Aggregated Residential Load Modeling Using Dynamic Bayesian Networks
Energy Technology Data Exchange (ETDEWEB)
Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai
2014-09-28
Abstract—It is already obvious that the future power grid will have to address higher demand for power and energy, and to incorporate renewable resources of different energy generation patterns. Demand response (DR) schemes could successfully be used to manage and balance power supply and demand under operating conditions of the future power grid. To achieve that, more advanced tools for DR management of operations and planning are necessary that can estimate the available capacity from DR resources. In this research, a Dynamic Bayesian Network (DBN) is derived, trained, and tested that can model aggregated load of Heating, Ventilation, and Air Conditioning (HVAC) systems. DBNs can provide flexible and powerful tools for both operations and planing, due to their unique analytical capabilities. The DBN model accuracy and flexibility of use is demonstrated by testing the model under different operational scenarios.
Dynamic queuing transmission model for dynamic network loading
DEFF Research Database (Denmark)
Raovic, Nevena; Nielsen, Otto Anker; Prato, Carlo Giacomo
2017-01-01
and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared...
Directory of Open Access Journals (Sweden)
K. Mohaideen Pitchai
2017-07-01
Full Text Available Wireless Sensor Network (WSN consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP. In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network.
Insensitive versus efficient dynamic load balancing in networks without blocking
Jonckheere, M.
2006-01-01
So-called Whittle networks have recently been shown to give tight approximations for the performance of non-locally balanced networks with blocking, including practical routing policies such as joining the shortest queue. In the present paper, we turn the attention to networks without blocking. To
Directory of Open Access Journals (Sweden)
Ridho Bayuaji
2018-04-01
Full Text Available No-fines lightweight concrete wall with horizontal reinforcement refers to an alternative material for wall construction with an aim of improving the wall quality towards horizontal loads. This study is focused on artificial neural network (ANN application to predicting the deflection deformation caused by dynamic loads. The ANN method is able to capture the complex interactions among input/output variables in a system without any knowledge of interaction nature and without any explicit assumption to model form. This paper explains the existing data research, data selection and process of ANN modelling training process and validation. The results of this research show that the deformation can be predicted more accurately, simply and quickly due to the alternating horizontal loads.
Directory of Open Access Journals (Sweden)
Muthukkumar R.
2017-04-01
Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.
Directory of Open Access Journals (Sweden)
Muthukkumar R.
2016-07-01
Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.
International Nuclear Information System (INIS)
Gherbi, Chirihane; Aliouat, Zibouda; Benmohammed, Mohamed
2016-01-01
Clustering is a well known approach to cope with large nodes density and efficiently conserving energy in Wireless Sensor Networks (WSN). Load balancing is an effective approach for optimizing resources like channel bandwidth, the main objective of this paper is to combine these two valuable approaches in order to significantly improve the main WSN service such as information routing. So, our proposal is a routing protocol in which load traffic is shared among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. To this end, a novel hierarchical approach, called Hierarchical Energy-Balancing Multipath routing protocol for Wireless Sensor Networks (HEBM) is proposed. The HEBM approach aims to fulfill the following purposes: decreasing the overall network energy consumption, balancing the energy dissipation among the sensor nodes and as direct consequence: extending the lifetime of the network. In fact, the cluster-heads are optimally determined and suitably distributed over the area of interest allowing the member nodes reaching them with adequate energy dissipation and appropriate load balancing utilization. In addition, nodes radio are turned off for fixed time duration according to sleeping control rules optimizing so their energy consumption. The performance evaluation of the proposed protocol is carried out through the well-known NS2 simulator and the exhibited results are convincing. Like this, the residual energy of sensor nodes was measured every 20 s throughout the duration of simulation, in order to calculate the total number of alive nodes. Based on the simulation results, we concluded that our proposed HEBM protocol increases the profit of energy, and prolongs the network lifetime duration from 32% to 40% compared to DEEAC reference protocol and from 25% to 28% compared to FEMCHRP protocol. The authors also note that the proposed protocol is 41.7% better than DEEAC with respect to FND (Fist node die), and 25
Directory of Open Access Journals (Sweden)
Loktev Aleksey Alekseevich
2013-01-01
Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.
Dynamic Load Balancing with Handover in Hybrid Li-Fi and Wi-Fi Networks
Haas, Harald; Wang, Yunlu
2015-01-01
In this paper, a hybrid network combining lightfidelity (Li-Fi) with a radio frequency (RF) wireless fidelity(Wi-Fi) network is considered. An additional tier of very smallLi-Fi attocells which utilise the visible light spectrum offers asignificant increase in wireless data throughput in an indoorenvironment while at the same time providing room illumination.Importantly, there is no interference between Li-Fi and Wi-Fi.A Li-Fi attocell covers a significantly smaller area than a Wi-Fi access p...
Directory of Open Access Journals (Sweden)
Ali Ghorbani
2017-01-01
Full Text Available Coupled Piled Raft Foundations (CPRFs are broadly applied to share heavy loads of superstructures between piles and rafts and reduce total and differential settlements. Settlements induced by static/coupled static-dynamic loads are one of the main concerns of engineers in designing CPRFs. Evaluation of induced settlements of CPRFs has been commonly carried out using three-dimensional finite element/finite difference modeling or through expensive real-scale/prototype model tests. Since the analyses, especially in the case of coupled static-dynamic loads, are not simply conducted, this paper presents two practical methods to gain the values of settlement. First, different nonlinear finite difference models under different static and coupled static-dynamic loads are developed to calculate exerted settlements. Analyses are performed with respect to different axial loads and pile’s configurations, numbers, lengths, diameters, and spacing for both loading cases. Based on the results of well-validated three-dimensional finite difference modeling, artificial neural networks and evolutionary polynomial regressions are then applied and introduced as capable methods to accurately present both static and coupled static-dynamic settlements. Also, using a sensitivity analysis based on Cosine Amplitude Method, axial load is introduced as the most influential parameter, while the ratio l/d is reported as the least effective parameter on the settlements of CPRFs.
Dynamic stability under sudden loads
International Nuclear Information System (INIS)
Simitses, G.J.
1998-01-01
The concept of dynamic stability of elastic structures subjected to sudden (step) loads is discussed. The various criteria and related methodologies for estimating critical conditions are presented with the emphasis on their similarities and differences. These are demonstrated by employing a simple mechanical model. Several structural configurations are analyzed, for demonstration purposes, with the intention of comparing critical dynamic loads to critical static loads. These configurations include shallow arches and shallow spherical caps, two bar frames, and imperfect cylindrical shells of metallic as well as laminated composite construction. In the demonstration examples, the effect of static pre loading on the dynamic critical load is presented
Xu, Zhanqi; Huang, Jiangjiang; Zhou, Zhiqiang; Ding, Zhe; Ma, Tao; Wang, Junping
2013-10-01
To maximize the resource utilization of optical networks, the dynamic traffic grooming, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. However, the link weights in the existing research works can be improved since they do not adapt to the network status and load well. By exploiting the information on the holding times of the preexisting and new lightpaths, and the requested bandwidth of a user service, this paper proposes a grooming algorithm using Adaptively Weighted Links for Holding-Time-Aware (HTA) (abbreviated as AWL-HTA) traffic, especially in the setup process of new lightpath(s). Therefore, the proposed algorithm can not only establish a lightpath that uses network resource efficiently, but also achieve load balancing. In this paper, the key issues on the link weight assignment and procedure within the AWL-HTA are addressed in detail. Comprehensive simulation and experimental results show that the proposed algorithm has a much lower blocking ratio and latency than other existing algorithms.
International Nuclear Information System (INIS)
Angrisani, Giovanni; Canelli, Michele; Rosato, Antonio; Roselli, Carlo; Sasso, Maurizio; Sibilio, Sergio
2014-01-01
, even in Mediterranean areas, where the climatic conditions are not always suitable for cogeneration. - Highlights: • Load sharing approach between house and office is proposed. • A system consisting of MCHP, heat storage, boiler and thermal network is simulated. • Two different geographical locations in Italy are considered. • An optimal thermo-economic control of MCHP system is implemented. • The energy, environmental and economic implication of the system are investigated
GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE
Directory of Open Access Journals (Sweden)
Ashish Jain
2012-07-01
Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.
Dynamical load factor of impact loaded shell structures
International Nuclear Information System (INIS)
Hammel, J.
1977-01-01
Dynamical loaded structures can be analysed by spectral representations, which usually lead to an enormous computational effort. If it is possible to find a fitting dynamical load factor, the dynamical problem can be reduced to a statical one. The computation of this statical problem is much simpler. The disadvantage is that the dynamical load factor usually leads to a very rough approximation. In this paper it will be shown, that by combination of these two methods, the approximation of the dynamical load factor can be improved and the consumption of computation time can be enormously reduced. (Auth.)
Load balancing in integrated optical wireless networks
DEFF Research Database (Denmark)
Yan, Ying; Dittmann, Lars; Wong, S-W.
2010-01-01
In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....
Local Dynamic Stability Associated with Load Carrying
Directory of Open Access Journals (Sweden)
Jian Liu
2013-03-01
Conclusion: Current study confirmed the sensitivity of local dynamic stability measure in load carrying situation. It was concluded that load carrying tasks were associated with declined local dynamic stability, which may result in increased risk of fall accident. This finding has implications in preventing fall accidents associated with occupational load carrying.
Scaling of load in communications networks.
Narayan, Onuttom; Saniee, Iraj
2010-09-01
We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k)∼k{-γ} , we show that the load is l(k)∼k{η} with η=γ-1 , implying that the probability distribution for the load is p(l)∼1/l{2} independent of γ . The results are obtained through scaling arguments supported by finite size scaling studies. They contradict earlier claims, but are in agreement with the exact solution for the special case of tree graphs. Results are also presented for real communications networks at the IP layer, using the latest available data. Our analysis of the data shows relatively poor power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes the importance of the load in network analysis.
Dynamic loading of galvanized parts
Directory of Open Access Journals (Sweden)
Michal Černý
2010-01-01
Full Text Available This work is divided into two parts: the theoretical part includes actual knowledge and points of view about degradation processes in construction materials, anticorrosion protection, zinc coat composition and high frequency fatigue. The laboratory part follow-up existing regulations contents Czech standards and formulate specifications for acquisition of objective information from acceleration laboratory tests in condensation chests, mechanical high frequency fatigue tests on pulsator machine and possibilities of evaluation of fatigue tests. Laboratory findings declare to fundamental types of damage of constructions with anticorrosion protection in real loading conditions with dynamic high frequency character. Laboratory tests were made in sulphide and chloride environments.
Neural Network Algorithm for Particle Loading
International Nuclear Information System (INIS)
Lewandowski, J.L.V.
2003-01-01
An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given
Directory of Open Access Journals (Sweden)
Tsirakis Christos
2017-01-01
Full Text Available The expected huge increase of mobile devices and user data demand by 2020 will stress the current mobile network in an unprecedented way. The future mobile networks must meet several strong requirements regarding the data rate, latency, quality of service and experience, mobility, spectrum and energy efficiency. Therefore, efforts for more efficient mobile network solutions have been recently initiated. To this direction, load balancing has attracted much attention as a promising solution for higher resource utilization, improved system performance and decreased operational cost. It is an effective method for balancing the traffic and alleviating the congestion among heterogeneous networks in the upcoming 5G networks. In this paper, we focus on an offloading scenario for load balancing among LTE and Wi-Fi networks. Additionally, network graphs methodology and its abstracted parameters are investigated in order to better manage wireless resource allocation among multiple connections. The COHERENT architectural framework, which consists of two main control components, makes use of such abstracted network graphs for controlling or managing various tasks such as traffic steering, load balancing, spectrum sharing and RAN sharing. As a result, the COHERENT project eventually develops a unified programmable control framework used to efficiently coordinate the underlying heterogeneous mobile networks as a whole.
Quantum load balancing in ad hoc networks
Hasanpour, M.; Shariat, S.; Barnaghi, P.; Hoseinitabatabaei, S. A.; Vahid, S.; Tafazolli, R.
2017-06-01
This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.
Neural Network Based Load Frequency Control for Restructuring ...
African Journals Online (AJOL)
Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.
Behavior of Brittle Materials Under Dynamic Loading
National Research Council Canada - National Science Library
Kanel, G
2000-01-01
Dynamic loading of brittle materials is related to many applications, including explosive excavation of rocks, design of ceramic armor, meteor impact on spacecraft windows, particle damage to turbine blades, etc...
Information Dynamics as Foundation for Network Management
2014-12-04
developed to adapt to channel dynamics in a mobile network environment. We devise a low- complexity online scheduling algorithm integrated with the...has been accepted for the Journal on Network and Systems Management in 2014. - RINC programmable platform for Infrastructure -as-a-Service public... backend servers. Rather than implementing load balancing in dedicated appliances, commodity SDN switches can perform this function. We design
CDMA coverage under mobile heterogeneous network load
Saban, D.; van den Berg, Hans Leo; Boucherie, Richardus J.; Endrayanto, A.I.
2002-01-01
We analytically investigate coverage (determined by the uplink) under non-homogeneous and moving traffic load of third generation UMTS mobile networks. In particular, for different call assignment policies, we investigate cell breathing and the movement of the coverage gap occurring between cells
Wavelet neural network load frequency controller
International Nuclear Information System (INIS)
Hemeida, Ashraf Mohamed
2005-01-01
This paper presents the feasibility of applying a wavelet neural network (WNN) approach for the load frequency controller (LFC) to damp the frequency oscillations of two area power systems due to load disturbances. The present intelligent control system trained the wavelet neural network (WNN) controller on line with adaptive learning rates, which are derived in the sense of a discrete type Lyapunov stability theorem. The present WNN controller is designed individually for each area. The proposed technique is applied successfully for a wide range of operating conditions. The time simulation results indicate its superiority and effectiveness over the conventional approach. The effects of consideration of the governor dead zone on the system performance are studied using the proposed controller and the conventional one
Disruptions, loads, and dynamic response of ITER
International Nuclear Information System (INIS)
Nelson, B.; Riemer, B.; Sayer, R.; Strickler, D.; Barabaschi, P.; Ioki, K.; Johnson, G.; Shimizu, K.; Williamson, D.
1995-01-01
Plasma disruptions and the resulting electromagnetic loads are critical to the design of the vacuum vessel and in-vessel components of the International Thermonuclear Experimental Reactor (ITER). This paper describes the status of plasma disruption simulations and related analysis, including the dynamic response of the vacuum vessel and in-vessel components, stresses and deflections in the vacuum vessel, and reaction loads in the support structures
Studying Dynamics in Business Networks
DEFF Research Database (Denmark)
Andersen, Poul Houman; Anderson, Helen; Havila, Virpi
1998-01-01
This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...
Dynamic training algorithm for dynamic neural networks
International Nuclear Information System (INIS)
Tan, Y.; Van Cauwenberghe, A.; Liu, Z.
1996-01-01
The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper
Wavelength converter placement in optical networks with dynamic traffic
DEFF Research Database (Denmark)
Buron, Jakob Due; Ruepp, Sarah Renée; Wessing, Henrik
2008-01-01
We evaluate the connection provisioning performance of GMPLS-controlled wavelength routed networks under dynamic traffic load and using three different wavelength converter placement heuristics. Results show that a simple uniform placement heuristic matches the performance of complex heuristics...
Daily Nigerian peak load forecasting using artificial neural network ...
African Journals Online (AJOL)
A daily peak load forecasting technique that uses artificial neural network with seasonal indices is presented in this paper. A neural network of relatively smaller size than the main prediction network is used to predict the daily peak load for a period of one year over which the actual daily load data are available using one ...
Dynamic Gust Load Analysis for Rotors
Directory of Open Access Journals (Sweden)
Yuting Dai
2016-01-01
Full Text Available Dynamic load of helicopter rotors due to gust directly affects the structural stress and flight performance for helicopters. Based on a large deflection beam theory, an aeroelastic model for isolated helicopter rotors in the time domain is constructed. The dynamic response and structural load for a rotor under the impulse gust and slope-shape gust are calculated, respectively. First, a nonlinear Euler beam model with 36 degrees-of-freedoms per element is applied to depict the structural dynamics for an isolated rotor. The generalized dynamic wake model and Leishman-Beddoes dynamic stall model are applied to calculate the nonlinear unsteady aerodynamic forces on rotors. Then, we transformed the differential aeroelastic governing equation to an algebraic one. Hence, the widely used Newton-Raphson iteration algorithm is employed to simulate the dynamic gust load. An isolated helicopter rotor with four blades is studied to validate the structural model and the aeroelastic model. The modal frequencies based on the Euler beam model agree well with published ones by CAMRAD. The flap deflection due to impulse gust with the speed of 2m/s increases twice to the one without gust. In this numerical example, results indicate that the bending moment at the blade root is alleviated due to elastic effect.
Rashvand, Habib
2013-01-01
Motivated by the exciting new application paradigm of using amalgamated technologies of the Internet and wireless, the next generation communication networks (also called 'ubiquitous', 'complex' and 'unstructured' networking) are changing the way we develop and apply our future systems and services at home and on local, national and global scales. Whatever the interconnection - a WiMAX enabled networked mobile vehicle, MEMS or nanotechnology enabled distributed sensor systems, Vehicular Ad hoc Networking (VANET) or Mobile Ad hoc Networking (MANET) - all can be classified under new networking s
Shaft Center Orbit in Dynamically Loaded Bearings
DEFF Research Database (Denmark)
Klit, Peder
2005-01-01
The aim of this work is to demonstrate how to utilize the bearings damping coe±cients to estimate the orbit for a dynamically loaded journal bearing. The classical method for this analysis was developed by Booker in 1965 [1]and described further in 1972 [2]. Several authors have re¯ned this metho...
Loading dynamics of a sliding DNA clamp.
Cho, Won-Ki; Jergic, Slobodan; Kim, Daehyung; Dixon, Nicholas E; Lee, Jong-Bong
2014-01-01
8° during clamp closure. The single-molecule polarization and FRET studies thus revealed the real-time dynamics of the ATP-hydrolysis-dependent 3D conformational change of the β clamp during loading at a ss/dsDNA junction.
Material properties under intensive dynamic loading
Cherne, Frank J; Zhernokletov, Mikhail V; Glushak, B L; Zocher, Marvin A
2007-01-01
Understanding the physical and thermomechanical response of materials subjected to intensive dynamic loading is a challenge of great significance in engineering today. This volume assumes the task of gathering both experimental and diagnostic methods in one place, since not much information has been previously disseminated in the scientific literature.
Load-induced modulation of signal transduction networks.
Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla
2011-10-11
Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.
Cognitive Dynamic Optical Networks
DEFF Research Database (Denmark)
de Miguel, Ignacio; Duran, Ramon J.; Lorenzo, Ruben M.
2013-01-01
Cognitive networks are a promising solution for the control of heterogeneous optical networks. We review their fundamentals as well as a number of applications developed in the framework of the EU FP7 CHRON project.......Cognitive networks are a promising solution for the control of heterogeneous optical networks. We review their fundamentals as well as a number of applications developed in the framework of the EU FP7 CHRON project....
Periodic dynamics in queuing networks
Energy Technology Data Exchange (ETDEWEB)
Addabbo, Tommaso [Information Engineering Department, University of Siena, Via Roma 56, 53100 Siena (Italy)], E-mail: addabbo@dii.unisi.it; Kocarev, Ljupco [Macedonian Academy of Sciences and Arts, bul. Krste Misirkov 2, P.O. Box 428, 1000 Skopje, Republic of Macedonia (Macedonia, The Former Yugoslav Republic of)], E-mail: lkocarev@ucsd.edu
2009-08-30
This paper deals with state-dependent open Markovian (or exponential) queuing networks, for which arrival and service rates, as well as routing probabilities, may depend on the queue lengths. For a network of this kind, following Mandelbaum and Pats, we provide a formal definition of its associated fluid model, and we focus on the relationships which may occur between the network stochastic dynamics and the deterministic dynamics of its corresponding fluid model, particularly focusing on queuing networks whose fluid models have global periodic attractors.
Cognitive Dynamic Optical Networks
DEFF Research Database (Denmark)
de Miguel, Ignacio; Duran, Ramon J.; Jimenez, Tamara
2013-01-01
The use of cognition is a promising element for the control of heterogeneous optical networks. Not only are cognitive networks able to sense current network conditions and act according to them, but they also take into account the knowledge acquired through past experiences; that is, they include...... learning with the aim of improving performance. In this paper, we review the fundamentals of cognitive networks and focus on their application to the optical networking area. In particular, a number of cognitive network architectures proposed so far, as well as their associated supporting technologies......, are reviewed. Moreover, several applications, mainly developed in the framework of the EU FP7 Cognitive Heterogeneous Reconfigurable Optical Network (CHRON) project, are also described....
Entropy of dynamical social networks
Zhao, Kun; Karsai, Marton; Bianconi, Ginestra
2012-02-01
Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.
Nonlinear Dynamics on Interconnected Networks
Arenas, Alex; De Domenico, Manlio
2016-06-01
Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.
NIF ICCS network design and loading analysis
International Nuclear Information System (INIS)
Tietbohl, G; Bryant, R
1998-01-01
The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738)
Dynamic behaviors in directed networks
International Nuclear Information System (INIS)
Park, Sung Min; Kim, Beom Jun
2006-01-01
Motivated by the abundance of directed synaptic couplings in a real biological neuronal network, we investigate the synchronization behavior of the Hodgkin-Huxley model in a directed network. We start from the standard model of the Watts-Strogatz undirected network and then change undirected edges to directed arcs with a given probability, still preserving the connectivity of the network. A generalized clustering coefficient for directed networks is defined and used to investigate the interplay between the synchronization behavior and underlying structural properties of directed networks. We observe that the directedness of complex networks plays an important role in emerging dynamical behaviors, which is also confirmed by a numerical study of the sociological game theoretic voter model on directed networks
National Research Council Canada - National Science Library
Schott, Brian
2004-01-01
...: Declarative Languages and Execution Environment includes topographical soldier interface and a sensor network simulation environment for algorithm development, deployment planning, and operational support. Finally, Task 3...
Dynamic and interacting complex networks
Dickison, Mark E.
This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible
Complex networks: Dynamics and security
Indian Academy of Sciences (India)
This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. ... Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona 85287, USA; Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil ...
Dynamic intelligent cleaning model of dirty electric load data
International Nuclear Information System (INIS)
Zhang Xiaoxing; Sun Caixin
2008-01-01
There are a number of dirty data in the load database derived from the supervisory control and data acquisition (SCADA) system. Thus, the data must be carefully and reasonably adjusted before it is used for electric load forecasting or power system analysis. This paper proposes a dynamic and intelligent data cleaning model based on data mining theory. Firstly, on the basis of fuzzy soft clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means soft clustering. Then, the proposed dynamic algorithm can automatically find the new clustering center (the characteristic curve of the data) with the updated sample data; At last, it is composed with radial basis function neural network (RBFNN), and then, an intelligent adjusting model is proposed to identify the dirty data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results of electrical load data analysis in Chongqing
Dynamic loads on the primary system
International Nuclear Information System (INIS)
Rohde, J.
1980-01-01
As a result of pipe breaks f.ex. in the primary system of a PWR-plant dynamic forces act on the components of the system as well as on their support-structures and internals. The design basis must guarantee that LOCA or system-transient generated loads cannot produce deformations or fractures that endanger the coolability of the reactor, the emergency feedwater supply to the core-region and a safe shut-down of the reactor. In this lecture the first part of a LOCA will be discussed, where the highest dynamic loads on the primary system are expected. In this connection comments are given on the main assumptions and boundary conditions, the related regulations and guide-lines, as well as the possible consequences of an accident. Next, a review is presented of the analytical methods being used for the determination of thermohydraulic generated loads. The stress-calculations on the basis of these load-functions are discussed in the following lectures. The application of the analytical methods, i.e. the different computer codes, and the verification on the basis of the experimental results are described together with a discussion of the theoretical results. In addition a survey will be given of the research work done in connection with the problems of the dynamic loads under accident conditions. Finally, the problems of the fluid-structure interaction will be explained and comments made on computer code development now under way regarding this problem. A short film will be presented to provide a better understanding of fast transient phenomena. (orig./RW)
Dynamic capabilities and network benefits
Directory of Open Access Journals (Sweden)
Helge Svare
2017-01-01
Full Text Available The number of publicly funded initiatives to establish or strengthen networks and clusters, in order to enhance innovation, has been increasing. Returns on such investments vary, and the aim of this study is to explore to what extent the variation in benefits for firms participating in networks or clusters can be explained by their dynamic capabilities (DC. Based on survey data from five Norwegian networks, the results suggest that firms with higher DC are more successful in harvesting the potential benefits of being member of a network.
Peak load-impulse characterization of critical pulse loads in structural dynamics
International Nuclear Information System (INIS)
Abrahamson, G.R.; Lindberg, H.E.
1975-01-01
In presenting the characterization scheme, some general features are described first. A detailed analysis is given for the rigid-plastic system of one degree of freedom to illustrate the calculation of critical load curves in terms of peak load and impulse. This is followed by the presentation of critical load curves for uniformly loaded rigid-plastic beams and plates and for dynamic buckling of cylindrical shells under uniform lateral loads. The peak load-impulse characterization of critical pulse loads is compared with the dynamic load factor characterization, and some aspects of the history of the peak load-pulse scheme are presented. (orig./HP) [de
Analysis of pile foundations under dynamic loads
International Nuclear Information System (INIS)
Waas, G.; Hartmann, H.G.
1981-01-01
A method is presented for the analysis of pile foundations which are subjected to horizontal dynamic loads from earthquakes, airplane impact, gas explosion or other sources. The motion of the pile cap and the pile forces are computed. - The loads may be applied to the pile cap or directly to the piles (e.g. by earthquake wave motion). The soil may be stratified and is considered to be an elastic or visco-elastic medium. The piles are assumed vertical. The method makes use of an approximate fundamental solution for displacements caused by a dynamic point load in a layered visco-elastic medium. The approximation involves a discretization of the medium in the vertical direction. In horizontal directions the medium is treated by continuum theory. The soil medium supports each pile at about 10 to 20 nodes. A dynamic flexiblity matrix for the soil is derived which relates the elastic, damping and inertial forces of the soil to the displacements at each node. It includes effects of radiation damping. All piles are coupled through the soil flexibility matrix. The piles are modelled by beam elements. Transient response is computed using fast discrete Fourier transforms. The arrangement of the piles is arbitrary. However, simple and double symmetry can be accounted for by the computer program. When the pile arrangement is axisymmetric, the degrees of freedom can be reduced to only those of two piles per ring. The influence of the number of piles and the influence of the pile spacing on group stiffness and on pile forces is presented for two soil profiles. Dynamic effects on pile forces of a foundation for a reactor building are studied. They are significant when soils are soft. (orig.)
Decoding network dynamics in cancer
DEFF Research Database (Denmark)
Linding, Rune
2014-01-01
Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...
Dynamic load effects on gate valve operability
International Nuclear Information System (INIS)
Steele, R. Jr.; MacDonald, P.E.; Arendts, J.G.
1986-01-01
The Idaho National Engineering Laboratory (INEL) participated in an internationally sponsored seismic research program conducted at the decommissioned Heissdampfreaktor (HDR) located in the Federal Republic of Germany. An existing piping system was modified by installation of an 8-in., naturally aged, motor-operated gate valve from a US nuclear power plant and a piping support system of US design. Six other piping support systems of varying flexibility from stiff to flexible were also installed at various times during the tests. Additional valve loadings included internal hydraulic loads and, during one block of tests, elevated temperature. The operability and integrity of the aged gate valve and the dynamic response of the various piping support system were measured during 25 representative seismic events
Dynamics of associating networks
Tang, Shengchang; Habicht, Axel; Wang, Muzhou; Li, Shuaili; Seiffert, Sebastian; Olsen, Bradley
Associating polymers offer important technological solutions to renewable and self-healing materials, conducting electrolytes for energy storage and transport, and vehicles for cell and protein deliveries. The interplay between polymer topologies and association chemistries warrants new interesting physics from associating networks, yet poses significant challenges to study these systems over a wide range of time and length scales. In a series of studies, we explored self-diffusion mechanisms of associating polymers above the percolation threshold, by combining experimental measurements using forced Rayleigh scattering and analytical insights from a two-state model. Despite the differences in molecular structures, a universal super-diffusion phenomenon is observed when diffusion of molecular species is hindered by dissociation kinetics. The molecular dissociation rate can be used to renormalize shear rheology data, which yields an unprecedented time-temperature-concentration superposition. The obtained shear rheology master curves provide experimental evidence of the relaxation hierarchy in associating networks.
An Initial Load-Based Green Software Defined Network
Directory of Open Access Journals (Sweden)
Ying Hu
2017-05-01
Full Text Available Software defined network (SDN is a new network architecture in which the control function is decoupled from the data forwarding plane, that is attracting wide attentions from both research and industry sectors. However, SDN still faces the energy waste problem as do traditional networks. At present, research on energy saving in SDN is mainly focused on the static optimization of the network with zero load when new traffic arrives, changing the transmission path of the uncompleted traffic which arrived before the optimization, possibly resulting in route oscillation and other deleterious effects. To avoid this, a dynamical energy saving optimization scheme in which the paths of the uncompleted flows will not be changed when new traffic arrives is designed. To find the optimal solution for energy saving, the problem is modeled as a mixed integer linear programming (MILP problem. As the high complexity of the problem prohibits the optimal solution, an improved heuristic routing algorithm called improved constant weight greedy algorithm (ICWGA is proposed to find a sub-optimal solution. Simulation results show that the energy saving capacity of ICWGA is close to that of the optimal solution, offering desirable improvement in the energy efficiency of the network.
Network Dynamics of Innovation Processes
Iacopini, Iacopo; Milojević, Staša; Latora, Vito
2018-01-01
We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.
Loading dynamics of a sliding DNA clamp.
Cho, Won-Ki
2014-05-22
Sliding DNA clamps are loaded at a ss/dsDNA junction by a clamp loader that depends on ATP binding for clamp opening. Sequential ATP hydrolysis results in closure of the clamp so that it completely encircles and diffuses on dsDNA. We followed events during loading of an E. coli β clamp in real time by using single-molecule FRET (smFRET). Three successive FRET states were retained for 0.3 s, 0.7 s, and 9 min: Hydrolysis of the first ATP molecule by the γ clamp loader resulted in closure of the clamp in 0.3 s, and after 0.7 s in the closed conformation, the clamp was released to diffuse on the dsDNA for at least 9 min. An additional single-molecule polarization study revealed that the interfacial domain of the clamp rotated in plane by approximately 8° during clamp closure. The single-molecule polarization and FRET studies thus revealed the real-time dynamics of the ATP-hydrolysis-dependent 3D conformational change of the β clamp during loading at a ss/dsDNA junction.
Artificial Neural Networks for SCADA Data based Load Reconstruction (poster)
Hofemann, C.; Van Bussel, G.J.W.; Veldkamp, H.
2011-01-01
If at least one reference wind turbine is available, which provides sufficient information about the wind turbine loads, the loads acting on the neighbouring wind turbines can be predicted via an artificial neural network (ANN). This research explores the possibilities to apply such a network not
Solving Dynamic Battlespace Movement Problems Using Dynamic Distributed Computer Networks
National Research Council Canada - National Science Library
Bradford, Robert
2000-01-01
.... The thesis designs a system using this architecture that invokes operations research network optimization algorithms to solve problems involving movement of people and equipment over dynamic road networks...
Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration
Energy Technology Data Exchange (ETDEWEB)
Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-08-23
In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.
Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint
Energy Technology Data Exchange (ETDEWEB)
Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-07-26
In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.
Competitive Dynamics on Complex Networks
Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan
2014-07-01
We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.
