WorldWideScience

Sample records for network computerized simulation

  1. Computerized Library Networking in Canada.

    Science.gov (United States)

    Duchesne, Roderick M.; Islam, Mazharul

    1979-01-01

    Reviews a study which examined computerized bibliographic centers in Canada identifying three types: (1) library processing facility; (2) library network user group; and (3) information retrieval facility. The study also reported on ways to promote a computerized library network with emphasis on national location service. (CWM)

  2. Computerized simulation of converter process

    Energy Technology Data Exchange (ETDEWEB)

    Jalkanen, H.; Suomi, M.L.; Wallgren, M. [Helsinki Univ. of Technology, Otaniemi (Finland). Lab. of Metallurgy

    1996-12-31

    Converter process is essentially an oxidising refining process aiming in addition to (1) the primary refining action, decarburisation of high carbon iron melt, also to (2) maximal elimination of impurity elements, especially silicon, phosphorus and sulphur, (3) melting of substantial amounts of scrap using the extra heat released in oxidation reactions and (4) to exact final steel temperature control, optimal for further treatments. `Quantitative modelling of such a complex non-stationary chemical process as oxygen converting necessitates extensive formulation of chemical and thermal evolution of the process in connection with the technological properties of the reactor and the process control measures. A comprehensive converter simulation program like CONSIM-3. 1 and its preceding versions that is based on the theoretical and practical knowledge on the process can be used for (1) educating specialists and smelter personnel, (2) planning of the blowing programs, (3) developing and testing of process control systems and after some elaboration and restructuring (4) it can be integrated to static or dynamic process control systems. (orig.) SULA 2 Research Programme; 10 refs.

  3. A computerized business simulation for dental practice management.

    Science.gov (United States)

    Willis, D O; Smith, J R; Golden, P

    1997-10-01

    Computerized simulations have been used for many years for teaching principles of management in business schools. This paper describes the development of a computerized business simulation for use in dental school practice management courses. The simulation is in a competitive game format. It requires students to formulate strategies and to implement management decisions that reinforce and fulfill that strategy. Participants use the outcomes of these decisions to formulate new management decisions for the upcoming period. Student response to participation in the simulation has been positive, with students indicating that participation is valuable for developing better understanding of analytical business management techniques and interpersonal techniques such as group process and leadership skills.

  4. 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.

  5. Computerized tomography of Castleman's disease simulating a false renal artery aneurysm: a case report.

    Science.gov (United States)

    Friedman, L; Dubowitz, B; Papert, B; Porteous, P

    1987-07-01

    We report a case of retroperitoneal Castleman's disease of the hyaline vascular type simulating a false renal artery aneurysm. Excretory urography with computerized tomography and angiographic findings are presented. All 3 investigations demonstrated a homogeneously enhancing hypervascular retroperitoneal mass.

  6. Airport Network Flow Simulator

    Science.gov (United States)

    1978-10-01

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

  7. Installation of Computerized Procedure System and Advanced Alarm System in the Human Systems Simulation Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Le Blanc, Katya Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States); Spielman, Zachary Alexander [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rice, Brandon Charles [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-04-01

    This report describes the installation of two advanced control room technologies, an advanced alarm system and a computerized procedure system, into the Human Systems Simulation Laboratory (HSSL). Installation of these technologies enables future phases of this research by providing a platform to systematically evaluate the effect of these technologies on operator and plant performance.

  8. Computerized Virtual Reality Simulation in Preclinical Dentistry: Can a Computerized Simulator Replace the Conventional Phantom Heads and Human Instruction?

    Science.gov (United States)

    Plessas, Anastasios

    2017-10-01

    In preclinical dental education, the acquisition of clinical, technical skills, and the transfer of these skills to the clinic are paramount. Phantom heads provide an efficient way to teach preclinical students dental procedures safely while increasing their dexterity skills considerably. Modern computerized phantom head training units incorporate features of virtual reality technology and the ability to offer concurrent augmented feedback. The aims of this review were to examine and evaluate the dental literature for evidence supporting their use and to discuss the role of augmented feedback versus the facilitator's instruction. Adjunctive training in these units seems to enhance student's learning and skill acquisition and reduce the required faculty supervision time. However, the virtual augmented feedback cannot be used as the sole method of feedback, and the facilitator's input is still critical. Well-powered longitudinal randomized trials exploring the impact of these units on student's clinical performance and issues of cost-effectiveness are warranted.

  9. Simulated Associating Polymer Networks

    Science.gov (United States)

    Billen, Joris

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

  10. GNS3 network simulation guide

    CERN Document Server

    Welsh, Chris

    2013-01-01

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

  11. Computerized Liquid Crystal Phase Identification by Neural Networks Analysis of Polarizing Microscopy Textures

    Science.gov (United States)

    Karaszi, Zoltan; Konya, Andrew; Dragan, Feodor; Jakli, Antal; CPIP/LCI; CS Dept. of Kent State University Collaboration

    Polarizing optical microscopy (POM) is traditionally the best-established method of studying liquid crystals, and using POM started already with Otto Lehman in 1890. An expert, who is familiar with the science of optics of anisotropic materials and typical textures of liquid crystals, can identify phases with relatively large confidence. However, for unambiguous identification usually other expensive and time-consuming experiments are needed. Replacement of the subjective and qualitative human eye-based liquid crystal texture analysis with quantitative computerized image analysis technique started only recently and were used to enhance the detection of smooth phase transitions, determine order parameter and birefringence of specific liquid crystal phases. We investigate if the computer can recognize and name the phase where the texture was taken. To judge the potential of reliable image recognition based on this procedure, we used 871 images of liquid crystal textures belonging to five main categories: Nematic, Smectic A, Smectic C, Cholesteric and Crystal, and used a Neural Network Clustering Technique included in the data mining software package in Java ``WEKA''. A neural network trained on a set of 827 LC textures classified the remaining 44 textures with 80% accuracy.

  12. The role of computerized modeling and simulation in the development of life support system technologies

    Science.gov (United States)

    Modell, Michael; Evanich, Peggy; Chen, Chau-Chyun; Anavi, Selim; Mai, Jeff

    Using conventional means of process development, it would take decades and hundreds of millions of dollars to develop technology for recycling of water and solid waste for lunar missions within the next thirty years. Since we anticipate neither that amount of time nor level of funding, new methodologies for developing life support systems (LSS) technologies are essential. Computerized modeling and simulation (CMAS) is a tool that can greatly reduce both the time and cost of technology development. By CMAS, we refer to computer methods for correlating, storing and retrieving property data for chemical species and for solving the phenomenological equations of physical/chemical processes (i.e., process conditions based on properties of materials and mass and energy balances, equipment sizing based on rate processes and the governing equations for unit operations). In particular, CMAS systems can be used to evaluate a LSS process design with minimal requirements for laboratory experimentation. A CMAS model using ASPEN PLUS is presented for a vapor compression distillation (VCD) system designed for reclaiming water from urine.

  13. Design and development of computerized local and overall country's environmental data analysis network system

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Gyu; Kang, Jong Gyu; Han, H.; Han, J. S.; Lee, Y. D.; Lee, S. R.; Kang, D. J.; Cho, Y. G.; Yun, S. H. [Daedeok College, Taejon (Korea, Republic of)

    2001-03-15

    In this development, we designed a integrated database for efficient data processing of radiation-environment data and developed the CLEAN (Computerized Local and overall country's Environmental data Analysis Network) system. The CLEAN system consists of local radiation-environment network, data analysis system, data open system. We developed the CLEAN system focused on building an integrated database, a data mart, and a CLEAN web site. It is expected that the developed system, which organizes the information related to environmental radiation data systematically, can be utilize for the accurate interpretation, analysis and evaluation.

  14. Computerized adaptive testing of population psychological distress: simulation-based evaluation of GHQ-30.

    Science.gov (United States)

    Stochl, Jan; Böhnke, Jan R; Pickett, Kate E; Croudace, Tim J

    2016-06-01

    Goldberg's General Health Questionnaire (GHQ) items are frequently used to assess psychological distress but no study to date has investigated the GHQ-30's potential for adaptive administration. In computerized adaptive testing (CAT) items are matched optimally to the targeted distress level of respondents instead of relying on fixed-length versions of instruments. We therefore calibrate GHQ-30 items and report a simulation study exploring the potential of this instrument for adaptive administration in a longitudinal setting. GHQ-30 responses of 3445 participants with 2 completed assessments (baseline, 7-year follow-up) in the UK Health and Lifestyle Survey were calibrated using item response theory. Our simulation study evaluated the efficiency of CAT administration of the items, cross-sectionally and longitudinally, with different estimators, item selection methods, and measurement precision criteria. To yield accurate distress measurements (marginal reliability at least 0.90) nearly all GHQ-30 items need to be administered to most survey respondents in general population samples. When lower accuracy is permissible (marginal reliability of 0.80), adaptive administration saves approximately 2/3 of the items. For longitudinal applications, change scores based on the complete set of GHQ-30 items correlate highly with change scores from adaptive administrations. The rationale for CAT-GHQ-30 is only supported when the required marginal reliability is lower than 0.9, which is most likely to be the case in cross-sectional and longitudinal studies assessing mean changes in populations. Precise measurement of psychological distress at the individual level can be achieved, but requires the deployment of all 30 items.

  15. Epiluminescence microscopy-based classification of pigmented skin lesions using computerized image analysis and an artificial neural network.

    Science.gov (United States)

    Binder, M; Kittler, H; Seeber, A; Steiner, A; Pehamberger, H; Wolff, K

    1998-06-01

    Epiluminescence microscopy (ELM) is a non-invasive technique for in vivo examination which can provide additional criteria for the clinical diagnosis of pigmented skin lesions (PSLs). In the present study we attempt to determine whether PSLs can be automatically diagnosed by an integrated computerized system. This system should recognize the PSL, automatically extract features and use these features in training an artificial neural network, which should--if sufficiently trained--be capable of recognizing and classifying a new PSL without human aid. One hundred and twenty images of randomly selected histologically proven PSLs (33 common naevi, 48 dysplastic naevi and 39 malignant melanomas) were used in this study. The images were digitally obtained and the morphological features of the PSLs were extracted electronically without human assistance. The numerical data were then divided into learning and testing cases and linked to an artificial neural network for training and for further classification of lesions that the system had not been trained on. Our results show that the computerized system was able to automatically identify 95% of the PSLs presented. The sensitivity and specificity of the computerized system were 90% and 74% respectively. In contrast, when differentiating between individual types of lesions, the system performed at true positive rates of only 38% for malignant melanoma, 62% for dysplastic naevi and 33% for common naevi. Our data indicate that (1) ELM images of PSLs provide an excellent source for digital image analysis; (2) the vast majority of PSLs can be correctly identified by a relatively simple (and thus not "intelligent") application of digital image analysis; (3) automatic feature extraction based mainly on ABCD rules provides reliable data on the distinction between benign and malignant PSLs; and (4) there is evidence that artificial neural networks can be trained to adequately discriminate between benign and malignant PSLs.

  16. Introduction to Network Simulator NS2

    CERN Document Server

    Issariyakul, Teerawat

    2008-01-01

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

  17. Trace Replay and Network Simulation Tool

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

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

  18. Improvement of sampling strategies for randomly distributed hotspots in soil applying a computerized simulation considering the concept of uncertainty.

    Science.gov (United States)

    Hildebrandt, Thomas; Pick, Denis; Einax, Jürgen W

    2012-02-01

    The pollution of soil and environment as a result of human activity is a major problem. Nowadays, the determination of local contaminations is of interest for environmental remediation. These hotspots can have various toxic effects on plants, animals, humans, and the whole ecological system. However, economical and juridical consequences are also possible, e.g., high costs for remediation measures. In this study three sampling strategies (simple random sampling, stratified sampling, and systematic sampling) were applied on randomly distributed hotspot contaminations to prove their efficiency in term of finding hotspots. The results were used for the validation of a computerized simulation. This application can simulate the contamination on a field, the sampling pattern, and a virtual sampling. A constant hit rate showed that none of the sampling patterns could reach better results than others. Furthermore, the uncertainty associated with the results is described by confidence intervals. It is to be considered that the uncertainty during sampling is enormous and will decrease slightly, even the number of samples applied was increased to an unreasonable amount. It is hardly possible to identify the exact number of randomly distributed hotspot contaminations by statistical sampling. But a range of possible results could be calculated. Depending on various parameters such as shape and size of the area, number of hotspots, and sample quantity, optimal sampling strategies could be derived. Furthermore, an estimation of bias arising from sampling methodology is possible. The developed computerized simulation is an innovative tool for optimizing sampling strategies in terrestrial compartments for hotspot distributions.

  19. SDL-based network performance simulation

    Science.gov (United States)

    Yang, Yang; Lu, Yang; Lin, Xiaokang

    2005-11-01

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

  20. 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

  1. Computerized cognitive training restores neural activity within the reality monitoring network in schizophrenia.

    Science.gov (United States)

    Subramaniam, Karuna; Luks, Tracy L; Fisher, Melissa; Simpson, Gregory V; Nagarajan, Srikantan; Vinogradov, Sophia

    2012-02-23

    Schizophrenia patients suffer from severe cognitive deficits, such as impaired reality monitoring. Reality monitoring is the ability to distinguish the source of internal experiences from outside reality. During reality monitoring tasks, schizophrenia patients make errors identifying "I made it up" items, and even during accurate performance, they show abnormally low activation of the medial prefrontal cortex (mPFC), a region that supports self-referential cognition. We administered 80 hr of computerized training of cognitive processes to schizophrenia patients and found improvement in reality monitoring that correlated with increased mPFC activity. In contrast, patients in a computer games control condition did not show any behavioral or neural improvements. Notably, recovery in mPFC activity after training was associated with improved social functioning 6 months later. These findings demonstrate that a serious behavioral deficit in schizophrenia, and its underlying neural dysfunction, can be improved by well-designed computerized cognitive training, resulting in better quality of life. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. 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.

  3. 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...

  4. Vectorized algorithms for spiking neural network simulation.

    Science.gov (United States)

    Brette, Romain; Goodman, Dan F M

    2011-06-01

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

  5. A user oriented active network simulator

    Science.gov (United States)

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

    1980-07-01

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

  6. Validation of computerized diagnostic information in a clinical database from a national equine clinic network

    Directory of Open Access Journals (Sweden)

    Egenvall Agneta

    2009-12-01

    Full Text Available Abstract Background Computerized diagnostic information offers potential for epidemiological research; however data accuracy must be addressed. The principal aim of this study was to evaluate the completeness and correctness of diagnostic information in a computerized equine clinical database compared to corresponding hand written veterinary clinical records, used as gold standard, and to assess factors related to correctness. Further, the aim was to investigate completeness (epidemiologic sensitivity, correctness (positive predictive value, specificity and prevalence for diagnoses for four body systems and correctness for affected limb information for four joint diseases. Methods A random sample of 450 visits over the year 2002 (nvisits = 49,591 was taken from 18 nation wide clinics headed under one company. Computerized information for the visits selected and copies of the corresponding veterinary clinical records were retrieved. Completeness and correctness were determined using semi-subjective criteria. Logistic regression was used to examine factors associated with correctness for diagnosis. Results Three hundred and ninety six visits had veterinary clinical notes that were retrievable. The overall completeness and correctness were 91% and 92%, respectively; both values considered high. Descriptive analyses showed significantly higher degree of correctness for first visits compared to follow up visits and for cases with a diagnostic code recorded in the veterinary records compared to those with no code noted. The correctness was similar regardless of usage category (leisure/sport horse, racing trotter and racing thoroughbred or gender. For the four body systems selected (joints, skin and hooves, respiratory, skeletal the completeness varied between 71% (respiration and 91% (joints and the correctness ranged from 87% (skin and hooves to 96% (respiration, whereas the specificity was >95% for all systems. Logistic regression showed that

  7. Validation of computerized diagnostic information in a clinical database from a national equine clinic network.

    Science.gov (United States)

    Penell, Johanna C; Bonnett, Brenda N; Pringle, John; Egenvall, Agneta

    2009-12-10

    Computerized diagnostic information offers potential for epidemiological research; however data accuracy must be addressed. The principal aim of this study was to evaluate the completeness and correctness of diagnostic information in a computerized equine clinical database compared to corresponding hand written veterinary clinical records, used as gold standard, and to assess factors related to correctness. Further, the aim was to investigate completeness (epidemiologic sensitivity), correctness (positive predictive value), specificity and prevalence for diagnoses for four body systems and correctness for affected limb information for four joint diseases. A random sample of 450 visits over the year 2002 (nvisits=49,591) was taken from 18 nation wide clinics headed under one company. Computerized information for the visits selected and copies of the corresponding veterinary clinical records were retrieved. Completeness and correctness were determined using semi-subjective criteria. Logistic regression was used to examine factors associated with correctness for diagnosis. Three hundred and ninety six visits had veterinary clinical notes that were retrievable. The overall completeness and correctness were 91% and 92%, respectively; both values considered high. Descriptive analyses showed significantly higher degree of correctness for first visits compared to follow up visits and for cases with a diagnostic code recorded in the veterinary records compared to those with no code noted. The correctness was similar regardless of usage category (leisure/sport horse, racing trotter and racing thoroughbred) or gender.For the four body systems selected (joints, skin and hooves, respiratory, skeletal) the completeness varied between 71% (respiration) and 91% (joints) and the correctness ranged from 87% (skin and hooves) to 96% (respiration), whereas the specificity was >95% for all systems. Logistic regression showed that correctness was associated with type of visit, whether

  8. Dose profile study on computerized tomography scanning of skull with simulator object; Estudo do perfil de dose em varreduras de TC de cranio com objeto simulador

    Energy Technology Data Exchange (ETDEWEB)

    Mourao, A.P., E-mail: aprata@des.cefetmg.b [Centro Federal de Educacao Tecnologica de Minas Gerais (CEFET/MG), Belo Horizonte, MG (Brazil). Nucleo de Engenharia Hospitalar; Alonso, Thessa C.; Silva, Teogenes A. da, E-mail: alonso@cdtn.b, E-mail: silvata@@cdtn.b [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

    2011-10-26

    This work presents a comparison among the dose profiles in scanning of computerized tomography of a simulator object of PMMA in its periphery region. To obtain the deposited dose at the PMMA thermoluminescent dosemeters were used positioned at the interior of PMMA simulated object longitudinal to periphery and at the center of cylinder (positions denominated North, South, East, West and Center). Eight scanning were performed of simulator object using the routine protocol for skull in eight different services of radiodiagnostic by TC

  9. Program Aids Simulation Of Neural Networks

    Science.gov (United States)

    Baffes, Paul T.

    1990-01-01

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

  10. Assessment of social cognition in non-human primates using a network of computerized automated learning device (ALDM) test systems.

    Science.gov (United States)

    Fagot, Joël; Marzouki, Yousri; Huguet, Pascal; Gullstrand, Julie; Claidière, Nicolas

    2015-05-05

    Fagot & Paleressompoulle(1) and Fagot & Bonte(2) have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys maintained in semi-free ranging conditions. Data accumulated during the last five years have consistently demonstrated the efficiency of this protocol to investigate individual/physical cognition in monkeys, and have further shown that this procedure reduces stress level during animal testing(3). This paper demonstrates that networks of ALDM can also be used to investigate different facets of social cognition and in-group expressed behaviors in monkeys, and describes three illustrative protocols developed for that purpose. The first study demonstrates how ethological assessments of social behavior and computerized assessments of cognitive performance could be integrated to investigate the effects of socially exhibited moods on the cognitive performance of individuals. The second study shows that batteries of ALDM running in parallel can provide unique information on the influence of the presence of others on task performance. Finally, the last study shows that networks of ALDM test units can also be used to study issues related to social transmission and cultural evolution. Combined together, these three studies demonstrate clearly that ALDM testing is a highly promising experimental tool for bridging the gap in the animal literature between research on individual cognition and research on social cognition.

  11. Buffer Management Simulation in ATM Networks

    Science.gov (United States)

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

    1998-01-01

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

  12. 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).

  13. 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...

  14. 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.

  15. Quality of computerized blast load simulation for non-linear dynamic ...

    African Journals Online (AJOL)

    Simulation has been carried out using a general-purpose, commercial software system and a special-purpose, blast-specific software product to assess and compare the quality of response prediction of such computational models. Nonlinear dynamic analysis has been performed using a three-dimensional model of a ...

  16. quality of computerized blast load simulation for non-linear dynamic

    African Journals Online (AJOL)

    STRANCOM

    2005. Simulation has been carried out using a general-purpose, commercial software system and a special-purpose, blast-specific software product to assess and compare the quality of response prediction of such computational models. Nonlinear dynamic analysis has been performed using a three-dimensional model of.

  17. The Effect of a Computerized Simulation on Middle School Students' Understanding of the Kinetic Molecular Theory

    Science.gov (United States)

    Stern, Luli; Barnea, Nitza; Shauli, Sofia

    2008-01-01

    The objective of this study was to evaluate the effect of a dynamic software simulation on the understanding of the kinetic molecular theory by 7th graders. Students in the control group (n = 62) studied a curricular unit that addressed the differences in arrangement and motion of molecules in the three phases of matter. The experimental group (n…

  18. 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...

