deformed swollen networks, were found to be consistent with experimental findings. Analysis of the relaxation dynamics of various network components revealed a dramatic slowdown due to the network connectivity. The cross-link junction spatial fluctuations for networks close to the sol-gel threshold, were observed to be at least comparable with the phantom network prediction. The dangling chain ends were found to display the largest characteristic relaxation time. (author)

  13. 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 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....

  14. Novel nucleotide and amino acid covariation between the 5'UTR and the NS2/NS3 proteins of hepatitis C virus: bioinformatic and functional analyses.

    Directory of Open Access Journals (Sweden)

    Hung-Yu Sun

    Full Text Available Molecular covariation of highly polymorphic viruses is thought to have crucial effects on viral replication and fitness. This study employs association rule data mining of hepatitis C virus (HCV sequences to search for specific evolutionary covariation and then tests functional relevance on HCV replication. Data mining is performed between nucleotides in the untranslated regions 5' and 3'UTR, and the amino acid residues in the non-structural proteins NS2, NS3 and NS5B. Results indicate covariance of the 243(rd nucleotide of the 5'UTR with the 14(th, 41(st, 76(th, 110(th, 211(th and 212(th residues of NS2 and with the 71(st, 175(th and 621(st residues of NS3. Real-time experiments using an HCV subgenomic system to quantify viral replication confirm replication regulation for each covariant pair between 5'UTR₂₄₃ and NS2-41, -76, -110, -211, and NS3-71, -175. The HCV subgenomic system with/without the NS2 region shows that regulatory effects vanish without NS2, so replicative modulation mediated by HCV 5'UTR₂₄₃ depends on NS2. Strong binding of the NS2 variants to HCV RNA correlates with reduced HCV replication whereas weak binding correlates with restoration of HCV replication efficiency, as determined by RNA-protein immunoprecipitation assay band intensity. The dominant haplotype 5'UTR₂₄₃-NS2-41-76-110-211-NS3-71-175 differs according to the HCV genotype: G-Ile-Ile-Ile-Gly-Ile-Met for genotype 1b and A-Leu-Val-Leu-Ser-Val-Leu for genotypes 1a, 2a and 2b. In conclusion, 5'UTR₂₄₃ co-varies with specific NS2/3 protein amino acid residues, which may have significant structural and functional consequences for HCV replication. This unreported mechanism involving HCV replication possibly can be exploited in the development of advanced anti-HCV medication.

  15. Numerical simulation for gas-liquid two-phase flow in pipe networks

    International Nuclear Information System (INIS)

    Li Xiaoyan; Kuang Bo; Zhou Guoliang; Xu Jijun

    1998-01-01

    The complex pipe network characters can not directly presented in single phase flow, gas-liquid two phase flow pressure drop and void rate change model. Apply fluid network theory and computer numerical simulation technology to phase flow pipe networks carried out simulate and compute. Simulate result shows that flow resistance distribution is non-linear in two phase pipe network

  16. Dynamic simulation of a steam generator by neural networks

    International Nuclear Information System (INIS)

    Masini, R.; Padovani, E.; Ricotti, M.E.; Zio, E.

    1999-01-01

    Numerical simulation by computers of the dynamic evolution of complex systems and components is a fundamental phase of any modern engineering design activity. This is of particular importance for risk-based design projects which require that the system behavior be analyzed under several and often extreme conditions. The traditional methods of simulation typically entail long, iterative, processes which lead to large simulation times, often exceeding the transients real time. Artificial neural networks (ANNs) may be exploited in this context, their advantages residing mainly in the speed of computation, in the capability of generalizing from few examples, in the robustness to noisy and partially incomplete data and in the capability of performing empirical input-output mapping without complete knowledge of the underlying physics. In this paper we present a novel approach to dynamic simulation by ANNs based on a superposition scheme in which a set of networks are individually trained, each one to respond to a different input forcing function. The dynamic simulation of a steam generator is considered as an example to show the potentialities of this tool and to point out the difficulties and crucial issues which typically arise when attempting to establish an efficient neural network simulator. The structure of the networks system is such to feedback, at each time step, a portion of the past evolution of the transient and this allows a good reproduction of also non-linear dynamic behaviors. A nice characteristic of the approach is that the modularization of the training reduces substantially its burden and gives this neural simulation tool a nice feature of transportability. (orig.)

  17. 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…

  18. 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).

  19. In Vitro Evaluation of Novel Inhibitors against the NS2B-NS3 Protease of Dengue Fever Virus Type 4

    Directory of Open Access Journals (Sweden)

    Thi Thanh Hanh Nguyen

    2013-12-01

    Full Text Available The discovery of potent therapeutic compounds against dengue virus is urgently needed. The NS2B-NS3 protease (NS2B-NS3pro of dengue fever virus carries out all enzymatic activities needed for polyprotein processing and is considered to be amenable to antiviral inhibition by analogy. Virtual screening of 300,000 compounds using Autodock 3 on the GVSS platform was conducted to identify novel inhibitors against the NS2B-NS3pro. Thirty-six compounds were selected for in vitro assay against NS2B-NS3pro expressed in Pichia pastoris. Seven novel compounds were identified as inhibitors with IC50 values of 3.9 ± 0.6–86.7 ± 3.6 μM. Three strong NS2B-NS3pro inhibitors were further confirmed as competitive inhibitors with Ki values of 4.0 ± 0.4, 4.9 ± 0.3, and 3.4 ± 0.1 μM, respectively. Hydrophobic and hydrogen bond interactions between amino acid residues in the NS3pro active site with inhibition compounds were also identified.

  20. The interactomes of influenza virus NS1 and NS2 proteins identify new host factors and provide insights for ADAR1 playing a supportive role in virus replication.

    Science.gov (United States)

    de Chassey, Benoît; Aublin-Gex, Anne; Ruggieri, Alessia; Meyniel-Schicklin, Laurène; Pradezynski, Fabrine; Davoust, Nathalie; Chantier, Thibault; Tafforeau, Lionel; Mangeot, Philippe-Emmanuel; Ciancia, Claire; Perrin-Cocon, Laure; Bartenschlager, Ralf; André, Patrice; Lotteau, Vincent

    2013-01-01

    Influenza A NS1 and NS2 proteins are encoded by the RNA segment 8 of the viral genome. NS1 is a multifunctional protein and a virulence factor while NS2 is involved in nuclear export of viral ribonucleoprotein complexes. A yeast two-hybrid screening strategy was used to identify host factors supporting NS1 and NS2 functions. More than 560 interactions between 79 cellular proteins and NS1 and NS2 proteins from 9 different influenza virus strains have been identified. These interacting proteins are potentially involved in each step of the infectious process and their contribution to viral replication was tested by RNA interference. Validation of the relevance of these host cell proteins for the viral replication cycle revealed that 7 of the 79 NS1 and/or NS2-interacting proteins positively or negatively controlled virus replication. One of the main factors targeted by NS1 of all virus strains was double-stranded RNA binding domain protein family. In particular, adenosine deaminase acting on RNA 1 (ADAR1) appeared as a pro-viral host factor whose expression is necessary for optimal viral protein synthesis and replication. Surprisingly, ADAR1 also appeared as a pro-viral host factor for dengue virus replication and directly interacted with the viral NS3 protein. ADAR1 editing activity was enhanced by both viruses through dengue virus NS3 and influenza virus NS1 proteins, suggesting a similar virus-host co-evolution.

  1. The interactomes of influenza virus NS1 and NS2 proteins identify new host factors and provide insights for ADAR1 playing a supportive role in virus replication.

    Directory of Open Access Journals (Sweden)

    Benoît de Chassey

    Full Text Available Influenza A NS1 and NS2 proteins are encoded by the RNA segment 8 of the viral genome. NS1 is a multifunctional protein and a virulence factor while NS2 is involved in nuclear export of viral ribonucleoprotein complexes. A yeast two-hybrid screening strategy was used to identify host factors supporting NS1 and NS2 functions. More than 560 interactions between 79 cellular proteins and NS1 and NS2 proteins from 9 different influenza virus strains have been identified. These interacting proteins are potentially involved in each step of the infectious process and their contribution to viral replication was tested by RNA interference. Validation of the relevance of these host cell proteins for the viral replication cycle revealed that 7 of the 79 NS1 and/or NS2-interacting proteins positively or negatively controlled virus replication. One of the main factors targeted by NS1 of all virus strains was double-stranded RNA binding domain protein family. In particular, adenosine deaminase acting on RNA 1 (ADAR1 appeared as a pro-viral host factor whose expression is necessary for optimal viral protein synthesis and replication. Surprisingly, ADAR1 also appeared as a pro-viral host factor for dengue virus replication and directly interacted with the viral NS3 protein. ADAR1 editing activity was enhanced by both viruses through dengue virus NS3 and influenza virus NS1 proteins, suggesting a similar virus-host co-evolution.

  2. 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.

  3. PWR system simulation and parameter estimation with neural networks

    International Nuclear Information System (INIS)

    Akkurt, Hatice; Colak, Uener

    2002-01-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

  4. PWR system simulation and parameter estimation with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

    2002-11-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

  5. 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.

  6. Simulation of Attacks for Security in Wireless Sensor Network

    Science.gov (United States)

    Diaz, Alvaro; Sanchez, Pablo

    2016-01-01

    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. PMID:27869710

  7. 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.

  8. Brian: a simulator for spiking neural networks in python.

    Science.gov (United States)

    Goodman, Dan; Brette, Romain

    2008-01-01

    "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.

  9. ESIM_DSN Web-Enabled Distributed Simulation Network

    Science.gov (United States)

    Bedrossian, Nazareth; Novotny, John

    2002-01-01

    In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

  10. Stochastic sensitivity analysis and Langevin simulation for neural network learning

    International Nuclear Information System (INIS)

    Koda, Masato

    1997-01-01

    A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method

  11. 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.

  12. Production of cellulases from Aspergillus niger NS-2 in solid state fermentation on agricultural and kitchen waste residues.

    Science.gov (United States)

    Bansal, Namita; Tewari, Rupinder; Soni, Raman; Soni, Sanjeev Kumar

    2012-07-01

    Various agricultural and kitchen waste residues were assessed for their ability to support the production of a complete cellulase system by Aspergillus niger NS-2 in solid state fermentation. Untreated as well as acid and base-pretreated substrates including corn cobs, carrot peelings, composite, grass, leaves, orange peelings, pineapple peelings, potato peelings, rice husk, sugarcane bagasse, saw dust, wheat bran, wheat straw, simply moistened with water, were found to be well suited for the organism's growth, producing good amounts of cellulases after 96 h without the supplementation of additional nutritional sources. Yields of cellulases were higher in alkali treated substrates as compared to acid treated and untreated substrates except in wheat bran. Of all the substrates tested, wheat bran appeared to be the best suited substrate producing appreciable yields of CMCase, FPase and β-glucosidase at the levels of 310, 17 and 33 U/g dry substrate respectively. An evaluation of various environmental parameters demonstrated that appreciable levels of cellulases could be produced over a wide range of temperatures (20-50 °C) and pH levels (3.0-8.0) with a 1:1.5 to 1:1.75 substrate to moisture ratio. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. 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.

  14. Hybrid neural network bushing model for vehicle dynamics simulation

    International Nuclear Information System (INIS)

    Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk

    2008-01-01

    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

  15. Host cell killing by the West Nile Virus NS2B-NS3 proteolytic complex: NS3 alone is sufficient to recruit caspase-8-based apoptotic pathway

    International Nuclear Information System (INIS)

    Ramanathan, Mathura P.; Chambers, Jerome A.; Pankhong, Panyupa; Chattergoon, Michael; Attatippaholkun, Watcharee; Dang, Kesen; Shah, Neelima; Weiner, David B.

    2006-01-01

    The West Nile Virus (WNV) non-structural proteins 2B and 3 (NS2B-NS3) constitute the proteolytic complex that mediates the cleavage and processing of the viral polyprotein. NS3 recruits NS2B and NS5 proteins to direct protease and replication activities. In an effort to investigate the biology of the viral protease, we cloned cDNA encoding the NS2B-NS3 proteolytic complex from brain tissue of a WNV-infected dead crow, collected from the Lower Merion area (Merion strain). Expression of the NS2B-NS3 gene cassette induced apoptosis within 48 h of transfection. Electron microscopic analysis of NS2B-NS3-transfected cells revealed ultra-structural changes that are typical of apoptotic cells including membrane blebbing, nuclear disintegration and cytoplasmic vacuolations. The role of NS3 or NS2B in contributing to host cell apoptosis was examined. NS3 alone triggers the apoptotic pathways involving caspases-8 and -3. Experimental results from the use of caspase-specific inhibitors and caspase-8 siRNA demonstrated that the activation of caspase-8 was essential to initiate apoptotic signaling in NS3-expressing cells. Downstream of caspase-3 activation, we observed nuclear membrane ruptures and cleavage of the DNA-repair enzyme, PARP in NS3-expressing cells. Nuclear herniations due to NS3 expression were absent in the cells treated with a caspase-3 inhibitor. Expression of protease and helicase domains themselves was sufficient to trigger apoptosis generating insight into the apoptotic pathways triggered by NS3 from WNV

  16. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichirou; Dershowitz, W.

    2005-01-01

    During Heisei-16, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the Mizunami Underground Research Laboratory (MIU), participation in Task 6 of the AEspoe Task Force on Modeling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU support during H-16 involved updating the H-15 FracMan discrete fracture network (DFN) models for the MIU shaft region, and developing improved simulation procedures. Updates to the conceptual model included incorporation of 'Step2' (2004) versions of the deterministic structures, and revision of background fractures to be consistent with conductive structure data from the DH-2 borehole. Golder developed improved simulation procedures for these models through the use of hybrid discrete fracture network (DFN), equivalent porous medium (EPM), and nested DFN/EPM approaches. For each of these models, procedures were documented for the entire modeling process including model implementation, MMP simulation, and shaft grouting simulation. Golder supported JNC participation in Task 6AB, 6D and 6E of the AEspoe Task Force on Modeling of Groundwater Flow and Transport during H-16. For Task 6AB, Golder developed a new technique to evaluate the role of grout in performance assessment time-scale transport. For Task 6D, Golder submitted a report of H-15 simulations to SKB. For Task 6E, Golder carried out safety assessment time-scale simulations at the block scale, using the Laplace Transform Galerkin method. During H-16, Golder supported JNC's Total System Performance Assessment (TSPA) strategy by developing technologies for the analysis of the use site characterization data in safety assessment. This approach will aid in the understanding of the use of site characterization to progressively reduce site characterization uncertainty. (author)

  17. SIMULATION OF NEGATIVE PRESSURE WAVE PROPAGATION IN WATER PIPE NETWORK

    Directory of Open Access Journals (Sweden)

    Tang Van Lam

    2017-11-01

    Full Text Available Subject: factors such as pipe wall roughness, mechanical properties of pipe materials, physical properties of water affect the pressure surge in the water supply pipes. These factors make it difficult to analyze the transient problem of pressure evolution using simple programming language, especially in the studies that consider only the magnitude of the positive pressure surge with the negative pressure phase being neglected. Research objectives: determine the magnitude of the negative pressure in the pipes on the experimental model. The propagation distance of the negative pressure wave will be simulated by the valve closure scenarios with the help of the HAMMER software and it is compared with an experimental model to verify the quality the results. Materials and methods: academic version of the Bentley HAMMER software is used to simulate the pressure surge wave propagation due to closure of the valve in water supply pipe network. The method of characteristics is used to solve the governing equations of transient process of pressure change in the pipeline. This method is implemented in the HAMMER software to calculate the pressure surge value in the pipes. Results: the method has been applied for water pipe networks of experimental model, the results show the affected area of negative pressure wave from valve closure and thereby we assess the largest negative pressure that may appear in water supply pipes. Conclusions: the experiment simulates the water pipe network with a consumption node for various valve closure scenarios to determine possibility of appearance of maximum negative pressure value in the pipes. Determination of these values in real-life network is relatively costly and time-consuming but nevertheless necessary for identification of the risk of pipe failure, and therefore, this paper proposes using the simulation model by the HAMMER software. Initial calibration of the model combined with the software simulation results and

  18. OPNET simulation Signaling System No.7 (SS7) network interfaces

    OpenAIRE

    Ow, Kong Chung.

    2000-01-01

    This thesis presents an OPNET model and simulation of the Signaling System No.7 (SS7) network, which is dubbed the world's largest data communications network. The main focus of the study is to model one of its levels, the Message Transfer Part Level 3, in accordance with the ITU.T recommendation Q.704. An overview of SS7 that includes the evolution and basics of SS7 architecture is provided to familarize the reader with the topic. This includes the protocol stack, signaling points, signaling...

  19. Simulating market dynamics: interactions between consumer psychology and social networks.

    Science.gov (United States)

    Janssen, Marco A; Jager, Wander

    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 model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

  20. Standard Molar Enthalpy of Formation of RE(C5H8NS2)3(o-phen)

    Institute of Scientific and Technical Information of China (English)

    MENG Xiang-Xin; GAO Sheng-Li; CHEN San-Ping; YANG Xu-Wu; XIE Gang; SHI Qi-Zhen

    2005-01-01

    Five solid ternary complexes of RE(C5H8NS2)3(o-phen) (RE=Ho, Er, Tm, Yb, Lu) have been synthesized in absolute ethanol by rare earth chloride low hydrate reacting with the mixed ligands of ammonium pyrrolidinedithiocarbamate (APDC) and 1,10-phenanthroline·H2O (o-phen·H2O) in the ordinary laboratory atmosphere without any cautions against moisture or air. IR spectra of the complexes showed that the RE3+ coordinated with six sulfur atoms of three PDC- and two nitrogen atoms of o-phen·H2O. It was assumed that the coordination number of RE3+was eight. The constant-volume combustion energies of the complexes, △cU, were determined as (-16788.46±7.74), (- 15434.53± 8.28), (- 15287.807.31), (- 15200.50±7.22) and (- 15254.34±6.61) kJ·mol-1, respectively, by a precise rotating-bomb calorimeter at 298.15 K. Its standard molar enthalpies of combustion, △cH m,and standard molar enthalpies of formation, △fH m, were calculated as (-16803.95 ±7.74), (-15450.02±8.28),(-15303.29±9.28), (-15215.99±7.22), (-15269.83±6.61) kJ·mol-1 and (-1115.42±8.94), (-2477.80±9.15), (-2619.95 ±10.44), (-2670.17 ± 8.22), ( -2650.06± 8.49) kJ·mol-1, respectively.

  1. Design of New Competitive Dengue Ns2b/Ns3 Protease Inhibitors—A Computational Approach

    Directory of Open Access Journals (Sweden)

    Noorsaadah Abd. Rahman

    2011-02-01

    Full Text Available Dengue is a serious disease which has become a global health burden in the last decade. Currently, there are no approved vaccines or antiviral therapies to combat the disease. The increasing spread and severity of the dengue virus infection emphasizes the importance of drug discovery strategies that could efficiently and cost-effectively identify antiviral drug leads for development into potent drugs. To this effect, several computational approaches were applied in this work. Initially molecular docking studies of reference ligands to the DEN2 NS2B/NS3 serine protease were carried out. These reference ligands consist of reported competitive inhibitors extracted from Boesenbergia rotunda (i.e., 4-hydroxypanduratin A and panduratin A and three other synthesized panduratin A derivative compounds (i.e., 246DA, 2446DA and 20H46DA. The design of new lead inhibitors was carried out in two stages. In the first stage, the enzyme complexed to the reference ligands was minimized and their complexation energies (i.e., sum of interaction energy and binding energy were computed. New compounds as potential dengue inhibitors were then designed by putting various substituents successively on the benzyl ring A of the reference molecule. These substituted benzyl compounds were then computed for their enzyme-ligand complexation energies. New enzyme-ligand complexes, exhibiting the lowest complexation energies and closest to the computed energy for the reference compounds, were then chosen for the next stage manipulation and design, which involved substituting positions 4 and 5 of the benzyl ring A (positions 3 and 4 for 2446DA with various substituents.

  2. 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.

  3. Image reconstruction using Monte Carlo simulation and artificial neural networks

    International Nuclear Information System (INIS)

    Emert, F.; Missimner, J.; Blass, W.; Rodriguez, A.

    1997-01-01

    PET data sets are subject to two types of distortions during acquisition: the imperfect response of the scanner and attenuation and scattering in the active distribution. In addition, the reconstruction of voxel images from the line projections composing a data set can introduce artifacts. Monte Carlo simulation provides a means for modeling the distortions and artificial neural networks a method for correcting for them as well as minimizing artifacts. (author) figs., tab., refs

  4. 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.

  5. [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.

  6. Simulation of lung motions using an artificial neural network

    International Nuclear Information System (INIS)

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

    2011-01-01

    Purpose. 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. Patients and methods. 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. Results. - The first results are promising: an average accuracy of 1 mm is obtained for a spatial resolution of 1 x 1 x 2.5 mm 3 . Conclusion. 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. (authors)

  7. 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.

  8. Healthcare Supported by Data Mule Networks in Remote Communities of the Amazon Region

    OpenAIRE

    Coutinho, Mauro Margalho; Efrat, Alon; Johnson, Thienne; Richa, Andrea; Liu, Mengxue

    2014-01-01

    This paper investigates the feasibility of using boats as data mule nodes, carrying medical ultrasound videos from remote and isolated communities in the Amazon region in Brazil, to the main city of that area. The videos will be used by physicians to perform remote analysis and follow-up routine of prenatal examinations of pregnant women. Two open source simulators (the ONE and NS-2) were used to evaluate the results obtained utilizing a CoDPON (continuous displacement plan oriented network)....

  9. Infection of Common Marmosets with GB Virus B Chimeric Virus Encoding the Major Nonstructural Proteins NS2 to NS4A of Hepatitis C Virus.

    Science.gov (United States)

    Zhu, Shaomei; Li, Tingting; Liu, Bochao; Xu, Yuxia; Sun, Yachun; Wang, Yilin; Wang, Yuanzhan; Shuai, Lifang; Chen, Zixuan; Allain, Jean-Pierre; Li, Chengyao

    2016-09-15

    A lack of immunocompetent-small-primate models has been an obstacle for developing hepatitis C virus (HCV) vaccines and affordable antiviral drugs. In this study, HCV/GB virus B (GBV-B) chimeric virus carrying the major nonstructural proteins NS2 to NS4A (HCV NS2 to -4A chimera) was produced and used to infect common marmosets, since HCV NS2 to NS4A proteins are critical proteases and major antigens. Seven marmosets were inoculated intrahepatically with HCV NS2 to -4A chimera RNA for primary infection or intravenously injected with chimera-containing serum for passage infection. Three animals used as controls were injected with phosphate-buffered saline (PBS) or GBV-B, respectively. Six of seven HCV NS2 to -4A chimera-infected marmosets exhibited consistent viremia and one showed transient viremia during the course of follow-up detection. All six infected animals with persistent circulating viremia presented characteristics typical of viral hepatitis, including viral RNA and proteins in hepatocytes and histopathological changes in liver tissue. Viremia was consistently detected for 5 to 54 weeks of follow-up. FK506 immunosuppression facilitated the establishment of persistent chimera infection in marmosets. An animal with chimera infection spontaneously cleared the virus in blood 7 weeks following the first inoculation, but viral-RNA persistence, low-level viral protein, and mild necroinflammation remained in liver tissue. The specific antibody and T-cell response to HCV NS3 in this viremia-resolved marmoset was boosted by rechallenging, but no viremia was detected during 57 weeks of follow-up. The chimera-infected marmosets described can be used as a suitable small-primate animal model for studying novel antiviral drugs and T-cell-based vaccines against HCV infection. HCV infection causes approximately 70% of chronic hepatitis and is frequently associated with primary liver cancer globally. Chimpanzees have been used as a reliable primate model for HCV infection

  10. 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

  11. Comparative Analysis of Disruption Tolerant Network Routing Simulations in the One and NS-3

    Science.gov (United States)

    2017-12-01

    The added levels of simulation increase the processing required by a simulation . ns-3’s simulation of other layers of the network stack permits...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS COMPARATIVE ANALYSIS OF DISRUPTION TOLERANT NETWORK ROUTING SIMULATIONS IN THE ONE AND NS-3...Thesis 03-23-2016 to 12-15-2017 4. TITLE AND SUBTITLE COMPARATIVE ANALYSIS OF DISRUPTION TOLERANT NETWORK ROUTING SIMULATIONS IN THE ONE AND NS-3 5

  12. 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.)