Antagonistic Phenomena in Network Dynamics
Motter, Adilson E.; Timme, Marc
2018-03-01
Recent research on the network modeling of complex systems has led to a convenient representation of numerous natural, social, and engineered systems that are now recognized as networks of interacting parts. Such systems can exhibit a wealth of phenomena that not only cannot be anticipated from merely examining their parts, as per the textbook definition of complexity, but also challenge intuition even when considered in the context of what is now known in network science. Here, we review the recent literature on two major classes of such phenomena that have far-reaching implications: (a) antagonistic responses to changes of states or parameters and (b) coexistence of seemingly incongruous behaviors or properties - both deriving from the collective and inherently decentralized nature of the dynamics. They include effects as diverse as negative compressibility in engineered materials, rescue interactions in biological networks, negative resistance in fluid networks, and the Braess paradox occurring across transport and supply networks. They also include remote synchronization, chimera states, and the converse of symmetry breaking in brain, power-grid, and oscillator networks as well as remote control in biological and bioinspired systems. By offering a unified view of these various scenarios, we suggest that they are representative of a yet broader class of unprecedented network phenomena that ought to be revealed and explained by future research.
Load-redistribution strategy based on time-varying load against cascading failure of complex network
International Nuclear Information System (INIS)
Liu Jun; Shi Xin; Wang Kai; Shi Wei-Ren; Xiong Qing-Yu
2015-01-01
Cascading failure can cause great damage to complex networks, so it is of great significance to improve the network robustness against cascading failure. Many previous existing works on load-redistribution strategies require global information, which is not suitable for large scale networks, and some strategies based on local information assume that the load of a node is always its initial load before the network is attacked, and the load of the failure node is redistributed to its neighbors according to their initial load or initial residual capacity. This paper proposes a new load-redistribution strategy based on local information considering an ever-changing load. It redistributes the loads of the failure node to its nearest neighbors according to their current residual capacity, which makes full use of the residual capacity of the network. Experiments are conducted on two typical networks and two real networks, and the experimental results show that the new load-redistribution strategy can reduce the size of cascading failure efficiently. (paper)
Load management in electrical networks. Objectives, methods, prospects
International Nuclear Information System (INIS)
Gabioud, D.
2008-01-01
This illustrated article takes up the problems related to the variation of the load in electricity networks. How to handle the peak load? Different solutions in the energy demand management are discussed. Method based on the price, method based on the reduction of the load by electric utilities. Information systems are presented which gives the consumer the needed data to participate in the local load management.
Failure cascade in interdependent network with traffic loads
International Nuclear Information System (INIS)
Hong, Sheng; Wang, Baoqing; Wang, Jianghui; Zhao, Tingdi; Ma, Xiaomin
2015-01-01
Complex networks have been widely studied recent years, but most researches focus on the single, non-interacting networks. With the development of modern systems, many infrastructure networks are coupled together and therefore should be modeled as interdependent networks. For interdependent networks, failure of nodes in one network may lead to failure of dependent nodes in the other networks. This may happen recursively and lead to a failure cascade. In the real world, different networks carry different traffic loads. Overload and load redistribution may lead to more nodes’ failure. Considering the dependency between the interdependent networks and the traffic load, a small fraction of fault nodes may lead to complete fragmentation of a system. Based on the robust analysis of interdependent networks, we propose a costless defense strategy to suppress the failure cascade. Our findings highlight the need to consider the load and coupling preference when designing robust interdependent networks. And it is necessary to take actions in the early stage of the failure cascade to decrease the losses caused by the large-scale breakdown of infrastructure networks. (paper)
Asynchronous networks: modularization of dynamics theorem
Bick, Christian; Field, Michael
2017-02-01
Building on the first part of this paper, we develop the theory of functional asynchronous networks. We show that a large class of functional asynchronous networks can be (uniquely) represented as feedforward networks connecting events or dynamical modules. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network: the modularization of dynamics theorem. We give examples to illustrate the main results.
Software defined networks reactive flow programming and load balance switching
Καλλιανιώτης, Νικόλαος; Kallianiotis, Nikolaos
2017-01-01
This project serves as a Master Thesis as the requirements of the master’s programme Master of Digital Communications and Networks. It proposes load balancing algorithms applied to Software-Defined Networks to achieve the best possible resource utilisation of each of the links present in a network. The open-sources Opendaylight project and Floodlight project are used as SDN controllers, and the network is emulated using Mininet software
Anomaly Detection in Dynamic Networks
Energy Technology Data Exchange (ETDEWEB)
Turcotte, Melissa [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-10-14
Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. A second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the
Dynamic Relaying in 3GPP LTE-Advanced Networks
Directory of Open Access Journals (Sweden)
Van Phan Vinh
2009-01-01
Full Text Available Relaying is one of the proposed technologies for LTE-Advanced networks. In order to enable a flexible and reliable relaying support, the currently adopted architectural structure of LTE networks has to be modified. In this paper, we extend the LTE architecture to enable dynamic relaying, while maintaining backward compatibility with LTE Release 8 user equipments, and without limiting the flexibility and reliability expected from relaying. With dynamic relaying, relays can be associated with base stations on a need basis rather than in a fixed manner which is based only on initial radio planning. Proposals are also given on how to further improve a relay enhanced LTE network by enabling multiple interfaces between the relay nodes and their controlling base stations, which can possibly be based on technologies different from LTE, so that load balancing can be realized. This load balancing can be either between different base stations or even between different networks.
A network dynamics approach to chemical reaction networks
van der Schaft, Abraham; Rao, S.; Jayawardhana, B.
2016-01-01
A treatment of chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a
Response of Rubble Foundation to Dynamic Loading
DEFF Research Database (Denmark)
Burcharth, H. F.; Ibsen, Lars Bo
1993-01-01
The soil beneath vertical monolithic structures is subjected to a combination of static load due to the submerged weight of the structure and stochastic non-stationary loads as a result of the wave loads on the vertical wall. The stress conditions in the soil below a foundation exposed to both...
Response of Rubble Foundation to Dynamic Loading
DEFF Research Database (Denmark)
Burcharth, H. F.; Ibsen, Lars Bo
1994-01-01
The soil beneath vertical monolithic structures is subjected to a combination of static load due to the submerged weight of the structure and stochastic non-stationary loads as a result of the wave loads on the vertical wall. The stress conditions in the soil below a foundation exposed to both...
An efficient dynamic load balancing algorithm
Lagaros, Nikos D.
2014-01-01
In engineering problems, randomness and uncertainties are inherent. Robust design procedures, formulated in the framework of multi-objective optimization, have been proposed in order to take into account sources of randomness and uncertainty. These design procedures require orders of magnitude more computational effort than conventional analysis or optimum design processes since a very large number of finite element analyses is required to be dealt. It is therefore an imperative need to exploit the capabilities of computing resources in order to deal with this kind of problems. In particular, parallel computing can be implemented at the level of metaheuristic optimization, by exploiting the physical parallelization feature of the nondominated sorting evolution strategies method, as well as at the level of repeated structural analyses required for assessing the behavioural constraints and for calculating the objective functions. In this study an efficient dynamic load balancing algorithm for optimum exploitation of available computing resources is proposed and, without loss of generality, is applied for computing the desired Pareto front. In such problems the computation of the complete Pareto front with feasible designs only, constitutes a very challenging task. The proposed algorithm achieves linear speedup factors and almost 100% speedup factor values with reference to the sequential procedure.
Dynamic state estimation for distribution networks with renewable energy integration
Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.
2013-01-01
The massive integration of variable and unpredictable Renewable Energy Sources (RES) and new types of load consumptions increases the dynamic and uncertain nature of the electricity grid. Emerging interests have focused on improving the monitoring capabilities of network operators so that they can
Adaptive dynamic capacity borrowing in road-covering mobile networks
Ule, A.; Boucherie, Richardus J.; Li, W.; Pan, Y.
2006-01-01
This paper introduces adaptive dynamic capacity borrowing strategies for wireless networks covering a road. In a F/TDMA-based model, road traffic prediction models are used to characterise the movement of hot spots, such as traffic jams, and subsequently to predict the teletraffic load offered to
Insensitivity of proportional fairness in critically loaded bandwidth sharing networks
Vlasiou, M.; Zhang, J.; Zwart, B.
2014-01-01
Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product form distribution under critical loading. Assuming
Short term load forecasting using neuro-fuzzy networks
Energy Technology Data Exchange (ETDEWEB)
Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)
2005-07-01
Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.
International Nuclear Information System (INIS)
Lee, Hyun Ah; Kim, Yong Il; Park, Gyung Jin; Kang, Byung Soo; Kim, Joo Sung
2006-01-01
All the loads in the real world are dynamic loads and structural optimization under dynamic loads is very difficult. Thus the dynamic loads are often transformed to static loads by dynamic factors, which are believed equivalent to the dynamic loads. However, due to the difference of load characteristics, there can be considerable differences between the results from static and dynamic analyses. When the natural frequency of a structure is high, the dynamic analysis result is similar to that of static analysis due to the small inertia effect on the behavior of the structure. However, if the natural frequency of the structure is low, the inertia effect should not be ignored. then, the behavior of the dynamic system is different from that of the static system. The difference of the two cases can be explained from the relationship between the homogeneous and the particular solutions of the differential equation that governs the behavior of the structure. Through various examples, the difference between the dynamic analysis and the static analysis are shown. Also dynamic response optimization results are compared with the results with static loads transformed from dynamic loads by dynamic factors, which show the necessity of the design considering dynamic loads
Tourism-planning network knowledge dynamics
DEFF Research Database (Denmark)
Dredge, Dianne
2014-01-01
This chapter explores the characteristics and functions of tourism networks as a first step in understanding how networks facilitate and reproduce knowledge. A framework to progress understandings of knowledge dynamics in tourism networks is presented that includes four key dimensions: context......, network agents, network boundaries and network resources. A case study of the development of the Next Generation Tourism Handbook (Queensland, Australia), a policy initiative that sought to bring tourism and land use planning knowledge closer together is presented. The case study illustrates...... that the tourism policy and land use planning networks operate in very different spheres and that context, network agents, network boundaries and network resources have a significant influence not only on knowledge dynamics but also on the capacity of network agents to overcome barriers to learning and to innovate....
Traffic Dynamics on Complex Networks: A Survey
Directory of Open Access Journals (Sweden)
Shengyong Chen
2012-01-01
Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.
Two Stage Secure Dynamic Load Balancing Architecture for SIP Server Clusters
Directory of Open Access Journals (Sweden)
G. Vennila
2014-08-01
Full Text Available Session Initiation Protocol (SIP is a signaling protocol emerged with an aim to enhance the IP network capabilities in terms of complex service provision. SIP server scalability with load balancing has a greater concern due to the dramatic increase in SIP service demand. Load balancing of session method (request/response and security measures optimizes the SIP server to regulate of network traffic in Voice over Internet Protocol (VoIP. Establishing a honeywall prior to the load balancer significantly reduces SIP traffic and drops inbound malicious load. In this paper, we propose Active Least Call in SIP Server (ALC_Server algorithm fulfills objectives like congestion avoidance, improved response times, throughput, resource utilization, reducing server faults, scalability and protection of SIP call from DoS attacks. From the test bed, the proposed two-tier architecture demonstrates that the ALC_Server method dynamically controls the overload and provides robust security, uniform load distribution for SIP servers.
A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics
Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan
2015-01-01
Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859
Peak loads and network investments in sustainable energy transitions
Energy Technology Data Exchange (ETDEWEB)
Blokhuis, Erik, E-mail: e.g.j.blokhuis@tue.nl [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Brouwers, Bart [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Putten, Eric van der [Endinet, Gas and Electricity Network Operations, P.O. Box 2005, 5600CA Eindhoven (Netherlands); Schaefer, Wim [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands)
2011-10-15
Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: > Sustainable energy transitions can result in major electricity peak load increases. > Introduction of heat pumps and electrical vehicles requires network expansion. > Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. > The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. > Future policy choices should be made from the viewpoint of the integral energy system.
Peak loads and network investments in sustainable energy transitions
International Nuclear Information System (INIS)
Blokhuis, Erik; Brouwers, Bart; Putten, Eric van der; Schaefer, Wim
2011-01-01
Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: → Sustainable energy transitions can result in major electricity peak load increases. → Introduction of heat pumps and electrical vehicles requires network expansion. → Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. → The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. → Future policy choices should be made from the viewpoint of the integral energy system.
Dynamic Load Balancing of Parallel Monte Carlo Transport Calculations
International Nuclear Information System (INIS)
O'Brien, M; Taylor, J; Procassini, R
2004-01-01
The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since the particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations
Software defined network architecture based research on load balancing strategy
You, Xiaoqian; Wu, Yang
2018-05-01
As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.
Dynamic Relaying in 3GPP LTE-Advanced Networks
DEFF Research Database (Denmark)
Teyeb, Oumer Mohammed; Van Phan, Vinh; Redana, Simone
2009-01-01
Relaying is one of the proposed technologies for LTE-Advanced networks. In order to enable a flexible and reliable relaying support, the currently adopted architectural structure of LTE networks has to be modified. In this paper, we extend the LTE architecture to enable dynamic relaying, while...... maintaining backward compatibility with LTE Release 8 user equipments, and without limiting the flexibility and reliability expected from relaying.With dynamic relaying, relays can be associated with base stations on a need basis rather than in a fixed manner which is based only on initial radio planning....... Proposals are also given on how to further improve a relay enhanced LTE network by enabling multiple interfaces between the relay nodes and their controlling base stations, which can possibly be based on technologies different from LTE, so that load balancing can be realized. This load balancing can...
Overload cascading failure on complex networks with heterogeneous load redistribution
Hou, Yueyi; Xing, Xiaoyun; Li, Menghui; Zeng, An; Wang, Yougui
2017-09-01
Many real systems including the Internet, power-grid and financial networks experience rare but large overload cascading failures triggered by small initial shocks. Many models on complex networks have been developed to investigate this phenomenon. Most of these models are based on the load redistribution process and assume that the load on a failed node shifts to nearby nodes in the networks either evenly or according to the load distribution rule before the cascade. Inspired by the fact that real power-grid tends to place the excess load on the nodes with high remaining capacities, we study a heterogeneous load redistribution mechanism in a simplified sandpile model in this paper. We find that weak heterogeneity in load redistribution can effectively mitigate the cascade while strong heterogeneity in load redistribution may even enlarge the size of the final failure. With a parameter θ to control the degree of the redistribution heterogeneity, we identify a rather robust optimal θ∗ = 1. Finally, we find that θ∗ tends to shift to a larger value if the initial sand distribution is homogeneous.
Airborne Network Optimization with Dynamic Network Update
2015-03-26
source si and a target ti . For each commodity (si, ki) the commodity specifies a non- negative demand di [5]. The objective of the multi-commodity...queue predictions, and network con- gestion [15]. The implementation of the DRQC uses the Kalman filter to predict the state of the network and optimize
Impact of Electric Vehicle Charging Station Load on Distribution Network
Directory of Open Access Journals (Sweden)
Sanchari Deb
2018-01-01
Full Text Available Recent concerns about environmental pollution and escalating energy consumption accompanied by the advancements in battery technology have initiated the electrification of the transportation sector. With the universal resurgence of Electric Vehicles (EVs the adverse impact of the EV charging loads on the operating parameters of the power system has been noticed. The detrimental impact of EV charging station loads on the electricity distribution network cannot be neglected. The high charging loads of the fast charging stations results in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. Further, the penalty paid by the utility for the degrading performance of the power system cannot be neglected. This work aims to investigate the impact of the EV charging station loads on the voltage stability, power losses, reliability indices, as well as economic losses of the distribution network. The entire analysis is performed on the IEEE 33 bus test system representing a standard radial distribution network for six different cases of EV charging station placement. It is observed that the system can withstand placement of fast charging stations at the strong buses up to a certain level, but the placement of fast charging stations at the weak buses of the system hampers the smooth operation of the power system. Further, a strategy for the placement of the EV charging stations on the distribution network is proposed based on a novel Voltage stability, Reliability, and Power loss (VRP index. The results obtained indicate the efficacy of the VRP index.
Dynamical Model of Rocket Propellant Loading with Liquid Hydrogen
National Aeronautics and Space Administration — A dynamical model describing the multi-stage process of rocket propellant loading has been developed. It accounts for both the nominal and faulty regimes of...
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
Temporal fidelity in dynamic social networks
DEFF Research Database (Denmark)
Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’
2015-01-01
of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution...
Revealing networks from dynamics: an introduction
International Nuclear Information System (INIS)
Timme, Marc; Casadiego, Jose
2014-01-01
What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity. (topical review)
Features wear nodes mechanization wing aircraft operating under dynamic loads
Directory of Open Access Journals (Sweden)
А.М. Хімко
2009-03-01
Full Text Available The conducted researches of titanic alloy ВТ-22 at dynamic loading with cycled sliding and dynamic loading in conditions of rolling with slipping. It is established that roller jamming in the carriage increases wear of rod of mechanization of a wing to twenty times. The optimum covering for strengthening wearied sites and restoration of working surfaces of wing’s mechanization rod is defined.
Local Dynamics in Trained Recurrent Neural Networks.
Rivkind, Alexander; Barak, Omri
2017-06-23
Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.
Local Dynamics in Trained Recurrent Neural Networks
Rivkind, Alexander; Barak, Omri
2017-06-01
Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.
Wang, Yaping; Lin, Shunjiang; Yang, Zhibin
2017-05-01
In the traditional three-phase power flow calculation of the low voltage distribution network, the load model is described as constant power. Since this model cannot reflect the characteristics of actual loads, the result of the traditional calculation is always different from the actual situation. In this paper, the load model in which dynamic load represented by air conditioners parallel with static load represented by lighting loads is used to describe characteristics of residents load, and the three-phase power flow calculation model is proposed. The power flow calculation model includes the power balance equations of three-phase (A,B,C), the current balance equations of phase 0, and the torque balancing equations of induction motors in air conditioners. And then an alternating iterative algorithm of induction motor torque balance equations with each node balance equations is proposed to solve the three-phase power flow model. This method is applied to an actual low voltage distribution network of residents load, and by the calculation of three different operating states of air conditioners, the result demonstrates the effectiveness of the proposed model and the algorithm.
Energy-Aware Routing Optimization in Dynamic GMPLS Controlled Optical Networks
DEFF Research Database (Denmark)
Wang, Jiayuan; Ricciardi, Sergio; Fagertun, Anna Manolova
2012-01-01
In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations...
Using Network Dynamical Influence to Drive Consensus
Punzo, Giuliano; Young, George F.; MacDonald, Malcolm; Leonard, Naomi E.
2016-05-01
Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.
Inferring network topology from complex dynamics
International Nuclear Information System (INIS)
Shandilya, Srinivas Gorur; Timme, Marc
2011-01-01
Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.
Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks
Directory of Open Access Journals (Sweden)
Zhisheng Zhang
2016-01-01
Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.
Dynamically-Loaded Hardware Libraries (HLL) Technology for Audio Applications
DEFF Research Database (Denmark)
Esposito, A.; Lomuscio, A.; Nunzio, L. Di
2016-01-01
In this work, we apply hardware acceleration to embedded systems running audio applications. We present a new framework, Dynamically-Loaded Hardware Libraries or HLL, to dynamically load hardware libraries on reconfigurable platforms (FPGAs). Provided a library of application-specific processors......, we load on-the-fly the specific processor in the FPGA, and we transfer the execution from the CPU to the FPGA-based accelerator. The proposed architecture provides excellent flexibility with respect to the different audio applications implemented, high quality audio, and an energy efficient solution....
Incorporating moving dynamic tyre loads in pavement design and analysis
CSIR Research Space (South Africa)
Steyn, WJvdM
2000-07-01
Full Text Available at the University of Pretoria. 4 REAL LIFE TYRE LOADS Characterisation Pavement loading has been shown by various authors to be a dynamic (time-dependent) phenomenon (Divine, 1997; Cebon, 1999). A pavement experiences a vehicle as a moving, time-varying set... frequencies. Body bounce generally dominates the dynamic loading, and is mainly caused by the response of the sprung mass of the vehicle to the pavement roughness. Axle hop becomes more significant at higher vehicle speeds and higher pavement roughnesses...
Failure mitigation in software defined networking employing load type prediction
Bouacida, Nader
2017-07-31
The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output.
Dynamic Fracture Simulations of Explosively Loaded Cylinders
Energy Technology Data Exchange (ETDEWEB)
Arthur, Carly W. [Univ. of California, Davis, CA (United States). Dept. of Civil and Environmental Engineering; Goto, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-11-30
This report documents the modeling results of high explosive experiments investigating dynamic fracture of steel (AerMet® 100 alloy) cylinders. The experiments were conducted at Lawrence Livermore National Laboratory (LLNL) during 2007 to 2008 [10]. A principal objective of this study was to gain an understanding of dynamic material failure through the analysis of hydrodynamic computer code simulations. Two-dimensional and three-dimensional computational cylinder models were analyzed using the ALE3D multi-physics computer code.
PLATON: Peer-to-Peer load adjusting tree overlay networks
Lymberopoulos, L.; Pittaras, C.; Grammatikou, M.; Papavassiliou, S.; Maglaris, V.
2011-01-01
Peer-to-Peer systems supporting multi attribute and range queries use a number of techniques to partition the multi dimensional data space among participating peers. Load-balancing of data accross peer partitions is necessary in order to avoid the presence of network hotspots which may cause
Three-Phase Unbalanced Load Flow Tool for Distribution Networks
DEFF Research Database (Denmark)
Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso
2012-01-01
This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....
Convergent dynamics for multistable delayed neural networks
International Nuclear Information System (INIS)
Shih, Chih-Wen; Tseng, Jui-Pin
2008-01-01
This investigation aims at developing a methodology to establish convergence of dynamics for delayed neural network systems with multiple stable equilibria. The present approach is general and can be applied to several network models. We take the Hopfield-type neural networks with both instantaneous and delayed feedbacks to illustrate the idea. We shall construct the complete dynamical scenario which comprises exactly 2 n stable equilibria and exactly (3 n − 2 n ) unstable equilibria for the n-neuron network. In addition, it is shown that every solution of the system converges to one of the equilibria as time tends to infinity. The approach is based on employing the geometrical structure of the network system. Positively invariant sets and componentwise dynamical properties are derived under the geometrical configuration. An iteration scheme is subsequently designed to confirm the convergence of dynamics for the system. Two examples with numerical simulations are arranged to illustrate the present theory
Information governance in dynamic networked business process management
Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.
2016-01-01
Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).
A dynamic allocation mechanism of delivering capacity in coupled networks
International Nuclear Information System (INIS)
Du, Wen-Bo; Zhou, Xing-Lian; Zhu, Yan-Bo; Zheng, Zheng
2015-01-01
Traffic process is ubiquitous in many critical infrastructures. In this paper, we introduce a mechanism to dynamically allocate the delivering capacity into the data-packet traffic model on the coupled Internet autonomous-system-level network of South Korea and Japan, and focus on its effect on the transport efficiency. In this mechanism, the total delivering capacity is constant and the lowest-load node will give one unit delivering capacity to the highest-load node at each time step. It is found that the delivering capacity of busy nodes and non-busy nodes can be well balanced and the effective betweenness of busy nodes with interconnections is significantly reduced. Consequently, the transport efficiency such as average traveling time and packet arrival rate is remarkably improved. Our work may shed some light on the traffic dynamics in coupled networks.
Pinning Synchronization of Switched Complex Dynamical Networks
Directory of Open Access Journals (Sweden)
Liming Du
2015-01-01
Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.
Psychology and social networks: a dynamic network theory perspective.
Westaby, James D; Pfaff, Danielle L; Redding, Nicholas
2014-04-01
Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
REDISTRIBUTION OF BASE STATIONS LOAD IN MOBILE COMMUNICATION NETWORKS
Directory of Open Access Journals (Sweden)
Igor Ruban
2017-09-01
Full Text Available The subject matter of the article is the processes of load distribution in mobile communication networks. The object of research is the handover. The goal is to develop a method for redistributing the load between neighboring areas for mobile nodes. The considered base stations are supposed to have the signal-to-noise ratios that are equal or close. The methods that are used: methods of system analysis, methods of digital signal processing. The following results are obtained. The method that allows mobile nodes, whose signal-to-noise ratios are equal or close, to switch to a less loaded base station. This method allows the base station to launch the handover process enabling more even distribution of the load from mobile nodes among neighboring base stations in wireless and mobile networks. In the suggested modification of the method, the function assessing the bandwidth of the uplink channel is added to the base stations, as well a threshold value for using its bandwidth. Thus, when the current value of bandwidth reaches the threshold, the base station starts sending out a message to all mobile nodes and verifies free neighboring areas for switching over mobile nodes. If there are adjacent areas with a lower load, the base station notifies all potential candidates about the necessity of their switching over. The handover process is launched when the available bandwidth of the base station decreases below a certain threshold. Therefore, it is possible to optimize the operation of the WiMAX network with respect to the criterion of the total bandwidth capacity of the base stations. Besides, the results of the comparative analysis of the handover process in networks based on the WiMAX technology that are obtained using the OpNet simulation environment are presented. Conclusions.The suggested approach can be used to improve the basic software of mobile communication networks. When moving a node from one area to another one in access servers, the
Characterization of dynamic loads on the LMFBR rotating shield
International Nuclear Information System (INIS)
Morris, E.
1979-01-01
The rotating shields structure is a potential weak point of some current designs of primary containment against postulated whole core explosions. The calculation of the effect of transient loads on this structure, resulting from such an explosion, is therefore important in developing a safety case. The transient loads are usually calculated by computer codes such as ASTARTE, SEURBNUK, REXCO or ICECO and the effect of these loads on the structure by a suitable finite element code. Such procedure can be lengthly and costly. The present paper proposed a procedure which allows the consequences of changes in the transient loads, resulting from design changes for example, to be quickly and simply gauged. The load-impulse method of characterizing dynamic response of a structural system is well established. Provided loads with a similar temporal variation are compared, it can be shown that the dynamic response depends on only two features of the load, an average load and a time intregrated load or impulse. The scope of this approach has been extended by Youngdahl who has shown, for structures which deform in a rigid-plastic manner, that complex laoding histories can be equated to a rectangular form of loading, in a precise manner for simple structures and in an approximate manner for more complicated structures. This paper proposes that the failure characteristics of the rotating shields for which extensive plastic deformation is involved, be calculated for rectangular type loadings. The complex transient loadings calculated for various explosions and various changes in the primary vessel design can then be reduced to an equivalent rectangular form and the consequencial response of the shields structure deduced. (orig.)
Purinergic responses of chondrogenic stem cells to dynamic loading
Directory of Open Access Journals (Sweden)
Gađanski Ivana
2013-01-01
Full Text Available In habitually loaded tissues, dynamic loading can trigger ATP (adenosine 5’- triphosphate release to extracellular environment, and result in calcium signaling via ATP binding to purine P2 receptors1. In the current study we have compared purinergic responses (ATP release of two types of cells: bovine chondrocytes (bCHs and human mesenchymal stem cells (hMSC that were encapsulated in agarose and subjected to dynamic loading. Both cell types were cultured under chondrogenic conditions, and their responses to loading were evaluated by ATP release assay in combination with connexin (Cx-sensitive fluorescent dye (Lucifer Yellow - LY and a Cx-hemichannel blocker (Flufenamic acid - FFA. In response to dynamic loading, chondrogenic hMSCs released significantly higher amounts of ATP (5-fold in comparison to the bCHs early in culture (day 2. Triggering of LY uptake in the bCHs and hMSCs by dynamic loading implies opening of the Cx-hemichannels. However, the number of LY-positive cells in hMSC-constructs was 2.5-fold lower compared to the loaded bCH-constructs, suggesting utilization of additional mechanisms of ATP release. Cx-reactive sites were detected in both bCHs and hMSCs-constructs. FFA application led to reduced ATP release both in bCHs and hMSCs, which confirms the involvement of connexin hemichannels, with more prominent effects in bCHs than in hMSCs, further implying the existence of additional mechanism of ATP release in chondrogenic hMSCs. Taken together, these results indicate stronger purinergic response to dynamic loading of chondrogenic hMSCs than primary chondrocytes, by activation of connexin hemichannels and additional mechanisms of ATP release. [Projekat Ministrastva nauke Republike Srbije, ON174028 i br. III41007
STUDY ON HEAT DYNAMIC LOADING OF RUBBER
Directory of Open Access Journals (Sweden)
T. I. Igumenova
2015-01-01
Full Text Available A number of studies on heat buildup in tire rubber surface scan method samples using a thermal imaging camera. Investigated the exothermic chemical reaction mechanical destruction rubber when loading designs permanent cyclic stretching with deformation of the working zone 50%. Percentage of deformation of the working zone was chosen on the basis of the actual data on the stretch-compression zone "Rusk" tires, which is the maximum level difference of deformation during run-in. Experiment plan provided for periodic relaxation samples of at least 72 hours for more accurate simulation of operation process of structural products. Created and processed data on temperature changes in samples for bar and line profile for rubber compounds with the introduction of nanomodifiers (fulleren technical carbon in comparison with the control sample without him. The data obtained reflect the nature of heat depending on the composition of the compound. Identified common patterns of thermal nature of physico-chemical process mechanical destruction rubbers. For rubber with nanomodifikatorom there has been an increase in the temperature interval reaction from a minimum to a maximum 2 degrees that is also linked to the rise in the average temperature of the reaction on the histogram also at 2-3 degrees of deformation under the same conditions and the level of cyclic loading. However, the temperature in the control sample that is associated with the beginning of the formation of hardened rubber structures, economies of Mallinz-Petrikeev, occurs with delay twice compared with modified Fullerenes. Measurement of physic-mechanical indicators selected in the course of testing of samples showed the beginning of formation of structure with increased strength of samples in the sample temperature zone that corresponds to the thermal effect of èndotermičeskomu recombination reactions of macromolecules.
Fundamental structures of dynamic social networks
DEFF Research Database (Denmark)
Sekara, Vedran; Stopczynski, Arkadiusz; Jørgensen, Sune Lehmann
2016-01-01
Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships...... and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection......, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals...
Evolutionary dynamics of complex communications networks
Karyotis, Vasileios; Papavassiliou, Symeon
2013-01-01
Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology-closing the network design loop in an evolutionary fashion similar to
Dynamics on Networks of Manifolds
DeVille, Lee; Lerman, Eugene
2015-03-01
We propose a precise definition of a continuous time dynamical system made up of interacting open subsystems. The interconnections of subsystems are coded by directed graphs. We prove that the appropriate maps of graphs called graph fibrations give rise to maps of dynamical systems. Consequently surjective graph fibrations give rise to invariant subsystems and injective graph fibrations give rise to projections of dynamical systems.
On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks
Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun
2011-01-01
This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809
Dynamic Response of Coarse Granular Material to Wave Load
DEFF Research Database (Denmark)
Ibsen, Lars Bo
1998-01-01
The soil beneath vertical breakwaters is subjected to a combination of forces induced by the waves. The forces acting on the soil can be characterized as 1) static load due to submerged weight of the structure, 2) quasi-static forces induced by cyclic wave loading, and 3) wave impact from breaking...... waves. The stress conditions in the soil below a foundation exposed to these types of loading are very complex. The key to explain and quantify the soil response beneath a vertical breakwater is to understand the role of the volume changes and to be able to model these correctly. It is shown...... that the volume changes in soil subjected to static and dynamic loading are controlled by the characteristic line. Experiments have been performed to study the factors that influence the location of the characteristic line in drained and undrained tests for various types of sand and various types of loading...
How complex a dynamical network can be?
International Nuclear Information System (INIS)
Baptista, M.S.; Kakmeni, F. Moukam; Del Magno, Gianluigi; Hussein, M.S.