  19. Computerized system of automated recording and processing of seismic data from the Upper Silesian microseismic network

    Energy Technology Data Exchange (ETDEWEB)

    Kornowski, J.; Sokolowski, H.

    1981-05-01

    This paper describes operation of the Upper Silesian microseismic network, developed and directed by the Central Mining Institute. Seismic events are detected by the T-8100 Racal-Thermionic multi-channel system with Willmore MK II seismic detectors, and are transmitted to the computer center, equipped with the PDP 11/45 minicomputer produced by the Digital Equipment Corp, by means of an FM system. The recording and processing system consists of the following stages: seismic event recording, determining time of seismic events, detection of shocks and elimination of disturbances, assessment of seismic energy of rocks, identifying time of shock recording, determining shock epicenter, storage of information on shocks. Basic computer codes of the system are described: shock detection, determination of time, determination of shock epicenters, statistical processing, and storage. The system collects and stores information on earthquakes and shocks caused by rock bursts. (6 refs.) (In Polish)

  20. Dynamic simulation of regulatory networks using SQUAD

    Directory of Open Access Journals (Sweden)

    Xenarios Ioannis

    2007-11-01

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

  1. Computerized classification of liver disease in MRI using an artificial neural network

    Science.gov (United States)

    Zhang, Xuejun; Kanematsu, Masayuki; Fujita, Hiroshi; Hara, Takeshi; Hoshi, Hiroaki

    2001-07-01

    We developed a software named LiverANN based on artificial neural network (ANN) technique for distinguishing the pathologies of focal liver lesions in magnetic resonance (MR) imaging, which helps radiologists integrate the imaging findings with different pulse sequences and raise the diagnostic accuracy even with radiologists inexperienced in liver MR imaging. In each patient, regions of focal liver lesion on T1-weighted, T2-weighted, and gadolinium-enhanced dynamic MR images obtained in the hepatic arterial and equilibrium phases were placed by a radiologist (M.K.), then the program automatically calculated the brightness and homogeneity into numerical data within the selected areas as the input signals to the ANN. The outputs from the ANN were the 5 categories of focal hepatic diseases: liver cyst, cavernous hemangioma, dysplasia, hepatocellular carcinoma, and metastasis. Fifty cases were used for training the ANN, while 30 cases for testing the performance. The result showed that the LiverANN classified 5 types of focal liver lesions with sensitivity of 93%, which demonstrated the ability of ANN to fuse the complex relationships among the image findings with different sequences, and the ANN-based software may provide radiologists with referential opinion during the radiologic diagnostic procedure.

  2. Computerized Classification of Pneumoconiosis on Digital Chest Radiography Artificial Neural Network with Three Stages.

    Science.gov (United States)

    Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

    2017-08-01

    It is difficult for radiologists to classify pneumoconiosis from category 0 to category 3 on chest radiographs. Therefore, we have developed a computer-aided diagnosis (CAD) system based on a three-stage artificial neural network (ANN) method for classification based on four texture features. The image database consists of 36 chest radiographs classified as category 0 to category 3. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from chest radiographs. We obtained a gray-level histogram, histogram of gray-level difference, gray-level run-length matrix (GLRLM) feature image, and gray-level co-occurrence matrix (GLCOM) feature image in each ROI. For ROI-based classification, the first ANN was trained with each texture feature. Next, the second ANN was trained with output patterns obtained from the first ANN. Finally, we obtained a case-based classification for distinguishing among four categories with the third ANN method. We determined the performance of the third ANN by receiver operating characteristic (ROC) analysis. The areas under the ROC curve (AUC) of the highest category (severe pneumoconiosis) case and the lowest category (early pneumoconiosis) case were 0.89 ± 0.09 and 0.84 ± 0.12, respectively. The three-stage ANN with four texture features showed the highest performance for classification among the four categories. Our CAD system would be useful for assisting radiologists in classification of pneumoconiosis from category 0 to category 3.

  3. Efficient simulation of a tandem Jackson network

    NARCIS (Netherlands)

    Kroese, Dirk; Nicola, V.F.

    2002-01-01

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

  4. Parameter estimation in channel network flow simulation

    Directory of Open Access Journals (Sweden)

    Han Longxi

    2008-03-01

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

  5. Impact of aneurysmal geometry on intraaneurysmal flow: a computerized flow simulation study

    Energy Technology Data Exchange (ETDEWEB)

    Szikora, Istvan [National Institute of Neurosurgery, Budapest (Hungary); National Institute of Neurosurgery, Interventional Neuroradiology, Budapest (Hungary); Paal, Gyorgy; Ugron, Adam; Nasztanovics, Ferenc; Bojtar, Imre [University of Technology and Economics, Budapest (Hungary); Marosfoi, Miklos; Berentei, Zsolt; Kulcsar, Zsolt; Lee, Wickly; Nyary, Istvan [National Institute of Neurosurgery, Budapest (Hungary)

    2008-05-15

    This study was performed to assess the effect of aneurysm geometry on parameters that may have an impact on the natural history of intracranial aneurysms, such as intraaneurysmal flow pressure and shear stress. Flow was simulated in 21 randomly selected aneurysms using finite volume modeling. Ten aneurysms were classified as side-wall aneurysms, with either single-sided or circumferential involvement of the parent artery wall, and 11 as bifurcation aneurysms (symmetric or asymmetric), with an axis either perpendicular or parallel to the parent artery. The flow patterns were classified as either jet or vortex types (with regular or irregular vortex flow). Pressures and shear stresses were characterized as evenly or unevenly distributed over the aneurysm wall and neck. All side-wall and four of the bifurcation aneurysms with a perpendicular axis had a vortex type flow pattern and seven bifurcation aneurysms with a parallel axis (four symmetric and two asymmetric) had a jet flow pattern. Jet type flow was associated with an uneven pressure distribution in seven out of seven aneurysms. Vortex type flow resulted in an even pressure distribution in five out of six aneurysms with an irregular flow pattern and six out of eight with a regular flow pattern. No firm relationship could be established between any geometrical type and shear stress distribution. Only 1 of 14 aneurysms with a perpendicular axis, but 4 of 7 aneurysms with a parallel axis, had ruptured. Aneurysm geometry does have an impact on flow conditions. Aneurysms with a main axis parallel to the parent artery have a tendency to have a jet flow pattern and uneven distribution of unsteady pressure. These aneurysms may have a higher rate of rupture as than those with a main axis perpendicular to the parent artery. (orig.)

  6. 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.

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

    Science.gov (United States)

    Payer, Garrett

    2015-05-01

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

  8. Simulating Autonomous Telecommunication Networks for Space Exploration

    Science.gov (United States)

    Segui, John S.; Jennings, Esther H.

    2008-01-01

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

  9. Modeling and Simulation Network Data Standards

    Science.gov (United States)

    2011-09-30

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

  10. Resilience Simulation for Water, Power & Road Networks

    Science.gov (United States)

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

    2014-12-01

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

  11. Simulation of developing human neuronal cell networks.

    Science.gov (United States)

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

    2016-08-30

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

  12. Spiking network simulation code for petascale computers

    Science.gov (United States)

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

    2014-01-01

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

  13. Spiking network simulation code for petascale computers.

    Science.gov (United States)

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

    2014-01-01

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

  14. C Library for Simulated Evolution of Biological Networks

    OpenAIRE

    Chandran, Deepak; Sauro, Herbert M.

    2010-01-01

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

  15. Measuring the performance of attention networks with the Dalhousie Computerized Attention Battery (DalCAB: Methodology and reliability in healthy adults

    Directory of Open Access Journals (Sweden)

    Stephanie Anne Holland Jones

    2016-06-01

    Full Text Available Attention is an important, multifaceted cognitive domain that has been linked to three distinct, yet interacting, networks: alerting, orienting, and executive control. The measurement of attention and deficits of attention within these networks is critical to the assessment of many neurological and psychiatric conditions in both research and clinical settings. The Dalhousie Computerized Attention Battery (DalCAB was created to assess attentional functions related to the three attention networks using a range of tasks including: simple reaction time, go/no-go, choice reaction time, dual task, flanker, item and location working memory and visual search. The current study provides preliminary normative data, test-retest reliability (intraclass correlations and practice effects in DalCAB performance 24-hours after baseline for healthy young adults (n = 96, 18-31 years. Performance on the DalCAB tasks demonstrated Good to Excellent test-retest reliability for mean reaction time, while accuracy and difference measures (e.g., switch costs, interference effects and working memory load effects were most reliable for tasks that require more extensive cognitive processing (e.g., choice reaction time, flanker, dual task, and conjunction search. Practice effects were common and pronounced at the 24-hour interval. In addition, performance related to specific within-task parameters of the DalCAB sub-tests provides preliminary support for future formal assessment of the convergent validity of our interpretation of the DalCAB as a potential clinical and research assessment tool for measuring aspects of attention related to the alerting, orienting and executive control networks.Keywords: computerized assessment; attention; orienting; alerting; executive function

  16. Motorway Network Simulation Using Bluetooth Data

    Directory of Open Access Journals (Sweden)

    Karakikes Ioannis

    2016-09-01

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

  17. 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.

  18. 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.

  19. 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...

  20. Computerizing a Department of Psychiatry.

    Science.gov (United States)

    Lombroso, Paul; Eng, Lenny

    1987-01-01

    Describes the process by which a department of psychiatry computerized its clinical services under a single communication network. Presents the program in detail, demonstrating the recording of various clinical, administrative and demographic data. Emphasizes the value of such information for returning patients, immediate updating of information,…

  1. The design and implementation of a network simulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2013-11-01

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

  2. 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...

  3. Computerized ionospheric tomography

    Energy Technology Data Exchange (ETDEWEB)

    Austen, J.R.; Raymund, T.D.; Klobuchar, J.A.; Stalker, J.; Liu, C.H.

    1990-05-03

    In this paper the background of computerized tomography (CT) and its application to the ionosphere is reviewed. CT techniques, using only total electron content (TEC) data, can be used to reconstruct a two-dimensional image of the electron density in the ionosphere. The limitations of this technique are discussed and examples showing the limitations and capabilities are presented. Simulation results for two applications are presented: imaging the high latitude trough, and the correction of tracking radar range rate errors. Some possible extensions of the technique are presented.

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

    OpenAIRE

    WenJun Zhang; GuangHua Liu

    2012-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tuomo eMäki-Marttunen

    2011-06-01

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

  7. Simulation Of Networking Protocols On Software Emulated Network Stack

    Directory of Open Access Journals (Sweden)

    Hrushikesh Nimkar

    2015-08-01

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

  8. The Effectiveness of Problem-based Learning Approach on Students’ Skills in Technical Vocational Education and Training (TVET) Specifically on Programming Course Using a Computerized Numerical Control (CNC) Simulator

    DEFF Research Database (Denmark)

    Mohamad, Hasim Bin; de Graaff, Erik

    2013-01-01

    using a Computerized Numerical Control (CNC) simulator. The study will use data from the German-Malaysian Institute in Malaysia. The findings of this study will provide a general guideline for educators in Technical and Vocational Education and Training (TVET) institutions in implementing Problem...

  9. 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.   

  10. Graphical user interface for wireless sensor networks simulator

    Science.gov (United States)

    Paczesny, Tomasz; Paczesny, Daniel; Weremczuk, Jerzy

    2008-01-01

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

  11. A Flexible System for Simulating Aeronautical Telecommunication Network

    Science.gov (United States)

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

    1998-01-01

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

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

    Science.gov (United States)

    Nicol, David M.

    1988-01-01

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

  13. A neural network simulation package in CLIPS

    Science.gov (United States)

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

    1990-01-01

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

  14. 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.

  15. Computerized analysis of interstitial lung diseases on chest radiographs based on lung texture, geometric-pattern features, and artificial neural networks

    Science.gov (United States)

    Ishida, Takayuki; Katsuragawa, Shigehiko; Nakamura, Katsumi; Ashizawa, Kazuto; MacMahon, Heber; Doi, Kunio

    2002-05-01

    For computerized detection of interstitial lung disease on chest radiographs, we developed three different methods: texture analysis based on the Fourier transform, geometric- pattern feature analysis, and artificial neural network (ANN) analysis of image data. With these computer-aided diagnostic methods, quantitative measures can be obtained. To improve the diagnostic accuracy, we investigated combined classification schemes by using the results obtained with the three methods for distinction between normal and abnormal chest radiographs with interstitial opacities. The sensitivities of texture analysis, geometric analysis, and ANN analysis were 88.0+/- 1.6%, 91.0+/- 2.6%, and 87.5+/- 1.9%, respectively, at a specificity of 90.0%, whereas the sensitivity of a combined classification scheme with the logical OR operation was improved to 97.1%+/- 1.5% at the same specificity of 90.0%. The combined scheme can achieve higher accuracy than the individual methods for distinction between normal and abnormal cases with interstitial opacities.

  16. Interfacing Network Simulations and Empirical Data

    Science.gov (United States)

    2009-05-01

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

  17. 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.

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

    Science.gov (United States)

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

    2012-12-01

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

  19. 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...

  20. AMPS data management requirements study, appendix 1. [user manuals (computer programs)/display devices - computerized simulation/experimentation/ionosphere

    Science.gov (United States)

    1975-01-01

    Flow charts and display formats for the simulation of five experiments are given. The experiments are: (1) electromagnetic wave transmission; (2) passive observations of ambient plasma; (3) ionospheric measurements with subsatellite; (4) electron accelerator beam measurements; and (5) measurement of acoustical gravity waves in the sodium layer using lasers. A detailed explanation of the simulation procedure, definition of variables, and an explanation of how the experimenter makes display choices is also presented. A functional description is included on each flow chart and the assumptions and definitions of terms and scope of the flow charts and displays are presented.

  1. Simulated evolution of signal transduction networks.

    Directory of Open Access Journals (Sweden)

    Mohammad Mobashir

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

  2. 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.

  3. Neural networks analysis on SSME vibration simulation data

    Science.gov (United States)

    Lo, Ching F.; Wu, Kewei

    1993-01-01

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

  4. 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".

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

    Science.gov (United States)

    Sargent, Jonathan; Bedford, Anthony

    2013-01-01

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

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

    Science.gov (United States)

    Ghosh, Debraj; De, Rajat K

    2017-10-30

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

  7. PyNN: A Common Interface for Neuronal Network Simulators

    Science.gov (United States)

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

    2008-01-01

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

  8. PyNN: a common interface for neuronal network simulators

    Directory of Open Access Journals (Sweden)

    Andrew P Davison

    2009-01-01

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

  9. AMPS data management requirements study. [user manuals (computer programs)/display devices - computerized simulation/experimentation/ionosphere

    Science.gov (United States)

    1975-01-01

    A data simulation is presented for instruments and associated control and display functions required to perform controlled active experiments of the atmosphere. A comprehensive user's guide is given for the data requirements and software developed for the following experiments: (1) electromagnetic wave transmission; (2) passive observation of ambient plasmas; (3) ionospheric measurements with a subsatellite; (4) electron accelerator beam measurements; and (5) measurement of acoustic gravity waves in the sodium layer using lasers. A complete description of each experiment is given.

  10. 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.

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

    Science.gov (United States)

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

    2015-10-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Simulating public private networks as evolving systems

    NARCIS (Netherlands)

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

    2013-01-01

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

  17. 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

  18. Queueing networks : Rare events and fast simulations

    NARCIS (Netherlands)

    Miretskiy, D.I.

    2009-01-01

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

  19. 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.

  20. Reduction in patient burdens with graphical computerized adaptive testing on the ADL scale: tool development and simulation

    Directory of Open Access Journals (Sweden)

    Wang Weng-Chung

    2009-05-01

    Full Text Available Abstract Background The aim of this study was to verify the effectiveness and efficacy of saving time and reducing burden for patients, nurses, and even occupational therapists through computer adaptive testing (CAT. Methods Based on an item bank of the Barthel Index (BI and the Frenchay Activities Index (FAI for assessing comprehensive activities of daily living (ADL function in stroke patients, we developed a visual basic application (VBA-Excel CAT module, and (1 investigated whether the averaged test length via CAT is shorter than that of the traditional all-item-answered non-adaptive testing (NAT approach through simulation, (2 illustrated the CAT multimedia on a tablet PC showing data collection and response errors of ADL clinical functional measures in stroke patients, and (3 demonstrated the quality control of endorsing scale with fit statistics to detect responding errors, which will be further immediately reconfirmed by technicians once patient ends the CAT assessment. Results The results show that endorsed items could be shorter on CAT (M = 13.42 than on NAT (M = 23 at 41.64% efficiency in test length. However, averaged ability estimations reveal insignificant differences between CAT and NAT. Conclusion This study found that mobile nursing services, placed at the bedsides of patients could, through the programmed VBA-Excel CAT module, reduce the burden to patients and save time, more so than the traditional NAT paper-and-pencil testing appraisals.

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

    Directory of Open Access Journals (Sweden)

    Elizabeth A Coker

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

  2. Integrated Circuit For Simulation Of Neural Network

    Science.gov (United States)

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

    1988-01-01

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

  3. Software for Brain Network Simulations: A Comparative Study

    Science.gov (United States)

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

    2017-01-01

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

  4. 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.

  5. 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.

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

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

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

  7. 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

  8. High Fidelity Simulations of Large-Scale Wireless Networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-01

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

  9. Stochastic Simulation of Biomolecular Networks in Dynamic Environments.

    Science.gov (United States)

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

    2016-06-01

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

  10. Stochastic Simulation of Biomolecular Networks in Dynamic Environments.

    Directory of Open Access Journals (Sweden)

    Margaritis Voliotis

    2016-06-01

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

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

    Science.gov (United States)

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

    2017-10-11

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

  12. 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.

  13. 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.

  14. 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.

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

    Science.gov (United States)

    Liu, Gang; Neelamegham, Sriram

    2008-04-15

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  17. Artificial Neural Network Metamodels of Stochastic Computer Simulations

    Science.gov (United States)

    1994-08-10

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

  18. Computerization of academic libraries: a case study of Hezekiah ...

    African Journals Online (AJOL)

    The paper discussed the computerization of the Hezekiah Oluwasanmi Library, Obafemi Awolowo University, Ile-Ife. The history, possible design options and the level of computerization were given. The Library's network architecture and the chosen design option used were explained with reasons. The state of the art of the ...

  19. Transmission network expansion planning with simulation optimization

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-01-01

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

  20. 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…

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

    African Journals Online (AJOL)

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

  2. 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).

  3. 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.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Perju Sorin

    2014-09-01

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

  6. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

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

  9. 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.

  10. 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.

  11. Hybrid neural network bushing model for vehicle dynamics simulation

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-12-15

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

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

    Science.gov (United States)

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

    1998-07-01

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

  13. Agent-Based Simulation Analysis for Network Formation

    OpenAIRE

    神原, 李佳; 林田, 智弘; 西﨑, 一郎; 片桐, 英樹

    2009-01-01

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

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Science.gov (United States)

    Goodman, Dan F M

    2010-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2016-01-01

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

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

    Science.gov (United States)

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

    2012-06-01

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

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  19. 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.

  20. Computer simulation of randomly cross-linked polymer networks

    CERN Document Server

    Williams, T P

    2002-01-01

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

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

    Science.gov (United States)

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

    1992-12-01

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

  2. 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.

  3. 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.

  4. [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.

  5. Computerized technique for recording board defect data

    Science.gov (United States)

    R. Bruce Anderson; R. Edward Thomas; Charles J. Gatchell; Neal D. Bennett; Neal D. Bennett

    1993-01-01

    A computerized technique for recording board defect data has been developed that is faster and more accurate than manual techniques. The lumber database generated by this technique is a necessary input to computer simulation models that estimate potential cutting yields from various lumber breakdown sequences. The technique allows collection of detailed information...

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

    OpenAIRE

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

    2016-01-01

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

  7. 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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  10. 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.)

  11. 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.

  12. 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.

  13. Computer Simulations of Bottlebrush Melts and Soft Networks

    Science.gov (United States)

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

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

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

    Science.gov (United States)

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-16

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

  15. Computerized Interactive Gaming via Supporting Vector Machines

    Directory of Open Access Journals (Sweden)

    Y. Jiang

    2008-01-01

    Full Text Available Computerized interactive gaming requires automatic processing of large volume of random data produced by players on spot, such as shooting, football kicking, and boxing. This paper describes a supporting vector machine-based artificial intelligence algorithm as one of the possible solutions to the problem of random data processing and the provision of interactive indication for further actions. In comparison with existing techniques, such as rule-based and neural networks, and so forth, our SVM-based interactive gaming algorithm has the features of (i high-speed processing, providing instant response to the players, (ii winner selection and control by one parameter, which can be predesigned and adjusted according to the needs of interaction and game design or specific level of difficulties, and (iii detection of interaction points is adaptive to the input changes, and no labelled training data is required. Experiments on numerical simulation support that the proposed algorithm is robust to random noise, accurate in picking up winning data, and convenient for all interactive gaming designs.

