Interim Service ISDN Satellite (ISIS) network model for advanced satellite designs and experiments
Pepin, Gerard R.; Hager, E. Paul
1991-01-01
The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Network Model for Advanced Satellite Designs and Experiments describes a model suitable for discrete event simulations. A top-down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ISDN modeling abstractions are added to permit the determination and performance for the NASA Satellite Communications Research (SCAR) Program.
Examining ISIS Support and Opposition Networks on Twitter
2016-01-01
Examining ISIS Support and Opposition Networks on Twitter Elizabeth Bodine-Baron, Todd C. Helmus, Madeline Magnuson, Zev Winkelman C O R P O R A T...Syria (ISIS), like no other terrorist organization before, has used Twitter and other social media channels to broadcast its message, inspire followers...and recruit new fighters. Though much less heralded, ISIS opponents have also taken to Twitter to cas- tigate the ISIS message. This report draws on
A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment
Directory of Open Access Journals (Sweden)
Sayadi Bessem
2005-01-01
Full Text Available This paper develops a new multiuser detector based on a network of kalman filters (NKF dealing with multiple access-interference (MAI, intersymbol Interference (ISI, and an impulsive observation noise. The two proposed schemes are based on the modeling of the DS-CDMA system by a discrete-time linear system that has non-Gaussian state and measurement noises. By approximating the non-Gaussian densities of the noises by a weighted sum of Gaussian terms and under the common MMSE estimation criterion, we first derive an NKF detector. This version is further optimized by introducing a feedback exploiting the ISI interference structure. The resulting scheme is an NKF detector based on a likelihood ratio test (LRT. Monte-Carlo simulations have shown that the NKF and the NKF based on LRT detectors significantly improve the efficiency and the performance of the classical Kalman algorithm.
Can Counter-Gang Models be Applied to Counter ISIS’s Internet Recruitment Campaign
2016-06-10
limitation that exists is the lack of reliable statistics from social media companies in regards to the quantity of ISIS-affiliated sites, which exist on... statistics , they have approximately 320-million monthly active users with thirty-five-plus languages supported and 77 percent of accounts located...Justice and Delinquency Prevention program. For deterrence-based models, the primary point of research is focused deterrence models with emphasis placed
Spike trains in Hodgkin-Huxley model and ISIs of acupuncture manipulations
International Nuclear Information System (INIS)
Wang Jiang; Si Wenjie; Che Yanqiu; Fei Xiangyang
2008-01-01
The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters and shows a variety of qualitatively different behaviors depending on the parameter values. Under stimulation of an external periodic voltage, the ISIs (interspike intervals) of a HH model are investigated in this work, while the frequency of the voltage is taken as the controlling parameter. As well-known, the science of acupuncture and moxibustion is an important component of Traditional Chinese Medicine with a long history. Although there are a number of different acupuncture manipulations, the method for distinguishing them is rarely investigated. With the idea of ISI, we study the electrical signal time series at the spinal dorsal horn produced by three different acupuncture manipulations in Zusanli point and present an effective way to distinguish them
Spike trains in Hodgkin-Huxley model and ISIs of acupuncture manipulations
Energy Technology Data Exchange (ETDEWEB)
Wang Jiang [School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072 (China)], E-mail: jiangwang@tju.edu.cn; Si Wenjie; Che Yanqiu; Fei Xiangyang [School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072 (China)
2008-05-15
The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters and shows a variety of qualitatively different behaviors depending on the parameter values. Under stimulation of an external periodic voltage, the ISIs (interspike intervals) of a HH model are investigated in this work, while the frequency of the voltage is taken as the controlling parameter. As well-known, the science of acupuncture and moxibustion is an important component of Traditional Chinese Medicine with a long history. Although there are a number of different acupuncture manipulations, the method for distinguishing them is rarely investigated. With the idea of ISI, we study the electrical signal time series at the spinal dorsal horn produced by three different acupuncture manipulations in Zusanli point and present an effective way to distinguish them.
From ISIS to CouchDB: Databases and Data Models for Bibliographic Records
Directory of Open Access Journals (Sweden)
Luciano Ramalho
2011-04-01
Full Text Available For decades bibliographic data has been stored in non-relational databases, and thousands of libraries in developing countries still use ISIS databases to run their OPACs. Fast forward to 2010 and the NoSQL movement has shown that non-relational databases are good enough for Google, Amazon.com and Facebook. Meanwhile, several Open Source NoSQL systems have appeared. This paper discusses the data model of one class of NoSQL products, semistructured, document-oriented databases exemplified by Apache CouchDB and MongoDB, and why they are well-suited to collective cataloging applications. Also shown are the methods, tools, and scripts used to convert, from ISIS to CouchDB, bibliographic records of LILACS, a key Latin American and Caribbean health sciences index operated by the Pan-American Health Organization.
Directory of Open Access Journals (Sweden)
R. G. Gillies
2007-02-01
Full Text Available The enhanced Polar Outflow Probe (ePOP is scheduled to be launched as part of the Cascade Demonstrator Small-Sat and Ionospheric Polar Explorer (CASSIOPE satellite in early 2008. A Radio Receiver Instrument (RRI on ePOP will receive HF transmissions from various ground-based transmitters. In preparation for the ePOP mission, data from a similar transionospheric experiment performed by the International Satellites for Ionospheric Studies (ISIS II satellite has been studied. Prominent features in the received 9.303-MHz signal were periodic Faraday fading of signal intensity at rates up to 13 Hz and a time of arrival delay between the O- and X-modes of up to 0.8 ms. Both features occurred when the satellite was above or south of the Ottawa transmitter. Ionospheric models for ray tracing were constructed using both International Reference Ionosphere (IRI profiles and local peak electron density values from ISIS ionograms. Values for fade rate and differential mode delay were computed and compared to the values observed in the ISIS II data. The computed values showed very good agreement to the observed values of both received signal parameters when the topside sounding foF2 values were used to scale IRI profiles, but not when strictly modelled IRI profiles were used. It was determined that the primary modifier of the received signal parameters was the foF2 density and not the shape of the profile. This dependence was due to refraction, at the 9.303-MHz signal frequency, causing the rays to travel larger distances near the peak density where essentially all the mode splitting occurred. This study should assist in interpretation of ePOP RRI data when they are available.
Operation and Thermal Modeling of the ISIS H– Source from 50 to 2 Hz Repetition Rates
Pereira, H; Lettry, J
2013-01-01
CERN’s Linac4 accelerator H− ion source, currently under construction, will operate at a 2 Hz repetition rate, with pulse length of 0.5 ms and a beam current of 80 mA. Its reliability must exceed 99 % with a mandatory 3 month uninterrupted operation period. A Penning ion source is successfully operated at ISIS; at 50 Hz repetition rate it reliably provides 55 mA H− pulses of 0.25 ms duration over 1 month. The discharge plasma ignition is very sensitive to the temperatures of the discharge region, especially of its cathode. The investigation by modeling and measurement of operation parameters suitable for arc ignition and H− production at 2 Hz is of paramount importance and must be understood prior to the implementation of discharge ion sources in the Linac4 accelerator. In its original configuration, the ISIS H− source delivers beam only if the repetition rate is above 12.5 Hz, this paper describes the implementation of a temperature control of the discharge region aiming at lower repetition rate op...
International Nuclear Information System (INIS)
Rao, B.P.C.; Shyamsunder, M.T.; Bhattacharya, D.K.; Raj, Baldev
1992-01-01
Non-destructive Evaluation (NDE) plays a major role in ensuring the safe and reliable operation of PHWRs which are the mainstay of India's nuclear power programme. An important in-service inspection (ISI) requirement in these reactors is carried out through Eddy Current Testing (ECT) of the pressure tube (PT)/calandria tube (CT) assemblies. The material of construction of these assemblies is zircaloy-2. The two main objectives of this ISI are the detection of garter spring between CT and PT and the profiling of gap between CT and PT. The paper discusses the work carried out at the authors' laboratory on the development of ECT probes for ISI of PT/CT assemblies. Emphasis has been given on the work done on the design and optimisation of the probes using computer modeling. A 2-D finite element code has been developed for this purpose. The code is developed around a diffusion equation which can be derived from Maxwell's equations governing the electromagnetic phenomenon. An axisymmetry has been considered, since the probes are bobbin type. Results of impedance plane outputs obtained by modelling and those by experiments using actual probes have shown good matching. Salient features of an indigenously developed interactive PC based data acquisition, analysis and retrieval system to cater to ISI of PC/CT assemblies are described. (author). 10 refs., 7 figs
Effects of the ISIS Recommender System for Navigation Support in Self-Organised Learning Networks
Drachsler, Hendrik; Hummel, Hans; van den Berg, Bert; Eshuis, Jannes; Waterink, Wim; Nadolski, Rob; Berlanga, Adriana; Boers, Nanda; Koper, Rob
2009-01-01
The need to support users of the Internet with the selection of information is becoming more important. Learners in complex, self-organising Learning Networks have similar problems and need guidance to find and select most suitable learning activities, in order to attain their lifelong learning goals in the most efficient way. Several research…
International Nuclear Information System (INIS)
Biggin, S.
1988-07-01
The paper presents the 1988 Annual Report for ISIS (United Kingdom). A description is given of the accelerator and target station. The capability of ISIS is described including the facilities available and the type of science carried out using the instruments. The development and support activities are outlined, along with the ISIS organisation and user interaction. The appendix contains experimental reports on research work conducted at ISIS. (U.K.)
Wahab, Bilal A.
Petroleum wealth is the lifeblood of Iraq, with the potential to promote prosperity, or become a curse that destabilizes the country and interrupts its economic and political development. The management and sharing of petroleum wealth has been at the center of economic, political and security developments in Iraq since the country's invasion in 2003. This study analyzes Iraq's experiment with petrofederalism, the influence of different actors (e.g. international oil companies and ISIS), and the emergence of Iraqi Kurdistan as a petroregion. Using case study method, it demonstrates how patronage politics exacerbated resource curse in Iraq and resulted in instability.
Pepin, Gerard R.
1992-01-01
The simulation development associated with the network models of both the Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures is documented. The ISIS Network Model design represents satellite systems like the Advanced Communications Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) Program, moves all control and switching functions on-board the next generation ISDN communications satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete event simulation experiments will be performed with these models using various traffic scenarios, design parameters, and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.
International Nuclear Information System (INIS)
Biggin, Sue
1986-07-01
The paper is the first 1985/6 report of the ISIS experimental facility for neutron scattering studies, which commenced operations June 1985, at the Rutherford Laboratory, United Kingdom. The report is divided into eight chapters, including: 1) accelerator, target station and moderators, 2) instruments and related science, 3) techniques, 4) future developments, 5) condensed matter theory research, 6) ISIS organisation and user interaction, 7) publications, and 8) experimental reports. (UK)
International Nuclear Information System (INIS)
Rees, G.H.
1987-01-01
The recent performance of the ISIS spallation neutron source is described and possible developments for the future are outlined. Aims for the near future are to raise the energy and intensity of the 50 Hz proton synchrotron to the design specification. Longer term aims are being evaluated by an International ISIS Project Group and an International Science Advisory Group. The hope is to develop the project in an international context to an improved specification
RUTHERFORD APPLETON: ISIS nice
Energy Technology Data Exchange (ETDEWEB)
Anon.
1986-07-15
The ISIS pulsed spallation neutron source continues to make good progress. In March the machine reached its highest intensity when 5 x 10{sup 12} protons per pulse at 550 MeV and 50 pulses per second were delivered to the neutron production target. This 40 microamperes of mean proton current is 20% of the design performance and confirms once again the potential of ISIS as a powerful accelerator- based pulsed neutron source.
Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann
2015-01-01
Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector.
Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann
2015-01-01
Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector. PMID:25806516
Unsupervised acoustic model training: comparing South African English and isiZulu
CSIR Research Space (South Africa)
Kleynhans, N
2015-11-01
Full Text Available and requires funding, time and expertise. Lightly-supervised training techniques, however, provide a means to rapidly transcribe audio, thus reducing the initial resource investment to begin the modelling process. Our findings suggest that the lightly...
1981-01-01
ISIS stands for Identification of Secondaries by Ionization Sampling. It was a drift chamber with an active volume of about 40 m3 built by Oxford University as a particle identifier for the European Hybrid Spectrometer (EHS). The photo shows the electrostatic grading structure and the central anode-wire plane, with Roger Giles standing just under it (Annual Report 1981 p. 57, Fig. 4). ISIS-II differed from the prototype ISIS-I only in the depth of the track (4 m instead of 1 m) thus extending the momentum range for particle identification to 50 GeV/c. See Nucl. Instr. and Meth. 224 (1984) 396, and Nucl. Instr. and Meth. 258 (1987) 26.
Collaborative networks: Reference modeling
Camarinha-Matos, L.M.; Afsarmanesh, H.
2008-01-01
Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of
Future data acquisition at ISIS
International Nuclear Information System (INIS)
Pulford, W.C.A.; Quinton, S.P.H.; Johnson, M.W.; Norris, J.
1989-01-01
Data collection techniques at ISIS are fast reaching the point where the current computer systems will no longer be able to migrate the data to long-term storage, let alone enable their analysis at a speed compatible with continuous use of the ISIS instruments. The current data acquisition electronics (DAE 1) and migration path work effectively but have a number of inherent difficulties: (1) Seven instruments are equipped with VAX computers as their Front End Minicomputers (FEM). Unfortunately these machines usually possess insufficient processor power to perform some of the more complex data reduction. This means that the raw data have necessarily to be networked to the HUB computer before analysis. (2) The size of bulk store memory is restricted to 16 Mbytes by the 24 bit address field of Multibus. (3) The DAE error detection and analysis system of FEM is crude. It is clear that the most effective method to improve on this situation is to reduce the data volume flowing between the DAE and the FEM and to provide facilities to monitor data acquisition within the DAE. For these purposes processing power must be incorporated closer to the point of data collection. It has been decided to implement processing elements within DAE 2 (the next generation of DAE) in the form of intelligent memory boards. 6 figs., 1 tab
International Nuclear Information System (INIS)
Finney, J.L.; Gray, D.A.
1989-01-01
The authors review the progress on ISIS, the pulsed neutron source at the Rutherford-Appleton Laboratory, since the last ICANS meeting. The machine is now running regularly at 100 μA at 750 MeV, and delivering neutrons for an increasing UK and international neutron scattering program. The current status of the operating and development instruments is summarized, and some examples given of recent science. 3 refs., 11 figs., 3 tabs
The use of CDS/ISIS software in Africa | Abboy | Innovation
African Journals Online (AJOL)
CDS/ISIS is free-of-charge software that has been developed by UNESCO and is distributed through a network of country distributors and more recently through the World Wide Web. CDS/ISIS is ideally suited for the manipulation of bibliographic data. Literature sources reveal that the use of CDS/ISIS is widespread in Africa ...
Directory of Open Access Journals (Sweden)
Hipólito Pecci Tenrero
2002-01-01
Full Text Available La diosa Isis es una de las divinidades más importantes de Egipto, al extenderse por el Mediterráneo continúa manteniendo esta significación. En el texto siguiente se intenta tratar de una forma sucinta como se ha producido esta expansión, la rapidez en conseguir adeptos fuera de Egipto y la influencia no solo dentro de la sociedad, sino también dentro de la política, así como su desaparición final.The goddess Isis is one of the most important divinities of Egypt, on having spread over the Mediterranean she continúes supporting this significance. In the next text one is tried to treat as a succinct form since this expansión, the rapidity has taken place in followers obtained out of Egypt and the influence not only inside the society, but also inside the politics, asweil as his final disappearance.
United States Counterterrorism on ISIS
Directory of Open Access Journals (Sweden)
ANTON MYNARDY
2016-05-01
Full Text Available The U.S. counter terrorism on ISIS had implemented with various strategies including degrading ISIS’s capability, shaping global coalition to defeat ISIS, and using trained military armed men for Iraq army forces, Kurdi army, Arabian army, and moderate opposition groups to fight against Bassar. In early 2015, U.S. government described the group as “losing this fight” and reported that anti- ISIS operations had killed more than 8,500 fighters, destroyed hundreds of vehicles and heavy weapons systems, and significantly degraded IS command and control capabilities. Unfortunately, ISIS still exists with their weapons. Moreover, the fear against ISIS and the worst conditions it brings are not exclusive in Syria, Iraq and Libya as the conflict has already spread to many countries in Europe. These countries are in dilemma because despite being affected by the conflict, still they intend to give asylum to the refugees, but their concern is that with refugees coming in, there might be exporting of ISIS’s ideologies which leads to bigger and more serious concerns than the possibility of economic instability. Inevitably, there have been questions regarding the existence of ISIS today: How can groups such as ISIS still exists despite being attacked for 3 years by the U.S? The reality is that the U.S. initiated the establishment of new and democratic governments in Afghanistan, Iraq, and Libya few years ago bothers some experts on the continuing existence of ISIS.
Modeling Network Interdiction Tasks
2015-09-17
118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two
Full Service ISDN Satellite (FSIS) network model for advanced ISDN satellite design and experiments
Pepin, Gerard R.
1992-01-01
The Full Service Integrated Services Digital Network (FSIS) network model for advanced satellite designs describes a model suitable for discrete event simulations. A top down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ACTS and the Interim Service ISDN Satellite (ISIS) perform ISDN protocol analyses and switching decisions in the terrestrial domain, whereas FSIS makes all its analyses and decisions on-board the ISDN satellite.
International Nuclear Information System (INIS)
Finney, J.L.
1991-01-01
Two years back, I reported at ICANS X that ISIS was running regularly at 100 μA, 750 MeV, with 9 scheduled neutron instruments and one muon beam line. Overall efficiency, measured as a percentage of time beam on target, was about 72%, and our stated priority was to improve reliability at 100 μA current. Over the past two years, major improvements have been made to several component parts of the system, and reliability so far in 1990 is just below 80%. Regular running periods at 100 μA have been achieved, with 100 μA average current achieved over a period of over a week. On 3 November 1989 a record integrated current over 24 hours of 2571 μA hrs was obtained. Trip rates have been significantly reduced. Three more neutron instruments are now scheduled, bringing the total to 12 neutron and 1 muon instruments. Around 350 neutron experiments were run in the 7 cycles of 1989, and about the same number are expected to be run in the 6 cycles of 1990. (author)
Bilitza, Dieter; Huang, Xueqin; Reinisch, Bodo W.; Benson, Robert F.; Hills, H. Kent; Schar, William B.
2004-02-01
The United States/Canadian ISIS-1 and ISIS-2 satellites collected several million topside ionograms in the 1960s and 1970s with a multinational network of ground stations that provided good global coverage. However, processing of these ionograms into electron density profiles required time-consuming manual scaling of the traces from the analog ionograms, and as a result, only a few percent of the ionograms had been processed into electron density profiles. In recent years an effort began to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2002, approximately 390,000 ISIS-1 and ISIS-2 digital topside-sounder ionograms have been produced. The Topside Ionogram Scaler With True Height Algorithm (TOPIST) program was developed for the automated scaling of the echo traces and for the inversion of these traces into topside electron density profiles. The program is based on the techniques that have been successfully applied in the analysis of ground-based Digisonde ionograms. The TOPIST software also includes an "editing option" for manual scaling of the more difficult ionograms, which could not be scaled during the automated TOPIST run. TOPIST is now successfully scaling ˜60% of the ISIS ionograms, and the electron density profiles are available through the online archive of the National Space Science Data Center at ftp://nssdcftp.gsfc.nasa.gov/spacecraft_data/isis/topside_sounder. This data restoration effort is producing a unique global database of topside electron densities over more than one solar cycle, which will be of particular importance for improvements of topside ionosphere models, especially the International Reference Ionosphere.
International Nuclear Information System (INIS)
Carne, A.; Broome, T.A.; Hogston, J.R.; Holding, M.
1989-01-01
This presentation discusses the two target failures that have occurred, gives the understanding of the causes and indicates the steps being taken to alleviate the problems. At the outset of the design it was understood that the target would have a finite lifetime, due to radiation damage effects, exacerbated by mechanical damage due to thermal cycling and fatigue. Estimates of target lifetime at full intensity are about 2 years for radiation damage swelling and about 10E4 gross thermal excursions. The latter number is the one which gives uncertainty in defining the life of the target, since it is dependent on the reliability of the accelerator and quality of the proton beam. The commissioning of an accelerator system and bringing it up to high beam intensities have their own special problems. There must be protection of components against uncontrolled beam loss, which produces thermal damage, prompt radiation and induced activity. Fast beam trips for beam loss protection, or equipment failures, result in quenches from high temperature in the target which get bigger with increasing beam intensity. But the target itself is a difficult device to make, taking about 12 months to manufacture. Further, changing one is a complex and time consuming task, not without its hazards. There is thus something of a balancing act to bring the accelerator towards specification before the target fails due to thermal cycling fatigue. In the early days of ISIS beam loss protection was the dominant consideration and the target was regarded somewhat as a sacrificial lamb to the goddess of machine reliability. 2 refs., 6 figs
Benthem BHB van; EPI
2007-01-01
The Infectious Diseases Surveillance Information system that collects data of medical microbiology laboratories in the Netherlands (ISIS-MML) is not suitable for early warning of infectious diseases outbreaks. However, the system is appropriate for monitoring trends in antimicrobial resistance.
International Nuclear Information System (INIS)
Max, G
2011-01-01
Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.
Modeling the citation network by network cosmology.
Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing
2015-01-01
Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.
DEFF Research Database (Denmark)
Andersen, Kasper Winther
Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...
Modeling Epidemic Network Failures
DEFF Research Database (Denmark)
Ruepp, Sarah Renée; Fagertun, Anna Manolova
2013-01-01
This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....
Artificial neural network modelling
Samarasinghe, Sandhya
2016-01-01
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .
Domitian between Isis and Minerva
DEFF Research Database (Denmark)
Clausen, Kristine Bülow
2013-01-01
This paper is concerned with the sculptural decoration of the Flavian sanctuary of Isis at Beneventum. It challenges the traditional “Egyptian” appearance of the sanctuary and suggests that “Graeco-Roman” elements, too, played a role in its sculptural decoration. Based on the analysis of a small...
The PRISMA spectrometer at ISIS
International Nuclear Information System (INIS)
Steigenberger, U.; Hagen, M.
1990-01-01
PRISMA stands for PRogetto dell'Istituto di Struttura dell MAteria del CNR. Under an international collaborative agreement signed in 1985 between SERC, the Science and Engineering Research Council, and the Consiglio Nazionale delle Ricerche (CNR), Italy, PRISMA was designed and manufactured by the ISM Laboratory of the CNR at Frascati for installation at ISIS, for use in inelastic neutron scattering experiments. (author)
International Nuclear Information System (INIS)
Hart, J.D.
The evolution of in-service inspection techniques from the Magnox reactors through the AGR constructions is described. The following aspects are mentioned: general principles; factors that have influenced the development of ISI; objectives of ISI; examples drawn from AGR experience; major design changes to accommodate ISI; PWR reactors; occupational safety. (U.K.)
Epithermal neutron instrumentation at ISIS
International Nuclear Information System (INIS)
Gorini, G; Festa, G; Andreani, C
2014-01-01
The advent of pulsed neutron sources makes available high epithermal neutron fluxes (in the energy range between 500 meV and 100 eV). New dedicated instrumentation, such as Resonance Detectors, was developed at ISIS spallation neutron source in the last years to apply the specific properties of this kind of neutron beam to the study of condensed matter. New detection strategies like Filter Difference method and Foil Cycling Technique were also developed in parallel to the detector improvement at the VESUVIO beamline. Recently, epithermal neutron beams were also used at the INES beamline to study elemental and isotopic composition of materials, with special application to cultural heritage studies. In this paper we review a series of epithermal neutron instrumentation developed at ISIS, their evolution over time and main results obtained
KARMEN: neutrino spectroscopy at ISIS
Energy Technology Data Exchange (ETDEWEB)
Drexlin, G [Forschungszentrum Karlsruhe GmbH Technik und Umwelt (Germany). Inst. fuer Kernphysik
1996-11-01
The Karlsruhe-Rutherford Neutrino Experiment KARMEN at the spallation neutron facility ISIS investigates fundamental properties of neutrinos as well as their interactions with matter. Low energy neutrinos with energies up to 50 MeV emitted by the pulsed {nu}-source ISIS are detected by a 56 tonne high resolution liquid scintillation calorimeter. Clear {nu}-signatures allow a reliable search for neutrino oscillations of the type {nu}{sub {mu}}{yields}{nu}{sub e} and {nu}{sub {mu}}{yields}{nu}{sub e} as well as a detailed investigation of neutrino-nucleus interactions in an energy range important for astrophysics. We present the results of the KARMEN experiment from data taking in the period from June 1990 - December 1995. (author) 9 figs., 10 refs.
Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model
Directory of Open Access Journals (Sweden)
Ying Du
2014-01-01
Full Text Available This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.
IAEA Safeguards Information System (ISIS)
International Nuclear Information System (INIS)
1984-10-01
Publication of this technical document should serve for better understanding of the technical and functional features of the IAEA Safeguards Information System (ISIS) within the Agency, as well as in the National Systems of accounting for and control of nuclear material. It will also serve as a foundation for further development and improvement of the design and modifications of the Safeguards Information System and its services as a function of Safeguards implementation
Statistical Models for Social Networks
Snijders, Tom A. B.; Cook, KS; Massey, DS
2011-01-01
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For
Future data acquisition at ISIS
International Nuclear Information System (INIS)
Pulford, W.C.A.; Quinton, S.P.H.; Johnson, M.W.; Norris, J.
1989-01-01
Over the past year ISIS beam intensity has increased steadily to 100 microamps during periods of good running. With the instrument users finding it comparatively easy to set up data-collection runs, we are facing an ever increasing volume of incoming data. Greatly improved detector technology, mainly involving large areas of zinc sulfide phosphor, are expected to contribute much to the capacity of new diffractometers as well as provide an enhancement path for many of the existing ones. It is clear that we are fast reaching the point where if we continue to use our current technology data collection techniques, our computer systems will no longer be able to migrate the data to long-term storage, let alone enable their analysis at a speed compatible with continuous use of the ISIS instruments. The most effect method to improve this situation is to reduce the volume of data flowing between the data acquisition electronics and the front end minicomputers, and to provide facilities to monitor data acquisition within the data acquisition electronics. Processing power must be incorporated closer to the point of data collection. Ways of doing this are discussed and evaluated. (author)
Coevolutionary modeling in network formation
Al-Shyoukh, Ibrahim
2014-12-03
Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.
Coevolutionary modeling in network formation
Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.
2014-01-01
Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.
Modeling online social signed networks
Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru
2018-04-01
People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.
A neighbourhood evolving network model
International Nuclear Information System (INIS)
Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.
2006-01-01
Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development
Implementation of an ISIS Compatible Stereo Processing Chain for 3D Stereo Reconstruction
Tasdelen, E.; Unbekannt, H.; Willner, K.; Oberst, J.
2012-09-01
The department for Planetary Geodesy at TU Berlin is developing routines for photogrammetric processing of planetary image data to derive 3D representations of planetary surfaces. The ISIS software, developed by USGS, Flagstaff, is readily available, open source, and very well documented. Hence, ISIS [1] was chosen as a prime processing platform and tool kit. However, ISIS does not provide a full photogrammetric stereo processing chain. Several components like image matching, bundle block adjustment (until recently) or digital terrain model (DTM) interpolation from 3D object points are missing. Our group aims to complete this photogrammetric stereo processing chain by implementing the missing components, taking advantage of already existing ISIS classes and functionality. With this abstract we would like to report on the development of a new image matching software that is optimized for both orbital and closeranged planetary images and compatible with ISIS formats and routines and an interpolation tool that is developed to create DTMs from large 3-D point clouds.
Frieler, K.; Huber, V.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.
2012-12-01
The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. Over 25 climate impact modelling teams from around the world, working within the agriculture, water, biomes, infrastructure and health sectors, are collaborating to find answers to the question "What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference?". The analysis is based on common, bias-corrected climate projections, and socio-economic pathways. The first, fast-tracked phase of the ISI-MIP has a focus on global impact models. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. Novel metrics, developed to emphasize societal impacts, will be used to identify regional 'hot-spots' of climate change impacts, as well as to quantify the cross-sectoral impact of the increasing frequency of extreme events in future climates. We present here first results from the Fast-Track phase of the project covering impact simulations in the biomes, agriculture and water sectors, in which the societal impacts of climate change are quantified for different levels of global warming. We also discuss the design of the scenario set-up and impact indicators chosen to suit the unique cross-sectoral, multi-model nature of the project.
An intense transmission spectrometer for ISIS
International Nuclear Information System (INIS)
Newport, R.J.; Howells, W.S.
1986-07-01
The report seeks to outline a design for an intense transmission spectrometer (ITS) suitable for installation on the pulsed neutron source ISIS. The performance of the instrument is evaluated and several examples of the areas of science made accessible are discussed. It is shown that the proposed design will represent a scientifically valuable and cost-effective addition to the present suite of ISIS instruments. (author)
ISI PUBLICATIONS MANAGEMENT THROUGH PERFORMANCE INDICATORS
Directory of Open Access Journals (Sweden)
Victor VELTER
2010-09-01
Full Text Available The paper proposes to describe the ways in which the research management and administration department from a certain institution can interfere with specific policies in order to increase the visibility of scientific publications. Scientometric analysis is made on ISI publications of “Constantin Brancsi” University from Targu Jiu and wants to reveal performance indicators able to monitor the visibility of the papers indexed in ThomsonReuters ISI base.
Developing Personal Network Business Models
DEFF Research Database (Denmark)
Saugstrup, Dan; Henten, Anders
2006-01-01
The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...
Mathematical Modelling Plant Signalling Networks
Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.
2013-01-01
methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more
Complex Networks in Psychological Models
Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.
We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.
A model of coauthorship networks
Zhou, Guochang; Li, Jianping; Xie, Zonglin
2017-10-01
A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property
Validation process of ISIS CFD software for fire simulation
International Nuclear Information System (INIS)
Lapuerta, C.; Suard, S.; Babik, F.; Rigollet, L.
2012-01-01
Fire propagation constitutes a major safety concern in nuclear facilities. In this context, IRSN is developing a CFD code, named ISIS, dedicated to fire simulations. This software is based on a coherent set of models that can be used to describe a fire in large, mechanically ventilated compartments. The system of balance equations obtained by combining these models is discretized in time using fractional step methods, including a pressure correction technique for solving hydrodynamic equations. Discretization in space combines two techniques, each proven in the relevant context: mixed finite elements for hydrodynamic equations and finite volumes for transport equations. ISIS is currently in an advanced stage of verification and validation. The results obtained for a full-scale fire test performed at IRSN are presented.
Telecommunications network modelling, planning and design
Evans, Sharon
2003-01-01
Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.
Campus network security model study
Zhang, Yong-ku; Song, Li-ren
2011-12-01
Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.
Generalized Network Psychometrics : Combining Network and Latent Variable Models
Epskamp, S.; Rhemtulla, M.; Borsboom, D.
2017-01-01
We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between
Neural network modeling of emotion
Levine, Daniel S.
2007-03-01
This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.
Modeling of fluctuating reaction networks
International Nuclear Information System (INIS)
Lipshtat, A.; Biham, O.
2004-01-01
Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press
Education and Training on ISIS Research Reactor
International Nuclear Information System (INIS)
Foulon, F.; Badeau, G.; Lescop, B.; Wohleber, X.
2013-01-01
In the frame of academic and vocational programs the National Institute for Nuclear Science and Technology uses the ISIS research reactor as a major tool to ensure a practical and comprehensive understanding of the nuclear reactor physics, principles and operation. A large set of training courses have been developed on ISIS, optimising both the content of the courses and the pedagogical approach. Programs with duration ranging from 3 hours (introduction to reactor operation) to 24 hours (full program for the future operators of research reactors) are carried out on ISIS reactor. The reactor is operated about 350 hours/year for education and training, about 40 % of the courses being carried out in English. Thus, every year about 400 trainees attend training courses on ISIS reactor. We present here the ISIS research reactor and the practical courses that have been developed on ISIS reactor. Emphasis is given to the pedagogical method which is used to focus on the operational and safety aspects, both in normal and incidental operation. We will present the curricula of the academic and vocational courses in which the practical courses are integrated, the courses being targeted to a wide public, including operators of research reactors, engineers involved in the design and operation of nuclear reactors as well as staff of the regulatory body. We address the very positive impact of the courses on the development of the competences and skills of participants. Finally, we describe the Internet Reactor Laboratories (IRL) that are under development and will consist in broadcasting the training courses via internet to remote facilities or institutions
Education and Training on ISIS Research Reactor
Energy Technology Data Exchange (ETDEWEB)
Foulon, F.; Badeau, G.; Lescop, B.; Wohleber, X. [French Atomic Energy and Alternative Energies Commission, Paris (France)
2013-07-01
In the frame of academic and vocational programs the National Institute for Nuclear Science and Technology uses the ISIS research reactor as a major tool to ensure a practical and comprehensive understanding of the nuclear reactor physics, principles and operation. A large set of training courses have been developed on ISIS, optimising both the content of the courses and the pedagogical approach. Programs with duration ranging from 3 hours (introduction to reactor operation) to 24 hours (full program for the future operators of research reactors) are carried out on ISIS reactor. The reactor is operated about 350 hours/year for education and training, about 40 % of the courses being carried out in English. Thus, every year about 400 trainees attend training courses on ISIS reactor. We present here the ISIS research reactor and the practical courses that have been developed on ISIS reactor. Emphasis is given to the pedagogical method which is used to focus on the operational and safety aspects, both in normal and incidental operation. We will present the curricula of the academic and vocational courses in which the practical courses are integrated, the courses being targeted to a wide public, including operators of research reactors, engineers involved in the design and operation of nuclear reactors as well as staff of the regulatory body. We address the very positive impact of the courses on the development of the competences and skills of participants. Finally, we describe the Internet Reactor Laboratories (IRL) that are under development and will consist in broadcasting the training courses via internet to remote facilities or institutions.
Replacement of the ISIS control system
International Nuclear Information System (INIS)
Mannix, R.P.; Barton, C.J.; Brownless, D.M.; Kerr, J.C.
1992-01-01
In operation since 1985, ISIS is the world's most powerful pulsed spallation neutron source. The decision has been taken to replace the existing ISIS control system, which has been in use for over ten years. The problems of such a project, given the legacy of processor specific hardware and software are discussed, a long with the problems associated with incorporating existing interface hardware into any new system. Present progress using commercial workstation based control software is presented with, an assessment of the benefits and pitfalls of such an approach. (author)
Upgrades to the ISIS moderator configuration
International Nuclear Information System (INIS)
Taylor, A.D.
1989-01-01
The current ISIS moderator configuration, was designed in 1980 to provide a flexible set of beams for a hypothetical instrument suite. The use of fluid moderators at three different temperatures offering six faces to the instruments, has proved to be effective. In this paper we discuss an upgrade of these moderators in the light of the current and projected instrument configuration. (author)
Network model of security system
Directory of Open Access Journals (Sweden)
Adamczyk Piotr
2016-01-01
Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.
Current approaches to gene regulatory network modelling
Directory of Open Access Journals (Sweden)
Brazma Alvis
2007-09-01
Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.
Target-Centric Network Modeling
DEFF Research Database (Denmark)
Mitchell, Dr. William L.; Clark, Dr. Robert M.
In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...
The ISI distribution of the stochastic Hodgkin-Huxley neuron.
Rowat, Peter F; Greenwood, Priscilla E
2014-01-01
The simulation of ion-channel noise has an important role in computational neuroscience. In recent years several approximate methods of carrying out this simulation have been published, based on stochastic differential equations, and all giving slightly different results. The obvious, and essential, question is: which method is the most accurate and which is most computationally efficient? Here we make a contribution to the answer. We compare interspike interval histograms from simulated data using four different approximate stochastic differential equation (SDE) models of the stochastic Hodgkin-Huxley neuron, as well as the exact Markov chain model simulated by the Gillespie algorithm. One of the recent SDE models is the same as the Kurtz approximation first published in 1978. All the models considered give similar ISI histograms over a wide range of deterministic and stochastic input. Three features of these histograms are an initial peak, followed by one or more bumps, and then an exponential tail. We explore how these features depend on deterministic input and on level of channel noise, and explain the results using the stochastic dynamics of the model. We conclude with a rough ranking of the four SDE models with respect to the similarity of their ISI histograms to the histogram of the exact Markov chain model.
Remote handling for an ISIS target change
International Nuclear Information System (INIS)
Broome, T.A.; Holding, M.
1989-01-01
During 1987 two ISIS targets were changed. This document describes the main features of the remote handling aspects of the work. All the work has to be carried out using remote handling techniques. The radiation level measured on the surface of the reflector when the second target had been removed was about 800 mGy/h demonstrating that hands on operations on any part of the target reflector moderator assembly is not practical. The target changes were the first large scale operations in the Target Station Remote Handling Cell and a great deal was learned about both equipment and working practices. Some general principles emerged which are applicable to other active handling tasks on facilities like ISIS and these are discussed below. 8 figs
Add Deterrence to the Strategy Against ISIS
2017-03-31
economic or social structures of a country or international organization.2 The U.S. 2015 National Military Strategy outlines an objective of...no way of determining their effectiveness. For example, the apparent random drone targeting of ISIS and Al Qaeda leadership from Pakistan to Yemen ...perception-shaping, cyber warfare, media operations, and legal investigative efforts to enhance legitimacy. A part of the strategy emphasizes publicly
Continuum Model for River Networks
Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.
1995-07-01
The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.
A molecular dynamics simulation code ISIS
International Nuclear Information System (INIS)
Kambayashi, Shaw
1992-06-01
Computer simulation based on the molecular dynamics (MD) method has become an important tool complementary to experiments and theoretical calculations in a wide range of scientific fields such as physics, chemistry, biology, and so on. In the MD method, the Newtonian equations-of-motion of classical particles are integrated numerically to reproduce a phase-space trajectory of the system. In the 1980's, several new techniques have been developed for simulation at constant-temperature and/or constant-pressure in convenient to compare result of computer simulation with experimental results. We first summarize the MD method for both microcanonical and canonical simulations. Then, we present and overview of a newly developed ISIS (Isokinetic Simulation of Soft-spheres) code and its performance on various computers including vector processors. The ISIS code has a capability to make a MD simulation under constant-temperature condition by using the isokinetic constraint method. The equations-of-motion is integrated by a very accurate fifth-order finite differential algorithm. The bookkeeping method is also utilized to reduce the computational time. Furthermore, the ISIS code is well adopted for vector processing: Speedup ratio ranged from 16 to 24 times is obtained on a VP2600/10 vector processor. (author)
Flaw distribution development from vessel ISI data
International Nuclear Information System (INIS)
Foulds, J.R.; Kennedy, E.L.; Basin, S.L.; Rosinski, S.T.
1991-01-01
Previous attempts to develop flaw distributions for use in the structural integrity evaluation of pressurized water reactor (PWR) vessels have aimed at the estimation of a ''generic'' distribution applicable to all vessels. In contrast, this paper describes the analysis of vessel-specific in-service inspection (ISI) data for the development of a flaw distribution reliably representative of the condition of the particular vessel inspected. The application of the methodology may be extended to other vessels, but has been primarily developed for PWR reactor vessels. For this study, the flaw data analyzed included data obtained from three recently performed PWR vessel ISIs and from laboratory inspection of selected weldment sections of the Midland reactor vessel. The variability in both the character of the reviewed data (size range of flaws, number of flaws) and the UT (ultrasonic test) inspection system performance identified a need for analyzing the inspection results on a vessel-, or data set-specific basis. For this purpose, traditional histogram-based methods were inadequate, and a new methodology that can accept a very small number of flaws (typical of vessel-specific ISI results) and that includes consideration of inspection system flaw detection reliability, flaw sizing accuracy and flaw detection threshold, was developed. Results of the application of the methodology to each of the four PWR reactor vessel cases studied are presented and discussed
The ISIS Open GENIE user manual
International Nuclear Information System (INIS)
Akeroyd, F.A.; Ashworth, R.L.; Campbell, S.I.; Johnston, S.D.; Martin, J.M.; Moreton-Smith, C.M.; Sivia, D.S.
2000-01-01
This manual should enable you to become familiar with Open GENIE quickly and easily. It therefore complements the Open GENIE Reference Manual which should be used to understand the full meaning of Open GENIE commands. The reference manual is accessible on the ISIS web server at: http://www.isis.rl.ac.uk/GENIEReferenceManual/ and the user manual is planned to be accessible by January '98 at http://www.isis.rl.ac.ukIGENIEUserManual/. The Open GENIE User Manual is separated into two parts: Part A. The User Manual. An introduction to the use of Open GENIE. Part B. The Installation Guide. General information on how to install and run Open GENIE. Assuming that you are new to Open GENIE and have just downloaded a copy you will need to consult the Installation Guide to get Open GENIE installed on your machine. After this we recommend you experiment with some of the example files to get an idea of the capabilities of Open GENIE. For further information, comments, additions of routines that you feel should be included, please contact us at genie at isise.rl.ac.uk
Biological transportation networks: Modeling and simulation
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.
Network modelling methods for FMRI.
Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W
2011-01-15
There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.
Research on the model of home networking
Yun, Xiang; Feng, Xiancheng
2007-11-01
It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network
Mathematical Modelling Plant Signalling Networks
Muraro, D.
2013-01-01
During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.
Energy modelling in sensor networks
Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.
2007-06-01
Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.
Automated Processing of ISIS Topside Ionograms into Electron Density Profiles
Reinisch, bodo W.; Huang, Xueqin; Bilitza, Dieter; Hills, H. Kent
2004-01-01
Modeling of the topside ionosphere has for the most part relied on just a few years of data from topside sounder satellites. The widely used Bent et al. (1972) model, for example, is based on only 50,000 Alouette 1 profiles. The International Reference Ionosphere (IRI) (Bilitza, 1990, 2001) uses an analytical description of the graphs and tables provided by Bent et al. (1972). The Alouette 1, 2 and ISIS 1, 2 topside sounder satellites of the sixties and seventies were ahead of their times in terms of the sheer volume of data obtained and in terms of the computer and software requirements for data analysis. As a result, only a small percentage of the collected topside ionograms was converted into electron density profiles. Recently, a NASA-funded data restoration project has undertaken and is continuing the process of digitizing the Alouette/ISIS ionograms from the analog 7-track tapes. Our project involves the automated processing of these digital ionograms into electron density profiles. The project accomplished a set of important goals that will have a major impact on understanding and modeling of the topside ionosphere: (1) The TOPside Ionogram Scaling and True height inversion (TOPIST) software was developed for the automated scaling and inversion of topside ionograms. (2) The TOPIST software was applied to the over 300,000 ISIS-2 topside ionograms that had been digitized in the fkamework of a separate AISRP project (PI: R.F. Benson). (3) The new TOPIST-produced database of global electron density profiles for the topside ionosphere were made publicly available through NASA s National Space Science Data Center (NSSDC) ftp archive at . (4) Earlier Alouette 1,2 and ISIS 1, 2 data sets of electron density profiles from manual scaling of selected sets of ionograms were converted fiom a highly-compressed binary format into a user-friendly ASCII format and made publicly available through nssdcftp.gsfc.nasa.gov. The new database for the topside ionosphere established
Biological transportation networks: Modeling and simulation
Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.
2015-01-01
We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation
Business Models for NFC based mobile payments
Johannes Sang Un Chae; Jonas Hedman
2015-01-01
Purpose: The purpose of the paper is to develop a business model framework for NFC based mobile payment solutions consisting of four mutually interdepended components: the value service, value network, value architecture, and value finance. Design: Using a comparative case study method, the paper investigates Google Wallet and ISIS Mobile Wallet and their underlying business models. Findings: Google Wallet and ISIS Mobile Wallet are focusing on providing an enhanced customer experienc...
An evolving network model with community structure
International Nuclear Information System (INIS)
Li Chunguang; Maini, Philip K
2005-01-01
Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties
Brand Marketing Model on Social Networks
Directory of Open Access Journals (Sweden)
Jolita Jezukevičiūtė
2014-04-01
Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.
The ISIS pre-injector reconfiguration
Energy Technology Data Exchange (ETDEWEB)
Wood, T., E-mail: trevor.wood@stfc.ac.uk; Faircloth, D. C.; Lawrie, S. R.; Letchford, A. P.; Whitehead, M. O.; Pike, T.; Perkins, M. [ISIS Pulsed Spallation Neutron and Muon Facility, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Oxford, Oxfordshire (United Kingdom)
2016-02-15
With the introduction of a new “low energy beams” group at ISIS, the decision was taken to expand the ion source area. This paper will explain what actions were taken, how this has improved the present working environment and how the space will be used to accommodate a medium energy beam transport (MEBT) section after the existing radio-frequency quadrupole. The MEBT will incorporate three 202.5 MHz re-bunching cavities and will achieve a transmission of 96% with minimal emittance growth.
A novel Direct Small World network model
Directory of Open Access Journals (Sweden)
LIN Tao
2016-10-01
Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.
RMBNToolbox: random models for biochemical networks
Directory of Open Access Journals (Sweden)
Niemi Jari
2007-05-01
Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.
Introducing advanced ISI requirements at Paks NPP for supporting the LTO
International Nuclear Information System (INIS)
Trampus, P.; Ratkai, S.
2012-01-01
The four VVER-440 model 213 units in operation at Paks NPP, Hungary, are facing to approach their licensed term of operation, which is 30 years. To extend the safe operation of the units beyond the original licensed term by additional 20 years belongs to the highest priorities of the owners/operator of MVM Paks NPP. According to the nuclear legislation, a formal license renewal application for the extended period has to be submitted to the Hungarian Atomic Energy Authority. A significant feature of the license renewal process is the demonstration of the effectiveness of the currently applied ageing management program. ISI is an essential part of the ageing management program thus the adequate ISI techniques and the tailor made requirements have to be incorporated in it. To cope with the expectations originating from the LTO at Paks NPP, it was decided to replace the original Soviet based ISI system by the widely applied ASME BPVC Section XI requirements. Additionally, in 2011 a new nuclear regulation was issued in Hungary, in which the ISI requirements have also been changed. This paper intends to present the entire structure of the new Hungarian regulation related to the ISI but mainly focusing on the deviation to the ASME Section XI with the perspective of the licence renewal. (author)
Conceptional design and some application for ISI systems of 'Monju'
International Nuclear Information System (INIS)
Nakamura, Takashi; Rindo, Hiroshi; Ara, Kuniaki; Kamimura, Takeo; Tsuzuki, Satoshi; Morimoto, Kazuo; Nagaoka, Etsuo; Ikeda, Naoaki.
1987-01-01
In order to fit the Monju system for inspection during use of the (prototype FBR) ''Monju'' plant, a system concept necessary for this plant has been established and part of the machinery has been tested, on the basis of ISI light water reactor and thermal plant technology. Electromagnetic acoustic testing equipment (EMAT), which is drawing attention for the volumetric examination without contact, and also a wall-to-wall four-wheel self-propelled vehicle, as an ISI tool for R/V of FBR, are both being developed. Contents are the following: basic concept and development of ISI system - reactor vessel proper and inlet piping ISI system, and concept of steam generator evaporator heat exchanger tube ISI system; development of ISI systems - experimental self-propelled four-wheel tool, and EMAT signal processing unit. (Mori, K.)
Brand Marketing Model on Social Networks
Jolita Jezukevičiūtė; Vida Davidavičienė
2014-01-01
The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...
Brand marketing model on social networks
Jezukevičiūtė, Jolita; Davidavičienė, Vida
2014-01-01
Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...
Network Bandwidth Utilization Forecast Model on High Bandwidth Network
Energy Technology Data Exchange (ETDEWEB)
Yoo, Wucherl; Sim, Alex
2014-07-07
With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.
Network bandwidth utilization forecast model on high bandwidth networks
Energy Technology Data Exchange (ETDEWEB)
Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2015-03-30
With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.
Magnetosphere VLF observation by satellite ISIS
International Nuclear Information System (INIS)
Ondo, Tadanori; Nakamura, Yoshikatsu; Watanabe, Shigeaki; Murakami, Toshimitsu
1978-01-01
On the basis of the VLF (50 Hz -- 30 kHz) electric field data from the satellite ISIS, the following works carried out in The Radio Research Laboratories are described: deuteron whistler and whistler duct, detection of plasmapause by LHR hiss, and the origin of 5 kHz hiss at low/middle latitudes. The deuteron whistlers are observable distinctly only at low latitude because of gyro-frequency and the frequency resolution of spectral analyzers. Whistler echo occurs when a whistler moves back and forth through a duct along the line of magnetic force, so it is considered that the ISIS satellite crosses the duct. The variation in ion composition around plasmapause obtained through LHR hiss is explainable by the plasamapause position and the magnetic storm effect on the plasamapause. Concerning the narrow band hiss of 5 kHz +- 1.0 kHz frequently observed on the ground at low/middle latitudes, it may occur around plasmapause, propagate through the ionosphere and then to the ground in waveguide mode, or otherwise, it may occur above the ionosphere and then propagate directly to the ground penetrating through the ionosphere. (J.P.N.)