2011-01-01
Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen; (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes.
Dynamical Adaptation in Terrorist Cells/Networks
DEFF Research Database (Denmark)
Hussain, Dil Muhammad Akbar; Ahmed, Zaki
2010-01-01
Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...
The Social Dynamics of Innovation Networks
Rutten, Roel; Benneworth, Paul Stephen; Irawati, Dessy; Boekema, Frans
2014-01-01
The social dynamics of innovation networks captures the important role of trust, social capital, institutions and norms and values in the creation of knowledge in innovation networks. In doing so, this book connects to a long-standing debate on the socio-spatial context of innovation in economic
Quantitative analysis of impact measurements using dynamic load cells
Directory of Open Access Journals (Sweden)
Brent J. Maranzano
2016-03-01
Full Text Available A mathematical model is used to estimate material properties from a short duration transient impact force measured by dropping spheres onto rectangular coupons fixed to a dynamic load cell. The contact stress between the dynamic load cell surface and the projectile are modeled using Hertzian contact mechanics. Due to the short impact time relative to the load cell dynamics, an additional Kelvin–Voigt element is included in the model to account for the finite response time of the piezoelectric crystal. Calculations with and without the Kelvin–Voigt element are compared to experimental data collected from combinations of polymeric spheres and polymeric and metallic surfaces. The results illustrate that the inclusion of the Kelvin–Voigt element qualitatively captures the post impact resonance and non-linear behavior of the load cell signal and quantitatively improves the estimation of the Young's elastic modulus and Poisson's ratio. Mathematically, the additional KV element couples one additional differential equation to the Hertzian spring-dashpot equation. The model can be numerically integrated in seconds using standard numerical techniques allowing for its use as a rapid technique for the estimation of material properties. Keywords: Young's modulus, Poisson's ratio, Dynamic load cell
Dynamic Frequency Control in Power Networks
Zhao, Changhong; Mallada Garcia, Enrique; Low, Steven H.
2016-01-01
Node controllers in power distribution networks in accordance with embodiments of the invention enable dynamic frequency control. One embodiment includes a node controller comprising a network interface a processor; and a memory containing a frequency control application; and a plurality of node operating parameters describing the operating parameters of a node, where the node is selected from a group consisting of at least one generator node in a power distribution network wherein the proces...
Immune networks: multi-tasking capabilities at medium load
Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.
2013-08-01
Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ frameworks are required to achieve effective retrieval.
A Dynamic Model for Load Balancing in Cloud Infrastructure
Directory of Open Access Journals (Sweden)
Jitendra Bhagwandas Bhatia
2015-08-01
Full Text Available This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform-independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, a prediction model is employed to maintain high availability and a power-aware algorithm is applied for choosing a suitable physical node for a virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.For anyone building a private, public or hybrid IaaS cloud infrastructure, load balancing of virtual hosts on a limited number of physical nodes, becomes a crucial aspect. This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, prediction model is employed to maintain high availability and power aware algorithm is applied for choosing a suitable physical node for virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.
Network Physiology: How Organ Systems Dynamically Interact.
Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch
2015-01-01
We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.
Network Physiology: How Organ Systems Dynamically Interact
Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.
2015-01-01
We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073
Leveraging Microgrids for Capturing Uncertain Distribution Network Net Load Ramping
Majzoobi, Alireza; Khodaei, Amin
2016-01-01
In this paper, a flexibility-oriented microgrid optimal scheduling model is proposed to mitigate distribution network net load variability caused by large penetration distributed solar generation. The distributed solar generation variability, which is caused by increasing adoption of this technology by end-use consumers, is mainly addressed by electric utilities using grid reinforcement. Microgrids, however, provide viable and local solutions to this pressing challenge. The proposed model, wh...
Intelligent harmonic load model based on neural networks
Ji, Pyeong-Shik; Lee, Dae-Jong; Lee, Jong-Pil; Park, Jae-Won; Lim, Jae-Yoon
2007-12-01
In this study, we developed a RBFNs(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method implemented by using harmonic information as well as fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. The RBFNs have certain advantage such as simple structure and rapid computation ability compared with multilayer perceptron which is extensively applied for load modeling. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynominal 2nd equation method, MLP and RBF without considering harmonic components.
Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo
2016-07-25
Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.
Immune networks: multi-tasking capabilities at medium load
International Nuclear Information System (INIS)
Agliari, E; Annibale, A; Barra, A; Coolen, A C C; Tantari, D
2013-01-01
Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ∼ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ∼ N δ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval. (paper)
Deep Neural Network Based Demand Side Short Term Load Forecasting
Directory of Open Access Journals (Sweden)
Seunghyoung Ryu
2016-12-01
Full Text Available In the smart grid, one of the most important research areas is load forecasting; it spans from traditional time series analyses to recent machine learning approaches and mostly focuses on forecasting aggregated electricity consumption. However, the importance of demand side energy management, including individual load forecasting, is becoming critical. In this paper, we propose deep neural network (DNN-based load forecasting models and apply them to a demand side empirical load database. DNNs are trained in two different ways: a pre-training restricted Boltzmann machine and using the rectified linear unit without pre-training. DNN forecasting models are trained by individual customer’s electricity consumption data and regional meteorological elements. To verify the performance of DNNs, forecasting results are compared with a shallow neural network (SNN, a double seasonal Holt–Winters (DSHW model and the autoregressive integrated moving average (ARIMA. The mean absolute percentage error (MAPE and relative root mean square error (RRMSE are used for verification. Our results show that DNNs exhibit accurate and robust predictions compared to other forecasting models, e.g., MAPE and RRMSE are reduced by up to 17% and 22% compared to SNN and 9% and 29% compared to DSHW.
Feasibility of Applying Controllable Lubrication to Dynamically Loaded Journal Bearings
DEFF Research Database (Denmark)
Estupinan, Edgar Alberto; Santos, Ilmar
2009-01-01
A multibody dynamic model of the main mechanical components of a hermetic reciprocating compressor is presented in this work. Considering that some of the mechanical elements are interconnected via thin fluid films, the multibody dynamic model is coupled to the equations from the dynamics...... of the fluid films, based on fluid film theory. For a dynamically loaded journal bearing, the fluid film pressure distribution can be computed by numerically solving the Reynolds equation, by means of finite-difference method. Particularly, in this study the main focus is on the lubrication behavior...... and reaction forces in a reciprocating compressor have a cyclic behavior, periodic oil pressure injection rules based on the instantaneous crank angle and load bearing condition can be established. In this paper, several bearing configurations working under different oil pressure injection rules conditions...
Incremental Centrality Algorithms for Dynamic Network Analysis
2013-08-01
literature. 7.1.3 Small World Networks In 1998, Watts and Strogatz introduced a model that starts with a regular lattice (ring) of n nodes and...and S. Strogatz , "Collective Dynamics of ‘Small-World’ Networks," Nature, vol. 393, pp. 440-442, 1998. [13] T. Opsahl, "Structure and Evolution of...34On Random Graphs," Publicationes Mathematicae, vol. 6, 1959. [167] D.J. Watts and S.H. Strogatz , "Collective Dynamics of ‘Small-World’ Networks
Insights and issues with simulating terrestrial DOC loading of Arctic river networks.
Kicklighter, David W; Hayes, Daniel J; McClelland, James W; Peterson, Bruce J; McGuire, A David; Melillo, Jerry M
2013-12-01
Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.
Insights and issues with simulating terrestrial DOC loading of Arctic river networks
Kicklighter, David W.; Hayes, Daniel J.; McClelland, James W.; Peterson, Bruce J.; McGuire, A. David; Melillo, Jerry M.
2013-01-01
Terrestrial carbon dynamics inﬂuence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildﬁres. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to inﬂuence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon ﬂux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil proﬁle, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic efﬂuents on carbon budgets of rivers in western Russia.
A network dynamics approach to chemical reaction networks
van der Schaft, A. J.; Rao, S.; Jayawardhana, B.
2016-04-01
A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.
Conflict and convention in dynamic networks.
Foley, Michael; Forber, Patrick; Smead, Rory; Riedl, Christoph
2018-03-01
An important way to resolve games of conflict (snowdrift, hawk-dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioural strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host-guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models. © 2017 The Author(s).
Markovian dynamics on complex reaction networks
Energy Technology Data Exchange (ETDEWEB)
Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu
2013-08-10
Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.
Markovian dynamics on complex reaction networks
International Nuclear Information System (INIS)
Goutsias, J.; Jenkinson, G.
2013-01-01
Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples
Learning State Space Dynamics in Recurrent Networks
Simard, Patrice Yvon
Fully recurrent (asymmetrical) networks can be used to learn temporal trajectories. The network is unfolded in time, and backpropagation is used to train the weights. The presence of recurrent connections creates internal states in the system which vary as a function of time. The resulting dynamics can provide interesting additional computing power but learning is made more difficult by the existence of internal memories. This study first exhibits the properties of recurrent networks in terms of convergence when the internal states of the system are unknown. A new energy functional is provided to change the weights of the units in order to the control the stability of the fixed points of the network's dynamics. The power of the resultant algorithm is illustrated with the simulation of a content addressable memory. Next, the more general case of time trajectories on a recurrent network is studied. An application is proposed in which trajectories are generated to draw letters as a function of an input. In another application of recurrent systems, a neural network certain temporal properties observed in human callosally sectioned brains. Finally the proposed algorithm for stabilizing dynamics around fixed points is extended to one for stabilizing dynamics around time trajectories. Its effects are illustrated on a network which generates Lisajous curves.
Dynamic Protection of Optical Networks
DEFF Research Database (Denmark)
Ruepp, Sarah Renée
2008-01-01
This thesis deals with making optical networks resilient to failures. The recovery performance of path, segment and span restoration is evaluated in a network with limited wavelength conversion capability using both standard and enhanced wavelength assignment schemes. The enhanced wavelength...... stubs at the failure adjacent nodes. Both modifcations have a positive influence on the recovery percentage. The recovery enhancements are applicable in both single and multi-domain network environments. Stub release, where the still working parts of a failure affected connection are released prior...... of the modularity of capacity units is investigated for resilient network design. Different span upgrading strategies and algorithms for finding restoration paths are evaluated. Furthermore, the capacity effciency of constraining restoration requests for the same destination node to the same restoration path...
Cognitive radio networks dynamic resource allocation schemes
Wang, Shaowei
2014-01-01
This SpringerBrief presents a survey of dynamic resource allocation schemes in Cognitive Radio (CR) Systems, focusing on the spectral-efficiency and energy-efficiency in wireless networks. It also introduces a variety of dynamic resource allocation schemes for CR networks and provides a concise introduction of the landscape of CR technology. The author covers in detail the dynamic resource allocation problem for the motivations and challenges in CR systems. The Spectral- and Energy-Efficient resource allocation schemes are comprehensively investigated, including new insights into the trade-off
LAMAN: Load Adaptable MAC for Ad Hoc Networks
Directory of Open Access Journals (Sweden)
Realp Marc
2005-01-01
Full Text Available In mobile ad hoc radio networks, mechanisms on how to access the radio channel are extremely important in order to improve network efficiency. In this paper, the load adaptable medium access control for ad hoc networks (LAMAN protocol is described. LAMAN is a novel decentralized multipacket MAC protocol designed following a cross-layer approach. Basically, this protocol is a hybrid CDMA-TDMA-based protocol that aims at throughput maximization in multipacket communication environments by efficiently combining contention and conflict-free protocol components. Such combination of components is used to adapt the nodes' access priority to changes on the traffic load while, at the same time, accounting for the multipacket reception (MPR capability of the receivers. A theoretical analysis of the system is developed presenting closed expressions of network throughput and packet delay. By simulations the validity of our analysis is shown and the performances of a LAMAN-based system and an Aloha-CDMA-based one are compared.
Competing dynamic phases of active polymer networks
Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.
Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.
Dynamics of High-Resolution Networks
DEFF Research Database (Denmark)
Sekara, Vedran
the unprecedented amounts of information collected by mobile phones to gain detailed insight into the dynamics of social systems. This dissertation presents an unparalleled data collection campaign, collecting highly detailed traces for approximately 1000 people over the course of multiple years. The availability...... are we all affected by an ever changing network structure? Answering these questions will enrich our understanding of ourselves, our organizations, and our societies. Yet, mapping the dynamics of social networks has traditionally been an arduous undertaking. Today, however, it is possible to use...... of such dynamic maps allows us to probe the underlying social network and understand how individuals interact and form lasting friendships. More importantly, these highly detailed dynamic maps provide us new perspectives at traditional problems and allow us to quantify and predict human life....
Control theory of digitally networked dynamic systems
Lunze, Jan
2013-01-01
The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic
Generalized Load Sharing for Homogeneous Networks of Distributed Environment
Directory of Open Access Journals (Sweden)
A. Satheesh
2008-01-01
Full Text Available We propose a method for job migration policies by considering effective usage of global memory in addition to CPU load sharing in distributed systems. When a node is identified for lacking sufficient memory space to serve jobs, one or more jobs of the node will be migrated to remote nodes with low memory allocations. If the memory space is sufficiently large, the jobs will be scheduled by a CPU-based load sharing policy. Following the principle of sharing both CPU and memory resources, we present several load sharing alternatives. Our objective is to reduce the number of page faults caused by unbalanced memory allocations for jobs among distributed nodes, so that overall performance of a distributed system can be significantly improved. We have conducted trace-driven simulations to compare CPU-based load sharing policies with our policies. We show that our load sharing policies not only improve performance of memory bound jobs, but also maintain the same load sharing quality as the CPU-based policies for CPU-bound jobs. Regarding remote execution and preemptive migration strategies, our experiments indicate that a strategy selection in load sharing is dependent on the amount of memory demand of jobs, remote execution is more effective for memory-bound jobs, and preemptive migration is more effective for CPU-bound jobs. Our CPU-memory-based policy using either high performance or high throughput approach and using the remote execution strategy performs the best for both CPU-bound and memory-bound job in homogeneous networks of distributed environment.
Dynamic loads during failure risk assessment of bridge crane structures
Gorynin, A. D.; Antsev, V. Yu; Shaforost, A. N.
2018-03-01
The paper presents the method of failure risk assessment associated with a bridge crane metal structure at the design stage. It also justifies the necessity of taking into account dynamic loads with regard to the operational cycle of a bridge crane during failure risk assessment of its metal structure.
Shaft centre orbit for dynamically loaded radial bearings
DEFF Research Database (Denmark)
Klit, Peder; Vølund, Anders
2002-01-01
The aim of this work is to demonstrate how to utilize the bearings damping coefficients to estimate the orbit for a dynamically loaded journal bearing. The classical method for this analysis was developed by Booker in 1965 Booker1 and described further in 1972 Booker2. Several authors have refine...
46 CFR 154.409 - Dynamic loads from vessel motion.
2010-10-01
... in length and is an analysis by the following formulae that corresponds to a 10−8 probability level... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...
Dynamic modelling of heavy metals - time scales and target loads
Posch, M.; Vries, de W.
2009-01-01
Over the past decade steady-state methods have been developed to assess critical loads of metals avoiding long-term risks in view of food quality and eco-toxicological effects on organisms in soils and surface waters. However, dynamic models are needed to estimate the times involved in attaining a
Dynamic analysis of reactor containment subjected to aircraft impact loading
International Nuclear Information System (INIS)
Li Xiaotian; He Shuyan
2004-01-01
In this paper, dynamic character of reactor containment subjected to aircraft impact loading is analyzed with MSC.DYTRAN program. The displacement of concrete and velocity curve of airplane is obtained. The results of the different material model are compared with empirical formula. It is concluded that reasonable result can be obtained using cap model for concrete
Dynamic Regression Intervention Modeling for the Malaysian Daily Load
Directory of Open Access Journals (Sweden)
Fadhilah Abdrazak
2014-05-01
Full Text Available Malaysia is a unique country due to having both fixed and moving holidays. These moving holidays may overlap with other fixed holidays and therefore, increase the complexity of the load forecasting activities. The errors due to holidays’ effects in the load forecasting are known to be higher than other factors. If these effects can be estimated and removed, the behavior of the series could be better viewed. Thus, the aim of this paper is to improve the forecasting errors by using a dynamic regression model with intervention analysis. Based on the linear transfer function method, a daily load model consists of either peak or average is developed. The developed model outperformed the seasonal ARIMA model in estimating the fixed and moving holidays’ effects and achieved a smaller Mean Absolute Percentage Error (MAPE in load forecast.
Reduction of Dynamic Loads in Mine Lifting Installations
Kuznetsov, N. K.; Eliseev, S. V.; Perelygina, A. Yu
2018-01-01
Article is devoted to a problem of decrease in the dynamic loadings arising in transitional operating modes of the mine lifting installations leading to heavy oscillating motions of lifting vessels and decrease in efficiency and reliability of work. The known methods and means of decrease in dynamic loadings and oscillating motions of the similar equipment are analysed. It is shown that an approach based on the concept of the inverse problems of dynamics can be effective method of the solution of this problem. The article describes the design model of a one-ended lifting installation in the form of a two-mass oscillation system, in which the inertial elements are the mass of the lifting vessel and the reduced mass of the engine, reducer, drum and pulley. The simplified mathematical model of this system and results of an efficiency research of an active way of reduction of dynamic loadings of lifting installation on the basis of the concept of the inverse problems of dynamics are given.
PPOOLEX experiments on dynamic loading with pressure feedback
International Nuclear Information System (INIS)
Puustinen, M.; Laine, J.; Raesaenen, A.
2011-01-01
This report summarizes the results of the dynamic loading experiments (DYN series) carried out with the scaled down, two compartment PPOOLEX test facility designed and constructed at LUT. Steam was blown into the dry well compartment and from there through the DN200 vertical blowdown pipe to the condensation pool filled with sub-cooled water. The main purpose of the experiments was to study dynamic loads caused by different condensation modes. Particularly, the effect of counterpressure on loads due to pressure oscillations induced by chugging was of interest. Before the experiments the condensation pool was filled with isothermal water so that the blowdown pipe outlet was submerged by 1.03-1.11 m. The initial temperature of the pool water varied from 11 deg. C to 63 deg. C, the steam flow rate from 290 g/s to 1220 g/s and the temperature of incoming steam from 132 deg. C to 182 deg. C. Non-condensables were pushed from the dry well into the gas space of the wet well with a short discharge of steam before the recorded period of the experiments. As a result of this procedure, the system pressure was at an elevated level in the beginning of the actual experiments. An increased counterpressure was used in the last experiment of the series. The diminishing effect of increased system pressure on chugging intensity and on measured loads is evident from the results of the last experiment. The highest pressure pulses both inside the blowdown pipe and in the condensation pool were about half of those measured with a lower system pressure but otherwise with similar test parameters. The experiments on dynamic loading gave expected results. The loads experienced by pool structures depended strongly on the steam mass flow rate, pool water temperature and system pressure. The DYN experiments indicated that chugging and condensation within the blowdown pipe cause significant dynamic loads in case of strongly sub-cooled pool water. The level of pool water temperature is decisive
PPOOLEX experiments on dynamic loading with pressure feedback
Energy Technology Data Exchange (ETDEWEB)
Puustinen, M.; Laine, J.; Raesaenen, A. (Lappeenranta Univ. of Technology, Nuclear Safety Research Unit (Finland))
2011-01-15
This report summarizes the results of the dynamic loading experiments (DYN series) carried out with the scaled down, two compartment PPOOLEX test facility designed and constructed at LUT. Steam was blown into the dry well compartment and from there through the DN200 vertical blowdown pipe to the condensation pool filled with sub-cooled water. The main purpose of the experiments was to study dynamic loads caused by different condensation modes. Particularly, the effect of counterpressure on loads due to pressure oscillations induced by chugging was of interest. Before the experiments the condensation pool was filled with isothermal water so that the blowdown pipe outlet was submerged by 1.03-1.11 m. The initial temperature of the pool water varied from 11 deg. C to 63 deg. C, the steam flow rate from 290 g/s to 1220 g/s and the temperature of incoming steam from 132 deg. C to 182 deg. C. Non-condensables were pushed from the dry well into the gas space of the wet well with a short discharge of steam before the recorded period of the experiments. As a result of this procedure, the system pressure was at an elevated level in the beginning of the actual experiments. An increased counterpressure was used in the last experiment of the series. The diminishing effect of increased system pressure on chugging intensity and on measured loads is evident from the results of the last experiment. The highest pressure pulses both inside the blowdown pipe and in the condensation pool were about half of those measured with a lower system pressure but otherwise with similar test parameters. The experiments on dynamic loading gave expected results. The loads experienced by pool structures depended strongly on the steam mass flow rate, pool water temperature and system pressure. The DYN experiments indicated that chugging and condensation within the blowdown pipe cause significant dynamic loads in case of strongly sub-cooled pool water. The level of pool water temperature is decisive
Effects of static pre-loading on the dynamic stability of a column on ...
African Journals Online (AJOL)
This paper presents, from strictly analytical consideration, the dynamic analysis of a finite column stressed by a step load but in the presence of a previously imposed static load. The results show that (a) the dynamic buckling load for this type of loading is relatively higher than that of a similar column stressed by a step load ...
Traffic Dynamics of Computer Networks
Fekete, Attila
2008-10-01
Two important aspects of the Internet, namely the properties of its topology and the characteristics of its data traffic, have attracted growing attention of the physics community. My thesis has considered problems of both aspects. First I studied the stochastic behavior of TCP, the primary algorithm governing traffic in the current Internet, in an elementary network scenario consisting of a standalone infinite-sized buffer and an access link. The effect of the fast recovery and fast retransmission (FR/FR) algorithms is also considered. I showed that my model can be extended further to involve the effect of link propagation delay, characteristic of WAN. I continued my thesis with the investigation of finite-sized semi-bottleneck buffers, where packets can be dropped not only at the link, but also at the buffer. I demonstrated that the behavior of the system depends only on a certain combination of the parameters. Moreover, an analytic formula was derived that gives the ratio of packet loss rate at the buffer to the total packet loss rate. This formula makes it possible to treat buffer-losses as if they were link-losses. Finally, I studied computer networks from a structural perspective. I demonstrated through fluid simulations that the distribution of resources, specifically the link bandwidth, has a serious impact on the global performance of the network. Then I analyzed the distribution of edge betweenness in a growing scale-free tree under the condition that a local property, the in-degree of the "younger" node of an arbitrary edge, is known in order to find an optimum distribution of link capacity. The derived formula is exact even for finite-sized networks. I also calculated the conditional expectation of edge betweenness, rescaled for infinite networks.
The dynamics of transmission and the dynamics of networks.
Farine, Damien
2017-05-01
A toy example depicted here highlighting the results of a study in this issue of the Journal of Animal Ecology that investigates the impact of network dynamics on potential disease outbreaks. Infections (stars) that spread by contact only (left) reduce the predicted outbreak size compared to situations where individuals can become infected by moving through areas that previously contained infected individuals (right). This is potentially important in species where individuals, or in this case groups, have overlapping ranges (as depicted on the top right). Incorporating network dynamics that maintain information about the ordering of contacts (central blocks; including the ordering of spatial overlap as noted by the arrows that highlight the blue group arriving after the red group in top-right of the figure) is important for capturing how a disease might not have the opportunity to spread to all individuals. By contrast, a static or 'average' network (lower blocks) does not capture any of these dynamics. Interestingly, although static networks generally predict larger outbreak sizes, the authors find that in cases when transmission probability is low, this prediction can switch as a result of changes in the estimated intensity of contacts among individuals. [Colour figure can be viewed at wileyonlinelibrary.com]. Springer, A., Kappeler, P.M. & Nunn, C.L. (2017) Dynamic vs. static social networks in models of parasite transmission: Predicting Cryptosporidium spread in wild lemurs. Journal of Animal Ecology, 86, 419-433. The spread of disease or information through networks can be affected by several factors. Whether and how these factors are accounted for can fundamentally change the predicted impact of a spreading epidemic. Springer, Kappeler & Nunn () investigate the role of different modes of transmission and network dynamics on the predicted size of a disease outbreak across several groups of Verreaux's sifakas, a group-living species of lemur. While some factors
Dynamics-based centrality for directed networks.
Masuda, Naoki; Kori, Hiroshi
2010-11-01
Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.
Design of dynamic loading support on high temperature pipe
International Nuclear Information System (INIS)
Sitandung, Y.B.; Bandriyana, B.
2002-01-01
As a follow up to pipe stress analysis result caused by high temperature operation loading, a design of dynamic loading support was made. The type of variable and constant support as acceptable choosing are applicated for reduce of over stress and over load on piping system. Analysis line schedule of AP600 as an example with apply three dynamic loading support (two type variable and one type constant support). The pre-design of the third support above are based on analysis result with follow the support catalog and field condition wherein its supports are installed. To guarantee the performance and accurate of the support, checking is performed for spring working rate tolerance, support variability and swing angle. The design results of variable spring are loads, size, working rate, type tolerance, spring rate, variability, long and sway angle with each values 5000; 15; 1,25; VM; 0.655; 1080; 0.114; 114,5; 0,48 for S1 and 2045; 12; 0,583; VS; 0,237; 900; 0,132; 130; 0,34 for S3
Critical dynamics in associative memory networks
Directory of Open Access Journals (Sweden)
Maximilian eUhlig
2013-07-01
Full Text Available Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics. The network endowed with Hebbian learning only does not allow for simultaneous information storage and criticality. However, the critical regime is can be stabilized by short-term synaptic dynamics in the form of synaptic depression and facilitation or, alternatively, by homeostatic adaptation of the synaptic weights. We show that a heterogeneous distribution of maximal synaptic strengths does not preclude criticality if the Hebbian learning is alternated with periods of critical dynamics recovery. We discuss the relevance of these findings for the flexibility of memory in aging and with respect to the recent theory of synaptic plasticity.
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...
Hydrogen application dynamics and networks
Energy Technology Data Exchange (ETDEWEB)
Schmidt, E. [Air Liquide Large Industries, Champigny-sur-Marne (France)
2010-12-30
The Chemical Industry consumes large volumes of hydrogen as raw material for the manufacture of numerous products (e.g. polyamides and polyurethanes account for 60% of hydrogen demand). The hydrogen demand was in the recent past and will continue to be driven by the polyurethane family. China will host about 60% of new hydrogen needs over the period 2010-2015 becoming the first hydrogen market next year and reaching 25% of market share by 2015 (vs. only 4% in 2001). Air Liquide supplies large volumes of Hydrogen (and other Industrial Gases) to customers by on-site plants and through pipeline networks which offer significant benefits such as higher safety, reliability and flexibility of supply. Thanks to its long term strategy and heavy investment in large units and pipeline networks, Air Liquide is the Industrial Gas leader in most of the world class Petrochemical basins (Rotterdam, Antwerp, US Gulf Coast, Yosu, Caojing,..) (orig.)
Loading technique for dynamic response studies of geological materials
International Nuclear Information System (INIS)
Butler, R.I.; Forrestal, M.J.
1979-04-01
A loading technique to study the dynamic response of tuff was explored. Loading is provided by electrically exploding etched copper mesh patterns with current from a capacitor discharge. Pressure pulses with peak pressures up to 1.25 kbar and 0.10 to 0.20 ms durations were measured with a pressure bar. The upper value of peak pressure was limited by the strength of the experimental apparatus, and higher pressure generation is possible with a redesign of test hardware. 6 figures, 2 tables
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.
DYNAMIC TIME HISTORY ANALYSIS OF BLAST RESISTANT DOOR USING BLAST LOAD MODELED AS IMPACT LOAD
Directory of Open Access Journals (Sweden)
Y. A. Pranata
2012-06-01
Full Text Available A blast resistant single door was designed to withstand a 0.91 bar blast pressure and 44 ms blast duration. The analysis was done using Dynamic Time History Analysis using Blast Load modeled as Impact Load for given duration. The material properties used have been modified to accommodate dynamic effects. The analysis was done using dynamic finite element method (fem for time of the blast duration, and the maximum/minimum internal forces and displacement were taken from the time history output, in order to know the behavior under blast load and estimate the safety margin of the door. Results obtained from this research indicated that the maximum z-displacement is 1.709 mm, while in the term of serviceability, the permitted is 25 mm. The maximum reaction force is 73,960 N, while the maximum anchor capacity is 82,069 N. On blast condition, the maximum frame stress is 71.71 MPa, the maximum hinge shear stress is 45.28 MPa. While on rebound condition, the maximum frame stress is 172.11 MPa, the maximum hinge shear stress is 29.46 MPa. The maximum door edge rotation is 0.44 degree, which is not exceed the permitted boundary (1.2 degree. Keywords: Dynamic time history, blast resistant door, single door, finite element method.
perception of communication network fraud dynamics by network ...
African Journals Online (AJOL)
ES Obe
work fraud dynamics by network administrators and stakeholders. In considering ... cyber crime within the last two years. How- ever, two-thirds of the ... ˆ increased exposure to unpredictable fi- nancial losses ... The intentions of the customers are reflected ..... 'There is a 95% confidence that the differ- ence between the ...
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.
Spreading dynamics in complex networks
Pei, Sen; Makse, Hernán A.
2013-12-01
Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.
Spreading dynamics in complex networks
International Nuclear Information System (INIS)
Pei, Sen; Makse, Hernán A
2013-01-01
Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality. (paper)
A technique for measuring dynamic friction coefficient under impact loading.
Lin, Y L; Qin, J G; Chen, R; Zhao, P D; Lu, F Y
2014-09-01
We develop a novel setup based on the split Hopkinson pressure bar technique to test the dynamic friction coefficient under impact loading. In the setup, the major improvement is that the end of the incident bar near the specimen is wedge-shaped, which results in a combined compressive and shear loading applied to the specimen. In fact, the shear loading is caused by the interfacial friction between specimen and bars. Therefore, when the two loading force histories are measured, the friction coefficient histories can be calculated without any assumptions and theoretical derivations. The geometry of the friction pairs is simple, and can be either cuboid or cylindrical. Regarding the measurements, two quartz transducers are used to directly record the force histories, and an optical apparatus is designed to test the interfacial slip movement. By using the setup, the dynamic friction coefficient of PTFE/aluminum 7075 friction pairs was tested. The time resolved dynamic friction coefficient and slip movement histories were achieved. The results show that the friction coefficient changes during the loading process, the average data of the relatively stable flat plateau section of the friction coefficient curves is 0.137, the maximum normal pressure is 52 MPa, the maximum relative slip velocity is 1.5 m/s, and the acceleration is 8400 m(2)/s. Furthermore, the friction test was simulated using an explicit FEM code LS-DYNA. The simulation results showed that the constant pressure and slip velocity can both be obtained with a wide flat plateau incident pulse. For some special friction pairs, normal pressure up to a few hundred MPa, interfacial slip velocities up to 10 m/s, and slip movement up to centimeter-level can be expected.
The dynamic behavior of mortar under impact-loading
Kawai, Nobuaki; Inoue, Kenji; Misawa, Satoshi; Tanaka, Kyoji; Hayashi, Shizuo; Kondo, Ken-Ichi; Riedel, Werner
2007-06-01
Concrete and mortar are the most fundamental structural material. Therefore, considerable interest in characterizing the dynamic behavior of them under impact-loading exists. In this study, plate impact experiments have been performed to determine the dynamic behavior of mortar. Longitudinal and lateral stresses have been directly measured by means of embedded polyvinylidene fluoride (PVDF) gauges up to 1 GPa. A 200 mm-cal. powder gun enable us to measure longitudinal and lateral stresses at several point from the impact surface, simultaneously. The shear strength under impact-loading has been obtained from measured longitudinal and lateral stresses. The longitudinal stress profile shows a two-wave structure. It is indicated that this structure is associated with the onset of pore compaction and failure of mortar by comparing with hydrocode simulations using an elastic-plastic damage model for concrete.