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

    Science.gov (United States)

    Zbinden, Cyrille

    2011-10-01

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

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

    Science.gov (United States)

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

    2012-12-01

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

  18. Artificial neural network simulator for SOFC performance prediction

    Science.gov (United States)

    Arriagada, Jaime; Olausson, Pernilla; Selimovic, Azra

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

  19. COEL: A Cloud-based Reaction Network Simulator

    Directory of Open Access Journals (Sweden)

    Peter eBanda

    2016-04-01

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

  20. A Network Scheduling Model for Distributed Control Simulation

    Science.gov (United States)

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

    2016-01-01

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

  1. Technologies in Computerized Lexicography

    African Journals Online (AJOL)

    scope of this paper (for a historical review of NLP, see Sparck Jones 1995). Here, it is relevant that the automatic analysis of language has become an inter- disciplinary topic of interest, and that some developments may have relevance to corpus analysis and computerized corpus-based lexicography. We particu- larly refer ...

  2. Computerized Mastery Testing.

    Science.gov (United States)

    Lewis, Charles; Sheehan, Kathleen

    1988-01-01

    Introduces a theoretical framework for mastery testing, using Item Response Theory and Bayesian Decision Theory. The idea of sequential testing is developed, with the goal of providing longer or shorter tests as needed, and a computerized application to a hypothetical professional knowledge examination is discussed. (Author/LRW)

  3. Simulation of heart rate variability model in a network

    Science.gov (United States)

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

    2017-07-01

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

  4. 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...

  5. 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.

  6. Research on accounting transition from computerization to informationization

    Directory of Open Access Journals (Sweden)

    Shu Chen

    2017-11-01

    Full Text Available The application for computer technology, digitalization technology and network technology in the accounting field has promoted the development of accounting informationization. Accounting informationization is a product integrated with traditional accounting theory and modern information technology, which is an inevitable trend of continuous development of modern accounting. This paper discusses the basic concepts and characteristics of accounting computerization and informationization based on the normative research method and literature data method, analyzes the feasibility of accounting transition from computerization to informationization, and finally puts forward the specific approaches and ultimate goals of accounting transition from computerization to informationization.

  7. Assessment of radiation exposure in dental cone-beam computerized tomography with the use of metal-oxide semiconductor field-effect transistor (MOSFET) dosimeters and Monte Carlo simulations.

    Science.gov (United States)

    Koivisto, J; Kiljunen, T; Tapiovaara, M; Wolff, J; Kortesniemi, M

    2012-09-01

    The aims of this study were to assess the organ and effective dose (International Commission on Radiological Protection (ICRP) 103) resulting from dental cone-beam computerized tomography (CBCT) imaging using a novel metal-oxide semiconductor field-effect transistor (MOSFET) dosimeter device, and to assess the reliability of the MOSFET measurements by comparing the results with Monte Carlo PCXMC simulations. Organ dose measurements were performed using 20 MOSFET dosimeters that were embedded in the 8 most radiosensitive organs in the maxillofacial and neck area. The dose-area product (DAP) values attained from CBCT scans were used for PCXMC simulations. The acquired MOSFET doses were then compared with the Monte Carlo simulations. The effective dose measurements using MOSFET dosimeters yielded, using 0.5-cm steps, a value of 153 μSv and the PCXMC simulations resulted in a value of 136 μSv. The MOSFET dosimeters placed in a head phantom gave results similar to Monte Carlo simulations. Minor vertical changes in the positioning of the phantom had a substantial affect on the overall effective dose. Therefore, the MOSFET dosimeters constitute a feasible method for dose assessment of CBCT units in the maxillofacial region. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. 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.

  9. Quantum versus simulated annealing in wireless interference network optimization

    Science.gov (United States)

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-01

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

  10. Simulation

    CERN Document Server

    Ross, Sheldon

    2006-01-01

    Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This text explains how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. It presents the statist

  11. 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

  12. Network condition simulator for benchmarking sewer deterioration models.

    Science.gov (United States)

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

    2011-10-15

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

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

    Science.gov (United States)

    Pregnolato, Maria; Ford, Alistair; Dawson, Richard

    2015-04-01

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

  14. Computerizing clinical practice guidelines

    DEFF Research Database (Denmark)

    Lyng, Karen Marie

    . The analysis focuses on the emergence of general clinical work practice demands on guidance • An analysis of guidance demands from clinical work practice and business strategy, focusing on implications for the design of computerised CPGs. In my research, I have applied observation studies, interviews......It is well described that hospitals have problems with sustaining high quality of care and expedient introduction of new medical knowledge. Clinical practice guidelines (CPGs) have been promoted as a remedy to deal with these problems. It is, however, also well described that application...... and compliance with CPGs in most areas of clinical practice are deficient. Computerization of CPGs has been brought forward as a method to disseminate and to support application of CPGs. Until now, CPG-computerization has focused on development of formal expressions of CPGs. The developed systems have, however...

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

    OpenAIRE

    Soshnikov, L. E.

    2013-01-01

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

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

    National Research Council Canada - National Science Library

    I. V. Lukyanov; N. A. Demchenko

    2014-01-01

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

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

    Science.gov (United States)

    Ullah, Sana; Kwak, Kyung Sup

    2012-10-01

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

  20. 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.

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

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael

    2005-01-01

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

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  3. 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

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

    Science.gov (United States)

    Godsey, Chad; Skubic, Marjorie

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mark S. Handcock

    2007-12-01

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

  6. Designing laboratory wind simulations using artificial neural networks

    Science.gov (United States)

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

    2015-05-01

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

  7. 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.

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

    Science.gov (United States)

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

    2016-10-01

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

  9. 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...

  10. 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

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

    Science.gov (United States)

    Zhang, Jingjing; Skryabin, Maxim; Song, Xiongwei

    2016-01-01

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

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

    Science.gov (United States)

    Martyna, Jerzy

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

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

    Directory of Open Access Journals (Sweden)

    Diogo Santos

    2016-06-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  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. Vergleich vom Einsatz Standardisierter Patienten mit Computerfällen in der Psychiatrie und Psychotherapie [Training with standardized patients versus computerized case simulations in psychiatry and psychotherapy: a comparison

    Directory of Open Access Journals (Sweden)

    Mathiak, Klaus

    2010-02-01

    Full Text Available [english] Aims: In this randomized comparative study, we obtained student evaluations for training with standardized patients as well as for computerized case simulations and correlated them with the student’s learning type. Training with standardized patients was also reviewed regarding acceptance.Methods: Medical students in the 5th clinical semester (N = 222 participated in a course with standardized patients (n = 99 or in computerized case simulations (n = 123. Following the course, the students completed a questionnaire including items concerning the methodology and didactics of both courses.Results: Training with standardized patients was evaluated as superior by the students. There was no correlation with the student’s learning type. Conclusions: The results show that it is possible to compare different methods of instruction in a controlled study. Both teaching methods provide the opportunity to practice clinical skills. Particularly in a neuropsychiatric setting, training with standardized patients can complement other methods as a means of developing communication skills.[german] Zielsetzung: Im Rahmen der vorliegenden Studie wurde der Einsatz von Standardisierten Patienten mit computerbasierten Falldemonstrationen in der psychiatrischen Lehre verglichen und die Bewertungen in Relation zu den Lernstilen der Studierenden gestellt. Darüber hinaus sollte die Akzeptanz von Standardisierten Patienten als innovative Lehrform überprüft werden.Methodik: Studierende des Regelstudiengangs Medizin im 5. klinischen Semester (N=222 nahmen entweder an einem Seminar mit Standardisierten Patienten (N=99 oder an einem Seminar mit computerbasierten Falldemonstrationen (N=123 teil. Im Anschluss an den Unterricht füllten die Studierenden einen Evaluationsbogen aus, welcher Fragen zur Bewertung der Methodik und der Didaktik beider Unterrichtsformen enthielt.Ergebnisse: Die Studenten gaben dem Fallunterricht mit Standardisierten Patienten in

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

    OpenAIRE

    Gupta, Manish; Kumar, Anurag; Shorey, Rajeev

    1996-01-01

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

  18. Computerizing natural history collections.

    Science.gov (United States)

    Sunderland, Mary E

    2013-09-01

    Computers are ubiquitous in the life sciences and are associated with many of the practical and conceptual changes that characterize biology's twentieth-century transformation. Yet comparatively little has been written about how scientists use computers. Despite this relative lack of scholarly attention, the claim that computers revolutionized the life sciences by making the impossible possible is widespread, and relatively unchallenged. How did the introduction of computers into research programs shape scientific practice? The Museum of Vertebrate Zoology (MVZ) at the University of California, Berkeley provides a tractable way into this under-examined question because it is possible to follow the computerization of data in the context of long-term research programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2017-05-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

  1. 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....

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

    NARCIS (Netherlands)

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

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

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

    NARCIS (Netherlands)

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

    2008-01-01

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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  5. 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.

  6. 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,

  7. 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...

  8. 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.

  9. Closed loop performance of a brushless dc motor powered electromechanical actuator for flight control applications. [computerized simulation for Shuttle Orbiter applications

    Science.gov (United States)

    Demerdash, N. A.; Nehl, T. W.

    1980-01-01

    A comprehensive digital model for the analysis and possible optimization of the closed loop dynamic (instantaneous) performance of a power conditioner fed, brushless dc motor powered, electromechanical actuator system (EMA) is presented. This model was developed for the simulation of the dynamic performance of an actual prototype EMA built for NASA-JSC as a possible alternative to hydraulic actuators for consideration in Space Shuttle Orbiter applications. Excellent correlation was achieved between numerical model simulation and experimental test results obtained from the actual hardware. These results include: various current and voltage waveforms in the machine-power conditioner (MPC) unit, flap position as well as other control loop variables in response to step commands of change of flap position. These results with consequent conclusions are detailed in the paper.

  10. 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.

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

    Science.gov (United States)

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

    1993-01-01

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

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

    Science.gov (United States)

    Chamis, Christos C.; Coroneos, Rula M.

    2007-01-01

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

  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. Marine biology and computerization

    Digital Repository Service at National Institute of Oceanography (India)

    Parulekar, A.H.

    stream_size 3 stream_content_type text/plain stream_name Natl_Workshop_Database_Networking_Mar_Biol_1994_1.pdf.txt stream_source_info Natl_Workshop_Database_Networking_Mar_Biol_1994_1.pdf.txt Content-Encoding ISO-8859-1 Content-Type... text/plain; charset=ISO-8859-1 ...

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

    OpenAIRE

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2007-01-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  19. 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.

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

    Science.gov (United States)

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

    1990-12-01

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

  1. Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

    Science.gov (United States)

    Aybek, Eren Can; Demirtasli, R. Nukhet

    2017-01-01

    This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

  2. 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.

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

    Science.gov (United States)

    Vestergaard, Christian L.; Génois, Mathieu

    2015-01-01

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

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

    National Research Council Canada - National Science Library

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

    2015-01-01

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

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

    Science.gov (United States)

    Chang, Qiang; Lu, Yang; Quan, Donghui

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Guy Pujolle

    2010-01-01

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

  7. Comparison of performance among three systems of Clinical PET by computerized simulation; Comparacao de desempenho entre tres sistemas de PET clinico por simulacao computacional

    Energy Technology Data Exchange (ETDEWEB)

    Franze, Daniel L.; Bertolo, Antonio C.N.; Gama, Andressa F.; Moraes, Eder R. [Universidade de Sao Paulo (GIMN/USP), Ribeirao Preto, SP (Brazil). Grupo de Imagens em Medicina Nuclear

    2016-07-01

    Whereas sensitivity and spatial resolution of PET images formed in coincidence systems may exhibit improvements with reduction of the distance between the detectors. Furthermore, since the human cross section not be a circle three different detection geometries of a PET system have been simulated; a circular and two ellipticals. The performance comparison was performed by the sensitivity, resolution and the Noise Equivalent Count Rate curve. The results show that elliptical systems may experience 25% lower cost detectors, increased sensitivity to 63%. The resolution improvements introduced in X direction, large loss in the Y direction, although the use of iterative reconstruction can reduce the loss in resolution. The reduction of peak NEC curve indicates the image with better quality is achieved with lower activity of the source. (author)

  8. 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.

  9. 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.

  10. 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.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    OpenAIRE

    Sharma, Satish; Shebalkov, Mikhail

    2013-01-01

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

  13. THE VALIDITY OF HUMAN AND COMPUTERIZED WRITING ASSESSMENT

    Energy Technology Data Exchange (ETDEWEB)

    Ronald L. Boring

    2005-09-01

    This paper summarizes an experiment designed to assess the validity of essay grading between holistic and analytic human graders and a computerized grader based on latent semantic analysis. The validity of the grade was gauged by the extent to which the student’s knowledge of the topic correlated with the grader’s expert knowledge. To assess knowledge, Pathfinder networks were generated by the student essay writers, the holistic and analytic graders, and the computerized grader. It was found that the computer generated grades more closely matched the definition of valid grading than did human generated grades.

  14. Effect of massive training artificial neural networks for rib suppression on reduction of false positives in computerized detection of nodules on chest radiographs

    Science.gov (United States)

    Suzuki, Kenji; Shiraishi, Junji; Li, Feng; Abe, Hiroyuki; MacMahon, Heber; Doi, Kunio

    2005-04-01

    A major challenge in computer-aided diagnostic (CAD) schemes for nodule detection on chest radiographs is the detection of nodules that overlap with ribs. Our purpose was to develop a technique for false-positive reduction in a CAD scheme using a rib-suppression technique based on massive training artificial neural networks (MTANNs). We developed a multiple MTANN (multi-MTANN) consisting of eight MTANNs for removing eight types of false positives. For further removal of false positives caused by ribs, we developed a rib-suppression technique using a multi-resolution MTANN consisting of three different resolution MTANNs. To suppress the contrast of ribs, the multi-resolution MTANN was trained with input chest radiographs and the teaching soft-tissue images obtained by using a dual-energy subtraction technique. Our database consisted of 91 nodules in 91 chest radiographs. With our original CAD scheme based on a difference image technique with linear discriminant analysis, a sensitivity of 82.4% (75/91 nodules) with 4.5 (410/91) false positives per image was achieved. The trained multi-MTANN was able to remove 62.7% (257/410) of false positives with a loss of one true positive. With the rib-suppression technique, the contrast of ribs in chest radiographs was suppressed substantially. Due to the effect of rib-suppression, 41.2% (63/153) of the remaining false positives were removed without a loss of any true positives. Thus, the false-positive rate of our CAD scheme was improved substantially, while a high sensitivity was maintained.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-04-13

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Reisman, A; Malone, R

    1978-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-10-15

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    Wu, Ming; Chan, Christina

    2012-03-02

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

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

    Science.gov (United States)

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

    2017-02-01

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

  1. Explaining the host-finding behavior of blood-sucking insects: computerized simulation of the effects of habitat geometry on tsetse fly movement.

    Science.gov (United States)

    Vale, Glyn A; Hargrove, John W; Solano, Philippe; Courtin, Fabrice; Rayaisse, Jean-Baptiste; Lehane, Michael J; Esterhuizen, Johan; Tirados, Inaki; Torr, Stephen J

    2014-06-01

    Male and female tsetse flies feed exclusively on vertebrate blood. While doing so they can transmit the diseases of sleeping sickness in humans and nagana in domestic stock. Knowledge of the host-orientated behavior of tsetse is important in designing bait methods of sampling and controlling the flies, and in understanding the epidemiology of the diseases. For this we must explain several puzzling distinctions in the behavior of the different sexes and species of tsetse. For example, why is it that the species occupying savannahs, unlike those of riverine habitats, appear strongly responsive to odor, rely mainly on large hosts, are repelled by humans, and are often shy of alighting on baits? A deterministic model that simulated fly mobility and host-finding success suggested that the behavioral distinctions between riverine, savannah and forest tsetse are due largely to habitat size and shape, and the extent to which dense bushes limit occupiable space within the habitats. These factors seemed effective primarily because they affect the daily displacement of tsetse, reducing it by up to ∼70%. Sex differences in behavior are explicable by females being larger and more mobile than males. Habitat geometry and fly size provide a framework that can unify much of the behavior of all sexes and species of tsetse everywhere. The general expectation is that relatively immobile insects in restricted habitats tend to be less responsive to host odors and more catholic in their diet. This has profound implications for the optimization of bait technology for tsetse, mosquitoes, black flies and tabanids, and for the epidemiology of the diseases they transmit.

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

    Science.gov (United States)

    Trefalt, Špela

    2014-01-01

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

  3. 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

  4. Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT

    Science.gov (United States)

    Suzuki, Kenji; Armato, Samuel G., III; Li, Feng; Sone, Shusuke; Doi, Kunio

    2003-05-01

    In this study, we investigated a pattern-classification technique which can be trained with a small number of cases with a massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT (LDCT). The MTANN consists of a modified multilayer artificial neural network (ANN), which is capable of operating on image data directly. The MTANN is trained by use of a large number of sub-regions extracted from input images together with the teacher images containing the distribution for the "likelihood of being a nodule." The output image is obtained by scanning of an input image with the MTANN. In the MTANN, the distinction between nodules and non-nodules is treated as an image-processing task, in other words, as a highly nonlinear filter that performs both nodule enhancement and non-nodule suppression. This allows us to train the MTANN not on a case basis, but on a sub-region basis. Therefore, the MTANN can be trained with a very small number of cases. Our database consisted of 101 LDCT scans acquired from 71 patients in a lung cancer screening program. The scans consisted of 2,822 sections, and contained 121 nodules including 104 nodules representing confirmed primary cancers. With our current CAD scheme, a sensitivity of 81.0% (98/121 nodules) with 0.99 false positives per section (2,804/2,822) was achieved. By use of the MTANN trained with a small number of training cases (n=10), i.e., five pairs of nodules and non-nodules, we were able to remove 55.8% of false positives without a reduction in the number of true positives, i.e., a classification sensitivity of 100%. Thus, the false-positive rate of our current CAD scheme was reduced from 0.99 to 0.44 false positive per section, while the current sensitivity (81.0%) was maintained.

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

    OpenAIRE

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    David R. Hunter

    2008-12-01

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

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

    Science.gov (United States)

    Goldstein, Yaron Ab; Bockmayr, Alexander

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

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

    NARCIS (Netherlands)

    Koper, Rob

    2004-01-01

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

  11. 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.

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

    Science.gov (United States)

    Dillard, Leslie A.; Blunt, Martin J.

    2000-01-01

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

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

    Science.gov (United States)

    Jin, Tao; Stanciulescu, Ilinca

    2016-08-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

    Zeng, Y.

    2017-09-01

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

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

    DEFF Research Database (Denmark)

    Klingenbrunn, Thomas; Mogensen, Preben Elgaard

    2000-01-01

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

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

    CERN Document Server

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-10-28

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

  19. 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.

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

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Sørensen, O.

    2000-01-01

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

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

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Sørensen, O.

    1999-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Massimo Di Gangi

    2017-01-01

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

  3. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-01

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

  5. 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

  6. 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

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

    Indian Academy of Sciences (India)

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

  8. 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.

  9. 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.

  10. Comparing the security risks of paper-based and computerized patient record systems

    Science.gov (United States)

    Collmann, Jeff R.; Meissner, Marion C.; Tohme, Walid G.; Winchester, James F.; Mun, Seong K.

    1997-05-01

    How should hospital administrators compare the security risks of paper-based and computerized patient record systems. There is a general tendency to assume that because computer networks potentially provide broad access to hospital archives, computerized patient records are less secure than paper records and increase the risk of breaches of patient confidentiality. This assumption is ill-founded on two grounds. Reasons exist to say that the computerized patient record provides better access to patient information while enhancing overall information system security. A range of options with different trade-offs between access and security exist in both paper-based and computerized records management systems. The relative accessibility and security of any particular patient record management system depends, therefore, on administrative choice, not simply on the intrinsic features of paper or computerized information management systems.

  11. 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.

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

    Science.gov (United States)

    Yang, Shufan; Wu, Qiang; Li, Renfa

    2011-09-01

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

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

    Science.gov (United States)

    Joghataie, Abdolreza; Torghabehi, Omid Oliyan

    2014-08-01

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

  14. Computerized sociometric assessment for preschool children

    NARCIS (Netherlands)

    Endedijk, Hinke M.; Cillessen, Antonius H. N.

    2015-01-01

    In preschool classes, sociometric peer ratings are used to measure children's peer relationships. The current study examined a computerized version of preschool sociometric ratings. The psychometric properties were compared of computerized sociometric ratings and traditional peer ratings for

  15. Technologies in computerized lexicography | Kruyt | Lexikos

    African Journals Online (AJOL)

    Although the topic of this paper is technology, focus is on functional rather than technical aspects of computerized lexicography. Keywords: computerized lexicography, electronic dictionary, electronic text corpus, lexicographer's workbench, integrated language database, automatic linguistic analysis, information retrieval, ...

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

    Science.gov (United States)

    2012-12-01

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

  17. Representing Dynamic Social Networks in Discrete Event Social Simulation

    Science.gov (United States)

    2010-12-01

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

  18. Analysis and Simulation of Hybrid Models for Reaction Networks

    OpenAIRE

    Kreim, Michael

    2014-01-01

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

  19. 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

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

    Science.gov (United States)

    2006-10-26

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

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

    Science.gov (United States)

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

    2016-01-01

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

  2. 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.