An acoustical model based monitoring network
Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der
2010-01-01
In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the
Bounds on the Capacity of ASK Molecular Communication Channels with ISI
Ghavami, Siavash; Adve, Raviraj; Lahouti, Farshad
2015-01-01
There are now several works on the use of the additive inverse Gaussian noise (AIGN) model for the random transit time in molecular communication~(MC) channels. The randomness invariably causes inter-symbol interference (ISI) in MC, an issue largely ignored or simplified. In this paper we derive an upper bound and two lower bounds for MC based on amplitude shift keying (ASK) in presence of ISI. The Blahut-Arimoto algorithm~(BAA) is modified to find the input distribution of transmitted symbol...
Spinal Cord Injury Model System Information Network
... the UAB-SCIMS More The UAB-SCIMS Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network as a resource to promote knowledge in the ...
Eight challenges for network epidemic models
Directory of Open Access Journals (Sweden)
Lorenzo Pellis
2015-03-01
Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.
Flaw distributions and use of ISI data in RPV integrity evaluations
International Nuclear Information System (INIS)
Dimitrijevic, V.; Ammirato, F.
1993-01-01
A probabilistic method for developing post-inspection flaw distributions has been developed that explicitly accounts for the capability of the inspection procedure to detect and size flaws. This methodology has been used to develop flaw distributions for calculating reactor vessel failure probability under postulated pressurized thermal shock (PTS) conditions. Realistic flaw distributions are important because plant-specific PTS safety assessments are very sensitive to assumptions made about major flaw parameters such as density, size, shape, and location. PTS analysis made in the past do not consider ISI. Two main reasons are (1) lack of a general and approved methodology which provides directions for involvement of ISI results in developing new flaw parameters and (2) lack of confidence in the capability of ISI procedures to detect critical flaws that may be present near the clad-to-base metal interface of the vessel, the location of most concern for PTS conditions. Recent developments in ISI practice, however, have led to substantial improvement in ISI capability and provide a basis for using ISI data to develop plant-specific post-inspection flaw distributions for vessel integrity evaluations. The key components of this evaluation are (1) the generic (preinspection) flaw distribution, (2) a probabilistic flaw detection model, and (3) Bayesian updating of the prior flaw distribution with the detection model to develop a post-inspection flaw distribution. Destructive analysis of RPV weld material was performed to develop data to support the pre-inspection flaw distributions. Since the probability of detection (POD) plays such an important role in the analysis and a high POD is needed to make significant reductions in probability of failure, a procedure was developed to achieve and demonstrate POD greater than 0.9 by using a combination of independent inspection techniques
Entropy Characterization of Random Network Models
Directory of Open Access Journals (Sweden)
Pedro J. Zufiria
2017-06-01
Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.
The model of social crypto-network
Directory of Open Access Journals (Sweden)
Марк Миколайович Орел
2015-06-01
Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks
Joseph, Kenneth; Carley, Kathleen M.
2017-01-01
The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets. PMID:29194446
Introducing Synchronisation in Deterministic Network Models
DEFF Research Database (Denmark)
Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.
2006-01-01
The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...
Bayesian Network Webserver: a comprehensive tool for biological network modeling.
Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan
2013-11-01
The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.
Development of PSI and ISI technique
International Nuclear Information System (INIS)
Chung, M.K.; Park, D.Y.; Choi, S.P.; Kim, H.J.; Moon, Y.S.; Shon, G.H.; Kim, T.S.
1983-01-01
This report describes the experimental results of the subjects selected from the PSI/ISI related problems which encountered by us in 1982. The main contents are 1) the characteristics of the typical ECT signals from the steam generator tubes of nuclear power plant and the results of ECT evaluation of Kori-1 steam generators, 2) the experimental result for the research for directional effects of ultrasonic transducers, 3) the basic experiment for the ultrasonic testing technique by immersion testing method, 4) how to write the scan plan of the mechanized ultrasonic testing for nuclear reactor. Attached appendix is a part of necessary materials for the scan plan of the mechanized ultrasonic testing for Kori-2 nuclear reactor. (Author)
RUTHERFORD/APPELTON: ISIS intensity record
International Nuclear Information System (INIS)
Anon.
1993-01-01
The Rutherford Appleton Laboratory in the UK is home to the world's most intense pulsed neutron source. The heart of ISIS is a 50 Hz proton synchrotron accelerating two bunches of protons from 70 to 800 MeV. After extraction the protons, occupying a total pulse length of less than 0.5 microseconds, strike a heavy metal target: the neutrons generated are moderated and directed through channels in the shielding to any of 14 instruments for condensed matter studies. As neutrinos and muons are copious byproducts, major investments have also been made for investigations in these fields. Efficient charge exchange injection into the synchrotron at 70 MeV is achieved using negative hydrogen ions and an aluminium oxide stripping foil. Some particles are lost during trapping and the early acceleration period, but they are captured by graphite-covered beam collectors to reduce machine activation. Later acceleration and fast-extraction are virtually without loss
Inelastic instruments at the ISIS facility
International Nuclear Information System (INIS)
Taylor, A.D.
1988-01-01
This summarises the status of the inelastic spectrometers at the ISIS facility and gives some highlights from their scientific programme. The inelastic spectrometers HET, TFXA and IRIS are now being used routinely by UK and International research groups and have produced notable scientific results. Work has progressed steadily on eVS. The PRISMA spectrometer, the product of a collaboration between CNR, Italy and RAL, was installed this summer. Earlier this year an agreement was reached in principle between the Rutherford Appleton Laboratory and the University of Wurzburg (West Germany) to build a second spectrometer (ROTAX) for the study of coherent inelastic excitations. A more sophisticated technical concept than that of PRISMA, based on a nonuniformly rotating analyser, it will allow a greater flexibility in the choice of dynamic scans. Substantial progress has also been made on the design of MARI, the sister spectrometer to HET, which is being built as part of the UK-Japan collaboration on pulsed neutron scattering. (author)
The Isis operation: working in nuclear environment
International Nuclear Information System (INIS)
Hilmoine, R.
1987-01-01
After describing the upper internal support structures of the Chinon A3 reactor, difficulties of ISIS operation are presented. The different phases to sort out the problem are: in-core topography, conforming the full-scale mock-up to the repair area, learning on this mock-up and in-core reparation. Robots have a telescopic mast 11 m long, 0.22 m in diameter, completed by jointed arms reaching a radius of 2.7 m. The load carrying capacity is then 70 daN and the repeatability is 0.1 mm. Several tool heads are handled by the robot: telemeter and reconstruction, scouring, welding, screwing. A high level computerized control system is organized around central unit monitoring several local units. It allows automatic or semi-automatic working modes. Our experience in operation and possible improvements are described [fr
On ISI effectiveness through inspection qualification
International Nuclear Information System (INIS)
Harutyunov, R.
2000-01-01
There are two units of WWER type in the ANPP. The results of the implementation of the IAEA qualification guidelines for the ANPP Primary Circuit for WWER are presented. The control methods according to the ISI Program are foreseen in the design and implemented during the preparation for the unit 2 restart. The result of control is plugging of more tubes than during the last operation period. During the next years in the presence of the blowdown water activity, the search on defective tubes was performed by Lumhydraulic methods and the tubes were plugged by welding plugs. In 1999 was performed the visual control on the Steam Generator 6 by WNIAES experts and by the ANPP experts from the Metal Laboratory. The result is confirmation of the irreversible process on erosive-corrosion destruction of feed waters distribution header; definition of the defects coordinates defined; detection of sediments within the SG vessel surfaces and in the head exchanged surface tubes. The purpose of the ISI effectiveness improvement is to discover the defects in the base metal and in the welds before developing into a problem at operating level or a safety problem. For the solution on the specific problems at the ANPP the project for technological co-operation with IAEA has been developed. It is necessary to organize training, certification, assessment methodology. The expected results after the project implementation are to establish the base for the equipment qualification body and staff certification; to upgrade the ANPP staff qualification; to prepare a group of experts, supported by ANRA, which to be also involved in the development of NDM national regulators
The status of ISI in the UK nuclear industry
Energy Technology Data Exchange (ETDEWEB)
Bann, T.; Rogerson, A. [AEA Technology, Risley (United Kingdom). Nuclear NDE Services
1999-08-01
This paper reviews the status of in-service inspection (ISI) in UK nuclear power generation industry through the experience of its nuclear utilities. The paper is intended to be a summary of some of the most recent and relevant ISI issues facing the utilities and the solutions devised to address those issues. (orig.)
How to model wireless mesh networks topology
International Nuclear Information System (INIS)
Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M
2013-01-01
The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches
Model checking mobile ad hoc networks
Ghassemi, Fatemeh; Fokkink, Wan
2016-01-01
Modeling arbitrary connectivity changes within mobile ad hoc networks (MANETs) makes application of automated formal verification challenging. We use constrained labeled transition systems as a semantic model to represent mobility. To model check MANET protocols with respect to the underlying
Agent-based modeling and network dynamics
Namatame, Akira
2016-01-01
The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Network structure exploration via Bayesian nonparametric models
International Nuclear Information System (INIS)
Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z
2015-01-01
Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)
Modelling the structure of complex networks
DEFF Research Database (Denmark)
Herlau, Tue
networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...
Journal maps on the basis of Scopus data: a comparison with the Journal Citation Reports of the ISI
Leydesdorff, L.; de Moya-Anegon, F.; Guerrero-Bote, V.P.
2010-01-01
Using the Scopus dataset (1996-2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained in the Journal Citation Reports (JCR) of the Institute of Scientific Information (ISI). Because the
Building functional networks of spiking model neurons.
Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin
2016-03-01
Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
. The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...
Port Hamiltonian modeling of Power Networks
van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R
2012-01-01
In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all
Modelling traffic congestion using queuing networks
Indian Academy of Sciences (India)
Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...
Settings in Social Networks : a Measurement Model
Schweinberger, Michael; Snijders, Tom A.B.
2003-01-01
A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive
Network interconnections: an architectural reference model
Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.
1985-01-01
One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for
Performance modeling of network data services
Energy Technology Data Exchange (ETDEWEB)
Haynes, R.A.; Pierson, L.G.
1997-01-01
Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.
Continuum Modeling of Biological Network Formation
Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias
2017-01-01
We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes
Network models in economics and finance
Pardalos, Panos; Rassias, Themistocles
2014-01-01
Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.
The Isis project: Fault-tolerance in large distributed systems
Birman, Kenneth P.; Marzullo, Keith
1993-01-01
This final status report covers activities of the Isis project during the first half of 1992. During the report period, the Isis effort has achieved a major milestone in its effort to redesign and reimplement the Isis system using Mach and Chorus as target operating system environments. In addition, we completed a number of publications that address issues raised in our prior work; some of these have recently appeared in print, while others are now being considered for publication in a variety of journals and conferences.
Synergistic effects in threshold models on networks
Juul, Jonas S.; Porter, Mason A.
2018-01-01
Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.
Gossip spread in social network Models
Johansson, Tobias
2017-04-01
Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.
Evaluation of EOR Processes Using Network Models
DEFF Research Database (Denmark)
Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette
1998-01-01
The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....
Towards reproducible descriptions of neuronal network models.
Directory of Open Access Journals (Sweden)
Eilen Nordlie
2009-08-01
Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.
Improved Maximum Parsimony Models for Phylogenetic Networks.
Van Iersel, Leo; Jones, Mark; Scornavacca, Celine
2018-05-01
Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.
Modeling, robust and distributed model predictive control for freeway networks
Liu, S.
2016-01-01
In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of
Directory of Open Access Journals (Sweden)
Allision McDowell-Smith
2017-03-01
Full Text Available ISIS recruits on a 24/7 basis in over 21 languages over the Internet using videos, memes, tweets and other social media postings and swarming in on anyone that retweets, likes or endorses their materials to try to seduce them into the group. Their unprecedented social media drive has resulted in over 30,000 foreign fighters from more than 100 countries migrating to Syria and Iraq. ISIS recruitment in the U.S. is for the most part Internet based and has resulted in the actual and attempted recruitment of over 100 individuals residing in the U.S. with over 200 Americans traveling to Syria to join terrorist groups. To date very little counter-narrative material exists and most of it is cognitive versus emotionally impactful. The International Center for the Study of Violent Extremism (ICSVE Breaking the ISIS Brand – the ISIS Defectors Interviews Project has managed to collect 43 ISIS defector interviews and thus far produce two video clips of ISIS defectors denouncing the group which were focus tested in this research in a small normative college student sample of 75 undergraduate students. The results demonstrate that American college students find the videos authentic, disturbing and turn them away from ISIS, fulfilling the goals that the project is aiming for in producing counter-narrative materials.
Pepin, Gerard R.
1992-01-01
The Interim Service Integrated Service Digital Network (ISDN) Satellite (ISIS) Hardware Experiment Development for Advanced Satellite Designs describes the development of the ISDN Satellite Terminal Adapter (ISTA) capable of translating ISDN protocol traffic into Time Division Multiple Access (TDMA) signals for use by a communications satellite. The ISTA connects the Type 1 Network Termination (NT1) via the U-interface on the line termination side of the CPE to the RS-499 interface for satellite uplink. The same ISTA converts in the opposite direction the RS-499 to U-interface data with a simple switch setting.
Pepin, Gerard R.
1992-01-01
The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Hardware Experiment Design for Advanced Satellite Designs describes the design of the ISDN Satellite Terminal Adapter (ISTA) capable of translating ISDN protocol traffic into time division multiple access (TDMA) signals for use by a communications satellite. The ISTA connects the Type 1 Network Termination (NT1) via the U-interface on the line termination side of the CPE to the V.35 interface for satellite uplink. The same ISTA converts in the opposite direction the V.35 to U-interface data with a simple switch setting.
Tool wear modeling using abductive networks
Masory, Oren
1992-09-01
A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.
Modelling of virtual production networks
Directory of Open Access Journals (Sweden)
2011-03-01
Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.
A Network Disruption Modeling Tool
National Research Council Canada - National Science Library
Leinart, James
1998-01-01
Given that network disruption has been identified as a military objective and C2-attack has been identified as the mechanism to accomplish this objective, a target set must be acquired and priorities...
Modeling Epidemics Spreading on Social Contact Networks.
Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua
2015-09-01
Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.
Spatial Epidemic Modelling in Social Networks
Simoes, Joana Margarida
2005-06-01
The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.
Implementing network constraints in the EMPS model
Energy Technology Data Exchange (ETDEWEB)
Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.
2010-02-15
This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)
Role models for complex networks
Reichardt, J.; White, D. R.
2007-11-01
We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.
Modeling the interdependent network based on two-mode networks
An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian
2017-10-01
Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.
Latent variable models are network models.
Molenaar, Peter C M
2010-06-01
Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.
Homophyly/Kinship Model: Naturally Evolving Networks
Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi
2015-10-01
It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.
Defeating ISIS by Winning the War of Ideas
2017-03-17
Partial Fulfillment of the Graduation Requirements Advisor: Lt Col Brande Walton Maxwell Air Force Base, Alabama 17 March 2017 DISTRIBUTION A...with their lives due to economic or emotional struggle could fall victim to ISIS messaging. ISIS messaging is sophisticated, attracting several...slavery, denying women’s rights, rape, torture, and jihadi groups are all forbidden.53 Though many Muslims have been branded as “radical extremists
Neural network tagging in a toy model
International Nuclear Information System (INIS)
Milek, Marko; Patel, Popat
1999-01-01
The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed
An endogenous model of the credit network
He, Jianmin; Sui, Xin; Li, Shouwei
2016-01-01
In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.
Modelling and designing electric energy networks
International Nuclear Information System (INIS)
Retiere, N.
2003-11-01
The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets
Queueing Models for Mobile Ad Hoc Networks
de Haan, Roland
2009-01-01
This thesis presents models for the performance analysis of a recent communication paradigm: \\emph{mobile ad hoc networking}. The objective of mobile ad hoc networking is to provide wireless connectivity between stations in a highly dynamic environment. These dynamics are driven by the mobility of
Modeling GMPLS and Optical MPLS Networks
DEFF Research Database (Denmark)
Christiansen, Henrik Lehrmann; Wessing, Henrik
2003-01-01
. The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...
Cyber threat model for tactical radio networks
Kurdziel, Michael T.
2014-05-01
The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.
Modeling documents with Generative Adversarial Networks
Glover, John
2016-01-01
This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.
Designing Network-based Business Model Ontology
DEFF Research Database (Denmark)
Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz
2015-01-01
Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....
Modeling trust context in networks
Adali, Sibel
2013-01-01
We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others.? In this brief, 'trust context' is defined as the system level description of how the trust evaluation process unfolds.Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout
Mathematical model of highways network optimization
Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.
2017-12-01
The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.
Graphical Model Theory for Wireless Sensor Networks
International Nuclear Information System (INIS)
Davis, William B.
2002-01-01
Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm
Modeling Network Traffic in Wavelet Domain
Directory of Open Access Journals (Sweden)
Sheng Ma
2004-12-01
Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.
Sparsity in Model Gene Regulatory Networks
International Nuclear Information System (INIS)
Zagorski, M.
2011-01-01
We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)
PENGEMBANGAN ISI KURIKULUM PENDIDIKAN TEKNIK ALAT BERAT BERBASIS KEBUTUHAN INDUSTRI
Directory of Open Access Journals (Sweden)
Mochamad Bruri Triyono
2016-12-01
Full Text Available Penelitian ini bertujuan untuk: (1 mengetahui rumusan kompetensi tenaga mekanik alat berat sesuai standar industri; (2 mengetahui kualifikasi tenaga instruktur alat berat yang dibutuhkan industri sesuai standar industri; (3 merumuskan isi kurikulum untuk materi ajar produktif untuk menciptakan tenaga kerja di bidang alat berat. Penelitian ini merupakan penelitian survei dengan model pilihan pengembangan kurikulum Task Analysis. Penelitian dilaksanakan di industri yang bergerak di bidang alat berat dan institusi pendidikan perguruan tinggi dan SMK yang bekerja sama dengan industri alat berat yaitu PT Thiess Contractors Indonesia, PT United Tractors Indonesia, dan PT Trakindo Utama. Hasil penelitian diperoleh bahwa: (1 kompetensi mekanik alat berat meliputi: menerapkan keselamatan dan kesehatan kerja, menguasai dasar mekanik alat berat, melaksanakan perawatan dan perbaikan engine, sistem hidrolik, powertrain, sistem vehicle control, serta sistem kelistrikan alat berat minimal pada level capable (di bawah supervisi; (2 kualifikasi tenaga instruktur alat berat meliputi: memiliki kemampuan mekanik alat berat level III, memiliki kemampuan mengelola pelatihan, memiliki pengalaman kerja, serta mendapatkan pelatihan instruktur; (3 isi kurikulum untuk materi ajar produktif mekanik alat berat meliputi: dasar mekanik alat berat dan keselamatan kerja, dasar engine, dasar hidrolik, dasar vehicle control, dasar kelistrikan, materi sistem engine lanjut, sistem hidrolik lanjut, sistem powertrain lanjut, sistem vehicle control lanjut, sistem kelistrikan lanjut, product training, serta electronic machine control. Kata kunci: kompetensi, instruktur alat berat, isi kurikulum, materi ajar THE CONTENT CURRICULLUM DEVELOPMENT OF EDUCATION TECHNIC IN HEAVY EQUIPMENT BASED ON INDUSTRIAL NEEDS ABSTRACT This study aims to: (1 find out the formula of competency for heavy equipment mechanic based on industry needs, (2 determine the qualifications of instructors in heavy
The QKD network: model and routing scheme
Yang, Chao; Zhang, Hongqi; Su, Jinhai
2017-11-01
Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.
2016-11-09
Figure 1. We generally express such networks in terms of the services running in each enclave as well as the routing and firewall rules between the...compromise a server, they can compromise other devices in the same subnet or protected enclave. They probe attached firewalls and routers for open ports and...spam and malware filter would prevent this content from reaching its destination. Content filtering provides another layer of defense to other controls
Thermal conductivity model for nanofiber networks
Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui
2018-02-01
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
Thermal conductivity model for nanofiber networks
Energy Technology Data Exchange (ETDEWEB)
Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA
2018-02-28
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
A quantum-implementable neural network model
Chen, Jialin; Wang, Lingli; Charbon, Edoardo
2017-10-01
A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.
Combinatorial explosion in model gene networks
Edwards, R.; Glass, L.
2000-09-01
The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such
Complex networks under dynamic repair model
Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao
2018-01-01
Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
Performance modeling, stochastic networks, and statistical multiplexing
Mazumdar, Ravi R
2013-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan
Network Modeling and Simulation A Practical Perspective
Guizani, Mohsen; Khan, Bilal
2010-01-01
Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strate
Modeling acquaintance networks based on balance theory
Directory of Open Access Journals (Sweden)
Vukašinović Vida
2014-09-01
Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models
Optimal transportation networks models and theory
Bernot, Marc; Morel, Jean-Michel
2009-01-01
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
Flood routing modelling with Artificial Neural Networks
Directory of Open Access Journals (Sweden)
R. Peters
2006-01-01
Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.
Linear approximation model network and its formation via ...
Indian Academy of Sciences (India)
To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...
Modeling Security Aspects of Network
Schoch, Elmar
With more and more widespread usage of computer systems and networks, dependability becomes a paramount requirement. Dependability typically denotes tolerance or protection against all kinds of failures, errors and faults. Sources of failures can basically be accidental, e.g., in case of hardware errors or software bugs, or intentional due to some kind of malicious behavior. These intentional, malicious actions are subject of security. A more complete overview on the relations between dependability and security can be found in [31]. In parallel to the increased use of technology, misuse also has grown significantly, requiring measures to deal with it.
Adaptive Detection and ISI Mitigation for Mobile Molecular Communication.
Chang, Ge; Lin, Lin; Yan, Hao
2018-03-01
Current studies on modulation and detection schemes in molecular communication mainly focus on the scenarios with static transmitters and receivers. However, mobile molecular communication is needed in many envisioned applications, such as target tracking and drug delivery. Until now, investigations about mobile molecular communication have been limited. In this paper, a static transmitter and a mobile bacterium-based receiver performing random walk are considered. In this mobile scenario, the channel impulse response changes due to the dynamic change of the distance between the transmitter and the receiver. Detection schemes based on fixed distance fail in signal detection in such a scenario. Furthermore, the intersymbol interference (ISI) effect becomes more complex due to the dynamic character of the signal which makes the estimation and mitigation of the ISI even more difficult. In this paper, an adaptive ISI mitigation method and two adaptive detection schemes are proposed for this mobile scenario. In the proposed scheme, adaptive ISI mitigation, estimation of dynamic distance, and the corresponding impulse response reconstruction are performed in each symbol interval. Based on the dynamic channel impulse response in each interval, two adaptive detection schemes, concentration-based adaptive threshold detection and peak-time-based adaptive detection, are proposed for signal detection. Simulations demonstrate that the ISI effect is significantly reduced and the adaptive detection schemes are reliable and robust for mobile molecular communication.
Modeling and optimization of an electric power distribution network ...
African Journals Online (AJOL)
Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
An evolving network model with modular growth
International Nuclear Information System (INIS)
Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi
2012-01-01
In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)
Modeling of contact tracing in social networks
Tsimring, Lev S.; Huerta, Ramón
2003-07-01
Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.
A Network Model of Credit Risk Contagion
Directory of Open Access Journals (Sweden)
Ting-Qiang Chen
2012-01-01
Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.
The International Trade Network: weighted network analysis and modelling
International Nuclear Information System (INIS)
Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K
2008-01-01
Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN
Keystone Business Models for Network Security Processors
Arthur Low; Steven Muegge
2013-01-01
Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor...
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Decomposed Implicit Models of Piecewise - Linear Networks
Directory of Open Access Journals (Sweden)
J. Brzobohaty
1992-05-01
Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.
Artificial Immune Networks: Models and Applications
Directory of Open Access Journals (Sweden)
Xian Shen
2008-06-01
Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.
Continuum Modeling of Biological Network Formation
Albi, Giacomo
2017-04-10
We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.
Adaptive-network models of collective dynamics
Zschaler, G.
2012-09-01
Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge
Network Design Models for Container Shipping
DEFF Research Database (Denmark)
Reinhardt, Line Blander; Kallehauge, Brian; Nielsen, Anders Nørrelund
This paper presents a study of the network design problem in container shipping. The paper combines the network design and fleet assignment problem into a mixed integer linear programming model minimizing the overall cost. The major contributions of this paper is that the time of a vessel route...... is included in the calculation of the capacity and that a inhomogeneous fleet is modeled. The model also includes the cost of transshipment which is one of the major cost for the shipping companies. The concept of pseudo simple routes is introduced to expand the set of feasible routes. The linearization...