Response of porous beryllium to static and dynamic loading
Energy Technology Data Exchange (ETDEWEB)
Isbell, W.M.; Walton, O.R.; Ree, F.H.
1977-07-01
Previous investigstions of the mechanical response of porous materials to dynamic loading have been extended to include the shock wave response of a brittle metal. The complex response of berylliums of 85 to 90 percent porosity in two initial conditions has been examined in a theoretical and experimental program to be described. The study has resulted in the development of constitutive relations placed in hydrocodes which are capable of accurately predicting wave propagation in the berylliums. A comprehensive set of static (0 to 4 Gpa) and dynamic (0 to 35 Gpa) experiments was performed to measure the behavior of these brittle, porous materials to imposed loads. The results of the experiments guided a modeling effort which added several new features to previous models, including deviatoric stresses, porosity-dependent relaxation time of pore closure, elastic-plastic reopening of pores, and improved compaction functions.
Response of porous beryllium to static and dynamic loading
International Nuclear Information System (INIS)
Isbell, W.M.; Walton, O.R.; Ree, F.H.
1977-07-01
Previous investigstions of the mechanical response of porous materials to dynamic loading have been extended to include the shock wave response of a brittle metal. The complex response of berylliums of 85 to 90 percent porosity in two initial conditions has been examined in a theoretical and experimental program to be described. The study has resulted in the development of constitutive relations placed in hydrocodes which are capable of accurately predicting wave propagation in the berylliums. A comprehensive set of static (0 to 4 Gpa) and dynamic (0 to 35 Gpa) experiments was performed to measure the behavior of these brittle, porous materials to imposed loads. The results of the experiments guided a modeling effort which added several new features to previous models, including deviatoric stresses, porosity-dependent relaxation time of pore closure, elastic-plastic reopening of pores, and improved compaction functions
Discontinuity effects in dynamically loaded tilting pad journal bearings
DEFF Research Database (Denmark)
Thomsen, Kim; Klit, Peder; Vølund, Anders
2011-01-01
This paper describes two discontinuity effects that can occur when modelling radial tilting pad bearings subjected to high dynamic loads. The first effect to be treated is a pressure build-up discontinuity effect. The second effect is a contact-related discontinuity that disappears when a contact...... force is included in the theoretical model. Methods for avoiding the pressure build-up discontinuity effect are proposed....
Dynamic response analysis of an aircraft structure under thermal-acoustic loads
International Nuclear Information System (INIS)
Cheng, H; Li, H B; Zhang, W; Wu, Z Q; Liu, B R
2016-01-01
Future hypersonic aircraft will be exposed to extreme combined environments includes large magnitude thermal and acoustic loads. It presents a significant challenge for the integrity of these vehicles. Thermal-acoustic test is used to test structures for dynamic response and sonic fatigue due to combined loads. In this research, the numerical simulation process for the thermal acoustic test is presented, and the effects of thermal loads on vibro-acoustic response are investigated. To simulate the radiation heating system, Monte Carlo theory and thermal network theory was used to calculate the temperature distribution. Considering the thermal stress, the high temperature modal parameters are obtained with structural finite element methods. Based on acoustic finite element, modal-based vibro-acoustic analysis is carried out to compute structural responses. These researches are very vital to optimum thermal-acoustic test and structure designs for future hypersonic vehicles structure (paper)
Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications
Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid
1999-01-01
The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.
Numerical evaluation of cracked pipes under dynamic loading
International Nuclear Information System (INIS)
Petit, M.; Jamet, P.
1989-01-01
In order to apply the leak-before-break concept to piping systems, the behavior of cracked pipes under dynamic, and especially seismic, loadings must be studied. A simple finite element model of a cracked pipe has been developed and implemented in the general purpose computer code CASTEM 2000. The model is a generalization of the approach proposed by Paris and Tada (1). Considered loads are bending moment and axial force (representing thermal expansion and internal pressure.) The elastic characteristics of the model are determined using the Zahoor formulae for the geometry-dependent factors. Owing to the material behabior plasticity must be taken into account. To represent the crack growth, the material is defined by two characteristic values: J 1c which is the level of energy corresponding to crack initiation and the tearing modulus, T, which governs the length of propagation of the crack. For dynamic loads, unilateral conditions are imposed to represent crack closure. The model has been used for the design of dynamic tests to be conducted on shaking tables. Test principle is briefly described and numerical results are presented. Finally evaluation of margin, due to plasticity, in comparison with the standard design procedure is made
Synchronization of coupled chaotic dynamics on networks
Indian Academy of Sciences (India)
We review some recent work on the synchronization of coupled dynamical systems on a variety of networks. When nodes show synchronized behaviour, two interesting phenomena can be observed. First, there are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters ...
Modular networks with hierarchical organization: The dynamical ...
Indian Academy of Sciences (India)
Most of the complex systems seen in real life also have associated dynamics [10], and the ... another example, this time a hierarchical structure, viz., the Cayley tree with b ..... natural constraints operating on networks in real life, such as the ...
Dynamical networks with topological self-organization
Zak, M.
2001-01-01
Coupled evolution of state and topology of dynamical networks is introduced. Due to the well organized tensor structure, the governing equations are presented in a canonical form, and required attractors as well as their basins can be easily implanted and controlled.
Dynamics of nephron-vascular network
DEFF Research Database (Denmark)
Postnov, Dmitry; Postnov, D E; Marsh, D J
2012-01-01
The paper presents a modeling study of the spatial dynamics of a nephro-vascular network consisting of individual nephrons connected via a tree-like vascular branching structure. We focus on the effects of nonlinear mechanisms that are responsible for the formation of synchronous patterns in order...
Discerning connectivity from dynamics in climate networks
Czech Academy of Sciences Publication Activity Database
Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin
2011-01-01
Roč. 18, č. 5 (2011), s. 751-763 ISSN 1023-5809 R&D Projects: GA ČR GCP103/11/J068 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex networks * climate dynamics * connectivity * North Atlantic Oscillation * solar activity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.597, year: 2011
Dynamical Networks Characterization of Space Weather Events
Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.
2017-12-01
Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show
Dynamical systems on networks a tutorial
Porter, Mason A
2016-01-01
This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Appli...
Power Aware Dynamic Provisioning of HPC Networks
Energy Technology Data Exchange (ETDEWEB)
Groves, Taylor [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-10-01
Future exascale systems are under increased pressure to find power savings. The network, while it consumes a considerable amount of power is often left out of the picture when discussing total system power. Even when network power is being considered, the references are frequently a decade or older and rely on models that lack validation on modern inter- connects. In this work we explore how dynamic mechanisms of an Infiniband network save power and at what granularity we can engage these features. We explore this within the context of the host controller adapter (HCA) on the node and for the fabric, i.e. switches, using three different mechanisms of dynamic link width, frequency and disabling of links for QLogic and Mellanox systems. Our results show that while there is some potential for modest power savings, real world systems need to improved responsiveness to adjustments in order to fully leverage these savings. This page intentionally left blank.
Individual heterogeneity generating explosive system network dynamics.
Manrique, Pedro D; Johnson, Neil F
2018-03-01
Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.
Individual heterogeneity generating explosive system network dynamics
Manrique, Pedro D.; Johnson, Neil F.
2018-03-01
Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.
Analysis of Dynamic Properties of Piezoelectric Structure under Impact Load
Directory of Open Access Journals (Sweden)
Taotao Zhang
2015-10-01
Full Text Available An analytical model of the dynamic properties is established for a piezoelectric structure under impact load, without considering noise and perturbations in this paper. Based on the general theory of piezo-elasticity and impact mechanics, the theoretical solutions of the mechanical and electrical fields of the smart structure are obtained with the standing and traveling wave methods, respectively. The comparisons between the two methods have shown that the standing wave method is better for studying long-time response after an impact load. In addition, good agreements are found between the theoretical and the numerical results. To simulate the impact load, both triangle and step pulse loads are used and comparisons are given. Furthermore, the influence of several parameters is discussed so as to provide some advices for practical use. It can be seen that the proposed analytical model would benefit, to some extent, the design and application (especially the airport runway of the related smart devices by taking into account their impact load performance.
Dynamic Loading of Carrara Marble in a Heated State
Wong, Louis Ngai Yuen; Li, Zhihuan; Kang, Hyeong Min; Teh, Cee Ing
2017-06-01
Useable land is a finite space, and with a growing global population, countries have been exploring the use of underground space as a strategic resource to sustain the growth of their society and economy. However, the effects of impact loading on rocks that have been heated, and hence the integrity of the underground structure, are still not fully understood and has not been included in current design standards. Such scenarios include traffic accidents and explosions during an underground fire. This study aims to provide a better understanding of the dynamic load capacity of Carrara marble at elevated temperatures. Dynamic uniaxial compression tests are performed on Carrara marble held at various temperatures using a split-Hopkinson Pressure Bar (SHPB) setup with varying input force. A customized oven is included in the SHPB setup to allow for testing of the marble specimens in a heated state. After the loading test, a three-wave analysis is performed to obtain the dynamic stress-strain curve of the specimen under loading. The fragments of the failed specimens were also collected and dry-sieved to obtain the particle size distribution. The results reveal that the peak stress of specimens that have been heated is negatively correlated with the heating temperature. However, the energy absorbed by the specimens at peak stress at all temperatures is similar, indicating that a significant amount of energy is dissipated via plastic deformation. Generally, fragment size is also found to show a negative correlation with heating temperature and loading pressure. However, in some cases this relationship does not hold true, probably due to the occurrence of stress shadowing. Linear Elastic Fracture Mechanics has been found to be generally applicable to specimens tested at low temperatures; but at higher temperatures, Elastic-Plastic Fracture Mechanics will give a more accurate prediction. Another contribution of this study is to show that other than the peak stress of the
Westberg, Lars; Eriksson, Anders; Karagiannis, Georgios; Heijenk, Geert; Rexhepi, Vlora; Partain, David
2001-01-01
A method and network subsystem for providing on demand end to end Quality of Service (Qos) in a dynamic manner, use a combination of Resource Reservation Protocol (RSVP), load control protocol (and its successors) and Bandwidth Brokers (BBs)(1106) which communicate using a predetermined protocol.
Westberg, Lars; Eriksson, Anders; Karagiannis, Georgios; Heijenk, Geert; Rexhepi, Vlora; Partain, David
2009-01-01
A method and network subsystem for providing on demand end to end Quality of Service (Qos) in a dynamic manner, use a combination of Resource Reservation Protocol (RSVP), load control protocol (and its successors) and Bandwidth Brokers (BBs)(1106) which communicate using a predetermined protocol.
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
Dynamic control of a bistable wing under aerodynamic loading
International Nuclear Information System (INIS)
Bilgen, Onur; Arrieta, Andres F; Friswell, Michael I; Hagedorn, Peter
2013-01-01
The aerodynamic evaluation of a dynamic control technique applied to a bistable unsymmetrical cross-ply composite plate with surface bonded piezoelectric actuators is presented. The plate is clamped on one end to form a low-aspect-ratio wing. A previously proposed dynamic control method, utilizing bending resonance in different stable equilibrium positions, is used to induce snap-through between the two equilibrium states. Compared to quasi-static actuation, driving the bistable plate near resonance using surface bonded piezoelectric materials requires, theoretically, a lower peak excitation voltage to achieve snap-through. First, a set of extensive wind tunnel experiments are conducted on the passive bistable wing to understand the change in the dynamic behavior under various aerodynamic conditions. The passive wing demonstrated sufficient bending stiffness to sustain its shape under aerodynamic loading while preserving the desired bistable behavior. Next, by the use of the resonant control technique, the plate is turned into an effectively monostable structure, or alternatively, both stable equilibrium positions can be reached actively from the other stable equilibrium. Dynamic forward and reverse snap-through is demonstrated in the wind tunnel which shows both the effectiveness of the piezoelectric actuation as well as the load carrying capability of both states of the bistable wing. (paper)
Innovation networking between stability and political dynamics
DEFF Research Database (Denmark)
Koch, Christian
2004-01-01
of the contribution is to challenge and transcend these notions and develop an understanding of innovation networks as an interplay between stable and dynamic elements, where political processes in innovation are much more than a disruptive and even a counterproductive feature. It reviews the growing number...... of studies that highlight the political aspect of innovation. The paper reports on a study of innovation processes conducted within the EU—TSER-programme and a study made under the banner of management of technology. Intensive field studies in two constellations of enterprises were carried out. One......This contribution views innovation as a social activity of building networks, using software product development in multicompany alliances and networks as example. Innovation networks are frequently understood as quite stable arrangements characterised by high trust among the participants. The aim...
Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.
Ong, Toan C; Kahn, Michael G; Kwan, Bethany M; Yamashita, Traci; Brandt, Elias; Hosokawa, Patrick; Uhrich, Chris; Schilling, Lisa M
2017-09-13
Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., "health data domain experts") and target common data model. D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical
Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation
Shi, Feng
Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as
Nonparametric inference of network structure and dynamics
Peixoto, Tiago P.
The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among
Volunteerism: Social Network Dynamics and Education
Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.
2016-01-01
Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570
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.
Decrease of dynamic loads in mobile energy means
Polivaev, O. I.; Gorban, L. K.; Vorohobin, A. V.; Vedrinsky, O. S.
2018-03-01
The increase in the productivity of machine and tractor units is possible due to the increase in operating speeds, this leads to the emergence of increased dynamic loads in the system “engine-transmission-propulsion unit-soil”, which worsens the performance of machine-tractor aggregates. To reduce fluctuations in the “engine-transmission” system, special vibration dampers are used, which installed in close proximity to the engine and protect well the transmission from uneven engine operation; however, such dampers practically do not eliminate the oscillations of external loads. Reducing dynamic loads on the transmission and the mobile power engine (MPE) is an important issue directly related to improving the performance, reliability and durability of the tractor, as well as reducing the slippage of the drive wheels. In order to reduce effectively dynamic loads on the transmission and on the MPE, it is necessary to introduce resilient damping elements closer to the sources of oscillations, namely, to the driving wheels. At the same time, the elastic-damping element should provide accumulation of vibration energy caused by external influences and have a large energy capacity. The installation of an elastic-damping element in the final link of the tractor transmission ensures a reduction in the magnitude of external influences, thereby protecting the engine and transmission from large dynamic loads, and allows one to reduce the slippage of the propellers, which has a positive effect on the traction and energy characteristics of the tractor. Traction tests of the LTP-55 tractor on a concrete road showed that the use of an elasto-damping drive makes it possible to increase the maximum tractive power from 33.5 to 35.3 kW and to reduce the slipping of propellers by 12-30%, the specific fuel consumption by 6-10%. When driving on stubble, the use of an elastic-damping drive increases the maximum tractive power from 25 to 26 kW, reduces the skidding of propellers by
Dynamic social networks based on movement
Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.
2016-01-01
Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.
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.
Dynamic motifs in socio-economic networks
Zhang, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo
2014-12-01
Socio-economic networks are of central importance in economic life. We develop a method of identifying and studying motifs in socio-economic networks by focusing on “dynamic motifs,” i.e., evolutionary connection patterns that, because of “node acquaintances” in the network, occur much more frequently than random patterns. We examine two evolving bi-partite networks: i) the world-wide commercial ship chartering market and ii) the ship build-to-order market. We find similar dynamic motifs in both bipartite networks, even though they describe different economic activities. We also find that “influence” and “persistence” are strong factors in the interaction behavior of organizations. When two companies are doing business with the same customer, it is highly probable that another customer who currently only has business relationship with one of these two companies, will become customer of the second in the future. This is the effect of influence. Persistence means that companies with close business ties to customers tend to maintain their relationships over a long period of time.
Mean field methods for cortical network dynamics
DEFF Research Database (Denmark)
Hertz, J.; Lerchner, Alexander; Ahmadi, M.
2004-01-01
We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate- and-fire neurons, we can show how the firing irregularity, as measured by the Fano factor, increases...... with the strength of the synapses in the network and with the value to which the membrane potential is reset after a spike. Generalizing the model to include conductance-based synapses gives insight into the connection between the firing statistics and the high- conductance state observed experimentally in visual...
MONOMIALS AND BASIN CYLINDERS FOR NETWORK DYNAMICS.
Austin, Daniel; Dinwoodie, Ian H
We describe methods to identify cylinder sets inside a basin of attraction for Boolean dynamics of biological networks. Such sets are used for designing regulatory interventions that make the system evolve towards a chosen attractor, for example initiating apoptosis in a cancer cell. We describe two algebraic methods for identifying cylinders inside a basin of attraction, one based on the Groebner fan that finds monomials that define cylinders and the other on primary decomposition. Both methods are applied to current examples of gene networks.
International Nuclear Information System (INIS)
Mock, Raymond Cecil; Nash, Thomas J.; Sanford, Thomas W. L.
2007-01-01
We present designs for dynamic hohlraum z-pinch loads on the 28 MA, 140 ns driver ZR. The scaling of axially radiated power with current in dynamic hohlraums is reviewed. With adequate stability on ZR this scaling indicates that 30 TW of axially radiated power should be possible. The performance of the dynamic hohlraum load on the 20 MA, 100 ns driver Z is extensively reviewed. The baseline z-pinch load on Z is a nested tungsten wire array imploding onto on-axis foam. Data from a variety of x-ray diagnostics fielded on Z are presented. These diagnostics include x-ray diodes, bolometers, fast x-ray imaging cameras, and crystal spectrometers. Analysis of these data indicates that the peak dynamic radiation temperature on Z is between 250 and 300 eV from a diameter less than 1 mm. Radiation from the dynamic hohlraum itself or from a radiatively driven pellet within the dynamic hohlraum has been used to probe a variety of matter associated with the dynamic hohlraum: the tungsten z-pinch itself, tungsten sliding across the end-on apertures, a titanium foil over the end aperture, and a silicon aerogel end cap. Data showing the existence of asymmetry in radiation emanating from the two ends of the dynamic hohlraum is presented, along with data showing load configurations that mitigate this asymmetry. 1D simulations of the dynamic hohlraum implosion are presented and compared to experimental data. The simulations provide insight into the dynamic hohlraum behavior but are not necessarily a reliable design tool because of the inherently 3D behavior of the imploding nested tungsten wire arrays
Dynamic load-balancing-extended gradient mechanism: Graphic representation
Energy Technology Data Exchange (ETDEWEB)
Muniz, Francisco J., E-mail: muniz@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2017-07-01
Load-balancing methods are quite well described in the open literature (hundreds of articles can be found about this subject). In particularly, about the Dynamic Load-balancing mechanism Extended Gradient (EG), several articles of the author are available. Even though, there are some overlap, each one of them is focused on a particular aspect of the mechanism, in a complementary way. In this article, a graphic representation of the Extended Gradient mechanism is done: this representation way had not yet been explored. However, for an in-depth knowledge of the Extended Gradient mechanism, at least, some other articles should to be read. In the CDTN, Clusters are used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)
Dynamic load-balancing-extended gradient mechanism: Graphic representation
International Nuclear Information System (INIS)
Muniz, Francisco J.
2017-01-01
Load-balancing methods are quite well described in the open literature (hundreds of articles can be found about this subject). In particularly, about the Dynamic Load-balancing mechanism Extended Gradient (EG), several articles of the author are available. Even though, there are some overlap, each one of them is focused on a particular aspect of the mechanism, in a complementary way. In this article, a graphic representation of the Extended Gradient mechanism is done: this representation way had not yet been explored. However, for an in-depth knowledge of the Extended Gradient mechanism, at least, some other articles should to be read. In the CDTN, Clusters are used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)
Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions
Energy Technology Data Exchange (ETDEWEB)
Fattebert, J.-L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Richards, D.F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Glosli, J.N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2012-12-01
We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10^{6} particles on 65,536 MPI tasks.
Dynamic Trust Management for Mobile Networks and Its Applications
Bao, Fenye
2013-01-01
Trust management in mobile networks is challenging due to dynamically changing network environments and the lack of a centralized trusted authority. In this dissertation research, we "design" and "validate" a class of dynamic trust management protocols for mobile networks, and demonstrate the utility of dynamic trust management…
Network dynamics: The World Wide Web
Adamic, Lada Ariana
Despite its rapidly growing and dynamic nature, the Web displays a number of strong regularities which can be understood by drawing on methods of statistical physics. This thesis finds power-law distributions in website sizes, traffic, and links, and more importantly, develops a stochastic theory which explains them. Power-law link distributions are shown to lead to network characteristics which are especially suitable for scalable localized search. It is also demonstrated that the Web is a "small world": to reach one site from any other takes an average of only 4 hops, while most related sites cluster together. Additional dynamical properties of the Web graph are extracted from diffusion processes.
Functional asynchronous networks: Factorization of dynamics and function
Directory of Open Access Journals (Sweden)
Bick Christian
2016-01-01
Full Text Available In this note we describe the theory of functional asynchronous networks and one of the main results, the Modularization of Dynamics Theorem, which for a large class of functional asynchronous networks gives a factorization of dynamics in terms of constituent subnetworks. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network and thereby answer a question originally raised by Alon in the context of biological networks.
Manolis, George
2017-01-01
This book provides state of the art coverage of important current issues in the analysis, measurement, and monitoring of the dynamic response of infrastructure to environmental loads, including those induced by earthquake motion and differential soil settlement. The coverage is in five parts that address numerical methods in structural dynamics, soil–structure interaction analysis, instrumentation and structural health monitoring, hybrid experimental mechanics, and structural health monitoring for bridges. Examples that give an impression of the scope of the topics discussed include the seismic analysis of bridges, soft computing in earthquake engineering, use of hybrid methods for soil–structure interaction analysis, effects of local site conditions on the inelastic dynamic analysis of bridges, embedded models in wireless sensor networks for structural health monitoring, recent developments in seismic simulation methods, and seismic performance assessment and retrofit of structures. Throughout, the empha...
Activating and inhibiting connections in biological network dynamics
Directory of Open Access Journals (Sweden)
Knight Rob
2008-12-01
Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.
System crash as dynamics of complex networks.
Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim
2016-10-18
Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
Application of high-resolution domestic electricity load profiles in network modelling
DEFF Research Database (Denmark)
Marszal, Anna Joanna; Mendaza, Iker Diaz de Cerio; Heiselberg, Per Kvols
2016-01-01
the generated profiles are inputted in a low-voltage network model created in DIgSILENT PowerFactory. By means of employing 1 hour based demand and generation profiles in during dynamic studies, the representation of the local power system performance might sometimes not be as accurate as needed. In the test...... with modeling when 1-minute domestic electricity demand and generation profiles are used as inputs. The analysis is done with a case study of low-voltage network located in Northern Denmark. The analysis includes two parts. The first part focuses on modeling the domestic demands and on-site generation in 1......-minute resolution. The load profiles of the household appliances are created using a bottom-up model, which uses the 1-minute cycle power use characteristics of a single appliance as the main building block. The profiles of heavy electric appliances, such as heat pump, are not included in the above...
Organization of excitable dynamics in hierarchical biological networks.
Directory of Open Access Journals (Sweden)
Mark Müller-Linow
Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.
Dynamics of domain wall networks with junctions
International Nuclear Information System (INIS)
Avelino, P. P.; Oliveira, J. C. R. E.; Martins, C. J. A. P.; Menezes, J.; Menezes, R.
2008-01-01
We use a combination of analytic tools and an extensive set of the largest and most accurate three-dimensional field theory numerical simulations to study the dynamics of domain wall networks with junctions. We build upon our previous work and consider a class of models which, in the limit of large number N of coupled scalar fields, approaches the so-called ''ideal'' model (in terms of its potential to lead to network frustration). We consider values of N between N=2 and N=20, and a range of cosmological epochs, and we also compare this class of models with other toy models used in the past. In all cases we find compelling evidence for a gradual approach to scaling, strongly supporting our no-frustration conjecture. We also discuss the various possible types of junctions (including cases where there is a hierarchy of them) and their roles in the dynamics of the network. Finally, we provide a cosmological Zel'dovich-type bound on the energy scale of this kind of defect network: it must be lower than 10 keV.
Dynamics of the ethanolamine glycerophospholipid remodeling network.
Directory of Open Access Journals (Sweden)
Lu Zhang
Full Text Available Acyl chain remodeling in lipids is a critical biochemical process that plays a central role in disease. However, remodeling remains poorly understood, despite massive increases in lipidomic data. In this work, we determine the dynamic network of ethanolamine glycerophospholipid (PE remodeling, using data from pulse-chase experiments and a novel bioinformatic network inference approach. The model uses a set of ordinary differential equations based on the assumptions that (1 sn1 and sn2 acyl positions are independently remodeled; (2 remodeling reaction rates are constant over time; and (3 acyl donor concentrations are constant. We use a novel fast and accurate two-step algorithm to automatically infer model parameters and their values. This is the first such method applicable to dynamic phospholipid lipidomic data. Our inference procedure closely fits experimental measurements and shows strong cross-validation across six independent experiments with distinct deuterium-labeled PE precursors, demonstrating the validity of our assumptions. In contrast, fits of randomized data or fits using random model parameters are worse. A key outcome is that we are able to robustly distinguish deacylation and reacylation kinetics of individual acyl chain types at the sn1 and sn2 positions, explaining the established prevalence of saturated and unsaturated chains in the respective positions. The present study thus demonstrates that dynamic acyl chain remodeling processes can be reliably determined from dynamic lipidomic data.
Network structure shapes spontaneous functional connectivity dynamics.
Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R
2015-04-08
The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.
Load forecasting method considering temperature effect for distribution network
Directory of Open Access Journals (Sweden)
Meng Xiao Fang
2016-01-01
Full Text Available To improve the accuracy of load forecasting, the temperature factor was introduced into the load forecasting in this paper. This paper analyzed the characteristics of power load variation, and researched the rule of the load with the temperature change. Based on the linear regression analysis, the mathematical model of load forecasting was presented with considering the temperature effect, and the steps of load forecasting were given. Used MATLAB, the temperature regression coefficient was calculated. Using the load forecasting model, the full-day load forecasting and time-sharing load forecasting were carried out. By comparing and analyzing the forecast error, the results showed that the error of time-sharing load forecasting method was small in this paper. The forecasting method is an effective method to improve the accuracy of load forecasting.
Effect of support conditions on structural response under dynamic loading
International Nuclear Information System (INIS)
Akram, T.; Memon, S.A.
2008-01-01
In design practice, dynamic structural analysis is carried out with base of structure considered as fixed; this means that foundation is placed on rock like soil material. While conducting this type of analyses the role of foundation and soil behaviour is totally neglected. The actions in members and loads transferred at foundation level obtained in this manner do not depict the true structural behaviour. FEM (Finite Element Methods) analysis where both superstructure and foundation soil are coupled together is quite complicated and expensive for design environments. A simplified model is required to depict dynamic response of structures with foundations based on flexible soils. The primary purpose of this research is to compare the superstructure dynamic responses of structural systems with fixed base to that of simple soil model base. The selected simple soil model is to be suitable for use in a design environment to give more realistic results. For this purpose building models are idealized with various heights and structural systems in both 2D (Two Dimensional) and 3D (Three Dimensional) space. These models are then provided with visco-elastic supports representing three soil bearing capacities and the analysis results are compared to that of fixed supports models. The results indicate that fixed support system underestimates natural time period of the structures. Dynamic behavior and force response of visco-elastic support is different from fixed support model. Fixed support models result in over designed base columns and under designed beams. (author)
Dynamic loads on reactor vessel components by low pressure waves
International Nuclear Information System (INIS)
Benkert, J.; Mika, C.; Stegemann, D.; Valero, M.
1978-01-01
Starting from the conservation theorems for mass and impulses the code DRUWE has been developed enabling the calculation of dynamic loads of the reactor shell on the basis of simplified assumptions for the first period shortly after rupture. According to the RSK-guidelines it can be assumed that the whole weld size is opened within 15 msec. This time-dependent opening of the fractured plane can be taken into account in the computer program. The calculation is composed in a way that for a reactor shell devided into cross and angle sections the local, chronological pressure and strength curves, the total dynamic load as well as the moments acting on the fastenings of the reactor shell can be calculated. As input data only geometrical details concerning the concept of the pressure vessel and its components as well as the effective subcooling of the fluid are needed. By means of several parameters the program can be operated in a way that the results are available in form of listings or diagrams, respectively, but also as card pile for further examinations, e.g. strength analysis. (orig./RW) [de
Jablonski, Piotr; Poe, Gina; Zochowski, Michal
2007-03-01
The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.
Discrete Opinion Dynamics on Online Social Networks
Hu, Yan-Li; Bai, Liang; Zhang, Wei-Ming
2013-01-01
This paper focuses on the dynamics of binary opinions {+1, -1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks.
Discrete Opinion Dynamics on Online Social Networks
International Nuclear Information System (INIS)
Hu Yan-Li; Bai Liang; Zhang Wei-Ming
2013-01-01
This paper focuses on the dynamics of binary opinions {+1, −1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks. (general)
Physical Proximity and Spreading in Dynamic Social Networks
Stopczynski, Arkadiusz; Pentland, Alex Sandy; Lehmann, Sune
2015-01-01
Most infectious diseases spread on a dynamic network of human interactions. Recent studies of social dynamics have provided evidence that spreading patterns may depend strongly on detailed micro-dynamics of the social system. We have recorded every single interaction within a large population, mapping out---for the first time at scale---the complete proximity network for a densely-connected system. Here we show the striking impact of interaction-distance on the network structure and dynamics ...
Pushing the network harder `Dynamic Ratings`
Energy Technology Data Exchange (ETDEWEB)
Liondas, V.; Howatt, C.; Norrie, P. [Prospect Electricity, Blacktown, NSW (Australia)
1995-12-31
The demand for electricity in the area serviced by Prospect Electricity, is increasing, necessitating an increase in power transfer through the distribution system. Satisfying this demand generally requires more electrical infrastructure, but this is becoming less feasible due to economic constraints and environmental considerations. This paper discusses an approach to the dynamic (or real time) rating of different network elements. Dynamic rating is taken to mean that rating which is determined essentially in real time using known temperature constraints for the relevant elements, together with the prevailing ambient or environmental conditions. The purpose of dynamic rating is to achieve greater system utilization, thus allowing significant economic benefits, particularly from deferment of capital expenditure and greater operational flexibility. A number of technologies are being developed to do this for overhead lines, underground cables and transformers. The dynamic rating of cables has proved to be the most intractable part of the dynamic rating project. Work done to date, however, using finite element techniques together with the proposals to further develop point and distributed temperature sensing using fibre optic methods gives some confidence to the future success of this development. (author). 2 tabs., 4 figs., 4 refs.
Opinion dynamics on an adaptive random network
Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.
2009-04-01
We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.
Collective Dynamics in Physical and Social Networks
Isakov, Alexander
We study four systems where individual units come together to display a range of collective behavior. First, we consider a physical system of phase oscillators on a network that expands the Kuramoto model to include oscillator-network interactions and the presence of noise: using a Hebbian-like learning rule, oscillators that synchronize in turn strengthen their connections to each other. We find that the average degree of connectivity strongly affects rates of flipping between aligned and anti-aligned states, and that this result persists to the case of complex networks. Turning to a fully multi-player, multi-strategy evolutionary dynamics model of cooperating bacteria that change who they give resources to and take resources from, we find several regimes that give rise to high levels of collective structure in the resulting networks. In this setting, we also explore the conditions in which an intervention that affects cooperation itself (e.g. "seeding the network with defectors") can lead to wiping out an infection. We find a non-monotonic connection between the percent of disabled cooperation and cure rate, suggesting that in some regimes a limited perturbation can lead to total population collapse. At a larger scale, we study how the locomotor system recovers after amputation in fruit flies. Through experiment and a theoretical model of multi-legged motion controlled by neural oscillators, we find that proprioception plays a role in the ability of flies to control leg forces appropriately to recover from a large initial turning bias induced by the injury. Finally, at the human scale, we consider a social network in a traditional society in Africa to understand how social ties lead to group formation for collective action (stealth raids). We identify critical and distinct roles for both leadership (important for catalyzing a group) and friendship (important for final composition). We conclude with prospects for future work.