  3. Computerized Proof Techniques for Undergraduates

    Science.gov (United States)

    Smith, Christopher J.; Tefera, Akalu; Zeleke, Aklilu

    2012-01-01

    The use of computer algebra systems such as Maple and Mathematica is becoming increasingly important and widespread in mathematics learning, teaching and research. In this article, we present computerized proof techniques of Gosper, Wilf-Zeilberger and Zeilberger that can be used for enhancing the teaching and learning of topics in discrete…

  4. Perspectives on Computerized Psychological Assessment.

    Science.gov (United States)

    Butcher, James N.

    1985-01-01

    Psychological assessment, a subspecialty of psychology has served as one of the earliest proving grounds of automated technology. This Special Series highlights some of the advances in computerized psychological assessment methods and discusses some of the lingering issues and contemporary problems with automated psychological assessment…

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

    Directory of Open Access Journals (Sweden)

    Li Jin

    2014-04-01

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

  6. 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.

  7. 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...

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

    Science.gov (United States)

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

    2011-01-14

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

  9. 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.

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

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-04-01

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

  11. Computer simulation of a novel pharmaceutical silicon nanocarrier

    Directory of Open Access Journals (Sweden)

    Saeed Soltani

    2010-11-01

    Full Text Available Saeed Soltani, Soroush Sardari, Sima Azadi SororDrug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, IranAbstract: We show the potential of the nanosilicon structure of the frustules of a typical diatom, Cymatopleura sp., as a new vehicle for drugs. The basic diatom nanostructure is a lattice of SiO2, and computerized methods in a dock project have identified the most likely and the best drug types to load into such a structure.Keywords: diatom, docking, artificial neural network, simulation, computerized methods

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

    Science.gov (United States)

    2017-03-03

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

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

    OpenAIRE

    Goldstein, Yaron AB; Bockmayr, Alexander

    2015-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  15. Attaining Realistic Simulations of Mobile Ad-hoc Networks

    Science.gov (United States)

    2010-06-01

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

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

    Science.gov (United States)

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

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

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

    National Research Council Canada - National Science Library

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2011-02-01

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

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Kit eCheung

    2016-01-01

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

  1. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2010-09-01

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

  4. 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

  5. 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.

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

    Science.gov (United States)

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

    2017-11-08

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

  7. 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...

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

    Science.gov (United States)

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

    2012-02-01

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

  9. Agent-based simulations of emotion spreading in online social networks

    CERN Document Server

    Šuvakov, Milovan; Schweitzer, Frank; Tadić, Bosiljka

    2012-01-01

    Quantitative analysis of empirical data from online social networks reveals group dynamics in which emotions are involved (\\v{S}uvakov et al). Full understanding of the underlying mechanisms, however, remains a challenging task. Using agent-based computer simulations, in this paper we study dynamics of emotional communications in online social networks. The rules that guide how the agents interact are motivated, and the realistic network structure and some important parameters are inferred from the empirical dataset of \\texttt{MySpace} social network. Agent's emotional state is characterized by two variables representing psychological arousal---reactivity to stimuli, and valence---attractiveness or aversiveness, by which common emotions can be defined. Agent's action is triggered by increased arousal. High-resolution dynamics is implemented where each message carrying agent's emotion along the network link is identified and its effect on the recipient agent is considered as continuously aging in time. Our res...

  10. 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.

  11. 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.

  12. 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.

  13. High power fuel cell simulator based on artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Chavez-Ramirez, Abraham U.; Munoz-Guerrero, Roberto [Departamento de Ingenieria Electrica, CINVESTAV-IPN. Av. Instituto Politecnico Nacional No. 2508, D.F. CP 07360 (Mexico); Duron-Torres, S.M. [Unidad Academica de Ciencias Quimicas, Universidad Autonoma de Zacatecas, Campus Siglo XXI, Edif. 6 (Mexico); Ferraro, M.; Brunaccini, G.; Sergi, F.; Antonucci, V. [CNR-ITAE, Via Salita S. Lucia sopra Contesse 5-98126 Messina (Italy); Arriaga, L.G. [Centro de Investigacion y Desarrollo Tecnologico en Electroquimica S.C., Parque Tecnologico Queretaro, Sanfandila, Pedro Escobedo, Queretaro (Mexico)

    2010-11-15

    Artificial Neural Network (ANN) has become a powerful modeling tool for predicting the performance of complex systems with no well-known variable relationships due to the inherent properties. A commercial Polymeric Electrolyte Membrane fuel cell (PEMFC) stack (5 kW) was modeled successfully using this tool, increasing the number of test into the 7 inputs - 2 outputs-dimensional spaces in the shortest time, acquiring only a small amount of experimental data. Some parameters could not be measured easily on the real system in experimental tests; however, by receiving the data from PEMFC, the ANN could be trained to learn the internal relationships that govern this system, and predict its behavior without any physical equations. Confident accuracy was achieved in this work making possible to import this tool to complex systems and applications. (author)

  14. Realistic computerized human phantoms

    Science.gov (United States)

    Zankl, M.; Veit, R.; Petoussi, N.; Mannweiler, E.; Wittmann, A.; Drexler, G.

    1994-10-01

    To estimate the risk resulting from exposures to ionizing radiation, the organ and tissue doses should be assessed. A convenient method is the calculation of these doses using representations of the human body, called models or phantoms, together with computer codes simulating the transport of radiation in the body. Most commonly used are mathematical phantoms whose external and internal volumes are defined by simple geometric bodies. More recently, phantoms constructed from computed tomographic data of real persons were introduced as an improvement. These phantoms present advantages concerning the location and shape of the organs, in particular the hard bone and bone marrow, whose distribution can be assessed with high resolution. So far, three of these phantoms were constructed at the GSF, a fourth is under process. The construction technique is described, and some calculational results of organ doses due to external photon irradiation are presented.

  15. Enhancing the NS-2 Network Simulator for Near Real-Time Control Feedback and Distributed Simulation

    Science.gov (United States)

    2009-03-21

    visualization of the simulation as it executes. 12 III. Command Feedback Design and Implementation U ser -simulator interaction is the key driver of this...TCL script. As the TCL script is parsed, a SocketListener object is created within C++. The SocketLis- tener object creates a new Boost::Thread [4] and

  16. Some issues related to simulation of the tracking and communications computer network

    Science.gov (United States)

    Lacovara, Robert C.

    1989-01-01

    The Communications Performance and Integration branch of the Tracking and Communications Division has an ongoing involvement in the simulation of its flight hardware for Space Station Freedom. Specifically, the communication process between central processor(s) and orbital replaceable units (ORU's) is simulated with varying degrees of fidelity. The results of investigations into three aspects of this simulation effort are given. The most general area involves the use of computer assisted software engineering (CASE) tools for this particular simulation. The second area of interest is simulation methods for systems of mixed hardware and software. The final area investigated is the application of simulation methods to one of the proposed computer network protocols for space station, specifically IEEE 802.4.

  17. 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.

  18. The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

    Science.gov (United States)

    Kunkel, Susanne; Schenck, Wolfram

    2017-01-01

    NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling. PMID:28701946

  19. The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code.

    Science.gov (United States)

    Kunkel, Susanne; Schenck, Wolfram

    2017-01-01

    NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

  20. ezBioNet: A modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2012-10-01

    To achieve robustness against living environments, a living organism is composed of complicated regulatory mechanisms ranging from gene regulations to signal transduction. If such life phenomena are to be understand, an integrated analysis tool that should have modeling and simulation functions for biological reactions, as well as new experimental methods for measuring biological phenomena, is fundamentally required. We have designed and implemented modeling and simulation software (ezBioNet) for analyzing biological reaction networks. The software can simultaneously perform an integrated modeling of various responses occurring in cells, ranging from gene expressions to signaling processes. To support massive analysis of biological networks, we have constructed a server-side simulation system (VCellSim) that can perform ordinary differential equations (ODE) analysis, sensitivity analysis, and parameter estimates. ezBioNet integrates the BioModel database by connecting the european bioinformatics institute (EBI) servers through Web services APIs and supports the handling of systems biology markup language (SBML) files. In addition, we employed eclipse RCP (rich client platform) which is a powerful modularity framework allowing various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool, as well as a simulation system, to understand the control mechanism by monitoring the change of each component in a biological network. A researcher may perform the kinetic modeling and execute the simulation. The simulation result can be managed and visualized on ezBioNet, which is freely available at http://ezbionet.cbnu.ac.kr.

  1. 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.

  2. Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

    Science.gov (United States)

    Christensen, Claire Petra

    Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author

  3. 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.

  4. A COMPUTERIZED OPERATOR SUPPORT SYSTEM PROTOTYPE

    Energy Technology Data Exchange (ETDEWEB)

    Thomas A. Ulrich; Roger Lew; Ronald L. Boring; Ken Thomas

    2015-03-01

    A computerized operator support system (COSS) is proposed for use in nuclear power plants to assist control room operators in addressing time-critical plant upsets. A COSS is a collection of technologies to assist operators in monitoring overall plant performance and making timely, informed decisions on appropriate control actions for the projected plant condition. A prototype COSS was developed in order to demonstrate the concept and provide a test bed for further research. The prototype is based on four underlying elements consisting of a digital alarm system, computer-based procedures, piping and instrumentation diagram system representations, and a recommender module for mitigation actions. The initial version of the prototype is now operational at the Idaho National Laboratory using the Human System Simulation Laboratory.

  5. Termination Criteria for Computerized Classification Testing

    Directory of Open Access Journals (Sweden)

    Nathan A. Thompson

    2011-02-01

    Full Text Available Computerized classification testing (CCT is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as - pass- and - fail.- Like adaptive testing for point estimation of ability, the key component is the termination criterion, namely the algorithm that decides whether to classify the examinee and end the test or to continue and administer another item. This paper applies a newly suggested termination criterion, the generalized likelihood ratio (GLR, to CCT. It also explores the role of the indifference region in the specification of likelihood-ratio based termination criteria, comparing the GLR to the sequential probability ratio test. Results from simulation studies suggest that the GLR is always at least as efficient as existing methods.

  6. Interfacing Space Communications and Navigation Network Simulation with Distributed System Integration Laboratories (DSIL)

    Science.gov (United States)

    Jennings, Esther H.; Nguyen, Sam P.; Wang, Shin-Ywan; Woo, Simon S.

    2008-01-01

    NASA's planned Lunar missions will involve multiple NASA centers where each participating center has a specific role and specialization. In this vision, the Constellation program (CxP)'s Distributed System Integration Laboratories (DSIL) architecture consist of multiple System Integration Labs (SILs), with simulators, emulators, testlabs and control centers interacting with each other over a broadband network to perform test and verification for mission scenarios. To support the end-to-end simulation and emulation effort of NASA' exploration initiatives, different NASA centers are interconnected to participate in distributed simulations. Currently, DSIL has interconnections among the following NASA centers: Johnson Space Center (JSC), Kennedy Space Center (KSC), Marshall Space Flight Center (MSFC) and Jet Propulsion Laboratory (JPL). Through interconnections and interactions among different NASA centers, critical resources and data can be shared, while independent simulations can be performed simultaneously at different NASA locations, to effectively utilize the simulation and emulation capabilities at each center. Furthermore, the development of DSIL can maximally leverage the existing project simulation and testing plans. In this work, we describe the specific role and development activities at JPL for Space Communications and Navigation Network (SCaN) simulator using the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to simulate communications effects among mission assets. Using MACHETE, different space network configurations among spacecrafts and ground systems of various parameter sets can be simulated. Data that is necessary for tracking, navigation, and guidance of spacecrafts such as Crew Exploration Vehicle (CEV), Crew Launch Vehicle (CLV), and Lunar Relay Satellite (LRS) and orbit calculation data are disseminated to different NASA centers and updated periodically using the High Level Architecture (HLA). In

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

    CERN Document Server

    Colombo, Tommaso; The ATLAS collaboration

    2015-01-01

    The ATLAS detector at CERN records particle collision “events” delivered by the Large Hadron Collider. Its data-acquisition system is a distributed software system that identifies, selects, and stores interesting events in near real-time, with an aggregate throughput of several 10 GB/s. It is a distributed software system executed on a farm of roughly 2000 commodity worker nodes communicating via TCP/IP on an Ethernet network. Event data fragments are received from the many detector readout channels and are buffered, collected together, analyzed and either stored permanently or discarded. This system, and data-acquisition systems in general, are sensitive to the latency of the data transfer from the readout buffers to the worker nodes. Challenges affecting this transfer include the many-to-one communication pattern and the inherently bursty nature of the traffic. In this paper we introduce the main performance issues brought about by this workload, focusing in particular on the so-called TCP incast pathol...

  8. Simulation and Noise Analysis of Multimedia Transmission in Optical CDMA Computer Networks

    Directory of Open Access Journals (Sweden)

    Nasaruddin Nasaruddin

    2013-09-01

    Full Text Available This paper simulates and analyzes noise of multimedia transmission in a flexible optical code division multiple access (OCDMA computer network with different quality of service (QoS requirements. To achieve multimedia transmission in OCDMA, we have proposed strict variable-weight optical orthogonal codes (VW-OOCs, which can guarantee the smallest correlation value of one by the optimal design. In developing multimedia transmission for computer network, a simulation tool is essential in analyzing the effectiveness of various transmissions of services. In this paper, implementation models are proposed to analyze the multimedia transmission in the representative of OCDMA computer networks by using MATLAB simulink tools. Simulation results of the models are discussed including spectrums outputs of transmitted signals, superimposed signals, received signals, and eye diagrams with and without noise. Using the proposed models, multimedia OCDMA computer network using the strict VW-OOC is practically evaluated. Furthermore, system performance is also evaluated by considering avalanche photodiode (APD noise and thermal noise. The results show that the system performance depends on code weight, received laser power, APD noise, and thermal noise which should be considered as important parameters to design and implement multimedia transmission in OCDMA computer networks.

  9. An enhanced simulated annealing routing algorithm for semi-diagonal torus network

    Science.gov (United States)

    Adzhar, Noraziah; Salleh, Shaharuddin

    2017-09-01

    Multiprocessor is another great technology that helps in advancing human civilization due to high demands for solving complex problems. A multiprocessing system can have a lot of replicated processor-memory pairs (henceforth regard as net) or also called as processing nodes. Each of these nodes is connected to each other through interconnection networks and passes message using a standard message passing mechanism. In this paper, we present a routing algorithm based on enhanced simulated annealing technique to provide the connection between nodes in a semi-diagonal torus (SD-Torus) network. This network is both symmetric and regular; thus, make it very beneficial in the implementation process. The main objective is to maximize the number of established connection between nodes in this SD-Torus network. In order to achieve this objective, each node must be connected in its shortest way as possible. We start our algorithm by designing shortest path algorithm based on Dijkstra’s method. While this algorithm guarantees to find the shortest path for each single net, if it exists, each routed net will form obstacle for later paths. This increases the complexity to route later nets and makes routing longer than optimal, or sometimes impossible to complete. The solution is further refined by re-routing all nets in different orders using simulated annealing method. Through simulation program, our proposed algorithm succeeded in performing complete routing up to 81 nodes with 40 nets in 9×9 SD-Torus network size.

  10. Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

    Science.gov (United States)

    Calvin, Nicholas T; J McDowell, J

    2015-11-01

    For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Simulation and Noise Analysis of Multimedia Transmission in Optical CDMA Computer Networks

    Directory of Open Access Journals (Sweden)

    Nasaruddin

    2009-11-01

    Full Text Available This paper simulates and analyzes noise of multimedia transmission in a flexible optical code division multiple access (OCDMA computer network with different quality of service (QoS requirements. To achieve multimedia transmission in OCDMA, we have proposed strict variable-weight optical orthogonal codes (VW-OOCs, which can guarantee the smallest correlation value of one by the optimal design. In developing multimedia transmission for computer network, a simulation tool is essential in analyzing the effectiveness of various transmissions of services. In this paper, implementation models are proposed to analyze the multimedia transmission in the representative of OCDMA computer networks by using MATLAB simulink tools. Simulation results of the models are discussed including spectrums outputs of transmitted signals, superimposed signals, received signals, and eye diagrams with and without noise. Using the proposed models, multimedia OCDMA computer network using the strict VW-OOC is practically evaluated. Furthermore, system performance is also evaluated by considering avalanche photodiode (APD noise and thermal noise. The results show that the system performance depends on code weight, received laser power, APD noise, and thermal noise which should be considered as important parameters to design and implement multimedia transmission in OCDMA computer networks.

  12. Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

    Directory of Open Access Journals (Sweden)

    Joshua Rodewald

    2016-10-01

    Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

  13. Lattice Boltzmann simulation of fluid flow in fracture networks with rough, self-affine surfaces.

    Science.gov (United States)

    Madadi, Mahyar; Sahimi, Muhammad

    2003-02-01

    Using the lattice Boltzmann method, we study fluid flow in a two-dimensional (2D) model of fracture network of rock. Each fracture in a square network is represented by a 2D channel with rough, self-affine internal surfaces. Various parameters of the model, such as the connectivity and the apertures of the fractures, the roughness profile of their surface, as well as the Reynolds number for flow of the fluid, are systematically varied in order to assess their effect on the effective permeability of the fracture network. The distribution of the fractures' apertures is approximated well by a log-normal distribution, which is consistent with experimental data. Due to the roughness of the fractures' surfaces, and the finite size of the networks that can be used in the simulations, the fracture network is anisotropic. The anisotropy increases as the connectivity of the network decreases and approaches the percolation threshold. The effective permeability K of the network follows the power law K approximately (beta), where is the average aperture of the fractures in the network and the exponent beta may depend on the roughness exponent. A crossover from linear to nonlinear flow regime is obtained at a Reynolds number Re approximately O(1), but the precise numerical value of the crossover Re depends on the roughness of the fractures' surfaces.

  14. Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

    Science.gov (United States)

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

    2016-01-01

    It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

  15. Simulation and evaluation of urban rail transit network based on multi-agent approach

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2013-03-01

    Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

  16. Distributed Particle Swarm Optimization and Simulated Annealing for Energy-efficient Coverage in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2007-05-01

    Full Text Available The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, we focus on energy-efficient coverage with distributed particle swarm optimization and simulated annealing. First, the energy-efficient coverage problem is formulated with sensing coverage and energy consumption models. We consider the network composed of stationary and mobile nodes. Second, coverage and energy metrics are presented to evaluate the coverage rate and energy consumption of a wireless sensor network, where a grid exclusion algorithm extracts the coverage state and Dijkstra’s algorithm calculates the lowest cost path for communication. Then, a hybrid algorithm optimizes the energy consumption, in which particle swarm optimization and simulated annealing are combined to find the optimal deployment solution in a distributed manner. Simulated annealing is performed on multiple wireless sensor nodes, results of which are employed to correct the local and global best solution of particle swarm optimization. Simulations of wireless sensor node deployment verify that coverage performance can be guaranteed, energy consumption of communication is conserved after deployment optimization and the optimization performance is boosted by the distributed algorithm. Moreover, it is demonstrated that energy efficiency of wireless sensor networks is enhanced by the proposed optimization algorithm in target tracking applications.

  17. Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

    Science.gov (United States)

    Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

    2011-01-01

    Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

  18. Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2017-01-01

    Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

  19. Simulation of emotions of agents in virtual environments using neural networks

    NARCIS (Netherlands)

    van Kesteren, A.-J.; van Kesteren, A.J.; op den Akker, Hendrikus J.A.; Poel, Mannes; Jokinen, K.; Heylen, Dirk K.J.; Nijholt, Antinus

    2000-01-01

    A distributed architecture for a system simulating the emotional state of an agent acting in a virtual environment is presented. The system is an implementation of an event appraisal model of emotional behaviour and uses neural networks to learn how the emotional state should be influenced by the

  20. Neural networks simulation of a discrete model of continious effects of irrelevant stimuli

    NARCIS (Netherlands)

    Molenaar, P.C.M.

    1990-01-01

    Presents a general simulation method based on minimal neural network representations of nonmathematical, structural models of information processes. The time-dependent behavior of each component in a given structural model is represented by a simple, noncommittal equation that does not affect the

  1. Use of a neural network to extract a missile flight model for simulation purposes

    Science.gov (United States)

    Pascale, Danny; Volckaert, Guy

    1996-03-01

    A neural network is used to extract the flight model of guided, short to medium range, tripod and shoulder-fired missile systems which is then integrated into a training simulator. The simulator uses injected video to replace the optical sight and is fitted with a multi-axis positioning system which senses the gunner's movement. The movement creates an image shift and affects the input data to the missile control algorithm. Accurate flight dynamics are a key to efficient training, particularly in the case of closed loop guided systems. However, flight model data is not always available, either because it is proprietary, or because it is too complex to embed in a real time simulator. A solution is to reverse engineer the flight model by analyzing the missile's response when submitted to typical input conditions. Training data can be extracted from either recorded video or from a combination of weapon and missile positioning data. The video camera can be located either on the weapon or attached to a through-sight adapter. No knowledge of the missile flight transfer function is used in the process. The data is fed to a three-layer back-propagation type neural network. The network is configured within a standard spreadsheet application and is optimized with the built-in solver functions. The structure of the network, the selected inputs and outputs, as well as training data, output data after training, and output data when embedded in the simulator are presented.

  2. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks

    Science.gov (United States)

    Slepoy, Alexander; Thompson, Aidan P.; Plimpton, Steven J.