Characterization and Modeling of Network Traffic
DEFF Research Database (Denmark)
Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur
2011-01-01
-arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...
Phenomenological network models: Lessons for epilepsy surgery.
Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans
2017-10-01
The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.
Student responses to being taught physics in isiZulu
Directory of Open Access Journals (Sweden)
Naven Chetty
2013-09-01
Full Text Available The University of KwaZulu-Natal is in the process of formulating a language policy to introduce teaching and learning in isiZulu as well as in English to improve throughput and increase the number of graduates. The aim of this study was to determine if this policy is feasible within the discipline of physics. Critical engagement with students and a literature search allowed the determination of the potential gains and pitfalls of such a language introduction. The study also provides some useful insight into student contexts, schooling history and their perceptions of being taught in their vernacular. The inconsistent use of isiZulu words to translate basic physics words will require the development of a common vocabulary for teaching physics in isiZulu.
Framework for applying RI-ISI methodology for Indian PHWRs
International Nuclear Information System (INIS)
Vinod, Gopika; Saraf, R.K.; Ghosh, A.K.; Kushwaha, H.S.
2006-01-01
Risk Informed In-Service Inspection (RI-ISI) aims at categorizing the components for In-Service inspection based on their contribution to Risk. For defining the contribution of risk from components, their failure probabilities and its subsequent effect on Core Damage Frequency (CDF) needs to be evaluated using Probabilistic Safety Assessment methodology. During the last several years, both the U.S. Nuclear Regulatory Commission (NRC) and the nuclear industry have recognized that Probabilistic Safety Assessment (PSA) has evolved to be more useful in supplementing traditional engineering approaches in reactor regulation. The paper highlights the various stages involved in applying RI-ISI and then compares the findings with existing ISI practices. (author)
Agent based modeling of energy networks
International Nuclear Information System (INIS)
Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz
2014-01-01
Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed
Delay and Disruption Tolerant Networking MACHETE Model
Segui, John S.; Jennings, Esther H.; Gao, Jay L.
2011-01-01
To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity
A comprehensive Network Security Risk Model for process control networks.
Henry, Matthew H; Haimes, Yacov Y
2009-02-01
The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.
Discrete dynamic modeling of cellular signaling networks.
Albert, Réka; Wang, Rui-Sheng
2009-01-01
Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.
Neural network modeling of associative memory: Beyond the Hopfield model
Dasgupta, Chandan
1992-07-01
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.
Constitutive modelling of composite biopolymer networks.
Fallqvist, B; Kroon, M
2016-04-21
The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modelling students' knowledge organisation: Genealogical conceptual networks
Koponen, Ismo T.; Nousiainen, Maija
2018-04-01
Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks.
Modelling Users` Trust in Online Social Networks
Directory of Open Access Journals (Sweden)
Iacob Cătoiu
2014-02-01
Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.
Bayesian network modelling of upper gastrointestinal bleeding
Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri
2013-09-01
Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.
2016-02-04
of complex systems [1]. Although the ODD protocol was originally intended for individual-based or agent-based models ( ABM ), we adopt this protocol for...applies to information transfer between air-gapped systems . Trust relationships between devices (e.g. a trust relationship created by a domain controller...prevention systems , and data leakage protection systems . 2.2 ATTACKER The model specifies an attacker who gains access to internal enclaves by
Modeling and optimization of potable water network
Energy Technology Data Exchange (ETDEWEB)
Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)
2000-07-01
Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.
Modelling dendritic ecological networks in space: An integrated network perspective
Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger
2013-01-01
Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...
PREDIKSI FOREX MENGGUNAKAN MODEL NEURAL NETWORK
Directory of Open Access Journals (Sweden)
R. Hadapiningradja Kusumodestoni
2015-11-01
Full Text Available ABSTRAK Prediksi adalah salah satu teknik yang paling penting dalam menjalankan bisnis forex. Keputusan dalam memprediksi adalah sangatlah penting, karena dengan prediksi dapat membantu mengetahui nilai forex di waktu tertentu kedepan sehingga dapat mengurangi resiko kerugian. Tujuan dari penelitian ini dimaksudkan memprediksi bisnis fores menggunakan model neural network dengan data time series per 1 menit untuk mengetahui nilai akurasi prediksi sehingga dapat mengurangi resiko dalam menjalankan bisnis forex. Metode penelitian pada penelitian ini meliputi metode pengumpulan data kemudian dilanjutkan ke metode training, learning, testing menggunakan neural network. Setelah di evaluasi hasil penelitian ini menunjukan bahwa penerapan algoritma Neural Network mampu untuk memprediksi forex dengan tingkat akurasi prediksi 0.431 +/- 0.096 sehingga dengan prediksi ini dapat membantu mengurangi resiko dalam menjalankan bisnis forex. Kata kunci: prediksi, forex, neural network.
Artificial neural network cardiopulmonary modeling and diagnosis
Kangas, Lars J.; Keller, Paul E.
1997-01-01
The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.
Green Network Planning Model for Optical Backbones
DEFF Research Database (Denmark)
Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Jensen, Michael
2010-01-01
on the environment in general. In network planning there are existing planning models focused on QoS provisioning, investment minimization or combinations of both and other parameters. But there is a lack of a model for designing green optical backbones. This paper presents novel ideas to be able to define......Communication networks are becoming more essential for our daily lives and critically important for industry and governments. The intense growth in the backbone traffic implies an increment of the power demands of the transmission systems. This power usage might have a significant negative effect...
A Model for Telestrok Network Evaluation
DEFF Research Database (Denmark)
Storm, Anna; Günzel, Franziska; Theiss, Stephan
2011-01-01
analysis lacking, current telestroke reimbursement by third-party payers is limited to special contracts and not included in the regular billing system. Based on a systematic literature review and expert interviews with health care economists, third-party payers and neurologists, a Markov model...... was developed from the third-party payer perspective. In principle, it enables telestroke networks to conduct cost-effectiveness studies, because the majority of the required data can be extracted from health insurance companies’ databases and the telestroke network itself. The model presents a basis...
PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL
Directory of Open Access Journals (Sweden)
S. Munapo
2012-01-01
Full Text Available
ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.
AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.
Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks
Santi, Paolo
2012-01-01
Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and
Allision McDowell-Smith; Anne Speckhard; Ahmet S. Yayla
2017-01-01
ISIS recruits on a 24/7 basis in over 21 languages over the Internet using videos, memes, tweets and other social media postings and swarming in on anyone that retweets, likes or endorses their materials to try to seduce them into the group. Their unprecedented social media drive has resulted in over 30,000 foreign fighters from more than 100 countries migrating to Syria and Iraq. ISIS recruitment in the U.S. is for the most part Internet based and has resulted in the actual and attempted r...
Modeling Renewable Penertration Using a Network Economic Model
Lamont, A.
2001-03-01
This paper evaluates the accuracy of a network economic modeling approach in designing energy systems having renewable and conventional generators. The network approach models the system as a network of processes such as demands, generators, markets, and resources. The model reaches a solution by exchanging prices and quantity information between the nodes of the system. This formulation is very flexible and takes very little time to build and modify models. This paper reports an experiment designing a system with photovoltaic and base and peak fossil generators. The level of PV penetration as a function of its price and the capacities of the fossil generators were determined using the network approach and using an exact, analytic approach. It is found that the two methods agree very closely in terms of the optimal capacities and are nearly identical in terms of annual system costs.
Security Modeling on the Supply Chain Networks
Directory of Open Access Journals (Sweden)
Marn-Ling Shing
2007-10-01
Full Text Available In order to keep the price down, a purchaser sends out the request for quotation to a group of suppliers in a supply chain network. The purchaser will then choose a supplier with the best combination of price and quality. A potential supplier will try to collect the related information about other suppliers so he/she can offer the best bid to the purchaser. Therefore, confidentiality becomes an important consideration for the design of a supply chain network. Chen et al. have proposed the application of the Bell-LaPadula model in the design of a secured supply chain network. In the Bell-LaPadula model, a subject can be in one of different security clearances and an object can be in one of various security classifications. All the possible combinations of (Security Clearance, Classification pair in the Bell-LaPadula model can be thought as different states in the Markov Chain model. This paper extends the work done by Chen et al., provides more details on the Markov Chain model and illustrates how to use it to monitor the security state transition in the supply chain network.
An evolving model of online bipartite networks
Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang
2013-12-01
Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.
An autocatalytic network model for stock markets
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-02-01
The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.
Overall aspects of control of ISIS-type nuclear reactor
International Nuclear Information System (INIS)
Amato, S.; Santinelli, A.
1996-01-01
The paper describes the main aspects related to the definition of main controls required to operate an ISIS-type nuclear power reactors. ISIS is a PWR-type intrinsically safe nuclear reactor designed by ANSALDO, based on density lock concept; it presents, between the other safety functions, self-depressurization and core cooling capability for unlimited time. Due to its specific characteristics, the ISIS reactor required to development of new control philosophy (if compared with actual nuclear power reactor) with the implementation of new control functions, for instance the density locks hot/cold interface locations control. This paper describes the main control functions implemented, their rationale, as well as the dynamic simulation performed to verify the adequacy of controls definitions. The dynamic simulations here described refers to a step-wise power ramp of 100-90-100 (% of nominal power) and to a power ramp of 100-50-100 with a slope of 5%/min; the results obtained have shown the ISIS capability to perform such operational transients, despite its innovative design was mainly focused on intrinsically safe behaviour. (author)
International Scientific Publication in ISI Journals: Chances and Obstacles
Omer, Rawda Ahmed
2015-01-01
Recently, many universities have started to do their best to enhance their contribution in the scientific publication. Thus, researchers and faculty members have been offered many various financial and promotional incentives for publishing their papers in international journals, particularly the ISI ones. The present study aims to identify the…
Keystone Business Models for Network Security Processors
Directory of Open Access Journals (Sweden)
Arthur Low
2013-07-01
Full Text Available Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor” models nor the silicon intellectual-property licensing (“IP-licensing” models allow small technology companies to successfully compete. This article describes an alternative approach that produces an ongoing stream of novel network security processors for niche markets through continuous innovation by both large and small companies. This approach, referred to here as the "business ecosystem model for network security processors", includes a flexible and reconfigurable technology platform, a “keystone” business model for the company that maintains the platform architecture, and an extended ecosystem of companies that both contribute and share in the value created by innovation. New opportunities for business model innovation by participating companies are made possible by the ecosystem model. This ecosystem model builds on: i the lessons learned from the experience of the first author as a senior integrated circuit architect for providers of public-key cryptography solutions and as the owner of a semiconductor startup, and ii the latest scholarly research on technology entrepreneurship, business models, platforms, and business ecosystems. This article will be of interest to all technology entrepreneurs, but it will be of particular interest to owners of small companies that provide security solutions and to specialized security professionals seeking to launch their own companies.
Modeling and Simulation Network Data Standards
2011-09-30
approaches . 2.3. JNAT. JNAT is a Web application that provides connectivity and network analysis capability. JNAT uses propagation models and low-fidelity...COMBATXXI Movement Logger Data Output Dictionary. Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal...B-8 Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal Transverse Mercator (UTM) Heading
The Kuramoto model in complex networks
Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen
2016-01-01
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.
An architectural model for network interconnection
van Sinderen, Marten J.; Vissers, C.A.; Kalin, T.
1983-01-01
This paper presents a technique of successive decomposition of a common users' activity to illustrate the problems of network interconnection. The criteria derived from this approach offer a structuring principle which is used to develop an architectural model that embeds heterogeneous subnetworks
Computational Modeling of Complex Protein Activity Networks
Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude
2017-01-01
Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a
A Model of Mental State Transition Network
Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo
Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.
UAV Trajectory Modeling Using Neural Networks
Xue, Min
2017-01-01
Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.
Modeling Insurgent Network Structure and Dynamics
Gabbay, Michael; Thirkill-Mackelprang, Ashley
2010-03-01
We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.
Hybrid simulation models of production networks
Kouikoglou, Vassilis S
2001-01-01
This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.
Propagating semantic information in biochemical network models
Directory of Open Access Journals (Sweden)
Schulz Marvin
2012-01-01
Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.
Model Predictive Control of Sewer Networks
DEFF Research Database (Denmark)
Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik
2016-01-01
The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....
Modeling Multistandard Wireless Networks in OPNET
DEFF Research Database (Denmark)
Zakrzewska, Anna; Berger, Michael Stübert; Ruepp, Sarah Renée
2011-01-01
Future wireless communication is emerging towards one heterogeneous platform. In this new environment wireless access will be provided by multiple radio technologies that are cooperating and complementing one another. The paper investigates the possibilities of developing such a multistandard sys...... system using OPNET Modeler. A network model consisting of LTE interworking with WLAN and WiMAX is considered from the radio resource management perspective. In particular, implementing a joint packet scheduler across multiple systems is discussed more in detail....
Modelling dendritic ecological networks in space: anintegrated network perspective
Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.
2013-01-01
Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within
Unified Model for Generation Complex Networks with Utility Preferential Attachment
International Nuclear Information System (INIS)
Wu Jianjun; Gao Ziyou; Sun Huijun
2006-01-01
In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.
Functional model of biological neural networks.
Lo, James Ting-Ho
2010-12-01
A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.
On traffic modelling in GPRS networks
DEFF Research Database (Denmark)
Madsen, Tatiana Kozlova; Schwefel, Hans-Peter; Prasad, Ramjee
2005-01-01
Optimal design and dimensioning of wireless data networks, such as GPRS, requires the knowledge of traffic characteristics of different data services. This paper presents an in-detail analysis of an IP-level traffic measurements taken in an operational GPRS network. The data measurements reported...... here are done at the Gi interface. The aim of this paper is to reveal some key statistics of GPRS data applications and to validate if the existing traffic models can adequately describe traffic volume and inter-arrival time distribution for different services. Additionally, we present a method of user...
A Networks Approach to Modeling Enzymatic Reactions.
Imhof, P
2016-01-01
Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.
A improved Network Security Situation Awareness Model
Directory of Open Access Journals (Sweden)
Li Fangwei
2015-08-01
Full Text Available In order to reflect the situation of network security assessment performance fully and accurately, a new network security situation awareness model based on information fusion was proposed. Network security situation is the result of fusion three aspects evaluation. In terms of attack, to improve the accuracy of evaluation, a situation assessment method of DDoS attack based on the information of data packet was proposed. In terms of vulnerability, a improved Common Vulnerability Scoring System (CVSS was raised and maked the assessment more comprehensive. In terms of node weights, the method of calculating the combined weights and optimizing the result by Sequence Quadratic Program (SQP algorithm which reduced the uncertainty of fusion was raised. To verify the validity and necessity of the method, a testing platform was built and used to test through evaluating 2000 DAPRA data sets. Experiments show that the method can improve the accuracy of evaluation results.
Spatial Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...
Fractional virus epidemic model on financial networks
Directory of Open Access Journals (Sweden)
Balci Mehmet Ali
2016-01-01
Full Text Available In this study, we present an epidemic model that characterizes the behavior of a financial network of globally operating stock markets. Since the long time series have a global memory effect, we represent our model by using the fractional calculus. This model operates on a network, where vertices are the stock markets and edges are constructed by the correlation distances. Thereafter, we find an analytical solution to commensurate system and use the well-known differential transform method to obtain the solution of incommensurate system of fractional differential equations. Our findings are confirmed and complemented by the data set of the relevant stock markets between 2006 and 2016. Rather than the hypothetical values, we use the Hurst Exponent of each time series to approximate the fraction size and graph theoretical concepts to obtain the variables.
Entanglement effects in model polymer networks
Everaers, R.; Kremer, K.
The influence of topological constraints on the local dynamics in cross-linked polymer melts and their contribution to the elastic properties of rubber elastic systems are a long standing problem in statistical mechanics. Polymer networks with diamond lattice connectivity (Everaers and Kremer 1995, Everaers and Kremer 1996a) are idealized model systems which isolate the effect of topology conservation from other sources of quenched disorder. We study their behavior in molecular dynamics simulations under elongational strain. In our analysis we compare the measured, purely entropic shear moduli G to the predictions of statistical mechanical models of rubber elasticity, making extensive use of the microscopic structural and topological information available in computer simulations. We find (Everaers and Kremer 1995) that the classical models of rubber elasticity underestimate the true change in entropy in a deformed network significantly, because they neglect the tension along the contour of the strands which cannot relax due to entanglements (Everaers and Kremer (in preparation)). This contribution and the fluctuations in strained systems seem to be well described by the constrained mode model (Everaers 1998) which allows to treat the crossover from classical rubber elasticity to the tube model for polymer networks with increasing strand length within one transparant formalism. While this is important for the description of the effects we try to do a first quantitative step towards their explanation by topological considerations. We show (Everaers and Kremer 1996a) that for the comparatively short strand lengths of our diamond networks the topology contribution to the shear modulus is proportional to the density of entangled mesh pairs with non-zero Gauss linking number. Moreover, the prefactor can be estimated consistently within a rather simple model developed by Vologodskii et al. and by Graessley and Pearson, which is based on the definition of an entropic
DEFF Research Database (Denmark)
Sindbæk, Søren Michael
2015-01-01
preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
IsiZulu as a vehicle towards teaching and conducting research in ...
African Journals Online (AJOL)
Results indicate that lecturers use isiZulu successfully for purposes of research and teaching, but there are some challenges which need to be considered. These challenges include isiZulu as language of instruction in some study programmes, and reporting research outputs through the use of an African language, isiZulu.
Intersections of two isiZulu genderlects and the construction of ...
African Journals Online (AJOL)
Kate H
The isiNgqumo lexicon is characterised largely by what Zulu speakers ... isiNgqumo offers a sense of community and an opportunity to escape public .... isiNgqumo use seems more prevalent in lower socioeconomic “gay” circles and semi-.
Artificial Neural Network Model for Predicting Compressive
Directory of Open Access Journals (Sweden)
Salim T. Yousif
2013-05-01
Full Text Available Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature. The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor affecting the output of the model. The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.
UAV Trajectory Modeling Using Neural Networks
Xue, Min
2017-01-01
Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural
Mapping and modeling of physician collaboration network.
Uddin, Shahadat; Hamra, Jafar; Hossain, Liaquat
2013-09-10
Effective provisioning of healthcare services during patient hospitalization requires collaboration involving a set of interdependent complex tasks, which needs to be carried out in a synergistic manner. Improved patients' outcome during and after hospitalization has been attributed to how effective different health services provisioning groups carry out their tasks in a coordinated manner. Previous studies have documented the underlying relationships between collaboration among physicians on the effective outcome in delivering health services for improved patient outcomes. However, there are very few systematic empirical studies with a focus on the effect of collaboration networks among healthcare professionals and patients' medical condition. On the basis of the fact that collaboration evolves among physicians when they visit a common hospitalized patient, in this study, we first propose an approach to map collaboration network among physicians from their visiting information to patients. We termed this network as physician collaboration network (PCN). Then, we use exponential random graph (ERG) models to explore the microlevel network structures of PCNs and their impact on hospitalization cost and hospital readmission rate. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks such as PCN. It simplifies a complex structure down to a combination of basic parameters such as 2-star, 3-star, and triangle. By applying our proposed mapping approach and ERG modeling technique to the electronic health insurance claims dataset of a very large Australian health insurance organization, we construct and model PCNs. We notice that the 2-star (subset of 3 nodes in which 1 node is connected to each of the other 2 nodes) parameter of ERG has significant impact on hospitalization cost. Further, we identify that triangle (subset of 3 nodes in which each node is connected to
Modeling In-Network Aggregation in VANETs
Dietzel, Stefan; Kargl, Frank; Heijenk, Geert; Schaub, Florian
2011-01-01
The multitude of applications envisioned for vehicular ad hoc networks requires efficient communication and dissemination mechanisms to prevent network congestion. In-network data aggregation promises to reduce bandwidth requirements and enable scalability in large vehicular networks. However, most
Different Epidemic Models on Complex Networks
International Nuclear Information System (INIS)
Zhang Haifeng; Small, Michael; Fu Xinchu
2009-01-01
Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals' relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each case. Finally, we present numerical simulations for each case to verify our results.
Centralized Bayesian reliability modelling with sensor networks
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
2013-01-01
Roč. 19, č. 5 (2013), s. 471-482 ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant - others:GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf
Modelling Pollutant Dispersion in a Street Network
Salem, N. Ben; Garbero, V.; Salizzoni, P.; Lamaison, G.; Soulhac, L.
2015-04-01
This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.
The Channel Network model and field applications
International Nuclear Information System (INIS)
Khademi, B.; Moreno, L.; Neretnieks, I.
1999-01-01
The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed
Advances in dynamic network modeling in complex transportation systems
Ukkusuri, Satish V
2013-01-01
This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang
2006-01-01
The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used by such ada......The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...
VESUVIO--the double difference inverse geometry spectrometer at ISIS
International Nuclear Information System (INIS)
Mayers, J.; Tomkinson, J.; Abdul-Redah, T.; Stirling, W.G.; Andreani, C.; Senesi, R.; Nardone, M.; Colognesi, D.; Degiorgi, E.
2004-01-01
The VESUVIO spectrometer at the ISIS pulsed neutron source performs inelastic neutron scattering at high-energy and wave vector transfers, employing gold and uranium resonant foils. A factor of two improvement in the instrumental resolution has been achieved by making use of the double filter difference method. Experimental results are presented for measurements on polycrystalline Pb, which indicate that accurate measurements of single-particle momentum distribution n(p) in quantum fluids are now possible at eV energy transfers
VESUVIO--the double difference inverse geometry spectrometer at ISIS
Energy Technology Data Exchange (ETDEWEB)
Mayers, J.; Tomkinson, J.; Abdul-Redah, T.; Stirling, W.G.; Andreani, C.; Senesi, R.; Nardone, M.; Colognesi, D.; Degiorgi, E
2004-07-15
The VESUVIO spectrometer at the ISIS pulsed neutron source performs inelastic neutron scattering at high-energy and wave vector transfers, employing gold and uranium resonant foils. A factor of two improvement in the instrumental resolution has been achieved by making use of the double filter difference method. Experimental results are presented for measurements on polycrystalline Pb, which indicate that accurate measurements of single-particle momentum distribution n(p) in quantum fluids are now possible at eV energy transfers.
VESUVIO-the double difference inverse geometry spectrometer at ISIS
Mayers, J.; Tomkinson, J.; Abdul-Redah, T.; Stirling, W. G.; Andreani, C.; Senesi, R.; Nardone, M.; Colognesi, D.; Degiorgi, E.
2004-07-01
The VESUVIO spectrometer at the ISIS pulsed neutron source performs inelastic neutron scattering at high-energy and wave vector transfers, employing gold and uranium resonant foils. A factor of two improvement in the instrumental resolution has been achieved by making use of the double filter difference method. Experimental results are presented for measurements on polycrystalline Pb, which indicate that accurate measurements of single-particle momentum distribution n(p) in quantum fluids are now possible at eV energy transfers.
Development of the pulsed muon facility at ISIS
International Nuclear Information System (INIS)
Eaton, G.H.; Scott, C.A.; Williams, W.G.
1994-01-01
The ISIS pulsed surface muon facility at RAL is presently undergoing a major expansion to provide three experimental ports with simultaneous single muon pulses at 50 Hz. This upgrade, funded by the European Community (EC), is described together with recent development results which are relevant to its future scientific programme. These new beam lines are expected to be available for experiments in June 1993. (orig.)
Applications of the ISI (Information Sciences Institute) Grapher
1988-06-01
pictorially and manipulated using the !S Grapher. SFruits and Vegetabks 2 =J "K avocado bananas] date s , cherries ’egln S S g..1 :-:.hot potatoes Figure 7...called statecharts and higraphs, was implemented in a commercial system called Statement1 and is currently being marketed by Ad Cad, Inc [Ad Cad...undertaking to market the resulting product. It is due to their energy and efforts that the ISI Grapher is now commercially available to the public, the
Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher
2005-01-01
This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.
A network model for Ebola spreading.