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

    International Nuclear Information System (INIS)

    Kositbowornchai, S.; Siriteptawee, S.; Plermkamon, S.; Bureerat, S.; Chetchotsak, D.

    2006-01-01

    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.)

  14. 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.

  15. Lyso-myristoyl phosphatidylcholine micelles sustain the activity of Dengue non-structural (NS) protein 3 protease domain fused with the full-length NS2B.

    Science.gov (United States)

    Huang, Qiwei; Li, Qingxin; Joy, Joma; Chen, Angela Shuyi; Ruiz-Carrillo, David; Hill, Jeffrey; Lescar, Julien; Kang, Congbao

    2013-12-01

    Dengue virus (DENV), a member of the flavivirus genus, affects 50-100 million people in tropical and sub-tropical regions. The DENV protease domain is located at the N-terminus of the NS3 protease and requires for its enzymatic activity a hydrophilic segment of the NS2B that acts as a cofactor. The protease is an important antiviral drug target because it plays a crucial role in virus replication by cleaving the genome-coded polypeptide into mature functional proteins. Currently, there are no drugs to inhibit DENV protease activity. Most structural and functional studies have been conducted using protein constructs containing the NS3 protease domain connected to a soluble segment of the NS2B membrane protein via a nine-residue linker. For in vitro structural and functional studies, it would be useful to produce a natural form of the DENV protease containing the NS3 protease domain and the full-length NS2B protein. Herein, we describe the expression and purification of a natural form of DENV protease (NS2BFL-NS3pro) containing the full-length NS2B protein and the protease domain of NS3 (NS3pro). The protease was expressed and purified in detergent micelles necessary for its folding. Our results show that this purified protein was active in detergent micelles such as lyso-myristoyl phosphatidylcholine (LMPC). These findings should facilitate further structural and functional studies of the protease and will facilitate drug discovery targeting DENV. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. 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.

  17. Real-Time-Simulation of IEEE-5-Bus Network on OPAL-RT-OP4510 Simulator

    Science.gov (United States)

    Atul Bhandakkar, Anjali; Mathew, Lini, Dr.

    2018-03-01

    The Real-Time Simulator tools have high computing technologies, improved performance. They are widely used for design and improvement of electrical systems. The advancement of the software tools like MATLAB/SIMULINK with its Real-Time Workshop (RTW) and Real-Time Windows Target (RTWT), real-time simulators are used extensively in many engineering fields, such as industry, education, and research institutions. OPAL-RT-OP4510 is a Real-Time Simulator which is used in both industry and academia. In this paper, the real-time simulation of IEEE-5-Bus network is carried out by means of OPAL-RT-OP4510 with CRO and other hardware. The performance of the network is observed with the introduction of fault at various locations. The waveforms of voltage, current, active and reactive power are observed in the MATLAB simulation environment and on the CRO. Also, Load Flow Analysis (LFA) of IEEE-5-Bus network is computed using MATLAB/Simulink power-gui load flow tool.

  18. 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.

  19. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichiro; Dershowitz, William

    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 Aespoe 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). MIU Underground Rock Laboratory support during H-14 involved discrete fracture network (DFN) modelling in support of the Multiple Modelling Project (MMP) and the Long Term Pumping Test (LPT). Golder developed updated DFN models for the MIU site, reflecting updated analyses of fracture data. Golder also developed scripts to support JNC simulations of flow and transport pathways within the MMP. Golder supported JNC participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-14. Task 6A and 6B compared safety assessment (PA) and experimental time scale simulations along a pipe transport pathway. Task 6B2 extended Task 6B simulations from 1-D to 2-D. For Task 6B2, Golder carried out single fracture transport simulations on a wide variety of generic heterogeneous 2D fractures using both experimental and safety assessment boundary conditions. The heterogeneous 2D fractures were implemented according to a variety of in plane heterogeneity patterns. Multiple immobile zones were considered including stagnant zones, infillings, altered wall rock, and intact rock. During H-14, JNC carried out extensive studies of the distributed rock zone (DRZ) surrounding repository tunnels and drifts. Golder supported this activity be evaluating the calculation time necessary for simulating a reference heterogeneous DRZ cell network for a range of computational strategies. To support the development of JNC's total system performance assessment (TSPA) strategy, Golder carried out a review of the US DOE Yucca Mountain Project TSPA. This

  20. Coarse-grained simulation of a real-time process control network under peak load

    International Nuclear Information System (INIS)

    George, A.D.; Clapp, N.E. Jr.

    1992-01-01

    This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

  1. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichiro; Dershowitz, William

    2004-01-01

    During Heisei-15, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU Underground Rock Laboratory support during H-15 involved development of new discrete fracture network (DFN) models for the MIU Shoba-sama Site, in the region of shaft development. Golder developed three DFN models for the site using discrete fracture network, equivalent porous medium (EPM), and nested DFN/EPM approaches. Each of these models were compared based upon criteria established for the multiple modeling project (MMP). Golder supported JNC participation in Task 6AB, 6D and 6E of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-15. For Task 6AB, Golder implemented an updated microstructural model in GoldSim, and used this updated model to simulate the propagation of uncertainty from experimental to safety assessment time scales, for 5 m scale transport path lengths. Task 6D and 6E compared safety assessment (PA) and experimental time scale simulations in a 200 m scale discrete fracture network. For Task 6D, Golder implemented a DFN model using FracMan/PA Works, and determined the sensitivity of solute transport to a range of material property and geometric assumptions. For Task 6E, Golder carried out demonstration FracMan/PA Works transport calculations at a 1 million year time scale, to ensure that task specifications are realistic. The majority of work for Task 6E will be carried out during H-16. During H-15, Golder supported JNC's Total System Performance Assessment (TSPO) strategy by developing technologies for the analysis of precipitant concentration. These approaches were based on the GoldSim precipitant data management features, and were

  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. Neural Networks Simulation of the Transport of Contaminants in Groundwater

    Directory of Open Access Journals (Sweden)

    Enrico Zio

    2009-12-01

    Full Text Available The performance assessment of an engineered solution for the disposal of radioactive wastes is based on mathematical models of the disposal system response to predefined accidental scenarios, within a probabilistic approach to account for the involved uncertainties. As the most significant potential pathway for the return of radionuclides to the biosphere is groundwater flow, intensive computational efforts are devoted to simulating the behaviour of the groundwater system surrounding the waste deposit, for different values of its hydrogeological parameters and for different evolution scenarios. In this paper, multilayered neural networks are trained to simulate the transport of contaminants in monodimensional and bidimensional aquifers. The results obtained in two case studies indicate that the approximation errors are within the uncertainties which characterize the input data.

  4. Accurate lithography simulation model based on convolutional neural networks

    Science.gov (United States)

    Watanabe, Yuki; Kimura, Taiki; Matsunawa, Tetsuaki; Nojima, Shigeki

    2017-07-01

    Lithography simulation is an essential technique for today's semiconductor manufacturing process. In order to calculate an entire chip in realistic time, compact resist model is commonly used. The model is established for faster calculation. To have accurate compact resist model, it is necessary to fix a complicated non-linear model function. However, it is difficult to decide an appropriate function manually because there are many options. This paper proposes a new compact resist model using CNN (Convolutional Neural Networks) which is one of deep learning techniques. CNN model makes it possible to determine an appropriate model function and achieve accurate simulation. Experimental results show CNN model can reduce CD prediction errors by 70% compared with the conventional model.

  5. 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 (< 5%) for a wide range of inlet-to-initial pressure ratios. A Fast Fourier Transform is preformed on the pressure oscillations to predict the various modal frequencies of the pressure wave. The shutdown problem, i.e. valve closing problem, the 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.

  6. Modeling and simulation of different and representative engineering problems using Network Simulation Method.

    Science.gov (United States)

    Sánchez-Pérez, J F; Marín, F; Morales, J L; Cánovas, M; Alhama, F

    2018-01-01

    Mathematical models simulating different and representative engineering problem, atomic dry friction, the moving front problems and elastic and solid mechanics are presented in the form of a set of non-linear, coupled or not coupled differential equations. For different parameters values that influence the solution, the problem is numerically solved by the network method, which provides all the variables of the problems. Although the model is extremely sensitive to the above parameters, no assumptions are considered as regards the linearization of the variables. The design of the models, which are run on standard electrical circuit simulation software, is explained in detail. The network model results are compared with common numerical methods or experimental data, published in the scientific literature, to show the reliability of the model.

  7. Modeling and simulation of different and representative engineering problems using Network Simulation Method

    Science.gov (United States)

    2018-01-01

    Mathematical models simulating different and representative engineering problem, atomic dry friction, the moving front problems and elastic and solid mechanics are presented in the form of a set of non-linear, coupled or not coupled differential equations. For different parameters values that influence the solution, the problem is numerically solved by the network method, which provides all the variables of the problems. Although the model is extremely sensitive to the above parameters, no assumptions are considered as regards the linearization of the variables. The design of the models, which are run on standard electrical circuit simulation software, is explained in detail. The network model results are compared with common numerical methods or experimental data, published in the scientific literature, to show the reliability of the model. PMID:29518121

  8. 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.

  9. STEADY-STATE modeling and simulation of pipeline networks for compressible fluids

    Directory of Open Access Journals (Sweden)

    A.L.H. Costa

    1998-12-01

    Full Text Available This paper presents a model and an algorithm for the simulation of pipeline networks with compressible fluids. The model can predict pressures, flow rates, temperatures and gas compositions at any point of the network. Any network configuration can be simulated; the existence of cycles is not an obstacle. Numerical results from simulated data on a proposed network are shown for illustration. The potential of the simulator is explored by the analysis of a pressure relief network, using a stochastic procedure for the evaluation of system performance.

  10. 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.

  11. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    Directory of Open Access Journals (Sweden)

    Shah Imran

    2011-07-01

    Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

  12. Identification of specific regions in hepatitis C virus core, NS2 and NS5A that genetically interact with p7 and co-ordinate infectious virus production.

    Science.gov (United States)

    Gouklani, H; Beyer, C; Drummer, H; Gowans, E J; Netter, H J; Haqshenas, G

    2013-04-01

    The p7 protein of hepatitis C virus (HCV) is a small, integral membrane protein that plays a critical role in virus replication. Recently, we reported two intergenotypic JFH1 chimeric viruses encoding the partial or full-length p7 protein of the HCV-A strain of genotype 1b (GT1b; Virology; 2007; 360:134). In this study, we determined the consensus sequences of the entire polyprotein coding regions of the wild-type JFH1 and the revertant chimeric viruses and identified predominant amino acid substitutions in core (K74M), NS2 (T23N, H99P) and NS5A (D251G). Forward genetic analysis demonstrated that all single mutations restored the infectivity of the defective chimeric genomes suggesting that the infectious virus production involves the association of p7 with specific regions in core, NS2 and NS5A. In addition, it was demonstrated that the NS2 T23N facilitated the generation of infectious intergenotypic chimeric virus encoding p7 from GT6 of HCV. © 2012 Blackwell Publishing Ltd.

  13. New approach for simulating groundwater flow in discrete fracture network

    Science.gov (United States)

    Fang, H.; Zhu, J.

    2017-12-01

    In this study, we develop a new approach to calculate groundwater flowrate and hydraulic head distribution in two-dimensional discrete fracture network (DFN) where both laminar and turbulent flows co-exist in individual fractures. The cubic law is used to calculate hydraulic head distribution and flow behaviors in fractures where flow is laminar, while the Forchheimer's law is used to quantify turbulent flow behaviors. Reynolds number is used to distinguish flow characteristics in individual fractures. The combination of linear and non-linear equations is solved iteratively to determine flowrates in all fractures and hydraulic heads at all intersections. We examine potential errors in both flowrate and hydraulic head from the approach of uniform flow assumption. Applying the cubic law in all fractures regardless of actual flow conditions overestimates the flowrate when turbulent flow may exist while applying the Forchheimer's law indiscriminately underestimate the flowrate when laminar flows exist in the network. The contrast of apertures of large and small fractures in the DFN has significant impact on the potential errors of using only the cubic law or the Forchheimer's law. Both the cubic law and Forchheimer's law simulate similar hydraulic head distributions as the main difference between these two approaches lies in predicting different flowrates. Fracture irregularity does not significantly affect the potential errors from using only the cubic law or the Forchheimer's law if network configuration remains similar. Relative density of fractures does not significantly affect the relative performance of the cubic law and Forchheimer's law.

  14. 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

  15. A conformational switch high-throughput screening assay and allosteric inhibition of the flavivirus NS2B-NS3 protease.

    Directory of Open Access Journals (Sweden)

    Matthew Brecher

    2017-05-01

    Full Text Available The flavivirus genome encodes a single polyprotein precursor requiring multiple cleavages by host and viral proteases in order to produce the individual proteins that constitute an infectious virion. Previous studies have revealed that the NS2B cofactor of the viral NS2B-NS3 heterocomplex protease displays a conformational dynamic between active and inactive states. Here, we developed a conformational switch assay based on split luciferase complementation (SLC to monitor the conformational change of NS2B and to characterize candidate allosteric inhibitors. Binding of an active-site inhibitor to the protease resulted in a conformational change of NS2B and led to significant SLC enhancement. Mutagenesis of key residues at an allosteric site abolished this induced conformational change and SLC enhancement. We also performed a virtual screen of NCI library compounds to identify allosteric inhibitors, followed by in vitro biochemical screening of the resultant candidates. Only three of these compounds, NSC135618, 260594, and 146771, significantly inhibited the protease of Dengue virus 2 (DENV2 in vitro, with IC50 values of 1.8 μM, 11.4 μM, and 4.8 μM, respectively. Among the three compounds, only NSC135618 significantly suppressed the SLC enhancement triggered by binding of active-site inhibitor in a dose-dependent manner, indicating that it inhibits the conformational change of NS2B. Results from virus titer reduction assays revealed that NSC135618 is a broad spectrum flavivirus protease inhibitor, and can significantly reduce titers of DENV2, Zika virus (ZIKV, West Nile virus (WNV, and Yellow fever virus (YFV on A549 cells in vivo, with EC50 values in low micromolar range. In contrast, the cytotoxicity of NSC135618 is only moderate with CC50 of 48.8 μM on A549 cells. Moreover, NSC135618 inhibited ZIKV in human placental and neural progenitor cells relevant to ZIKV pathogenesis. Results from binding, kinetics, Western blot, mass spectrometry and

  16. 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 ...

  17. 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 ...

  18. Imaging Simulations for the Korean VLBI Network (KVN

    Directory of Open Access Journals (Sweden)

    Tae-Hyun Jung

    2005-03-01

    Full Text Available The Korean VLBI Network (KVN will open a new field of research in astronomy, geodesy and earth science using the newest three 21m radio telescopes. This will expand our ability to look at the Universe in the millimeter regime. Imaging capability of radio interferometry is highly dependent upon the antenna configuration, source size, declination and the shape of target. In this paper, imaging simulations are carried out with the KVN system configuration. Five test images were used which were a point source, multi-point sources, a uniform sphere with two different sizes compared to the synthesis beam of the KVN and a Very Large Array (VLA image of Cygnus A. The declination for the full time simulation was set as +60 degrees and the observation time range was --6 to +6 hours around transit. Simulations have been done at 22GHz, one of the KVN observation frequency. All these simulations and data reductions have been run with the Astronomical Image Processing System (AIPS software package. As the KVN array has a resolution of about 6 mas (milli arcsecond at 22GHz, in case of model source being approximately the beam size or smaller, the ratio of peak intensity over RMS shows about 10000:1 and 5000:1. The other case in which model source is larger than the beam size, this ratio shows very low range of about 115:1 and 34:1. This is due to the lack of short baselines and the small number of antenna. We compare the coordinates of the model images with those of the cleaned images. The result shows mostly perfect correspondence except in the case of the 12mas uniform sphere. Therefore, the main astronomical targets for the KVN will be the compact sources and the KVN will have an excellent performance in the astrometry for these sources.

  19. Computer simulation of the Blumlein pulse forming network

    International Nuclear Information System (INIS)

    Edwards, C.B.

    1981-03-01

    A computer simulation of the Blumlein pulse-forming network is described. The model is able to treat the case of time varying loads, non-zero conductor resistance, and switch closure effects as exhibited by real systems employing non-ohmic loads such as field-emission vacuum diodes in which the impedance is strongly time and voltage dependent. The application of the code to various experimental arrangements is discussed, with particular reference to the prediction of the behaviour of the output circuit of 'ELF', the electron beam generator in operation at the Rutherford Laboratory. The output from the code is compared directly with experimentally obtained voltage waveforms applied to the 'ELF' diode. (author)

  20. Secure Data Aggregation in Wireless Sensor Network-Fujisaki Okamoto(FO) Authentication Scheme against Sybil Attack.

    Science.gov (United States)

    Nirmal Raja, K; Maraline Beno, M

    2017-07-01

    In the wireless sensor network(WSN) security is a major issue. There are several network security schemes proposed in research. In the network, malicious nodes obstruct the performance of the network. The network can be vulnerable by Sybil attack. When a node illicitly assertions multiple identities or claims fake IDs, the WSN grieves from an attack named Sybil attack. This attack threatens wireless sensor network in data aggregation, synchronizing system, routing, fair resource allocation and misbehavior detection. Henceforth, the research is carried out to prevent the Sybil attack and increase the performance of the network. This paper presents the novel security mechanism and Fujisaki Okamoto algorithm and also application of the work. The Fujisaki-Okamoto (FO) algorithm is ID based cryptographic scheme and gives strong authentication against Sybil attack. By using Network simulator2 (NS2) the scheme is simulated. In this proposed scheme broadcasting key, time taken for different key sizes, energy consumption, Packet delivery ratio, Throughput were analyzed.

  1. 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.

  2. 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

  3. OpenFlow Switching Performance using Network Simulator - 3

    OpenAIRE

    Sriram Prashanth, Naguru

    2016-01-01

    Context. In the present network inventive world, there is a quick expansion of switches and protocols, which are used to cope up with the increase in customer requirement in the networking. With increasing demand for higher bandwidths and lower latency and to meet these requirements new network paths are introduced. To reduce network load in present switching network, development of new innovative switching is required. These required results can be achieved by Software Define Network or Trad...

  4. 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.

  5. 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. PMID:23781198

  6. Cleavage preference distinguishes the two-component NS2B-NS3 serine proteinases of Dengue and West Nile viruses.

    Science.gov (United States)

    Shiryaev, Sergey A; Kozlov, Igor A; Ratnikov, Boris I; Smith, Jeffrey W; Lebl, Michal; Strongin, Alex Y

    2007-02-01

    Regulated proteolysis of the polyprotein precursor by the NS2B-NS3 protease is required for the propagation of infectious virions. Unless the structural and functional parameters of NS2B-NS3 are precisely determined, an understanding of its functional role and the design of flaviviral inhibitors will be exceedingly difficult. Our objectives were to define the substrate recognition pattern of the NS2B-NS3 protease of West Nile and Dengue virises (WNV and DV respectively). To accomplish our goals, we used an efficient, 96-well plate format, method for the synthesis of 9-mer peptide substrates with the general P4-P3-P2-P1-P1'-P2'-P3'-P4'-Gly structure. The N-terminus and the constant C-terminal Gly of the peptides were tagged with a fluorescent tag and with a biotin tag respectively. The synthesis was followed by the proteolytic cleavage of the synthesized, tagged peptides. Because of the strict requirement for the presence of basic amino acid residues at the P1 and the P2 substrate positions, the analysis of approx. 300 peptide sequences was sufficient for an adequate representation of the cleavage preferences of the WNV and DV proteinases. Our results disclosed the strict substrate specificity of the WNV protease for which the (K/R)(K/R)R/GG amino acid motifs was optimal. The DV protease was less selective and it tolerated well the presence of a number of amino acid residue types at either the P1' or the P2' site, as long as the other position was occupied by a glycine residue. We believe that our data represent a valuable biochemical resource and a solid foundation to support the design of selective substrates and synthetic inhibitors of flaviviral proteinases.

  7. A Single Amino Acid Substitution in the NS2A Protein of Japanese Encephalitis Virus Affects Virus Propagation In Vitro but Not In Vivo.

    Science.gov (United States)

    Takamatsu, Yuki; Morita, Kouichi; Hayasaka, Daisuke

    2015-06-01

    We identified a unique amino acid of NS2A113, phenylalanine, that affects the efficient propagation of two Japanese encephalitis virus strains, JaTH160 and JaOArS982, in neuroblastoma Neuro-2a cells but not in cell lines of extraneural origin. This amino acid did not affect viral loads in the brain or survival curves in mice. These findings suggest that virus propagation in vitro may not reflect the level of virus neuroinvasiveness in vivo. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  8. A robust fractional-order PID controller design based on active queue management for TCP network

    Science.gov (United States)

    Hamidian, Hamideh; Beheshti, Mohammad T. H.

    2018-01-01

    In this paper, a robust fractional-order controller is designed to control the congestion in transmission control protocol (TCP) networks with time-varying parameters. Fractional controllers can increase the stability and robustness. Regardless of advantages of fractional controllers, they are still not common in congestion control in TCP networks. The network parameters are time-varying, so the robust stability is important in congestion controller design. Therefore, we focused on the robust controller design. The fractional PID controller is developed based on active queue management (AQM). D-partition technique is used. The most important property of designed controller is the robustness to the time-varying parameters of the TCP network. The vertex quasi-polynomials of the closed-loop characteristic equation are obtained, and the stability boundaries are calculated for each vertex quasi-polynomial. The intersection of all stability regions is insensitive to network parameter variations, and results in robust stability of TCP/AQM system. NS-2 simulations show that the proposed algorithm provides a stable queue length. Moreover, simulations show smaller oscillations of the queue length and less packet drop probability for FPID compared to PI and PID controllers. We can conclude from NS-2 simulations that the average packet loss probability variations are negligible when the network parameters change.

  9. Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations.

    Science.gov (United States)

    Gerlach, Kathy D; Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L

    2014-12-01

    We spend much of our daily lives imagining how we can reach future goals and what will happen when we attain them. Despite the prevalence of such goal-directed simulations, neuroimaging studies on planning have mainly focused on executive processes in the frontal lobe. This experiment examined the neural basis of process simulations, during which participants imagined themselves going through steps toward attaining a goal, and outcome simulations, during which participants imagined events they associated with achieving a goal. In the scanner, participants engaged in these simulation tasks and an odd/even control task. We hypothesized that process simulations would recruit default and frontoparietal control network regions, and that outcome simulations, which allow us to anticipate the affective consequences of achieving goals, would recruit default and reward-processing regions. Our analysis of brain activity that covaried with process and outcome simulations confirmed these hypotheses. A functional connectivity analysis with posterior cingulate, dorsolateral prefrontal cortex and anterior inferior parietal lobule seeds showed that their activity was correlated during process simulations and associated with a distributed network of default and frontoparietal control network regions. During outcome simulations, medial prefrontal cortex and amygdala seeds covaried together and formed a functional network with default and reward-processing regions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  10. The computer simulation of the resonant network for the B-factory model power supply

    International Nuclear Information System (INIS)

    Zhou, W.; Endo, K.

    1993-07-01

    A high repetition model power supply and the resonant magnet network are simulated with the computer in order to check and improve the design of the power supply for the B-factory booster. We put our key point on a transient behavior of the power supply and the resonant magnet network. The results of the simulation are given. (author)

  11. 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

  12. Modelisation et simulation d'un PON (Passive Optical Network) base ...

    African Journals Online (AJOL)

    English Title: Modeling and simulation of a PON (Passive Optical Network) Based on hybrid technology WDM/TDM. English Abstract. This development is part of dynamism of design for a model combining WDM and TDM multiplexing in the optical network of PON (Passive Optical Network) type, in order to satisfy the high bit ...