    2008-05-01

    The time evolution of species concentrations in biochemical reaction networks is often modeled using the stochastic simulation algorithm (SSA) [Gillespie, J. Phys. Chem. 81, 2340 (1977)]. The computational cost of the original SSA scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [Gibson and Bruck, J. Phys. Chem. A 104, 1876 (2000)]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure. While applicable to kinetic Monte Carlo simulations in general, we describe the algorithm in the context of biochemical simulations and demonstrate its competitive performance on small- and medium-size networks, as well as its superior constant-time performance on very large networks, which are becoming necessary to represent the increasing complexity of biochemical data for pathways that mediate cell function.

  3. A hybrid Genetic and Simulated Annealing Algorithm for Chordal Ring implementation in large-scale networks

    DEFF Research Database (Denmark)

    Riaz, M. Tahir; Gutierrez Lopez, Jose Manuel; Pedersen, Jens Myrup

    2011-01-01

    of the networks. There have been many use of evolutionary algorithms to solve the problems which are in combinatory complexity nature, and extremely hard to solve by exact approaches. Both Genetic and Simulated annealing algorithms are similar in using controlled stochastic method to search the solution...

  4. Largenet2: an object-oriented programming library for simulating large adaptive networks.

    Science.gov (United States)

    Zschaler, Gerd; Gross, Thilo

    2013-01-15

    The largenet2 C++ library provides an infrastructure for the simulation of large dynamic and adaptive networks with discrete node and link states. The library is released as free software. It is available at http://biond.github.com/largenet2. Largenet2 is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. gerd@biond.org

  5. Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics

    DEFF Research Database (Denmark)

    Papaleo, Elena

    2015-01-01

    that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome...... simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations....

  6. An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

    Science.gov (United States)

    Leon, Barbara D.; Heller, Paul R.

    1987-05-01

    A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system

  7. Cellular neural network modelling of soft tissue dynamics for surgical simulation.

    Science.gov (United States)

    Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

    2017-07-20

    Currently, the mechanical dynamics of soft tissue deformation is achieved by numerical time integrations such as the explicit or implicit integration; however, the explicit integration is stable only under a small time step, whereas the implicit integration is computationally expensive in spite of the accommodation of a large time step. This paper presents a cellular neural network method for stable simulation of soft tissue deformation dynamics. The non-rigid motion equation is formulated as a cellular neural network with local connectivity of cells, and thus the dynamics of soft tissue deformation is transformed into the neural dynamics of the cellular neural network. Results show that the proposed method can achieve good accuracy at a small time step. It still remains stable at a large time step, while maintaining the computational efficiency of the explicit integration. The proposed method can achieve stable soft tissue deformation with efficiency of explicit integration for surgical simulation.

  8. Simulating Local Area Network Protocols with the General Purpose Simulation System (GPSS)

    Science.gov (United States)

    1990-03-01

    because of insufficient buffer capacity ), and the mean transmitter and receiver utilisations. Figure 11 shows that the buffer overflow probability is...made. (1) Infinite buffer capacity at each station (2) 1 M bit/s data rate (3) Network of 50 stations equally spaced over a 2000 m length ring (4

  9. Fractional Diffusion Emulates a Human Mobility Network during a Simulated Disease Outbreak

    Directory of Open Access Journals (Sweden)

    Kyle B. Gustafson

    2017-04-01

    Full Text Available Mobility networks facilitate the growth of populations, the success of invasive species, and the spread of communicable diseases among social animals, including humans. Disease control and elimination efforts, especially during an outbreak, can be optimized by numerical modeling of disease dynamics on transport networks. This is especially true when incidence data from an emerging epidemic is sparse and unreliable. However, mobility networks can be complex, challenging to characterize, and expensive to simulate with agent-based models. We therefore studied a parsimonious model for spatiotemporal disease dynamics based on a fractional diffusion equation. We implemented new stochastic simulations of a prototypical influenza-like infection spreading through the United States' highly-connected air travel network. We found that the national-averaged infected fraction during an outbreak is accurately reproduced by a space-fractional diffusion equation consistent with the connectivity of airports. Fractional diffusion therefore seems to be a better model of network outbreak dynamics than a diffusive model. Our fractional reaction-diffusion method and the result could be extended to other mobility networks in a variety of applications for population dynamics.

  10. Building Model for the University of Mosul Computer Network Using OPNET Simulator

    Directory of Open Access Journals (Sweden)

    Modhar Modhar A. Hammoudi

    2013-04-01

    Full Text Available This paper aims at establishing a model in OPNET (Optimized Network Engineering Tool simulator for the University of Mosul computer network. The proposed network model was made up of two routers (Cisco 2600, core switch (Cisco6509, two servers, ip 32 cloud and 37 VLANs. These VLANs were connected to the core switch using fiber optic cables (1000BaseX. Three applications were added to test the network model. These applications were FTP (File Transfer Protocol, HTTP (Hyper Text Transfer Protocol and VoIP (Voice over Internet Protocol. The results showed that the proposed model had a positive efficiency on designing and managing the targeted network and can be used to view the data flow in it. Also, the simulation results showed that the maximum number of VoIP service users could be raised upto 5000 users when working under IP Telephony. This means that the ability to utilize VoIP service in this network can be maintained and is better when subjected to IP telephony scheme.

  11. Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

    Science.gov (United States)

    Davis, Paul; Boisvert, Benjamin

    2017-01-01

    The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

  12. Architecture for an integrated real-time air combat and sensor network simulation

    Science.gov (United States)

    Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara

    2007-04-01

    An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.

  13. Simulated Annealing Technique for Routing in a Rectangular Mesh Network

    Directory of Open Access Journals (Sweden)

    Noraziah Adzhar

    2014-01-01

    Full Text Available In the process of automatic design for printed circuit boards (PCBs, the phase following cell placement is routing. On the other hand, routing process is a notoriously difficult problem, and even the simplest routing problem which consists of a set of two-pin nets is known to be NP-complete. In this research, our routing region is first tessellated into a uniform Nx×Ny array of square cells. The ultimate goal for a routing problem is to achieve complete automatic routing with minimal need for any manual intervention. Therefore, shortest path for all connections needs to be established. While classical Dijkstra’s algorithm guarantees to find shortest path for a single net, each routed net will form obstacles for later paths. This will add complexities to route later nets and make its routing longer than the optimal path or sometimes impossible to complete. Today’s sequential routing often applies heuristic method to further refine the solution. Through this process, all nets will be rerouted in different order to improve the quality of routing. Because of this, we are motivated to apply simulated annealing, one of the metaheuristic methods to our routing model to produce better candidates of sequence.

  14. Teleradiology system analysis using a discrete event-driven block-oriented network simulator

    Science.gov (United States)

    Stewart, Brent K.; Dwyer, Samuel J., III

    1992-07-01

    Performance evaluation and trade-off analysis are the central issues in the design of communication networks. Simulation plays an important role in computer-aided design and analysis of communication networks and related systems, allowing testing of numerous architectural configurations and fault scenarios. We are using the Block Oriented Network Simulator (BONeS, Comdisco, Foster City, CA) software package to perform discrete, event- driven Monte Carlo simulations in capacity planning, tradeoff analysis and evaluation of alternate architectures for a high-speed, high-resolution teleradiology project. A queuing network model of the teleradiology system has been devise, simulations executed and results analyzed. The wide area network link uses a switched, dial-up N X 56 kbps inverting multiplexer where the number of digital voice-grade lines (N) can vary from one (DS-0) through 24 (DS-1). The proposed goal of such a system is 200 films (2048 X 2048 X 12-bit) transferred between a remote and local site in an eight hour period with a mean delay time less than five minutes. It is found that: (1) the DS-1 service limit is around 100 films per eight hour period with a mean delay time of 412 +/- 39 seconds, short of the goal stipulated above; (2) compressed video teleconferencing can be run simultaneously with image data transfer over the DS-1 wide area network link without impacting the performance of the described teleradiology system; (3) there is little sense in upgrading to a higher bandwidth WAN link like DS-2 or DS-3 for the current system; and (4) the goal of transmitting 200 films in an eight hour period with a mean delay time less than five minutes can be achieved simply if the laser printer interface is updated from the current DR-11W interface to a much faster SCSI interface.

  15. Simulating microinjection experiments in a novel model of the rat sleep-wake regulatory network.

    Science.gov (United States)

    Diniz Behn, Cecilia G; Booth, Victoria

    2010-04-01

    This study presents a novel mathematical modeling framework that is uniquely suited to investigating the structure and dynamics of the sleep-wake regulatory network in the brain stem and hypothalamus. It is based on a population firing rate model formalism that is modified to explicitly include concentration levels of neurotransmitters released to postsynaptic populations. Using this framework, interactions among primary brain stem and hypothalamic neuronal nuclei involved in rat sleep-wake regulation are modeled. The model network captures realistic rat polyphasic sleep-wake behavior consisting of wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep states. Network dynamics include a cyclic pattern of NREM sleep, REM sleep, and wake states that is disrupted by simulated variability of neurotransmitter release and external noise to the network. Explicit modeling of neurotransmitter concentrations allows for simulations of microinjections of neurotransmitter agonists and antagonists into a key wake-promoting population, the locus coeruleus (LC). Effects of these simulated microinjections on sleep-wake states are tracked and compared with experimental observations. Agonist/antagonist pairs, which are presumed to have opposing effects on LC activity, do not generally induce opposing effects on sleep-wake patterning because of multiple mechanisms for LC activation in the network. Also, different agents, which are presumed to have parallel effects on LC activity, do not induce parallel effects on sleep-wake patterning because of differences in the state dependence or independence of agonist and antagonist action. These simulation results highlight the utility of formal mathematical modeling for constraining conceptual models of the sleep-wake regulatory network.

  16. SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method.

    Science.gov (United States)

    Bernal, Javier; Torres-Jimenez, Jose

    2015-01-01

    SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.

  17. Efficient Constant-Time Complexity Algorithm for Stochastic Simulation of Large Reaction Networks.

    Science.gov (United States)

    Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado

    2017-01-01

    Exact stochastic simulation is an indispensable tool for a quantitative study of biochemical reaction networks. The simulation realizes the time evolution of the model by randomly choosing a reaction to fire and update the system state according to a probability that is proportional to the reaction propensity. Two computationally expensive tasks in simulating large biochemical networks are the selection of next reaction firings and the update of reaction propensities due to state changes. We present in this work a new exact algorithm to optimize both of these simulation bottlenecks. Our algorithm employs the composition-rejection on the propensity bounds of reactions to select the next reaction firing. The selection of next reaction firings is independent of the number reactions while the update of propensities is skipped and performed only when necessary. It therefore provides a favorable scaling for the computational complexity in simulating large reaction networks. We benchmark our new algorithm with the state of the art algorithms available in literature to demonstrate its applicability and efficiency.

  18. Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

    Directory of Open Access Journals (Sweden)

    Wang Chao

    2016-03-01

    Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

  19. Operator Splitting Method for Simulation of Dynamic Flows in Natural Gas Pipeline Networks

    CERN Document Server

    Dyachenko, Sergey A; Chertkov, Michael

    2016-01-01

    We develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.

  20. Simulation of Missile Autopilot with Two-Rate Hybrid Neural Network System

    Directory of Open Access Journals (Sweden)

    ASTROV, I.

    2007-04-01

    Full Text Available This paper proposes a two-rate hybrid neural network system, which consists of two artificial neural network subsystems. These neural network subsystems are used as the dynamic subsystems controllers.1 This is because such neuromorphic controllers are especially suitable to control complex systems. An illustrative example - two-rate neural network hybrid control of decomposed stochastic model of a rigid guided missile over different operating conditions - was carried out using the proposed two-rate state-space decomposition technique. This example demonstrates that this research technique results in simplified low-order autonomous control subsystems with various speeds of actuation, and shows the quality of the proposed technique. The obtained results show that the control tasks for the autonomous subsystems can be solved more qualitatively than for the original system. The simulation and animation results with use of software package Simulink demonstrate that this research technique would work for real-time stochastic systems.

  1. Operator splitting method for simulation of dynamic flows in natural gas pipeline networks

    Science.gov (United States)

    Dyachenko, Sergey A.; Zlotnik, Anatoly; Korotkevich, Alexander O.; Chertkov, Michael

    2017-12-01

    We develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.

  2. Simulation of unsteady flow and solute transport in a tidal river network

    Science.gov (United States)

    Zhan, X.

    2003-01-01

    A mathematical model and numerical method for water flow and solute transport in a tidal river network is presented. The tidal river network is defined as a system of open channels of rivers with junctions and cross sections. As an example, the Pearl River in China is represented by a network of 104 channels, 62 nodes, and a total of 330 cross sections with 11 boundary section for one of the applications. The simulations are performed with a supercomputer for seven scenarios of water flow and/or solute transport in the Pearl River, China, with different hydrological and weather conditions. Comparisons with available data are shown. The intention of this study is to summarize previous works and to provide a useful tool for water environmental management in a tidal river network, particularly for the Pearl River, China.

  3. 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.

  4. 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.

  5. 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.

  6. Numerical Simulation of Fluid Flow through Fractal-Based Discrete Fractured Network

    Directory of Open Access Journals (Sweden)

    Wendong Wang

    2018-01-01

    Full Text Available Abstract: In recent years, multi-stage hydraulic fracturing technologies have greatly facilitated the development of unconventional oil and gas resources. However, a quantitative description of the “complexity” of the fracture network created by the hydraulic fracturing is confronted with many unsolved challenges. Given the multiple scales and heterogeneity of the fracture system, this study proposes a “bifurcated fractal” model to quantitatively describe the distribution of induced hydraulic fracture networks. The construction theory is employed to generate hierarchical fracture patterns as a scaled numerical model. With the implementation of discrete fractal-fracture network modeling (DFFN, fluid flow characteristics in bifurcated fractal fracture networks are characterized. The effects of bifurcated fracture length, bifurcated tendency, and number of bifurcation stages are examined. A field example of the fractured horizontal well is introduced to calibrate the accuracy of the flow model. The proposed model can provide a more realistic representation of complex fracture networks around a fractured horizontal well, and offer the way to quantify the “complexity” of the fracture network in shale reservoirs. The simulation results indicate that the geometry of the bifurcated fractal fracture network model has a significant impact on production performance in the tight reservoir, and enhancing connectivity of each bifurcate fracture is the key to improve the stimulation performance. In practice, this work provides a novel and efficient workflow for complex fracture characterization and production prediction in naturally-fractured reservoirs of multi-stage fractured horizontal wells.

  7. 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.

  8. USING THE RANDOM OF QUANTIZATION IN THE SIMULATION OF NETWORKED CONTROL SYSTEMS

    Directory of Open Access Journals (Sweden)

    V. K. Bitiukov

    2014-01-01

    Full Text Available Network control systems using a network channel for communication between the elements. This approach has several advantages: lower installation costs, ease of configuration, ease of diagnostics and maintenance. The use of networks in control systems poses new problems. The network characteristics make the analysis, modeling, and control of networked control systems more complex and challenging. In the simulation must consider the following factors: packet loss, packet random time over the network, the need for location records in a channel simultaneously multiple data packets with sequential transmission. Attempts to account at the same time all of these factors lead to a significant increase in the dimension of the mathematical model and, as a con-sequence, a significant computational challenges. Such models tend to have a wide application in research. However, for engineering calculations required mathematical models of small dimension, but at the same time having sufficient accuracy. Considered the networks channels with random delays and packet loss. Random delay modeled by appropriate distribution the Erlang. The probability of packet loss depends on the arrival rate of data packets in the transmission channel, and the parameters of the distribution Erlang. We propose a model of the channel in the form of a serial connection of discrete elements. Discrete elements produce independents quantization of the input signal. To change the probability of packet loss is proposed to use a random quantization input signal. Obtained a formula to determine the probability of packet loss during transmission.

  9. A vascular image registration method based on network structure and circuit simulation.

    Science.gov (United States)

    Chen, Li; Lian, Yuxi; Guo, Yi; Wang, Yuanyuan; Hatsukami, Thomas S; Pimentel, Kristi; Balu, Niranjan; Yuan, Chun

    2017-05-02

    Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods.

  10. 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.

  11. Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer.

    Science.gov (United States)

    ElKalaawy, Nesma; Wassal, Amr

    2015-03-01

    Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Simulated apoptosis/neurogenesis regulates learning and memory capabilities of adaptive neural networks.

    Science.gov (United States)

    Chambers, R Andrew; Potenza, Marc N; Hoffman, Ralph E; Miranker, Willard

    2004-04-01

    Characterization of neuronal death and neurogenesis in the adult brain of birds, humans, and other mammals raises the possibility that neuronal turnover represents a special form of neuroplasticity associated with stress responses, cognition, and the pathophysiology and treatment of psychiatric disorders. Multilayer neural network models capable of learning alphabetic character representations via incremental synaptic connection strength changes were used to assess additional learning and memory effects incurred by simulation of coordinated apoptotic and neurogenic events in the middle layer. Using a consistent incremental learning capability across all neurons and experimental conditions, increasing the number of middle layer neurons undergoing turnover increased network learning capacity for new information, and increased forgetting of old information. Simulations also showed that specific patterns of neural turnover based on individual neuronal connection characteristics, or the temporal-spatial pattern of neurons chosen for turnover during new learning impacts new learning performance. These simulations predict that apoptotic and neurogenic events could act together to produce specific learning and memory effects beyond those provided by ongoing mechanisms of connection plasticity in neuronal populations. Regulation of rates as well as patterns of neuronal turnover may serve an important function in tuning the informatic properties of plastic networks according to novel informational demands. Analogous regulation in the hippocampus may provide for adaptive cognitive and emotional responses to novel and stressful contexts, or operate suboptimally as a basis for psychiatric disorders. The implications of these elementary simulations for future biological and neural modeling research on apoptosis and neurogenesis are discussed.

  13. Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

    Science.gov (United States)

    Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

    2016-09-01

    The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

  14. Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation.

    Science.gov (United States)

    Anderson, William S; Kudela, Pawel; Weinberg, Seth; Bergey, Gregory K; Franaszczuk, Piotr J

    2009-03-01

    A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of the evolving bursting activity, as well as effects due to network stimulation. The model represents a cortical region of 1.6 mm x 1.6mm, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. There are a total of 65,536 modeled single compartment neurons that operate according to a version of Hodgkin-Huxley dynamics. The intercellular wiring is based on histological studies and our previous modeling efforts. The bursting phase is characterized by a flat frequency spectrum. Stimulation pulses are applied to this modeled network, with an electric field provided by a 1mm radius circular electrode represented mathematically in the simulation. A phase dependence to the post-stimulation quiescence is demonstrated, with local relative maxima in efficacy occurring before or during the network depolarization phase in the underlying activity. Brief periods of network insensitivity to stimulation are also demonstrated. The phase dependence was irregular and did not reach statistical significance when averaged over the full 2.5s of simulated bursting investigated. This result provides comparison with previous in vivo studies which have also demonstrated increased efficacy of stimulation when pulses are applied at the peak of the local field potential during cortical after discharges. The network bursting is synchronous when comparing the different neuron classes represented up to an uncertainty of 10 ms. Studies performed with an excitatory chandelier cell component demonstrated increased synchronous bursting in the model, as predicted from

  15. An Efficient Neural Network Based Modeling Method for Automotive EMC Simulation

    Science.gov (United States)

    Frank, Florian; Weigel, Robert

    2011-09-01

    This paper presents a newly developed methodology for VHDL-AMS model integration into SPICE-based EMC simulations. To this end the VHDL-AMS model, which is available in a compiled version only, is characterized under typical loading conditions, and afterwards a neural network based technique is applied to convert characteristic voltage and current data into an equivalent circuit in SPICE syntax. After the explanation of the whole method and the presentation of a newly developed switched state space dynamic neural network model, the entire analysis process is demonstrated using a typical application from automotive industry.

  16. A Cut Cell Method for Simulating Spatial Models of Biochemical Reaction Networks in Arbitrary Geometries.

    Science.gov (United States)

    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C

    2010-01-01

    Cells use signaling networks consisting of multiple interacting proteins to respond to changes in their environment. In many situations, such as chemotaxis, spatial and temporal information must be transmitted through the network. Recent computational studies have emphasized the importance of cellular geometry in signal transduction, but have been limited in their ability to accurately represent complex cell morphologies. We present a finite volume method that addresses this problem. Our method uses Cartesian cut cells and is second order in space and time. We use our method to simulate several models of signaling systems in realistic cell morphologies obtained from live cell images and examine the effects of geometry on signal transduction.

  17. 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.

  18. 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.

  19. Simulation of A 90o Differential Phase Shifter for Korean VLBI Network 129 GHz Band Polarizer

    Directory of Open Access Journals (Sweden)

    Moon-Hee Chung

    2010-09-01

    Full Text Available A simulation for the design of a 90o differential phase shifter aimed toward Korean VLBI Network (KVN 129 GHz band polarizer is described in this paper. A dual-circular polarizer for KVN 129 GHz band consists of a 90o differential phase shifter and an orthomode transducer. The differential phase shifter is made up of a square waveguide with two opposite walls loaded with corrugations. Three-dimensional electromagnetic simulation has been performed to predict the 90o differential phase shifter’s characteristics. The simulation for the differential phase shifter shows that the phase shift is 90o ± 3.3o across 108-160 GHz and the return losses of two orthogonal modes are better than -30 dB within the design frequency band. According to the simulation results the calculated performance is quite encouraging for KVN 129 GHz band application.