Rizzo, Alessandro; Pedalino, Biagio; Porfiri, Maurizio
2016-04-07
The availability of accurate models for the spreading of infectious diseases has opened a new era in management and containment of epidemics. Models are extensively used to plan for and execute vaccination campaigns, to evaluate the risk of international spreadings and the feasibility of travel bans, and to inform prophylaxis campaigns. Even when no specific therapeutical protocol is available, as for the Ebola Virus Disease (EVD), models of epidemic spreading can provide useful insight to steer interventions in the field and to forecast the trend of the epidemic. Here, we propose a novel mathematical model to describe EVD spreading based on activity driven networks (ADNs). Our approach overcomes the simplifying assumption of homogeneous mixing, which is central to most of the mathematically tractable models of EVD spreading. In our ADN-based model, each individual is not bound to contact every other, and its network of contacts varies in time as a function of an activity potential. Our model contemplates the possibility of non-ideal and time-varying intervention policies, which are critical to accurately describe EVD spreading in afflicted countries. The model is calibrated from field data of the 2014 April-to-December spreading in Liberia. We use the model as a predictive tool, to emulate the dynamics of EVD in Liberia and offer a one-year projection, until December 2015. Our predictions agree with the current vision expressed by professionals in the field, who consider EVD in Liberia at its final stage. The model is also used to perform a what-if analysis to assess the efficacy of timely intervention policies. In particular, we show that an earlier application of the same intervention policy would have greatly reduced the number of EVD cases, the duration of the outbreak, and the infrastructures needed for the implementation of the intervention. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling Network Transition Constraints with Hypergraphs
DEFF Research Database (Denmark)
Harrod, Steven
2011-01-01
Discrete time dynamic graphs are frequently used to model multicommodity flows or activity paths through constrained resources, but simple graphs fail to capture the interaction effects of resource transitions. The resulting schedules are not operationally feasible, and return inflated objective...... values. A directed hypergraph formulation is derived to address railway network sequencing constraints, and an experimental problem sample solved to estimate the magnitude of objective inflation when interaction effects are ignored. The model is used to demonstrate the value of advance scheduling...... of train paths on a busy North American railway....
Mathematical model for spreading dynamics of social network worms
International Nuclear Information System (INIS)
Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin
2012-01-01
In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks
Model parameter updating using Bayesian networks
International Nuclear Information System (INIS)
Treml, C.A.; Ross, Timothy J.
2004-01-01
This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
Complex networks-based energy-efficient evolution model for wireless sensor networks
Energy Technology Data Exchange (ETDEWEB)
Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)
2009-08-30
Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Complex networks-based energy-efficient evolution model for wireless sensor networks
International Nuclear Information System (INIS)
Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun
2009-01-01
Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Modeling online social networks based on preferential linking
International Nuclear Information System (INIS)
Hu Hai-Bo; Chen Jun; Guo Jin-Li
2012-01-01
We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks
Modeling the Effect of Bandwidth Allocation on Network Performance
African Journals Online (AJOL)
... The proposed model showed improved performance for CDMA networks, but further increase in the bandwidth did not benefit the network; (iii) A reliability measure such as the spectral efficiency is therefore useful to redeem the limitation in (ii). Keywords: Coverage Capacity, CDMA, Mobile Network, Network Throughput ...
Aeronautical telecommunications network advances, challenges, and modeling
Musa, Sarhan M
2015-01-01
Addresses the Challenges of Modern-Day Air Traffic Air traffic control (ATC) directs aircraft in the sky and on the ground to safety, while the Aeronautical Telecommunications Network (ATN) comprises all systems and phases that assist in aircraft departure and landing. The Aeronautical Telecommunications Network: Advances, Challenges, and Modeling focuses on the development of ATN and examines the role of the various systems that link aircraft with the ground. The book places special emphasis on ATC-introducing the modern ATC system from the perspective of the user and the developer-and provides a thorough understanding of the operating mechanism of the ATC system. It discusses the evolution of ATC, explaining its structure and how it works; includes design examples; and describes all subsystems of the ATC system. In addition, the book covers relevant tools, techniques, protocols, and architectures in ATN, including MIPv6, air traffic control (ATC), security of air traffic management (ATM), very-high-frequenc...
Modelling dependable systems using hybrid Bayesian networks
International Nuclear Information System (INIS)
Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter
2008-01-01
A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems
Logic integer programming models for signaling networks.
Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert
2009-05-01
We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.
Bayesian Recurrent Neural Network for Language Modeling.
Chien, Jen-Tzung; Ku, Yuan-Chu
2016-02-01
A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.
Research on network information security model and system construction
Wang Haijun
2016-01-01
It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the...
A Complex Network Approach to Distributional Semantic Models.
Directory of Open Access Journals (Sweden)
Akira Utsumi
Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.
Two stage neural network modelling for robust model predictive control.
Patan, Krzysztof
2018-01-01
The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Exact model reduction of combinatorial reaction networks
Directory of Open Access Journals (Sweden)
Fey Dirk
2008-08-01
Full Text Available Abstract Background Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models. Results We introduce methods that extend and complete the already introduced approach. For instance, we provide techniques to handle the formation of multi-scaffold complexes as well as receptor dimerization. Furthermore, we discuss a new modeling approach that allows the direct generation of exactly reduced model structures. The developed methods are used to reduce a model of EGF and insulin receptor crosstalk comprising 5,182 ordinary differential equations (ODEs to a model with 87 ODEs. Conclusion The methods, presented in this contribution, significantly enhance the available methods to exactly reduce models of combinatorial reaction networks.
Neural Networks For Electrohydrodynamic Effect Modelling
Directory of Open Access Journals (Sweden)
Wiesław Wajs
2004-01-01
Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.
Social network models predict movement and connectivity in ecological landscapes
Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.
2011-01-01
Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.
Social network models predict movement and connectivity in ecological landscapes.
Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M
2011-11-29
Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.
Neural network models of categorical perception.
Damper, R I; Harnad, S R
2000-05-01
Studies of the categorical perception (CP) of sensory continua have a long and rich history in psychophysics. In 1977, Macmillan, Kaplan, and Creelman introduced the use of signal detection theory to CP studies. Anderson and colleagues simultaneously proposed the first neural model for CP, yet this line of research has been less well explored. In this paper, we assess the ability of neural-network models of CP to predict the psychophysical performance of real observers with speech sounds and artificial/novel stimuli. We show that a variety of neural mechanisms are capable of generating the characteristics of CP. Hence, CP may not be a special model of perception but an emergent property of any sufficiently powerful general learning system.
Combination of Bayesian Network and Overlay Model in User Modeling
Directory of Open Access Journals (Sweden)
Loc Nguyen
2009-12-01
Full Text Available The core of adaptive system is user model containing personal information such as knowledge, learning styles, goals… which is requisite for learning personalized process. There are many modeling approaches, for example: stereotype, overlay, plan recognition… but they don’t bring out the solid method for reasoning from user model. This paper introduces the statistical method that combines Bayesian network and overlay modeling so that it is able to infer user’s knowledge from evidences collected during user’s learning process.
Networks model of the East Turkistan terrorism
Li, Ben-xian; Zhu, Jun-fang; Wang, Shun-guo
2015-02-01
The presence of the East Turkistan terrorist network in China can be traced back to the rebellions on the BAREN region in Xinjiang in April 1990. This article intends to research the East Turkistan networks in China and offer a panoramic view. The events, terrorists and their relationship are described using matrices. Then social network analysis is adopted to reveal the network type and the network structure characteristics. We also find the crucial terrorist leader. Ultimately, some results show that the East Turkistan network has big hub nodes and small shortest path, and that the network follows a pattern of small world network with hierarchical structure.
Pruning Boltzmann networks and hidden Markov models
DEFF Research Database (Denmark)
Pedersen, Morten With; Stork, D.
1996-01-01
We present sensitivity-based pruning algorithms for general Boltzmann networks. Central to our methods is the efficient calculation of a second-order approximation to the true weight saliencies in a cross-entropy error. Building upon previous work which shows a formal correspondence between linear...... Boltzmann chains and hidden Markov models (HMMs), we argue that our method can be applied to HMMs as well. We illustrate pruning on Boltzmann zippers, which are equivalent to two HMMs with cross-connection links. We verify that our second-order approximation preserves the rank ordering of weight saliencies...
Compartmentalization analysis using discrete fracture network models
Energy Technology Data Exchange (ETDEWEB)
La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)
1997-08-01
This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.
Analysis and Comparison of Typical Models within Distribution Network Design
DEFF Research Database (Denmark)
Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.
This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....
Fundamentals of complex networks models, structures and dynamics
Chen, Guanrong; Li, Xiang
2014-01-01
Complex networks such as the Internet, WWW, transportationnetworks, power grids, biological neural networks, and scientificcooperation networks of all kinds provide challenges for futuretechnological development. In particular, advanced societies havebecome dependent on large infrastructural networks to an extentbeyond our capability to plan (modeling) and to operate (control).The recent spate of collapses in power grids and ongoing virusattacks on the Internet illustrate the need for knowledge aboutmodeling, analysis of behaviors, optimized planning and performancecontrol in such networks. F
A Search Model with a Quasi-Network
DEFF Research Database (Denmark)
Ejarque, Joao Miguel
This paper adds a quasi-network to a search model of the labor market. Fitting the model to an average unemployment rate and to other moments in the data implies the presence of the network is not noticeable in the basic properties of the unemployment and job finding rates. However, the network...
Joint Modelling of Structural and Functional Brain Networks
DEFF Research Database (Denmark)
Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten
-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...
Artificial Neural Network Modeling of an Inverse Fluidized Bed ...
African Journals Online (AJOL)
A Radial Basis Function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. In the proposed model, the trained neural network represents the kinetics of biological decomposition of pollutants in the reactor. The neural network has been trained with experimental data ...
Degree distribution of a new model for evolving networks
Indian Academy of Sciences (India)
on intuitive but realistic consideration that nodes are added to the network with both preferential and random attachments. The degree distribution of the model is between a power-law and an exponential decay. Motivated by the features of network evolution, we introduce a new model of evolving networks, incorporating the ...
Neural Network Based Models for Fusion Applications
Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff
2017-10-01
Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-Ânetwork (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.
Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.
2018-04-01
The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.
QSAR modelling using combined simple competitive learning networks and RBF neural networks.
Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E
2018-04-01
The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.
Linear approximation model network and its formation via ...
Indian Academy of Sciences (India)
niques, an alternative `linear approximation model' (LAM) network approach is .... network is LPV, existing LTI theory is difficult to apply (Kailath 1980). ..... Beck J V, Arnold K J 1977 Parameter estimation in engineering and science (New York: ...
Equity venture capital platform model based on complex network
Guo, Dongwei; Zhang, Lanshu; Liu, Miao
2018-05-01
This paper uses the small-world network and the random-network to simulate the relationship among the investors, construct the network model of the equity venture capital platform to explore the impact of the fraud rate and the bankruptcy rate on the robustness of the network model while observing the impact of the average path length and the average agglomeration coefficient of the investor relationship network on the income of the network model. The study found that the fraud rate and bankruptcy rate exceeded a certain threshold will lead to network collapse; The bankruptcy rate has a great influence on the income of the platform; The risk premium exists, and the average return is better under a certain range of bankruptcy risk; The structure of the investor relationship network has no effect on the income of the investment model.
Frank, Laurence Emmanuelle
2006-01-01
Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor
Related work on reference modeling for collaborative networks
Afsarmanesh, H.; Camarinha-Matos, L.M.; Camarinha-Matos, L.M.; Afsarmanesh, H.
2008-01-01
Several international research and development initiatives have led to development of models for organizations and organization interactions. These models and their approaches constitute a background for development of reference models for collaborative networks. A brief survey of work on modeling
A random spatial network model based on elementary postulates
Karlinger, Michael R.; Troutman, Brent M.
1989-01-01
A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
PageRank model of opinion formation on Ulam networks
Chakhmakhchyan, L.; Shepelyansky, D.
2013-12-01
We consider a PageRank model of opinion formation on Ulam networks, generated by the intermittency map and the typical Chirikov map. The Ulam networks generated by these maps have certain similarities with such scale-free networks as the World Wide Web (WWW), showing an algebraic decay of the PageRank probability. We find that the opinion formation process on Ulam networks has certain similarities but also distinct features comparing to the WWW. We attribute these distinctions to internal differences in network structure of the Ulam and WWW networks. We also analyze the process of opinion formation in the frame of generalized Sznajd model which protects opinion of small communities.
An Improved Car-Following Model in Vehicle Networking Based on Network Control
Directory of Open Access Journals (Sweden)
D. Y. Kong
2014-01-01
Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.
Modeling management of research and education networks
Galagan, D.V.
2004-01-01
Computer networks and their services have become an essential part of research and education. Nowadays every modern R&E institution must have a computer network and provide network services to its students and staff. In addition to its internal computer network, every R&E institution must have a
Marketing communications model for innovation networks
Directory of Open Access Journals (Sweden)
Tiago João Freitas Correia
2015-10-01
Full Text Available Innovation is an increasingly relevant concept for the success of any organization, but it also represents a set of internal and external considerations, barriers and challenges to overcome. Along the concept of innovation, new paradigms emerge such as open innovation and co-creation that are simultaneously innovation modifiers and intensifiers in organizations, promoting organizational openness and stakeholder integration within the value creation process. Innovation networks composed by a multiplicity of agents in co-creative work perform as innovation mechanisms to face the increasingly complexity of products, services and markets. Technology, especially the Internet, is an enabler of all process among organizations supported by co-creative platforms for innovation. The definition of marketing communication strategies that promote motivation and involvement of all stakeholders in synergic creation and external promotion is the central aspect of this research. The implementation of the projects is performed by participative workshops with stakeholders from Madan Parque through IDEAS(REVOLUTION methodology and the operational model LinkUp parameterized for the project. The project is divided into the first part, the theoretical framework, and the second part where a model is developed for the marketing communication strategies that appeal to the Madan Parque case study. Keywords: Marketing Communication; Open Innovation, Technology; Innovation Networks; Incubator; Co-Creation.
A graph model for opportunistic network coding
Sorour, Sameh
2015-08-12
© 2015 IEEE. Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.
Efficient Bayesian network modeling of systems
International Nuclear Information System (INIS)
Bensi, Michelle; Kiureghian, Armen Der; Straub, Daniel
2013-01-01
The Bayesian network (BN) is a convenient tool for probabilistic modeling of system performance, particularly when it is of interest to update the reliability of the system or its components in light of observed information. In this paper, BN structures for modeling the performance of systems that are defined in terms of their minimum link or cut sets are investigated. Standard BN structures that define the system node as a child of its constituent components or its minimum link/cut sets lead to converging structures, which are computationally disadvantageous and could severely hamper application of the BN to real systems. A systematic approach to defining an alternative formulation is developed that creates chain-like BN structures that are orders of magnitude more efficient, particularly in terms of computational memory demand. The formulation uses an integer optimization algorithm to identify the most efficient BN structure. Example applications demonstrate the proposed methodology and quantify the gained computational advantage
Modeling stochasticity in biochemical reaction networks
International Nuclear Information System (INIS)
Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N
2016-01-01
Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)
SUSTAIN: a network model of category learning.
Love, Bradley C; Medin, Douglas L; Gureckis, Todd M
2004-04-01
SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.
First results from the MAPS spectrometer at ISIS
International Nuclear Information System (INIS)
Frost, C.D.; Perring, T.G.
2001-01-01
The scientific commissioning of MAPS, the new state-of-the-art neutron scattering instrument at ISIS, has just begun. The design of MAPS has been optimised for studies of coherent excitations in single-crystals. The principal innovation is the use of position sensitive detectors that provide close to continuos coverage over a large solid angle detector array in the forward direction. The technical description of the spectrometer is presented, and examples from the first scientific experiments are used to illustrate how the position sensitive detectors coupled with easy-to-use visualisation software is already beginning to have an impact in the measurement of excitations in single crystals. (author)
Java Image I/O for VICAR, PDS, and ISIS
Deen, Robert G.; Levoe, Steven R.
2011-01-01
This library, written in Java, supports input and output of images and metadata (labels) in the VICAR, PDS image, and ISIS-2 and ISIS-3 file formats. Three levels of access exist. The first level comprises the low-level, direct access to the file. This allows an application to read and write specific image tiles, lines, or pixels and to manipulate the label data directly. This layer is analogous to the C-language "VICAR Run-Time Library" (RTL), which is the image I/O library for the (C/C++/Fortran) VICAR image processing system from JPL MIPL (Multimission Image Processing Lab). This low-level library can also be used to read and write labeled, uncompressed images stored in formats similar to VICAR, such as ISIS-2 and -3, and a subset of PDS (image format). The second level of access involves two codecs based on Java Advanced Imaging (JAI) to provide access to VICAR and PDS images in a file-format-independent manner. JAI is supplied by Sun Microsystems as an extension to desktop Java, and has a number of codecs for formats such as GIF, TIFF, JPEG, etc. Although Sun has deprecated the codec mechanism (replaced by IIO), it is still used in many places. The VICAR and PDS codecs allow any program written using the JAI codec spec to use VICAR or PDS images automatically, with no specific knowledge of the VICAR or PDS formats. Support for metadata (labels) is included, but is format-dependent. The PDS codec, when processing PDS images with an embedded VIAR label ("dual-labeled images," such as used for MER), presents the VICAR label in a new way that is compatible with the VICAR codec. The third level of access involves VICAR, PDS, and ISIS Image I/O plugins. The Java core includes an "Image I/O" (IIO) package that is similar in concept to the JAI codec, but is newer and more capable. Applications written to the IIO specification can use any image format for which a plug-in exists, with no specific knowledge of the format itself.
An Exegetical Note on Plutarch, Isis and Osiris 351E
Directory of Open Access Journals (Sweden)
Geert Roskam
2015-06-01
Full Text Available In this article, I deal with a short but complex sentence at the end of the first chapter of Plutarch’s Isis and Osiris. Plutarch there says that «the happiness of even the eternal life, which God has obtained as his portion, consists in the fact that the things that come to be do not, through knowledge, fail in advance» (351E. This obscure phrase implies, so I argue, that Plutarch’s providential God has a knowledge of particular contingencies and that this knowledge indeed contributes to his eternal blessedness without affecting His essence.
Localized 31PNMR spectroscopy with ISIS and surface coils
International Nuclear Information System (INIS)
Heindel, W.; Schreier, G.; Steinbrich, W.; Glathe, S.; Huttmann, P.
1990-01-01
A new method for image-guided localized phosphorus NMR spectroscopy of superficial tissues has been investigated using a 1.5 Tesla whole-body-MR-system. We used a surface coil combined with adiabatic excitation pulses and a modified ISIS sequence. This approach is related to imaging sequences and thus permits a flexible and accurate determination of the volume of interest from 'conventional' proton images. The scope and advantages of the method are demonstrated by phantom studies. Clinical applications to the liver, renal transplants, and the mediastinum are described. (orig.) [de
First results from the MAPS spectrometer at ISIS
Energy Technology Data Exchange (ETDEWEB)
Frost, C.D.; Perring, T.G. [ISIS Facility, CLRC Rutherford Appleton Laboratory, Didcot, Oxon (United Kingdom)
2001-03-01
The scientific commissioning of MAPS, the new state-of-the-art neutron scattering instrument at ISIS, has just begun. The design of MAPS has been optimised for studies of coherent excitations in single-crystals. The principal innovation is the use of position sensitive detectors that provide close to continuos coverage over a large solid angle detector array in the forward direction. The technical description of the spectrometer is presented, and examples from the first scientific experiments are used to illustrate how the position sensitive detectors coupled with easy-to-use visualisation software is already beginning to have an impact in the measurement of excitations in single crystals. (author)
Multiplicative Attribute Graph Model of Real-World Networks
Energy Technology Data Exchange (ETDEWEB)
Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)
2010-10-20
Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.
Multilevel method for modeling large-scale networks.
Energy Technology Data Exchange (ETDEWEB)
Safro, I. M. (Mathematics and Computer Science)
2012-02-24
Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network
Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.
2018-02-01
Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.
Directory of Open Access Journals (Sweden)
Wang Hao
2016-01-01
Full Text Available In current communication network for distribution in Chinese power grid systems, the fiber communication backbone network for distribution and TD-LTE power private wireless backhaul network of power grid are both bearing by the SDH optical transmission network, which also carries the communication network of transformer substation and main electric. As the data traffic of the distribution communication and TD-LTE power private wireless network grow rapidly in recent years, it will have a big impact with the SDH network’s bearing capacity which is mainly used for main electric communication in high security level. This paper presents a fusion networking model which use a multiple-layer PTN network as the unified bearing of the TD-LTE power private wireless backhaul network and fiber communication backbone network for distribution. Network dataflow analysis shows that this model can greatly reduce the capacity pressure of the traditional SDH network as well as ensure the reliability of the transmission of the communication network for distribution and TD-LTE power private wireless network.
Road network safety evaluation using Bayesian hierarchical joint model.
Wang, Jie; Huang, Helai
2016-05-01
Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.
Models as Tools of Analysis of a Network Organisation
Directory of Open Access Journals (Sweden)
Wojciech Pająk
2013-06-01
Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.
Resolving structural variability in network models and the brain.
Directory of Open Access Journals (Sweden)
Florian Klimm
2014-03-01
Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful
Electron cloud observations at the ISIS Proton Synchrotron
Pertica, A.
2013-04-22
The build up of electron clouds inside a particle accelerator vacuum chamber can produce strong transverse and longitudinal beam instabilities which in turn can lead to high levels of beam loss often requiring the accelerator to be run below its design specification. To study the behaviour of electron clouds at the ISIS Proton Synchrotron, a Micro-Channel Plate (MCP) based electron cloud detector has been developed. The detector is based on the Retarding Field Analyser (RFA) design and consists of a retarding grid, which allows energy analysis of the electron signal, and a MCP assembly placed in front of the collector plate. The MCP assembly provides a current gain over the range 300 to 25K, thereby increasing the signal to noise ratio and dynamic range of the measurements. This paper presents the first electron cloud observations at the ISIS Proton Synchrotron. These results are compared against signals from a beam position monitor and a fast beam loss monitor installed at the same location.
ISIS muons for materials and molecular science studies
International Nuclear Information System (INIS)
King, Philip J C; Cottrell, Stephen P; Hillier, Adrian D; Cox, Stephen F J; De Renzi, Roberto
2013-01-01
This paper marks the first 25 years of muon production at ISIS and the creation in that time of a facility dedicated to the use of these elementary particles as unique microscopic probes in condensed matter and molecular science. It introduces the basic techniques of muon spin rotation, relaxation and resonance, collectively known as μSR, that were already in use by specialist groups at other accelerator labs by the mid-1980s. It describes how these techniques have been implemented and made available at ISIS, beginning in 1987, and how they have evolved and improved since then. Ever widening applications embrace magnetism, superconductivity, interstitial diffusion and charge transport, semiconductors and dielectrics, chemical physics and radical chemistry. Over these first 25 years, a fully supported user facility has been established, open to all academic and industrial users. It presently comprises four scheduled instruments, optimized for different types of measurement, together with auxiliary equipment for radiofrequency or microwave spin manipulation and future plans for pump–probe laser excitation. (comment)
The development of PSI, ISI technique for nuclear power plant
International Nuclear Information System (INIS)
Park, Day-Young; Kwak, Kyung-Jin; Chang, Kee-Ok; Hong, Soon-Shin; Lee, Jong-Po; Chung, Tae-Eon
1985-01-01
The analysis and sizing of detect signal is the most essential in PSI/ISI technique. Ultrasonic testing is the most versatile technique, and the knowledge of ultrsonic attenuation of metal component examined by ultrasonic testing is important to evaluate the signal appeared and to size the flaw of the component. Ultrasonic attenuation measurements were made by using the specimens made of AISI 4140 Carbon Steel with different grain size. Yield strength and ultimate tensile strength were also taken. This report also describes about the principle of multifrequency eddy current test method using two or more operating frequencies simultaneously, and about the simple experiment to read and identify precisely the combined signal caused by more test parameters. It was found that ultrasonic attenuation was increased with increasing grain size and ultrasonic frequency, and yield strength and ultimate tensile strength were decreased with increasing grain size. The results are applicable for ultrasonic testing of carbon steel components as reactor vessel or pressured vessel. The complicated eddy current signal outputs caused by more test parameters and undesirables variables can be identified using multifrequency eddy current test method. It is intended to use multifrequency ECT method for ISI and PSI of steam generator tubes from 1985. (Author)
Profile analysis of neutron powder diffraction data at ISIS
International Nuclear Information System (INIS)
David, W.I.F.; Ibberson, R.M.; Matthewman, J.C.
1992-05-01
The aim of this manual is to document the current suite of time-of-flight neutron powder diffraction profile refinement programs available to ISIS users. Aspects of data collation and normalisation specific to the individual diffraction instruments are dealt with elsewhere. It will be assumed the user has produced a suitable data file (.DAT file) containing the profile data consisting of point by point values of the corrected diffraction profile across the pattern. The analysis of neutron powder diffraction data at ISIS by profile refinement utilises a suite of ''in-house'' written and supported programs based on the Cambridge Crystallography Subroutine Library (CCSL). A quick scan through the CCSL manual will give the user a general feel for the procedure to adopt in the use of the library and hence of the profile codes. The instructions documented in this handbook are complementary to those in the more specialist CCSL manual, and consequently go into no great detail regarding technical details of any of the CCSL routines. The programs may be run from each individual user account, for example [USER01], once the appropriate login procedure has been set-up by the instrument scientists. The programs are mostly activated by one line commands and only a basic knowledge of a VAX editor should be required; details can be found in the ''VAX primer'' available from Computer Support. (Author)
Women’s Social Networks and Birth Attendant Decisions: Application of the Network-Episode Model
Edmonds, Joyce K.; Hruschka, Daniel; Bernard, H. Russell; Sibley, Lynn
2011-01-01
This paper examines the association of women's social networks with the use of skilled birth attendants in uncomplicated pregnancy and childbirth in Matlab, Bangladesh. The Network-Episode Model was applied to determine if network structure variables (density / kinship homogeneity / strength of ties) together with network content (endorsement for or against a particular type of birth attendant) explain the type of birth attendant used by women above and beyond the variance explained by women'...