  13. Battery Performance Modelling ad Simulation: a Neural Network Based Approach

    Science.gov (United States)

    Ottavianelli, Giuseppe; Donati, Alessandro

    2002-01-01

    This project has developed on the background of ongoing researches within the Control Technology Unit (TOS-OSC) of the Special Projects Division at the European Space Operations Centre (ESOC) of the European Space Agency. The purpose of this research is to develop and validate an Artificial Neural Network tool (ANN) able to model, simulate and predict the Cluster II battery system's performance degradation. (Cluster II mission is made of four spacecraft flying in tetrahedral formation and aimed to observe and study the interaction between sun and earth by passing in and out of our planet's magnetic field). This prototype tool, named BAPER and developed with a commercial neural network toolbox, could be used to support short and medium term mission planning in order to improve and maximise the batteries lifetime, determining which are the future best charge/discharge cycles for the batteries given their present states, in view of a Cluster II mission extension. This study focuses on the five Silver-Cadmium batteries onboard of Tango, the fourth Cluster II satellite, but time restrains have allowed so far to perform an assessment only on the first battery. In their most basic form, ANNs are hyper-dimensional curve fits for non-linear data. With their remarkable ability to derive meaning from complicated or imprecise history data, ANN can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. ANNs learn by example, and this is why they can be described as an inductive, or data-based models for the simulation of input/target mappings. A trained ANN can be thought of as an "expert" in the category of information it has been given to analyse, and this expert can then be used, as in this project, to provide projections given new situations of interest and answer "what if" questions. The most appropriate algorithm, in terms of training speed and memory storage requirements, is clearly the Levenberg

  14. 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.

  15. 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.

  16. Environmental regulation in a network of simulated microbial ecosystems.

    Science.gov (United States)

    Williams, Hywel T P; Lenton, Timothy M

    2008-07-29

    The Earth possesses a number of regulatory feedback mechanisms involving life. In the absence of a population of competing biospheres, it has proved hard to find a robust evolutionary mechanism that would generate environmental regulation. It has been suggested that regulation must require altruistic environmental alterations by organisms and, therefore, would be evolutionarily unstable. This need not be the case if organisms alter the environment as a selectively neutral by-product of their metabolism, as in the majority of biogeochemical reactions, but a question then arises: Why should the combined by-product effects of the biota have a stabilizing, rather than destabilizing, influence on the environment? Under certain conditions, selection acting above the level of the individual can be an effective adaptive force. Here we present an evolutionary simulation model in which environmental regulation involving higher-level selection robustly emerges in a network of interconnected microbial ecosystems. Spatial structure creates conditions for a limited form of higher-level selection to act on the collective environment-altering properties of local communities. Local communities that improve their environmental conditions achieve larger populations and are better colonizers of available space, whereas local communities that degrade their environment shrink and become susceptible to invasion. The spread of environment-improving communities alters the global environment toward the optimal conditions for growth and tends to regulate against external perturbations. This work suggests a mechanism for environmental regulation that is consistent with evolutionary theory.

  17. BWR-plant simulator and its neural network companion with programming under mat lab environment

    International Nuclear Information System (INIS)

    Ghenniwa, Fatma Suleiman

    2008-01-01

    Stand alone nuclear power plant simulators, as well as building blocks based nuclear power simulator are available from different companies throughout the world. In this work, a review of such simulators has been explored for both types. Also a survey of the possible authoring tools for such simulators development has been performed. It is decided, in this research, to develop prototype simulator based on components building blocks. Further more, the authoring tool (Mat lab software) has been selected for programming. It has all the basic tools required for the simulator development similar to that developed by specialized companies for simulator like MMS, APROS and others. Components simulations, as well as integrated components for power plant simulation have been demonstrated. Preliminary neural network reactor model as part of a prepared neural network modules library has been used to demonstrate module order shuffling during simulation. The developed components library can be refined and extended for further development. (author)

  18. A Hybrid Communications Network Simulation-Independent Toolkit

    National Research Council Canada - National Science Library

    Dines, David M

    2008-01-01

    .... Evolving a grand design of the enabling network will require a flexible evaluation platform to try and select the right combination of network strategies and protocols in the realms of topology control and routing...

  19. 'BioNessie(G) - a grid enabled biochemical networks simulation environment

    OpenAIRE

    Liu, X; Jiang, J; Ajayi, O; Gu, X; Gilbert, D; Sinnott, R

    2008-01-01

    The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scal...

  20. 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....

  1. 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,

  2. 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.

  3. Limits to high-speed simulations of spiking neural networks using general-purpose computers.

    Science.gov (United States)

    Zenke, Friedemann; Gerstner, Wulfram

    2014-01-01

    To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

  4. 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...

  5. Active queue management controller design for TCP communication networks: Variable structure control approach

    International Nuclear Information System (INIS)

    Chen, C.-K.; Liao, T.-L.; Yan, J.-J.

    2009-01-01

    On the basis of variable structure control (VSC), an active queue management (AQM) controller is presented for a class of TCP communication networks. In the TCP/IP networks, the packet drop probability is limited between 0 and 1. Therefore, we modeled TCP/AQM as a rate-based non-linear system with a saturated input. The objective of the VSC-based AQM controller is to achieve the desired queue size and to guarantee the asymptotic stability of the closed-loop TCP non-linear system with saturated input. The performance and effectiveness of the proposed control law are then validated for different network scenarios through numerical simulations in both MATLAB and Network Simulator-2 (NS-2). Both sets of simulation results have confirmed that the proposed scheme outperforms other AQM schemes.

  6. Active queue management controller design for TCP communication networks: Variable structure control approach

    Energy Technology Data Exchange (ETDEWEB)

    Chen, C.-K. [Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan (China); Liao, T.-L. [Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan (China)], E-mail: tlliao@mail.ncku.edu; Yan, J.-J. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)

    2009-04-15

    On the basis of variable structure control (VSC), an active queue management (AQM) controller is presented for a class of TCP communication networks. In the TCP/IP networks, the packet drop probability is limited between 0 and 1. Therefore, we modeled TCP/AQM as a rate-based non-linear system with a saturated input. The objective of the VSC-based AQM controller is to achieve the desired queue size and to guarantee the asymptotic stability of the closed-loop TCP non-linear system with saturated input. The performance and effectiveness of the proposed control law are then validated for different network scenarios through numerical simulations in both MATLAB and Network Simulator-2 (NS-2). Both sets of simulation results have confirmed that the proposed scheme outperforms other AQM schemes.

  7. NCC simulation model. Phase 2: Simulating the operations of the Network Control Center and NCC message manual

    Science.gov (United States)

    Benjamin, Norman M.; Gill, Tepper; Charles, Mary

    1994-01-01

    The network control center (NCC) provides scheduling, monitoring, and control of services to the NASA space network. The space network provides tracking and data acquisition services to many low-earth orbiting spacecraft. This report describes the second phase in the development of simulation models for the FCC. Phase one concentrated on the computer systems and interconnecting network.Phase two focuses on the implementation of the network message dialogs and the resources controlled by the NCC. Performance measures were developed along with selected indicators of the NCC's operational effectiveness.The NCC performance indicators were defined in terms of the following: (1) transfer rate, (2) network delay, (3) channel establishment time, (4) line turn around time, (5) availability, (6) reliability, (7) accuracy, (8) maintainability, and (9) security. An NCC internal and external message manual is appended to this report.

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

    Directory of Open Access Journals (Sweden)

    Jan Hahne

    2017-05-01

    Full Text Available 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.

  9. 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.

  10. On securing wireless sensor network--novel authentication scheme against DOS attacks.

    Science.gov (United States)

    Raja, K Nirmal; Beno, M Marsaline

    2014-10-01

    Wireless sensor networks are generally deployed for collecting data from various environments. Several applications specific sensor network cryptography algorithms have been proposed in research. However WSN's has many constrictions, including low computation capability, less memory, limited energy resources, vulnerability to physical capture, which enforce unique security challenges needs to make a lot of improvements. This paper presents a novel security mechanism and algorithm for wireless sensor network security and also an application of this algorithm. The proposed scheme is given to strong authentication against Denial of Service Attacks (DOS). The scheme is simulated using network simulator2 (NS2). Then this scheme is analyzed based on the network packet delivery ratio and found that throughput has improved.

  11. Cross-Layer Design Approach for Power Control in Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    A. Sarfaraz Ahmed

    2015-03-01

    Full Text Available In mobile ad hoc networks, communication among mobile nodes occurs through wireless medium The design of ad hoc network protocol, generally based on a traditional “layered approach”, has been found ineffective to deal with receiving signal strength (RSS-related problems, affecting the physical layer, the network layer and transport layer. This paper proposes a design approach, deviating from the traditional network design, toward enhancing the cross-layer interaction among different layers, namely physical, MAC and network. The Cross-Layer design approach for Power control (CLPC would help to enhance the transmission power by averaging the RSS values and to find an effective route between the source and the destination. This cross-layer design approach was tested by simulation (NS2 simulator and its performance over AODV was found to be better.

  12. 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.

  13. 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.

  14. Simulating large-scale spiking neuronal networks with NEST

    OpenAIRE

    Schücker, Jannis; Eppler, Jochen Martin

    2014-01-01

    The Neural Simulation Tool NEST [1, www.nest-simulator.org] is the simulator for spiking neural networkmodels of the HBP that focuses on the dynamics, size and structure of neural systems rather than on theexact morphology of individual neurons. Its simulation kernel is written in C++ and it runs on computinghardware ranging from simple laptops to clusters and supercomputers with thousands of processor cores.The development of NEST is coordinated by the NEST Initiative [www.nest-initiative.or...

  15. Prioritizing Signaling Information Transmission in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Jasmina Baraković

    2011-01-01

    Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.

  16. 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.

  17. 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.

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

    Science.gov (United States)

    Wang, Wei; Huang, Li; Liang, Xuedong

    2018-01-01

    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. PMID:29316614

  19. Computer Networks E-learning Based on Interactive Simulations and SCORM

    Directory of Open Access Journals (Sweden)

    Francisco Andrés Candelas

    2011-05-01

    Full Text Available This paper introduces a new set of compact interactive simulations developed for the constructive learning of computer networks concepts. These simulations, which compose a virtual laboratory implemented as portable Java applets, have been created by combining EJS (Easy Java Simulations with the KivaNS API. Furthermore, in this work, the skills and motivation level acquired by the students are evaluated and measured when these simulations are combined with Moodle and SCORM (Sharable Content Object Reference Model documents. This study has been developed to improve and stimulate the autonomous constructive learning in addition to provide timetable flexibility for a Computer Networks subject.

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Vestergaard, Christian L; Génois, Mathieu

    2015-10-01

    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.

  4. 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

    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...

  5. FERN - a Java framework for stochastic simulation and evaluation of reaction networks.

    Science.gov (United States)

    Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

    2008-08-29

    Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand-alone program and within new

  6. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Y W [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Zhang, L F [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Huang, J P [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China)

    2007-07-20

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property.

  7. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    International Nuclear Information System (INIS)

    Chen, Y W; Zhang, L F; Huang, J P

    2007-01-01

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property

  8. Development of neural network simulating power distribution of a BWR fuel bundle

    International Nuclear Information System (INIS)

    Tanabe, A.; Yamamoto, T.; Shinfuku, K.; Nakamae, T.

    1992-01-01

    A neural network model is developed to simulate the precise nuclear physics analysis program code for quick scoping survey calculations. The relation between enrichment and local power distribution of BWR fuel bundles was learned using two layers neural network (ENET). A new model is to introduce burnable neutron absorber (Gadolinia), added to several fuel rods to decrease initial reactivity of fresh bundle. The 2nd stages three layers neural network (GNET) is added on the 1st stage network ENET. GNET studies the local distribution difference caused by Gadolinia. Using this method, it becomes possible to survey of the gradients of sigmoid functions and back propagation constants with reasonable time. Using 99 learning patterns of zero burnup, good error convergence curve is obtained after many trials. This neural network model is able to simulate no learned cases fairly as well as the learned cases. Computer time of this neural network model is about 100 times faster than a precise analysis model. (author)

  9. 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.

  10. 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...... difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the experiment are compared with results obtained by a false killer whale (pseudorca crassidens)....

  11. Simulation of noise-assisted transport via optical cavity networks

    International Nuclear Information System (INIS)

    Caruso, Filippo; Plenio, Martin B.; Spagnolo, Nicolo; Vitelli, Chiara; Sciarrino, Fabio

    2011-01-01

    Recently, the presence of noise has been found to play a key role in assisting the transport of energy and information in complex quantum networks and even in biomolecular systems. Here we propose an experimentally realizable optical network scheme for the demonstration of the basic mechanisms underlying noise-assisted transport. The proposed system consists of a network of coupled quantum-optical cavities, injected with a single photon, whose transmission efficiency can be measured. Introducing dephasing in the photon path, this system exhibits a characteristic enhancement of the transport efficiency that can be observed with presently available technology.

  12. Smart Grid: Network simulator for smart grid test-bed

    International Nuclear Information System (INIS)

    Lai, L C; Ong, H S; Che, Y X; Do, N Q; Ong, X J

    2013-01-01

    Smart Grid become more popular, a smaller scale of smart grid test-bed is set up at UNITEN to investigate the performance and to find out future enhancement of smart grid in Malaysia. The fundamental requirement in this project is design a network with low delay, no packet drop and with high data rate. Different type of traffic has its own characteristic and is suitable for different type of network and requirement. However no one understands the natural of traffic in smart grid. This paper presents the comparison between different types of traffic to find out the most suitable traffic for the optimal network performance.

  13. Importance Sampling Simulation of Population Overflow in Two-node Tandem Networks

    NARCIS (Netherlands)

    Nicola, V.F.; Zaburnenko, T.S.; Baier, C; Chiola, G.; Smirni, E.

    2005-01-01

    In this paper we consider the application of importance sampling in simulations of Markovian tandem networks in order to estimate the probability of rare events, such as network population overflow. We propose a heuristic methodology to obtain a good approximation to the 'optimal' state-dependent

  14. Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.

    Directory of Open Access Journals (Sweden)

    Luis E C Rocha

    2011-03-01

    Full Text Available Sexual contact patterns, both in their temporal and network structure, can influence the spread of sexually transmitted infections (STI. Most previous literature has focused on effects of network topology; few studies have addressed the role of temporal structure. We simulate disease spread using SI and SIR models on an empirical temporal network of sexual contacts in high-end prostitution. We compare these results with several other approaches, including randomization of the data, classic mean-field approaches, and static network simulations. We observe that epidemic dynamics in this contact structure have well-defined, rather high epidemic thresholds. Temporal effects create a broad distribution of outbreak sizes, even if the per-contact transmission probability is taken to its hypothetical maximum of 100%. In general, we conclude that the temporal correlations of our network accelerate outbreaks, especially in the early phase of the epidemics, while the network topology (apart from the contact-rate distribution slows them down. We find that the temporal correlations of sexual contacts can significantly change simulated outbreaks in a large empirical sexual network. Thus, temporal structures are needed alongside network topology to fully understand the spread of STIs. On a side note, our simulations further suggest that the specific type of commercial sex we investigate is not a reservoir of major importance for HIV.

  15. Transport link scanner: simulating geographic transport network expansion through individual investments

    NARCIS (Netherlands)

    Koopmans, C.C.; Jacobs, C.G.W.

    2016-01-01

    This paper introduces a GIS-based model that simulates the geographic expansion of transport networks by several decision-makers with varying objectives. The model progressively adds extensions to a growing network by choosing the most attractive investments from a limited choice set. Attractiveness

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

    Directory of Open Access Journals (Sweden)

    Jan eHahne

    2015-09-01

    Full Text Available 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...

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

    International Nuclear Information System (INIS)

    Ding, Yi; Wang, Peng; Goel, Lalit; Billinton, Roy; Karki, Rajesh

    2007-01-01

    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)

  18. Developing Simulated Cyber Attack Scenarios Against Virtualized Adversary Networks

    Science.gov (United States)

    2017-03-01

    enclave, as shown in Figure 11, is a common design for many secure networks. Different variations of a cyber-attack scenario can be rehearsed based...achieved a greater degree of success against multiple variations of an enemy network. E. ATTACK TYPES A primary goal of this thesis is to define and...2013. [33] R. Goldberg , “Architectural principles for virtual computer systems,” Ph.D. dissertation, Dept. of Comp. Sci., Harvard Univ., Cambridge

  19. 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

  20. Digitalization and networking of analog simulators and portal images

    Energy Technology Data Exchange (ETDEWEB)

    Pesznyak, C.; Zarand, P.; Mayer, A. [Uzsoki Hospital, Budapest (Hungary). Inst. of Oncoradiology

    2007-03-15

    Background: Many departments have analog simulators and irradiation facilities (especially cobalt units) without electronic portal imaging. Import of the images into the R and V (Record and Verify) system is required. Material and Methods: 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. Results: 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. Conclusion: 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 and V system. (orig.)

  1. 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.

  2. Simulating the formation of keratin filament networks by a piecewise-deterministic Markov process.

    Science.gov (United States)

    Beil, Michael; Lück, Sebastian; Fleischer, Frank; Portet, Stéphanie; Arendt, Wolfgang; Schmidt, Volker

    2009-02-21

    Keratin intermediate filament networks are part of the cytoskeleton in epithelial cells. They were found to regulate viscoelastic properties and motility of cancer cells. Due to unique biochemical properties of keratin polymers, the knowledge of the mechanisms controlling keratin network formation is incomplete. A combination of deterministic and stochastic modeling techniques can be a valuable source of information since they can describe known mechanisms of network evolution while reflecting the uncertainty with respect to a variety of molecular events. We applied the concept of piecewise-deterministic Markov processes to the modeling of keratin network formation with high spatiotemporal resolution. The deterministic component describes the diffusion-driven evolution of a pool of soluble keratin filament precursors fueling various network formation processes. Instants of network formation events are determined by a stochastic point process on the time axis. A probability distribution controlled by model parameters exercises control over the frequency of different mechanisms of network formation to be triggered. Locations of the network formation events are assigned dependent on the spatial distribution of the soluble pool of filament precursors. Based on this modeling approach, simulation studies revealed that the architecture of keratin networks mostly depends on the balance between filament elongation and branching processes. The spatial distribution of network mesh size, which strongly influences the mechanical characteristics of filament networks, is modulated by lateral annealing processes. This mechanism which is a specific feature of intermediate filament networks appears to be a major and fast regulator of cell mechanics.

  3. Fracture Simulation of Highly Crosslinked Polymer Networks: Triglyceride-Based Adhesives

    Science.gov (United States)

    Lorenz, Christian; Stevens, Mark; Wool, Richard

    2003-03-01

    The ACRES program at the U. of Delaware has shown that triglyceride oils derived from plants are a favorable alternative to the traditional adhesives. The triglyceride networks are formed from an initial mixture of styrene monomers, free-radical initiators and triglycerides. We have performed simulations to study the effect of physical composition and physical characteristics of the triglyceride network on the strength of triglyceride network. A coarse-grained, bead-spring model of the triglyceride system is used. The average triglyceride consists of 6 beads per chain, the styrenes are represented as a single bead and the initiators are two bead chains. The polymer network is formed using an off-lattice 3D Monte Carlo simulation, in which the initiators activate the styrene and triglyceride reactive sites and then bonds are randomly formed between the styrene and active triglyceride monomers producing a highly crosslinked polymer network. Molecular dynamics simulations of the network under tensile and shear strains were performed to determine the strength as a function of the network composition. The relationship between the network structure and its strength will also be discussed.

  4. Modeling and simulating the adaptive electrical properties of stochastic polymeric 3D networks

    International Nuclear Information System (INIS)

    Sigala, R; Smerieri, A; Camorani, P; Schüz, A; Erokhin, V

    2013-01-01

    Memristors are passive two-terminal circuit elements that combine resistance and memory. Although in theory memristors are a very promising approach to fabricate hardware with adaptive properties, there are only very few implementations able to show their basic properties. We recently developed stochastic polymeric matrices with a functionality that evidences the formation of self-assembled three-dimensional (3D) networks of memristors. We demonstrated that those networks show the typical hysteretic behavior observed in the ‘one input-one output’ memristive configuration. Interestingly, using different protocols to electrically stimulate the networks, we also observed that their adaptive properties are similar to those present in the nervous system. Here, we model and simulate the electrical properties of these self-assembled polymeric networks of memristors, the topology of which is defined stochastically. First, we show that the model recreates the hysteretic behavior observed in the real experiments. Second, we demonstrate that the networks modeled indeed have a 3D instead of a planar functionality. Finally, we show that the adaptive properties of the networks depend on their connectivity pattern. Our model was able to replicate fundamental qualitative behavior of the real organic 3D memristor networks; yet, through the simulations, we also explored other interesting properties, such as the relation between connectivity patterns and adaptive properties. Our model and simulations represent an interesting tool to understand the very complex behavior of self-assembled memristor networks, which can finally help to predict and formulate hypotheses for future experiments. (paper)

  5. Overview of DOS attacks on wireless sensor networks and experimental results for simulation of interference attacks

    Directory of Open Access Journals (Sweden)

    Željko Gavrić

    2018-01-01

    Full Text Available Wireless sensor networks are now used in various fields. The information transmitted in the wireless sensor networks is very sensitive, so the security issue is very important. DOS (denial of service attacks are a fundamental threat to the functioning of wireless sensor networks. This paper describes some of the most common DOS attacks and potential methods of protection against them. The case study shows one of the most frequent attacks on wireless sensor networks – the interference attack. In the introduction of this paper authors assume that the attack interference can cause significant obstruction of wireless sensor networks. This assumption has been proved in the case study through simulation scenario and simulation results.

  6. Application of neural network technology to setpoint control of a simulated reactor experiment loop

    International Nuclear Information System (INIS)

    Cordes, G.A.; Bryan, S.R.; Powell, R.H.; Chick, D.R.

    1991-01-01

    This paper describes the design, implementation, and application of artificial neural networks to achieve temperature and flow rate control for a simulation of a typical experiment loop in the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory (INEL). The goal of the project was to research multivariate, nonlinear control using neural networks. A loop simulation code was adapted for the project and used to create a training set and test the neural network controller for comparison with the existing loop controllers. The results for the best neural network design are documented and compared with existing loop controller action. The neural network was shown to be as accurate at loop control as the classical controllers in the operating region represented by the training set. 5 refs., 8 figs., 3 tabs

  7. 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...

  8. Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

    OpenAIRE

    Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

    2009-01-01

    Abstract Background Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori assumptions about the interactions, which all simulate the observed patterns. It is important to analyze the properties of the circuits. Findings We have analyzed the simulated gene expression ...

  9. 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.

  10. Analiza karakteristika MPLS simulatora / Characteristics analyse of the MPLS network simulator

    Directory of Open Access Journals (Sweden)

    Boban Pavlović

    2005-05-01

    Full Text Available U ovom radu predstavljena je arhitektura i analizirane su karakteristike MPLS mrežnog simulatora MNS (Multiprotocol Label Switching Network Simulator, koji se koristi u projektovanju paketskih mreža zasnovanih na IP (Internet Protocol protokolu koje moraju podržavati saobraćaj u realnom vremenu i multimedijalni saobraćaj. Na bazi mrežnog simulatora prikazane su i opisane procedure simulacije saobraćaja različitog QoS, kao i simulacija posluživanja saobraćaja višeg prioriteta. / In this article are presented architecture and characteristics analyze of the MPLS Network Simulator (MNS. MNS is used for design packet networks based on Internet Protocol (IP which must support Real-time Traffic and Multimedia. In this document are presented and described simulation procedure for traffics -with different QoS and simulation for resource preemption.