Dynamics of neural networks with continuous attractors
Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si
2008-10-01
We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus.
Multinephron dynamics on the renal vascular network
DEFF Research Database (Denmark)
Marsh, Donald J; Wexler, Anthony S; Brazhe, Alexey
2012-01-01
Tubuloglomerular feedback (TGF) and the myogenic mechanism combine in each nephron to regulate blood flow and glomerular filtration rate. Both mechanisms are non-linear, generate self-sustained oscillations, and interact as their signals converge on arteriolar smooth muscle, forming a regulatory...... clusters. In-phase synchronization predominated among nephrons separated by 1 or 3 vascular nodes, and anti-phase synchronization for 5 or 7 nodes of separation. Nephron dynamics were irregular and contained low frequency fluctuations. Results are consistent with simultaneous blood flow measurements...... of both mechanisms in the regulatory ensemble, to examine the effects of network structure on nephron synchronization. Symmetry, as a property of a network, facilitates synchronization. Nephrons received blood from a symmetric electrically conductive vascular tree. Symmetry was created by using identical...
A class of convergent neural network dynamics
Fiedler, Bernold; Gedeon, Tomáš
1998-01-01
We consider a class of systems of differential equations in Rn which exhibits convergent dynamics. We find a Lyapunov function and show that every bounded trajectory converges to the set of equilibria. Our result generalizes the results of Cohen and Grossberg (1983) for convergent neural networks. It replaces the symmetry assumption on the matrix of weights by the assumption on the structure of the connections in the neural network. We prove the convergence result also for a large class of Lotka-Volterra systems. These are naturally defined on the closed positive orthant. We show that there are no heteroclinic cycles on the boundary of the positive orthant for the systems in this class.
International Nuclear Information System (INIS)
Serban, Viorel; Chirita, Alexandru Mihai; Androne, Marian; Alexandru, Constantin; Ciuca, Camelia; Badara, Janina; Alexandru, Carmen
1995-01-01
The paper presents the analytic methods for estimating the dynamic effects induced in pipe systems in transient regimes. They are based on computation programs developed in order to check the behaviour of ECCS and EWS under 'water hammer effect' and the behaviour of the primary circuit system under stresses caused by pipe cracks. Computation examples are presented in order to emphasize the capabilities of the programs to model transient phenomena in complex pipe networks. The overpressure induced by the water hammer effect, as revealed by comparing several transient regimes, depends on the fluid viscosity, the initial speed, the duration of starting the transient regime, the system rigidity, etc. Values several ten times higher that the initial one could be thus reached. An overview of new types of devices designed for damping the effect of water hammer phenomenon, as well as of sustaining supports for pipe systems and equipment able to damp the vibrations produced by the transient regimes of fluid flows and seismic movements is presented. These devices have also to cope with the high shocks produced by pipe breakage as well as high static loads. The paper contains the following sections: 1. Introduction; 2. Evaluating dynamic loads associated to the water hammer phenomenon; 3. Determining loads associated to the water hammer phenomenon for the ECC system of the Cernavoda NPP Unit 1; 4. Device for reducing the water hammer effects; 5. Evaluating dynamic loads associated to pipe cracks; 6. Determining loads associated to pipe cracks in the Cernavoda NPP primary circuit; 7. Devices for absorbing and damping the dynamic loads in pipe systems and equipment; 8. Conclusions. (authors)
Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling
International Nuclear Information System (INIS)
Wang Lifu; Kong Zhi; Jing Yuanwei
2010-01-01
This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)
Content Dynamics Over the Network Cloud
2015-11-04
AFRL-AFOSR-CL-TR-2015-0003 Content dynamics over the network cloud Fernando Paganini UNIVERSIDAD ORT URUGUAY CUAREIM 1451 MONTEVIDEO, 11100 UY 11/04...approved for public release. FINAL PERFORMANCE REPORT: 7-15-2012 to 7-14-2015 AFOSR GRANT NUMBER: FA9550-12-1-0398 PI: Fernando Paganini Universidad ORT...349-362, Apr 2014. 7. M. Zubeldía, “From resource allocation to neighbor selection in peer-to-peer networks”, MS Thesis, Universidad ORT Uruguay
Load reduction test method of similarity theory and BP neural networks of large cranes
Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening
2016-01-01
Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.
Reliable dynamics in Boolean and continuous networks
International Nuclear Information System (INIS)
Ackermann, Eva; Drossel, Barbara; Peixoto, Tiago P
2012-01-01
We investigate the dynamical behavior of a model of robust gene regulatory networks which possess ‘entirely reliable’ trajectories. In a Boolean representation, these trajectories are characterized by being insensitive to the order in which the nodes are updated, i.e. they always go through the same sequence of states. The Boolean model for gene activity is compared with a continuous description in terms of differential equations for the concentrations of mRNA and proteins. We found that entirely reliable Boolean trajectories can be reproduced perfectly in the continuous model when realistic Hill coefficients are used. We investigate to what extent this high correspondence between Boolean and continuous trajectories depends on the extent of reliability of the Boolean trajectories, and we identify simple criteria that enable the faithful reproduction of the Boolean dynamics in the continuous description. (paper)
Green IGP Link Weights for Energy-efficiency and Load-balancing in IP Backbone Networks
Francois, Frederic; Wang, Ning; Moessner, Klaus; Georgoulas, Stylianos; Xu, Ke
2013-01-01
The energy consumption of backbone networks has become a primary concern for network operators and regulators due to the pervasive deployment of wired backbone networks to meet the requirements of bandwidth-hungry applications. While traditional optimization of IGP link weights has been used in IP based load-balancing operations, in this paper we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency ...
Directory of Open Access Journals (Sweden)
Ирина Александровна Гавриленко
2016-02-01
Full Text Available The approach to automated management of load flow in engineering networks considering functional reliability was proposed in the article. The improvement of the concept of operational and strategic management of load flow in engineering networks was considered. The verbal statement of the problem for thesis research is defined, namely, the problem of development of information technology for exact calculation of the functional reliability of the network, or the risk of short delivery of purpose-oriented product for consumers
Prediction-based dynamic load-sharing heuristics
Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.
1993-01-01
The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.
Dynamic Stability of Columns Subjected to Follower Loads: a Survey
LANGTHJEM, M. A.; SUGIYAMA, Y.
2000-12-01
This paper offers a survey of simple, flexible structural elements subjected to non-conservative follower loads, such as those caused by the thrust of rocket- and jet engines, and by dry friction in automotive disk- and drum-brake systems. Emphasis is on the “canonical problems”, Beck's, Reut's, Leipholz's, and Hauger's columns. Beck's and Reut's columns have been realized experimentally, and very good agreement between theory and experiments has been found. Leipholz's column is basically realized in an automobile brake system, where noise due to dynamic or parametric instability (brake squeal) is a well-known environmental problem. It is attempted to give a broad overview, with emphasis on experimental works and the associated theoretical problems. Structural optimization is also included in the review, as many studies in that area have served an important purpose in the development of optimization techniques for practical, large-scale optimization problems with non-conservative forces, such as in aeroelasticity.
Planar dynamics of large-deformation rods under moving loads
Zhao, X. W.; van der Heijden, G. H. M.
2018-01-01
We formulate the problem of a slender structure (a rod) undergoing large deformation under the action of a moving mass or load motivated by inspection robots crawling along bridge cables or high-voltage power lines. The rod is described by means of geometrically exact Cosserat theory which allows for arbitrary planar flexural, extensional and shear deformations. The equations of motion are discretised using the generalised-α method. The formulation is shown to handle the discontinuities of the problem well. Application of the method to a cable and an arch problem reveals interesting nonlinear phenomena. For the cable problem we find that large deformations have a resonance detuning effect on cable dynamics. The problem also offers a compelling illustration of the Timoshenko paradox. For the arch problem we find a stabilising (delay) effect on the in-plane collapse of the arch, with failure suppressed entirely at sufficiently high speed.
Prediction of dynamic blade loading of the Francis-99 turbine
International Nuclear Information System (INIS)
Nicolle, J; Cupillard, S
2015-01-01
CFD simulations focusing on capturing dynamic fluctuations of the flow for three operating points were performed for a scale model of a high head Francis turbine. A mesh sensitivity study showed an influence of the near wall resolution, consequently a low Reynolds mesh with a SST turbulence model was used. Rotor/stator fluctuations are well reproduced with the full turbine simulation at all operating points. Velocity contours and average velocity profiles from LDV measurements in the draft tube confirm that the flow physics is generally well reproduced. Simplified approaches such as profile transform and Fourier transform underestimated the measured fluctuations. As full turbine simulations were time-consuming, a simulation with only the draft tube was performed at part load to predict the fluctuations in the draft tube cone. The SAS-SST turbulence model was able to capture the vortex rope behavior
Dynamics and mechanics of bed-load tracer particles
Directory of Open Access Journals (Sweden)
C. B. Phillips
2014-12-01
Full Text Available Understanding the mechanics of bed load at the flood scale is necessary to link hydrology to landscape evolution. Here we report on observations of the transport of coarse sediment tracer particles in a cobble-bedded alluvial river and a step-pool bedrock tributary, at the individual flood and multi-annual timescales. Tracer particle data for each survey are composed of measured displacement lengths for individual particles, and the number of tagged particles mobilized. For single floods we find that measured tracer particle displacement lengths are exponentially distributed; the number of mobile particles increases linearly with peak flood Shields stress, indicating partial bed load transport for all observed floods; and modal displacement distances scale linearly with excess shear velocity. These findings provide quantitative field support for a recently proposed modeling framework based on momentum conservation at the grain scale. Tracer displacement is weakly negatively correlated with particle size at the individual flood scale; however cumulative travel distance begins to show a stronger inverse relation to grain size when measured over many transport events. The observed spatial sorting of tracers approaches that of the river bed, and is consistent with size-selective deposition models and laboratory experiments. Tracer displacement data for the bedrock and alluvial channels collapse onto a single curve – despite more than an order of magnitude difference in channel slope – when variations of critical Shields stress and flow resistance between the two are accounted for. Results show how bed load dynamics may be predicted from a record of river stage, providing a direct link between climate and sediment transport.
DECREASING OF MECHANISMS DYNAMIC LOADING AT THE TRANSIENT STATE
Directory of Open Access Journals (Sweden)
V. S. Loveikin
2015-11-01
Full Text Available Purpose. It is necessary to select modes of motion to reduce the dynamic loads in the mechanisms. This choice should be made on optimization basis. The purpose of research is to study methods of synthesis regimes of mechanisms and machines motion that provide optimal modes of movement for terminal and integral criteria. Methodology. For research the one-mass dynamic model of the mechanism has been used. As optimization criteria the terminal and comprehensive integral criteria were used. The stated optimization problem has been solved using dynamic programming and variational calculation. The direct variation method, which allowed finding only approximate solution of the original problem of optimal control, has been used as well. Findings. The ways of ensuring the absolute minimum of terminal criterion have been set for each method of problem solving. The stated characteristics show softness changes of kinematic functions during braking of mechanism. They point to the absolute minimum of adopted terminal criterion in the calculation. Originality. It is necessary to introduce new variables in the system equations during the solving of optimal control problems using dynamic programming to achieve an absolute minimum of terminal criteria. In general, to achieve a minimum of n-order terminal criterion an optimization problem should find relatively (n+1-th order function. When optimization problems is solving by variational calculation in order to ensure a minimization of n-th order terminal criterion by selecting the appropriate boundary conditions, it is necessary to solve the Euler-Poisson 2(n+1-th order equation (subject to symmetric setting boundary conditions. It is a necessary condition for an extremum of the functional with the (n+1-th order integrant. Practical value. Minimizing of adopted terminal criterion in the calculation allows eliminate the brunt in kinematic gearing of mechanisms, which increases their operational life. In addition
Chain networking revealed by molecular dynamics simulation
Zheng, Yexin; Tsige, Mesfin; Wang, Shi-Qing
Based on Kremer-Grest model for entangled polymer melts, we demonstrate how the response of a polymer glass depends critically on the chain length. After quenching two melts of very different chain lengths (350 beads per chain and 30 beads per chain) into deeply glassy states, we subject them to uniaxial extension. Our MD simulations show that the glass of long chains undergoes stable necking after yielding whereas the system of short chains is unable to neck and breaks up after strain localization. During ductile extension of the polymer glass made of long chain significant chain tension builds up in the load-bearing strands (LBSs). Further analysis is expected to reveal evidence of activation of the primary structure during post-yield extension. These results lend support to the recent molecular model 1 and are the simulations to demonstrate the role of chain networking. This work is supported, in part, by a NSF Grant (DMR-EAGER-1444859)
Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle
Directory of Open Access Journals (Sweden)
Ram Prahlad T
2008-08-01
Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models
Predicting Dynamic Response of Structures under Earthquake Loads Using Logical Analysis of Data
Directory of Open Access Journals (Sweden)
Ayman Abd-Elhamed
2018-04-01
Full Text Available In this paper, logical analysis of data (LAD is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA. The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN, since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.
Islam, Mujahidul
from the vast network. A path tracing methodology is developed to identify the power lines that are vulnerable to an unscheduled flow effect in the sub-transmission network. It is much harder to aggregate power system network sensitivity information or data from measuring load flow physically than to simulate in software. System dynamics is one of the key factors to determine an appropriate dynamic control mechanism at an optimum network location. Once a model of deterministic but variable power generator is used, the simulation can be meaningful in justifying this claim. The method used to model the variable generator is named the two-components phase distortion model. The model was validated from the high resolution data collected from three pilot photovoltaic sites in Florida - two in the city of St. Petersburg and one in the city of Tampa. The high resolution data was correlated with weather radar closest to the sites during the design stage of the model. Technically the deterministic model cannot replicate a stochastic model which is more realistically applicable for solar isolation and involves a Markov chain. The author justified the proposition based on the fact that for analysis of the response functions of different systems, the excitation function should be common for comparison. Moreover, there could be many possible simulation scenarios but fewer worst cases. Almost all commercial systems are protected against potential faults and contingencies to a certain extent. Hence, the proposed model for worst case studies was designed within a reasonable limit. The simulation includes steady state and transient mode using multiple software modules including MatlabRTM, PSCADRTM and Paladin Design BaseRTM. It is shown that by identifying vulnerable or sensitive branches in the network, the control mechanisms can be coordinated reliably. In the long run this can save money by preventing unscheduled power flow in the network and eventually stabilizing the energy market.
EURDYN, Nonlinear Transient Analysis of Structure with Dynamic Loads
International Nuclear Information System (INIS)
Donea, J.; Giuliani, S.; Halleux, J.P.
1987-01-01
1 - Description of program or function: The EURDYN computer codes are under development at JRC-Ispra since 1973 for the simulation of non- linear dynamic response of fast-reactor components submitted to impulsive loading due to abnormal working conditions. They are thus mainly used in reactor safety analysis but can apply to other fields. Indeed the codes compute the elasto-plastic transient response of 2-D and thin 3-D structures submitted to fast dynamic loading generated by explosions, impacts... and represented by time dependent pressures, concentrated loads and prescribed displacements, or by initial speeds. Two releases of the structural computer codes EURDYN 01 (2-D beams and triangles and axisymmetric conical shells and triangular tori), 02 (axisymmetric and 2-D quadratic iso-parametric elements) and 03 (triangular plate elements) have already been produced in 1976(1) and 1980(2). They include material (elasto-plasticity using the classical flow theory approach) and geometrical (large displacements and rotations treated by a co-rotational technique) nonlinearities. The present version (Release 3) has been completed mid-1982 and is documented in EUR 8357 EN. The new features of Release 3, as compared to the former ones, roughly consist in: - full large strain capability for 9-node iso-parametric elements (EURDYN 02), - generalized array dimensions, - introduction of the radial return algorithm for elasto-plastic material modelling, - extension of the energy check facility to the case of prescribed displacements, - possible interface to a post-processing package including time plot facilities (TPLOT). The theoretical aspects can be found in refs. 2,4,5,6,7,8. 2 - Method of solution: - Finite element space discretization. - Explicit time integration. - Lumped masses. - EURDYN 01: 2-D co-rotational formulation including constant strain triangles (plane or axisymmetric), beams and conical shells, this last element being particularly useful for the study of thin
Imaging complex nutrient dynamics in mycelial networks.
Fricker, M D; Lee, J A; Bebber, D P; Tlalka, M; Hynes, J; Darrah, P R; Watkinson, S C; Boddy, L
2008-08-01
techniques shows that as the colony forms, it self-organizes into well demarcated domains that are identifiable by differences in the phase relationship of the pulses. On the centimetre to metre scale, we have begun to use techniques borrowed from graph theory to characterize the development and dynamics of the network, and used these abstracted network models to predict the transport characteristics, resilience, and cost of the network.
International Nuclear Information System (INIS)
Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S
2013-01-01
A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 – 10 kg with a sensitivity of 0.043 kg -1 . (laser optics 2012)
Stochastic dynamics of genetic broadcasting networks
Potoyan, Davit A.; Wolynes, Peter G.
2017-11-01
The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a "time-scale crisis" for master genes that broadcast their signals to a large number of binding sites. We demonstrate that this time-scale crisis for clearance in a large broadcasting network can be resolved by actively regulating residence times through molecular stripping. We illustrate these ideas by studying a model of the stochastic dynamics of the genetic network of the central eukaryotic master regulator NFκ B which broadcasts its signals to many downstream genes that regulate immune response, apoptosis, etc.
Investigation of Dynamic Friction Induced by Shock Loading Conditions
International Nuclear Information System (INIS)
Juanicotena, A.; Szarzynski, S.
2006-01-01
Modeling the frictional sliding of one surface against another under high pressure is often required to correctly describe the response of complex systems to shock loading. In order to provide data for direct code and model comparison, a new friction experiment investigating dry sliding characteristics of metal on metal at normal pressures up to 10 GPa and sliding velocities up to 400 m/s has been developed. The test consists of a specifically designed target made of two materials. A plane shock wave generated by plate impact results in one material sliding against the other. The material velocity of the rear surface of the target is recorded versus time by Doppler Laser Interferometry. The dynamic friction coefficient μ is then indirectly determined by comparison with results of numerical simulations involving the conventional Coulomb law. Using this new experimental configuration, three dynamic friction experiments were performed on AA 5083-Al (H111) / AISI 321 stainless steel tribo-pair. Results suggest a decrease in the friction coefficient with increasing sliding velocity
The Response of Simple Polymer Structures Under Dynamic Loading
Proud, William; Ellison, Kay; Yapp, Su; Cole, Cloe; Galimberti, Stefano; Institute of Shock Physics Team
2017-06-01
The dynamic response of polymeric materials has been widely studied with the effects of degree of crystallinity, strain rate, temperature and sample size being commonly reported. This study uses a simple PMMA structure, a right cylindrical sample, with structural features such as holes. The features are added an varied in a systematic fashion. Samples were dynamically loaded using a Split Hopkinson Pressure Bar up to failure. The resulting stress-strain curves are presented showing the change in sample response. The strain to failure is shown to increase initially with the presence of holes, while failure stress is relatively unaffected. The fracture patterns seen in the failed samples change, with tensile cracks, Hertzian cones, shear effects being dominant for different holes sizes and geometries. The sample were prepared by laser cutting and checked for residual stress before experiment. The data is used to validate predictive model predictions where material, structure and damage are included.. The Institute of Shock Physics acknowledges the support of Imperial College London and the Atomic Weapons Establishment.
In Situ Test Study of Characteristics of Coal Mining Dynamic Load
Directory of Open Access Journals (Sweden)
Jiang He
2015-01-01
Full Text Available Combination of coal mining dynamic load and high static stress can easily induce such dynamic disasters as rock burst, coal and gas outburst, roof fall, and water inrush. In order to obtain the characteristic parameters of mining dynamic load and dynamic mechanism of coal and rock, the stress wave theory is applied to derive the relation of mining dynamic load strain rate and stress wave parameters. The in situ test was applied to study the stress wave propagation law of coal mine dynamic load by using the SOS microseismic monitoring system. An evaluation method for mining dynamic load strain rate was proposed, and the statistical evaluation was carried out for the range of strain rate. The research results show that the loading strain rate of mining dynamic load is in direct proportion to the seismic frequency of coal-rock mass and particle peak vibration velocity and is in inverse proportion to wave velocity. The high-frequency component damps faster than the low-frequency component in the shockwave propagating process; and the peak particle vibration velocity has a power functional relationship with the transmitting distance. The loading strain rate of mining dynamic load is generally less than class 10−1/s.
Quantifying the dynamics of coupled networks of switches and oscillators.
Directory of Open Access Journals (Sweden)
Matthew R Francis
Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.
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 ...
Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application
Li, Xiang
2005-01-01
In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...
Potential of dynamic spectrum allocation in LTE macro networks
Hoffmann, H.; Ramachandra, P.; Kovács, I. Z.; Jorguseski, L.; Gunnarsson, F.; Kürner, T.
2015-11-01
In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic (i.e. the requested traffic from the users) increases the LTE deployment evolves with macro cells expanded with additional capacity boosting LTE carriers in higher frequency bands complemented with micro or small cells in traffic hotspot areas. For MNOs it is crucial to use the LTE spectrum assets, as well as the installed network infrastructure, in the most cost efficient way. The dynamic spectrum allocation (DSA) aims at (de)activating the available LTE frequency carriers according to the temporal and spatial traffic variations in order to increase the overall LTE system performance in terms of total network capacity by reducing the interference. This paper evaluates the DSA potential of achieving the envisaged performance improvement and identifying in which system and traffic conditions the DSA should be deployed. A self-optimised network (SON) DSA algorithm is also proposed and evaluated. The evaluations have been carried out in a hexagonal and a realistic site-specific urban macro layout assuming a central traffic hotspot area surrounded with an area of lower traffic with a total size of approximately 8 × 8 km2. The results show that up to 47 % and up to 40 % possible DSA gains are achievable with regards to the carried system load (i.e. used resources) for homogenous traffic distribution with hexagonal layout and for realistic site-specific urban macro layout, respectively. The SON DSA algorithm evaluation in a realistic site-specific urban macro cell deployment scenario including realistic non-uniform spatial traffic distribution shows insignificant cell throughput (i.e. served traffic) performance gains. Nevertheless, in the SON DSA investigations, a gain of up
Google matrix, dynamical attractors, and Ulam networks.
Shepelyansky, D L; Zhirov, O V
2010-03-01
We study the properties of the Google matrix generated by a coarse-grained Perron-Frobenius operator of the Chirikov typical map with dissipation. The finite-size matrix approximant of this operator is constructed by the Ulam method. This method applied to the simple dynamical model generates directed Ulam networks with approximate scale-free scaling and characteristics being in certain features similar to those of the world wide web with approximate scale-free degree distributions as well as two characteristics similar to the web: a power-law decay in PageRank that mirrors the decay of PageRank on the world wide web and a sensitivity to the value alpha in PageRank. The simple dynamical attractors play here the role of popular websites with a strong concentration of PageRank. A variation in the Google parameter alpha or other parameters of the dynamical map can drive the PageRank of the Google matrix to a delocalized phase with a strange attractor where the Google search becomes inefficient.
Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks
Directory of Open Access Journals (Sweden)
Jose P. Perez
2014-01-01
Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.
Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa
2016-01-01
Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE
Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo
2016-04-13
Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear
Directory of Open Access Journals (Sweden)
Pei-Yun Shu
2018-06-01
Full Text Available Intact rock-like specimens and specimens that include a single, smooth planar joint at various angles are prepared for split Hopkinson pressure bar (SHPB testing. A buffer pad between the striker bar and the incident bar of an SHPB apparatus is used to absorb some of the shock energy. This can generate loading rates of 20.2–4627.3 GPa/s, enabling dynamic peak stresses/strengths and associated failure patterns of the specimens to be investigated. The effects of the loading rate and angle of load applied on the dynamic peak stresses/strengths of the specimens are examined. Relevant experimental results demonstrate that the failure pattern of each specimen can be classified as four types: Type A, integrated with or without tiny flake-off; Type B, slide failure; Type C, fracture failure; and Type D, crushing failure. The dynamic peak stresses/strengths of the specimens that have similar failure patterns increase linearly with the loading rate, yielding high correlations that are evident on semi-logarithmic plots. The slope of the failure envelope is the smallest for slide failure, followed by crushing failure, and that of fracture failure is the largest. The magnitude of the plot slope of the dynamic peak stress against the loading rate for the specimens that are still integrated after testing is between that of slide failure and crushing failure. The angle of application has a limited effect on the dynamic peak stresses/strengths of the specimens regardless of the failure pattern, but it affects the bounds of the loading rates that yield each failure pattern, and thus influences the dynamic responses of the single jointed specimen. Slide failure occurs at the lowest loading rate of any failure, but can only occur in single jointed specimen that allows sliding. Crushing failure is typically associated with the largest loading rate, and fracture failure may occur when the loading rate is between the boundaries for slide failure and crushing
Dynamics of the cell-cycle network under genome-rewiring perturbations
International Nuclear Information System (INIS)
Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna
2013-01-01
The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes
Cascading failures with local load redistribution in interdependent Watts-Strogatz networks
Hong, Chen; Zhang, Jun; Du, Wen-Bo; Sallan, Jose Maria; Lordan, Oriol
2016-05-01
Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent Watts-Strogatz (WS) networks. The effects of rewiring probability and coupling strength on the resilience of interdependent WS networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness. For low values of coupling strength, the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.
Seismicity as dynamic load of pipes and fittings
International Nuclear Information System (INIS)
Rejent, B.
1984-01-01
The load is discussed of pipe systems and fittings for nuclear power plants which may result from earthquakes, etc. Modifications of the equation of motion are discussed which may be solved using the response spectrum method or the method of direct numerical integration. A mathematical description of both methods is given. The seismic resistance of fittings, pumps, etc., is experimentally determined by loking for their eigenfrequencies and monitoring the response of equipment to resonance oscillations. The principle is described of uniaxial hydraulic and mechanical shock absorbers and a viscous damper. The presented computation method was used for evaluating the primary circuit (Sigma Modrany) and rods for the remote control of fittings (Sigma Hodonin) supplied for the Mochovce nuclear power plant. Variants were compared of seismic protection of the primary circuit by hydraulic and mechanical shock absorbers with viscous dampers and of circuits without any protection. The unprotected system oscillates in the first harmonic, the system with shock absorbers keeps the deflections within the range of the shock absorber function (to 2 mm), and the system using viscous dampers oscillates approximately according to the first waveform with a deflection of around 11 mm. A diagram and a dynamic model are presented of a rod for the remote control of fittings. Figure shows the computation model and the response of this rod in individual time moments, both affected and not affected by play in the dilatation joint. Table shows the effect of play in the dilatation joint on deformation maxima and on rod bend stress from a symmetric load of 8g. (E.S.)
Characteristics and modeling of spruce wood under dynamic compression load
International Nuclear Information System (INIS)
Eisenacher, Germar
2014-01-01
Spruce wood is frequently used as an energy absorbing material in impact limiters of packages for the transportation of radioactive material. A 9m drop test onto an unyielding target is mandatory for the packages. The impact results in a dynamic compression load of the spruce wood inside the impact limiter. The lateral dilation of the wood is restrained thereby due to encasing steel sheets. This work's objective was to provide a material model for spruce wood based on experimental investigations to enable the calculation of such loading conditions. About 600 crush tests with cubical spruce wood specimens were performed to characterize the material. The compression was up to 70% and the material was assumed to be transversely isotropic. Particularly the lateral constraint showed to have an important effect: the material develops a high lateral dilation without lateral constraint. The force-displacement characteristics show a comparably low force level and no or only slight hardening. Distinctive softening occurs after the linear-elastic region when loaded parallel to the fiber. On the other hand, using a lateral constraint results in significantly higher general force levels, distinctive hardening and lateral forces. The softening effect when loaded parallel to the fiber is less distinctive. Strain rate and temperature raise or lower the strength level, which was quantified for the applicable ranges of impact limiters. The hypothesis of an uncoupled evolution of the yield surface was proposed based on the experimental findings. It postulates an independent strength evolution with deviatoric and volumetric deformation. The hypothesis could be established using the first modeling approach, the modified LS-DYNA material model MAT075. A transversely isotropic material model was developed based thereupon and implemented in LS-DYNA. The material characteristics of spruce wood were considered using a multi-surface yield criterion and a non-associated flow rule. The yield
Coarse-grained simulation of a real-time process control network under peak load
International Nuclear Information System (INIS)
George, A.D.; Clapp, N.E. Jr.
1992-01-01
This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks
Interestingness-Driven Diffusion Process Summarization in Dynamic Networks
DEFF Research Database (Denmark)
Qu, Qiang; Liu, Siyuan; Jensen, Christian S.
2014-01-01
The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...
Self-organization of complex networks as a dynamical system.
Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio
2015-01-01
To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.
Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium
Directory of Open Access Journals (Sweden)
Xiao Han
2017-12-01
Full Text Available This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE generation, energy storage systems (ESSs, and thermostatically controlled loads (TCLs. This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibrium of the load curve. Accordingly, we propose a concept of load equilibrium entropy to quantify the overall equilibrium of the load curve and reflect the allocation optimization of electric energy. Based on this entropy, we built a novel multi-objective optimal dispatching model to minimize the operational cost and maximize the load curve equilibrium. To aggregate TCLs into the optimization objective, we introduced the concept of a virtual power plant (VPP and proposed a calculation method for VPP operating characteristics based on the equivalent thermal parameter model and the state-queue control method. The Particle Swarm Optimization algorithm was employed to solve the optimization problems. The simulation results illustrated that the proposed dispatching model can achieve cost reductions of system operations, peak load curtailment, and efficiency improvements, and also verified that the load equilibrium entropy can be used as a novel index of load characteristics.
Magnetoencephalography from signals to dynamic cortical networks
Aine, Cheryl
2014-01-01
"Magnetoencephalography (MEG) provides a time-accurate view into human brain function. The concerted action of neurons generates minute magnetic fields that can be detected---totally noninvasively---by sensitive multichannel magnetometers. The obtained millisecond accuracycomplements information obtained by other modern brain-imaging tools. Accurate timing is quintessential in normal brain function, often distorted in brain disorders. The noninvasiveness and time-sensitivityof MEG are great assets to developmental studies, as well. This multiauthored book covers an ambitiously wide range of MEG research from introductory to advanced level, from sensors to signals, and from focal sources to the dynamics of cortical networks. Written by active practioners of this multidisciplinary field, the book contains tutorials for newcomers and chapters of new challenging methods and emerging technologies to advanced MEG users. The reader will obtain a firm grasp of the possibilities of MEG in the study of audition, vision...
Attractor dynamics in local neuronal networks
Directory of Open Access Journals (Sweden)
Jean-Philippe eThivierge
2014-03-01
Full Text Available Patterns of synaptic connectivity in various regions of the brain are characterized by the presence of synaptic motifs, defined as unidirectional and bidirectional synaptic contacts that follow a particular configuration and link together small groups of neurons. Recent computational work proposes that a relay network (two populations communicating via a third, relay population of neurons can generate precise patterns of neural synchronization. Here, we employ two distinct models of neuronal dynamics and show that simulated neural circuits designed in this way are caught in a global attractor of activity that prevents neurons from modulating their response on the basis of incoming stimuli. To circumvent the emergence of a fixed global attractor, we propose a mechanism of selective gain inhibition that promotes flexible responses to external stimuli. We suggest that local neuronal circuits may employ this mechanism to generate precise patterns of neural synchronization whose transient nature delimits the occurrence of a brief stimulus.