  20. 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.

  1. Algorithms for Computerized Fetal Heart Rate Diagnosis with Direct Reporting

    Directory of Open Access Journals (Sweden)

    Kazuo Maeda

    2015-06-01

    Full Text Available Aims: Since pattern classification of fetal heart rate (FHR was subjective and enlarged interobserver difference, objective FHR analysis was achieved with computerized FHR diagnosis. Methods: The computer algorithm was composed of an experts’ knowledge system, including FHR analysis and FHR score calculation, and also of an objective artificial neural network system with software. In addition, a FHR frequency spectrum was studied to detect ominous sinusoidal FHR and the loss of baseline variability related to fetal brain damage. The algorithms were installed in a central-computerized automatic FHR monitoring system, which gave the diagnosis rapidly and directly to the attending doctor. Results: Clinically perinatal mortality decreased significantly and no cerebral palsy developed after introduction of the centralized system. Conclusion: The automatic multichannel FHR monitoring system improved the monitoring, increased the objectivity of FHR diagnosis and promoted clinical results.

  2. 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.

  3. Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks

    Directory of Open Access Journals (Sweden)

    Biao Xiong

    2017-01-01

    Full Text Available The effectiveness of military supply chain networks is an important reference for logistics decision-making, and it is crucial to evaluate it scientifically and accurately. This paper highlights the problem from the perspective of dynamic and discrete networks. A topological structure model with the characteristics of dynamic and discreteness is used to describe the structure of military supply chain networks (MSCNs. In order to provide a platform for evaluating the effectiveness, simulation algorithms based on topological structure models for MSCNs are presented. Considering military and economic factors, evaluation metrics including supply capability and supply efficiency are proposed. By applying the model and algorithms to a POL supply network in a theater, we obtain the values of supply capability and efficiency metrics in a dynamic environment. We also identify an optimal solution from multiple feasible solutions to help decision-makers to make scientific and rational decisions by using exploratory analysis method. The results show that new evaluation metrics can capture important effectiveness requirements for military supply networks positively. We also find the proposed method in this paper can solve the problem of evaluating the effectiveness of dynamic and discrete network effectiveness evaluation in a feasible and effective manner.

  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. Catastrophic approach to satellite imagery utilization on network-based flight simulators

    Science.gov (United States)

    Levin, Eugene; Ternovskiy, Igor V.

    2001-11-01

    Presently, there are many technological and industrial efforts for development of virtual flight simulators, usually based on networked technologies. In order to solve the problems of real time availability and realistic quality of simulators, source data images and digital terrain models (DTM) should have some generalized structure, which supposes different imagery resolution and different amount of detail on each level of 3D simulation. One of the central problems is geotruthing of satellite imagery with realistic accuracy requirements with respect to DTM. Traditionally such geotruthing can be achieved by means of geo control points measurements. This process is labor intensive and requires special photogrammetric operator skills. In order to avoid such a process an algorithm of terrain and image models singularity's recognition based on Catastrophe theory is investigated in this paper. This approach does not require training but operates with direct comparison of the analytical manifolds from DTM with those actually extracted from the image. The technology described in this paper, the Catastrophe Approach, and algorithms of satellite imagery treatment may be implemented in a multi-level image pyramid flight simulators. Theoretical approaches and practical realization indicates that the Catastrophe Approach is easy- to-use for a final customer and can be implemented on-line to networked flight simulators.

  6. 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.

  7. Simulation and optimization of a pulsating heat pipe using artificial neural network and genetic algorithm

    Science.gov (United States)

    Jokar, Ali; Godarzi, Ali Abbasi; Saber, Mohammad; Shafii, Mohammad Behshad

    2016-11-01

    In this paper, a novel approach has been presented to simulate and optimize the pulsating heat pipes (PHPs). The used pulsating heat pipe setup was designed and constructed for this study. Due to the lack of a general mathematical model for exact analysis of the PHPs, a method has been applied for simulation and optimization using the natural algorithms. In this way, the simulator consists of a kind of multilayer perceptron neural network, which is trained by experimental results obtained from our PHP setup. The results show that the complex behavior of PHPs can be successfully described by the non-linear structure of this simulator. The input variables of the neural network are input heat flux to evaporator (q″), filling ratio (FR) and inclined angle (IA) and its output is thermal resistance of PHP. Finally, based upon the simulation results and considering the heat pipe's operating constraints, the optimum operating point of the system is obtained by using genetic algorithm (GA). The experimental results show that the optimum FR (38.25 %), input heat flux to evaporator (39.93 W) and IA (55°) that obtained from GA are acceptable.

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

    Science.gov (United States)

    Li, Ming; Huang, Xiaobo; Kang, Zhan

    2015-08-01

    Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.

  9. Simulation of Neurocomputing Based on Photophobic Reactions of Euglena: Toward Microbe-Based Neural Network Computing

    Science.gov (United States)

    Ozasa, Kazunari; Aono, Masashi; Maeda, Mizuo; Hara, Masahiko

    In order to develop an adaptive computing system, we investigate microscopic optical feedback to a group of microbes (Euglena gracilis in this study) with a neural network algorithm, expecting that the unique characteristics of microbes, especially their strategies to survive/adapt against unfavorable environmental stimuli, will explicitly determine the temporal evolution of the microbe-based feedback system. The photophobic reactions of Euglena are extracted from experiments, and built in the Monte-Carlo simulation of a microbe-based neurocomputing. The simulation revealed a good performance of Euglena-based neurocomputing. Dynamic transition among the solutions is discussed from the viewpoint of feedback instability.

  10. Physical Properties and Hydrogen-Bonding Network of Water-Ethanol Mixtures from Molecular Dynamics Simulations.

    Science.gov (United States)

    Ghoufi, A; Artzner, F; Malfreyt, P

    2016-02-04

    While many numerical and experimental works were focused on water-ethanol mixtures at low ethanol concentration, this work reports predictions of a few physical properties (thermodynamical, interfacial, dynamical, and dielectrical properties) of water-ethanol mixture at high alcohol concentrations by means of molecular dynamics simulations. By using a standard force field a good agreement was found between experiment and molecular simulation. This was allowed us to explore the dynamics, structure, and interplay between both hydrogen-bonding networks of water and ethanol.

  11. Modeling and Simulation of Road Traffic Noise Using Artificial Neural Network and Regression.

    Science.gov (United States)

    Honarmand, M; Mousavi, S M

    2014-04-01

    Modeling and simulation of noise pollution has been done in a large city, where the population is over 2 millions. Two models of artificial neural network and regression were developed to predict in-city road traffic noise pollution with using the data of noise measurements and vehicle counts at three points of the city for a period of 12 hours. The MATLAB and DATAFIT softwares were used for simulation. The predicted results of noise level were compared with the measured noise levels in three stations. The values of normalized bias, sum of squared errors, mean of squared errors, root mean of squared errors, and squared correlation coefficient calculated for each model show the results of two models are suitable, and the predictions of artificial neural network are closer to the experimental data.

  12. Simulation tests of the optimization method of Hopfield and Tank using neural networks

    Science.gov (United States)

    Paielli, Russell A.

    1988-01-01

    The method proposed by Hopfield and Tank for using the Hopfield neural network with continuous valued neurons to solve the traveling salesman problem is tested by simulation. Several researchers have apparently been unable to successfully repeat the numerical simulation documented by Hopfield and Tank. However, as suggested to the author by Adams, it appears that the reason for those difficulties is that a key parameter value is reported erroneously (by four orders of magnitude) in the original paper. When a reasonable value is used for that parameter, the network performs generally as claimed. Additionally, a new method of using feedback to control the input bias currents to the amplifiers is proposed and successfully tested. This eliminates the need to set the input currents by trial and error.

  13. Prediction of Maximum Story Drift of MDOF Structures under Simulated Wind Loads Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Omar Payán-Serrano

    2017-05-01

    Full Text Available The aim of this paper is to investigate the prediction of maximum story drift of Multi-Degree of Freedom (MDOF structures subjected to dynamics wind load using Artificial Neural Networks (ANNs through the combination of several structural and turbulent wind parameters. The maximum story drift of 1600 MDOF structures under 16 simulated wind conditions are computed with the purpose of generating the data set for the networks training with the Levenberg–Marquardt method. The Shinozuka and Newmark methods are used to simulate the turbulent wind and dynamic response, respectively. In order to optimize the computational time required for the dynamic analyses, an array format based on the Shinozuka method is presented to perform the parallel computing. Finally, it is observed that the already trained ANNs allow for predicting adequately the maximum story drift with a correlation close to 99%.

  14. Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks

    DEFF Research Database (Denmark)

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.

    2012-01-01

    linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using...... numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from...... the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results...

  15. Acquiring Efficient Locomotion in a Simulated Quadruped through Evolving Random and Predefined Neural Networks

    DEFF Research Database (Denmark)

    Veenstra, Frank; Struck, Alexander; Krauledat, Matthias

    2015-01-01

    The acquisition and optimization of dynamically stable locomotion is important to engender fast and energy efficient locomotion in animals. Conventional optimization strategies tend to have difficulties in acquiring dynamically stable gaits in legged robots. In this paper, an evolving neural...... network (ENN) was implemented with the aim to optimize the locomotive behavior of a four-legged simulated robot. In the initial generation, individuals had neural networks (NNs) that were either predefined or randomly initialized. Additional investigations show that the efficiency of applying additional...... sensors to the simulated quadruped improved the performance of the ENN slightly. Promising results were seen in the evolutionary runs where the initial predefined NNs of the population contributed to slight movements of the limbs. This paper shows how a predefined ENNs linked to bio-inspired sensors can...

  16. Computerization of Hungarian reforestation manual with machine learning methods

    Science.gov (United States)

    Czimber, Kornél; Gálos, Borbála; Mátyás, Csaba; Bidló, András; Gribovszki, Zoltán

    2017-04-01

    Hungarian forests are highly sensitive to the changing climate, especially to the available precipitation amount. Over the past two decades several drought damages were observed for tree species which are in the lower xeric limit of their distribution. From year to year these affected forest stands become more difficult to reforest with the same native species because these are not able to adapt to the increasing probability of droughts. The climate related parameter set of the Hungarian forest stand database needs updates. Air humidity that was formerly used to define the forest climate zones is not measured anymore and its value based on climate model outputs is highly uncertain. The aim was to develop a novel computerized and objective method to describe the species-specific climate conditions that is essential for survival, growth and optimal production of the forest ecosystems. The method is expected to project the species spatial distribution until 2100 on the basis of regional climate model simulations. Until now, Hungarian forest managers have been using a carefully edited spreadsheet for reforestation purposes. Applying binding regulations this spreadsheet prescribes the stand-forming and admixed tree species and their expected growth rate for each forest site types. We are going to present a new machine learning based method to replace the former spreadsheet. We took into great consideration of various methods, such as maximum likelihood, Bayesian networks, Fuzzy logic. The method calculates distributions, setups classification, which can be validated and modified by experts if necessary. Projected climate change conditions makes necessary to include into this system an additional climate zone that does not exist in our region now, as well as new options for potential tree species. In addition to or instead of the existing ones, the influence of further limiting parameters (climatic extremes, soil water retention) are also investigated. Results will be

  17. 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

  18. An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

    Science.gov (United States)

    He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

    2014-01-01

    Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation

  19. 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.

  20. 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.

  1. Intelligent Controlling Simulation of Traffic Flow in a Small City Network

    Science.gov (United States)

    Fouladvand, M. Ebrahim; Shaebani, M. Reza; Sadjadi, Zeinab

    2004-11-01

    We propose a two dimensional probabilistic cellular automata for the description of traffic flow in a small city network composed of two intersections. The traffic in the network is controlled by a set of traffic lights which can be operated both in fixed-time and a traffic responsive manner. Vehicular dynamics is simulated and the total delay experienced by the traffic is evaluated within specified time intervals. We investigate both decentralized and centralized traffic responsive schemes and in particular discuss the implementation of the green-wave strategy. Our investigations prove that the network delay strongly depends on the signalisation strategy. We show that in some traffic conditions, the application of the green-wave scheme may destructively lead to the increment of the global delay.

  2. 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.

  3. 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.

  4. 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).

  5. Design and simulation of sensor networks for tracking Wifi users in outdoor urban environments

    Science.gov (United States)

    Thron, Christopher; Tran, Khoi; Smith, Douglas; Benincasa, Daniel

    2017-05-01

    We present a proof-of-concept investigation into the use of sensor networks for tracking of WiFi users in outdoor urban environments. Sensors are fixed, and are capable of measuring signal power from users' WiFi devices. We derive a maximum likelihood estimate for user location based on instantaneous sensor power measurements. The algorithm takes into account the effects of power control, and is self-calibrating in that the signal power model used by the location algorithm is adjusted and improved as part of the operation of the network. Simulation results to verify the system's performance are presented. The simulation scenario is based on a 1.5 km2 area of lower Manhattan, The self-calibration mechanism was verified for initial rms (root mean square) errors of up to 12 dB in the channel power estimates: rms errors were reduced by over 60% in 300 track-hours, in systems with limited power control. Under typical operating conditions with (without) power control, location rms errors are about 8.5 (5) meters with 90% accuracy within 9 (13) meters, for both pedestrian and vehicular users. The distance error distributions for smaller distances (issue of optimal sensor placement in the sensor network is also addressed. We specify a linear programming algorithm for determining sensor placement for networks with reduced number of sensors. In our test case, the algorithm produces a network with 18.5% fewer sensors with comparable accuracy estimation performance. Finally, we discuss future research directions for improving the accuracy and capabilities of sensor network systems in urban environments.

  6. 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.

  7. 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)

  8. Exact subthreshold integration with continuous spike times in discrete-time neural network simulations.

    Science.gov (United States)

    Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus

    2007-01-01

    Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

  9. Impact of Stoichiometry Representation on Simulation of Genotype-Phenotype Relationships in Metabolic Networks

    Science.gov (United States)

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.; Patil, Kiran R.

    2012-01-01

    Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in Saccharomyces cerevisiae. PMID:23133362

  10. A Mobility and Traffic Generation Framework for Modeling and Simulating Ad Hoc Communication Networks

    Directory of Open Access Journals (Sweden)

    Chris Barrett

    2004-01-01

    Full Text Available We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad~hoc networks. Three components of this framework, namely a mobility data generator (MDG, a graph structure generator (GSG and an occlusion modification tool (OMT allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG which generates packet transmission activities for transceivers and a packet activity simulator (PAS which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of

  11. Applying Computerized Adaptive Testing in Schools.

    Science.gov (United States)

    Olsen, James B.

    1990-01-01

    Presents two studies applying computerized adaptive testing (CAT) in schools. Compared paper-administered, computer-administered, and CAT modes for administering school achievement and assessment tests. Then compared computerized adaptive aptitude test results with individually administered Weschler Intelligence Scale for Children-Revised. Found…

  12. An Anatomical Study of Maxillary-Zygomatic Complex Using Three-Dimensional Computerized Tomography-Based Zygomatic Implantation

    National Research Council Canada - National Science Library

    2017-01-01

    Objective. To obtain anatomical data of maxillary-zygomatic complex based on simulating the zygomatic implantation using cadaver heads and three-dimensional computerized tomography (3D-CT). Methods...

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

    Directory of Open Access Journals (Sweden)

    Massin R

    2010-01-01

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

  14. Modeling languages for biochemical network simulation: reaction vs equation based approaches.

    Science.gov (United States)

    Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

    2010-01-01

    Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

  15. 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

  16. 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.

  17. 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.

  18. Computerizing primary schools in rural kenya

    DEFF Research Database (Denmark)

    Ogembo, J.G.; Ngugi, B.; Pelowski, Matthew John

    2012-01-01

    This paper investigates the outstanding challenges facing primary schools' computerization in rural Kenya. Computerization of schools is often envisaged as a 'magic', or at least a particularly efficient, solution to many of the problems that developing countries face in improving primary school...... education. However, while a great deal of consideration is given to the technical issues surrounding computer implementation, government policy makers, administrators, aid organizations and individuals participating in school computerization programs often have not carefully considered the contextual...... questions surrounding this endeavour. Specifically: 1.) what problems do rural schools actually want to solve with computerization; 2.) is computerization the most important priority for rural schools; 3.) are schools ready, in terms of infrastructure, for a computer in the classroom; or 4.) might...

  19. Modeling and simulation of network-on-chip systems with DEVS and DEUS.

    Science.gov (United States)

    Amoretti, Michele

    2014-01-01

    Networks on-chip (NoCs) provide enhanced performance, scalability, modularity, and design productivity as compared with previous communication architectures for VLSI systems on-chip (SoCs), such as buses and dedicated signal wires. Since the NoC design space is very large and high dimensional, evaluation methodologies rely heavily on analytical modeling and simulation. Unfortunately, there is no standard modeling framework. In this paper we illustrate how to design and evaluate NoCs by integrating the Discrete Event System Specification (DEVS) modeling framework and the simulation environment called DEUS. The advantage of such an approach is that both DEVS and DEUS support modularity-the former being a sound and complete modeling framework and the latter being an open, general-purpose platform, characterized by a steep learning curve and the possibility to simulate any system at any level of detail.

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

    Energy Technology Data Exchange (ETDEWEB)

    Djeffal, F. [LEA, Department of Electronics, University of Batna 05000 (Algeria)], E-mail: faycaldzdz@hotmail.com; Dibi, Z. [LEA, Department of Electronics, University of Batna 05000 (Algeria)], E-mail: zohirdibi@univ-batna.dz; Hafiane, M.L.; Arar, D. [LEA, Department of Electronics, University of Batna 05000 (Algeria)

    2007-09-15

    The double gate (DG) MOSFET has received great attention in recent years owing to the inherent suppression of short channel effects (SCEs), excellent subthreshold slope (S), improved drive current (I{sub ds}) and transconductance (gm), volume inversion for symmetric devices and excellent scalability. Therefore, simulation tools which can be applied to design nanoscale transistors in the future require new theory and modeling techniques that capture the physics of quantum transport accurately and efficiently. In this sense, this work presents the applicability of the artificial neural networks (ANN) for the design and simulation of a nanoelectronic DG MOSFET current source. The latter is based on the 2D numerical Non-Equilibrium Green's Function (NEGF) simulation of the current-voltage characteristics of an undoped symmetric DG MOSFET. Our results are discussed in order to obtain some new and useful information about the ULSI technology.

  1. 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.

  2. Mesoscopic simulations of hydrophilic cross-linked polycarbonate polyurethane networks: structure and morphology.

    Science.gov (United States)

    Iype, E; Esteves, A C C; de With, G

    2016-06-14

    Polyurethane (PU) cross-linked networks are frequently used in biomedical and marine applications, e.g., as hydrophilic polymer coatings with antifouling or low-friction properties and have been reported to exhibit characteristic phase separation between soft and hard segments. Understanding this phase-separation behavior is critical to design novel hydrophilic polymer coatings. However, most of the studies on the structure and morphology of cross-linked coatings are experimental, which only assess the phase separation via indirect methods. Herein we present a mesoscopic simulation study of the network characteristics of model hydrophilic polymer networks, consisting of PU with and without methyl-polyethylene glycol (mPEG) dangling chains. The systems are analyzed using a number of tools, such as the radial distribution function, the cross-link point density distribution and the Voronoi volume distribution (of the cross-linking points). The combined results show that the cross-linked networks without dangling chains are rather homogeneous but contain a small amount of clustering of cross-linker molecules. A clear phase separation is observed when introducing the dangling chains. In spite of that, the amount of cross-linker molecules connected to dangling chains only, i.e., not connected to the main network, is relatively small, leading to about 3 wt% extractables. Thus, these cross-linked polymers consist of a phase-separated, yet highly connected network. This study provides valuable guidelines towards new self-healing hydrophilic coatings based on the molecular design of cross-linked networks in direct contact with water or aqueous fluids, e.g., as anti-fouling self-repairing coatings for marine applications.