  11. MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

    Science.gov (United States)

    Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

    This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

  12. Efficient Culture Adaptation of Hepatitis C Virus Recombinants with Genotype-Specific Core-NS2 by Using Previously Identified Mutations

    DEFF Research Database (Denmark)

    Scheel, Troels Kasper Høyer; Gottwein, Judith M; Carlsen, Thomas H R

    2011-01-01

    Hepatitis C virus (HCV) is an important cause of chronic liver disease, and interferon-based therapy cures only 40 to 80% of patients, depending on HCV genotype. Research was accelerated by genotype 2a (strain JFH1) infectious cell culture systems. We previously developed viable JFH1-based...... (HC-TN and DH6), 1b (DH1 and DH5), and 3a (DBN) isolates, using previously identified adaptive mutations. Introduction of mutations from isolates of the same subtype either led to immediate efficient virus production or accelerated culture adaptation. The DH6 and DH5 recombinants without introduced...... mutations did not adapt to culture. Universal adaptive effects of mutations in NS3 (Q1247L, I1312V, K1398Q, R1408W, and Q1496L) and NS5A (V2418L) were investigated for JFH1-based genotype 1 to 5 core-NS2 recombinants; several mutations conferred adaptation to H77C (1a), J4 (1b), S52 (3a), and SA13 (5a...

  13. 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

  14. Distributed dynamic simulations of networked control and building performance applications

    NARCIS (Netherlands)

    Yahiaoui, Azzedine

    2018-01-01

    The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the

  15. 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

  16. Analysis of hepatitis C virus core/NS5A protein co-localization using novel cell culture systems expressing core-NS2 and NS5A of genotypes 1-7

    DEFF Research Database (Denmark)

    Galli, Andrea; Scheel, Troels K H; Prentoe, Jannick C

    2013-01-01

    Hepatitis C virus (HCV) is an important human pathogen infecting hepatocytes. With the advent of infectious cell culture systems, the HCV particle assembly and release processes are finally being uncovered. The HCV core and NS5A proteins co-localize on cytoplasmic lipid droplets (c......LDs) or on the endoplasmic reticulum (ER) at different stages of particle assembly. Current knowledge on assembly and release is primarily based on studies in genotype 2a cell culture systems; however, given the high genetic heterogeneity of HCV, variations might exist among genotypes. Here, we developed novel HCV strain...... JFH1-based recombinants expressing core-NS2 and NS5A from genotypes 1-7, and analysed core and NS5A co-localization in infected cells. Huh7.5 cells were transfected with RNA of core-NS2/NS5A recombinants and putative adaptive mutations were analysed by reverse genetics. Adapted core-NS2/NS5A...

  17. Simulation and measurement of optical access network with different types of optical-fiber amplifiers

    Science.gov (United States)

    Latal, Jan; Vogl, Jan; Koudelka, Petr; Vitasek, Jan; Siska, Petr; Liner, Andrej; Papes, Martin; Vasinek, Vladimir

    2012-01-01

    The optical access networks are nowadays swiftly developing in the telecommunications field. These networks can provide higher data transfer rates, and have great potential to the future in terms of transmission possibilities. Many local internet providers responded to these facts and began gradually installing optical access networks into their originally built networks, mostly based on wireless communication. This allowed enlargement of possibilities for end-users in terms of high data rates and also new services such as Triple play, IPTV (Internet Protocol television) etc. However, with this expansion and building-up is also related the potential of reach in case of these networks. Big cities, such as Prague, Brno, Ostrava or Olomouc cannot be simply covered, because of their sizes and also because of their internal regulations given by various organizations in each city. Standard logical and also physical reach of EPON (IEEE 802.3ah - Ethernet Passive Optical Network) optical access network is about 20 km. However, for networks based on Wavelength Division Multiplex the reach can be up to 80 km, if the optical-fiber amplifier is inserted into the network. This article deals with simulation of different types of amplifiers for WDM-PON (Wavelength Division Multiplexing-Passive Optical Network) network in software application Optiwave OptiSystem and than are the values from the application and from real measurement compared.

  18. 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.

  19. IP2P K-means: an efficient method for data clustering on sensor networks

    Directory of Open Access Journals (Sweden)

    Peyman Mirhadi

    2013-03-01

    Full Text Available Many wireless sensor network applications require data gathering as the most important parts of their operations. There are increasing demands for innovative methods to improve energy efficiency and to prolong the network lifetime. Clustering is considered as an efficient topology control methods in wireless sensor networks, which can increase network scalability and lifetime. This paper presents a method, IP2P K-means – Improved P2P K-means, which uses efficient leveling in clustering approach, reduces false labeling and restricts the necessary communication among various sensors, which obviously saves more energy. The proposed method is examined in Network Simulator Ver.2 (NS2 and the preliminary results show that the algorithm works effectively and relatively more precisely.

  20. 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.

  1. Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

    Directory of Open Access Journals (Sweden)

    Jakob Jordan

    2018-02-01

    Full Text Available State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

  2. Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

    Science.gov (United States)

    Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

    2018-01-01

    State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

  3. Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

    Science.gov (United States)

    Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

    2018-01-01

    State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613

  4. Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro

    2015-01-01

    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.

  5. XNsim: Internet-Enabled Collaborative Distributed Simulation via an Extensible Network

    Science.gov (United States)

    Novotny, John; Karpov, Igor; Zhang, Chendi; Bedrossian, Nazareth S.

    2007-01-01

    In this paper, the XNsim approach to achieve Internet-enabled, dynamically scalable collaborative distributed simulation capabilities is presented. With this approach, a complete simulation can be assembled from shared component subsystems written in different formats, that run on different computing platforms, with different sampling rates, in different geographic locations, and over singlelmultiple networks. The subsystems interact securely with each other via the Internet. Furthermore, the simulation topology can be dynamically modified. The distributed simulation uses a combination of hub-and-spoke and peer-topeer network topology. A proof-of-concept demonstrator is also presented. The XNsim demonstrator can be accessed at http://www.jsc.draver.corn/xn that hosts various examples of Internet enabled simulations.

  6. 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.

  7. Simulation of Radiation Heat Transfer in a VAR Furnace Using an Electrical Resistance Network

    Science.gov (United States)

    Ballantyne, A. Stewart

    The use of electrical resistance networks to simulate heat transfer is a well known analytical technique that greatly simplifies the solution of radiation heat transfer problems. In a VAR furnace, radiative heat transfer occurs between the ingot, electrode, and crucible wall; and the arc when the latter is present during melting. To explore the relative heat exchange between these elements, a resistive network model was developed to simulate the heat exchange between the electrode, ingot, and crucible with and without the presence of an arc. This model was then combined with an ingot model to simulate the VAR process and permit a comparison between calculated and observed results during steady state melting. Results from simulations of a variety of alloys of different sizes have demonstrated the validity of the model. Subsequent simulations demonstrate the application of the model to the optimization of both steady state and hot top melt practices, and raises questions concerning heat flux assumptions at the ingot top surface.

  8. On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)

    2015-06-28

    Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

  9. 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

  10. Development of CANDU prototype fuel handling simulator - concept and some simulation results with physical network modeling approach

    Energy Technology Data Exchange (ETDEWEB)

    Xu, X.P. [Candu Energy Inc, Mississauga, Ontario (Canada)

    2012-07-01

    This paper reviewed the need for a fuel handling(FH) simulator in training operators and maintenance personnel, in FH design enhancement based on operating experience (OPEX), and the potential application of Virtual Reality (VR) based simulation technology. Modeling and simulation of the fuelling machine (FM) magazine drive plant (one of the CANDU FH sub-systems) was described. The work established the feasibility of modeling and simulating a physical FH drive system using the physical network approach and computer software tools. The concept and approach can be applied similarly to create the other FH subsystem plant models, which are expected to be integrated with control modules to develop a master FH control model and further to create a virtual FH system. (author)

  11. Development of CANDU prototype fuel handling simulator - concept and some simulation results with physical network modeling approach

    International Nuclear Information System (INIS)

    Xu, X.P.

    2012-01-01

    This paper reviewed the need for a fuel handling(FH) simulator in training operators and maintenance personnel, in FH design enhancement based on operating experience (OPEX), and the potential application of Virtual Reality (VR) based simulation technology. Modeling and simulation of the fuelling machine (FM) magazine drive plant (one of the CANDU FH sub-systems) was described. The work established the feasibility of modeling and simulating a physical FH drive system using the physical network approach and computer software tools. The concept and approach can be applied similarly to create the other FH subsystem plant models, which are expected to be integrated with control modules to develop a master FH control model and further to create a virtual FH system. (author)

  12. 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.

  13. 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.

  14. 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...

  15. Prior-knowledge-based feedforward network simulation of true boiling point curve of crude oil.

    Science.gov (United States)

    Chen, C W; Chen, D Z

    2001-11-01

    Theoretical results and practical experience indicate that feedforward networks can approximate a wide class of functional relationships very well. This property is exploited in modeling chemical processes. Given finite and noisy training data, it is important to encode the prior knowledge in neural networks to improve the fit precision and the prediction ability of the model. In this paper, as to the three-layer feedforward networks and the monotonic constraint, the unconstrained method, Joerding's penalty function method, the interpolation method, and the constrained optimization method are analyzed first. Then two novel methods, the exponential weight method and the adaptive method, are proposed. These methods are applied in simulating the true boiling point curve of a crude oil with the condition of increasing monotonicity. The simulation experimental results show that the network models trained by the novel methods are good at approximating the actual process. Finally, all these methods are discussed and compared with each other.

  16. Simbrain 3.0: A flexible, visually-oriented neural network simulator.

    Science.gov (United States)

    Tosi, Zachary; Yoshimi, Jeffrey

    2016-11-01

    Simbrain 3.0 is a software package for neural network design and analysis, which emphasizes flexibility (arbitrarily complex networks can be built using a suite of basic components) and a visually rich, intuitive interface. These features support both students and professionals. Students can study all of the major classes of neural networks in a familiar graphical setting, and can easily modify simulations, experimenting with networks and immediately seeing the results of their interventions. With the 3.0 release, Simbrain supports models on the order of thousands of neurons and a million synapses. This allows the same features that support education to support research professionals, who can now use the tool to quickly design, run, and analyze the behavior of large, highly customizable simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. 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.

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

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-12-01

    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.

  19. Standard Molar Enthalpy of Formation of RE(C5H8NS2)3(C12H8N2)

    Institute of Scientific and Technical Information of China (English)

    Meng Xiangxin; Shuai Qi; Chen Sanping; Xie Gang; Gao Shengli; Shi Qizhen

    2005-01-01

    Four solid ternary complexes of RE (C5H8NS2)3(C12H8N2) (RE=Eu, Gd, Tb, Dy) were synthesized in absolute ethanol by rare earth chloride low hydrate with the mixed ligands of ammonium pyrrolidinedi-thiocarbamate (APDC) and 1, 10-phenanthroline*H2O (o-phen*H2O) in the ordinary laboratory atmosphere without any cautions against moisture or air sensitivity. IR spectra of the complexes show that the RE3+ coordinated with six sulfur atoms of three PDC- and two nitrogen atoms of o-phen*H2O. It was assumed that the coordination number of RE3+ is eight. The constant-volume combustion energies of the complexes, ΔcU, were determined as (-16937.88±9.79 ), (-17588.79±8.62 ), (-17747.14±8.25 ) and (-17840.37±8.87 ) kJ*mol-1, by a precise rotating-bomb calorimeter at 298.15 K. Its standard molar enthalpies of combustion, ΔcHθm, and standard molar enthalpies of formation, ΔfHθm, were calculated as (-16953.37±9.79), (-17604.28±8.62), (-17762.63±8.25), (-17855.86±8.87) kJ*mol-1 and (-857.04±10.52), (-282.43±9.58), (-130.08±9.13), (-55.75±9.83) kJ*mol-1.

  20. Cross Layer Optimization and Simulation of Smart Grid Home Area Network

    Directory of Open Access Journals (Sweden)

    Lipi K. Chhaya

    2018-01-01

    Full Text Available An electrical “Grid” is a network that carries electricity from power plants to customer premises. Smart Grid is an assimilation of electrical and communication infrastructure. Smart Grid is characterized by bidirectional flow of electricity and information. Smart Grid is a complex network with hierarchical architecture. Realization of complete Smart Grid architecture necessitates diverse set of communication standards and protocols. Communication network protocols are engineered and established on the basis of layered approach. Each layer is designed to produce an explicit functionality in association with other layers. Layered approach can be modified with cross layer approach for performance enhancement. Complex and heterogeneous architecture of Smart Grid demands a deviation from primitive approach and reworking of an innovative approach. This paper describes a joint or cross layer optimization of Smart Grid home/building area network based on IEEE 802.11 standard using RIVERBED OPNET network design and simulation tool. The network performance can be improved by selecting various parameters pertaining to different layers. Simulation results are obtained for various parameters such as WLAN throughput, delay, media access delay, and retransmission attempts. The graphical results show that various parameters have divergent effects on network performance. For example, frame aggregation decreases overall delay but the network throughput is also reduced. To prevail over this effect, frame aggregation is used in combination with RTS and fragmentation mechanisms. The results show that this combination notably improves network performance. Higher value of buffer size considerably increases throughput but the delay is also greater and thus the choice of optimum value of buffer size is inevitable for network performance optimization. Parameter optimization significantly enhances the performance of a designed network. This paper is expected to serve

  1. Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks

    DEFF Research Database (Denmark)

    Talebnia, Farid; Mighani, Moein; Rahimnejad, Mostafa

    2015-01-01

    and 67% of maximum theoretical value. Next, data of the experimental runs were exploited for modeling the processes by artificial neural networks (ANNs) and performance of the developed models was evaluated. The ANN-based models showed a great potential for time-course prediction of the studied processes....... Efficiency of the joint network for simulating the whole process was also determined and promising results were obtained....

  2. Lattice Boltzmann simulation of CO2 reactive transport in network fractured media

    Science.gov (United States)

    Tian, Zhiwei; Wang, Junye

    2017-08-01

    Carbon dioxide (CO2) geological sequestration plays an important role in mitigating CO2 emissions for climate change. Understanding interactions of the injected CO2 with network fractures and hydrocarbons is key for optimizing and controlling CO2 geological sequestration and evaluating its risks to ground water. However, there is a well-known, difficult process in simulating the dynamic interaction of fracture-matrix, such as dynamic change of matrix porosity, unsaturated processes in rock matrix, and effect of rock mineral properties. In this paper, we develop an explicit model of the fracture-matrix interactions using multilayer bounce-back treatment as a first attempt to simulate CO2 reactive transport in network fractured media through coupling the Dardis's LBM porous model for a new interface treatment. Two kinds of typical fracture networks in porous media are simulated: straight cross network fractures and interleaving network fractures. The reaction rate and porosity distribution are illustrated and well-matched patterns are found. The species concentration distribution and evolution with time steps are also analyzed and compared with different transport properties. The results demonstrate the capability of this model to investigate the complex processes of CO2 geological injection and reactive transport in network fractured media, such as dynamic change of matrix porosity.

  3. Development of Fast-Running Simulation Methodology Using Neural Networks for Load Follow Operation

    International Nuclear Information System (INIS)

    Seong, Seung-Hwan; Park, Heui-Youn; Kim, Dong-Hoon; Suh, Yong-Suk; Hur, Seop; Koo, In-Soo; Lee, Un-Chul; Jang, Jin-Wook; Shin, Yong-Chul

    2002-01-01

    A new fast-running analytic model has been developed for analyzing the load follow operation. The new model was based on the neural network theory, which has the capability of modeling the input/output relationships of a nonlinear system. The new model is made up of two error back-propagation neural networks and procedures to calculate core parameters, such as the distributions and density of xenon in a quasi-steady-state core like load follow operation. One neural network is designed to retrieve the axial offset of power distribution, and the other is for reactivity corresponding to a given core condition. The training data sets for learning the neural networks in the new model are generated with a three-dimensional nodal code and, also, the measured data of the first-day test of load follow operation. Using the new model, the simulation results of the 5-day load follow test in a pressurized water reactor show a good agreement between the simulation data and the actual measured data. Required computing time for simulating a load follow operation is comparable to that of a fast-running lumped model. Moreover, the new model does not require additional engineering factors to compensate for the difference between the actual measurements and analysis results because the neural network has the inherent learning capability of neural networks to new situations

  4. Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

    Science.gov (United States)

    Radev, Dimitar; Lokshina, Izabella

    2010-11-01

    The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

  5. Data flow methods for dynamic system simulation - A CSSL-IV microcomputer network interface

    Science.gov (United States)

    Makoui, A.; Karplus, W. J.

    1983-01-01

    A major problem in employing networks of microcomputers for the real-time simulation of complex systems is to allocate computational tasks to the various microcomputers in such a way that idle time and time lost in interprocess communication is minimized. The research reported in this paper is directed to the development of a software interface between a higher-level simulation language and a network of microcomputers. A CSSL-IV source program is translated to a data flow graph. This graph is then analyzed automatically so as to allocate computing tasks to the various processors.

  6. 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.

  7. The framework for simulation of bioinspired security mechanisms against network infrastructure attacks.

    Science.gov (United States)

    Shorov, Andrey; Kotenko, Igor

    2014-01-01

    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 procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary 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.

  8. 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.

  9. Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

    Directory of Open Access Journals (Sweden)

    Lorenzo L. Pesce

    2013-01-01

    Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  10. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    Science.gov (United States)

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    2013-01-01

    Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  11. 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

  12. Application and Simulation of Fuzzy Neural Network PID Controller in the Aircraft Cabin Temperature

    Directory of Open Access Journals (Sweden)

    Ding Fang

    2013-06-01

    Full Text Available Considering complex factors of affecting ambient temperature in Aircraft cabin, and some shortages of traditional PID control like the parameters difficult to be tuned and control ineffective, this paper puts forward the intelligent PID algorithm that makes fuzzy logic method and neural network together, scheming out the fuzzy neural net PID controller. After the correction of the fuzzy inference and dynamic learning of neural network, PID parameters of the controller get the optimal parameters. MATLAB simulation results of the cabin temperature control model show that the performance of the fuzzy neural network PID controller has been greatly improved, with faster response, smaller overshoot and better adaptability.

  13. 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.

  14. Network reliability analysis of complex systems using a non-simulation-based method

    International Nuclear Information System (INIS)

    Kim, Youngsuk; Kang, Won-Hee

    2013-01-01

    Civil infrastructures such as transportation, water supply, sewers, telecommunications, and electrical and gas networks often establish highly complex networks, due to their multiple source and distribution nodes, complex topology, and functional interdependence between network components. To understand the reliability of such complex network system under catastrophic events such as earthquakes and to provide proper emergency management actions under such situation, efficient and accurate reliability analysis methods are necessary. In this paper, a non-simulation-based network reliability analysis method is developed based on the Recursive Decomposition Algorithm (RDA) for risk assessment of generic networks whose operation is defined by the connections of multiple initial and terminal node pairs. The proposed method has two separate decomposition processes for two logical functions, intersection and union, and combinations of these processes are used for the decomposition of any general system event with multiple node pairs. The proposed method is illustrated through numerical network examples with a variety of system definitions, and is applied to a benchmark gas transmission pipe network in Memphis TN to estimate the seismic performance and functional degradation of the network under a set of earthquake scenarios.

  15. 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.

  16. Tests of peak flow scaling in simulated self-similar river networks

    Science.gov (United States)

    Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.

    2001-01-01

    The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

  17. 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...

  18. Application of a distributed network in computational fluid dynamic simulations

    Science.gov (United States)

    Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.; Deshpande, Ashish

    1994-01-01

    A general-purpose 3-D, incompressible Navier-Stokes algorithm is implemented on a network of concurrently operating workstations using parallel virtual machine (PVM) and compared with its performance on a CRAY Y-MP and on an Intel iPSC/860. The problem is relatively computationally intensive, and has a communication structure based primarily on nearest-neighbor communication, making it ideally suited to message passing. Such problems are frequently encountered in computational fluid dynamics (CDF), and their solution is increasingly in demand. The communication structure is explicitly coded in the implementation to fully exploit the regularity in message passing in order to produce a near-optimal solution. Results are presented for various grid sizes using up to eight processors.

  19. Dual Arm Work Package performance estimates and telerobot task network simulation

    International Nuclear Information System (INIS)

    Draper, J.V.

    1997-01-01

    This paper describes the methodology and results of a network simulation study of the Dual Arm Work Package (DAWP), to be employed for dismantling the Argonne National Laboratory CP-5 reactor. The development of the simulation model was based upon the results of a task analysis for the same system. This study was performed by the Oak Ridge National Laboratory (ORNL), in the Robotics and Process Systems Division. Funding was provided the US Department of Energy's Office of Technology Development, Robotics Technology Development Program (RTDP). The RTDP is developing methods of computer simulation to estimate telerobotic system performance. Data were collected to provide point estimates to be used in a task network simulation model. Three skilled operators performed six repetitions of a pipe cutting task representative of typical teleoperation cutting operations

  20. 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.

  1. 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.

  2. Versatile networks of simulated spiking neurons displaying winner-take-all behavior.

    Science.gov (United States)

    Chen, Yanqing; McKinstry, Jeffrey L; Edelman, Gerald M

    2013-01-01

    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.

  3. 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

    2018-06-01

    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.

  4. 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.

  5. HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

    International Nuclear Information System (INIS)

    Marchetti, Luca; Priami, Corrado; Thanh, Vo Hong

    2016-01-01

    This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

  6. HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Marchetti, Luca, E-mail: marchetti@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); University of Trento, Department of Mathematics (Italy); Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy)

    2016-07-15

    This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

  7. 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.

  8. 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.

  9. Efficient computation in networks of spiking neurons: simulations and theory

    International Nuclear Information System (INIS)

    Natschlaeger, T.

    1999-01-01

    One of the most prominent features of biological neural systems is that individual neurons communicate via short electrical pulses, the so called action potentials or spikes. In this thesis we investigate possible mechanisms which can in principle explain how complex computations in spiking neural networks (SNN) can be performed very fast, i.e. within a few 10 milliseconds. Some of these models are based on the assumption that relevant information is encoded by the timing of individual spikes (temporal coding). We will also discuss a model which is based on a population code and still is able to perform fast complex computations. In their natural environment biological neural systems have to process signals with a rich temporal structure. Hence it is an interesting question how neural systems process time series. In this context we explore possible links between biophysical characteristics of single neurons (refractory behavior, connectivity, time course of postsynaptic potentials) and synapses (unreliability, dynamics) on the one hand and possible computations on times series on the other hand. Furthermore we describe a general model of computation that exploits dynamic synapses. This model provides a general framework for understanding how neural systems process time-varying signals. (author)

  10. Modeling a Large Data Acquisition Network in a Simulation Framework

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00337030; The ATLAS collaboration; Froening, Holger; Garcia, Pedro Javier; Vandelli, Wainer

    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...

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

    NARCIS (Netherlands)

    Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

    2009-01-01

    Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

  16. 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…

  17. 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.

  18. 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

    The paper presents a hybrid Genetic and Simulated Annealing algorithm for implementing Chordal Ring structure in optical backbone network. In recent years, topologies based on regular graph structures gained a lot of interest due to their good communication properties for physical topology of the...

  19. Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation

    CSIR Research Space (South Africa)

    Ngwangwa, HM

    2010-04-01

    Full Text Available -1 Journal of Terramechanics Volume 47, Issue 2, April 2010, Pages 97-111 Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation H.M. Ngwangwaa, P.S. Heynsa, , , F...

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. Transport link scanner: simulating geographic transport network expansion through individual investments

    Science.gov (United States)

    Jacobs-Crisioni, C.; Koopmans, C. C.

    2016-07-01

    This paper introduces a GIS-based model that simulates the geographic expansion of transport networks by several decision-makers with varying objectives. The model progressively adds extensions to a growing network by choosing the most attractive investments from a limited choice set. Attractiveness is defined as a function of variables in which revenue and broader societal benefits may play a role and can be based on empirically underpinned parameters that may differ according to private or public interests. The choice set is selected from an exhaustive set of links and presumably contains those investment options that best meet private operator's objectives by balancing the revenues of additional fare against construction costs. The investment options consist of geographically plausible routes with potential detours. These routes are generated using a fine-meshed regularly latticed network and shortest path finding methods. Additionally, two indicators of the geographic accuracy of the simulated networks are introduced. A historical case study is presented to demonstrate the model's first results. These results show that the modelled networks reproduce relevant results of the historically built network with reasonable accuracy.