A last updating evolution model for online social networks
Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui
2013-05-01
As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.
Adaptive Networks Theory, Models and Applications
Gross, Thilo
2009-01-01
With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.
A graph model for opportunistic network coding
Sorour, Sameh; Aboutoraby, Neda; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2015-01-01
© 2015 IEEE. Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase
Modeling and control of magnetorheological fluid dampers using neural networks
Wang, D. H.; Liao, W. H.
2005-02-01
Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.
Structural equation models from paths to networks
Westland, J Christopher
2015-01-01
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data. Tables of software, methodologies and fit st...
Network formation under heterogeneous costs: The multiple group model
Kamphorst, J.J.A.; van der Laan, G.
2007-01-01
It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between
Neural networks in economic modelling : An empirical study
Verkooijen, W.J.H.
1996-01-01
This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a
Multiple Social Networks, Data Models and Measures for
DEFF Research Database (Denmark)
Magnani, Matteo; Rossi, Luca
2017-01-01
Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...
Agent Based Modeling on Organizational Dynamics of Terrorist Network
Bo Li; Duoyong Sun; Renqi Zhu; Ze Li
2015-01-01
Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...
Learning Analytics for Networked Learning Models
Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan
2014-01-01
Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…
Network model for fine coal dewatering. Part I. The model
Energy Technology Data Exchange (ETDEWEB)
Qamar, I.; Tierney, J.W.; Chiang, S.H.
1985-08-01
There is a body of well established research in filtration and related subjects, but much of it has been empirical - based on correlations from experimental data. This approach has the disadvantage that it lacks generality, and it is difficult to predict the behavior of new or different systems. A more general method for studying dewatering is needed-one which will include the microscopic characteristics of the filter cake, which, like other porous media, contains a complicated network of interconnected pores through which the fluid must flow. These pores play an important role in dewatering because they give rise to capillary forces when one fluid is displacing another. In this report, we describe a network model which we believe satisfies these requirements. In the main body of this report, the model is described in detail. Background information is given where appropriate, and a brief description is given of the experimental work being done in our laboratories to verify the model. A detailed description of the experimental procedures and results is given in other DOE reports. The computer programs which are needed to solve the model are described in detail in the Appendices and are accompanied by flow charts, sample problems, and sample outputs. Sufficient detail is given in order to use the model programs on other computer systems. 32 refs., 7 figs., 5 tabs.
Directory of Open Access Journals (Sweden)
Lan Liu
2017-01-01
Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when q
Stochastic actor-oriented models for network change
Snijders, T.A.B.
1996-01-01
A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous
Modeling the reemergence of information diffusion in social network
Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong
2018-01-01
Information diffusion in networks is an important research topic in various fields. Existing studies either focus on modeling the process of information diffusion, e.g., independent cascade model and linear threshold model, or investigate information diffusion in networks with certain structural characteristics such as scale-free networks and small world networks. However, there are still several phenomena that have not been captured by existing information diffusion models. One of the prominent phenomena is the reemergence of information diffusion, i.e., a piece of information reemerges after the completion of its initial diffusion process. In this paper, we propose an optimized information diffusion model by introducing a new informed state into traditional susceptible-infected-removed model. We verify the proposed model via simulations in real-world social networks, and the results indicate that the model can reproduce the reemergence of information during the diffusion process.
An Improved Walk Model for Train Movement on Railway Network
International Nuclear Information System (INIS)
Li Keping; Mao Bohua; Gao Ziyou
2009-01-01
In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic. (general)
Infinite Multiple Membership Relational Modeling for Complex Networks
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai
Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...
Stabilization of model-based networked control systems
Energy Technology Data Exchange (ETDEWEB)
Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)
2016-06-08
A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.
Mixture models with entropy regularization for community detection in networks
Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang
2018-04-01
Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.
Conceptual and methodological biases in network models.
Lamm, Ehud
2009-10-01
Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between "program" and "data." The evolutionary significance of the dynamics of trans-generational and interorganism regulatory networks is explored and implications are presented for understanding the evolution of the biological categories development-heredity, plasticity-evolvability, and epigenetic-genetic.
Directory of Open Access Journals (Sweden)
Mohammad Taghi Ameli
2012-01-01
Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.
Switching performance of OBS network model under prefetched real traffic
Huang, Zhenhua; Xu, Du; Lei, Wen
2005-11-01
Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Modeling MAC layer for powerline communications networks
Hrasnica, Halid; Haidine, Abdelfatteh
2001-02-01
The usage of electrical power distribution networks for voice and data transmission, called Powerline Communications, becomes nowadays more and more attractive, particularly in the telecommunication access area. The most important reasons for that are the deregulation of the telecommunication market and a fact that the access networks are still property of former monopolistic companies. In this work, first we analyze a PLC network and system structure as well as a disturbance scenario in powerline networks. After that, we define a logical structure of the powerline MAC layer and propose the reservation MAC protocols for the usage in the PLC network which provides collision free data transmission. This makes possible better network utilization and realization of QoS guarantees which can make PLC networks competitive to other access technologies.
Developing intonation corpora for isiXhosa and isiZulu
CSIR Research Space (South Africa)
Govender, N
2005-11-01
Full Text Available also show how those corpora can be used without further interpretation to gain insight into matters such as overall pitch contours and gender differences, and discuss the additional steps that will be required to create truly generative models from...
Ripple-Spreading Network Model Optimization by Genetic Algorithm
Directory of Open Access Journals (Sweden)
Xiao-Bing Hu
2013-01-01
Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.
Modelling the impact of social network on energy savings
International Nuclear Information System (INIS)
Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.
2016-01-01
Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout
Redesign of the Analysing Magnet in the ISIS H- Penning Ion Source
International Nuclear Information System (INIS)
Lawrie, S. R.; Faircloth, D. C.; Letchford, A. P.; Westall, M.; Whitehead, M. O.; Wood, T.; Pozimski, J.
2009-01-01
A full 3D electromagnetic finite element analysis and particle tracking study is undertaken of the ISIS Penning surface plasma H - ion source. The extraction electrode, 90 deg. analysing magnet, post-extraction acceleration gap and 700 mm of drift space have been modelled in CST Particle Studio 2008 to study the beam acceleration and transport at all points in the system. The analyzing magnet is found to have a sub-optimal field index, causing beam divergence and contributing the beam loss. Different magnet pole piece geometries are modelled and the effects of space charge investigated. The best design for the analysing magnet involves a shallower intersection angle and larger separation of the pole faces. This provides radial focusing to the beam, leading to less collimation. Three new sets of magnet poles are manufactured and tested on the Ion Source Development Rig to compare with predictions.
Hybrid neural network bushing model for vehicle dynamics simulation
International Nuclear Information System (INIS)
Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk
2008-01-01
Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers
Model for the growth of the world airline network
Verma, T.; Araújo, N. A. M.; Nagler, J.; Andrade, J. S.; Herrmann, H. J.
2016-06-01
We propose a probabilistic growth model for transport networks which employs a balance between popularity of nodes and the physical distance between nodes. By comparing the degree of each node in the model network and the World Airline Network (WAN), we observe that the difference between the two is minimized for α≈2. Interestingly, this is the value obtained for the node-node correlation function in the WAN. This suggests that our model explains quite well the growth of airline networks.
ISI system for MONJU primary heat transfer system (PHTS)
International Nuclear Information System (INIS)
Tagawa, Akihiro; Narisawa, Masataka; Ueda, Masashi; Yamashita, Takuya
2007-01-01
This paper describes the development of a new inspection robot for the in-service inspection (ISI) of the heat transfer system of the FBR MONJU. The inspection is carried out using a tire type for volumetric tests at elevated temperature (Atmosphere 55 degree C, Piping Surface 80 degree C) and irradiation dose condition (Dose Rate 10mSv/h, Piping Surface Dose Rate 15mSv/h). The inspection robot which took in a new tire type ultrasonic testing sensor and a new control method was developed. Detection goals that signal to noise ratio by over 2 for 50% thickness defect of wall were attained as a result of the functional test. (author)
Auroral kilometric radiation source region observations from ISIS 1
International Nuclear Information System (INIS)
Benson, R.F.
1981-01-01
The ISIS 1 observations of the high-frequency portion of the auroral kilometric radiation (AKR) spectrum are considered, that is, from the minimum frequency encountered for the extraordinary mode cut-off (approximately 450 kHz) to the upper frequency cut-off (approximately 800 kHz). AKR is found to be generated in the extraordinary mode just above the local cutoff frequency and to emanate in a direction that is nearly perpendicular to the magnetic field. It occurs within local depletions of electron density, where the ratio of plasma frequency to cyclotron frequency is below 0.2. The density depletion is restricted to altitudes above approximately 2,000 km, and the upper AKR frequency limit corresponds to the extraordinary cutoff frequency at this altitude
MERLIN, a new high count rate spectrometer at ISIS
International Nuclear Information System (INIS)
Bewley, R.I.; Eccleston, R.S.; McEwen, K.A.; Hayden, S.M.; Dove, M.T.; Bennington, S.M.; Treadgold, J.R.; Coleman, R.L.S.
2006-01-01
MERLIN is designed to be a high intensity, medium energy resolution spectrometer. As such, it will complement the high-resolution MAPS spectrometer at ISIS. MERLIN will utilise all the latest advances in technology with a supermirror guide to enhance flux as well as 3 m long position-sensitive detectors in a vacuum making it ideal for single-crystal users. The detector bank will cover a massive π steradians of solid angle with an angular range from -45 o to +135 o degrees in the horizontal plane and ±30 o degrees in the vertical plane. This will allow large swathes of Q,ω space to be accessed in a single run. The instrument will be ready for commissioning in February 2006. This paper presents details of design and performance of this new instrument
User guide for the POLARIS powder diffractometer at ISIS
International Nuclear Information System (INIS)
Hull, S.; Mayers, J.
1989-11-01
The POLARIS spectrometer at ISIS is currently being scheduled for use as a high intensity, medium resolution powder diffractometer. The particularly high neutron flux on POLARIS enables experiments to be performed with comparatively short counting times or on small sample volumes. This ability has been exploited during kinetic experiments of phase changes, where diffraction data is collected whilst the furnace is heating up. The provision of a large detector bank at 2 θ ∼ 90 0 is particularly important for studies of powder samples at high pressures. This scattering geometry has significant advantages for experiments of this kind, as suitable collimation of the incident and outgoing beams eliminates scattering from the surrounding pressure transmitting medium. This guide is intended to give a short description of the POLARIS powder diffractometer and to provide the basic information required to perform a powder diffraction experiment. (author)
Modelling the dependability in Network Function Virtualisation
Lin, Wenqi
2017-01-01
Network Function Virtualization has been brought up to allow the TSPs to have more possibilities and flexibilities to provision services with better load optimizing, energy utilizing and dynamic scaling. Network functions will be decoupled from the underlying dedicated hardware into software instances that run on commercial off-the-shelf servers. However, the development is still at an early stage and the dependability concerns raise by the virtualization of the network functions are touched ...
Mode Choice Modeling Using Artificial Neural Networks
Edara, Praveen Kumar
2003-01-01
Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...
Bayesian Networks for Modeling Dredging Decisions
2011-10-01
years, that algorithms have been developed to solve these problems efficiently. Most modern Bayesian network software uses junction tree (a.k.a. join... software was used to develop the network . This is by no means an exhaustive list of Bayesian network applications, but it is representative of recent...characteristic node (SCN), state- defining node ( SDN ), effect node (EFN), or value node. The five types of nodes can be described as follows: ERDC/EL TR-11
A genetic algorithm for solving supply chain network design model
Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.
2013-09-01
Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.
Runoff Modelling in Urban Storm Drainage by Neural Networks
DEFF Research Database (Denmark)
Rasmussen, Michael R.; Brorsen, Michael; Schaarup-Jensen, Kjeld
1995-01-01
A neural network is used to simulate folw and water levels in a sewer system. The calibration of th neural network is based on a few measured events and the network is validated against measureed events as well as flow simulated with the MOUSE model (Lindberg and Joergensen, 1986). The neural...... network is used to compute flow or water level at selected points in the sewer system, and to forecast the flow from a small residential area. The main advantages of the neural network are the build-in self calibration procedure and high speed performance, but the neural network cannot be used to extract...... knowledge of the runoff process. The neural network was found to simulate 150 times faster than e.g. the MOUSE model....
Model of community emergence in weighted social networks
Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.
2009-04-01
Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.
A control model for district heating networks with storage
Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro
2014-01-01
In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and
Travel Time Reliability for Urban Networks : Modelling and Empirics
Zheng, F.; Liu, Xiaobo; van Zuylen, H.J.; Li, Jie; Lu, Chao
2017-01-01
The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data
Deterministic ripple-spreading model for complex networks.
Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel
2011-04-01
This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.
Mathematical modelling of complex contagion on clustered networks
O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James
2015-09-01
The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
Mathematical modelling of complex contagion on clustered networks
Directory of Open Access Journals (Sweden)
David J. P. O'Sullivan
2015-09-01
Full Text Available The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010, adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the complex contagion effects of social reinforcement are important in such diffusion, in contrast to simple contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010, to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
A small-world network model of facial emotion recognition.
Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto
2016-01-01
Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.
A general evolving model for growing bipartite networks
International Nuclear Information System (INIS)
Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin
2012-01-01
In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.
Modeling geomagnetic induced currents in Australian power networks
Marshall, R. A.; Kelly, A.; Van Der Walt, T.; Honecker, A.; Ong, C.; Mikkelsen, D.; Spierings, A.; Ivanovich, G.; Yoshikawa, A.
2017-07-01
Geomagnetic induced currents (GICs) have been considered an issue for high-latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a "geoelectric field" determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29-31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29-31 October 2003 exceed 40 A with the larger GICs occurring in the south-east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east-west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.
Systems and methods for modeling and analyzing networks
Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W
2013-10-29
The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.
The Lemmatization of Loan Words in the isiNdebele–English ...
African Journals Online (AJOL)
user
English Dictionary and the selection of words for lemmatization are ... The IsiNdebele–English Dictionary is a bilingual, bi-directional dictionary, which is divided ... In the above examples, lemmas are in isiNdebele and English and each lemma.
Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant
International Nuclear Information System (INIS)
Park, Un Su; Park, Ik Keun; Um, Byong Guk; Park, Yun Won; Kang, Suk Chul
1998-01-01
For an effective and efficient management of large amounts of preservice/inservice inspection(PSI/ISI) data in nuclear power plants, an intelligent Windows 95-based data management program was developed. This program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. The program extracts, and the associated remedies. Furthermore, additional inspection data and comments can be easily added or deleted for subsequent PSI/ISI operation. Although the initial version of the program was applied to Kori nuclear power plant, this program can be equally applied to other nuclear power plant. And also this program can be used to offer the fundamental data for application of evaluation data related to fracture mechanics analysis(FMA), probabilistic reliability assessment(PRA) of PSI/ISI results, performance demonstration initiative(PDI) and risk-informed ISI based on probability of detection(POD) information of ultrasonic examination. Besides, the program can be further developed as a unique PSI/ISI data management expert system that can be apart of PSI/ISI data management expert system that can be a part of PSI/ISI Total Support System(TSS) for Korean nuclear power plants
Ocean wave prediction using numerical and neural network models
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; Prabaharan, N.
This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...
Dynamic thermo-hydraulic model of district cooling networks
International Nuclear Information System (INIS)
Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd
2016-01-01
Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.
Dynamic Pathloss Model for Future Mobile Communication Networks
DEFF Research Database (Denmark)
Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee
2016-01-01
that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......— Future mobile communication networks (MCNs) are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network...... planning depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...
Dynamic Pathloss Model for Place and Time Itinerant Networks
DEFF Research Database (Denmark)
Kumar, Ambuj; Mihovska, Albena; Prasad, Ramjee
2018-01-01
that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......t Future mobile communication networks are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network planning...... depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...
An information spreading model based on online social networks
Wang, Tao; He, Juanjuan; Wang, Xiaoxia
2018-01-01
Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.
A Mathematical Model to Improve the Performance of Logistics Network
Directory of Open Access Journals (Sweden)
Muhammad Izman Herdiansyah
2012-01-01
Full Text Available The role of logistics nowadays is expanding from just providing transportation and warehousing to offering total integrated logistics. To remain competitive in the global market environment, business enterprises need to improve their logistics operations performance. The improvement will be achieved when we can provide a comprehensive analysis and optimize its network performances. In this paper, a mixed integer linier model for optimizing logistics network performance is developed. It provides a single-product multi-period multi-facilities model, as well as the multi-product concept. The problem is modeled in form of a network flow problem with the main objective to minimize total logistics cost. The problem can be solved using commercial linear programming package like CPLEX or LINDO. Even in small case, the solver in Excel may also be used to solve such model.Keywords: logistics network, integrated model, mathematical programming, network optimization
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.
Efficient Neural Network Modeling for Flight and Space Dynamics Simulation
Directory of Open Access Journals (Sweden)
Ayman Hamdy Kassem
2011-01-01
Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.
Model and simulation of Krause model in dynamic open network
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.
A comprehensive multi-local-world model for complex networks
International Nuclear Information System (INIS)
Fan Zhengping; Chen Guanrong; Zhang Yunong
2009-01-01
The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.
Hydrometeorological network for flood monitoring and modeling
Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris
2013-08-01
Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its
SIMULTANEOUS FITS IN ISIS ON THE EXAMPLE OF GRO J1008–57
Directory of Open Access Journals (Sweden)
M. Kühnel
2015-04-01
Full Text Available Parallel computing and steadily increasing computation speed have led to a new tool for analyzing multiple datasets and datatypes: fitting several datasets simultaneously. With this technique, physically connected parameters of individual data can be treated as a single parameter by implementing this connection directly into the fit. We discuss the terminology, implementation, and possible issues of simultaneous fits based on the Interactive Spectral Interpretation System (ISIS X-ray data analysis tool. While all data modeling tools in X-ray astronomy in principle allow data to be fitted individually from multiple data sets, the syntax used in these tools is not often well suited for this task. Applying simultaneous fits to the transient X-ray binary GRO J1008–57, we find that the spectral shape is only dependent on X-ray flux. We determine time independent parameters e.g., the folding energy Efold, with unprecedented precision.
Simultaneous fits in ISIS on the example of GRO J1008-57
Kühnel, Matthias; Müller, Sebastian; Kreykenbohm, Ingo; Schwarm, Fritz-Walter; Grossberger, Christoph; Dauser, Thomas; Pottschmidt, Katja; Ferrigno, Carlo; Rothschild, Richard E.; Klochkov, Dmitry; Staubert, Rüdiger; Wilms, Joern
2015-04-01
Parallel computing and steadily increasing computation speed have led to a new tool for analyzing multiple datasets and datatypes: fitting several datasets simultaneously. With this technique, physically connected parameters of individual data can be treated as a single parameter by implementing this connection into the fit directly. We discuss the terminology, implementation, and possible issues of simultaneous fits based on the X-ray data analysis tool Interactive Spectral Interpretation System (ISIS). While all data modeling tools in X-ray astronomy allow in principle fitting data from multiple data sets individually, the syntax used in these tools is not often well suited for this task. Applying simultaneous fits to the transient X-ray binary GRO J1008-57, we find that the spectral shape is only dependent on X-ray flux. We determine time independent parameters such as, e.g., the folding energy E_fold, with unprecedented precision.
Hidden long evolutionary memory in a model biochemical network
Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan
2018-04-01
We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.
Linear control theory for gene network modeling.
Shin, Yong-Jun; Bleris, Leonidas
2010-09-16
Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.
Modeling Temporal Evolution and Multiscale Structure in Networks
DEFF Research Database (Denmark)
Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard
2013-01-01
Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...
Growth of cortical neuronal network in vitro: Modeling and analysis
International Nuclear Information System (INIS)
Lai, P.-Y.; Jia, L. C.; Chan, C. K.
2006-01-01
We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed
SPLAI: Computational Finite Element Model for Sensor Networks
Directory of Open Access Journals (Sweden)
Ruzana Ishak
2006-01-01
Full Text Available Wireless sensor network refers to a group of sensors, linked by a wireless medium to perform distributed sensing task. The primary interest is their capability in monitoring the physical environment through the deployment of numerous tiny, intelligent, wireless networked sensor nodes. Our interest consists of a sensor network, which includes a few specialized nodes called processing elements that can perform some limited computational capabilities. In this paper, we propose a model called SPLAI that allows the network to compute a finite element problem where the processing elements are modeled as the nodes in the linear triangular approximation problem. Our model also considers the case of some failures of the sensors. A simulation model to visualize this network has been developed using C++ on the Windows environment.
Modeling the propagation of mobile malware on complex networks
Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue
2016-08-01
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.
Analysis and logical modeling of biological signaling transduction networks
Sun, Zhongyao
The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.
UML modelling of network warfare examples
CSIR Research Space (South Africa)
Veerasamy, N
2011-08-01
Full Text Available ] Affects both civilian and military domains [8] [9] Related to the concepts of infowar, information operations, hacking, hackivism, cyberterrorism and cybotage depending on motivations and techniques [10] Encompasses both technological solutions...]. In addition, Williers as well as Qingbao and Anwar discuss more offensive aspects of information security and Network Warfare like Hacking, Vulnerability Injection, Network Attacks, Denial of Capability, Interception and Blockage [6] [18] [19]. Various...
Neural Network Models for Time Series Forecasts
Tim Hill; Marcus O'Connor; William Remus
1996-01-01
Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...
Stochastic model and method of zoning water networks
Тевяшев, Андрей Дмитриевич; Матвиенко, Ольга Ивановна
2014-01-01
Water consumption at different time of the day is uneven. The model of steady flow distribution in water-supply networks is calculated for maximum consumption and effectively used in the network design and reconstruction. Quasi-stationary modes, in which the parameters are random variables and vary relative to their mean values are more suitable for operational management and planning of rational network operation modes.Leaks, which sometimes exceed 50 % of the volume of water supplied, are o...
A three-dimensional computational model of collagen network mechanics.
Directory of Open Access Journals (Sweden)
Byoungkoo Lee
Full Text Available Extracellular matrix (ECM strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned. We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions.
Hybrid network defense model based on fuzzy evaluation.
Cho, Ying-Chiang; Pan, Jen-Yi
2014-01-01
With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.
A Secure Network Coding-based Data Gathering Model and Its Protocol in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Qian Xiao
2012-09-01
Full Text Available To provide security for data gathering based on network coding in wireless sensor networks (WSNs, a secure network coding-based data gathering model is proposed, and a data-privacy preserving and pollution preventing (DPPaamp;PP protocol using network coding is designed. DPPaamp;PP makes use of a new proposed pollution symbol selection and pollution (PSSP scheme based on a new obfuscation idea to pollute existing symbols. Analyses of DPPaamp;PP show that it not only requires low overhead on computation and communication, but also provides high security on resisting brute-force attacks.
Generalized Tavis-Cummings models and quantum networks
Gorokhov, A. V.
2018-04-01
The properties of quantum networks based on generalized Tavis-Cummings models are theoretically investigated. We have calculated the information transfer success rate from one node to another in a simple model of a quantum network realized with two-level atoms placed in the cavities and interacting with an external laser field and cavity photons. The method of dynamical group of the Hamiltonian and technique of corresponding coherent states were used for investigation of the temporal dynamics of the two nodes model.
Analysis of organizational culture with social network models
Titov, S.
2015-01-01
Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...
Asaad Almohammad
2018-01-01
Research on the engagement of children with the so-called Islamic State (a.k.a. ISIS) relies heavily on the analysis of obtained ISIS documents and ISIS-disseminated propaganda, leaving major elements of the recruitment and deployment process uncovered. Such ambiguities hinder future efforts aimed at dealing with ISIS’ child soldiers. As such, an intensive effort to compile data using interviews and naturalistic observations across ISIS-held territories in Syria was made to exhaustively explo...
Mathematics of epidemics on networks from exact to approximate models
Kiss, István Z; Simon, Péter L
2017-01-01
This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate...
Exponential random graph models for networks with community structure.