  3. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

    Directory of Open Access Journals (Sweden)

    Régis Corinne

    2011-07-01

    Full Text Available Abstract Background The spread of infectious diseases crucially depends on the pattern of contacts between individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. However, there are few empirical studies available that provide estimates of the number and duration of contacts between social groups. Moreover, their space and time resolutions are limited, so that data are not explicit at the person-to-person level, and the dynamic nature of the contacts is disregarded. In this study, we aimed to assess the role of data-driven dynamic contact patterns between individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. Methods We considered high-resolution data about face-to-face interactions between the attendees at a conference, obtained from the deployment of an infrastructure based on radiofrequency identification (RFID devices that assessed mutual face-to-face proximity. The spread of epidemics along these interactions was simulated using an SEIR (Susceptible, Exposed, Infectious, Recovered model, using both the dynamic network of contacts defined by the collected data, and two aggregated versions of such networks, to assess the role of the data temporal aspects. Results We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation that retains only the topology of the contact network fails to reproduce the size of the epidemic. Conclusions These results have important implications for understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics. Please see related article BMC Medicine, 2011, 9:88

  4. A parallel program for numerical simulation of discrete fracture network and groundwater flow

    Science.gov (United States)

    Huang, Ting-Wei; Liou, Tai-Sheng; Kalatehjari, Roohollah

    2017-04-01

    The ability of modeling fluid flow in Discrete Fracture Network (DFN) is critical to various applications such as exploration of reserves in geothermal and petroleum reservoirs, geological sequestration of carbon dioxide and final disposal of spent nuclear fuels. Although several commerical or acdametic DFN flow simulators are already available (e.g., FracMan and DFNWORKS), challenges in terms of computational efficiency and three-dimensional visualization still remain, which therefore motivates this study for developing a new DFN and flow simulator. A new DFN and flow simulator, DFNbox, was written in C++ under a cross-platform software development framework provided by Qt. DFNBox integrates the following capabilities into a user-friendly drop-down menu interface: DFN simulation and clipping, 3D mesh generation, fracture data analysis, connectivity analysis, flow path analysis and steady-state grounwater flow simulation. All three-dimensional visualization graphics were developed using the free OpenGL API. Similar to other DFN simulators, fractures are conceptualized as random point process in space, with stochastic characteristics represented by orientation, size, transmissivity and aperture. Fracture meshing was implemented by Delaunay triangulation for visualization but not flow simulation purposes. Boundary element method was used for flow simulations such that only unknown head or flux along exterior and interection bounaries are needed for solving the flow field in the DFN. Parallel compuation concept was taken into account in developing DFNbox for calculations that such concept is possible. For example, the time-consuming seqential code for fracture clipping calculations has been completely replaced by a highly efficient parallel one. This can greatly enhance compuational efficiency especially on multi-thread platforms. Furthermore, DFNbox have been successfully tested in Windows and Linux systems with equally-well performance.

  5. Hierarchical assembly of block copolymer micelles into reversible networks: MC simulations

    Science.gov (United States)

    Wang, Zilu; Dormidontova, Elena

    2015-03-01

    The rapid development of nanoscience has considerably expanded the range of building blocks for complex self-assembled nanostructure formation, which show great potential for numerous advanced applications. We apply Monte Carlo simulations to gain understanding of molecular mechanism of self-assembly of nanostructures formed by diblock copolymer micelles interconnected by means of metal-ligand complexation. These systems exhibit interesting chemical and mechanical stimuli-responsive behavior and possess two levels of self-assembly: 1) self-assembly of diblock copolymers into micelles and 2) reversible inter-micelle bridging by coordination bonding between metal ions and ligands attached to the corona of nanoparticles, which is responsible for the network viscoelastic properties. Using MC simulations we investigate the effect of metal-ligand complexation on diblock-copolymer micelle formation and vice versa. We analyze the extent of intra- and inter-micelle loops and bridges formed by metal-ligand complexation in relation to the degree of crosslinking and elastic properties of the network. The effect of polymer concentration, hydrophilic block length, metal to oligomer ratio and type of complexation (2:1 or 3:1) on equilibrium properties of reversible networks will be discussed.

  6. Reading fiction and reading minds: the role of simulation in the default network

    Science.gov (United States)

    Bricker, Andrew B.; Dodell-Feder, David; Mitchell, Jason P.

    2016-01-01

    Research in psychology has suggested that reading fiction can improve individuals’ social-cognitive abilities. Findings from neuroscience show that reading and social cognition both recruit the default network, a network which is known to support our capacity to simulate hypothetical scenes, spaces and mental states. The current research tests the hypothesis that fiction reading enhances social cognition because it serves to exercise the default subnetwork involved in theory of mind. While undergoing functional neuroimaging, participants read literary passages that differed along two dimensions: (i) vivid vs abstract and (ii) social vs non-social. Analyses revealed distinct subnetworks of the default network respond to the two dimensions of interest: the medial temporal lobe subnetwork responded preferentially to vivid passages, with or without social content; the dorsomedial prefrontal cortex (dmPFC) subnetwork responded preferentially to passages with social and abstract content. Analyses also demonstrated that participants who read fiction most often also showed the strongest social cognition performance. Finally, mediation analysis showed that activity in the dmPFC subnetwork in response to the social content mediated this relation, suggesting that the simulation of social content in fiction plays a role in fiction’s ability to enhance readers’ social cognition. PMID:26342221

  7. Reconstruction of chalk pore networks from 2D backscatter electron micrographs using a simulated annealing technique

    Energy Technology Data Exchange (ETDEWEB)

    Talukdar, M.S.; Torsaeter, O. [Department of Petroleum Engineering and Applied Geophysics, Norwegian University of Science and Technology, Trondheim (Norway)

    2002-05-01

    We report the stochastic reconstruction of chalk pore networks from limited morphological information that may be readily extracted from 2D backscatter electron (BSE) images of the pore space. The reconstruction technique employs a simulated annealing (SA) algorithm, which can be constrained by an arbitrary number of morphological descriptors. Backscatter electron images of a high-porosity North Sea chalk sample are analyzed and the morphological descriptors of the pore space are determined. The morphological descriptors considered are the void-phase two-point probability function and lineal path function computed with or without the application of periodic boundary conditions (PBC). 2D and 3D samples have been reconstructed with different combinations of the descriptors and the reconstructed pore networks have been analyzed quantitatively to evaluate the quality of reconstructions. The results demonstrate that simulated annealing technique may be used to reconstruct chalk pore networks with reasonable accuracy using the void-phase two-point probability function and/or void-phase lineal path function. Void-phase two-point probability function produces slightly better reconstruction than the void-phase lineal path function. Imposing void-phase lineal path function results in slight improvement over what is achieved by using the void-phase two-point probability function as the only constraint. Application of periodic boundary conditions appears to be not critically important when reasonably large samples are reconstructed.

  8. 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.

  9. 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.

  10. 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.

  11. Multi-Sensor Network for Landslides Simulation and Hazard Monitoring - Design and Deployment

    Science.gov (United States)

    Wu, H.; Qiao, G.; Lu, P.; Feng, T.; Tian, Y.; Fan, H.; Liu, S.; Liu, C.; Tong, X.; Wang, W.; Shen, Y.; Guan, Z.; Li, R.

    2011-08-01

    This paper describes a newly developed multi-sensor network system for landslide and hazard monitoring. Landslide hazard is one of the most destructive natural disasters, which has severely affected human safety, properties and infrastructures. We report the results of designing and deploying the multi-sensor network, based on the simulated landslide model, to monitor typical landslide areas and with a goal to predict landslide hazard and mitigate damages. The integration and deployment of the prototype sensor network were carried out in an experiment area at Tongji University in Shanghai. In order to simulate a real landslide, a contractible landslide body is constructed in the experiment area by 7m*1.5m. Then, some different kind of sensors, such as camera, GPS, crackmeter, accelerometer, laser scanning system, inclinometer, etc., are installed near or in the landslide body. After the sensors are powered, continuous sampling data will be generated. With the help of communication method, such as GPRS, and certain transport devices, such as iMesh and 3G router, all the sensor data will be transported to the server and stored in Oracle. These are the current results of an ongoing project of the center. Further research results will be updated and presented in the near future.

  12. 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.

  13. On Improved Least Squares Regression and Artificial Neural Network Meta-Models for Simulation via Control Variates

    Science.gov (United States)

    2016-09-15

    neural network using applications across varied industries . Alam et al. [2] showed the factorial design did not perform as well as other designs (mentioned...composite design with a neural network using applications across varied industries . Alam et al. [2] showed the central composite design did not perform as...ON IMPROVED LEAST SQUARES REGRESSION & ARTIFICIAL NEURAL NETWORK META-MODELS FOR SIMULATION VIA CONTROL VARIATES DISSERTATION Michael P. Gibb

  14. Artificial neural network model for simulation of water distribution in sprinkle irrigation

    Directory of Open Access Journals (Sweden)

    Paulo L. de Menezes

    2015-09-01

    Full Text Available ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN to simulate sprinkler precipitation, using the values ​​of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs ranging from 0.92 to 0.97 and Willmott agreement index (d from 0.950 to 0.991, between the observed and simulated values for ten analysed trials. The ANN model shows promise in the simulation of precipitation in sprinkle irrigation systems.

  15. ChemChains: a platform for simulation and analysis of biochemical networks aimed to laboratory scientists

    Science.gov (United States)

    Helikar, Tomáš; Rogers, Jim A

    2009-01-01

    Background New mathematical models of complex biological structures and computer simulation software allow modelers to simulate and analyze biochemical systems in silico and form mathematical predictions. Due to this potential predictive ability, the use of these models and software has the possibility to compliment laboratory investigations and help refine, or even develop, new hypotheses. However, the existing mathematical modeling techniques and simulation tools are often difficult to use by laboratory biologists without training in high-level mathematics, limiting their use to trained modelers. Results We have developed a Boolean network-based simulation and analysis software tool, ChemChains, which combines the advantages of the parameter-free nature of logical models while providing the ability for users to interact with their models in a continuous manner, similar to the way laboratory biologists interact with laboratory data. ChemChains allows users to simulate models in an automatic fashion under tens of thousands of different external environments, as well as perform various mutational studies. Conclusion ChemChains combines the advantages of logical and continuous modeling and provides a way for laboratory biologists to perform in silico experiments on mathematical models easily, a necessary component of laboratory research in the systems biology era. PMID:19500393

  16. ChemChains: a platform for simulation and analysis of biochemical networks aimed to laboratory scientists

    Directory of Open Access Journals (Sweden)

    Rogers Jim A

    2009-06-01

    Full Text Available Abstract Background New mathematical models of complex biological structures and computer simulation software allow modelers to simulate and analyze biochemical systems in silico and form mathematical predictions. Due to this potential predictive ability, the use of these models and software has the possibility to compliment laboratory investigations and help refine, or even develop, new hypotheses. However, the existing mathematical modeling techniques and simulation tools are often difficult to use by laboratory biologists without training in high-level mathematics, limiting their use to trained modelers. Results We have developed a Boolean network-based simulation and analysis software tool, ChemChains, which combines the advantages of the parameter-free nature of logical models while providing the ability for users to interact with their models in a continuous manner, similar to the way laboratory biologists interact with laboratory data. ChemChains allows users to simulate models in an automatic fashion under tens of thousands of different external environments, as well as perform various mutational studies. Conclusion ChemChains combines the advantages of logical and continuous modeling and provides a way for laboratory biologists to perform in silico experiments on mathematical models easily, a necessary component of laboratory research in the systems biology era.

  17. Enabling distributed simulation multilevel security using virtual machine and virtual private network technology

    Science.gov (United States)

    Stytz, Martin R.; Banks, Sheila B.

    2007-04-01

    Increasing the accuracy of the portrayal of all of the elements of a simulation environment has long been a prime goal of the modeling and simulation community; a goal that has remained far out of reach for many reasons. One of the greatest hurdles facing simulation developers in the effort to increase simulation accuracy is the need to segregate information across the entire simulation environment according to access restrictions in order to insure the integrity, security, and reliability requirements imposed on the data. However, this need for segregation does not mean that those with the highest access permissions should be forced to use multiple computers and displays to integrate the information that they need or that intelligent agents should be restricted in their access to the information that they need in order to adequately assist their human operators. In this paper, we present a potential solution to the problem of integrating and segregating data, which is the use of virtual machine and virtual private network technology in order to maintain segregation of data, control access, and control intercommunication.

  18. Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks

    Science.gov (United States)

    Cota, Wesley; Ferreira, Silvio C.

    2017-10-01

    Numerical simulation of continuous-time Markovian processes is an essential and widely applied tool in the investigation of epidemic spreading on complex networks. Due to the high heterogeneity of the connectivity structure through which epidemic is transmitted, efficient and accurate implementations of generic epidemic processes are not trivial and deviations from statistically exact prescriptions can lead to uncontrolled biases. Based on the Gillespie algorithm (GA), in which only steps that change the state are considered, we develop numerical recipes and describe their computer implementations for statistically exact and computationally efficient simulations of generic Markovian epidemic processes aiming at highly heterogeneous and large networks. The central point of the recipes investigated here is to include phantom processes, that do not change the states but do count for time increments. We compare the efficiencies for the susceptible-infected-susceptible, contact process and susceptible-infected-recovered models, that are particular cases of a generic model considered here. We numerically confirm that the simulation outcomes of the optimized algorithms are statistically indistinguishable from the original GA and can be several orders of magnitude more efficient.

  19. 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.

  20. 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.

  1. Simulation and stability analysis of neural network based control scheme for switched linear systems.

    Science.gov (United States)

    Singh, H P; Sukavanam, N

    2012-01-01

    This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709-14] is presented. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  2. 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.

  3. Operational departmentwide picture archiving communication system analysis using discrete event-driven block-oriented network simulation.

    Science.gov (United States)

    Stewart, B K

    1993-05-01

    The accurate prediction of image throughput is a critical issue in planning for and acquisition of any successful picture archiving and communication system (PACS). Simulation plays an important role in this effort. The PACS image management chain is decomposed into eight subsystems. These subsystems include network transfers over three different networks and five software programs and/or queueing structures. This decomposition is used to create a simulation model that was effectuated using commercially available block-oriented network simulation software. From the PACS database, the traffic generation patterns of the imaging modality devices are used to drive the simulation. The simulation models the image file flow through the PACS for a 24-hour period. The behavior of the simulated traffic generators agreed well with the values derived from the PACS database. The mean delay for the simulated PACS is found to be 225 +/- 59 seconds. The delay time was found to vary during the simulated 24-hour cycle in a consistent manner with observations. This simulation provides estimates on what a radiological department can expect from a PACS in terms of throughput, utilization, and delay. The block-oriented network simulator (BONeS, Comdisco Systems Inc, Foster City, CA) simulation model of the modeled PACS is highly accurate. The models for the imaging modality traffic sources are validated with a high degree of accuracy. The simulation model allows for the study of what happens to the delay time under various loads. In this simulation, the reformatting process was determined to be the bottleneck causing a large increase in delay time under heavy loads.

  4. Direct Numerical Simulation of Cellular-Scale Blood Flow in 3D Microvascular Networks.

    Science.gov (United States)

    Balogh, Peter; Bagchi, Prosenjit

    2017-12-19

    We present, to our knowledge, the first direct numerical simulation of 3D cellular-scale blood flow in physiologically realistic microvascular networks. The vascular networks are designed following in vivo images and data, and are comprised of bifurcating, merging, and winding vessels. Our model resolves the large deformation and dynamics of each individual red blood cell flowing through the networks with high fidelity, while simultaneously retaining the highly complex geometric details of the vascular architecture. To our knowledge, our simulations predict several novel and unexpected phenomena. We show that heterogeneity in hemodynamic quantities, which is a hallmark of microvascular blood flow, appears both in space and time, and that the temporal heterogeneity is more severe than its spatial counterpart. 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 red blood cell jamming at vascular bifurcations 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. A striking result from our simulations is negative pressure-flow correlations observed in several vessels, implying a significant deviation from Poiseuille's law. Furthermore, negative correlations between vascular resistance and hematocrit are observed in various vessels, also defying a major principle of particulate suspension flow. To our knowledge, these novel findings are absent in blood flow in straight tubes, and they underscore the importance of considering realistic physiological geometry and resolved cellular interactions in modeling microvascular hemodynamics. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  5. 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.

  6. 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...

  7. 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

  8. 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

    explaining possible applications of the proposed model for evaluation of: 1) Control strategies; and, 2) System modifications, are provided. The proposed framework is specifically designed to allow for easy development and comparison of multiple control possibilities and integration with existing......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...

  9. Comment on high resolution simulations of cosmic strings. 1: Network evoloution

    Energy Technology Data Exchange (ETDEWEB)

    Turok, N.; Albrecht, A.

    1990-03-01

    Comments are made on recent claims (Albrecht and Turok, 1989) regarding simulations of cosmic string evolution. Specially, it was claimed that results were dominated by a numerical artifact which rounds out kinks on a scale of the order of the correlation length on the network. This claim was based on an approximate analysis of an interpolation equation which is solved herein. The typical rounding scale is actually less than one fifth of the correlation length, and comparable with other numerical cutoffs. Results confirm previous estimates of numerical uncertainties, and show that the approximations poorly represent the real solutions to the interpolation equation.

  10. 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.

  11. 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

  12. Optimization and Simulation of Collaborative Networks for Sustainable Production and Transportation

    DEFF Research Database (Denmark)

    Liotta, Giacomo; Kaihara, Toshiya; Stecca, Giuseppe

    2016-01-01

    Complex and delocalized manufacturing industries require high levels of integration between production and transportation in order to effectively implement lean and agile operations. There are, however, limitations in research and applications simultaneously embodying further sustainability...... dimensions. This paper presents a methodological framework based on optimization and simulation to integrate aggregate optimized plans for production and multimodal transportation with detailed dynamic distribution plans affected by demand uncertainty. The objective function of the optimization model...... considers supply, production, transportation, and CO2 emission costs, as well as collaboration over the multimodal network. Bill-of-materials and capacity constraints are included. A feedback between simulation and optimization is used to plan requirements for materials and components. Computational...

  13. Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Magnier, Laurent; Haghighat, Fariborz [Department of Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd. W., BE-351, Montreal, Quebec H3G 1M8 (Canada)

    2010-03-15

    Building optimization involving multiple objectives is generally an extremely time-consuming process. The GAINN approach presented in this study first uses a simulation-based Artificial Neural Network (ANN) to characterize building behaviour, and then combines this ANN with a multiobjective Genetic Algorithm (NSGA-II) for optimization. The methodology has been used in the current study for the optimization of thermal comfort and energy consumption in a residential house. Results of ANN training and validation are first discussed. Two optimizations were then conducted taking variables from HVAC system settings, thermostat programming, and passive solar design. By integrating ANN into optimization the total simulation time was considerably reduced compared to classical optimization methodology. Results of the optimizations showed significant reduction in terms of energy consumption as well as improvement in thermal comfort. Finally, thanks to the multiobjective approach, dozens of potential designs were revealed, with a wide range of trade-offs between thermal comfort and energy consumption. (author)

  14. First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems.

    Science.gov (United States)

    Behler, Jörg

    2017-10-09

    Modern simulation techniques have reached a level of maturity which allows a wide range of problems in chemistry and materials science to be addressed. Unfortunately, the application of first principles methods with predictive power is still limited to rather small systems, and despite the rapid evolution of computer hardware no fundamental change in this situation can be expected. Consequently, the development of more efficient but equally reliable atomistic potentials to reach an atomic level understanding of complex systems has received considerable attention in recent years. A promising new development has been the introduction of machine learning (ML) methods to describe the atomic interactions. Once trained with electronic structure data, ML potentials can accelerate computer simulations by several orders of magnitude, while preserving quantum mechanical accuracy. This Review considers the methodology of an important class of ML potentials that employs artificial neural networks. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. A real-time control method-based simulation for high-speed trains on large-scale rail network

    Science.gov (United States)

    Liu, Yutong; Cao, Chengxuan; Zhou, Yaling; Feng, Ziyan

    In this paper, an improved real-time control model based on the discrete-time method is constructed to control and simulate the movement of high-speed trains on large-scale rail network. The constraints of acceleration and deceleration are introduced in this model, and a more reasonable definition of the minimal headway is also presented. Considering the complicated rail traffic environment in practice, we propose a set of sound operational strategies to excellently control traffic flow on rail network under various conditions. Several simulation experiments with different parameter combinations are conducted to verify the effectiveness of the control simulation method. The experimental results are similar to realistic environment and some characteristics of rail traffic flow are also investigated, especially the impact of stochastic disturbances and the minimal headway on the rail traffic flow on large-scale rail network, which can better assist dispatchers in analysis and decision-making. Meanwhile, experimental results also demonstrate that the proposed control simulation method can be in real-time control of traffic flow for high-speed trains not only on the simple rail line, but also on the complicated large-scale network such as China’s high-speed rail network and serve as a tool of simulating the traffic flow on large-scale rail network to study the characteristics of rail traffic flow.

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

    Science.gov (United States)

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

    2015-01-01

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

  17. Reflections on Teaching in a Computerized Classroom: Knowledge, Power and Technology.

    Science.gov (United States)

    Sykes, Lynn; Uber, Nancy

    A study focused on teachers who have worked in computerized, networked writing classrooms at Purdue University (Indiana) for several year. Each of the subjects was a teaching assistant in the Purdue English Department, and the courses involved were upper division technical writing courses. Three theoretical approaches underpinned the study:…

  18. Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

    Science.gov (United States)

    Chao, Zenas C.; Bakkum, Douglas J.; Potter, Steve M.

    2007-09-01

    Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

  19. 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.

  20. Computerizing marine biota: a rational approach

    Digital Repository Service at National Institute of Oceanography (India)

    Chavan, V.S.; Chandramohan, D.; Parulekar, A.H.

    Data on marine biota while being extensive are also patchy and scattered; thus making retrieval and dissemination of information time consuming. This emphasise the need for computerizing information on marine biota with the objective to collate...

  1. Computerizing a house organ: recharting familiar territory

    Energy Technology Data Exchange (ETDEWEB)

    None

    1982-01-01

    Computerization can offer great advantages. But one publication ideally suited to computerization was slow to take advantage of the new technology. The main reason was reluctance to try an unfamiliar way of doing things. Having now switched to computerization, the publication has reaped many benefits. Among them: production time is faster; costs are lower; errors are fewer. Computerization has not been without minor problems. The most obvious is vulnerability to the rarity of a system failure. Others include the technology's potential reinforcement of overediting and of excessive reliance on extremely rapid response. Such problems, however, do not indicate weaknesses in the technology itself; rather, they reflect an incomplete adaption to it and the need for more realistic expectations. An unwarranted reluctance to innovate can slow advances in communication. Technical communicators must be willing to rechart their own familiar territory.