Short term and medium term power distribution load forecasting by neural networks
International Nuclear Information System (INIS)
Yalcinoz, T.; Eminoglu, U.
2005-01-01
Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey
Dynamics of subway networks based on vehicles operation timetable
Xiao, Xue-mei; Jia, Li-min; Wang, Yan-hui
2017-05-01
In this paper, a subway network is represented as a dynamic, directed and weighted graph, in which vertices represent subway stations and weights of edges represent the number of vehicles passing through the edges by considering vehicles operation timetable. Meanwhile the definitions of static and dynamic metrics which can represent vertices' and edges' local and global attributes are proposed. Based on the model and metrics, standard deviation is further introduced to study the dynamic properties (heterogeneity and vulnerability) of subway networks. Through a detailed analysis of the Beijing subway network, we conclude that with the existing network structure, the heterogeneity and vulnerability of the Beijing subway network varies over time when the vehicle operation timetable is taken into consideration, and the distribution of edge weights affects the performance of the network. In other words, although the vehicles operation timetable is restrained by the physical structure of the network, it determines the performances and properties of the Beijing subway network.
The stochastic network dynamics underlying perceptual discrimination
Directory of Open Access Journals (Sweden)
Genis Prat-Ortega
2015-04-01
Full Text Available The brain is able to interpret streams of high-dimensional ambiguous information and yield coherent percepts. The mechanisms governing sensory integration have been extensively characterized using time-varying visual stimuli (Britten et al. 1996; Roitman and Shadlen 2002, but some of the basic principles regarding the network dynamics underlying this process remain largely unknown. We captured the basic features of a neural integrator using three canonical one-dimensional models: (1 the Drift Diffusion Model (DDM, (2 the Perfect Integrator (PI which is a particular case of the DDM where the bounds are set to infinity and (3 the double-well potential (DW which captures the dynamics of the attractor networks (Wang 2002; Roxin and Ledberg 2008. Although these models has been widely studied (Bogacz et al. 2006; Roxin and Ledberg 2008; Gold and Shadlen 2002, it has been difficult to experimentally discriminate among them because most of the observables measured are only quantitatively different among these models (e.g. psychometric curves. Here we aim to find experimentally measurable quantities that can yield qualitatively different behaviors depending on the nature of the underlying network dynamics. We examined the categorization dynamics of these models in response to fluctuating stimuli of different duration (T. On each time step, stimuli are drawn from a Gaussian distribution N(μ, σ and the two stimulus categories are defined by μ > 0 and μ < 0. Psychometric curves can therefore be obtained by quantifying the probability of the integrator to yield one category versus μ . We find however that varying σ can reveal more clearly the differences among the different integrators. In the small σ regime, both the DW and the DDM perform transient integration and exhibit a decaying stimulus reverse correlation kernel revealing a primacy effect (Nienborg and Cumming 2009; Wimmer et al. 2015 . In the large σ regime, the integration in the DDM
The Dynamics of Initiative in Communication Networks.
Directory of Open Access Journals (Sweden)
Anders Mollgaard
Full Text Available Human social interaction is often intermittent. Two acquainted persons can have extended periods without social interaction punctuated by periods of repeated interaction. In this case, the repeated interaction can be characterized by a seed initiative by either of the persons and a number of follow-up interactions. The tendency to initiate social interaction plays an important role in the formation of social networks and is in general not symmetric between persons. In this paper, we study the dynamics of initiative by analysing and modeling a detailed call and text message network sampled from a group of 700 individuals. We show that in an average relationship between two individuals, one part is almost twice as likely to initiate communication compared to the other part. The asymmetry has social consequences and ultimately might lead to the discontinuation of a relationship. We explain the observed asymmetry by a positive feedback mechanism where individuals already taking initiative are more likely to take initiative in the future. In general, people with many initiatives receive attention from a broader spectrum of friends than people with few initiatives. Lastly, we compare the likelihood of taking initiative with the basic personality traits of the five factor model.
Choice Shift in Opinion Network Dynamics
Gabbay, Michael
Choice shift is a phenomenon associated with small group dynamics whereby group discussion causes group members to shift their opinions in a more extreme direction so that the mean post-discussion opinion exceeds the mean pre-discussion opinion. Also known as group polarization, choice shift is a robust experimental phenomenon and has been well-studied within social psychology. In opinion network models, shifts toward extremism are typically produced by the presence of stubborn agents at the extremes of the opinion axis, whose opinions are much more resistant to change than moderate agents. However, we present a model in which choice shift can arise without the assumption of stubborn agents; the model evolves member opinions and uncertainties using coupled nonlinear differential equations. In addition, we briefly describe the results of a recent experiment conducted involving online group discussion concerning the outcome of National Football League games are described. The model predictions concerning the effects of network structure, disagreement level, and team choice (favorite or underdog) are in accord with the experimental results. This research was funded by the Office of Naval Research and the Defense Threat Reduction Agency.
Filtering in Hybrid Dynamic Bayesian Networks
Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin
2000-01-01
We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).
Dynamic characteristics of motor-gear system under load saltations and voltage transients
Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.
2018-02-01
In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.
Load-aware modeling for uplink cellular networks in a multi-channel environment
Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim
2014-01-01
We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint
Ka'ka, Simon; Himran, Syukri; Renreng, Ilyas; Sutresman, Onny
2018-02-01
Almost all of road damage can be caused by dynamic loads of vehicles that fluctuate according to the type of vehicle that passes through. This study aims to calculate the vertical dynamic load of the vehicle actually occurs on road construction by the mechanism of vehicle wheel suspension. Pneumatic cylinders driven by pressurized air directly load the spring and shock absorber installed on the wheels of the vehicle. The load fluctuations of the medium weight categorized vehicles are determined by the regulation of the amount of pressurized air that enters into the pneumatic cylinder chamber, pushing the piston and connecting rods. The displacement that occurs during compression on the spring and shock absorber, is substituted into the equation of vehicle dynamic load while taking into account the spring stiffness constant, and the fluid or damper gas coefficient. The results show that the magnitude of the displacement when the compression force works has significant influences to the amount of vertical dynamic load of the vehicle that overlies the road construction. The presence of dynamic load of vehicles that fluctuates and repeats, also affects on the reduction of road ability to receive the load. Experimental results using pneumatic actuators instead of real dynamic vehicle loads illustrate the characteristics of the relationship between work pressure and dynamic load. If the working pressure of P2 (bar) is greater, the vertical dynamic load Ft (N) that overloads the road structure is also greater. The associate graphs show that the shock absorber has a greater ability to reduce dynamic load vertically that burden the road structure when compared with the ability of screw spring.
Cooperation of axisymmetric connection elements under dynamic load
Directory of Open Access Journals (Sweden)
Kołodziej Andrzej
2018-01-01
Full Text Available The article presents a method for determining the parameters that define the cooperation of the elements in the axisymmetic connection. The connection, which constitutes a shaft cooperating with a sleeve, has been tested for reaction forces in the connection during shaft rotation in the static sleeve. The shaft was characterized by deliberately modelled roundness deviations in the form of ovality, triangularity and quadrangularity. In addition, the research programme has taken into account the determination of the impact of tolerance of the outside diameter of the shaft. Determination of reaction forces has been carried out using the FEM software. The shaft has been modelled as a rigid element that rotates with a given rotational speed in the deformable sleeve. The conclusions present the impact of roundness deviation types and the tolerance value on reaction forces in the connection restraint. The method presented in the article can be used to predict the behaviour of the elements of axisymmetic connections under dynamic load, which can contribute to forecasting the durability of the connection.
Response of borehole extensometers to explosively generated dynamic loads
International Nuclear Information System (INIS)
Patrick, W.C.; Brough, W.G.
1980-01-01
Commercially available, hydraulically anchored, multiple-point borehole extensometers (MPBX) were evaluated with respect to response to dynamic loads produced by explosions. This study is part of the DOE-funded Spent Fuel Test-Climax (SFT-C), currently being conducted in the Climax granitic stock at the Nevada Test Site. The SFT-C is an investigation of the feasibility of short-term storage and retrieval of spent nuclear reactor fuel assemblies at a plausible repository depth in granitic rock. Eleven spent fuel assemblies are stored at a depth of 420 m for three to five years, and will then be retrieved. MPBX units are used in the SFT-C to measure both excavation-induced and thermally induced rock displacements. Long-term reliability of extensometers in this hostile environment is essential in order to obtain valid data during the course of this test. Research to date shows conclusively that extensometers of this type continue to function reliably even though subjected to accelerations of 1.8 g; research also implies that they function well though subjected to accelerations in excess of 100 g. MPBX survivability during the first four months of testing at ambient temperatures was about 90 percent
Effects of moving dynamic tyre loads on tyre-pavement contact stresses
CSIR Research Space (South Africa)
Steyn, WJvdM
2002-01-01
Full Text Available The purpose of this paper is to indicate the effect that moving dynamic tyre loads has on the tyre-pavement contact stresses used in pavement analysis. Traditionally tyre loads (in pavement analysis) are modelled as constant loads applied through...
Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.
Feng, Jianyuan; Feng, Zhiyong
2017-09-11
Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.
Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command
2017-11-22
ARL-TN-0859 ● NOV 2017 US Army Research Laboratory Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled...Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command by John K Hawley Human Research and Engineering...REPORT TYPE Technical Note 3. DATES COVERED (From - To) 1 May 2016–20 April 2017 4. TITLE AND SUBTITLE Applied Knowledge Management to Mitigate
Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics
Chen, Yu-Zhong; Lai, Ying-Cheng
2018-03-01
Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.
Impact evaluation of conducted UWB transients on loads in power-line networks
Li, Bing; Månsson, Daniel
2017-09-01
Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI) becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB) disturbance, as an example of intentional electromagnetic interference (IEMI) source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT), the UWB transient is characterized in the frequency domain. Based on a modified Baum-Liu-Tesche (BLT) method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT), we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive) of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.
Radial basis function neural network for power system load-flow
International Nuclear Information System (INIS)
Karami, A.; Mohammadi, M.S.
2008-01-01
This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)
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 ...
Influence of the implant abutment types and the dynamic loading on initial screw loosening
Kim, Eun-Sook; Shin, Soo-Yeon
2013-01-01
PURPOSE This study examined the effects of the abutment types and dynamic loading on the stability of implant prostheses with three types of implant abutments prepared using different fabrication methods by measuring removal torque both before and after dynamic loading. MATERIALS AND METHODS Three groups of abutments were produced using different types of fabrication methods; stock abutment, gold cast abutment, and CAD/CAM custom abutment. A customized jig was fabricated to apply the load at ...
Failure mitigation in software defined networking employing load type prediction
Bouacida, Nader; Alghadhban, Amer Mohammad JarAlla; Alalmaei, Shiyam Mohammed Abdullah; Mohammed, Haneen; Shihada, Basem
2017-01-01
The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since
Energy savings in mobile broadband network based on load predictions
DEFF Research Database (Denmark)
Samulevicius, Saulius; Pedersen, Torben Bach; Sørensen, Troels Bundgaard
2012-01-01
Abstract—The deployment of new network equipment is resulting in increasing energy consumption in mobile broadband networks (MBNs). This contributes to higher CO2 emissions. Over the last 10 years MBNs have grown considerably, and are still growing to meet the evolution in traffic volume carried...
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.
Dynamic Mobile IP routers in ad hoc networks
Kock, B.A.; Schmidt, J.R.
2005-01-01
This paper describes a concept combining mobile IP and ad hoc routing to create a robust mobile network. In this network all nodes are mobile and globally and locally reachable under the same IP address. Essential for implementing this network are the dynamic mobile IP routers. They act as gateways
Gender, Friendship Networks, and Delinquency: A Dynamic Network Approach.
Haynie, Dana L; Doogan, Nathan J; Soller, Brian
2014-11-01
Researchers have examined selection and influence processes in shaping delinquency similarity among friends, but little is known about the role of gender in moderating these relationships. Our objective is to examine differences between adolescent boys and girls regarding delinquency-based selection and influence processes. Using longitudinal network data from adolescents attending two large schools in AddHealth ( N = 1,857) and stochastic actor-oriented models, we evaluate whether girls are influenced to a greater degree by friends' violence or delinquency than boys (influence hypothesis) and whether girls are more likely to select friends based on violent or delinquent behavior than boys (selection hypothesis). The results indicate that girls are more likely than boys to be influenced by their friends' involvement in violence. Although a similar pattern emerges for nonviolent delinquency, the gender differences are not significant. Some evidence shows that boys are influenced toward increasing their violence or delinquency when exposed to more delinquent or violent friends but are immune to reducing their violence or delinquency when associating with less violent or delinquent friends. In terms of selection dynamics, although both boys and girls have a tendency to select friends based on friends' behavior, girls have a stronger tendency to do so, suggesting that among girls, friends' involvement in violence or delinquency is an especially decisive factor for determining friendship ties.
Gender, Friendship Networks, and Delinquency: A Dynamic Network Approach**
Haynie, Dana L.; Doogan, Nathan J.; Soller, Brian
2014-01-01
Researchers have examined selection and influence processes in shaping delinquency similarity among friends, but little is known about the role of gender in moderating these relationships. Our objective is to examine differences between adolescent boys and girls regarding delinquency-based selection and influence processes. Using longitudinal network data from adolescents attending two large schools in AddHealth (N = 1,857) and stochastic actor-oriented models, we evaluate whether girls are influenced to a greater degree by friends' violence or delinquency than boys (influence hypothesis) and whether girls are more likely to select friends based on violent or delinquent behavior than boys (selection hypothesis). The results indicate that girls are more likely than boys to be influenced by their friends' involvement in violence. Although a similar pattern emerges for nonviolent delinquency, the gender differences are not significant. Some evidence shows that boys are influenced toward increasing their violence or delinquency when exposed to more delinquent or violent friends but are immune to reducing their violence or delinquency when associating with less violent or delinquent friends. In terms of selection dynamics, although both boys and girls have a tendency to select friends based on friends' behavior, girls have a stronger tendency to do so, suggesting that among girls, friends' involvement in violence or delinquency is an especially decisive factor for determining friendship ties. PMID:26097241
Dynamic Sensor Network Reprogramming using SensorScheme
Evers, L.; Havinga, Paul J.M.; Kuper, Jan
2007-01-01
Building wireless sensor network applications is a challenging task, and it has become apparent that it is crucial for many sensor networks to be able to load or update the application after deployment. Since communication is a scarce resource and costly in terms of energy, it is important to
Dynamics of slow and fast systems on complex networks
Indian Academy of Sciences (India)
synchrony in oscillator networks [10]. In power grids and the Internet it has been shown that heterogeneity due to different loads on nodes can cause a cascade ..... from that of the bipartite one even when they start from the same initial conditions. In the network of 3 sys- tems the configurations 3 and 4 exhibited frequency.
Topology Identification of General Dynamical Network with Distributed Time Delays
International Nuclear Information System (INIS)
Zhao-Yan, Wu; Xin-Chu, Fu
2009-01-01
General dynamical networks with distributed time delays are studied. The topology of the networks are viewed as unknown parameters, which need to be identified. Some auxiliary systems (also called the network estimators) are designed to achieve this goal. Both linear feedback control and adaptive strategy are applied in designing these network estimators. Based on linear matrix inequalities and the Lyapunov function method, the sufficient condition for the achievement of topology identification is obtained. This method can also better monitor the switching topology of dynamical networks. Illustrative examples are provided to show the effectiveness of this method. (general)
Dynamic defense and network randomization for computer systems
Chavez, Adrian R.; Stout, William M. S.; Hamlet, Jason R.; Lee, Erik James; Martin, Mitchell Tyler
2018-05-29
The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissance stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.
Arresting Strategy Based on Dynamic Criminal Networks Changing over Time
Directory of Open Access Journals (Sweden)
Junqing Yuan
2013-01-01
Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.
Using Gait Dynamics to Estimate Load from a Body-Worn Accelerometer
2016-02-05
dynamics, ambulation, correlation structure, musculoskeletal injury I. INTRODUCTION ilitary personnel commonly engage in training and operational...according to their load estimation accuracy, which is defined by the Pearson correlation , r, of its load estimates with the true loads (see Tables...method. In Table IV are shown the mean absolute error, MAE, and Pearson correlation , r, of the load estimates using estimates from GS alone, PLS alone
A study on the evolution of crack networks under thermal fatigue loading
International Nuclear Information System (INIS)
Kamaya, Masayuki; Taheri, Said
2008-01-01
The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components
Major component analysis of dynamic networks of physiologic organ interactions
International Nuclear Information System (INIS)
Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P
2015-01-01
The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)
Identify Dynamic Network Modules with Temporal and Spatial Constraints
Energy Technology Data Exchange (ETDEWEB)
Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J
2007-09-24
Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.
Load control strategies in 2G mobile network for W-CDMA radio ...
African Journals Online (AJOL)
Network planning requires a faithful analysis of each individual cell's capacity. In this paper, we examine load control equations as a resource allocation tool to analyse cell capacity for the uplink and downlink of Wideband Code Division Multiple Access (W-CDMA) networks. In the uplink, the noise rise is a parameter of ...
International Nuclear Information System (INIS)
Mahmoud, Thair S.; Habibi, Daryoush; Hassan, Mohammed Y.; Bass, Octavian
2015-01-01
Highlights: • A novel Short Term Medium Voltage (MV) Load Forecasting (STLF) model is presented. • A knowledge-based STLF error control mechanism is implemented. • An Artificial Neural Network (ANN)-based optimum tuning is applied on STLF. • The relationship between load profiles and operational conditions is analysed. - Abstract: This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.
Transport on river networks: A dynamical approach
Zaliapin, I; Foufoula-Georgiou, E; Ghil, M
2017-01-01
This study is motivated by problems related to environmental transport on river networks. We establish statistical properties of a flow along a directed branching network and suggest its compact parameterization. The downstream network transport is treated as a particular case of nearest-neighbor hierarchical aggregation with respect to the metric induced by the branching structure of the river network. We describe the static geometric structure of a drainage network by a tree, referred to as...
Under-Frequency Load Shedding Technique Considering Event-Based for an Islanded Distribution Network
Directory of Open Access Journals (Sweden)
Hasmaini Mohamad
2016-06-01
Full Text Available One of the biggest challenge for an islanding operation is to sustain the frequency stability. A large power imbalance following islanding would cause under-frequency, hence an appropriate control is required to shed certain amount of load. The main objective of this research is to develop an adaptive under-frequency load shedding (UFLS technique for an islanding system. The technique is designed considering an event-based which includes the moment system is islanded and a tripping of any DG unit during islanding operation. A disturbance magnitude is calculated to determine the amount of load to be shed. The technique is modeled by using PSCAD simulation tool. A simulation studies on a distribution network with mini hydro generation is carried out to evaluate the UFLS model. It is performed under different load condition: peak and base load. Results show that the load shedding technique have successfully shed certain amount of load and stabilized the system frequency.
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
Bistable responses in bacterial genetic networks: Designs and dynamical consequences
Tiwari, Abhinav; Ray, J. Christian J.; Narula, Jatin; Igoshin, Oleg A.
2011-01-01
A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses. PMID:21385588
Investigation of Load Sharing in Hybrid (2G/3G Mobile Networks
Directory of Open Access Journals (Sweden)
Martynas Stirbys
2015-07-01
Full Text Available The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indicators.
Investigation of Load Sharing in Hybrid (2G/3G) Mobile Networks
Martynas Stirbys; Karolis Žvinys
2015-01-01
The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indica...
CAC DPLB MCN: A Distributed Load Balancing Scheme in Multimedia Mobile Cellular Networks
Directory of Open Access Journals (Sweden)
Sharma Abhijit
2016-11-01
Full Text Available The problem of non-uniform traffic demand in different cells of a cellular network may lead to a gross imbalance in the system performance. Thus, the users in hot cells may suffer from low throughput. In this paper, an effective and simple load balancing scheme CAC_DPLB_MCN is proposed that can effectively reduce the overall call blocking. This model considers dealing with multi-media traffic as well as time-varying geographical traffic distribution. The proposed scheme uses the concept of cell-tiering thereby creating fractional frequency reuse environment. A message exchange based distributed scheme instead of centralized one is used which help the proposed scheme be implemented in a multiple hot cell environment also. Furthermore, concept of dynamic pricing is used to serve the best interest of the users as well as for the service providers. The performance of the proposed scheme is compared with two other existing schemes in terms of call blocking probability and bandwidth utilization. Simulation results show that the proposed scheme can reduce the call blocking significantly in highly congested cell with highest bandwidth utilization. Use of dynamic pricing also makes the scheme useful to increase revenue of the service providers in contrast with compared schemes.
Epidemic dynamics and endemic states in complex networks
Pastor-Satorras, Romualdo; Vespignani, Alessandro
2001-01-01
We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below which the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are pron...
Development of Fast-Running Simulation Methodology Using Neural Networks for Load Follow Operation
International Nuclear Information System (INIS)
Seong, Seung-Hwan; Park, Heui-Youn; Kim, Dong-Hoon; Suh, Yong-Suk; Hur, Seop; Koo, In-Soo; Lee, Un-Chul; Jang, Jin-Wook; Shin, Yong-Chul
2002-01-01
A new fast-running analytic model has been developed for analyzing the load follow operation. The new model was based on the neural network theory, which has the capability of modeling the input/output relationships of a nonlinear system. The new model is made up of two error back-propagation neural networks and procedures to calculate core parameters, such as the distributions and density of xenon in a quasi-steady-state core like load follow operation. One neural network is designed to retrieve the axial offset of power distribution, and the other is for reactivity corresponding to a given core condition. The training data sets for learning the neural networks in the new model are generated with a three-dimensional nodal code and, also, the measured data of the first-day test of load follow operation. Using the new model, the simulation results of the 5-day load follow test in a pressurized water reactor show a good agreement between the simulation data and the actual measured data. Required computing time for simulating a load follow operation is comparable to that of a fast-running lumped model. Moreover, the new model does not require additional engineering factors to compensate for the difference between the actual measurements and analysis results because the neural network has the inherent learning capability of neural networks to new situations
Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Wang Tao
2014-04-01
Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.
International Nuclear Information System (INIS)
Zhang Li-Sheng; Mi Yuan-Yuan; Gu Wei-Feng; Hu Gang
2014-01-01
All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend on network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks (ECNs) and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns (e.g., periodic, quasiperiodic, and chaotic). In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies (random or scale-free topologies) and different interaction structures (symmetric or asymmetric couplings). The mechanisms behind these differences are explained physically. (interdisciplinary physics and related areas of science and technology)
Opinion competition dynamics on multiplex networks
Amato, R.; Kouvaris, N. E.; San Miguel, M.; Díaz-Guilera, A.
2017-12-01
Multilayer and multiplex networks represent a good proxy for the description of social phenomena where social structure is important and can have different origins. Here, we propose a model of opinion competition where individuals are organized according to two different structures in two layers. Agents exchange opinions according to the Abrams-Strogatz model in each layer separately and opinions can be copied across layers by the same individual. In each layer a different opinion is dominant, so each layer has a different absorbing state. Consensus in one opinion is not the only possible stable solution because of the interaction between the two layers. A new mean field solution has been found where both opinions coexist. In a finite system there is a long transient time for the dynamical coexistence of both opinions. However, the system ends in a consensus state due to finite size effects. We analyze sparse topologies in the two layers and the existence of positive correlations between them, which enables the coexistence of inter-layer groups of agents sharing the same opinion.
Opinion dynamics in activity-driven networks
Li, Dandan; Han, Dun; Ma, Jing; Sun, Mei; Tian, Lixin; Khouw, Timothy; Stanley, H. Eugene
2017-10-01
Social interaction between individuals constantly affects the development of their personal opinions. Previous models such as the Deffuant model and the Hegselmann-Krause (HK) model have assumed that individuals only update their opinions after interacting with neighbors whose opinions are similar to their own. However, people are capable of communicating widely with all of their neighbors to gather their ideas and opinions, even if they encounter a number of opposing attitudes. We propose a model in which agents listen to the opinions of all their neighbors. Continuous opinion dynamics are investigated in activity-driven networks with a tolerance threshold. We study how the initial opinion distribution, tolerance threshold, opinion-updating speed, and activity rate affect the evolution of opinion. We find that when the initial fraction of positive opinion is small, all opinions become negative by the end of the simulation. As the initial fraction of positive opinions rises above a certain value —about 0.45— the final fraction of positive opinions sharply increases and eventually equals 1. Increased tolerance threshold δ is found to lead to a more varied final opinion distribution. We also find that if the negative opinion has an initial advantage, the final fraction of negative opinion increases and reaches its peak as the updating speed λ approaches 0.5. Finally we show that the lower the activity rate of individuals, the greater the fluctuation range of their opinions.
Effects of dynamic loading of motor-operated valve actuators
International Nuclear Information System (INIS)
Damerell, P.S.; Daubresse, S.; Wolfe, K.J.; Dogan, T.; Gleeson, J.
1994-01-01
Experience has shown that valves with rising, nonrotating stems that are operated using electro-motor driven actuators can be susceptible to changes in output thrust at a constant torque switch setting as a result of changes in stem load time history. This effect is a concern because tests on these types of valves to verify thrust achieved at torque switch trip are often performed in situ under load conditions different from the required performance conditions. As part of a motor-operated valve research program being carried out by the Electric Power Research Institute, tests of typical electric motor actuators used with nuclear services valves have been performed. The test results show that changes in output thrust with load time history occur o varying degrees on different stem and stem nut combinations. When the effect exists, there is generally an increase in thrust at torque switch trip when load is developed rapidly from low initial loads, compared to when load is developed slowly. The effect is mainly a result of changes in the coefficient of friction at the stem-stem nut interface. The coefficient of friction is temporarily reduced under rapid loading conditions from low initial load, leading to increased thrust. The root cause is hypothesized to be a open-quotes squeeze-filmclose quotes effect, whereby mixed-mode lubrication (hydrodynamic plus boundary) temporarily replaces boundary lubrication. This paper describes the results of tests performed to better understand the phenomenon
Load Balanced Mapping of Distributed Objects to Minimize Network Communication
Stoyenko, Alexander D.; Bosch, J.; Bosch, Jan; Aksit, Mehmet; Marlowe, Thomas J.
1996-01-01
This paper introduces a new load balancing and communica- tion minimizing heuristic used in the Inverse Remote Procedure Call (IRPC) system. While the paper briefly describes the IRPC system, the focus is on the new IRPC assignment heuristic. The IRPC compiler maps a distributed program to a graph
Clustering promotes switching dynamics in networks of noisy neurons
Franović, Igor; Klinshov, Vladimir
2018-02-01
Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.
Synthesis of recurrent neural networks for dynamical system simulation.
Trischler, Adam P; D'Eleuterio, Gabriele M T
2016-08-01
We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks
Lin, Likun
Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network
Complex systems and networks dynamics, controls and applications
Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu
2016-01-01
This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...
Controlling the dynamics of multi-state neural networks
International Nuclear Information System (INIS)
Jin, Tao; Zhao, Hong
2008-01-01
In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks
Dynamic Axle Load of an Automotive Vehicle When Driven on a Mobile Measurement Platform
Jagiełowicz-Ryznar C.
2014-01-01
An analysis of the dynamic axle load of an automotive vehicle (AV) when it is driven on a mobile measurement platform is presented in this paper. During the ride, the time characteristic of the dynamic force N(t), acting on the axle, was recorded. The effect of the vehicle axle mass on the maximum dynamic force value and the dynamic coefficient were studied. On this basis it was attempted to calculate the total vehicle’s weight. Conclusions concerning the dynamic loads of the vehicle axles in...
Dynamic Intelligent Feedback Scheduling in Networked Control Systems
Directory of Open Access Journals (Sweden)
Hui-ying Chen
2013-01-01
Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.
Effect of loading rate on dynamic fracture of reaction bonded silicon nitride
Liaw, B. M.; Kobayashi, A. S.; Emery, A. F.
1986-01-01
Wedge-loaded, modified tapered double cantilever beam (WL-MTDCB) specimens under impact loading were used to determine the room temperature dynamic fracture response of reaction bonded silicon nitride (RBSN). The crack extension history, with the exception of the terminal phase, was similar to that obtained under static loading. Like its static counterpart, a distinct crack acceleration phase, which was not observed in dynamic fracture of steel and brittle polymers, was noted. Unlike its static counterpart, the crack continued to propagate at nearly its terminal velocity under a low dynamic stress intensity factor during the terminal phase of crack propagation. These and previously obtained results for glass and RBSN show that dynamic crack arrest under a positive dynamic stress intensity factor is unlikely in static and impact loaded structural ceramics.
A User Driven Dynamic Circuit Network Implementation
Energy Technology Data Exchange (ETDEWEB)
Guok, Chin; Robertson, David; Chaniotakis, Evangelos; Thompson, Mary; Johnston, William; Tierney, Brian
2008-10-01
The requirements for network predictability are becoming increasingly critical to the DoE science community where resources are widely distributed and collaborations are world-wide. To accommodate these emerging requirements, the Energy Sciences Network has established a Science Data Network to provide user driven guaranteed bandwidth allocations. In this paper we outline the design, implementation, and secure coordinated use of such a network, as well as some lessons learned.
Network rewiring dynamics with convergence towards a star network.
Whigham, P A; Dick, G; Parry, M
2016-10-01
Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440-442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach.
Traffic Policing in Dynamic Military Networks Using Software Defined Networking
Skappel, Hans Fredrik
2016-01-01
This thesis looks at how Software Defined Networking (SDN) can be used to provide traffic engineering and to police traffic in an Operational Military Network (OMN). SDN is a concept where the control plane is separated from the forwarding plane, and the control plane is capable of controlling forwarding plane elements located on multiple network nodes using the OpenFlow protocol. Specifically, we have discussed the problems in OMNs, and possible SDN approaches to mitigate the challenges. Bas...
Dynamic backcalculation with different load-time histories
DEFF Research Database (Denmark)
Madsen, Stine Skov; Levenberg, Eyal
2017-01-01
This paper focused attention to the falling weight deflectometer (FWD) load-time history. For a commonly used device, it studied the pulse generation mechanism and the influence of different load histories on backcalculation results. In this connection, a semi-analytic impact theory was first...... for an experimental dataset that resulted from operating an FWD with different loading configurations. It was found that backcalculated parameters are sensitive to the FWD pulse features. Consequently, it is recommended that, whenever advanced pavement characterisation is sought, experimental attention should...
Design and implementation of dynamic hybrid Honeypot network
Qiao, Peili; Hu, Shan-Shan; Zhai, Ji-Qiang
2013-05-01
The method of constructing a dynamic and self-adaptive virtual network is suggested to puzzle adversaries, delay and divert attacks, exhaust attacker resources and collect attacking information. The concepts of Honeypot and Honeyd, which is the frame of virtual Honeypot are introduced. The techniques of network scanning including active fingerprint recognition are analyzed. Dynamic virtual network system is designed and implemented. A virtual network similar to real network topology is built according to the collected messages from real environments in this system. By doing this, the system can perplex the attackers when Hackers attack and can further analyze and research the attacks. The tests to this system prove that this design can successfully simulate real network environment and can be used in network security analysis.
Dynamics of epidemic diseases on a growing adaptive network.
Demirel, Güven; Barter, Edmund; Gross, Thilo
2017-02-10
The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.
Synchronization of complex delayed dynamical networks with nonlinearly coupled nodes
International Nuclear Information System (INIS)
Liu Tao; Zhao Jun; Hill, David J.