Fronczak, Piotr; Fronczak, Agata; Bujok, Maksymilian
2013-09-01
Although the community structure organization is an important characteristic of real-world networks, most of the traditional network models fail to reproduce the feature. Therefore, the models are useless as benchmark graphs for testing community detection algorithms. They are also inadequate to predict various properties of real networks. With this paper we intend to fill the gap. We develop an exponential random graph approach to networks with community structure. To this end we mainly built upon the idea of blockmodels. We consider both the classical blockmodel and its degree-corrected counterpart and study many of their properties analytically. We show that in the degree-corrected blockmodel, node degrees display an interesting scaling property, which is reminiscent of what is observed in real-world fractal networks. A short description of Monte Carlo simulations of the models is also given in the hope of being useful to others working in the field.
Dynamic Evolution Model Based on Social Network Services
Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen
2013-11-01
Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.
Nonlinear adaptive inverse control via the unified model neural network
Jeng, Jin-Tsong; Lee, Tsu-Tian
1999-03-01
In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.
Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.
Energy Technology Data Exchange (ETDEWEB)
Kelic, Andjelka; Campbell, Philip L
2018-04-01
The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.
Constraints and entropy in a model of network evolution
Tee, Philip; Wakeman, Ian; Parisis, George; Dawes, Jonathan; Kiss, István Z.
2017-11-01
Barabási-Albert's "Scale Free" model is the starting point for much of the accepted theory of the evolution of real world communication networks. Careful comparison of the theory with a wide range of real world networks, however, indicates that the model is in some cases, only a rough approximation to the dynamical evolution of real networks. In particular, the exponent γ of the power law distribution of degree is predicted by the model to be exactly 3, whereas in a number of real world networks it has values between 1.2 and 2.9. In addition, the degree distributions of real networks exhibit cut offs at high node degree, which indicates the existence of maximal node degrees for these networks. In this paper we propose a simple extension to the "Scale Free" model, which offers better agreement with the experimental data. This improvement is satisfying, but the model still does not explain why the attachment probabilities should favor high degree nodes, or indeed how constraints arrive in non-physical networks. Using recent advances in the analysis of the entropy of graphs at the node level we propose a first principles derivation for the "Scale Free" and "constraints" model from thermodynamic principles, and demonstrate that both preferential attachment and constraints could arise as a natural consequence of the second law of thermodynamics.
A large deformation viscoelastic model for double-network hydrogels
Mao, Yunwei; Lin, Shaoting; Zhao, Xuanhe; Anand, Lallit
2017-03-01
We present a large deformation viscoelasticity model for recently synthesized double network hydrogels which consist of a covalently-crosslinked polyacrylamide network with long chains, and an ionically-crosslinked alginate network with short chains. Such double-network gels are highly stretchable and at the same time tough, because when stretched the crosslinks in the ionically-crosslinked alginate network rupture which results in distributed internal microdamage which dissipates a substantial amount of energy, while the configurational entropy of the covalently-crosslinked polyacrylamide network allows the gel to return to its original configuration after deformation. In addition to the large hysteresis during loading and unloading, these double network hydrogels also exhibit a substantial rate-sensitive response during loading, but exhibit almost no rate-sensitivity during unloading. These features of large hysteresis and asymmetric rate-sensitivity are quite different from the response of conventional hydrogels. We limit our attention to modeling the complex viscoelastic response of such hydrogels under isothermal conditions. Our model is restricted in the sense that we have limited our attention to conditions under which one might neglect any diffusion of the water in the hydrogel - as might occur when the gel has a uniform initial value of the concentration of water, and the mobility of the water molecules in the gel is low relative to the time scale of the mechanical deformation. We also do not attempt to model the final fracture of such double-network hydrogels.
Constructive Lower Bounds on Model Complexity of Shallow Perceptron Networks
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra
2018-01-01
Roč. 29, č. 7 (2018), s. 305-315 ISSN 0941-0643 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : shallow and deep networks * model complexity and sparsity * signum perceptron networks * finite mappings * variational norms * Hadamard matrices Subject RIV: IN - Informatics, Computer Science Impact factor: 2.505, year: 2016
Line and lattice networks under deterministic interference models
Goseling, Jasper; Gastpar, Michael; Weber, Jos H.
Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of
Radio Channel Modelling for UAV Communication over Cellular Networks
DEFF Research Database (Denmark)
Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard
2017-01-01
The main goal of this paper is to obtain models for path loss exponents and shadowing for the radio channel between airborne Unmanned Aerial Vehicles (UAVs) and cellular networks. In this pursuit, field measurements were conducted in live LTE networks at the 800 MHz frequency band, using a commer...
Modelling aspects of distributed processing in telecommunication networks
Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW
1998-01-01
The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in
Oxygen diffusion in a network model of the myocardial microcirculation
Wieringa, P. A.; Stassen, H. G.; van Kan, J. J.; Spaan, J. A.
1993-01-01
Oxygen supply was studied in a three-dimensional capillary network model of the myocardial microcirculation. Capillary networks were generated using one common strategy to locate the capillary branchings and segments, arterioles and venules. Flow paths developed with different capillary flow
Modelling flow dynamics in water distribution networks using ...
African Journals Online (AJOL)
One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...
Modelling the permeability of polymers: a neural network approach
Wessling, Matthias; Mulder, M.H.V.; Bos, A.; Bos, A.; van der Linden, M.K.T.; Bos, M.; van der Linden, W.E.
1994-01-01
In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships. Here it is used to correlate the IR spectrum of a
Towards a Social Networks Model for Online Learning & Performance
Chung, Kon Shing Kenneth; Paredes, Walter Christian
2015-01-01
In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…
Capacity allocation in wireless communication networks - models and analyses
Litjens, Remco
2003-01-01
This monograph has concentrated on capacity allocation in cellular and Wireless Local Area Networks, primarily with a network operator’s perspective. In the introduc- tory chapter, a reference model has been proposed for the extensive suite of capacity allocation mechanisms that can be applied at
DAILY RAINFALL-RUNOFF MODELLING BY NEURAL NETWORKS ...
African Journals Online (AJOL)
K. Benzineb, M. Remaoun
2016-09-01
Sep 1, 2016 ... The hydrologic behaviour modelling of w. Journal of ... i Ouahrane's basin from rainfall-runoff relation which is non-linea networks ... will allow checking efficiency of formal neural networks for flows simulation in semi-arid zone.
Energy Model of Networks-on-Chip and a Bus
Wolkotte, P.T.; Smit, Gerardus Johannes Maria; Kavaldjiev, N.K.; Becker, Jens E.; Becker, Jürgen; Nurmi, J.; Takala, J.; Hamalainen, T.D.
2005-01-01
A Network-on-Chip (NoC) is an energy-efficient onchip communication architecture for Multi-Processor Systemon-Chip (MPSoC) architectures. In earlier papers we proposed two Network-on-Chip architectures based on packet-switching and circuit-switching. In this paper we derive an energy model for both
modeling and optimization of an electric power distribution network
African Journals Online (AJOL)
user
EDNEPP) was solved by a mixed binary integer programming (MBIP) formulation of the network, where the steady-state operation of the network was modelled with non-linear mathematical expressions. The non-linear terms are linearized, using ...
Agent Based Modeling on Organizational Dynamics of Terrorist Network
Directory of Open Access Journals (Sweden)
Bo Li
2015-01-01
Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.
System-level Modeling of Wireless Integrated Sensor Networks
DEFF Research Database (Denmark)
Virk, Kashif M.; Hansen, Knud; Madsen, Jan
2005-01-01
Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...
A continuous-time control model on production planning network ...
African Journals Online (AJOL)
A continuous-time control model on production planning network. DEA Omorogbe, MIU Okunsebor. Abstract. In this paper, we give a slightly detailed review of Graves and Hollywood model on constant inventory tactical planning model for a job shop. The limitations of this model are pointed out and a continuous time ...
Non-consensus Opinion Models on Complex Networks
Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo
2013-04-01
Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not
Linear control theory for gene network modeling.
Directory of Open Access Journals (Sweden)
Yong-Jun Shin
Full Text Available Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain and linear state-space (time domain can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.
Modelling, synthesis and analysis of biorefinery networks
DEFF Research Database (Denmark)
Bertran, Maria-Ona
for the conversion of biomass into chemicals, fuels and energy, because they have the potential to maximize biomass value while reducing emissions. The design of biorefinery networks is a complex decisionmaking problem that involves the selection of feedstocks, processing technologies, products, geographical...... locations, and operating conditions, among others. Unlike petroleumbased processing networks, biorefineries rely on feedstocks that are nonhomogeneous across geographical areas in terms of their availability, type and properties. For this reason, the performance of biorefinery networks depends...... of reactions to convert available biomassbased feedstocks into desired products, the selection of processing routes and technologies from a large set of alternatives, or the generation of hybrid technologies through process intensification. Systematic process synthesis and design methods have been developed...
Phase-synchronisation in continuous flow models of production networks
Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael
2006-04-01
To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.
Hybrid modeling and empirical analysis of automobile supply chain network
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
Graphite analyser upgrade for the IRIS spectrometer at ISIS
International Nuclear Information System (INIS)
Campbell, S.I.; Telling, M.T.F.; Carlile, C.J.
1999-01-01
Complete text of publication follows. The pyrolytic graphite (PG) analyser bank on the IRIS high resolution inelastic spectrometer [1] at ISIS is to be upgraded. At present the analyser consists of 1350 graphite pieces (6 rows by 225 columns) cooled to 25K [2]. The new analyser array, however, will provide a three-fold increase in area and employ 4212 crystal pieces (18 rows by 234 columns). In addition, the graphite crystals will be cooled close to liquid helium temperature to further reduce thermal diffuse scattering (TDS) and improve the sensitivity of the spectrometer [2]. For an instrument such as IRIS, with its analyser in near back-scattering geometry, optical aberration and variation in the time-of-flight of the analysed neutrons is introduced as one moves out from the horizontal scattering plane. To minimise such effects, the profile of the analyser array has been redesigned. The concept behind the design of the new analyser bank and factors that effect the overall resolution of the instrument are discussed. Results of Monte Carlo simulations of the expected resolution and intensity of the complete instrument are presented and compared to the current instrument performance. (author) [1] C.J. Carlile et al, Physica B 182 (1992) 431-440.; [2] C.J. Carlile et al, Nuclear Instruments and Methods In Physics Research A 338 (1994) 78-82
User guide for the Polaris powder diffractometer at ISIS
International Nuclear Information System (INIS)
Smith, R.I.; Hull, S.
1997-09-01
Version 3.0 of the Polaris User Guide has been produced to coincide with the move of the instrument onto ISIS beamline N7. The new instrument has been built to an almost identical specification as the old, however the ability to start from scratch on a new beamline has allowed certain aspects of Polaris to be optimised. Polaris on beamline N7 retains its four discrete detector banks, situated at backscattering angles, 90 degrees, low angles and very low angles. During the instrument move the Polaris detector complement was increased, with 20 3 He tubes added to the backscattering detector bank and a further two ZnS scintillator modules added to the 90 degrees detector bank. This has approximately doubled the count rate of the backscattering bank, whereas in the 90 degrees bank the detectors have been moved further from the sample resulting in an improvement in resolution while maintaining the count rate. Finally, the geometry of the four ZnS scintillator detector modules in the very low angle bank was altered slightly to improve the performance of this bank. The most significant change in the new Polaris, however is the redesign of the instrument blockhouse. Access to the sample position is now at floor level, and no longer requires entry into the blockhouse. With only a small enclosure built around the sample position sample environment equipment, such as furnaces and cryostats, can be operated in a much more convenient and flexible manner. (Author)
Post design evaluation (ageing mechanisms, effects, management, monitoring, PSR, ISI)
International Nuclear Information System (INIS)
Ichikawa, Toshio
2001-01-01
Although the nuclear plant was designed for the purpose of the 30-year life the early stages of construction, it also already has the plant abolished by passing in 30 years. There is a plant under operation and a plant that is employed variously, extends the original life and continues operation now, and the plant that is going to be abolished politically is before a life. By using a nuclear plant for a long period of time, damage. by the influence of irradiation, wear of slipping, corrosion, etc. appears. When this degradation is left, the serious accident is caused. In this lecture, refer to Assessment and management of ageing of major nuclear power plant components important to safety, Oct. 1999 of IAEA. A point of view from guide is introduced about management of the mechanism in the secular degradation mode expected by operating for a long period of time, the influence of secular degradation, and influence, monitoring technology, periodical safe evaluation, and a periodic inspection. And raises and explains the correspondence situation of secular degradation, and the example of evaluation of PSR and ISI equipment. The aging mechanism for reactor vessel internal components considered are related to embrittlement, fatigue, corrosion, radiation induced creep, relaxation and swelling, and mechanical wear. This lecture includes; monitoring methods, a description of periodic safety reviews and a sample of seismic design periodic safety report for the reactor internals
First results with prototype ISIS devices for ILC vertex detector
International Nuclear Information System (INIS)
Damerell, C.; Zhang, Z.; Gao, R.; John John, Jaya; Li, Y.; Nomerotski, A.; Holland, A.; Seabroke, G.; Havranek, M.; Stefanov, K.; Kar-Roy, A.; Bell, R.; Burt, D.; Pool, P.
2010-01-01
The vertex detectors at the International Linear Collider (ILC) (there will be two of them, one for each of two general purpose detectors) will certainly be built with silicon pixel detectors, either monolithic or perhaps vertically integrated. However, beyond this general statement, there is a wide range of options supported by active R and D programmes all over the world. Pixel-based vertex detectors build on the experience at the SLAC large detector (SLD) operating at the SLAC linear collider (SLC), where a 307 Mpixel detector permitted the highest physics performance at LEP or SLC. For ILC, machine conditions demand much faster readout than at SLC, something like 20 time slices during the 1 ms bunch train. The approach of the image sensor with in-situ storage (ISIS) is unique in offering this capability while avoiding the undesirable requirement of 'pulsed power'. First results from a prototype device that approaches the pixel size of 20 μm square, needed for physics, are reported. The dimensional challenge is met by using a 0.18 μm imaging CMOS process, instead of a conventional CCD process.
First results with prototype ISIS devices for ILC vertex detector
Energy Technology Data Exchange (ETDEWEB)
Damerell, C., E-mail: c.damerell@rl.ac.u [RAL, Oxon OX11 0QX (United Kingdom); Zhang, Z. [RAL, Oxon OX11 0QX (United Kingdom); Gao, R.; John John, Jaya; Li, Y.; Nomerotski, A. [Oxford U (United Kingdom); Holland, A.; Seabroke, G. [Centre for Electronic Imaging, Open U (United Kingdom); Havranek, M. [Czech Technical University in Prague (Czech Republic); Stefanov, K. [Sentec Ltd, Cambridge (United Kingdom); Kar-Roy, A. [Jazz Semiconductors, California (United States); Bell, R.; Burt, D.; Pool, P. [e2V Technologies, Chelmsford (United Kingdom)
2010-12-11
The vertex detectors at the International Linear Collider (ILC) (there will be two of them, one for each of two general purpose detectors) will certainly be built with silicon pixel detectors, either monolithic or perhaps vertically integrated. However, beyond this general statement, there is a wide range of options supported by active R and D programmes all over the world. Pixel-based vertex detectors build on the experience at the SLAC large detector (SLD) operating at the SLAC linear collider (SLC), where a 307 Mpixel detector permitted the highest physics performance at LEP or SLC. For ILC, machine conditions demand much faster readout than at SLC, something like 20 time slices during the 1 ms bunch train. The approach of the image sensor with in-situ storage (ISIS) is unique in offering this capability while avoiding the undesirable requirement of 'pulsed power'. First results from a prototype device that approaches the pixel size of 20 {mu}m square, needed for physics, are reported. The dimensional challenge is met by using a 0.18 {mu}m imaging CMOS process, instead of a conventional CCD process.
Overview of the IAEA's activity on ISI qualification
International Nuclear Information System (INIS)
Trampus, P.
2000-01-01
The IAEA Subprogram on Nuclear Power Planning, Implementation and Performance is presented. It's objective is to assist Member States in: planning nuclear power programmes in an integrated manner considering all necessary factors; systematically improving overall performance and competitiveness of NPPs trough entire service life with due regard to safety; applying technological/engineering best practices including QA/QM in all areas of nuclear power utilisation. International working group on life management of NPPs (IWG-LMNPP) has been established in 1975 with 26 Member States and 2 international organizations in order to provide the Director General with advice and opinions and the Member States with information, recommendations and support in life management issues.The technical co-operation program RER/4/020 'Advanced NDT of Primary Circuit Components' is presented.The pilot study is aimed to provide the participating Member States with practical advice how to apply the IAEA's qualification methodology. The target application is Technical Justification for UT of WWER-1000 RPV shell weld (unit 5 of 'Kozloduy NPP). The concept is to simulate the qualification process through assistance to establish qualification for a real NPP component, using real ISI, in a real regulatory environment. Interim results for Bulgaria are reported and further tasks are outlined
A DUAL NETWORK MODEL OF INTERLOCKING DIRECTORATES
Directory of Open Access Journals (Sweden)
Humphry Hung
2003-01-01
Full Text Available The article proposes an integrative framework for the study of interlocking directorates by using an approach that encompasses the concepts of multiple networks and resource endowment. This serves to integrate the traditional views of interorganizational linkages and intra-class cohesion. Through appropriate strategic analysis of relevant resource endowment of internal environment and external networks of organizations and corporate elites, this article argues that the selection of directors, if used effectively, can be adopted as a strategic device to enhance the corporation's overall performance.
A Simplified Network Model for Travel Time Reliability Analysis in a Road Network
Directory of Open Access Journals (Sweden)
Kenetsu Uchida
2017-01-01
Full Text Available This paper proposes a simplified network model which analyzes travel time reliability in a road network. A risk-averse driver is assumed in the simplified model. The risk-averse driver chooses a path by taking into account both a path travel time variance and a mean path travel time. The uncertainty addressed in this model is that of traffic flows (i.e., stochastic demand flows. In the simplified network model, the path travel time variance is not calculated by considering all travel time covariance between two links in the network. The path travel time variance is calculated by considering all travel time covariance between two adjacent links in the network. Numerical experiments are carried out to illustrate the applicability and validity of the proposed model. The experiments introduce the path choice behavior of a risk-neutral driver and several types of risk-averse drivers. It is shown that the mean link flows calculated by introducing the risk-neutral driver differ as a whole from those calculated by introducing several types of risk-averse drivers. It is also shown that the mean link flows calculated by the simplified network model are almost the same as the flows calculated by using the exact path travel time variance.
Copula-based modeling of degree-correlated networks
International Nuclear Information System (INIS)
Raschke, Mathias; Schläpfer, Markus; Trantopoulos, Konstantinos
2014-01-01
Dynamical processes on complex networks such as information exchange, innovation diffusion, cascades in financial networks or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree–degree correlations. Here, we introduce the concept of copulas in order to generate random networks with an arbitrary degree distribution and a rich a priori degree–degree correlation (or ‘association’) structure. The accuracy of the proposed formalism and corresponding algorithm is numerically confirmed, while the method is tested on a real-world network of yeast protein–protein interactions. The derived network ensembles can be systematically deployed as proper null models, in order to unfold the complex interplay between the topology of real-world networks and the dynamics on top of them. (paper)
neural network based model o work based model of an industrial oil
African Journals Online (AJOL)
eobe
technique. g, Neural Network Model, Regression, Mean Square Error, PID controller. ... during the training processes. An additio ... used to carry out simulation studies of the mode .... A two-layer feed-forward neural network with Matlab.
A Gaussian graphical model approach to climate networks
Energy Technology Data Exchange (ETDEWEB)
Zerenner, Tanja, E-mail: tanjaz@uni-bonn.de [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)
2014-06-15
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.
A Gaussian graphical model approach to climate networks
International Nuclear Information System (INIS)
Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus
2014-01-01
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately
Quebec mental health services networks: models and implementation
Directory of Open Access Journals (Sweden)
Marie-Josée Fleury
2005-06-01
Full Text Available Purpose: In the transformation of health care systems, the introduction of integrated service networks is considered to be one of the main solutions for enhancing efficiency. In the last few years, a wealth of literature has emerged on the topic of services integration. However, the question of how integrated service networks should be modelled to suit different implementation contexts has barely been touched. To fill that gap, this article presents four models for the organization of mental health integrated networks. Data sources: The proposed models are drawn from three recently published studies on mental health integrated services in the province of Quebec (Canada with the author as principal investigator. Description: Following an explanation of the concept of integrated service network and a description of the Quebec context for mental health networks, the models, applicable in all settings: rural, urban or semi-urban, and metropolitan, and summarized in four figures, are presented. Discussion and conclusion: To apply the models successfully, the necessity of rallying all the actors of a system, from the strategic, tactical and operational levels, according to the type of integration involved: functional/administrative, clinical and physician-system is highlighted. The importance of formalizing activities among organizations and actors in a network and reinforcing the governing mechanisms at the local level is also underlined. Finally, a number of integration strategies and key conditions of success to operationalize integrated service networks are suggested.
Characterization of γ-ray background at IMAT beamline of ISIS Spallation Neutron Source
Festa, G.; Andreani, C.; Arcidiacono, L.; Burca, G.; Kockelmann, W.; Minniti, T.; Senesi, R.
2017-08-01
The environmental γ -ray background on the IMAT beamline at ISIS Spallation Neutron Source, Target Station 2, is characterized via γ spectroscopy. The measurements include gamma exposure at the imaging detector position, along with the gamma background inside the beamline. Present results are discussed and compared with previous measurements recorded at INES and VESUVIO beamlines operating at Target Station 1. They provide new outcome for expanding and optimizing the PGAA experimental capability at the ISIS neutron source for the investigation of materials, engineering components and cultural heritage objects at the ISIS neutron source.
ISIS Training Reactor: A Reactor Dedicated to Education and Training for Students and Professionals
International Nuclear Information System (INIS)
Foulon, F.
2014-01-01
Conclusion: • INSTN strategy: complete theoretical courses by practical courses on the ISIS research reactor. • Training courses integrated both in Academic degree programs and continuing education. • 27 hours of training courses have been developed focusing on the practical and safety aspects of reactor operation. • The Education and Training activity became the main activity of ISIS reactor: 400 trainees/year; 360 hours/year; 40% in English. • Remote access to the Training courses: Internet Reactor Laboratory under development to be started from 2014 to broadcast training courses from ISIS reactor to guest institutions
Characterization of γ-ray background at IMAT beamline of ISIS Spallation Neutron Source
International Nuclear Information System (INIS)
Festa, G.; Andreani, C.; Arcidiacono, L.; Senesi, R.; Burca, G.; Kockelmann, W.; Minniti, T.
2017-01-01
The environmental γ -ray background on the IMAT beamline at ISIS Spallation Neutron Source, Target Station 2, is characterized via γ spectroscopy. The measurements include gamma exposure at the imaging detector position, along with the gamma background inside the beamline. Present results are discussed and compared with previous measurements recorded at INES and VESUVIO beamlines operating at Target Station 1. They provide new outcome for expanding and optimizing the PGAA experimental capability at the ISIS neutron source for the investigation of materials, engineering components and cultural heritage objects at the ISIS neutron source.
A ternary logic model for recurrent neuromime networks with delay.
Hangartner, R D; Cull, P
1995-07-01
In contrast to popular recurrent artificial neural network (RANN) models, biological neural networks have unsymmetric structures and incorporate significant delays as a result of axonal propagation. Consequently, biologically inspired neural network models are more accurately described by nonlinear differential-delay equations rather than nonlinear ordinary differential equations (ODEs), and the standard techniques for studying the dynamics of RANNs are wholly inadequate for these models. This paper develops a ternary-logic based method for analyzing these networks. Key to the technique is the realization that a nonzero delay produces a bounded stability region. This result significantly simplifies the construction of sufficient conditions for characterizing the network equilibria. If the network gain is large enough, each equilibrium can be classified as either asymptotically stable or unstable. To illustrate the analysis technique, the swim central pattern generator (CPG) of the sea slug Tritonia diomedea is examined. For wide range of reasonable parameter values, the ternary analysis shows that none of the network equilibria are stable, and thus the network must oscillate. The results show that complex synaptic dynamics are not necessary for pattern generation.
Business Process Modeling Languages Supporting Collaborative Networks
Soleimani Malekan, H.; Afsarmanesh, H.; Hammoudi, S.; Maciaszek, L.A.; Cordeiro, J.; Dietz, J.L.G.
2013-01-01
Formalizing the definition of Business Processes (BPs) performed within each enterprise is fundamental for effective deployment of their competencies and capabilities within Collaborative Networks (CN). In our approach, every enterprise in the CN is represented by its set of BPs, so that other
Message Integrity Model for Wireless Sensor Networks
Qleibo, Haider W.