  5. 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.

  6. Network Signaling Channel for Improving ZigBee Performance in Dynamic Cluster-Tree Networks

    Directory of Open Access Journals (Sweden)

    D. Hämäläinen

    2008-03-01

    Full Text Available ZigBee is one of the most potential standardized technologies for wireless sensor networks (WSNs. Yet, sufficient energy-efficiency for the lowest power WSNs is achieved only in rather static networks. This severely limits the applicability of ZigBee in outdoor and mobile applications, where operation environment is harsh and link failures are common. This paper proposes a network channel beaconing (NCB algorithm for improving ZigBee performance in dynamic cluster-tree networks. NCB reduces the energy consumption of passive scans by dedicating one frequency channel for network beacon transmissions and by energy optimizing their transmission rate. According to an energy analysis, the power consumption of network maintenance operations reduces by 70%–76% in dynamic networks. In static networks, energy overhead is negligible. Moreover, the service time for data routing increases up to 37%. The performance of NCB is validated by ns-2 simulations. NCB can be implemented as an extension on MAC and NWK layers and it is fully compatible with ZigBee.

  7. 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.

  8. Harmonic currents circulation in electrical networks simulation and analysis

    Energy Technology Data Exchange (ETDEWEB)

    Em-Mamlouk, W.M. [MEP, Cairo (Egypt); El-Sharkawy, M.A. [Shams Univ., Cairo (Egypt). Dept. of Electrical Power and Machines; Mostafa, H.E. [Jazan Univ., Jazan (Saudi Arabia). Electrical Dept.

    2009-07-01

    A detailed harmonic flow analysis for a 13-bus balanced industrial distribution system was presented. The aim of the study was to determine the influence of harmonic sources in various branches of the system on voltage and current waveforms before disruptions to the utility supply system occurred. The current harmonic contents of an adjustable speed drive (ASD) were studied under various loading conditions. The test system was simulated using a standard study test system. Harmonic effects from multiple sources were investigated, and voltage distortion on the different buses was monitored. The study demonstrated that while the harmonic loads circulated harmonic currents in all system branches, no harmonic source was directly connected to the system buses. Many of the investigated cases exceeded allowable voltage total harmonic distortion and or current total harmonic distortion standards set by the Institute of Electrical and Electronic Engineers (IEEE). It was concluded that active harmonic filters should be used to prevent the effects of harmonic current circulation at different buses on neighbouring loads within a system. 8 refs., 11 tabs., 15 figs.

  9. 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.

  10. 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.

  11. Using Equation-Free Computation to Accelerate Network-Free Stochastic Simulation of Chemical Kinetics.

    Science.gov (United States)

    Lin, Yen Ting; Chylek, Lily A; Lemons, Nathan W; Hlavacek, William S

    2018-06-21

    The chemical kinetics of many complex systems can be concisely represented by reaction rules, which can be used to generate reaction events via a kinetic Monte Carlo method that has been termed network-free simulation. Here, we demonstrate accelerated network-free simulation through a novel approach to equation-free computation. In this process, variables are introduced that approximately capture system state. Derivatives of these variables are estimated using short bursts of exact stochastic simulation and finite differencing. The variables are then projected forward in time via a numerical integration scheme, after which a new exact stochastic simulation is initialized and the whole process repeats. The projection step increases efficiency by bypassing the firing of numerous individual reaction events. As we show, the projected variables may be defined as populations of building blocks of chemical species. The maximal number of connected molecules included in these building blocks determines the degree of approximation. Equation-free acceleration of network-free simulation is found to be both accurate and efficient.

  12. Can surgical simulation be used to train detection and classification of neural networks?

    Science.gov (United States)

    Zisimopoulos, Odysseas; Flouty, Evangello; Stacey, Mark; Muscroft, Sam; Giataganas, Petros; Nehme, Jean; Chow, Andre; Stoyanov, Danail

    2017-10-01

    Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems.

  13. 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.

  14. Personalizes lung motion simulation fore external radiotherapy using an artificial neural network

    International Nuclear Information System (INIS)

    Laurent, R.

    2011-01-01

    The development of new techniques in the field of external radiotherapy opens new ways of gaining accuracy in dose distribution, in particular through the knowledge of individual lung motion. The numeric simulation NEMOSIS (Neural Network Motion Simulation System) we describe is based on artificial neural networks (ANN) and allows, in addition to determining motion in a personalized way, to reduce the necessary initial doses to determine it. In the first part, we will present current treatment options, lung motion as well as existing simulation or estimation methods. The second part describes the artificial neural network used and the steps for defining its parameters. An accurate evaluation of our approach was carried out on original patient data. The obtained results are compared with an existing motion estimated method. The extremely short computing time, in the range of milliseconds for the generation of one respiratory phase, would allow its use in clinical routine. Modifications to NEMOSIS in order to meet the requirements for its use in external radiotherapy are described, and a study of the motion of tumor outlines is carried out. This work lays the basis for lung motion simulation with ANNs and validates our approach. Its real time implementation coupled to its predication accuracy makes NEMOSIS promising tool for the simulation of motion synchronized with breathing. (author)

  15. 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.

  16. The General-Use Nodal Network Solver (GUNNS) Modeling Package for Space Vehicle Flow System Simulation

    Science.gov (United States)

    Harvey, Jason; Moore, Michael

    2013-01-01

    The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.

  17. Event Based Simulator for Parallel Computing over the Wide Area Network for Real Time Visualization

    Science.gov (United States)

    Sundararajan, Elankovan; Harwood, Aaron; Kotagiri, Ramamohanarao; Satria Prabuwono, Anton

    As the computational requirement of applications in computational science continues to grow tremendously, the use of computational resources distributed across the Wide Area Network (WAN) becomes advantageous. However, not all applications can be executed over the WAN due to communication overhead that can drastically slowdown the computation. In this paper, we introduce an event based simulator to investigate the performance of parallel algorithms executed over the WAN. The event based simulator known as SIMPAR (SIMulator for PARallel computation), simulates the actual computations and communications involved in parallel computation over the WAN using time stamps. Visualization of real time applications require steady stream of processed data flow for visualization purposes. Hence, SIMPAR may prove to be a valuable tool to investigate types of applications and computing resource requirements to provide uninterrupted flow of processed data for real time visualization purposes. The results obtained from the simulation show concurrence with the expected performance using the L-BSP model.

  18. 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.

  19. 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.

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

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael

    2005-01-01

    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...

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

    Science.gov (United States)

    Mones, Enys; Stopczynski, Arkadiusz; Pentland, Alex 'Sandy'; Hupert, Nathaniel; Lehmann, Sune

    2018-01-01

    Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the 'holy grails' of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time. 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 call 'cyber-directed vaccination') can enhance vaccination campaigns against diseases with short-range (but not full-range) modes of transmission. © 2018 The Author(s).

  2. 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.

  3. Use of high performance networks and supercomputers for real-time flight simulation

    Science.gov (United States)

    Cleveland, Jeff I., II

    1993-01-01

    In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be consistent in processing time and be completed in as short a time as possible. These operations include simulation mathematical model computation and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to the Computer Automated Measurement and Control (CAMAC) technology which resulted in a factor of ten increase in the effective bandwidth and reduced latency of modules necessary for simulator communication. This technology extension is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC are completing the development of the use of supercomputers for mathematical model computation to support real-time flight simulation. This includes the development of a real-time operating system and development of specialized software and hardware for the simulator network. This paper describes the data acquisition technology and the development of supercomputing for flight simulation.

  4. 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.

  5. Fluid distribution network and steam generators and method for nuclear power plant training simulator

    International Nuclear Information System (INIS)

    Alliston, W.H.; Johnson, S.J.; Mutafelija, B.A.

    1975-01-01

    A description is given of a training simulator for the real-time dynamic operation of a nuclear power plant which utilizes apparatus that includes control consoles having manual and automatic devices corresponding to simulated plant components and indicating devices for monitoring physical values in the simulated plant. A digital computer configuration is connected to the control consoles to calculate the dynamic real-time simulated operation of the plant in accordance with the simulated plant components to provide output data including data for operating the control console indicating devices. In the method and system for simulating a fluid distribution network of the power plant, such as that which includes, for example, a main steam system which distributes steam from steam generators to high pressure turbine steam reheaters, steam dump valves, and feedwater heaters, the simultaneous solution of linearized non-linear algebraic equations is used to calculate all the flows throughout the simulated system. A plurality of parallel connected steam generators that supply steam to the system are simulated individually, and include the simulation of shrink-swell characteristics

  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. Simulation Modeling of Resilience Assessment in Indonesian Fertiliser Industry Supply Networks

    Science.gov (United States)

    Utami, I. D.; Holt, R. J.; McKay, A.

    2018-01-01

    Supply network resilience is a significant aspect in the performance of the Indonesian fertiliser industry. Decision makers use risk assessment and port management reports to evaluate the availability of infrastructure. An opportunity was identified to incorporate both types of data into an approach for the measurement of resilience. A framework, based on a synthesis of literature and interviews with industry practitioners, covering both social and technical factors is introduced. A simulation model was then built to allow managers to explore implications for resilience and predict levels of risk in different scenarios. Result of interview with respondens from Indonesian fertiliser industry indicated that the simulation model could be valuable in the assessment. This paper provides details of the simulation model for decision makers to explore levels of risk in supply networks. For practitioners, the model could be used by government to assess the current condition of supply networks in Indonesian industries. On the other hand, for academia, the approach provides a new application of agent-based models in research on supply network resilience and presents a real example of how agent-based modeling could be used as to support the assessment approach.

  8. 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.

  9. Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

    Science.gov (United States)

    Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

    2010-01-01

    This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

  10. ADAPTIVE GOSSIP BASED PROTOCOL FOR ENERGY EFFICIENT MOBILE ADHOC NETWORK

    Directory of Open Access Journals (Sweden)

    S. Rajeswari

    2012-03-01

    Full Text Available In Gossip Sleep Protocol, network performance is enhanced based on energy resource. But energy conservation is achieved with the reduced throughput. In this paper, it has been proposed a new Protocol for Mobile Ad hoc Network to achieve reliability with energy conservation. Based on the probability (p values, the value of sleep nodes is fixed initially. The probability value can be adaptively adjusted by Remote Activated Switch during the transmission process. The adaptiveness of gossiping probability is determined by the Packet Delivery Ratio. For performance comparison, we have taken Routing overhead, Packet Delivery Ratio, Number of dropped packets and Energy consumption with the increasing number of forwarding nodes. We used UDP based traffic models to analyze the performance of this protocol. We analyzed TCP based traffic models for average end to end delay. We have used the NS-2 simulator.

  11. First-order design of geodetic networks using the simulated annealing method

    Science.gov (United States)

    Berné, J. L.; Baselga, S.

    2004-09-01

    The general problem of the optimal design for a geodetic network subject to any extrinsic factors, namely the first-order design problem, can be dealt with as a numeric optimization problem. The classic theory of this problem and the optimization methods are revised. Then the innovative use of the simulated annealing method, which has been successfully applied in other fields, is presented for this classical geodetic problem. This method, belonging to iterative heuristic techniques in operational research, uses a thermodynamical analogy to crystalline networks to offer a solution that converges probabilistically to the global optimum. Basic formulation and some examples are studied.

  12. ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

    Science.gov (United States)

    Matsuyama, Shinako; Terano, Takao

    This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

  13. 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.

  14. 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.

  15. 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.

  16. Isotachophoresis of proteins in a networked microfluidic chip: experiment and 2-D simulation.

    Science.gov (United States)

    Cui, Huanchun; Dutta, Prashanta; Ivory, Cornelius F

    2007-04-01

    This paper reports both the experimental application and 2-D simulation of ITP of proteins in a networked microfluidic chip. Experiments demonstrate that a mixture of three fluorescent proteins can be concentrated and stacked into adjacent zones of pure protein under a constant voltage of 100 V over a 2 cm long microchannel. Measurements of the isotachophoretic velocity of the moving zones demonstrates that, during ITP under a constant voltage, the zone velocity decreases as more of the channel is occupied by the terminating electrolyte. A 2-D ITP model based on the Nernst-Planck equations illustrates the stacking and separation features of ITP using simulations of three virtual proteins. The self-sharpening behavior of ITP zones dispersed by a T-junction is clearly demonstrated both by experiment and by simulation. Comparison of 2-D simulations of ITP and zone electrophoresis (ZE) confirms that ZE lacks the ability to resharpen protein zones after they pass through a T-junction.

  17. 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...... with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties...... 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....

  18. 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.

  19. Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

    International Nuclear Information System (INIS)

    Li, Ming; Kang, Zhan; Huang, Xiaobo

    2015-01-01

    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

  20. Applications of wireless sensor networks for monitoring oil and gas onshore fields; Aplicacoes de redes de sensores sem fio em monitoramento de pocos petroliferos terrestres

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Ivanovitch Medeiros D. da; Oliveira, Luiz Affonso H. Guedes de [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil)

    2008-07-01

    The major part of onshore oil wells monitoring currently is based on wireless solutions. However these solutions employ old technologies based on analog radios and inefficient communication topologies. On the other hand, technologies based on digital radios can provide more efficient solutions related to energy consumption, security and fault tolerance. Thus, this paper investigates the Wireless Sensor Network as an approach to onshore oil wells monitoring. Reliability, energy consumption and communication delay in a mesh topology will be used as metrics to validate the proposal using the simulation tool NS-2. (author)

  1. Artificial neural networks for dynamic monitoring of simulated-operating parameters of high temperature gas cooled engineering test reactor (HTTR)

    International Nuclear Information System (INIS)

    Seker, Serhat; Tuerkcan, Erdinc; Ayaz, Emine; Barutcu, Burak

    2003-01-01

    This paper addresses to the problem of utilisation of the artificial neural networks (ANNs) for detecting anomalies as well as physical parameters of a nuclear power plant during power operation in real time. Three different types of neural network algorithms were used namely, feed-forward neural network (back-propagation, BP) and two types of recurrent neural networks (RNN). The data used in this paper were gathered from the simulation of the power operation of the Japan's High Temperature Engineering Testing Reactor (HTTR). For the wide range of power operation, 56 signals were generated by the reactor dynamic simulation code for several hours of normal power operation at different power ramps between 30 and 100% nominal power. Paper will compare the outcomes of different neural networks and presents the neural network system and the determination of physical parameters from the simulated operating data

  2. Simulation model for centrifugal pump in flow networks based on internal characteristics

    International Nuclear Information System (INIS)

    Sun, Ji-Lin; Xue, Ruo-Jun; Peng, Min-Jun

    2018-01-01

    For the simulation of centrifugal pump in flow network system, in general three approaches can be used, the fitting model, the numerical method and the internal characteristics model. The fitting model is simple and rapid thus widely used. The numerical method can provide more detailed information in comparison with the fitting model, but increases implementation complexity and computational cost. In real-time simulations of flow networks, to simulate the condition out of the rated condition, especially for the volume flow rate, which the accuracy of fitting model is incredible, a new method for simulating centrifugal pumps was proposed in this research. The method based on the theory head and hydraulic loss in centrifugal pumps, and cavitation is also to be considered. The simulation results are verified with experimental benchmark data from an actual pump. The comparison confirms that the proposed method could fit the flow-head curves well, and the responses of main parameters in dynamic-state operations are consistent with theoretical analyses.

  3. 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.

  4. 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;

  5. Catchment & sewer network simulation model to benchmark control strategies within urban wastewater systems

    DEFF Research Database (Denmark)

    Saagi, Ramesh; Flores Alsina, Xavier; Fu, Guangtao

    2016-01-01

    This paper aims at developing a benchmark simulation model to evaluate control strategies for the urban catchment and sewer network. Various modules describing wastewater generation in the catchment, its subsequent transport and storage in the sewer system are presented. Global/local overflow based...... evaluation criteria describing the cumulative and acute effects are presented. Simulation results show that the proposed set of models is capable of generating daily, weekly and seasonal variations as well as describing the effect of rain events on wastewater characteristics. Two sets of case studies...

  6. Tetrahedral ↔ octahedral network structure transition in simulated vitreous SiO2

    International Nuclear Information System (INIS)

    Vo Van Hoang; Nguyen Trung Hai; Hoang Zung

    2006-01-01

    By using molecular dynamics (MD) simulations we found a transition from a tetrahedral to an octahedral network structure in an amorphous SiO 2 model under compression from 2.20 to 5.35 g/cm 3 . And on heating of a high density amorphous (hda) model of 5.35 g/cm 3 at zero pressure, the structure transforms to a low density amorphous (lda) form. Simulations were done in a model containing 3000 particles under periodic boundary conditions with interatomic potentials which have a weak Coulomb interaction and a Morse type short-range interaction

  7. A more realistic simulation of the performance of the infra-sound monitoring network

    International Nuclear Information System (INIS)

    Le Pichon, A.; Vergoz, J.; Blanc, E.

    2008-01-01

    The first global maps showing the performance of the infra-sound network of the international monitoring system were set in the nineties. Recent measurement of the background noise by the 36 operating stations combined with advanced models of wind give now a more realistic mapping. It has become possible to validate simulations by measuring real events. For instance the explosion that happened in March 2008 in an ammunition storehouse in Albania was detected till Zalesovo (Russia) 4920 km away. These new simulations confirm the detection capability of the network to detect and localize atmospheric explosions whose energy is over 1 kt. It is also shown that the detection performance are very sensitive to both time and places. (A.C.)

  8. Modelling and Simulation of National Electronic Product Code Network Demonstrator Project

    Science.gov (United States)

    Mo, John P. T.

    The National Electronic Product Code (EPC) Network Demonstrator Project (NDP) was the first large scale consumer goods track and trace investigation in the world using full EPC protocol system for applying RFID technology in supply chains. The NDP demonstrated the methods of sharing information securely using EPC Network, providing authentication to interacting parties, and enhancing the ability to track and trace movement of goods within the entire supply chain involving transactions among multiple enterprise. Due to project constraints, the actual run of the NDP was 3 months only and was unable to consolidate with quantitative results. This paper discusses the modelling and simulation of activities in the NDP in a discrete event simulation environment and provides an estimation of the potential benefits that can be derived from the NDP if it was continued for one whole year.

  9. 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

  10. 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.

  11. 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.

  12. Effects of Network Characteristics on Reaching the Payoff-Dominant Equilibrium in Coordination Games: A Simulation study.

    Science.gov (United States)

    Buskens, Vincent; Snijders, Chris

    2016-01-01

    We study how payoffs and network structure affect reaching the payoff-dominant equilibrium in a [Formula: see text] coordination game that actors play with their neighbors in a network. Using an extensive simulation analysis of over 100,000 networks with 2-25 actors, we show that the importance of network characteristics is restricted to a limited part of the payoff space. In this part, we conclude that the payoff-dominant equilibrium is chosen more often if network density is larger, the network is more centralized, and segmentation of the network is smaller. Moreover, it is more likely that heterogeneity in behavior persists if the network is more segmented and less centralized. Persistence of heterogeneous behavior is not related to network density.

  13. 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.

  14. Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users

    OpenAIRE

    Vladislav D. Veksler; Norbou Buchler; Blaine E. Hoffman; Daniel N. Cassenti; Char Sample; Shridat Sugrim

    2018-01-01

    Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision li...

  15. Impact of window decrement rate on TCP performance in an adhoc network

    Science.gov (United States)

    Suherman; Hutasuhut, Arief T. W.; Badra, Khaldun; Al-Akaidi, Marwan

    2017-09-01

    Transmission control protocol (TCP) is a reliable transport protocol handling end to end connection in TCP/IP stack. It works well in copper or optical fibre link, but experiences increasing delay in wireless network. Further, TCP experiences multiple retransmissions due to higher collision probability within wireless network. The situation may get worsen in an ad hoc network. This paper examines the impact half window or window reduction rate to the overall TCP performances. The evaluation using NS-2 simulator shows that the smaller the window decrement rate results the smaller end to end delay. Delay is reduced to 17.05% in average when window decrement rate decreases. Average jitter also decreases 4.15%, while packet loss is not affected.

  16. 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.

  17. Numerical Simulation of Flow and Suspended Sediment Transport in the Distributary Channel Networks

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2014-01-01

    Full Text Available Flow and suspended sediment transport in distributary channel networks play an important role in the evolution of deltas and estuaries, as well as the coastal environment. In this study, a 1D flow and suspended sediment transport model is presented to simulate the hydrodynamics and suspended sediment transport in the distributary channel networks. The governing equations for river flow are the Saint-Venant equations and for suspended sediment transport are the nonequilibrium transport equations. The procedure of solving the governing equations is firstly to get the matrix form of the water level and suspended sediment concentration at all connected junctions by utilizing the transformation of the governing equations of the single channel. Secondly, the water level and suspended sediment concentration at all junctions can be obtained by solving these irregular spare matrix equations. Finally, the water level, discharge, and suspended sediment concentration at each river section can be calculated. The presented 1D flow and suspended sediment transport model has been applied to the Pearl River networks and can reproduce water levels, discharges, and suspended sediment concentration with good accuracy, indicating this that model can be used to simulate the hydrodynamics and suspended sediment concentration in the distributary channel networks.

  18. A MPLS Simulation for Use in Design Networking for Multi Site Businesses

    Directory of Open Access Journals (Sweden)

    Petac Eugen

    2017-01-01

    Full Text Available The ease of administration and its reduced costs make the MPLS (Multiprotocol LabelSwitching technology attractive to those who want to deploy a performant, reliable and scalableprivate network. Connecting enterprises to remote locations, customers, and vendors via the MPLSis a very flexible solution that is being taken into account by many communication providers. VPN(Virtual Private Networks is one of the most demanding services for the MPLS technology. Theservice providing of MPLS Differentiated Services (MPLS DiffServ allows the customization ofeach client's traffic. This paper briefly outlines the theoretical aspects of the MPLS technology. Thetheoretical analysis is summed up in a case study called MPLS_DiffServ, developed with theOPNET Modeler simulator. This simulator allowed us to create a network model and configure thenetwork equipment to provide MPLS DiffServ services. The results that are obtained from thesimulation run are suggestive for networking education and a good starting point for thenetworking research area, as services for new business environment.

  19. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    Science.gov (United States)

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

  20. 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).

  1. A simulation training evaluation method for distribution network fault based on radar chart

    Directory of Open Access Journals (Sweden)

    Yuhang Xu

    2018-01-01

    Full Text Available In order to solve the problem of automatic evaluation of dispatcher fault simulation training in distribution network, a simulation training evaluation method based on radar chart for distribution network fault is proposed. The fault handling information matrix is established to record the dispatcher fault handling operation sequence and operation information. The four situations of the dispatcher fault isolation operation are analyzed. The fault handling anti-misoperation rule set is established to describe the rules prohibiting dispatcher operation. Based on the idea of artificial intelligence reasoning, the feasibility of dispatcher fault handling is described by the feasibility index. The relevant factors and evaluation methods are discussed from the three aspects of the fault handling result feasibility, the anti-misoperation correctness and the operation process conciseness. The detailed calculation formula is given. Combining the independence and correlation between the three evaluation angles, a comprehensive evaluation method of distribution network fault simulation training based on radar chart is proposed. The method can comprehensively reflect the fault handling process of dispatchers, and comprehensively evaluate the fault handling process from various angles, which has good practical value.

  2. 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.