2009-01-01
In this paper, we study the global synchronization of nonlinearly coupled complex delayed dynamical networks with both directed and undirected graphs. Via Lyapunov-Krasovskii stability theory and the network topology, we investigate the global synchronization of such networks. Under the assumption that coupling coefficients are known, a family of delay-independent decentralized nonlinear feedback controllers are designed to globally synchronize the networks. When coupling coefficients are unavailable, an adaptive mechanism is introduced to synthesize a family of delay-independent decentralized adaptive controllers which guarantee the global synchronization of the uncertain networks. Two numerical examples of directed and undirected delayed dynamical network are given, respectively, using the Lorenz system as the nodes of the networks, which demonstrate the effectiveness of proposed results.
Energy Efficiency Analysis for Dynamic Routing in Optical Transport Networks
DEFF Research Database (Denmark)
Vizcaíno, Jorge López; Ye, Yabin; Tafur Monroy, Idelfonso
2012-01-01
The energy efficiency in telecommunication networks is gaining more relevance as the Internet traffic is growing. The introduction of OFDM and dynamic operation opens new horizons in the operation of optical networks, improving the network flexibility and its efficiency. In this paper, we compare...... the performance in terms of energy efficiency of a flexible-grid OFDM-based solution with a fixed-grid WDM network in a dynamic scenario with time-varying connections. We highlight the benefits that the bandwidth elasticity and the flexibility of selecting different modulation formats can offer compared...
Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading
Yang, Shu; Han, Shou-Hong; Lu, Zhen-Hua
2014-01-01
It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances. PMID:25126606
Dynamic response and optimal design of curved metallic sandwich panels under blast loading.
Qi, Chang; Yang, Shu; Yang, Li-Jun; Han, Shou-Hong; Lu, Zhen-Hua
2014-01-01
It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a "soft" outer face and a "hard" inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.
Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading
Directory of Open Access Journals (Sweden)
Chang Qi
2014-01-01
Full Text Available It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.
Bulk Electric Load Cost Calculation Methods: Iraqi Network Comparative Study
Directory of Open Access Journals (Sweden)
Qais M. Alias
2016-09-01
Full Text Available It is vital in any industry to regain the spent capitals plus running costs and a margin of profits for the industry to flourish. The electricity industry is an everyday life touching industry which follows the same finance-economic strategy. Cost allocation is a major issue in all sectors of the electric industry, viz, generation, transmission and distribution. Generation and distribution service costing’s well documented in the literature, while the transmission share is still of need for research. In this work, the cost of supplying a bulk electric load connected to the EHV system is calculated. A sample basic lump-average method is used to provide a rough costing guide. Also, two transmission pricing methods are employed, namely, the postage-stamp and the load-flow based MW-distance methods to calculate transmission share in the total cost of each individual bulk load. The three costing methods results are then analyzed and compared for the 400kV Iraqi power grid considered for a case study.
neural network based load frequency control for restructuring power
African Journals Online (AJOL)
2012-03-01
Mar 1, 2012 ... the system in the back propagation chain used in controller training. For this application, .... The partial derivative of E with respect to ele- ments of Γ, for example W, ... Ki = any non-negative value. Figure 7: Neural Network ...
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum
Dynamic modeling and analysis of load sharing characteristics of wind turbine gearbox
Directory of Open Access Journals (Sweden)
Pengxing Yi
2015-03-01
Full Text Available A coupled dynamic model, which contains helical gears-shafts-bearings for a wind turbine gearbox transmission system, was built considering nonlinear factors of the time-varying mesh stiffness, the external varying load, and the dynamic transmission error at first. The model is confirmed to be right after comparing the theoretical data with the experimental load sharing values, and also it is found that the static load sharing is conservative to evaluate the non-equilibrium effect of a planetary gear system. Besides, the analyzing results of the influence of average error and amplitude error on the load sharing show that the load sharing could be decreased if the error goes up a little. Then, by means of treating the static tracing point as the dynamic initial values, we analyzed the initial position’s influence on the load sharing of transmission system to provide a theoretical basis of load sharing control. Furthermore, we explored the influence of high-speed shaft position angle on the load sharing and the dynamic load factor of gears fixed on the parallel shafts. The results provide useful theoretical guidelines for the design of parallel shaft gear system in the wind turbines.
A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting
Directory of Open Access Journals (Sweden)
Ping-Huan Kuo
2018-01-01
Full Text Available One of the most important research topics in smart grid technology is load forecasting, because accuracy of load forecasting highly influences reliability of the smart grid systems. In the past, load forecasting was obtained by traditional analysis techniques such as time series analysis and linear regression. Since the load forecast focuses on aggregated electricity consumption patterns, researchers have recently integrated deep learning approaches with machine learning techniques. In this study, an accurate deep neural network algorithm for short-term load forecasting (STLF is introduced. The forecasting performance of proposed algorithm is compared with performances of five artificial intelligence algorithms that are commonly used in load forecasting. The Mean Absolute Percentage Error (MAPE and Cumulative Variation of Root Mean Square Error (CV-RMSE are used as accuracy evaluation indexes. The experiment results show that MAPE and CV-RMSE of proposed algorithm are 9.77% and 11.66%, respectively, displaying very high forecasting accuracy.
Efficiency Evaluation of Strategies for Dynamic Management of Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Andrea Verônica González
2017-01-01
Full Text Available This paper presents and evaluates dynamic management strategies to improve efficiency in event-triggered wireless sensor networks. We are considering mobility, where nodes move themselves to maximize the coverage, and load balancing state-of-the-art techniques, by which the number of nodes sensing the same area is reduced. To explore mobility, we present a simple method by which nodes can dynamically reorganize themselves based on the force fields approach of mobile robotics. Firstly, the strategies are evaluated separately through experiments with different network configurations and, afterwards, a joint evaluation has been conducted to observe the impact of mobility on the efficiency of load balancing techniques. We show that mobile nodes significantly contribute to keeping the coverage as nodes die in mesh and powerfully improving it in random deployments. Load balancing techniques achieve important results, increasing lifetime and the number of sensed events. However, in random deployments, these techniques lose efficiency and become unsuitable strategies. Combining these strategies with mobility, we observe that PS-based technique keeps its contribution in mesh and random deployments, as well as improving its performance for not so dense networks. Ant-based technique when combined with mobile nodes loses performance significantly in mesh and keeps its good performance in random deployed and less dense networks.
Testing for time-varying loadings in dynamic factor models
DEFF Research Database (Denmark)
Mikkelsen, Jakob Guldbæk
Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....
Dynamic Response to Pedestrian Loads with Statistical Frequency Distribution
DEFF Research Database (Denmark)
Krenk, Steen
2012-01-01
on the magnitude of the resulting response. A frequency representation of vertical pedestrian load is developed, and a compact explicit formula is developed for the magnitude of the resulting response, in terms of the damping ratio of the structure, the bandwidth of the pedestrian load, and the mean footfall...... frequency. The accuracy of the formula is verified by a statistical moment analysis using the Lyapunov equations....
International Nuclear Information System (INIS)
Omata, Takayuki; Saito, Kazuhiro; Kotake, Fumio; Mizokami, Yuji; Matsuoka, Takeshi; Abe, Kimihiko
2002-01-01
Dynamic MR cholangiography was conducted on patients with cholelithiasis or choledocholithiasis who had consumed a fatty test meal (Molyork) and the cystic contractility and dynamics of biliary stasis was evaluated. The subjects were 25 with intracystic cholelithiasis, 10 with choledocholithiasis and 10 normal controls. For an imaging sequence, the rapid acquisition with relaxation enhancement (RARE) method was employed and imaging was conducted for 40 min (every 30 s following Molyork administration) without breath-holding. The gallbladder contraction ratio was computed and the contractile ratio for the common bile duct was calculated. To determine the bile flow to the duodenum, the high-intensity signal, indicating the flow from the lower common bile duct, and perfusion of the duodenum were observed in dynamic mode on the monitor with the naked eye and interpreted as positive bile flow. The frequency of this flow was visually monitored. The gallbladder contractile ratio was significantly reduced in patients with cholelithiasis or choledocholithiasis compared with the controls. In a comparison with the normal controls, no sequential changes were noted in the mean contractile ratio of the common bile duct of the patients with cholelithiasis or choledocholithiasis. The mean frequency of bile flow observed for each 40 min period was 13±2.4, 6±2.2, and 4±1.3 times for the controls, those with intracystic cholelithiasis, and those with choledocholithiasis, respectively. Compared with the controls, the latter two patient groups showed evident reductions in the frequency of bile flow to the duodenum (p<0.001). Dynamic MRC combined with Molyork loading makes it possible to compute cystic contractile ratios and perform a dynamic examination of bile flow under non-invasive, near-physiological conditions. (author)
Perception of Communication Network Fraud Dynamics by Network ...
African Journals Online (AJOL)
In considering the implications of the varied nature of the potential targets, the paper identifies the view to develop effective intelligence analysis methodologies for network fraud detection and prevention by network administrators and stakeholders. The paper further notes that organizations are fighting an increasingly ...
An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments
Directory of Open Access Journals (Sweden)
Xiaohong Li
2018-03-01
Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.
Directory of Open Access Journals (Sweden)
Z. Q. Yin
2014-03-01
Full Text Available Fracture experiments in a notched semi-circular bend configuration were conducted to test the dynamic fracture toughness of a marble under static-dynamic coupling load using a modified split Hopkinson pressure bar. The fracture process of the specimen was monitored using a high speed (HS camera. Based on digital image correlation (DIC and strain gauges, the full-field strain fields and time-to-fracture of the marble were measured under static-dynamic coupling load. Experimental results show that dynamic fracture toughness was well determined, and the HS-DIC technique provides reliable full-field strain fields in the specimens under static-dynamic coupling loads. The failure characteristics of the marble under external impact were affected obviously by pre-compression stress. Increase of axial pre-compression stress was helpful to improve the crack propagation velocity, and dynamic crack initiation toughness was decreased.
Neural Networks in Modelling Maintenance Unit Load Status
Directory of Open Access Journals (Sweden)
Anđelko Vojvoda
2002-03-01
Full Text Available This paper deals with a way of applying a neural networkfor describing se1vice station load in a maintenance unit. Dataacquired by measuring the workload of single stations in amaintenance unit were used in the process of training the neuralnetwork in order to create a model of the obse1ved system.The model developed in this way enables us to make more accuratepredictions over critical overload. Modelling was realisedby developing and using m-functions of the Matlab software.
Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks.
Onaga, Tomokatsu; Gleeson, James P; Masuda, Naoki
2017-09-08
Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.
Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks
Onaga, Tomokatsu; Gleeson, James P.; Masuda, Naoki
2017-09-01
Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.
Dynamical community structure of populations evolving on genotype networks
International Nuclear Information System (INIS)
Capitán, José A.; Aguirre, Jacobo; Manrubia, Susanna
2015-01-01
Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics
Optimizing the Quality of Dynamic Context Subscriptions for Scarce Network Resources
DEFF Research Database (Denmark)
Shawky, Ahmed; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup
2012-01-01
Scalable access to dynamic context information is a key challenge for future context-sensitive systems. When increasing the access frequency, the information accuracy can improve but at the same time the additional context management traffic may reduce network performance, which creates...... the opposite effect on information reliability. In order to understand and control this trade-off, this paper develops a model that allows to calculate context reliability, captured by the so-called mismatch probability, in relation to the network load. The model is subsequently used for a real time algorithm...
Spontaneous formation of dynamical groups in an adaptive networked system
International Nuclear Information System (INIS)
Li Menghui; Guan Shuguang; Lai, C-H
2010-01-01
In this work, we investigate a model of an adaptive networked dynamical system, where the coupling strengths among phase oscillators coevolve with the phase states. It is shown that in this model the oscillators can spontaneously differentiate into two dynamical groups after a long time evolution. Within each group, the oscillators have similar phases, while oscillators in different groups have approximately opposite phases. The network gradually converts from the initial random structure with a uniform distribution of connection strengths into a modular structure that is characterized by strong intra-connections and weak inter-connections. Furthermore, the connection strengths follow a power-law distribution, which is a natural consequence of the coevolution of the network and the dynamics. Interestingly, it is found that if the inter-connections are weaker than a certain threshold, the two dynamical groups will almost decouple and evolve independently. These results are helpful in further understanding the empirical observations in many social and biological networks.
Structure-based control of complex networks with nonlinear dynamics.
Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka
2017-07-11
What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.
Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism
DEFF Research Database (Denmark)
Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu
2012-01-01
Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical...
Epidemic dynamics and endemic states in complex networks
Pastor-Satorras, Romualdo; Vespignani, Alessandro
2001-06-01
We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.
Epidemic dynamics and endemic states in complex networks
International Nuclear Information System (INIS)
Pastor-Satorras, Romualdo; Vespignani, Alessandro
2001-01-01
We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks
Characterization of Static/Dynamic Topological Routing For Grid Networks
DEFF Research Database (Denmark)
Gutierrez Lopez, Jose Manuel; Cuevas, Ruben; Riaz, M. Tahir
2009-01-01
Grid or 2D Mesh structures are becoming one of the most attractive network topologies to study. They can be used in many different fields raging from future broadband networks to multiprocessors structures. In addition, the high requirements of future services and applications demand more flexible...... and adaptive networks. Topological routing in grid networks is a simple and efficient alternative to traditional routing techniques, e.g. routing tables, and the paper extends this kind of routing providing a "Dynamic" attribute. This new property attempts to improve the overall network performance for future...
Dynamical Encoding by Networks of Competing Neuron Groups: Winnerless Competition
International Nuclear Information System (INIS)
Rabinovich, M.; Volkovskii, A.; Lecanda, P.; Huerta, R.; Abarbanel, H. D. I.; Laurent, G.
2001-01-01
Following studies of olfactory processing in insects and fish, we investigate neural networks whose dynamics in phase space is represented by orbits near the heteroclinic connections between saddle regions (fixed points or limit cycles). These networks encode input information as trajectories along the heteroclinic connections. If there are N neurons in the network, the capacity is approximately e(N-1) ! , i.e., much larger than that of most traditional network structures. We show that a small winnerless competition network composed of FitzHugh-Nagumo spiking neurons efficiently transforms input information into a spatiotemporal output
The Graph Laplacian and the Dynamics of Complex Networks
Energy Technology Data Exchange (ETDEWEB)
Thulasidasan, Sunil [Los Alamos National Laboratory
2012-06-11
In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.
Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak
2010-02-01
This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.
Using adaptive network based fuzzy inference system to forecast regional electricity loads
International Nuclear Information System (INIS)
Ying, L.-C.; Pan, M.-C.
2008-01-01
Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads
Using adaptive network based fuzzy inference system to forecast regional electricity loads
Energy Technology Data Exchange (ETDEWEB)
Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)
2008-02-15
Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)
DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING
National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...
Testing of tunnel support: dynamic load testing of rock support containment systems (eg wire mesh).
CSIR Research Space (South Africa)
Ortlepp, WD
1997-07-01
Full Text Available The objective of this project was to determine the performance characteristics of containment elements of tunnel support in common use in South African mines under dynamic loading. The magnitude of the energy levels in this testing had...
Quality of computerized blast load simulation for non-linear dynamic ...
African Journals Online (AJOL)
Quality of computerized blast load simulation for non-linear dynamic response ... commercial software system and a special-purpose, blast-specific software product to ... depend both on the analysis model of choice and the stand-off distances.
Dynamic analysis of scraper conveyor operation with external loads
Directory of Open Access Journals (Sweden)
Świder Jerzy
2017-01-01
Full Text Available A load to an armoured face conveyor (AFC during coal mining is changeable and very difficult or even impossible to be predicted. Changes of the load to the upper scraper chain affect the load of the driving motor and generate changes in a scraper chain tension. Impact of increasing the external load to the upper scraper chain on the operation of electric motors and on the scraper chain tension is presented. The developed numerical model of the Rybnik 850 conveyor enabled identifying the places of the scraper chain high tension or places of its loosening. An impact of changing frequency of driving motor voltage on AFC’s operational conditions was tested and analysed using the AFC’s numerical model. During tests, tension of the scraper chain on the discharge end and the return end was recorded. High tension of the scraper chain and its loosening during the changeable load were also recorded on upward and downward transportation of run-of-mine material.
Dynamic axle and wheel loads identification: laboratory studies
Zhu, X. Q.; Law, S. S.
2003-12-01
Two methods have been reported by Zhu and Law to identify moving loads on the top of a bridge deck. One is based on the exact solution (ESM) and the other is based on the finite element formulation (FEM). Simulation studies on the effect of different influencing factors have been reported previously. This paper comparatively studies the performances of these two methods with experimental measurements obtained from a bridge/vehicle system in the laboratory. The strains of the bridge deck are measured when a model car moves across the bridge deck along different paths. The moving loads on the bridge deck are identified from the measured strains using these two methods, and the responses are reconstructed from the identified loads for comparison with the measured responses to verify the performances of these methods. Studies on the identification accuracy due to the effect of the number of vibration mode used, the number of measuring points and eccentricities of travelling paths are performed. Results show that the ESM could identify the moving loads individually or as axle loads when they are travelling at an eccentricity with the sensors located close to the travelling path of the forces. And the accuracy of the FEM is dependent on the amount of measured information used in the identification.
Recovery time after localized perturbations in complex dynamical networks
Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.
2017-10-01
Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed
Recovery time after localized perturbations in complex dynamical networks
International Nuclear Information System (INIS)
Mitra, Chiranjit; Kittel, Tim; Kurths, Jürgen; Donner, Reik V; Choudhary, Anshul
2017-01-01
Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed
International Nuclear Information System (INIS)
Dai, H.L.; Wang, X.
2006-01-01
In this paper, an analytical method is introduced to solve the problem for the dynamic stress-focusing and centred-effect of perturbation of the magnetic field vector in orthotropic cylinders under thermal and mechanical shock loads. Analytical expressions for the dynamic stresses and the perturbation of the magnetic field vector are obtained by means of finite Hankel transforms and Laplace transforms. The response histories of dynamic stresses and the perturbation of the field vector are also obtained. In practical examples, the dynamic focusing effect on both magnetoelastic stress and perturbation of the axial magnetic field vector in an orthotropic cylinder subjected to various shock loads is presented and discussed
Successive lag synchronization on dynamical networks with communication delay
International Nuclear Information System (INIS)
Zhang Xin-Jian; Wei Ai-Ju; Li Ke-Zan
2016-01-01
In this paper, successive lag synchronization (SLS) on a dynamical network with communication delay is investigated. In order to achieve SLS on the dynamical network with communication delay, we design linear feedback control and adaptive control, respectively. By using the Lyapunov function method, we obtain some sufficient conditions for global stability of SLS. To verify these results, some numerical examples are further presented. This work may find potential applications in consensus of multi-agent systems. (paper)
Impact evaluation of conducted UWB transients on loads in power-line networks
Directory of Open Access Journals (Sweden)
B. Li
2017-09-01
Full Text Available Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB disturbance, as an example of intentional electromagnetic interference (IEMI source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT, the UWB transient is characterized in the frequency domain. Based on a modified Baum–Liu–Tesche (BLT method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT, we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.
A 3D Lumped Thermal Network Model for Long-term Load Profiles Analysis in High Power IGBT Modules
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Ghimire, Pramod
2016-01-01
)-based simulation is another method which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel...... enables both accurate and fast temperature estimation of high power IGBT modules in the real loading conditions of the converter; meanwhile the critical details of the thermal dynamics and thermal distribution are also maintained. The proposed thermal model is verified by both FEM simulation......The conventional RC lumped thermal networks are widely used to estimate the temperature of power devices, but they are lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high power IGBT modules. On the other hand, Finite Element (FE...
The Influence of External Load on Quadriceps Muscle and Tendon Dynamics during Jumping.
Earp, Jacob E; Newton, Robert U; Cormie, Prue; Blazevich, Anthony J
2017-11-01
Tendons possess both viscous (rate-dependent) and elastic (rate-independent) properties that determine tendon function. During high-speed movements external loading increases both the magnitude (FT) and rate (RFDT) of tendon loading. The influence of external loading on muscle and tendon dynamics during maximal vertical jumping was explored. Ten resistance-trained men performed parallel-depth, countermovement vertical jumps with and without additional load (0%, 30%, 60%, and 90% of maximum squat lift strength), while joint kinetics and kinematics, quadriceps tendon length (LT) and patellar tendon FT and RFDT were estimated using integrated ultrasound, motion analysis and force platform data and muscle tendon modelling. Estimated FT and RFDT, but not peak LT, increased with external loading. Temporal comparisons between 0% and 90% loads revealed that FT was greater with 90% loading throughout the majority of the movement (11%-81% and 87%-95% movement duration). However, RFDT was greater with 90% load only during the early movement initiation phase (8%-15% movement duration) but was greater in the 0% load condition later in the eccentric phase (27%-38% movement duration). LT was longer during the early movement (12%-23% movement duration) but shorter in the late eccentric and early concentric phases (48%-55% movement duration) with 90% load. External loading positively influenced peak FT and RFDT but tendon strain appeared unaffected, suggesting no additive effect of external loading on patellar tendon lengthening during human jumping. Temporal analysis revealed that external loading resulted in a large initial RFDT that may have caused dynamic stiffening of the tendon and attenuated tendon strain throughout the movement. These results suggest that external loading influences tendon lengthening in both a load- and movement-dependent manner.
Practical synchronization on complex dynamical networks via optimal pinning control
Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu
2015-07-01
We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.
Complex networks: when random walk dynamics equals synchronization
International Nuclear Information System (INIS)
Kriener, Birgit; Anand, Lishma; Timme, Marc
2012-01-01
Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for such equivalence for networks of pulse-coupled oscillators, which serve as models for neurons and pacemaker cells interacting by exchanging electric pulses or fireflies interacting via light flashes. We find that the pulse synchronization process is less simple, but there are classes of, e.g., network topologies that ensure equivalence. In particular, local dynamical operators are required to be doubly stochastic. These results provide a natural link between stochastic processes and deterministic synchronization on networks. Tools for analyzing diffusion (or, more generally, Markov processes) may now be transferred to pin down features of synchronization in networks of pulse-coupled units such as neural circuits. (paper)
Hazell, Tom J; Kenno, Kenji A; Jakobi, Jennifer M
2010-07-01
The purpose of this investigation was to examine if the addition of a light external load would enhance whole-body vibration (WBV)-induced increases in muscle activity during dynamic squatting in 4 leg muscles. Thirteen recreationally active male university students performed a series of dynamic squats (unloaded with no WBV, unloaded with WBV, loaded with no WBV, and loaded with WBV). The load was set to 30% of body mass and WBV included 25-, 35-, and 45-Hz frequencies with 4-mm amplitude. Muscle activity was recorded with surface electromyography (EMG) on the vastus lateralis (VL), biceps femoris (BF), tibialis anterior (TA), and gastrocnemius (GC) and is reported as EMGrms (root mean square) normalized to %maximal voluntary exertion. During unloaded dynamic squats, exposure to WBV (45 Hz) significantly (p squat exercise in all muscles but decreased the TA. This loaded level of muscle activity was further increased with WBV (45 Hz) in all muscles. The WBV-induced increases in muscle activity in the loaded condition (approximately 3.5%) were of a similar magnitude to the WBV-induced increases during the unloaded condition (approximately 2.5%) demonstrating the addition of WBV to unloaded or loaded dynamic squatting results in an increase in muscle activity. These results demonstrate the potential effectiveness of using external loads with exposure to WBV.
Xu, Yuan; Dai, Feng
2018-03-01
A novel method is developed for characterizing the mechanical response and failure mechanism of brittle rocks under dynamic compression-shear loading: an inclined cylinder specimen using a modified split Hopkinson pressure bar (SHPB) system. With the specimen axis inclining to the loading direction of SHPB, a shear component can be introduced into the specimen. Both static and dynamic experiments are conducted on sandstone specimens. Given carefully pulse shaping, the dynamic equilibrium of the inclined specimens can be satisfied, and thus the quasi-static data reduction is employed. The normal and shear stress-strain relationships of specimens are subsequently established. The progressive failure process of the specimen illustrated via high-speed photographs manifests a mixed failure mode accommodating both the shear-dominated failure and the localized tensile damage. The elastic and shear moduli exhibit certain loading-path dependence under quasi-static loading but loading-path insensitivity under high loading rates. Loading rate dependence is evidently demonstrated through the failure characteristics involving fragmentation, compression and shear strength and failure surfaces based on Drucker-Prager criterion. Our proposed method is convenient and reliable to study the dynamic response and failure mechanism of rocks under combined compression-shear loading.
Dynamic Load Balancing for PIC code using Eulerian/Lagrangian partitioning
Sauget, Marc; Latu, Guillaume
2017-01-01
This document presents an analysis of different load balance strategies for a Plasma physics code that models high energy particle beams with PIC method. A comparison of different load balancing algorithms is given: static or dynamic ones. Lagrangian and Eulerian partitioning techniques have been investigated.
Loading Processes Dynamics Modelling Taking into Account the Bucket-Soil Interaction
Directory of Open Access Journals (Sweden)
Carmen Debeleac
2007-10-01
Full Text Available The author propose three dynamic models specialized for the vibrations and resistive forces analysis that appear at the loading process with different construction equipment like frontal loaders and excavators.The models used putting into evidence the components of digging: penetration, cutting, and loading.The conclusions of this study consist by evidentiate the dynamic overloads that appear on the working state and that induced the self-oscillations into the equipment structure.
A Reduced-Order Model for Evaluating the Dynamic Response of Multilayer Plates to Impulsive Loads
2016-04-12
A REDUCED-ORDER MODEL FOR EVALUATING THE DYNAMIC RESPONSE OF MULTILAYER PLATES TO IMPULSIVE LOADS Weiran Jiang, Alyssa Bennett, Nickolas...innovative multilayer materials or structures to optimize the dynamic performance as a mechanism to absorb and spread energy from an impulsive load...models. • Optimizing the structural weight and levels of protection of the multilayer plates with a good combination of materials. Technical Approach 2016
International Nuclear Information System (INIS)
Shumilov, V.F.
2003-01-01
New methods for the investigation of automatic systems based on the inverse tasks of dynamics with the use of rational, trigonometric and polynomial spline functions are discussed. By means of SH function the technological regimes: start-up, steadiness, racing, braking, reverse, stop were determined. Procedure for the provision of dynamic load smoothness is suggested, and example of control over the transport systems for fuel load is considered [ru
Network dynamics in the healthy and epileptic developing brain
Directory of Open Access Journals (Sweden)
Richard Rosch
2018-03-01
Full Text Available Electroencephalography (EEG allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months. We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis.
Network evolution driven by dynamics applied to graph coloring
International Nuclear Information System (INIS)
Wu Jian-She; Li Li-Guang; Yu Xin; Jiao Li-Cheng; Wang Xiao-Hua
2013-01-01
An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring
Simulating market dynamics: interactions between consumer psychology and social networks.
Janssen, Marco A; Jager, Wander
2003-01-01
Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).
Safety margins associated with containment structures under dynamic loading
International Nuclear Information System (INIS)
Lu, S.C.
1978-01-01
A technical basis for assessing the true safety margins of containment structures involved with MARK I boiling water reactor reevaluation activities is presented. It is based on the results of a plane-strain, large displacement, elasto-plastic, finite-element analysis of a thin cylindrical shell subjected to external and internal pressure pulses. An analytical procedure is presented for estimating the ultimate load capacity of the thin shell structure, and subsequently, for quantifying the design margins of safety for the type of loads under consideration. For defining failure of structures, a finite strain failure criterion is derived that accounts for multiaxiality effects
Dynamic photonic lightpaths in the StarPlane network
Grosso, P.; Marchal, D.; Maassen, J.; Bernier, E.; Xu, L.; de Laat, C.
2009-01-01
The StarPlane project enables users to dynamically control network photonic paths. Applications running on the Distributed ASCI Supercomputer (DAS-3) can manipulate wavelengths in the Dutch research and education network SURFnet6. The goal is to achieve fast switching times so that when the
Complete synchronization on multi-layer center dynamical networks
International Nuclear Information System (INIS)
Liu Meng; Shao Yingying; Fu Xinchu
2009-01-01
In this paper, complete synchronization of three-layer center networks is studied. By using linear stability analysis approach, several different coupling schemes of three-layer center networks with the Logistic map local dynamics are discussed, and the stability conditions for synchronization are illustrated via some examples.
Collaborative Recurrent Neural Networks forDynamic Recommender Systems
2016-11-22
JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population
Popularity and Adolescent Friendship Networks : Selection and Influence Dynamics
Dijkstra, Jan Kornelis; Cillessen, Antonius H. N.; Borch, Casey
This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to
Popularity and Adolescent Friendship Networks: Selection and Influence Dynamics
Dijkstra, J.K.; Cillessen, A.H.N.; Borch, C.
2013-01-01
This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to
Popularity and Adolescent Friendship Networks: Selection and Influence Dynamics
Dijkstra, Jan Kornelis; Cillessen, Antonius H. N.; Borch, Casey
2013-01-01
This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to enhance their status through befriending higher…
Resumption of dynamism in damaged networks of coupled oscillators
Kundu, Srilena; Majhi, Soumen; Ghosh, Dibakar
2018-05-01
Deterioration in dynamical activities may come up naturally or due to environmental influences in a massive portion of biological and physical systems. Such dynamical degradation may have outright effect on the substantive network performance. This requires us to provide some proper prescriptions to overcome undesired circumstances. In this paper, we present a scheme based on external feedback that can efficiently revive dynamism in damaged networks of active and inactive oscillators and thus enhance the network survivability. Both numerical and analytical investigations are performed in order to verify our claim. We also provide a comparative study on the effectiveness of this mechanism for feedbacks to the inactive group or to the active group only. Most importantly, resurrection of dynamical activity is realized even in time-delayed damaged networks, which are considered to be less persistent against deterioration in the form of inactivity in the oscillators. Furthermore, prominence in our approach is substantiated by providing evidence of enhanced network persistence in complex network topologies taking small-world and scale-free architectures, which makes the proposed remedy quite general. Besides the study in the network of Stuart-Landau oscillators, affirmative influence of external feedback has been justified in the network of chaotic Rössler systems as well.
Non-homogeneous dynamic Bayesian networks for continuous data
Grzegorczyk, Marco; Husmeier, Dirk
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with non-homogeneous temporal processes. Various approaches to relax the homogeneity assumption have recently been proposed. The present paper presents a combination of a Bayesian network with
Developing a dynamic control system for mine compressed air networks
Van Heerden, S.W.; Pelzer, R.; Marais, J.H.
2014-01-01
Mines in general, make use of compressed air systems for daily operational activities. Compressed air on mines is traditionally distributed via compressed air ring networks where multiple shafts are supplied with compressed air from an integral system. These compressed air networks make use of a number of compressors feeding the ring from various locations in the network. While these mines have sophisticated control systems to control these compressors, they are not dynamic systems. Compresso...
Energy Technology Data Exchange (ETDEWEB)
Kulicke, B [Inst. fuer Hochspannungstechnik und Starkstromanlagen, Berlin (Germany); Schlegel, S [Inst. fuer Hochspannungstechnik und Starkstromanlagen, Berlin (Germany)
1993-06-28
An important part of network operation management is the estimation and maintenance of the security of supply. So far the control personnel has only been supported by static network analyses and safety calculations. The authors describe an expert system, which is coupled to a real time simulation program on a transputer basis, for dynamic network safety calculations. They also introduce the system concept and the most important functions of the expert system. (orig.)