2009-01-01
WSNs are susceptible to a variety of attacks. These attacks vary in the way they are performed and executed; they include but not limited to node capture, physical tampering, denial of service, and message alteration. It is of paramount importance to protect gathered data by WSNs and defend the network against illegal access and malicious…
Modeling urbanization patterns with generative adversarial networks
Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta
2018-01-01
In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.
International Nuclear Information System (INIS)
Ramirez-Marquez, Jose Emmanuel; Rocco S, Claudio M.
2009-01-01
This paper introduces an evolutionary optimization approach that can be readily applied to solve stochastic network interdiction problems (SNIP). The network interdiction problem solved considers the minimization of the cost associated with an interdiction strategy such that the maximum flow that can be transmitted between a source node and a sink node for a fixed network design is greater than or equal to a given reliability requirement. Furthermore, the model assumes that the nominal capacity of each network link and the cost associated with their interdiction can change from link to link and that such interdiction has a probability of being successful. This version of the SNIP is for the first time modeled as a capacitated network reliability problem allowing for the implementation of computation and solution techniques previously unavailable. The solution process is based on an evolutionary algorithm that implements: (1) Monte-Carlo simulation, to generate potential network interdiction strategies, (2) capacitated network reliability techniques to analyze strategies' source-sink flow reliability and, (3) an evolutionary optimization technique to define, in probabilistic terms, how likely a link is to appear in the final interdiction strategy. Examples for different sizes of networks are used throughout the paper to illustrate the approach
SCYNet. Testing supersymmetric models at the LHC with neural networks
Energy Technology Data Exchange (ETDEWEB)
Bechtle, Philip; Belkner, Sebastian; Hamer, Matthias [Universitaet Bonn, Bonn (Germany); Dercks, Daniel [Universitaet Hamburg, Hamburg (Germany); Keller, Tim; Kraemer, Michael; Sarrazin, Bjoern; Schuette-Engel, Jan; Tattersall, Jamie [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany)
2017-10-15
SCYNet (SUSY Calculating Yield Net) is a tool for testing supersymmetric models against LHC data. It uses neural network regression for a fast evaluation of the profile likelihood ratio. Two neural network approaches have been developed: one network has been trained using the parameters of the 11-dimensional phenomenological Minimal Supersymmetric Standard Model (pMSSM-11) as an input and evaluates the corresponding profile likelihood ratio within milliseconds. It can thus be used in global pMSSM-11 fits without time penalty. In the second approach, the neural network has been trained using model-independent signature-related objects, such as energies and particle multiplicities, which were estimated from the parameters of a given new physics model. (orig.)
Numeral eddy current sensor modelling based on genetic neural network
International Nuclear Information System (INIS)
Yu Along
2008-01-01
This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method
Modelling and predicting biogeographical patterns in river networks
Directory of Open Access Journals (Sweden)
Sabela Lois
2016-04-01
Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.
Particle swarm optimization of a neural network model in a ...
Indian Academy of Sciences (India)
. Since tool life is critically affected by the tool wear, accurate prediction of this wear ... In their work, they established an improvement in the quality ... objective optimization of hard turning using neural network modelling and swarm intelligence ...
Modelling the self-organization and collapse of complex networks
Indian Academy of Sciences (India)
Modelling the self-organization and collapse of complex networks. Sanjay Jain Department of Physics and Astrophysics, University of Delhi Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore Santa Fe Institute, Santa Fe, New Mexico.
Numerical Analysis of Modeling Based on Improved Elman Neural Network
Directory of Open Access Journals (Sweden)
Shao Jie
2014-01-01
Full Text Available A modeling based on the improved Elman neural network (IENN is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL model, Chebyshev neural network (CNN model, and basic Elman neural network (BENN model, the proposed model has better performance.
Feed forward neural networks modeling for K-P interactions
International Nuclear Information System (INIS)
El-Bakry, M.Y.
2003-01-01
Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K-P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data
Modeling Evolution on Nearly Neutral Network Fitness Landscapes
Yakushkina, Tatiana; Saakian, David B.
2017-08-01
To describe virus evolution, it is necessary to define a fitness landscape. In this article, we consider the microscopic models with the advanced version of neutral network fitness landscapes. In this problem setting, we suppose a fitness difference between one-point mutation neighbors to be small. We construct a modification of the Wright-Fisher model, which is related to ordinary infinite population models with nearly neutral network fitness landscape at the large population limit. From the microscopic models in the realistic sequence space, we derive two versions of nearly neutral network models: with sinks and without sinks. We claim that the suggested model describes the evolutionary dynamics of RNA viruses better than the traditional Wright-Fisher model with few sequences.
Infection dynamics on spatial small-world network models
Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario
2017-11-01
The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.
Modelling, Synthesis, and Configuration of Networks-on-Chips
DEFF Research Database (Denmark)
Stuart, Matthias Bo
This thesis presents three contributions in two different areas of network-on-chip and system-on-chip research: Application modelling and identifying and solving different optimization problems related to two specific network-on-chip architectures. The contribution related to application modelling...... is an analytical method for deriving the worst-case traffic pattern caused by an application and the cache-coherence protocol in a cache-coherent shared-memory system. The contributions related to network-on-chip optimization problems consist of two parts: The development and evaluation of six heuristics...... for solving the network synthesis problem in the MANGO network-on-chip, and the identification and formalization of the ReNoC configuration problem together with three heuristics for solving it....
Statistical inference to advance network models in epidemiology.
Welch, David; Bansal, Shweta; Hunter, David R
2011-03-01
Contact networks are playing an increasingly important role in the study of epidemiology. Most of the existing work in this area has focused on considering the effect of underlying network structure on epidemic dynamics by using tools from probability theory and computer simulation. This work has provided much insight on the role that heterogeneity in host contact patterns plays on infectious disease dynamics. Despite the important understanding afforded by the probability and simulation paradigm, this approach does not directly address important questions about the structure of contact networks such as what is the best network model for a particular mode of disease transmission, how parameter values of a given model should be estimated, or how precisely the data allow us to estimate these parameter values. We argue that these questions are best answered within a statistical framework and discuss the role of statistical inference in estimating contact networks from epidemiological data. Copyright © 2011 Elsevier B.V. All rights reserved.
Neural network modeling for near wall turbulent flow
International Nuclear Information System (INIS)
Milano, Michele; Koumoutsakos, Petros
2002-01-01
A neural network methodology is developed in order to reconstruct the near wall field in a turbulent flow by exploiting flow fields provided by direct numerical simulations. The results obtained from the neural network methodology are compared with the results obtained from prediction and reconstruction using proper orthogonal decomposition (POD). Using the property that the POD is equivalent to a specific linear neural network, a nonlinear neural network extension is presented. It is shown that for a relatively small additional computational cost nonlinear neural networks provide us with improved reconstruction and prediction capabilities for the near wall velocity fields. Based on these results advantages and drawbacks of both approaches are discussed with an outlook toward the development of near wall models for turbulence modeling and control
Modeling and Analysis of New Products Diffusion on Heterogeneous Networks
Directory of Open Access Journals (Sweden)
Shuping Li
2014-01-01
Full Text Available We present a heterogeneous networks model with the awareness stage and the decision-making stage to explain the process of new products diffusion. If mass media is neglected in the decision-making stage, there is a threshold whether the innovation diffusion is successful or not, or else it is proved that the network model has at least one positive equilibrium. For networks with the power-law degree distribution, numerical simulations confirm analytical results, and also at the same time, by numerical analysis of the influence of the network structure and persuasive advertisements on the density of adopters, we give two different products propagation strategies for two classes of nodes in scale-free networks.
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Directory of Open Access Journals (Sweden)
Natalie Berestovsky
Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them
Bayesian network modeling of operator's state recognition process
International Nuclear Information System (INIS)
Hatakeyama, Naoki; Furuta, Kazuo
2000-01-01
Nowadays we are facing a difficult problem of establishing a good relation between humans and machines. To solve this problem, we suppose that machine system need to have a model of human behavior. In this study we model the state cognition process of a PWR plant operator as an example. We use a Bayesian network as an inference engine. We incorporate the knowledge hierarchy in the Bayesian network and confirm its validity using the example of PWR plant operator. (author)
Attention-based Memory Selection Recurrent Network for Language Modeling
Liu, Da-Rong; Chuang, Shun-Po; Lee, Hung-yi
2016-01-01
Recurrent neural networks (RNNs) have achieved great success in language modeling. However, since the RNNs have fixed size of memory, their memory cannot store all the information about the words it have seen before in the sentence, and thus the useful long-term information may be ignored when predicting the next words. In this paper, we propose Attention-based Memory Selection Recurrent Network (AMSRN), in which the model can review the information stored in the memory at each previous time ...
Design and realization of a network security model
WANG, Jiahai; HAN, Fangxi; Tang, Zheng; TAMURA, Hiroki; Ishii, Masahiro
2002-01-01
The security of information is a key problem in the development of network technology. The basic requirements of security of information clearly include confidentiality, integrity, authentication and non-repudiation. This paper proposes a network security model that is composed of security system, security connection and communication, and key management. The model carries out encrypting, decrypting, signature and ensures confidentiality, integrity, authentication and non-repudiation. Finally...
Trojan detection model based on network behavior analysis
International Nuclear Information System (INIS)
Liu Junrong; Liu Baoxu; Wang Wenjin
2012-01-01
Based on the analysis of existing Trojan detection technology, this paper presents a Trojan detection model based on network behavior analysis. First of all, we abstract description of the Trojan network behavior, then according to certain rules to establish the characteristic behavior library, and then use the support vector machine algorithm to determine whether a Trojan invasion. Finally, through the intrusion detection experiments, shows that this model can effectively detect Trojans. (authors)
Aplikasi Bidirectional Assosiatif Memori (BAM) Network pada Pengenalan Model
Iskandar, Iskhaq
2001-01-01
Penelitian ini bertujuan untuk menyusun suatu simulasi komputer yang dapat dipergunakan untuk menguji kemampuan memori komputer dalam mengenali suatu model tertentu berdasarkan algoritma Bidirectional Assosiatif Memori Neural Network. Model yang digunakan dalam penelitian dalam penelitian ini adalah huruf-huruf abjad yang dinyatakan dalam kode polar –1 dan +1 dalam bentuk matrik [5x3]. Hasil yang didapat dalam penelitian ini menunjukkan bahwa rancangan network yang disusun mampu mengenali mod...
Directory of Open Access Journals (Sweden)
Haibo Zhang
2016-08-01
Full Text Available The security incidents ion networks are sudden and uncertain, it is very hard to precisely predict the network security situation by traditional methods. In order to improve the prediction accuracy of the network security situation, we build a network security situation prediction model based on Wavelet Neural Network (WNN with optimized parameters by the Improved Niche Genetic Algorithm (INGA. The proposed model adopts WNN which has strong nonlinear ability and fault-tolerance performance. Also, the parameters for WNN are optimized through the adaptive genetic algorithm (GA so that WNN searches more effectively. Considering the problem that the adaptive GA converges slowly and easily turns to the premature problem, we introduce a novel niche technology with a dynamic fuzzy clustering and elimination mechanism to solve the premature convergence of the GA. Our final simulation results show that the proposed INGA-WNN prediction model is more reliable and effective, and it achieves faster convergence-speed and higher prediction accuracy than the Genetic Algorithm-Wavelet Neural Network (GA-WNN, Genetic Algorithm-Back Propagation Neural Network (GA-BPNN and WNN.
Extending a configuration model to find communities in complex networks
International Nuclear Information System (INIS)
Jin, Di; Hu, Qinghua; He, Dongxiao; Yang, Bo; Baquero, Carlos
2013-01-01
Discovery of communities in complex networks is a fundamental data analysis task in various domains. Generative models are a promising class of techniques for identifying modular properties from networks, which has been actively discussed recently. However, most of them cannot preserve the degree sequence of networks, which will distort the community detection results. Rather than using a blockmodel as most current works do, here we generalize a configuration model, namely, a null model of modularity, to solve this problem. Towards decomposing and combining sub-graphs according to the soft community memberships, our model incorporates the ability to describe community structures, something the original model does not have. Also, it has the property, as with the original model, that it fixes the expected degree sequence to be the same as that of the observed network. We combine both the community property and degree sequence preserving into a single unified model, which gives better community results compared with other models. Thereafter, we learn the model using a technique of nonnegative matrix factorization and determine the number of communities by applying consensus clustering. We test this approach both on synthetic benchmarks and on real-world networks, and compare it with two similar methods. The experimental results demonstrate the superior performance of our method over competing methods in detecting both disjoint and overlapping communities. (paper)
Spatial-temporal modeling of malware propagation in networks.
Chen, Zesheng; Ji, Chuanyi
2005-09-01
Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.
Statistical mechanics of attractor neural network models with synaptic depression
International Nuclear Information System (INIS)
Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato
2009-01-01
Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.
Reactor pressure vessel embrittlement: Insights from neural network modelling
Mathew, J.; Parfitt, D.; Wilford, K.; Riddle, N.; Alamaniotis, M.; Chroneos, A.; Fitzpatrick, M. E.
2018-04-01
Irradiation embrittlement of steel pressure vessels is an important consideration for the operation of current and future light water nuclear reactors. In this study we employ an ensemble of artificial neural networks in order to provide predictions of the embrittlement using two literature datasets, one based on US surveillance data and the second from the IVAR experiment. We use these networks to examine trends with input variables and to assess various literature models including compositional effects and the role of flux and temperature. Overall, the networks agree with the existing literature models and we comment on their more general use in predicting irradiation embrittlement.
Randomizing growing networks with a time-respecting null model
Ren, Zhuo-Ming; Mariani, Manuel Sebastian; Zhang, Yi-Cheng; Medo, Matúš
2018-05-01
Complex networks are often used to represent systems that are not static but grow with time: People make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of measurements made on such networks, we propose a randomization methodology—a time-respecting null model—that preserves both the network's degree sequence and the time evolution of individual nodes' degree values. By preserving the temporal linking patterns of the analyzed system, the proposed model is able to factor out the effect of the system's temporal patterns on its structure. We apply the model to the citation network of Physical Review scholarly papers and the citation network of US movies. The model reveals that the two data sets are strikingly different with respect to their degree-degree correlations, and we discuss the important implications of this finding on the information provided by paradigmatic node centrality metrics such as indegree and Google's PageRank. The randomization methodology proposed here can be used to assess the significance of any structural property in growing networks, which could bring new insights into the problems where null models play a critical role, such as the detection of communities and network motifs.
Innovative research of AD HOC network mobility model
Chen, Xin
2017-08-01
It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.
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.
Maritime piracy situation modelling with dynamic Bayesian networks
CSIR Research Space (South Africa)
Dabrowski, James M
2015-05-01
Full Text Available A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a...
The communications model of using social network by sports clubs
S. Kowalski
2012-01-01
This article presents a model of marketing communications using social network by sports clubs. It presents the links between the sports club and its environment and uses of the Internet to promote it. The model of communication is composed of the elements responsible for the success of marketing in the web. Article also includes recommendations for using the model in practice.
A network growth model based on the evolutionary ultimatum game
International Nuclear Information System (INIS)
Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S
2012-01-01
In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)
Language Networks as Models of Cognition: Understanding Cognition through Language
Beckage, Nicole M.; Colunga, Eliana
Language is inherently cognitive and distinctly human. Separating the object of language from the human mind that processes and creates language fails to capture the full language system. Linguistics traditionally has focused on the study of language as a static representation, removed from the human mind. Network analysis has traditionally been focused on the properties and structure that emerge from network representations. Both disciplines could gain from looking at language as a cognitive process. In contrast, psycholinguistic research has focused on the process of language without committing to a representation. However, by considering language networks as approximations of the cognitive system we can take the strength of each of these approaches to study human performance and cognition as related to language. This paper reviews research showcasing the contributions of network science to the study of language. Specifically, we focus on the interplay of cognition and language as captured by a network representation. To this end, we review different types of language network representations before considering the influence of global level network features. We continue by considering human performance in relation to network structure and conclude with theoretical network models that offer potential and testable explanations of cognitive and linguistic phenomena.
Two-component network model in voice identification technologies
Directory of Open Access Journals (Sweden)
Edita K. Kuular
2018-03-01
Full Text Available Among the most important parameters of biometric systems with voice modalities that determine their effectiveness, along with reliability and noise immunity, a speed of identification and verification of a person has been accentuated. This parameter is especially sensitive while processing large-scale voice databases in real time regime. Many research studies in this area are aimed at developing new and improving existing algorithms for presentation and processing voice records to ensure high performance of voice biometric systems. Here, it seems promising to apply a modern approach, which is based on complex network platform for solving complex massive problems with a large number of elements and taking into account their interrelationships. Thus, there are known some works which while solving problems of analysis and recognition of faces from photographs, transform images into complex networks for their subsequent processing by standard techniques. One of the first applications of complex networks to sound series (musical and speech analysis are description of frequency characteristics by constructing network models - converting the series into networks. On the network ontology platform a previously proposed technique of audio information representation aimed on its automatic analysis and speaker recognition has been developed. This implies converting information into the form of associative semantic (cognitive network structure with amplitude and frequency components both. Two speaker exemplars have been recorded and transformed into pertinent networks with consequent comparison of their topological metrics. The set of topological metrics for each of network models (amplitude and frequency one is a vector, and together those combine a matrix, as a digital "network" voiceprint. The proposed network approach, with its sensitivity to personal conditions-physiological, psychological, emotional, might be useful not only for person identification
Introducing serendipity in a social network model of knowledge diffusion
International Nuclear Information System (INIS)
Cremonini, Marco
2016-01-01
Highlights: • Serendipity as a control mechanism for knowledge diffusion in social network. • Local communication enhanced in the periphery of a network. • Prevalence of hub nodes in the network core mitigated. • Potential disruptive effect on network formation of uncontrolled serendipity. - Abstract: In this paper, we study serendipity as a possible strategy to control the behavior of an agent-based network model of knowledge diffusion. The idea of considering serendipity in a strategic way has been first explored in Network Learning and Information Seeking studies. After presenting the major contributions of serendipity studies to digital environments, we discuss the extension to our model: Agents are enriched with random topics for establishing new communication according to different strategies. The results show how important network properties could be influenced, like reducing the prevalence of hubs in the network’s core and increasing local communication in the periphery, similar to the effects of more traditional self-organization methods. Therefore, from this initial study, when serendipity is opportunistically directed, it appears to behave as an effective and applicable approach to social network control.
A Network-Individual-Resource Model for HIV Prevention
Johnson, Blair T.; Redding, Colleen A.; DiClemente, Ralph J.; Mustanski, Brian S.; Dodge, Brian M.; Sheeran, Paschal; Warren, Michelle R.; Zimmerman, Rick S.; Fisher, William A.; Conner, Mark T.; Carey, Michael P.; Fisher, Jeffrey D.; Stall, Ronald D.; Fishbein, Martin
2014-01-01
HIV is transmitted through dyadic exchanges of individuals linked in transitory or permanent networks of varying sizes. To optimize prevention efficacy, a complementary theoretical perspective that bridges key individual level elements with important network elements can be a foundation for developing and implementing HIV interventions with outcomes that are more sustainable over time and have greater dissemination potential. Toward that end, we introduce a Network-Individual-Resource (NIR) model for HIV prevention that recognizes how exchanges of resources between individuals and their networks underlies and sustains HIV-risk behaviors. Individual behavior change for HIV prevention, then, may be dependent on increasing the supportiveness of that individual's relevant networks for such change. Among other implications, an NIR model predicts that the success of prevention efforts depends on whether the prevention efforts (1) prompt behavior changes that can be sustained by the resources the individual or their networks possess; (2) meet individual and network needs and are consistent with the individual's current situation/developmental stage; (3) are trusted and valued; and (4) target high HIV-prevalence networks. PMID:20862606
Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.
Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J
2017-07-25
Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.
A growing social network model in geographical space
Antonioni, Alberto; Tomassini, Marco
2017-09-01
In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.
Perception of similarity: a model for social network dynamics
International Nuclear Information System (INIS)
Javarone, Marco Alberto; Armano, Giuliano
2013-01-01
Some properties of social networks (e.g., the mixing patterns and the community structure) appear deeply influenced by the individual perception of people. In this work we map behaviors by considering similarity and popularity of people, also assuming that each person has his/her proper perception and interpretation of similarity. Although investigated in different ways (depending on the specific scientific framework), from a computational perspective similarity is typically calculated as a distance measure. In accordance with this view, to represent social network dynamics we developed an agent-based model on top of a hyperbolic space on which individual distance measures are calculated. Simulations, performed in accordance with the proposed model, generate small-world networks that exhibit a community structure. We deem this model to be valuable for analyzing the relevant properties of real social networks. (paper)
Bayesian network models for error detection in radiotherapy plans
International Nuclear Information System (INIS)
Kalet, Alan M; Ford, Eric C; Phillips, Mark H; Gennari, John H
2015-01-01
The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures. (paper)
A Critical Analysis of the Lemmatisation of Nouns and Verbs in isiZulu
African Journals Online (AJOL)
of isiZulu. The advantages versus disadvantages of lemmatising verbal and nominal stems, verbal .... imisebenzikazi (1) (imisebenzi+kazi) 'big jobs'. Affixes ...... of related items, new routes to the data, less dependency on alphabetical order,.
Horizontal beams creation on a mean power reactor: Isis 700 kW
International Nuclear Information System (INIS)
Morin, C.
1987-08-01
To satisfy the requests of experimenters, two horizontal beams, tangential at core, have been created. After a brief recall of the Isis reactor the author describes the realized works and gives a summary description of the two beams equipment [fr
Literaure search for intermittent rivers research using ISI Web of Science
U.S. Environmental Protection Agency — The dataset is the bibliometric information included in the ISI Web of Science database of scientific literature. Table S2 accessible from the dataset link provides...
The high resolution powder diffractometer (HRPD) at ISIS - a user guide
International Nuclear Information System (INIS)
Ibberson, R.M.; David, W.I.F.; Knight, K.S.
1992-05-01
This guide is intended to give a short description of the High Resolution Powder Diffractometer, HRPD, at ISIS and to provide the basic information required in order to perform a routine powder diffraction experiment. (Author)
Bayesian Network Models in Cyber Security: A Systematic Review
Chockalingam, S.; Pieters, W.; Herdeiro Teixeira, A.M.; van Gelder, P.H.A.J.M.; Lipmaa, Helger; Mitrokotsa, Aikaterini; Matulevicius, Raimundas
2017-01-01
Bayesian Networks (BNs) are an increasingly popular modelling technique in cyber security especially due to their capability to overcome data limitations. This is also instantiated by the growth of BN models development in cyber security. However, a comprehensive comparison and analysis of these models is missing. In this paper, we conduct a systematic review of the scientific literature and identify 17 standard BN models in cyber security. We analyse these models based on 9 different criteri...
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2014-11-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.
The new challenges of multiplex networks: Measures and models
Battiston, Federico; Nicosia, Vincenzo; Latora, Vito
2017-02-01
What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.
Neural Network Models for Free Radical Polymerization of Methyl Methacrylate
International Nuclear Information System (INIS)
Curteanu, S.; Leon, F.; Galea, D.
2003-01-01
In this paper, a neural network modeling of the batch bulk methyl methacrylate polymerization is performed. To obtain conversion, number and weight average molecular weights, three neural networks were built. Each was a multilayer perception with one or two hidden layers. The choice of network topology, i.e. the number of hidden layers and the number of neurons in these layers, was based on achieving a compromise between precision and complexity. Thus, it was intended to have an error as small as possible at the end of back-propagation training phases, while using a network with reduced complexity. The performances of the networks were evaluated by comparing network predictions with training data, validation data (which were not uses for training), and with the results of a mechanistic model. The accurate predictions of neural networks for monomer conversion, number average molecular weight and weight average molecular weight proves that this modeling methodology gives a good representation and generalization of the batch bulk methyl methacrylate polymerization. (author)
Generalized memory associativity in a network model for the neuroses
Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.
2009-03-01
We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's idea that consciousness is related to symbolic and linguistic memory activity in the brain. We have introduced a generalization of the Boltzmann machine to model memory associativity. Model behavior is illustrated with simulations and some of its properties are analyzed with methods from statistical mechanics.
Semi-automatic Term Extraction for an isiZulu Linguistic Terms ...
African Journals Online (AJOL)
user
This paper advances the use of frequency analysis and the keyword analysis as strategies to extract terms for the compilation of the dictionary of isiZulu linguistic terms. The study uses the isiZulu. National Corpus (INC) of about 1,2 million tokens as a reference corpus as well as an LSP corpus of about 100,000 tokens as a ...