  3. 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)

  4. Conducting multicenter research in healthcare simulation: Lessons learned from the INSPIRE network.

    Science.gov (United States)

    Cheng, Adam; Kessler, David; Mackinnon, Ralph; Chang, Todd P; Nadkarni, Vinay M; Hunt, Elizabeth A; Duval-Arnould, Jordan; Lin, Yiqun; Pusic, Martin; Auerbach, Marc

    2017-01-01

    Simulation-based research has grown substantially over the past two decades; however, relatively few published simulation studies are multicenter in nature. Multicenter research confers many distinct advantages over single-center studies, including larger sample sizes for more generalizable findings, sharing resources amongst collaborative sites, and promoting networking. Well-executed multicenter studies are more likely to improve provider performance and/or have a positive impact on patient outcomes. In this manuscript, we offer a step-by-step guide to conducting multicenter, simulation-based research based upon our collective experience with the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE). Like multicenter clinical research, simulation-based multicenter research can be divided into four distinct phases. Each phase has specific differences when applied to simulation research: (1) Planning phase , to define the research question, systematically review the literature, identify outcome measures, and conduct pilot studies to ensure feasibility and estimate power; (2) Project Development phase , when the primary investigator identifies collaborators, develops the protocol and research operations manual, prepares grant applications, obtains ethical approval and executes subsite contracts, registers the study in a clinical trial registry, forms a manuscript oversight committee, and conducts feasibility testing and data validation at each site; (3) Study Execution phase , involving recruitment and enrollment of subjects, clear communication and decision-making, quality assurance measures and data abstraction, validation, and analysis; and (4) Dissemination phase , where the research team shares results via conference presentations, publications, traditional media, social media, and implements strategies for translating results to practice. With this manuscript, we provide a guide to conducting quantitative multicenter

  5. Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

    Science.gov (United States)

    Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

    2015-08-01

    Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. 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.

  7. 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.

  8. Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis.

    Science.gov (United States)

    Wang, Ting; Plecháč, Petr

    2017-12-21

    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.

  9. Combined Simulated Annealing and Genetic Algorithm Approach to Bus Network Design

    Science.gov (United States)

    Liu, Li; Olszewski, Piotr; Goh, Pong-Chai

    A new method - combined simulated annealing (SA) and genetic algorithm (GA) approach is proposed to solve the problem of bus route design and frequency setting for a given road network with fixed bus stop locations and fixed travel demand. The method involves two steps: a set of candidate routes is generated first and then the best subset of these routes is selected by the combined SA and GA procedure. SA is the main process to search for a better solution to minimize the total system cost, comprising user and operator costs. GA is used as a sub-process to generate new solutions. Bus demand assignment on two alternative paths is performed at the solution evaluation stage. The method was implemented on four theoretical grid networks of different size and a benchmark network. Several GA operators (crossover and mutation) were utilized and tested for their effectiveness. The results show that the proposed method can efficiently converge to the optimal solution on a small network but computation time increases significantly with network size. The method can also be used for other transport operation management problems.

  10. 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

  11. Global motions exhibited by proteins in micro- to milliseconds simulations concur with anisotropic network model predictions

    Science.gov (United States)

    Gur, M.; Zomot, E.; Bahar, I.

    2013-09-01

    The Anton supercomputing technology recently developed for efficient molecular dynamics simulations permits us to examine micro- to milli-second events at full atomic resolution for proteins in explicit water and lipid bilayer. It also permits us to investigate to what extent the collective motions predicted by network models (that have found broad use in molecular biophysics) agree with those exhibited by full-atomic long simulations. The present study focuses on Anton trajectories generated for two systems: the bovine pancreatic trypsin inhibitor, and an archaeal aspartate transporter, GltPh. The former, a thoroughly studied system, helps benchmark the method of comparative analysis, and the latter provides new insights into the mechanism of function of glutamate transporters. The principal modes of motion derived from both simulations closely overlap with those predicted for each system by the anisotropic network model (ANM). Notably, the ANM modes define the collective mechanisms, or the pathways on conformational energy landscape, that underlie the passage between the crystal structure and substates visited in simulations. In particular, the lowest frequency ANM modes facilitate the conversion between the most probable substates, lending support to the view that easy access to functional substates is a robust determinant of evolutionarily selected native contact topology.

  12. A network-based system of simulation, control and online assistance for HTR-10

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Shutang [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)], E-mail: zhust@tsinghua.edu.cn; Luo Shaojie; Shi Lei [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)

    2008-07-15

    A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design.

  13. A network-based system of simulation, control and online assistance for HTR-10

    International Nuclear Information System (INIS)

    Zhu Shutang; Luo Shaojie; Shi Lei

    2008-01-01

    A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design

  14. 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.

  15. Design and simulation of a nanoelectronic DG MOSFET current source using artificial neural networks

    International Nuclear Information System (INIS)

    Djeffal, F.; Dibi, Z.; Hafiane, M.L.; Arar, D.

    2007-01-01

    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 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

  16. Simulation of an image network in a medical image information system

    International Nuclear Information System (INIS)

    Massar, A.D.A.; De Valk, J.P.J.; Reijns, G.L.; Bakker, A.R.

    1985-01-01

    The desirability of an integrated (digital) communication system for medical images is widely accepted. In the USA and in Europe several experimental projects are in progress to realize (a part of) such a system. Among these is the IMAGIS project in the Netherlands. From the conclusions of the preliminary studies performed, some requirements can be formulated such a system should meet in order to be accepted by its users. For example, the storage resolution of the images should match the maximum resolution of the presently acquired digital images. This determines the amount of data and therefore the storage requirements. Further, the desired images should be there when needed. This time constraint determines the speed requirements to be imposed on the system. As compared to current standards, very large storage capacities and very fast communication media are needed to meet these requirements. By employing cacheing techniques and suitable data compression schemes for the storage and by carefully choosing the network protocols, bare capacity demands can be alleviated. A communication network is needed to make the imaging system available over a larger area. As the network is very likely to become a major bottleneck for system performance, effects of variation of various attributes have to be carefully studied and analysed. After interesting results had been obtained (although preliminary) using a simulation model for a layered storage structure, it was decided to apply simulation also to this problem. Effects of network topology, access protocols and buffering strategies will be tested. Changes in performance resulting from changes in various network parameters will be studied. Results of this study at its present state are presented

  17. Proposed Development of NASA Glenn Research Center's Aeronautical Network Research Simulator

    Science.gov (United States)

    Nguyen, Thanh C.; Kerczewski, Robert J.; Wargo, Chris A.; Kocin, Michael J.; Garcia, Manuel L.

    2004-01-01

    Accurate knowledge and understanding of data link traffic loads that will have an impact on the underlying communications infrastructure within the National Airspace System (NAS) is of paramount importance for planning, development and fielding of future airborne and ground-based communications systems. Attempting to better understand this impact, NASA Glenn Research Center (GRC), through its contractor Computer Networks & Software, Inc. (CNS, Inc.), has developed an emulation and test facility known as the Virtual Aircraft and Controller (VAC) to study data link interactions and the capacity of the NAS to support Controller Pilot Data Link Communications (CPDLC) traffic. The drawback of the current VAC test bed is that it does not allow the test personnel and researchers to present a real world RF environment to a complex airborne or ground system. Fortunately, the United States Air Force and Navy Avionics Test Commands, through its contractor ViaSat, Inc., have developed the Joint Communications Simulator (JCS) to provide communications band test and simulation capability for the RF spectrum through 18 GHz including Communications, Navigation, and Identification and Surveillance functions. In this paper, we are proposing the development of a new and robust test bed that will leverage on the existing NASA GRC's VAC and the Air Force and Navy Commands JCS systems capabilities and functionalities. The proposed NASA Glenn Research Center's Aeronautical Networks Research Simulator (ANRS) will combine current Air Traffic Control applications and physical RF stimulation into an integrated system capable of emulating data transmission behaviors including propagation delay, physical protocol delay, transmission failure and channel interference. The ANRS will provide a simulation/stimulation tool and test bed environment that allow the researcher to predict the performance of various aeronautical network protocol standards and their associated waveforms under varying

  18. SIDON: A simulator of radio-frequency networks. Application to WEST ICRF launchers

    Science.gov (United States)

    Helou, Walid; Dumortier, Pierre; Durodié, Frédéric; Goniche, Marc; Hillairet, Julien; Mollard, Patrick; Berger-By, Gilles; Bernard, Jean-Michel; Colas, Laurent; Lombard, Gilles; Maggiora, Riccardo; Magne, Roland; Milanesio, Daniele; Moreau, Didier

    2015-12-01

    SIDON (SImulator of raDiO-frequency Networks) is an in-house developed Radio-Frequency (RF) network solver that has been implemented to cross-validate the design of WEST ICRF launchers and simulate their impedance matching algorithm while considering all mutual couplings and asymmetries. In this paper, the authors illustrate the theory of SIDON as well as results of its calculations. The authors have built time-varying plasma scenarios (a sequence of launchers front-faces L-mode and H-mode Z-matrices), where at each time step (1 millisecond here), SIDON solves the RF network. At the same time, when activated, the impedance matching algorithm controls the matching elements (vacuum capacitors) and thus their corresponding S-matrices. Typically a 1-second pulse requires around 10 seconds of computational time on a desktop computer. These tasks can be hardly handled by commercial RF software. This innovative work allows identifying strategies for the launchers future operation while insuring the limitations on the currents, voltages and electric fields, matching and Load-Resilience, as well as the required straps voltage amplitude/phase balance. In this paper, a particular attention is paid to the simulation of the launchers behavior when arcs appear at several locations of their circuits using SIDON calculator. This latter work shall confirm or identify strategies for the arc detection using various RF electrical signals. One shall note that the use of such solvers in not limited to ICRF launchers simulations but can be employed, in principle, to any linear or linearized RF problem.

  19. Combining neural networks and signed particles to simulate quantum systems more efficiently

    Science.gov (United States)

    Sellier, Jean Michel

    2018-04-01

    Recently a new formulation of quantum mechanics has been suggested which describes systems by means of ensembles of classical particles provided with a sign. This novel approach mainly consists of two steps: the computation of the Wigner kernel, a multi-dimensional function describing the effects of the potential over the system, and the field-less evolution of the particles which eventually create new signed particles in the process. Although this method has proved to be extremely advantageous in terms of computational resources - as a matter of fact it is able to simulate in a time-dependent fashion many-body systems on relatively small machines - the Wigner kernel can represent the bottleneck of simulations of certain systems. Moreover, storing the kernel can be another issue as the amount of memory needed is cursed by the dimensionality of the system. In this work, we introduce a new technique which drastically reduces the computation time and memory requirement to simulate time-dependent quantum systems which is based on the use of an appropriately tailored neural network combined with the signed particle formalism. In particular, the suggested neural network is able to compute efficiently and reliably the Wigner kernel without any training as its entire set of weights and biases is specified by analytical formulas. As a consequence, the amount of memory for quantum simulations radically drops since the kernel does not need to be stored anymore as it is now computed by the neural network itself, only on the cells of the (discretized) phase-space which are occupied by particles. As its is clearly shown in the final part of this paper, not only this novel approach drastically reduces the computational time, it also remains accurate. The author believes this work opens the way towards effective design of quantum devices, with incredible practical implications.

  20. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com [Centre of Preparatory and General Studies, TATI University College, 24000 Kemaman, Terengganu, Malaysia and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Yusof, Fadhilah, E-mail: fadhilahy@utm.my [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Daud, Zalina Mohd, E-mail: zalina@ic.utm.my [UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia); Yusop, Zulkifli, E-mail: zulyusop@utm.my [Institute of Environmental and Water Resource Management (IPASA), Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Kasno, Mohammad Afif, E-mail: mafifkasno@gmail.com [Malaysia - Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia)

    2015-02-03

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.

  1. 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.

  2. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    International Nuclear Information System (INIS)

    Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif

    2015-01-01

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system

  3. 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.

  4. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    Science.gov (United States)

    Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif

    2015-02-01

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.

  5. 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.

  6. Supervisory control of mobile sensor networks: math formulation, simulation, and implementation.

    Science.gov (United States)

    Giordano, Vincenzo; Ballal, Prasanna; Lewis, Frank; Turchiano, Biagio; Zhang, Jing Bing

    2006-08-01

    This paper uses a novel discrete-event controller (DEC) for the coordination of cooperating heterogeneous wireless sensor networks (WSNs) containing both unattended ground sensors (UGSs) and mobile sensor robots. The DEC sequences the most suitable tasks for each agent and assigns sensor resources according to the current perception of the environment. A matrix formulation makes this DEC particularly useful for WSN, where missions change and sensor agents may be added or may fail. WSN have peculiarities that complicate their supervisory control. Therefore, this paper introduces several new tools for DEC design and operation, including methods for generating the required supervisory matrices based on mission planning, methods for modifying the matrices in the event of failed nodes, or nodes entering the network, and a novel dynamic priority assignment weighting approach for selecting the most appropriate and useful sensors for a given mission task. The resulting DEC represents a complete dynamical description of the WSN system, which allows a fast programming of deployable WSN, a computer simulation analysis, and an efficient implementation. The DEC is actually implemented on an experimental wireless-sensor-network prototyping system. Both simulation and experimental results are presented to show the effectiveness and versatility of the developed control architecture.

  7. 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.

  8. Simulation of emergency response operations for a static chemical spill within a building using an opportunistic resource utilization network

    NARCIS (Netherlands)

    Lilien, L.T.; Elbes, M.W.; Ben Othmane, L.; Salih, R.M.

    2013-01-01

    We investigate supporting emergency response operations with opportunistic resource utilization networks ("oppnets"), based on a network paradigm for inviting and integrating diverse devices and systems available in the environment. We simulate chemical spill on a single floor of a building and

  9. A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran

    International Nuclear Information System (INIS)

    Azadeh, A.; Ghaderi, S.F.; Sohrabkhani, S.

    2008-01-01

    This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on artificial neural network (ANN), computer simulation and design of experiments using stochastic procedures. First, an ANN approach is illustrated based on supervised multi-layer perceptron (MLP) network for the electrical consumption forecasting. The chosen model, therefore, can be compared to that of estimated by time series model. Computer simulation is developed to generate random variables for monthly electricity consumption. This is achieved to foresee the effects of probabilistic distribution on monthly electricity consumption. The simulated-based ANN model is then developed. Therefore, there are four treatments to be considered in analysis of variance (ANOVA), which are actual data, time series, ANN and simulated-based ANN. Furthermore, ANOVA is used to test the null hypothesis of the above four alternatives being statistically equal. If the null hypothesis is accepted, then the lowest mean absolute percentage error (MAPE) value is used to select the best model, otherwise the Duncan method (DMRT) of paired comparison is used to select the optimum model which could be time series, ANN or simulated-based ANN. In case of ties the lowest MAPE value is considered as the benchmark. The integrated algorithm has several unique features. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the best fitted ANN model based on MAPE or relative error results. Second, the proposed algorithm may identify conventional time series as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that ANN always provide the best solutions and estimation. To show the applicability and superiority of the proposed algorithm, the monthly electricity consumption in Iran from March 1994 to February 2005 (131 months) is used and applied to

  10. Uncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations

    Science.gov (United States)

    Niemeier, Wolfgang; Tengen, Dieter

    2017-06-01

    In this article first ideas are presented to extend the classical concept of geodetic network adjustment by introducing a new method for uncertainty assessment as two-step analysis. In the first step the raw data and possible influencing factors are analyzed using uncertainty modeling according to GUM (Guidelines to the Expression of Uncertainty in Measurements). This approach is well established in metrology, but rarely adapted within Geodesy. The second step consists of Monte-Carlo-Simulations (MC-simulations) for the complete processing chain from raw input data and pre-processing to adjustment computations and quality assessment. To perform these simulations, possible realizations of raw data and the influencing factors are generated, using probability distributions for all variables and the established concept of pseudo-random number generators. Final result is a point cloud which represents the uncertainty of the estimated coordinates; a confidence region can be assigned to these point clouds, as well. This concept may replace the common concept of variance propagation and the quality assessment of adjustment parameters by using their covariance matrix. It allows a new way for uncertainty assessment in accordance with the GUM concept for uncertainty modelling and propagation. As practical example the local tie network in "Metsähovi Fundamental Station", Finland is used, where classical geodetic observations are combined with GNSS data.

  11. Direct numerical simulation of cellular-scale blood flow in microvascular networks

    Science.gov (United States)

    Balogh, Peter; Bagchi, Prosenjit

    2017-11-01

    A direct numerical simulation method is developed to study cellular-scale blood flow in physiologically realistic microvascular networks that are constructed in silico following published in vivo images and data, and are comprised of bifurcating, merging, and winding vessels. The model resolves large deformation of individual red blood cells (RBC) flowing in such complex networks. The vascular walls and deformable interfaces of the RBCs are modeled using the immersed-boundary methods. Time-averaged hemodynamic quantities obtained from the simulations agree quite well with published in vivo data. Our simulations reveal that in several vessels the flow rates and pressure drops could be negatively correlated. The flow resistance and hematocrit are also found to be negatively correlated in some vessels. These observations suggest a deviation from the classical Poiseuille's law in such vessels. The cells are observed to frequently jam at vascular bifurcations resulting in reductions in hematocrit and flow rate in the daughter and mother vessels. We find that RBC jamming results in several orders of magnitude increase in hemodynamic resistance, and thus provides an additional mechanism of increased in vivo blood viscosity as compared to that determined in vitro. Funded by NSF CBET 1604308.

  12. An electronic system for simulation of neural networks with a micro-second real time constraint

    International Nuclear Information System (INIS)

    Chorti, Arsenia; Granado, Bertrand; Denby, Bruce; Garda, Patrick

    2001-01-01

    Neural networks implemented in hardware can perform pattern recognition very quickly, and as such have been used to advantage in the triggering systems of certain high energy physics experiments. Typically, time constants of the order of a few microseconds are required. In this paper, we present a new system. MAHARADJA, for evaluating MLP and RBF neural network paradigms in real time. The system is tested on a possible ATLAS muon triggering application suggested by the Tel Aviv ATLAS group, consisting of a 4-8-8-4 MLP which must be evaluated in 10 microseconds. The inputs to the net are dx/dz, x(z=0), dy/dz, and y(z=0), whereas the outputs give pt, tan(phi), sin(theta), and q, the charge. With a 10 MHz clock, MAHARADJA calculates the result in 6.8 microseconds; at 20 MHz, which is readily attainable, this would be reduced to only 3.4 microseconds. The system can also handle RBF networks with 3 different distance metrics (Euclidean, Manhattan and Mahalanobis), and can simulate any MLP of 10 hidden layers or less. The electronic implementation is with FPGA's, which can be optimized for a specific neural network because the number of processing elements can be modified

  13. An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

    Science.gov (United States)

    Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

    2017-01-01

    In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

  14. Timetable-based simulation method for choice set generation in large-scale public transport networks

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Kjær; Anderson, Marie Karen; Nielsen, Otto Anker

    2016-01-01

    The composition and size of the choice sets are a key for the correct estimation of and prediction by route choice models. While existing literature has posed a great deal of attention towards the generation of path choice sets for private transport problems, the same does not apply to public...... transport problems. This study proposes a timetable-based simulation method for generating path choice sets in a multimodal public transport network. Moreover, this study illustrates the feasibility of its implementation by applying the method to reproduce 5131 real-life trips in the Greater Copenhagen Area...... and to assess the choice set quality in a complex multimodal transport network. Results illustrate the applicability of the algorithm and the relevance of the utility specification chosen for the reproduction of real-life path choices. Moreover, results show that the level of stochasticity used in choice set...

  15. Decoherence and Entanglement Simulation in a Model of Quantum Neural Network Based on Quantum Dots

    Directory of Open Access Journals (Sweden)

    Altaisky Mikhail V.

    2016-01-01

    Full Text Available We present the results of the simulation of a quantum neural network based on quantum dots using numerical method of path integral calculation. In the proposed implementation of the quantum neural network using an array of single-electron quantum dots with dipole-dipole interaction, the coherence is shown to survive up to 0.1 nanosecond in time and up to the liquid nitrogen temperature of 77K.We study the quantum correlations between the quantum dots by means of calculation of the entanglement of formation in a pair of quantum dots on the GaAs based substrate with dot size of 100 ÷ 101 nanometer and interdot distance of 101 ÷ 102 nanometers order.

  16. Flash and Continuous Photolysis Studies of the Thionitrosyl Complex Cr(CH3CN)5(NS)2+ and the Nitric Oxide Analogs. Reactions of Nitrogen Monosulfide in Solution

    DEFF Research Database (Denmark)

    Dethlefsen, Johannes Wied; Hedegård, Erik; Rimmer, R. Dale

    2009-01-01

    Photolysis of the thionitrosyl complex Cr(CH3CN)5(NS)2+ (1) in acetonitrile solution leads to the dissociation of nitrogen monosulfide (NS).  In deaerated solution, this reaction is reversible, and flash photolysis studies demonstrate that NS reacts with Cr(CH3CN)62+ according to the rate law d[1...... dependent quantum yields of 0.3-1.0 mol/Einstein. Mass spectroscopic studies of the product solutions demonstrate formation of S8, presumably from the decomposition of NS. The quantitative photochemical behaviors of 1 and the nitrosyl analog 2 are compared. Udgivelsesdato: Jan....

  17. Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

    Science.gov (United States)

    Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

    2017-02-01

    The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

  18. Simulation of heat exchanger network (HEN) and planning the optimum cleaning schedule

    International Nuclear Information System (INIS)

    Sanaye, Sepehr; Niroomand, Behzad

    2007-01-01

    Modeling and simulation of heat exchanger networks for estimating the amount of fouling, variations in overall heat transfer coefficient, and variations in outlet temperatures of hot and cold streams has a significant effect on production analysis. In this analysis, parameters such as the exchangers' types and arrangements, their heat transfer surface areas, mass flow rates of hot and cold streams, heat transfer coefficients and variations of fouling with time are required input data. The main goal is to find the variations of the outlet temperatures of the hot and cold streams with time to plan the optimum cleaning schedule of heat exchangers that provides the minimum operational cost or maximum amount of savings. In this paper, the simulation of heat exchanger networks is performed by choosing an asymptotic fouling function. Two main parameters in the asymptotic fouling formation model, i.e. the decay time of fouling formation (τ) and the asymptotic fouling resistance (R f ∼ ) were obtained from empirical data as input parameters to the simulation relations. These data were extracted from the technical history sheets of the Khorasan Petrochemical Plant to guaranty the consistency between our model outputs and the real operating conditions. The output results of the software program developed, including the variations with time of the outlet temperatures of the hot and cold streams, the heat transfer coefficient and the heat transfer rate in the exchangers, are presented for two case studies. Then, an objective function (operational cost) was defined, and the optimal cleaning schedule of the HEN (heat exchanger network) in the Urea and Ammonia units were found by minimizing the objective function using a numerical search method. Based on this minimization procedure, the decision was made whether a heat exchanger should be cleaned or continue to operate. The final result was the most cost effective plan for the HEN cleaning schedule. The corresponding savings by

  19. Simulation of heat exchanger network (HEN) and planning the optimum cleaning schedule

    Energy Technology Data Exchange (ETDEWEB)

    Sanaye, Sepehr [Energy Systems Improvement Laboratory, Mechanical Engineering Department, Iran University of Science and Technology (IUST), Narmak, Tehran 16488 (Iran, Islamic Republic of)]. E-mail: sepehr@iust.ac.ir; Niroomand, Behzad [Energy Systems Improvement Laboratory, Mechanical Engineering Department, Iran University of Science and Technology (IUST), Narmak, Tehran 16488 (Iran, Islamic Republic of)

    2007-05-15

    Modeling and simulation of heat exchanger networks for estimating the amount of fouling, variations in overall heat transfer coefficient, and variations in outlet temperatures of hot and cold streams has a significant effect on production analysis. In this analysis, parameters such as the exchangers' types and arrangements, their heat transfer surface areas, mass flow rates of hot and cold streams, heat transfer coefficients and variations of fouling with time are required input data. The main goal is to find the variations of the outlet temperatures of the hot and cold streams with time to plan the optimum cleaning schedule of heat exchangers that provides the minimum operational cost or maximum amount of savings. In this paper, the simulation of heat exchanger networks is performed by choosing an asymptotic fouling function. Two main parameters in the asymptotic fouling formation model, i.e. the decay time of fouling formation ({tau}) and the asymptotic fouling resistance (R{sub f}{sup {approx}}) were obtained from empirical data as input parameters to the simulation relations. These data were extracted from the technical history sheets of the Khorasan Petrochemical Plant to guaranty the consistency between our model outputs and the real operating conditions. The output results of the software program developed, including the variations with time of the outlet temperatures of the hot and cold streams, the heat transfer coefficient and the heat transfer rate in the exchangers, are presented for two case studies. Then, an objective function (operational cost) was defined, and the optimal cleaning schedule of the HEN (heat exchanger network) in the Urea and Ammonia units were found by minimizing the objective function using a numerical search method. Based on this minimization procedure, the decision was made whether a heat exchanger should be cleaned or continue to operate. The final result was the most cost effective plan for the HEN cleaning schedule. The

  20. Earth-Mars Telecommunications and Information Management System (TIMS): Antenna Visibility Determination, Network Simulation, and Management Models

    Science.gov (United States)

    Odubiyi, Jide; Kocur, David; Pino, Nino; Chu, Don

    1996-01-01

    This report presents the results of our research on Earth-Mars Telecommunications and Information Management System (TIMS) network modeling and unattended network operations. The primary focus of our research is to investigate the feasibility of the TIMS architecture, which links the Earth-based Mars Operations Control Center, Science Data Processing Facility, Mars Network Management Center, and the Deep Space Network of antennae to the relay satellites and other communication network elements based in the Mars region. The investigation was enhanced by developing Build 3 of the TIMS network modeling and simulation model. The results of several 'what-if' scenarios are reported along with reports on upgraded antenna visibility determination software and unattended network management prototype.