  2. HUMAN RELIABILITY ANALYSIS FOR COMPUTERIZED PROCEDURES

    Energy Technology Data Exchange (ETDEWEB)

    Ronald L. Boring; David I. Gertman; Katya Le Blanc

    2011-09-01

    This paper provides a characterization of human reliability analysis (HRA) issues for computerized procedures in nuclear power plant control rooms. It is beyond the scope of this paper to propose a new HRA approach or to recommend specific methods or refinements to those methods. Rather, this paper provides a review of HRA as applied to traditional paper-based procedures, followed by a discussion of what specific factors should additionally be considered in HRAs for computerized procedures. Performance shaping factors and failure modes unique to computerized procedures are highlighted. Since there is no definitive guide to HRA for paper-based procedures, this paper also serves to clarify the existing guidance on paper-based procedures before delving into the unique aspects of computerized procedures.

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

    Science.gov (United States)

    Unal, B.; Askan, A.

    2014-12-01

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

  4. [Simulation Analysis of the Pulse Signal on the Electricity Network of Cardiovascular System].

    Science.gov (United States)

    Liu, Ying; Yin, Yanfei; Zhang, Defa; Wang, Menghong; Bi, Yongqiang

    2015-12-01

    Pulse waves contain abundant physiological and pathological information of human body. Research of the relationship between pulse wave and human cardiovascular physiological parameters can not only help clinical diagnosis and treatment of cardiovascular diseases, but also contribute to develop many new medical instruments. Based on the traditional double elastic cavity model, the human cardiovascular system was established by using the electric network model in this paper. The change of wall pressure and blood flow in artery was simulated. And the influence of the peripheral resistance and vessel compliance to the distribution of blood flow in artery was analyzed. The simulation results were compared with the clinical monitoring results to predict the physiological and pathological state of human body. The result showed that the simulation waveform of arterial wall pressure and blood flow was stabile after the second cardiac cycle. With the increasing of peripheral resistance, the systolic blood pressure of artery increased, the diastolic blood pressure had no significant change, and the pulse pressure of artery increased gradually. With the decreasing of vessel compliance, the vasoactivity became worse and the pulse pressure increased correspondingly. The simulation results were consistent with the clinical monitoring results. The increasing of peripheral resistance and decreasing of vascular compliance indicated that the incidence of hypertension and atherosclerosis was increased.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

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

    Science.gov (United States)

    Shen, Lin; Yang, Weitao

    2018-02-13

    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 complex environment but very time consuming. The computational cost on 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 way. 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 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 reaction dynamics, which provides a useful tool to study chemical or biochemical systems in solution or enzymes.

  12. Concerto: A Framework for Computerized Adaptive Test Applications

    Directory of Open Access Journals (Sweden)

    Eren Can AYBEK

    2016-12-01

    Full Text Available In the studies of computerized adaptive tests (CAT, real life CAT applications are used besides of post-hoc simulations which held by real-data. The purpose of this study is to introduce Concerto, a CAT platform which provides practical framework for researchers, and demonstrate the installation of Concerto and run a sample CAT application. For this purpose; configuration of Concerto to Linux server, installation of server and necessary software, installation of Concerto and downloading, editing and running a sample CAT application have been demonstrated step-by-step.

  13. Modeling, analysis, and simulation of the co-development of road networks and vehicle ownership

    Science.gov (United States)

    Xu, Mingtao; Ye, Zhirui; Shan, Xiaofeng

    2016-01-01

    A two-dimensional logistic model is proposed to describe the co-development of road networks and vehicle ownership. The endogenous interaction between road networks and vehicle ownership and how natural market forces and policies transformed into their co-development are considered jointly in this model. If the involved parameters satisfy a certain condition, the proposed model can arrive at a steady equilibrium level and the final development scale will be within the maximum capacity of an urban traffic system; otherwise, the co-development process will be unstable and even manifest chaotic behavior. Then sensitivity tests are developed to determine the proper values for a series of parameters in this model. Finally, a case study, using Beijing City as an example, is conducted to explore the applicability of the proposed model to the real condition. Results demonstrate that the proposed model can effectively simulate the co-development of road network and vehicle ownership for Beijing City. Furthermore, we can obtain that their development process will arrive at a stable equilibrium level in the years 2040 and 2045 respectively, and the equilibrium values are within the maximum capacity.

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

    Science.gov (United States)

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

    1985-07-01

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

  16. System-level network simulation for robust centrifugal-microfluidic lab-on-a-chip systems.

    Science.gov (United States)

    Schwarz, I; Zehnle, S; Hutzenlaub, T; Zengerle, R; Paust, N

    2016-05-10

    Centrifugal microfluidics shows a clear trend towards a higher degree of integration and parallelization. This trend leads to an increase in the number and density of integrated microfluidic unit operations. The fact that all unit operations are processed by the same common spin protocol turns higher integration into higher complexity. To allow for efficient development anyhow, we introduce advanced lumped models for network simulations in centrifugal microfluidics. These models consider the interplay of centrifugal and Euler pressures, viscous dissipation, capillary pressures and pneumatic pressures. The simulations are fast and simple to set up and allow for the precise prediction of flow rates as well as switching and valving events. During development, channel and chamber geometry variations due to manufacturing tolerances can be taken into account as well as pipetting errors, variations of contact angles, compliant chamber walls and temperature variations in the processing device. As an example of considering these parameters during development, we demonstrate simulation based robustness analysis for pneumatic siphon valving in centrifugal microfluidics. Subsequently, the influence of liquid properties on pumping and valving is studied for four liquids relevant for biochemical analysis, namely, water (large surface tension), blood plasma (large contact angle hysteresis), ethanol/water (highly wetting) and glycerine/water (highly viscous). In a second example, we derive a spin protocol to attain a constant flow rate under varying pressure conditions. Both examples show excellent agreement with experimental validations.

  17. pSSAlib: The partial-propensity stochastic chemical network simulator.

    Directory of Open Access Journals (Sweden)

    Oleksandr Ostrenko

    2017-12-01

    Full Text Available Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de.

  18. pSSAlib: The partial-propensity stochastic chemical network simulator.

    Science.gov (United States)

    Ostrenko, Oleksandr; Incardona, Pietro; Ramaswamy, Rajesh; Brusch, Lutz; Sbalzarini, Ivo F

    2017-12-01

    Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de.

  19. Spatial Estimation, Data Assimilation and Stochastic Conditional Simulation using the Counterpropagation Artificial Neural Network

    Science.gov (United States)

    Besaw, L. E.; Rizzo, D. M.; Boitnoitt, G. N.

    2006-12-01

    Accurate, yet cost effective, sites characterization and analysis of uncertainty are the first steps in remediation efforts at sites with subsurface contamination. From the time of source identification to the monitoring and assessment of a remediation design, the management objectives change, resulting in increased costs and the need for additional data acquisition. Parameter estimation is a key component in reliable site characterization, contaminant flow and transport predictions, plume delineation and many other data management goals. We implement a data-driven parameter estimation technique using a counterpropagation Artificial Neural Network (ANN) that is able to incorporate multiple types of data. This method is applied to estimates of geophysical properties measured on a slab of Berea sandstone and delineation of the leachate plume migrating from a landfill in upstate N.Y. The estimates generated by the ANN have been found to be statistically similar to estimates generated using conventional geostatistical kriging methods. The associated parameter uncertainty in site characterization, due to sparsely distributed samples (spatial or temporal) and incomplete site knowledge, is of major concern in resource mining and environmental engineering. We also illustrate the ability of the ANN method to perform conditional simulation using the spatial structure of parameters identified with semi-variogram analysis. This method allows for the generation of simulations that respect the observed measurement data, as well as the data's underlying spatial structure. The method of conditional simulation is used in a 3-dimensional application to estimate the uncertainty of soil lithology.

  20. pSSAlib: The partial-propensity stochastic chemical network simulator

    Science.gov (United States)

    Ostrenko, Oleksandr; Incardona, Pietro; Ramaswamy, Rajesh

    2017-01-01

    Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de. PMID:29206229

  1. Global network of embodied water flow by systems input-output simulation

    Science.gov (United States)

    Chen, Zhanming; Chen, Guoqian; Xia, Xiaohua; Xu, Shiyun

    2012-09-01

    The global water resources network is simulated in the present work for the latest target year with statistical data available and with the most detailed data disaggregation. A top-down approach of systems inputoutput simulation is employed to track the embodied water flows associated with economic flows for the globalized economy in 2004. The numerical simulation provides a database of embodied water intensities for all economic commodities from 4928 producers, based on which the differences between direct and indirect water using efficiencies at the global scale are discussed. The direct and embodied water uses are analyzed at continental level. Besides, the commodity demand in terms of monetary expenditure and the water demand in terms of embodied water use are compared for the world as well as for three major water using regions, i.e., India, China, and the United States. Results show that food product contributes to a significant fraction for water demand, despite the value varies significantly with respect to the economic status of region.

  2. Simulator Network Project Report: A tool for improvement of teaching materials and targeted resource usage in Skills Labs

    Science.gov (United States)

    Damanakis, Alexander; Blaum, Wolf E.; Stosch, Christoph; Lauener, Hansjörg; Richter, Sabine; Schnabel, Kai P.

    2013-01-01

    During the last decade, medical education in the German-speaking world has been striving to become more practice-oriented. This is currently being achieved in many schools through the implementation of simulation-based instruction in Skills Labs. Simulators are thus an essential part of this type of medical training, and their acquisition and operation by a Skills Lab require a large outlay of resources. Therefore, the Practical Skills Committee of the Medical Education Society (GMA) introduced a new project, which aims to improve the flow of information between the Skills Labs and enable a transparent assessment of the simulators via an online database (the Simulator Network). PMID:23467581

  3. A Computerized Test of Design Fluency.

    Directory of Open Access Journals (Sweden)

    David L Woods

    Full Text Available Tests of design fluency (DF assess a participant's ability to generate geometric patterns and are thought to measure executive functions involving the non-dominant frontal lobe. Here, we describe the properties of a rapidly administered computerized design-fluency (C-DF test that measures response times, and is automatically scored. In Experiment 1, we found that the number of unique patterns produced over 90 s by 180 control participants (ages 18 to 82 years correlated with age, education, and daily computer-use. Each line in the continuous 4-line patterns required approximately 1.0 s to draw. The rate of pattern production and the incidence of repeated patterns both increased over the 90 s test. Unique pattern z-scores (corrected for age and computer-use correlated with the results of other neuropsychological tests performed on the same day. Experiment 2 analyzed C-DF test-retest reliability in 55 participants in three test sessions at weekly intervals and found high z-score intraclass correlation coefficients (ICC = 0.79. Z-scores in the first session did not differ significantly from those of Experiment 1, but performance improved significantly over repeated tests. Experiment 3 investigated the performance of Experiment 2 participants when instructed to simulate malingering. Z-scores were significantly reduced and pattern repetitions increased, but there was considerable overlap with the performance of the control population. Experiment 4 examined performance in veteran patients tested more than one year after traumatic brain injury (TBI. Patients with mild TBI performed within the normal range, but patients with severe TBI showed reduced z-scores. The C-DF test reliably measures visuospatial pattern generation ability and reveals performance deficits in patients with severe TBI.

  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. A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

    Science.gov (United States)

    Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

    2012-01-01

    This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

  6. Some alternatives to Sympson-Hetter item-exposure control in computerized adaptive testing

    NARCIS (Netherlands)

    van der Linden, Willem J.

    2003-01-01

    The Hetter and Sympson (1997; 1985) method is a method of probabilistic item-exposure control in computerized adaptive testing. Setting its control parameters to admissible values requires an iterative process of computer simulations that has been found to be time consuming, particularly if the

  7. 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.

  8. 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.

  9. Computerized occlusal analysis in bruxism

    Directory of Open Access Journals (Sweden)

    Lazić Vojkan

    2006-01-01

    Full Text Available Introduction. Sleep bruxism as nocturnal parafunction, also known as tooth grinding, is the most common parasomnia (sleep disorder. Most tooth grinding occurs during rapid eye movement - REM sleep. Sleep bruxism is an oral habit characterized by rhythmic activity of the masticatory muscles (m. masseter that causes forced contact between dental surfaces during sleep. Sleep bruxism has been associated with craniomandibular disorders including temporomandibular joint discomfort, pulpalgia, premature loss of teeth due to excessive attrition and mobility, headache, muscle ache, sleep interruption of an individual and problems with removable and fixed denture. Basically, two groups of etiological factors can be distinguished, viz., peripheral (occlusal factors and central (pathophysiological and psychological factors. The role of occlusion (occlusal discrepancies as the causative factor is not enough mentioned in relation to bruxism. Objective. The main objective of this paper was to evaluate the connection between occlusal factors and nocturnal parafunctional activities (occlusal disharmonies and bruxism. Method. Two groups were formed- experimental of 15 persons with signs and symptoms of nocturnal parafunctional activity of mandible (mean age 26.6 years and control of 42 persons with no signs and symptoms of bruxism (mean age 26.3 yrs.. The computerized occlusal analyses were performed using the T-Scan II system (Tekscan, Boston, USA. 2D occlusograms were analyzed showing the occlusal force, the center of the occlusal force with the trajectory and the number of antagonistic tooth contacts. Results. Statistically significant difference of force distribution was found between the left and the right side of the arch (L%-R% (t=2.773; p<0.02 in the group with bruxism. The difference of the centre of occlusal force - COF trajectory between the experimental and control group was not significant, but the trajectory of COF was longer in the group of

  10. Model and Simulation of Network Crisis Information Diffusion under Uncertain Environment

    Directory of Open Access Journals (Sweden)

    Yi-Rui Deng

    2016-01-01

    Full Text Available Network crisis information diffusion will have a certain impact on the public’s psychology and behavior and will cause harm to the normal operation social of the public system and the effective allocation of the public resources. So we should timely control the key factors which affect the diffusion process to reduce the damage. Using cellular automata theory, the paper views the public as a series of cellular automata and sets up some cellular state evolution rules. With the help of MATLAB simulated evolution, this paper explores the diffusion rule of crisis information diffusion process and finds out the key factors of crisis information diffusion process and its influence on the diffusion scale and effect, so as to put forward coping strategies. It is hoped that this paper provides reference for the theoretical study of the crisis information diffusion and provides suggestion for the real world to control the crisis information diffusion.

  11. 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.

  12. Probing the Effects of Stochasticity in Biochemical Reaction Networks using Multiscale Simulation

    CERN Document Server

    Harris, Leonard A; Majusiak, Emily R; Clancy, Paulette

    2007-01-01

    Using our recent contribution, the "partitioned leaping algorithm" [L. A. Harris and P. Clancy, J. Chem. Phys. 125, 144107 (2006)], we investigate the effects of stochasticity in two model biochemical reaction networks. By considering situations both where "leaping" proves beneficial and where it does not, we gain valuable insight that can aid in and advance the use of leaping methods in computational biology. In particular, we identify reaction subnetworks with small populations and large rate constants as a major bottleneck for leaping. We also demonstrate the use of "model reduction" in conjunction with leaping to circumvent this problem and expose a current need in this area: a model-reduction hierarchy analogous to that on which the leaping methods are based [D. T. Gillespie, J. Chem. Phys. 113, 297 (2000); 115, 1716 (2001)]. In situations where leaping is seen to perform well, we emphasize the significant advantages to using these methods over more traditional simulation approaches. We show how leaping ...

  13. Object-Oriented NeuroSys: Parallel Programs for Simulating Large Networks of Biologically Accurate Neurons

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco, P; Miller, P; Kim, J; Leese, T; Zabiyaka, Y

    2003-05-07

    Object-oriented NeuroSys (ooNeuroSys) is a collection of programs for simulating very large networks of biologically accurate neurons on distributed memory parallel computers. It includes two principle programs: ooNeuroSys, a parallel program for solving the large systems of ordinary differential equations arising from the interconnected neurons, and Neurondiz, a parallel program for visualizing the results of ooNeuroSys. Both programs are designed to be run on clusters and use the MPI library to obtain parallelism. ooNeuroSys also includes an easy-to-use Python interface. This interface allows neuroscientists to quickly develop and test complex neuron models. Both ooNeuroSys and Neurondiz have a design that allows for both high performance and relative ease of maintenance.

  14. A hybrid mortar virtual element method for discrete fracture network simulations

    Science.gov (United States)

    Benedetto, Matías Fernando; Berrone, Stefano; Borio, Andrea; Pieraccini, Sandra; Scialò, Stefano

    2016-02-01

    The most challenging issue in performing underground flow simulations in Discrete Fracture Networks (DFN) is to effectively tackle the geometrical difficulties of the problem. In this work we put forward a new application of the Virtual Element Method combined with the Mortar method for domain decomposition: we exploit the flexibility of the VEM in handling polygonal meshes in order to easily construct meshes conforming to the traces on each fracture, and we resort to the mortar approach in order to ;weakly; impose continuity of the solution on intersecting fractures. The resulting method replaces the need for matching grids between fractures, so that the meshing process can be performed independently for each fracture. Numerical results show optimal convergence and robustness in handling very complex geometries.

  15. Compact model of power MOSFET with temperature dependent Cauer RC network for more accurate thermal simulations

    Science.gov (United States)

    Marek, Juraj; Chvála, Aleš; Donoval, Daniel; Príbytný, Patrik; Molnár, Marián; Mikolášek, Miroslav

    2014-04-01

    A new, more accurate SPICE-like model of a power MOSFET containing a temperature dependent thermal network is described. The designed electro-thermal MOSFET model consists of several parts which represent different transistor behavior under different conditions such as reverse bias, avalanche breakdown and others. The designed model is able to simulate destruction of the device as thermal runaway and/or overcurrent destruction during the switching process of a wide variety of inductive loads. Modified thermal equivalent circuit diagrams were designed taking into account temperature dependence of thermal resistivity. The potential and limitations of the new models are presented and analyzed. The new model is compared with the standard and empirical models and brings a higher accuracy for rapid heating pulses. An unclamped inductive switching (UIS) test as a stressful condition was used to verify the proper behavior of the designed MOSFET model.

  16. 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.

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

    Science.gov (United States)

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George

    2014-11-01

    The aim of the present work is to address the closure problem for hemodynamics 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. We model blood flow in the sub-pixel vasculature by using a nonlinear 1D model in self-similar networks of compliant arteries that mimic the structure and hierarchy of vessels in the meso-vascular regime. The proposed model accounts for wall viscoelasticity and non-Newtonian flow effects in arterioles, overcomes cut-off radius sensitivity issues by introducing a monotonically decreasing artery length to radius ratio across different generations of the fractal tree, and convergences to a periodic state in just two cardiac cycles. The resulting fractal trees typically consist of thousands to millions of arteries, posing the need for efficient parallel algorithms. To this end, we have developed a scalable hybrid MPI/OpenMP solver that is capable of computing near real-time solutions. The proposed model is tested on a large patient-specific cranial network returning physiological flow and pressure wave predictions without requiring any parameter estimation or calibration procedures.

  19. Application of RBFN network and GM (1, 1) for groundwater level simulation

    Science.gov (United States)

    Li, Zijun; Yang, Qingchun; Wang, Luchen; Martín, Jordi Delgado

    2017-10-01

    Groundwater is a prominent resource of drinking and domestic water in the world. In this context, a feasible water resources management plan necessitates acceptable predictions of groundwater table depth fluctuations, which can help ensure the sustainable use of a watershed's aquifers for urban and rural water supply. Due to the difficulties of identifying non-linear model structure and estimating the associated parameters, in this study radial basis function neural network (RBFNN) and GM (1, 1) models are used for the prediction of monthly groundwater level fluctuations in the city of Longyan, Fujian Province (South China). The monthly groundwater level data monitored from January 2003 to December 2011 are used in both models. The error criteria are estimated using the coefficient of determination ( R 2), mean absolute error (E) and root mean squared error (RMSE). The results show that both the models can forecast the groundwater level with fairly high accuracy, but the RBFN network model can be a promising tool to simulate and forecast groundwater level since it has a relatively smaller RMSE and MAE.

  20. Efficient Simulation of Wing Modal Response: Application of 2nd Order Shape Sensitivities and Neural Networks

    Science.gov (United States)

    Kapania, Rakesh K.; Liu, Youhua

    2000-01-01

    At the preliminary design stage of a wing structure, an efficient simulation, one needing little computation but yielding adequately accurate results for various response quantities, is essential in the search of optimal design in a vast design space. In the present paper, methods of using sensitivities up to 2nd order, and direct application of neural networks are explored. The example problem is how to decide the natural frequencies of a wing given the shape variables of the structure. It is shown that when sensitivities cannot be obtained analytically, the finite difference approach is usually more reliable than a semi-analytical approach provided an appropriate step size is used. The use of second order sensitivities is proved of being able to yield much better results than the case where only the first order sensitivities are used. When neural networks are trained to relate the wing natural frequencies to the shape variables, a negligible computation effort is needed to accurately determine the natural frequencies of a new design.