  1. Molecular dynamics simulations of disordered materials from network glasses to phase-change memory alloys

    CERN Document Server

    Massobrio, Carlo; Bernasconi, Marco; Salmon, Philip S

    2015-01-01

    This book is a unique reference work in the area of atomic-scale simulation of glasses. For the first time, a highly selected panel of about 20 researchers provides, in a single book, their views, methodologies and applications on the use of molecular dynamics as a tool to describe glassy materials. The book covers a wide range of systems covering ""traditional"" network glasses, such as chalcogenides and oxides, as well as glasses for applications in the area of phase change materials. The novelty of this work is the interplay between molecular dynamics methods (both at the classical and firs

  2. Generalized Fluid System Simulation Program (GFSSP) Version 6 - General Purpose Thermo-Fluid Network Analysis Software

    Science.gov (United States)

    Majumdar, Alok; Leclair, Andre; Moore, Ric; Schallhorn, Paul

    2011-01-01

    GFSSP stands for Generalized Fluid System Simulation Program. It is a general-purpose computer program to compute pressure, temperature and flow distribution in a flow network. GFSSP calculates pressure, temperature, and concentrations at nodes and calculates flow rates through branches. It was primarily developed to analyze Internal Flow Analysis of a Turbopump Transient Flow Analysis of a Propulsion System. GFSSP development started in 1994 with an objective to provide a generalized and easy to use flow analysis tool for thermo-fluid systems.

  3. Binary Factorization in Hopfield-Like Neural Networks: Single-Step Approximation and Computer Simulations

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Sirota, A.M.; Húsek, Dušan; Muraviev, I. P.

    2004-01-01

    Roč. 14, č. 2 (2004), s. 139-152 ISSN 1210-0552 R&D Projects: GA ČR GA201/01/1192 Grant - others:BARRANDE(EU) 99010-2/99053; Intellectual computer Systems(EU) Grant 2.45 Institutional research plan: CEZ:AV0Z1030915 Keywords : nonlinear binary factor analysis * feature extraction * recurrent neural network * Single-Step approximation * neurodynamics simulation * attraction basins * Hebbian learning * unsupervised learning * neuroscience * brain function modeling Subject RIV: BA - General Mathematics

  4. Use of neural networks in process engineering. Thermodynamics, diffusion, and process control and simulation applications

    International Nuclear Information System (INIS)

    Otero, F

    1998-01-01

    This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control

  5. Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

    Science.gov (United States)

    Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

    2015-01-01

    BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  6. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    Science.gov (United States)

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

  7. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    Directory of Open Access Journals (Sweden)

    Xerxes D. Arsiwalla

    2015-02-01

    Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  8. Simulation Network for Test and Evaluation of Defense Systems. Phase I. Survey of DoD Testbed Requirements,

    Science.gov (United States)

    1983-05-15

    Interconnection (ISO 051) is the model used as a guide for this introduction to network protocols [30] T. Utsumi, " GLOSAS Project (GLObal Systems...Analysis and Simulation)," Proceedings of the 1980 Winter Simulation * Conference, Orlando, Fl., December, 1980, pp. 165-217. GLOSAS Project proposes the

  9. An effective fractal-tree closure model for simulating blood flow in large arterial networks.

    Science.gov (United States)

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

    2015-06-01

    The aim of the present work is to address the closure problem for hemodynamic simulations by developing a flexible and effective model that accurately distributes flow in the downstream vasculature and can stably provide a physiological pressure outflow boundary condition. To achieve this goal, we model blood flow in the sub-pixel vasculature by using a non-linear 1D model in self-similar networks of compliant arteries that mimic the structure and hierarchy of vessels in the meso-vascular regime (radii [Formula: see text]). We introduce a variable vessel length-to-radius ratio for small arteries and arterioles, while also addressing non-Newtonian blood rheology and arterial wall viscoelasticity effects in small arteries and arterioles. This methodology aims to overcome substantial cut-off radius sensitivities, typically arising in structured tree and linearized impedance models. The proposed model is not sensitive to outflow boundary conditions applied at the end points of the fractal network, and thus does not require calibration of resistance/capacitance parameters typically required for outflow conditions. The proposed model convergences to a periodic state in two cardiac cycles even when started from zero-flow initial conditions. The resulting fractal-trees typically consist of thousands to millions of arteries, posing the need for efficient parallel algorithms. To this end, we have scaled up a Discontinuous Galerkin solver that utilizes the MPI/OpenMP hybrid programming paradigm to thousands of computer cores, and can simulate blood flow in networks of millions of arterial segments at the rate of one cycle per 5 min. The proposed model has been extensively tested on a large and complex cranial network with 50 parent, patient-specific arteries and 21 outlets to which fractal trees where attached, resulting to a network of up to 4,392,484 vessels in total, and a detailed network of the arm with 276 parent arteries and 103 outlets (a total of 702,188 vessels

  10. Dynamical properties of fractal networks: Scaling, numerical simulations, and physical realizations

    International Nuclear Information System (INIS)

    Nakayama, T.; Yakubo, K.; Orbach, R.L.

    1994-01-01

    This article describes the advances that have been made over the past ten years on the problem of fracton excitations in fractal structures. The relevant systems to this subject are so numerous that focus is limited to a specific structure, the percolating network. Recent progress has followed three directions: scaling, numerical simulations, and experiment. In a happy coincidence, large-scale computations, especially those involving array processors, have become possible in recent years. Experimental techniques such as light- and neutron-scattering experiments have also been developed. Together, they form the basis for a review article useful as a guide to understanding these developments and for charting future research directions. In addition, new numerical simulation results for the dynamical properties of diluted antiferromagnets are presented and interpreted in terms of scaling arguments. The authors hope this article will bring the major advances and future issues facing this field into clearer focus, and will stimulate further research on the dynamical properties of random systems

  11. THERMODYNAMIC ANALYSIS AND SIMULATION OF A NEW COMBINED POWER AND REFRIGERATION CYCLE USING ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Hossein Rezvantalab

    2011-01-01

    Full Text Available In this study, a new combined power and refrigeration cycle is proposed, which combines the Rankine and absorption refrigeration cycles. Using a binary ammonia-water mixture as the working fluid, this combined cycle produces both power and refrigeration output simultaneously by employing only one external heat source. In order to achieve the highest possible exergy efficiency, a secondary turbine is inserted to expand the hot weak solution leaving the boiler. Moreover, an artificial neural network (ANN is used to simulate the thermodynamic properties and the relationship between the input thermodynamic variables on the cycle performance. It is shown that turbine inlet pressure, as well as heat source and refrigeration temperatures have significant effects on the net power output, refrigeration output and exergy efficiency of the combined cycle. In addition, the results of ANN are in excellent agreement with the mathematical simulation and cover a wider range for evaluation of cycle performance.

  12. Development of Tools for Simulation Systems in a Distribution Network and Validated by Measurements

    DEFF Research Database (Denmark)

    Mihet-Popa, Lucian; Koch-Ciobotaru, C.; Isleifsson, Fridrik Rafn

    2012-01-01

    The increasing amount of DER components into distribution networks involves the development of accurate simulation models that take into account an increasing number of factors that influence the output power from the DG systems. This paper presents two simulation models: a PV panel model using....../Simulink, has also been developed and implemented in PowerFactory to study load flow, steadystate voltage stability and dynamic behavior of a distribution power system....... the single-diode four-parameter model based on data sheet values and a VRB system model based on the efficiency of different components and the power losses. The models were implemented first in MATLAB/Simulink and the results have been compared with the data sheet values and with the characteristics...

  13. The analysis of transient noise of PCB P/G network based on PI/SI co-simulation

    Science.gov (United States)

    Haohang, Su

    2018-02-01

    With the frequency of the space camera become higher than before, the power noise of the imaging electronic system become the important factor. Much more power noise would disturb the transmissions signal, and even influence the image sharpness and system noise. "Target impedance method" is one of the traditional design method of P/G network (power and ground network), which is shorted of transient power noise analysis and often made "over design". In this paper, a new design method of P/G network is provided which simulated by PI/SI co-simulation. The transient power noise can be simulated and then applied in the design of noise reduction, thus effectively controlling the change of the noise in the P/G network. The method can efficiently control the number of adding decoupling capacitor, and is very efficient and feasible to keep the power integrity.

  14. 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.

  15. ABS-TrustSDN: An Agent-Based Simulator of Trust Strategies in Software-Defined Networks

    Directory of Open Access Journals (Sweden)

    Iván García-Magariño

    2017-01-01

    Full Text Available Software-defined networks (SDNs have become a mechanism to separate the control plane and the data plane in the communication in networks. SDNs involve several challenges around their security and their confidentiality. Ideally, SDNs should incorporate autonomous and adaptive systems for controlling the routing to be able to isolate network resources that may be malfunctioning or whose security has been compromised with malware. The current work introduces a novel agent-based framework that simulates SDN isolation protocols by means of trust and reputation models. This way, SDN programmers may estimate the repercussions of certain isolation protocols based on trust models before actually deploying the protocol into the network.

  16. Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

    Energy Technology Data Exchange (ETDEWEB)

    Brown, D L

    2009-05-01

    Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex

  17. Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

    International Nuclear Information System (INIS)

    Brown, D.L.

    2009-01-01

    Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex networked systems

  18. Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS

    Directory of Open Access Journals (Sweden)

    Philipp Weidel

    2016-08-01

    Full Text Available In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS to the Multi-Simulator Coordinator (MUSIC. This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning.

  19. Dynamic Simulation of Water Networks to Control and Reduce Physical Unaccounted-for Water

    Directory of Open Access Journals (Sweden)

    Nima Zorriasateyn

    2005-09-01

    Full Text Available A significant percentage of unaccounted-for water consists of leakage in water distribution networks in Iran. To detect leakage area with less costs and time spending and then identify the exact  place of it with special instruments, would be economical and a better water resource management. In this research, a real case has been selected and examined with dynamic simulation using MIKE NET. The method that has been carried out in this research based on maximizing the correlation coefficient and minimizing the sum of error squares between pressure measured inputs (observed data and calculated pressure (by model. According to the results, dynamic simulation of municipal water distribution system can be used as a guide to determine the place and the amount of leakage.Thereby the area of  large leakage can be simulated with appropriate accuracy through measured pressure. Therefor from management aspect, dynamic simulation can be used to decrease time consumption and to save costs for detecting leakage.

  20. Integrating atomistic molecular dynamics simulations, experiments and network analysis to study protein dynamics: strength in unity

    Directory of Open Access Journals (Sweden)

    Elena ePapaleo

    2015-05-01

    Full Text Available In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties 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 their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular 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.

  1. Simulating GPS radio signal to synchronize network--a new technique for redundant timing.

    Science.gov (United States)

    Shan, Qingxiao; Jun, Yang; Le Floch, Jean-Michel; Fan, Yaohui; Ivanov, Eugene N; Tobar, Michael E

    2014-07-01

    Currently, many distributed systems such as 3G mobile communications and power systems are time synchronized with a Global Positioning System (GPS) signal. If there is a GPS failure, it is difficult to realize redundant timing, and thus time-synchronized devices may fail. In this work, we develop time transfer by simulating GPS signals, which promises no extra modification to original GPS-synchronized devices. This is achieved by applying a simplified GPS simulator for synchronization purposes only. Navigation data are calculated based on a pre-assigned time at a fixed position. Pseudo-range data which describes the distance change between the space vehicle (SV) and users are calculated. Because real-time simulation requires heavy-duty computations, we use self-developed software optimized on a PC to generate data, and save the data onto memory disks while the simulator is operating. The radio signal generation is similar to the SV at an initial position, and the frequency synthesis of the simulator is locked to a pre-assigned time. A filtering group technique is used to simulate the signal transmission delay corresponding to the SV displacement. Each SV generates a digital baseband signal, where a unique identifying code is added to the signal and up-converted to generate the output radio signal at the centered frequency of 1575.42 MHz (L1 band). A prototype with a field-programmable gate array (FPGA) has been built and experiments have been conducted to prove that we can realize time transfer. The prototype has been applied to the CDMA network for a three-month long experiment. Its precision has been verified and can meet the requirements of most telecommunication systems.

  2. A Multilevel Adaptive Reaction-splitting Simulation Method for Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro; Tempone, Raul; Vilanova, Pedro

    2016-01-01

    In this work, we present a novel multilevel Monte Carlo method for kinetic simulation of stochastic reaction networks characterized by having simultaneously fast and slow reaction channels. To produce efficient simulations, our method adaptively classifies the reactions channels into fast and slow channels. To this end, we first introduce a state-dependent quantity named level of activity of a reaction channel. Then, we propose a low-cost heuristic that allows us to adaptively split the set of reaction channels into two subsets characterized by either a high or a low level of activity. Based on a time-splitting technique, the increments associated with high-activity channels are simulated using the tau-leap method, while those associated with low-activity channels are simulated using an exact method. This path simulation technique is amenable for coupled path generation and a corresponding multilevel Monte Carlo algorithm. To estimate expected values of observables of the system at a prescribed final time, our method bounds the global computational error to be below a prescribed tolerance, TOL, within a given confidence level. This goal is achieved with a computational complexity of order O(TOL-2), the same as with a pathwise-exact method, but with a smaller constant. We also present a novel low-cost control variate technique based on the stochastic time change representation by Kurtz, showing its performance on a numerical example. We present two numerical examples extracted from the literature that show how the reaction-splitting method obtains substantial gains with respect to the standard stochastic simulation algorithm and the multilevel Monte Carlo approach by Anderson and Higham. © 2016 Society for Industrial and Applied Mathematics.

  3. A Multilevel Adaptive Reaction-splitting Simulation Method for Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro

    2016-07-07

    In this work, we present a novel multilevel Monte Carlo method for kinetic simulation of stochastic reaction networks characterized by having simultaneously fast and slow reaction channels. To produce efficient simulations, our method adaptively classifies the reactions channels into fast and slow channels. To this end, we first introduce a state-dependent quantity named level of activity of a reaction channel. Then, we propose a low-cost heuristic that allows us to adaptively split the set of reaction channels into two subsets characterized by either a high or a low level of activity. Based on a time-splitting technique, the increments associated with high-activity channels are simulated using the tau-leap method, while those associated with low-activity channels are simulated using an exact method. This path simulation technique is amenable for coupled path generation and a corresponding multilevel Monte Carlo algorithm. To estimate expected values of observables of the system at a prescribed final time, our method bounds the global computational error to be below a prescribed tolerance, TOL, within a given confidence level. This goal is achieved with a computational complexity of order O(TOL-2), the same as with a pathwise-exact method, but with a smaller constant. We also present a novel low-cost control variate technique based on the stochastic time change representation by Kurtz, showing its performance on a numerical example. We present two numerical examples extracted from the literature that show how the reaction-splitting method obtains substantial gains with respect to the standard stochastic simulation algorithm and the multilevel Monte Carlo approach by Anderson and Higham. © 2016 Society for Industrial and Applied Mathematics.

  4. Package Equivalent Reactor Networks as Reduced Order Models for Use with CAPE-OPEN Compliant Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Meeks, E.; Chou, C. -P.; Garratt, T.

    2013-03-31

    Engineering simulations of coal gasifiers are typically performed using computational fluid dynamics (CFD) software, where a 3-D representation of the gasifier equipment is used to model the fluid flow in the gasifier and source terms from the coal gasification process are captured using discrete-phase model source terms. Simulations using this approach can be very time consuming, making it difficult to imbed such models into overall system simulations for plant design and optimization. For such system-level designs, process flowsheet software is typically used, such as Aspen Plus® [1], where each component where each component is modeled using a reduced-order model. For advanced power-generation systems, such as integrated gasifier/gas-turbine combined-cycle systems (IGCC), the critical components determining overall process efficiency and emissions are usually the gasifier and combustor. Providing more accurate and more computationally efficient reduced-order models for these components, then, enables much more effective plant-level design optimization and design for control. Based on the CHEMKIN-PRO and ENERGICO software, we have developed an automated methodology for generating an advanced form of reduced-order model for gasifiers and combustors. The reducedorder model offers representation of key unit operations in flowsheet simulations, while allowing simulation that is fast enough to be used in iterative flowsheet calculations. Using high-fidelity fluiddynamics models as input, Reaction Design’s ENERGICO® [2] software can automatically extract equivalent reactor networks (ERNs) from a CFD solution. For the advanced reduced-order concept, we introduce into the ERN a much more detailed kinetics model than can be included practically in the CFD simulation. The state-of-the-art chemistry solver technology within CHEMKIN-PRO allows that to be accomplished while still maintaining a very fast model turn-around time. In this way, the ERN becomes the basis for

  5. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    OpenAIRE

    Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  6. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    OpenAIRE

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  7. Social Networks and Smoking: Exploring the Effects of Influence and Smoker Popularity through Simulations

    Science.gov (United States)

    Schaefer, David R.; adams, jimi; Haas, Steven A.

    2015-01-01

    Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw upon recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention strategies targeted toward micro-level processes. Our approach begins by estimating a stochastic actor-based model using data from one school in the National Longitudinal Study of Adolescent Health. The model provides estimates of several factors predicting friendship ties and smoking behavior. We then use estimated model parameters to simulate the co-evolution of friendship and smoking behavior under potential intervention scenarios. Namely, we manipulate the strength of peer influence on smoking and the popularity of smokers relative to nonsmokers. We measure how these manipulations affect smoking prevalence, smoking initiation, and smoking cessation. Results indicate that both peer influence and smoking-based popularity affect smoking behavior, and that their joint effects are nonlinear. This study demonstrates how a simulation-based approach can be used to explore alternative scenarios that may be achievable through intervention efforts and offers new hypotheses about the association between friendship and smoking. PMID:24084397

  8. Social networks and smoking: exploring the effects of peer influence and smoker popularity through simulations.

    Science.gov (United States)

    Schaefer, David R; Adams, Jimi; Haas, Steven A

    2013-10-01

    Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw on recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention strategies targeted toward micro-level processes. Our approach begins by estimating a stochastic actor-based model using data from one school in the National Longitudinal Study of Adolescent Health. The model provides estimates of several factors predicting friendship ties and smoking behavior. We then use estimated model parameters to simulate the coevolution of friendship and smoking behavior under potential intervention scenarios. Namely, we manipulate the strength of peer influence on smoking and the popularity of smokers relative to nonsmokers. We measure how these manipulations affect smoking prevalence, smoking initiation, and smoking cessation. Results indicate that both peer influence and smoking-based popularity affect smoking behavior and that their joint effects are nonlinear. This study demonstrates how a simulation-based approach can be used to explore alternative scenarios that may be achievable through intervention efforts and offers new hypotheses about the association between friendship and smoking.

  9. Achieving Fair Throughput among TCP Flows in Multi-Hop Wireless Mesh Networks

    Science.gov (United States)

    Hou, Ting-Chao; Hsu, Chih-Wei

    Previous research shows that the IEEE 802.11 DCF channel contention mechanism is not capable of providing throughput fairness among nodes in different locations of the wireless mesh network. The node nearest the gateway will always strive for the chance to transmit data, causing fewer transmission opportunities for the nodes farther from the gateway, resulting in starvation. Prior studies modify the DCF mechanism to address the fairness problem. This paper focuses on the fairness study when TCP flows are carried over wireless mesh networks. By not modifying lower layer protocols, the current work identifies TCP parameters that impact throughput fairness and proposes adjusting those parameters to reduce frame collisions and improve throughput fairness. With the aid of mathematical formulation and ns2 simulations, this study finds that frame transmission from each node can be effectively controlled by properly controlling the delayed ACK timer and using a suitable advertised window. The proposed method reduces frame collisions and greatly improves TCP throughput fairness.

  10. PERFORMANCE EVALUATION OF INTEGRATED MACRO AND MICRO MOBILITY PROTOCOLS FOR WIDE AREA WIRELESS NETWORKS

    Directory of Open Access Journals (Sweden)

    R.Gunasundari

    2010-03-01

    Full Text Available The success of next generation wireless networks will rely much on advanced mechanisms for seamless mobility support among emerging heterogeneous technologies. Currently, Mobile IP is the most promising solution for mobility management in the Internet. Several IP micro mobility approaches have been proposed to enhance the performance of Mobile IP which supports quality of service, minimum packet loss, limited handoff delay and scalability and power conservation but they are not scalable for macro mobility. A practical solution would therefore require integration of Mobile IP and Micro mobility protocols where Mobile IP handles macro mobility and micro mobility protocols handles micro mobility. In this paper an integrated mobility management protocol for IP based wireless networks is proposed and analyzed. Simulation results presented in this paper are based on ns 2.

  11. Mobile Device Based Dynamic Key Management Protocols for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chin-Ling Chen

    2015-01-01

    Full Text Available In recent years, wireless sensor network (WSN applications have tended to transmit data hop by hop, from sensor nodes through cluster nodes to the base station. As a result, users must collect data from the base station. This study considers two different applications: hop by hop transmission of data from cluster nodes to the base station and the direct access to cluster nodes data by mobile users via mobile devices. Due to the hardware limitations of WSNs, some low-cost operations such as symmetric cryptographic algorithms and hash functions are used to implement a dynamic key management. The session key can be updated to prevent threats of attack from each communication. With these methods, the data gathered in wireless sensor networks can be more securely communicated. Moreover, the proposed scheme is analyzed and compared with related schemes. In addition, an NS2 simulation is developed in which the experimental results show that the designed communication protocol is workable.

  12. Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

    Science.gov (United States)

    Shen, Lin; Yang, Weitao

    2018-03-13

    Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of

  13. A Control Simulation Method of High-Speed Trains on Railway Network with Irregular Influence

    International Nuclear Information System (INIS)

    Yang Lixing; Li Xiang; Li Keping

    2011-01-01

    Based on the discrete time method, an effective movement control model is designed for a group of highspeed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains' movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and rescheduling trains on the rail network. (general)

  14. Emulation of reionization simulations for Bayesian inference of astrophysics parameters using neural networks

    Science.gov (United States)

    Schmit, C. J.; Pritchard, J. R.

    2018-03-01

    Next generation radio experiments such as LOFAR, HERA, and SKA are expected to probe the Epoch of Reionization (EoR) and claim a first direct detection of the cosmic 21cm signal within the next decade. Data volumes will be enormous and can thus potentially revolutionize our understanding of the early Universe and galaxy formation. However, numerical modelling of the EoR can be prohibitively expensive for Bayesian parameter inference and how to optimally extract information from incoming data is currently unclear. Emulation techniques for fast model evaluations have recently been proposed as a way to bypass costly simulations. We consider the use of artificial neural networks as a blind emulation technique. We study the impact of training duration and training set size on the quality of the network prediction and the resulting best-fitting values of a parameter search. A direct comparison is drawn between our emulation technique and an equivalent analysis using 21CMMC. We find good predictive capabilities of our network using training sets of as low as 100 model evaluations, which is within the capabilities of fully numerical radiative transfer codes.

  15. Lattice Boltzmann simulation of immiscible fluid displacement in porous media: Homogeneous versus heterogeneous pore network

    International Nuclear Information System (INIS)

    Liu, Haihu; Zhang, Yonghao; Valocchi, Albert J.

    2015-01-01

    Injection of anthropogenic carbon dioxide (CO 2 ) into geological formations is a promising approach to reduce greenhouse gas emissions into the atmosphere. Predicting the amount of CO 2 that can be captured and its long-term storage stability in subsurface requires a fundamental understanding of multiphase displacement phenomena at the pore scale. In this paper, the lattice Boltzmann method is employed to simulate the immiscible displacement of a wetting fluid by a non-wetting one in two microfluidic flow cells, one with a homogeneous pore network and the other with a randomly heterogeneous pore network. We have identified three different displacement patterns, namely, stable displacement, capillary fingering, and viscous fingering, all of which are strongly dependent upon the capillary number (Ca), viscosity ratio (M), and the media heterogeneity. The non-wetting fluid saturation (S nw ) is found to increase nearly linearly with logCa for each constant M. Increasing M (viscosity ratio of non-wetting fluid to wetting fluid) or decreasing the media heterogeneity can enhance the stability of the displacement process, resulting in an increase in S nw . In either pore networks, the specific interfacial length is linearly proportional to S nw during drainage with equal proportionality constant for all cases excluding those revealing considerable viscous fingering. Our numerical results confirm the previous experimental finding that the steady state specific interfacial length exhibits a linear dependence on S nw for either favorable (M ≥ 1) or unfavorable (M < 1) displacement, and the slope is slightly higher for the unfavorable displacement

  16. Simulation Study on the Application of the Generalized Entropy Concept in Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2018-04-01

    Full Text Available Artificial neural networks are currently one of the most commonly used classifiers and over the recent years they have been successfully used in many practical applications, including banking and finance, health and medicine, engineering and manufacturing. A large number of error functions have been proposed in the literature to achieve a better predictive power. However, only a few works employ Tsallis statistics, although the method itself has been successfully applied in other machine learning techniques. This paper undertakes the effort to examine the q -generalized function based on Tsallis statistics as an alternative error measure in neural networks. In order to validate different performance aspects of the proposed function and to enable identification of its strengths and weaknesses the extensive simulation was prepared based on the artificial benchmarking dataset. The results indicate that Tsallis entropy error function can be successfully introduced in the neural networks yielding satisfactory results and handling with class imbalance, noise in data or use of non-informative predictors.

  17. Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network

    Science.gov (United States)

    Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun

    2016-01-01

    A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0–1 integer programming to describe passengers’ responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated. PMID:27935963

  18. Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network.

    Directory of Open Access Journals (Sweden)

    Haodong Yin

    Full Text Available A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1 A basic passenger behavior optimization model is mathematically constructed based on 0-1 integer programming to describe passengers' responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2 An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1, the impact of the closure can be somewhat mitigated.

  19. Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network.

    Science.gov (United States)

    Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun

    2016-01-01

    A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0-1 integer programming to describe passengers' responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated.

  20. A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks.

    Science.gov (United States)

    Perisic, Ana; Bauch, Chris T

    2009-05-28

    Human behavior influences infectious disease transmission, and numerous "prevalence-behavior" models have analyzed this interplay. These previous analyses assumed homogeneously mixing populations without spatial or social structure. However, spatial and social heterogeneity are known to significantly impact transmission dynamics and are particularly relevant for certain diseases. Previous work has demonstrated that social contact structure can change the individual incentive to vaccinate, thus enabling eradication of a disease under a voluntary vaccination policy when the corresponding homogeneous mixing model predicts that eradication is impossible due to free rider effects. Here, we extend this work and characterize the range of possible behavior-prevalence dynamics on a network. We simulate transmission of a vaccine-preventable infection through a random, static contact network. Individuals choose whether or not to vaccinate on any given day according to perceived risks of vaccination and infection. We find three possible outcomes for behavior-prevalence dynamics on this type of network: small final number vaccinated and final epidemic size (due to rapid control through voluntary ring vaccination); large final number vaccinated and significant final epidemic size (due to imperfect voluntary ring vaccination), and little or no vaccination and large final epidemic size (corresponding to little or no voluntary ring vaccination). We also show that the social contact structure enables eradication under a broad range of assumptions, except when vaccine risk is sufficiently high, the disease risk is sufficiently low, or individuals vaccinate too late for the vaccine to be effective. For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large differences in population-level outcomes such as final size

  1. Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

    Science.gov (United States)

    Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

    2015-09-01

    Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

  2. The application of neutral network integrated with genetic algorithm and simulated annealing for the simulation of rare earths separation processes by the solvent extraction technique using EHEHPA agent

    International Nuclear Information System (INIS)

    Tran Ngoc Ha; Pham Thi Hong Ha

    2003-01-01

    In the present work, neutral network has been used for mathematically modeling equilibrium data of the mixture of two rare earth elements, namely Nd and Pr with PC88A agent. Thermo-genetic algorithm based on the idea of the genetic algorithm and the simulated annealing algorithm have been used in the training procedure of the neutral networks, giving better result in comparison with the traditional modeling approach. The obtained neutral network modeling the experimental data is further used in the computer program to simulate the solvent extraction process of two elements Nd and Pr. Based on this computer program, various optional schemes for the separation of Nd and Pr have been investigated and proposed. (author)

  3. Accurate Simulation of 802.11 Indoor Links: A "Bursty" Channel Model Based on Real Measurements

    Directory of Open Access Journals (Sweden)

    Agüero Ramón

    2010-01-01

    Full Text Available We propose a novel channel model to be used for simulating indoor wireless propagation environments. An extensive measurement campaign was carried out to assess the performance of different transport protocols over 802.11 links. This enabled us to better adjust our approach, which is based on an autoregressive filter. One of the main advantages of this proposal lies in its ability to reflect the "bursty" behavior which characterizes indoor wireless scenarios, having a great impact on the behavior of upper layer protocols. We compare this channel model, integrated within the Network Simulator (ns-2 platform, with other traditional approaches, showing that it is able to better reflect the real behavior which was empirically assessed.

  4. Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models

    KAUST Repository

    Moraes, Alvaro

    2015-01-01

    Epidemics have shaped, sometimes more than wars and natural disasters, demo- graphic aspects of human populations around the world, their health habits and their economies. Ebola and the Middle East Respiratory Syndrome (MERS) are clear and current examples of potential hazards at planetary scale. During the spread of an epidemic disease, there are phenomena, like the sudden extinction of the epidemic, that can not be captured by deterministic models. As a consequence, stochastic models have been proposed during the last decades. A typical forward problem in the stochastic setting could be the approximation of the expected number of infected individuals found in one month from now. On the other hand, a typical inverse problem could be, given a discretely observed set of epidemiological data, infer the transmission rate of the epidemic or its basic reproduction number. Markovian epidemic models are stochastic models belonging to a wide class of pure jump processes known as Stochastic Reaction Networks (SRNs), that are intended to describe the time evolution of interacting particle systems where one particle interacts with the others through a finite set of reaction channels. SRNs have been mainly developed to model biochemical reactions but they also have applications in neural networks, virus kinetics, and dynamics of social networks, among others. 4 This PhD thesis is focused on novel fast simulation algorithms and statistical inference methods for SRNs. Our novel Multi-level Monte Carlo (MLMC) hybrid simulation algorithms provide accurate estimates of expected values of a given observable of SRNs at a prescribed final time. They are designed to control the global approximation error up to a user-selected accuracy and up to a certain confidence level, and with near optimal computational work. We also present novel dual-weighted residual expansions for fast estimation of weak and strong errors arising from the MLMC methodology. Regarding the statistical inference

  5. Networks and their traffic in multiplayer games

    Directory of Open Access Journals (Sweden)

    Cristian Andrés Melo López

    2016-06-01

    Full Text Available Computer games called multiplayer real-time, or (MCG are at the forefront of the use of the possibilities of the network. Research on this subject have been made for military simulations, virtual reality systems, computer support teamwork, the solutions diverge on the problems posed by MCG. With this in mind, this document provides an overview of the four issues affecting networking at the MCG. First, network resources (bandwidth, latency and computing capacity, together with the technical limits within which the MCG must operate. Second, the distribution concepts include communication architectures (peer-to-peer, client / server, server / network, and data and control architectures (centralized, distributed and reproduced .Thirdly, scalability allows the MCG to adapt to changes in parameterization resources. Finally, security is intended to fend off the traps and vandalism, which are common in online games; to check traffic, particularly these games we decided to take the massively multiplayer game League of Legends, a scene corresponding to a situation of real life in a network of ADSL access network is deployed has been simulated by using NS2 Three variants of TCP, it means SACK TCP, New Reno TCP, and TCP Vegas, have been considered for the cross traffic. The results show that TCP Vegas is able to maintain a constant speed while racing against the game traffic, since it avoids the packet loss and the delays in the tail caused by high peaks, without increasing the size of the sender window. SACK TCP and TCP New Reno, on the other hand, tend to increase continuously the sender window size, which could allow a greater loss of packages and also to cause unwanted delays for the game traffic.

  6. SIMULATION AND ANALYSIS OF GREEDY ROUTING PROTOCOL IN VIEW OF ENERGY CONSUMPTION AND NETWORK LIFETIME IN THREE DIMENSIONAL UNDERWATER WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    SHEENA KOHLI

    2017-11-01

    Full Text Available Underwater Wireless Sensor Network (UWSN comprises of a number of miniature sized sensing devices deployed in the sea or ocean, connected by dint of acoustic links to each other. The sensors trap the ambient conditions and transmit the data from one end to another. For transmission of data in any medium, routing protocols play a crucial role. Moreover, being battery limited, an unavoidable parameter to be considered in operation and analysis of protocols is the network energy and the network lifetime. The paper discusses the greedy routing protocol for underwater wireless sensor networks. The simulation of this routing protocol also takes into consideration the characteristics of acoustic communication like attenuation, transmission loss, signal to noise ratio, noise, propagation delay. The results from these observations may be used to construct an accurate underwater communication model.

  7. COMPUTER DYNAMICS SIMULATION OF DRUG DEPENDENCE THROUGH ARTIFICIAL NEURONAL NETWORK: PEDAGOGICAL AND CLINICAL IMPLICATIONS

    Directory of Open Access Journals (Sweden)

    G. SANTOS

    2008-05-01

    Full Text Available To develop and to evaluate the efficiency of a software able to simulate a virtual patient at different stages of addition was the main goal and challenge of this work. We developed the software in Borland™ Delphi  5®  programming language. Techniques of artificial intelligence, neuronal networks and expert systems, were responsible for modeling the neurobiological structures and mechanisms of the interaction with the drugs used. Dynamical simulation and  hypermedia were designed to increase the software’s interactivity which was able to show graphical information from virtual instrumentation and from realistic functional magnetic resonance imaging display. Early, the program was designed to be used by undergraduate students to improve their neurophysiologic learn, based not only in an interaction of membrane receptors with drugs, but in such a large behavioral simulation. The experimental manipulation of the software was accomplished by: i creating a virtual patient from a normal mood to a behavioral addiction, increasing gradatively: alcohol, opiate or cocaine doses. ii designing an approach to treat the patient, to get total or partial remission of behavioral disorder by combining psychopharmacology and psychotherapy. Integration of dynamic simulation with hypermedia and artificial intelligence has been able to point out behavioral details as tolerance, sensitization and level of addiction to drugs of abuse and so on, turned into a potentially useful tool in the development of teaching activities on several ways, such as education as well clinical skills, in which it could assist patients, families and health care to improve and test their knowledge and skills about different faces supported by drugs dependency. Those features are currently under investigation.

  8. Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies

    International Nuclear Information System (INIS)

    Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

    1991-01-01

    Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs

  9. Movilidad en IPV6: simulación con Network Simulator

    Directory of Open Access Journals (Sweden)

    Javier Eduardo Carvajal Escobar

    2013-07-01

    Full Text Available IP Móvil es la propuesta de Internet Engineering Task Force (IETF para el protocolo de movilidad llamado MIPv6. Este protocolo se ha convertido en la columna vertebral de las nuevas tecnologías de redes inalámbricas mediante las cuales se busca proveer de un servicio ininterrumpido mientras se está en movimiento. Este artículo presenta una visión general del funcionamiento de dicho protocolo, los términos relacionados con este y los nuevos ensajes que vienen dentro del encabezado de movilidad en IPv6. Después se realiza una simulación de dicho protocolo con el software Network Simulator 2, bajo licencia GNU de distribución libre. Como resultado de la simulación se obtiene un archivo de trazas en el cual se plasman todos los eventos.

  10. Knowledge-enhanced network simulation modeling of the nuclear power plant operator

    International Nuclear Information System (INIS)

    Schryver, J.C.; Palko, L.E.

    1988-01-01

    Simulation models of the human operator of advanced control systems must provide an adequate account of the cognitive processes required to control these systems. The Integrated Reactor Operator/System (INTEROPS) prototype model was developed at Oak Ridge National Laboratory (ORNL) to demonstrate the feasibility of dynamically integrating a cognitive operator model and a continuous plant process model (ARIES-P) to provide predictions of the total response of a nuclear power plant during upset/emergency conditions. The model consists of a SAINT network of cognitive tasks enhanced with expertise provided by a knowledge-based fault diagnosis model. The INTEROPS prototype has been implemented in both closed and open loop modes. The prototype model is shown to be cognitively relevant by accounting for cognitive tunneling, confirmation bias, evidence chunking, intentional error, and forgetting

  11. Numerical study of Free Convective Viscous Dissipative flow along Vertical Cone with Influence of Radiation using Network Simulation method

    Science.gov (United States)

    Kannan, R. M.; Pullepu, Bapuji; Immanuel, Y.

    2018-04-01

    A two dimensional mathematical model is formulated for the transient laminar free convective flow with heat transfer over an incompressible viscous fluid past a vertical cone with uniform surface heat flux with combined effects of viscous dissipation and radiation. The dimensionless boundary layer equations of the flow which are transient, coupled and nonlinear Partial differential equations are solved using the Network Simulation Method (NSM), a powerful numerical technique which demonstrates high efficiency and accuracy by employing the network simulator computer code Pspice. The velocity and temperature profiles have been investigated for various factors, namely viscous dissipation parameter ε, Prandtl number Pr and radiation Rd are analyzed graphically.

  12. Unfolding neutron spectra from simulated response of thermoluminescence dosimeters inside a polyethylene sphere using GRNN neural network

    Science.gov (United States)

    Lotfalizadeh, F.; Faghihi, R.; Bahadorzadeh, B.; Sina, S.

    2017-07-01

    Neutron spectrometry using a single-sphere containing dosimeters has been developed recently, as an effective replacement for Bonner sphere spectrometry. The aim of this study is unfolding the neutron energy spectra using GRNN artificial neural network, from the response of thermoluminescence dosimeters, TLDs, located inside a polyethylene sphere. The spectrometer was simulated using MCNP5. TLD-600 and TLD-700 dosimeters were simulated at different positions in all directions. Then the GRNN was used for neutron spectra prediction, using the TLDs' readings. Comparison of spectra predicted by the network with the real spectra, show that the single-sphere dosimeter is an effective instrument in unfolding neutron spectra.

  13. Adaptive mutations enhance assembly and cell-to-cell transmission of a high-titer hepatitis C virus genotype 5a Core-NS2 JFH1-based recombinant

    DEFF Research Database (Denmark)

    Mathiesen, Christian K; Prentoe, Jannick; Meredith, Luke W

    2015-01-01

    UNLABELLED: Recombinant hepatitis C virus (HCV) clones propagated in human hepatoma cell cultures yield relatively low infectivity titers. Here, we adapted the JFH1-based Core-NS2 recombinant SA13/JFH1C3405G,A3696G (termed SA13/JFH1orig), of the poorly characterized genotype 5a, to Huh7.5 cells......-titer production of diverse HCV strains would be advantageous. Our study offers important functional data on how cell culture-adaptive mutations identified in genotype 5a JFH1-based HCVcc permit high-titer culture by affecting HCV genesis through increasing virus assembly and HCV fitness by enhancing the virus...... specific infectivity and cell-to-cell transmission ability, without influencing the biophysical particle properties. High-titer HCVcc like the one described in this study may be pivotal in future vaccine-related studies where large quantities of infectious HCV particles are necessary....

  14. Development and application of hepatitis C reporter viruses with genotype 1 to 7 core-nonstructural protein 2 (NS2) expressing fluorescent proteins or luciferase in modified JFH1 NS5A

    DEFF Research Database (Denmark)

    Gottwein, Judith M; Jensen, Tanja B; Mathiesen, Christian K

    2011-01-01

    to 2a(J6) tagged with EGFP, DsRed-Express2, mCherry, or Renilla luciferase (RLuc), yielding peak supernatant infectivity titers of 4 to 5 log(10) focus-forming units (FFU)/ml. 2a(J6) with ¿40 or ¿25 was fully viable in Huh7.5 cells. In human liver chimeric mice, 2a(J6)-EGFP¿40 acquired various...... deletions in EGFP, while 2a(J6)¿40 did not show an impaired viability. We further developed panels of JFH1-based genotype 1 to 7 core-NS2 recombinants expressing EGFP- or RLuc-NS5A¿40 fusion proteins. In cell culture, the different EGFP recombinants showed growth characteristics comparable to those...

  15. The dynamical modeling and simulation analysis of the recommendation on the user-movie network

    Science.gov (United States)

    Zhang, Shujuan; Jin, Zhen; Zhang, Juan

    2016-12-01

    At present, most research about the recommender system is based on graph theory and algebraic methods, but these methods cannot predict the evolution of the system with time under the recommendation method, and cannot dynamically analyze the long-term utility of the recommendation method. However, these two aspects can be studied by the dynamical method, which essentially investigates the intrinsic evolution mechanism of things, and is widely used to study a variety of actual problems. So, in this paper, network dynamics is used to study the recommendation on the user-movie network, which consists of users and movies, and the movies are watched either by the personal search or through the recommendation. Firstly, dynamical models are established to characterize the personal search and the system recommendation mechanism: the personal search model, the random recommendation model, the preference recommendation model, the degree recommendation model and the hybrid recommendation model. The rationality of the models established is verified by comparing the stochastic simulation with the numerical simulation. Moreover, the validity of the recommendation methods is evaluated by studying the movie degree, which is defined as the number of the movie that has been watched. Finally, we combine the personal search and the recommendation to establish a more general model. The change of the average degree of all the movies is given with the strength of the recommendation. Results show that for each recommendation method, the change of the movie degree is different, and is related to the initial degree of movies, the adjacency matrix A representing the relation between users and movies, the time t. Additionally, we find that in a long time, the degree recommendation is not as good as that in a short time, which fully demonstrates the advantage of the dynamical method. For the whole user-movie system, the preference recommendation is the best.

  16. 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

    2013-12-01

    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.

  17. 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.

  18. A subjective scheduler for subjective dedicated networks

    Science.gov (United States)

    Suherman; Fakhrizal, Said Reza; Al-Akaidi, Marwan

    2017-09-01

    Multiple access technique is one of important techniques within medium access layer in TCP/IP protocol stack. Each network technology implements the selected access method. Priority can be implemented in those methods to differentiate services. Some internet networks are dedicated for specific purpose. Education browsing or tutorial video accesses are preferred in a library hotspot, while entertainment and sport contents could be subjects of limitation. Current solution may use IP address filter or access list. This paper proposes subjective properties of users or applications are used for priority determination in multiple access techniques. The NS-2 simulator is employed to evaluate the method. A video surveillance network using WiMAX is chosen as the object. Subjective priority is implemented on WiMAX scheduler based on traffic properties. Three different traffic sources from monitoring video: palace, park, and market are evaluated. The proposed subjective scheduler prioritizes palace monitoring video that results better quality, xx dB than the later monitoring spots.

  19. Gas network simulations of the regional utility GVT; Gasnetzsimulation des Regionalgasversorgers GVT

    Energy Technology Data Exchange (ETDEWEB)

    Schacht, W. [Gasversorgung Thueringen GmbH (GVT), Erfurt (Germany)

    2000-07-01

    At the turn of the millenium, the German gas industry is faced with new challenges, e.g. the European single market, energy political boundary conditions, deregulation and increased competition. Flexibility, new marketing concepts and higher profitability are key concerns. Optimisation of gas supply can only be ensured by dynamic gas network simulation which also provide information on the current state of gas flow in the network. [German] Zum Beginn des neuen Jahrtausends steht die Erdgaswirtschaft in Deutschland vor voellig neuen Herausforderungen. Der EU-Binnenmarkt, die neuen energiepolitischen Rahmenbedingungen, die Oeffnung und Liberalisierung der Energiemaerkte und die damit im Zusammenhang stehende Verschaerfung des Gas-zu-Gas-Wettbewerbes zwingen zu einer hoeheren Flexibilitaet, zur Einfuehrung neuer Marketingkonzepte und zu einer weiteren Erhoehung der Rentabilitaet unserer Versorgungsunternehmen durch Nutzung von neuen oder noch nicht ausgeschoepften Kosteneinsparungspotentialen. Eine wichtige Voraussetzung fuer den Aufbau einer modernen Gasbezugsoptimierung ist die prozessbegleitende dynamische Gasnetzsimulation. Ausserdem setzen moderne Verfahren der Netzsteuerung derartige Kenntnisse ueber den aktuellen Stroemungszustand im Netz voraus. Mit den im Simulationssystem vorhandenen Zustandsbeobachtern koennen die gewonnenen Aussagen gestuetzt und praezisiert werden. Mit Blick auf die neue Marktordnung gewinnt die online Gasnetzsimulation noch zusaetzlich an Bedeutung. Aus der zeitlichen Entkopplung von Menge und Preis, der Durchleitung sowie der Speicherung und des effektiven Einsatzes von Spottmengen leiten sich voellig neue Aufgaben ab, die operativ nur mit Hilfe einer qualitativ neuen Leittechnik und einer online Gasnetzsimulation geloest werden koennen. Werden diese Aufgaben nicht adaequat geloest, steigt das wirtschaftliche Risiko eklatant an. (orig.)

  20. Determining the inventory impact of extended-shelf-life platelets with a network simulation model.

    Science.gov (United States)

    Blake, John T

    2017-12-01

    The regulatory shelf life for platelets (PLTs) in many jurisdictions is 5 days. PLT shelf life can be extended to 7 days with an enhanced bacterial detection algorithm. Enhanced testing, however, comes at a cost, which may be offset by reductions in wastage due to longer shelf life. This article describes a method for estimating systemwide reductions in PLT outdates after PLT shelf life is extended. A simulation was used to evaluate the impact of an extended PLT shelf life within a national blood network. A network model of the Canadian Blood Services PLT supply chain was built and validated. PLT shelf life was extended from 5 days to 6, 7, and 8 days and runs were completed to determine the impact on outdates. Results suggest that, in general, a 16.3% reduction in PLT wastage can be expected with each additional day that PLT shelf life is extended. Both suppliers and hospitals will experience fewer outdating units, but wastage will decrease at a faster rate at hospitals. No effect was seen by blood group, but there was some evidence that supplier site characteristics influences both the number of units wasted and the site's ability to benefit from extended-shelf-life PLTs. Extended-shelf-life PLTs will reduce wastage within a blood supply chain. At 7 days, an improvement of 38% reduction in wastage can be expected with outdates being equally distributed between suppliers and hospital customers. © 2017 AABB.