Traffic dynamics on coupled spatial networks
International Nuclear Information System (INIS)
Du, Wen-Bo; Zhou, Xing-Lian; Chen, Zhen; Cai, Kai-Quan; Cao, Xian-Bin
2014-01-01
With the rapid development of modern traffic, various means of transportation systems make it more convenient and diversified for passengers to travel out. In this paper, we establish a two-layered spatial network model where the low-speed lower layer is a regular lattice and the high-speed upper layer is a scale-free network embedded in the lattice. Passengers will travel along the path with the minimal travel time, and they can transfer from one layer to the other, which will induce extra transfer cost. We extensively investigate the traffic process on these coupled spatial networks and focus on the effect of the parameter α, the speed ratio between two networks. It is found that, as α grows, the network capacity of the coupled networks increases in the early stage and then decreases, indicating that cooperation between the coupled networks will induce the highest network capacity at an optimal α. We then provide an explanation for this non-monotonous dependence from a micro-scope point of view. The travel time reliability is also examined. Both in free-flow state and congestion state, the travel time is linearly related to the Euclidean distance. However, the variance of travel time in the congestion state is remarkably larger than that in the free-flow state, namely, people have to set aside more redundant time in an unreliable traffic system
International Nuclear Information System (INIS)
Montani, S.; Portinale, L.; Bobbio, A.; Codetta-Raiteri, D.
2008-01-01
In this paper, we present RADYBAN (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained
Vaccination intervention on epidemic dynamics in networks
Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Zhou, Tao
2013-02-01
Vaccination is an important measure available for preventing or reducing the spread of infectious diseases. In this paper, an epidemic model including susceptible, infected, and imperfectly vaccinated compartments is studied on Watts-Strogatz small-world, Barabási-Albert scale-free, and random scale-free networks. The epidemic threshold and prevalence are analyzed. For small-world networks, the effective vaccination intervention is suggested and its influence on the threshold and prevalence is analyzed. For scale-free networks, the threshold is found to be strongly dependent both on the effective vaccination rate and on the connectivity distribution. Moreover, so long as vaccination is effective, it can linearly decrease the epidemic prevalence in small-world networks, whereas for scale-free networks it acts exponentially. These results can help in adopting pragmatic treatment upon diseases in structured populations.
Functional clustering in hippocampal cultures: relating network structure and dynamics
International Nuclear Information System (INIS)
Feldt, S; Dzakpasu, R; Olariu, E; Żochowski, M; Wang, J X; Shtrahman, E
2010-01-01
In this work we investigate the relationship between gross anatomic structural network properties, neuronal dynamics and the resultant functional structure in dissociated rat hippocampal cultures. Specifically, we studied cultures as they developed under two conditions: the first supporting glial cell growth (high glial group), and the second one inhibiting it (low glial group). We then compared structural network properties and the spatio-temporal activity patterns of the neurons. Differences in dynamics between the two groups could be linked to the impact of the glial network on the neuronal network as the cultures developed. We also implemented a recently developed algorithm called the functional clustering algorithm (FCA) to obtain the resulting functional network structure. We show that this new algorithm is useful for capturing changes in functional network structure as the networks evolve over time. The FCA detects changes in functional structure that are consistent with expected dynamical differences due to the impact of the glial network. Cultures in the high glial group show an increase in global synchronization as the cultures age, while those in the low glial group remain locally synchronized. We additionally use the FCA to quantify the amount of synchronization present in the cultures and show that the total level of synchronization in the high glial group is stronger than in the low glial group. These results indicate an interdependence between the glial and neuronal networks present in dissociated cultures
Discriminating lysosomal membrane protein types using dynamic neural network.
Tripathi, Vijay; Gupta, Dwijendra Kumar
2014-01-01
This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.
Dynamic behaviour of TM380 mild steel and Ti6Al4V alloy subjected to blast loading
CSIR Research Space (South Africa)
Shoke, Lerato
2016-10-01
Full Text Available and Base Metals Development Network Conference 2016, 19-20 October 2016, KwaZulu Natal, Maharani Hotel Dynamic behaviour of TM380 mild steel and Ti6Al4V alloy subjected to blast loading L. Shoke,1* K. Mutombo2, I.M. Snyman1 and T. Sono1 1... Landwards Sciences, Defence Peace Safety and Security (DPSS), 2 Material Sciences and Manufacturing (MSM), Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa Lshoke@csir.co.za Abstract This paper deals...
Load bearing and deformation behaviour of dynamically loaded wide plate specimens
International Nuclear Information System (INIS)
Julisch, P.; Haedrich, H.J.; Stadtmueller, W.; Sturm, D.
1989-01-01
For the testing of large-scale specimens, a 12 MN-High Loading Rate Tensile Testing Machine was designed and built at MPA Stuttgart. The aim was to determine the influence of high loading rates on the stress and strain behaviour of unwelded and welded components of ferritic and austenitic materials. This new generation of testing machines is driven by a propellant charge, and generates a maximum tensile force of 12 MN with a piston velocity of 25 m/s after a stroke of 20 mm, or a maximum velocity of 60 m/s after a stroke of 400 mm. In a first test programme, welded and unwelded wide plate specimens made of material X 6 CrNi 18 11 were tested at room temperature with different strain rates from 10 -3 /s to 63/s. In addition to a description of the 12 MN-High Loading Rate Tensile Testing Machine, the results of the high loading rate tensile tests performed will be presented and compared with quasistatically tested wide plate specimens. (orig.)
Dynamic load balance scheme for the DSMC algorithm
International Nuclear Information System (INIS)
Li, Jin; Geng, Xiangren; Jiang, Dingwu; Chen, Jianqiang
2014-01-01
The direct simulation Monte Carlo (DSMC) algorithm, devised by Bird, has been used over a wide range of various rarified flow problems in the past 40 years. While the DSMC is suitable for the parallel implementation on powerful multi-processor architecture, it also introduces a large load imbalance across the processor array, even for small examples. The load imposed on a processor by a DSMC calculation is determined to a large extent by the total of simulator particles upon it. Since most flows are impulsively started with initial distribution of particles which is surely quite different from the steady state, the total of simulator particles will change dramatically. The load balance based upon an initial distribution of particles will break down as the steady state of flow is reached. The load imbalance and huge computational cost of DSMC has limited its application to rarefied or simple transitional flows. In this paper, by taking advantage of METIS, a software for partitioning unstructured graphs, and taking the total of simulator particles in each cell as a weight information, the repartitioning based upon the principle that each processor handles approximately the equal total of simulator particles has been achieved. The computation must pause several times to renew the total of simulator particles in each processor and repartition the whole domain again. Thus the load balance across the processors array holds in the duration of computation. The parallel efficiency can be improved effectively. The benchmark solution of a cylinder submerged in hypersonic flow has been simulated numerically. Besides, hypersonic flow past around a complex wing-body configuration has also been simulated. The results have displayed that, for both of cases, the computational time can be reduced by about 50%
Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.
Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu
2017-10-01
This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.
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...
Stochastic Online Learning in Dynamic Networks under Unknown Models
2016-08-02
The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for
The Dynamics of network and dyad level supply management
DEFF Research Database (Denmark)
Ellegaard, Chris
-supplier relation and its immediate network context, are presented. In analysing the data, the dynamic interdependency between management of one level and management of the other, will be demonstrated. The analysis reveals a need for an alternating approach to supply management, which takes the dynamic complexity...
Classification of networks of automata by dynamical mean field theory
International Nuclear Information System (INIS)
Burda, Z.; Jurkiewicz, J.; Flyvbjerg, H.
1990-01-01
Dynamical mean field theory is used to classify the 2 24 =65,536 different networks of binary automata on a square lattice with nearest neighbour interactions. Application of mean field theory gives 700 different mean field classes, which fall in seven classes of different asymptotic dynamics characterized by fixed points and two-cycles. (orig.)
Dynamic baseline detection method for power data network service
Chen, Wei
2017-08-01
This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.
Dynamic fracture initiation in brittle materials under combined mode I/II loading
International Nuclear Information System (INIS)
Nakano, M.; Kishida, K.; Yamauchi, Y.; Sogabe, Y.
1994-01-01
A new test method has been developed to measure the resistance of dynamic fracture initiation in brittle materials under combined mode I/II loadings. The Brazilian disks with center-cracks have been fractured under oblique impact loadings in diametral-compression. The dynamic stress intensity factors of mode I and II are evaluated from the superposition integrals of the step response functions for the cracked disk. The experimental results are presented to elucidate the influence of loading rate on the combined mode fracture toughness for ceramics and glasses. (orig.)
A STUDY ON DYNAMIC LOAD HISTORY RECONSTRUCTION USING PSEUDO-INVERSE METHODS
Santos, Ariane Rebelato Silva dos; Marczak, Rogério José
2017-01-01
Considering that the vibratory forces generally cannot be measured directly at the interface of two bodies, an inverse method is studied in the present work to recover the load history in such cases. The proposed technique attempts to reconstruct the dynamic loads history by using a frequency domain analysis and Moore-Penrose pseudo-inverses of the frequency response function (FRF) of the system. The methodology consists in applying discrete dynamic loads on a finite element model in the time...
Spatial price dynamics: From complex network perspective
Li, Y. L.; Bi, J. T.; Sun, H. J.
2008-10-01
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.
The architecture of dynamic reservoir in the echo state network
Cui, Hongyan; Liu, Xiang; Li, Lixiang
2012-09-01
Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.
Scalable Approaches to Control Network Dynamics: Prospects for City Networks
Motter, Adilson E.; Gray, Kimberly A.
2014-07-01
A city is a complex, emergent system and as such can be conveniently represented as a network of interacting components. A fundamental aspect of networks is that the systemic properties can depend as much on the interactions as they depend on the properties of the individual components themselves. Another fundamental aspect is that changes to one component can affect other components, in a process that may cause the entire or a substantial part of the system to change behavior. Over the past 2 decades, much research has been done on the modeling of large and complex networks involved in communication and transportation, disease propagation, and supply chains, as well as emergent phenomena, robustness and optimization in such systems...
Dynamic behaviour of a typical PHWR under earthquake load conditions
International Nuclear Information System (INIS)
Fischer, U.; Brandt, K.; Krutzik, N.J.
1984-01-01
The paper deals with dynamic calculations for a PHWR reactor building founded on rock and on a base isolation system. The zero period accelerations, displacements, mode shapes and the floor response spectra of both calculations are compared. (Author) [pt
Extracting neuronal functional network dynamics via adaptive Granger causality analysis.
Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash
2018-04-24
Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.
Aircraft dynamic loads generated in wake vortex encounters
Suñer Perucho, Carles
2014-01-01
The study illustrated in these pages was developed in the Structural Dynamics and Aeroelasticity Department of the Military Aircraft division of Airbus Defence and Space in Getafe, Madrid (Spain). That department is a multidisciplinary one involving several categories. Some of its competences are the analysis of impacts, acoustics and vibrations for the aircraft and all their systems. Also, the dynamic response of the aircraft to different events is part of the tasks for that department. It i...
Dynamic properties of epidemic spreading on finite size complex networks
Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben
2005-11-01
The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.
Congested Link Inference Algorithms in Dynamic Routing IP Network
Directory of Open Access Journals (Sweden)
Yu Chen
2017-01-01
Full Text Available The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP and Rest Bayesian Network Model (RBNM, we proposed an Improved CLINK (ICLINK algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.
Actin dynamics and the elasticity of cytoskeletal networks
Directory of Open Access Journals (Sweden)
2009-09-01
Full Text Available The structural integrity of a cell depends on its cytoskeleton, which includes an actin network. This network is transient and depends upon the continual polymerization and depolymerization of actin. The degradation of an actin network, and a corresponding reduction in cell stiffness, can indicate the presence of disease. Numerical simulations will be invaluable for understanding the physics of these systems and the correlation between actin dynamics and elasticity. Here we develop a model that is capable of generating actin network structures. In particular, we develop a model of actin dynamics which considers the polymerization, depolymerization, nucleation, severing, and capping of actin filaments. The structures obtained are then fed directly into a mechanical model. This allows us to qualitatively assess the effects of changing various parameters associated with actin dynamics on the elasticity of the material.
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.
Dynamic Virtual LANs for Adaptive Network Security
National Research Council Canada - National Science Library
Merani, Diego; Berni, Alessandro; Leonard, Michel
2004-01-01
The development of Network-Enabled capabilities in support of undersea research requires architectures for the interconnection and data sharing that are flexible, scalable, and built on open standards...
Value network dynamics and industry evolution
Vermeulen, B.
2012-01-01
Machines, appliances, and consumption goods are developed and produced in value networks populated by firms ranging from final assemblers, component suppliers, complement providers, the suppliers’ suppliers, all the way upstream to firms that extrude raw material. Evolutionary models of industry
Dynamic Data-Driven UAV Network for Plume Characterization
2016-05-23
AFRL-AFOSR-VA-TR-2016-0203 Dynamic Data-Driven UAV Network for Plume Characterization Kamran Mohseni UNIVERSITY OF FLORIDA Final Report 05/23/2016...AND SUBTITLE Dynamic Data-Driven UAV Network for Plume Characterization 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0090 5c. PROGRAM ELEMENT...studied a dynamic data driven (DDD) approach to operation of a heterogeneous team of unmanned aerial vehicles ( UAVs ) or micro/miniature aerial
Network Reconstruction of Dynamic Biological Systems
Asadi, Behrang
2013-01-01
Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of differe...
Connectivity, topology and dynamics in climate networks
Czech Academy of Sciences Publication Activity Database
Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin
2012-01-01
Roč. 14, - (2012), s. 8397 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : complex networks * climate network * connectivity * entropy rate * El Nino Southern Oscillation * North Atlantic Oscillation Subject RIV: BB - Applied Statistics, Operational Research
Dynamic Aggregation Protocol for Wireless Sensor Networks
Mounir Said , Adel; William Ibrahim , Ashraf; Soua , Ahmed; Afifi , Hossam
2013-01-01
International audience; Sensor networks suffer from limited capabilities such as bandwidth, low processing power, and memory size. There is therefore a need for protocols that deliver sensor data in an energy-efficient way to the sink. One of those techniques, it gathers sensors' data in a small size packet suitable for transmission. In this paper, we propose a new Effective Data Aggregation Protocol (DAP) to reduce the energy consumption in Wireless Sensor Networks (WSNs), which prolongs the...
Strength and behavior in shear of reinforced concrete deep beams under dynamic loading conditions
Energy Technology Data Exchange (ETDEWEB)
Adhikary, Satadru Das [School of Civil and Environmental Engineering, Nanyang Technological University, 639798 (Singapore); Li, Bing, E-mail: cbli@ntu.edu.sg [School of Civil and Environmental Engineering, Nanyang Technological University, 639798 (Singapore); Fujikake, Kazunori [Department of Civil and Environmental Engineering, National Defense Academy, Yokosuka 239 8686 (Japan)
2013-06-15
Highlights: ► Effects of wider range of loading rates on dynamic shear behavior of RC deep beams. ► Experimental investigation of RC deep beam with and without shear reinforcements. ► Verification of experimental results with truss model and FE simulation results. ► Empirical equations are proposed to predict the dynamic increase factor of maximum resistance. -- Abstract: Research on reinforced concrete (RC) deep beams has seen considerable headway over the past three decades; however, information on the dynamic shear strength and behavior of RC deep beams under varying rates of loads remains limited. This paper describes the experimental results of 24 RC deep beams with and without shear reinforcements under varying rates of concentrated loading. Results obtained serve as useful data on shear resistance, failure patterns and strain rates corresponding to varying loading rates. An analytical truss model approach proves its efficacy in predicting the dynamic shear resistance under varying loading rates. Furthermore, three-dimensional nonlinear finite element (FE) model is described and the simulation results are verified with the experimental results. A parametric study is then conducted to investigate the influence of longitudinal reinforcement ratio, transverse reinforcement ratio and shear span to effective depth ratio on shear behavior. Subsequently, two empirical equations were proposed by integrating the various parameters to assess the dynamic increase factor (DIF) of maximum resistance under varying rates of concentrated loading.
Analysing Stagecoach Network Problem Using Dynamic ...
African Journals Online (AJOL)
In this paper we present a recursive dynamic programming algorithm for solving the stagecoach problem. The algorithm is computationally more efficient than the first method as it obtains its minimum total cost using the suboptimal policies of the different stages without computing the cost of all the routes. By the dynamic ...
Identifying and tracking dynamic processes in social networks
Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George
2006-05-01
The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.
Cytoskeleton dynamics: Fluctuations within the network
International Nuclear Information System (INIS)
Bursac, Predrag; Fabry, Ben; Trepat, Xavier; Lenormand, Guillaume; Butler, James P.; Wang, Ning; Fredberg, Jeffrey J.; An, Steven S.
2007-01-01
Out-of-equilibrium systems, such as the dynamics of a living cytoskeleton (CSK), are inherently noisy with fluctuations arising from the stochastic nature of the underlying biochemical and molecular events. Recently, such fluctuations within the cell were characterized by observing spontaneous nano-scale motions of an RGD-coated microbead bound to the cell surface [Bursac et al., Nat. Mater. 4 (2005) 557-561]. While these reported anomalous bead motions represent a molecular level reorganization (remodeling) of microstructures in contact with the bead, a precise nature of these cytoskeletal constituents and forces that drive their remodeling dynamics are largely unclear. Here, we focused upon spontaneous motions of an RGD-coated bead and, in particular, assessed to what extent these motions are attributable to (i) bulk cell movement (cell crawling), (ii) dynamics of focal adhesions, (iii) dynamics of lipid membrane, and/or (iv) dynamics of the underlying actin CSK driven by myosin motors
State-dependent intrinsic predictability of cortical network dynamics.
Directory of Open Access Journals (Sweden)
Leila Fakhraei
Full Text Available The information encoded in cortical circuit dynamics is fleeting, changing from moment to moment as new input arrives and ongoing intracortical interactions progress. A combination of deterministic and stochastic biophysical mechanisms governs how cortical dynamics at one moment evolve from cortical dynamics in recently preceding moments. Such temporal continuity of cortical dynamics is fundamental to many aspects of cortex function but is not well understood. Here we study temporal continuity by attempting to predict cortical population dynamics (multisite local field potential based on its own recent history in somatosensory cortex of anesthetized rats and in a computational network-level model. We found that the intrinsic predictability of cortical dynamics was dependent on multiple factors including cortical state, synaptic inhibition, and how far into the future the prediction extends. By pharmacologically tuning synaptic inhibition, we obtained a continuum of cortical states with asynchronous population activity at one extreme and stronger, spatially extended synchrony at the other extreme. Intermediate between these extremes we observed evidence for a special regime of population dynamics called criticality. Predictability of the near future (10-100 ms increased as the cortical state was tuned from asynchronous to synchronous. Predictability of the more distant future (>1 s was generally poor, but, surprisingly, was higher for asynchronous states compared to synchronous states. These experimental results were confirmed in a computational network model of spiking excitatory and inhibitory neurons. Our findings demonstrate that determinism and predictability of network dynamics depend on cortical state and the time-scale of the dynamics.
Influence of the implant abutment types and the dynamic loading on initial screw loosening
Kim, Eun-Sook
2013-01-01
PURPOSE This study examined the effects of the abutment types and dynamic loading on the stability of implant prostheses with three types of implant abutments prepared using different fabrication methods by measuring removal torque both before and after dynamic loading. MATERIALS AND METHODS Three groups of abutments were produced using different types of fabrication methods; stock abutment, gold cast abutment, and CAD/CAM custom abutment. A customized jig was fabricated to apply the load at 30° to the long axis. The implant fixtures were fixed to the jig, and connected to the abutments with a 30 Ncm tightening torque. A sine curved dynamic load was applied for 105 cycles between 25 and 250 N at 14 Hz. Removal torque before loading and after loading were evaluated. The SPSS was used for statistical analysis of the results. A Kruskal-Wallis test was performed to compare screw loosening between the abutment systems. A Wilcoxon signed-rank test was performed to compare screw loosening between before and after loading in each group (α=0.05). RESULTS Removal torque value before loading and after loading was the highest in stock abutment, which was then followed by gold cast abutment and CAD/CAM custom abutment, but there were no significant differences. CONCLUSION The abutment types did not have a significant influence on short term screw loosening. On the other hand, after 105 cycles dynamic loading, CAD/CAM custom abutment affected the initial screw loosening, but stock abutment and gold cast abutment did not. PMID:23509006
Tourist activated networks: Implications for dynamic packaging systems in tourism
DEFF Research Database (Denmark)
Zach, Florian; Gretzel, Ulrike; Fesenmaier, Daniel R.
2008-01-01
This paper discusses tourist activated networks as a concept to inform technological applications supporting dynamic bundling and en-route recommendations. Empirical data was collected from travellers who visited a regional destination in the US and then analyzed with respect to its network...... structure. The results indicate that the tourist activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist activated network and provide implications for technology design and tourism...
Analysis of recurrent neural networks for short-term energy load forecasting
Di Persio, Luca; Honchar, Oleksandr
2017-11-01
Short-term forecasts have recently gained an increasing attention because of the rise of competitive electricity markets. In fact, short-terms forecast of possible future loads turn out to be fundamental to build efficient energy management strategies as well as to avoid energy wastage. Such type of challenges are difficult to tackle both from a theoretical and applied point of view. Latter tasks require sophisticated methods to manage multidimensional time series related to stochastic phenomena which are often highly interconnected. In the present work we first review novel approaches to energy load forecasting based on recurrent neural network, focusing our attention on long/short term memory architectures (LSTMs). Such type of artificial neural networks have been widely applied to problems dealing with sequential data such it happens, e.g., in socio-economics settings, for text recognition purposes, concerning video signals, etc., always showing their effectiveness to model complex temporal data. Moreover, we consider different novel variations of basic LSTMs, such as sequence-to-sequence approach and bidirectional LSTMs, aiming at providing effective models for energy load data. Last but not least, we test all the described algorithms on real energy load data showing not only that deep recurrent networks can be successfully applied to energy load forecasting, but also that this approach can be extended to other problems based on time series prediction.
Multi-Layer Mobility Load Balancing in a Heterogeneous LTE Network
DEFF Research Database (Denmark)
Fotiadis, Panagiotis; Polignano, Michele; Laselva, Daniela
2012-01-01
This paper analyzes the behavior of a distributed Mobility Load Balancing (MLB) scheme in a multi-layer 3GPP (3rd Generation Partnership Project) Long Term Evolution (LTE) deployment with different User Equipment (UE) densities in certain network areas covered with pico cells. Target of the study...
Suryanarayana, Gowri; Lago Garcia, J.; Geysen, Davy; Aleksiejuk, Piotr; Johansson, Christian
2018-01-01
Recent research has seen several forecasting methods being applied for heat load forecasting of district heating networks. This paper presents two methods that gain significant improvements compared to the previous works. First, an automated way of handling non-linear dependencies in linear
A constitutive model for concrete under dynamic loading
International Nuclear Information System (INIS)
Suaris, W.; Shah, S.P.
1983-01-01
A continuous damage theory for the quasistatic and dynamic behaviour of concrete is presented. The continuous damage theory is rational choice for use in predicing the dynamic behaviour of concrete as the strain-rate effects that have been observed for concrete can to a large extent be attributed to the rate-sensitivity of the microcracking process. A vectorial representation is adopted for the damage to account for the planar nature of the microcracks in concrete. Damage is treated as an internal state variable influencing the free energy of the material and the constitutive equations and the damage evolution equations are derived consistently using thermodynamic considerations. The developed constitutive model is then calibrated by using test results in flexure and compression over a range of strain-rates. The constitutive model is also shown to be capable of predicting certain other experimentally observed characteristics of the dynamic response of concrete. (orig./HP)
Directory of Open Access Journals (Sweden)
Houda Jouini
2010-01-01
Full Text Available As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.
Dynamic Analysis of Helical Planetary Gear Sets under Combined Force and Moment Loading
Directory of Open Access Journals (Sweden)
Yanfang Liu
2017-01-01
Full Text Available The dynamic behavior of a single-stage planetary gear set with helical gears of multishaft automotive automatic transmissions has been studied, in which one component of the planetary gear set is imposed by additional external vertical and axial loading from countershaft gear pair in addition to the moment. Under these combined loading conditions, the contributions of the deflections of the ring gear and the carrier cannot be neglected. A three-dimensional nonlinear time-variant dynamic model considering not only the transverse, torsional, axial, and rotational motions of the gears but also the elasticity of the mounted shafts has been developed by combining the lumped parameter method with finite element method. The natural modes and the forced vibration responses due to static transmission errors have been obtained. The proposed dynamic model is employed to describe the effects of the combined external loading condition and positioning on the dynamic behavior of a four-planet system.
Dynamic analysis of a pumped-storage hydropower plant with random power load
Zhang, Hao; Chen, Diyi; Xu, Beibei; Patelli, Edoardo; Tolo, Silvia
2018-02-01
This paper analyzes the dynamic response of a pumped-storage hydropower plant in generating mode. Considering the elastic water column effects in the penstock, a linearized reduced order dynamic model of the pumped-storage hydropower plant is used in this paper. As the power load is always random, a set of random generator electric power output is introduced to research the dynamic behaviors of the pumped-storage hydropower plant. Then, the influences of the PI gains on the dynamic characteristics of the pumped-storage hydropower plant with the random power load are analyzed. In addition, the effects of initial power load and PI parameters on the stability of the pumped-storage hydropower plant are studied in depth. All of the above results will provide theoretical guidance for the study and analysis of the pumped-storage hydropower plant.
Towards building a neural network model for predicting pile static load test curves
Directory of Open Access Journals (Sweden)
Alzo’ubi A. K.
2018-01-01
Full Text Available In the United Arab Emirates, Continuous Flight Auger piles are the most widely used type of deep foundation. To test the pile behaviour, the Static Load Test is routinely conducted in the field by increasing the dead load while monitoring the displacement. Although the test is reliable, it is expensive to conduct. This test is usually conducted in the UAE to verify the pile capacity and displacement as the load increase and decreases in two cycles. In this paper we will utilize the Artificial Neural Network approach to build a model that can predict a complete Static Load Pile test. We will show that by integrating the pile configuration, soil properties, and ground water table in one artificial neural network model, the Static Load Test can be predicted with confidence. We believe that based on this approach, the model is able to predict the entire pile load test from start to end. The suggested approach is an excellent tool to reduce the cost associated with such expensive tests or to predict pile’s performance ahead of the actual test.
Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks
Directory of Open Access Journals (Sweden)
Francisco eAboitiz
2014-03-01
Full Text Available A cardinal symptom of Attenion Deficit and Hyperactivity Disorder (ADHD is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the Default Mode Network (DMN. Related networks are the ventral attentional network (VAN involved in attentional shifting, and the salience network (SN related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produce an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.
Rumor Diffusion in an Interests-Based Dynamic Social Network
Directory of Open Access Journals (Sweden)
Mingsheng Tang
2013-01-01
Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.
Study on the Flare Load Estimation of the Deethanizer using Dynamic Simulation
Energy Technology Data Exchange (ETDEWEB)
Park, Kyungtae; Won, Wangyun [GS EC, Seoul (Korea, Republic of); Shin, Dongil [Myongji University, Yongin (Korea, Republic of)
2014-10-15
A flare system is a very important system that crucially affects on the process safety in chemical plants. If a flare system is designed too small, it cannot prevent catastrophic accidents of a chemical plant. On the other hand, if a flare system is designed too large, it will waste resources. Therefore, reasonable relief load estimation has been a crucial issue in the industry. American Petroleum Institute (API) suggests basic guidelines for relief load estimation, and a lot of engineering companies have developed their own relief load estimation methods that use an unbalanced heat and material method. However, these methods have to involve lots of conservative assumptions that lead to an overestimation of relief loads. In this study, the new design procedure for a flare system based on dynamic simulation was proposed in order to avoid the overestimation of relief loads. The relief load of a deethanizer process was tested to verify the performance of the proposed design procedure.
Dynamic supplier selection problem considering full truck load in probabilistic environment
Sutrisno, Wicaksono, Purnawan Adi
2017-11-01
In this paper, we propose a mathematical model in a probabilistic dynamic optimization to solve a dynamic supplier selection problem considering full truck load in probabilistic environment where some parameters are uncertain. We determine the optimal strategy for this problem by using stochastic dynamic programming. We give some numerical experiments to evaluate and analyze the model. From the results, the optimal supplier and the optimal product volume from the optimal supplier were determined for each time period.
Employing Deceptive Dynamic Network Topology Through Software-Defined Networking
2014-03-01
actions. From [64] . . . . . 37 xi THIS PAGE INTENTIONALLY LEFT BLANK xii List of Acronyms and Abbreviations ACL Access Control List API Application...can be extremely useful in topology mapping through various latency-based geolocation methods [35], [36], [37]. PING 1 7 2 . 2 0 . 5 . 2 ( 1 7 2 . 2 0...defined northbound Applica- tion Programming Interfaces ( APIs ). Figure 3.1: Software-Defined Network Architecture. From [8] 29 3.3 SDN OpenFlow
Recruitment dynamics in adaptive social networks
International Nuclear Information System (INIS)
Shkarayev, Maxim S; Shaw, Leah B; Schwartz, Ira B
2013-01-01
We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime). (paper)
Recruitment dynamics in adaptive social networks
Shkarayev, Maxim S.; Schwartz, Ira B.; Shaw, Leah B.
2013-06-01
We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime).
Dynamic artificial neural networks with affective systems.
Directory of Open Access Journals (Sweden)
Catherine D Schuman
Full Text Available Artificial neural networks (ANNs are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP and long term depression (LTD, and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.
Response of Buried Vertically Oriented Cylinders to Dynamic Loading,
1980-06-01
BALSARA • , . / ,, _,-, -. 1i S ,LESPONSE OF BURIED VERTICALLY 9RIENTED CYLINDERS .-TO DINAMIC LOADING_ 9AYLE E. LRTOrwW&-N JIIMY P./BALSARA Nk...1.7, 2,8, and 4.0 inches). The end caps for the cylinders consisted of a steel shell filled with high- strength concrete; however, the end caps were...not designed to be test articles. The average concrete compressive strength of the cylinders on test day was 44.0 MPa (6,380 psi). The three DEOT
Cortical electrophysiological network dynamics of feedback learning
Cohen, M.X.; Wilmes, K.A.; van de Vijver, I.
2011-01-01
Understanding the neurophysiological mechanisms of learning is important for both fundamental and clinical neuroscience. We present a neurophysiologically inspired framework for understanding cortical mechanisms of feedback-guided learning. This framework is based on dynamic changes in systems-level
The topology and dynamics of complex networks
Dezso, Zoltan
We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.
Reliability-based Dynamic Network Design with Stochastic Networks
Li, H.
2009-01-01
Transportation systems are stochastic and dynamic systems. The road capacities and the travel demand are fluctuating from time to time within a day and at the same time from day to day. For road users, the travel time and travel costs experienced over time and space are stochastic, thus desire
Predictive coding of dynamical variables in balanced spiking networks.
Boerlin, Martin; Machens, Christian K; Denève, Sophie
2013-01-01
Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.
Stiffness compatibility of coralline hydroxyapatite bone substitute under dynamic loading
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
When hydroxyapatite bone substitutes are implanted in human bodies,bone tissues will grow into their porous structure,which will reinforce their strength and stiffness.The concept of mechanical com-patibility of bone substitutes implies that their mechanical properties are similar to the bone tissues around,as if they were part of the bone.The mechanical compatibility of bone substitutes includes both static and dynamic behavior,due to the mechanical properties of bone depending on the strain rate.In this study,split Hopkinson pressure bar technique(SHPB) was employed to determine the dy-namic mechanical properties of coralline hydroxyapatite,bones with and bones without organic com-ponents,and their dynamic stress-strain curves of the three materials were obtained.The mechanical effects of collagens in bone were assessed,by comparing the difference between the Young’s moduli of the three materials.As the implanted bone substitute becomes a part of bone,it can be regarded as an inclusion composite.The effective modulus of the composite was also evaluated in order to estimate its mechanical compatibility on stiffness.The evaluated result shows that the suitable porosity of HA is 0.8,which is in favor of both static and dynamic stiffness compatibility.
Stiffness compatibility of coralline hydroxyapatite bone substitute under dynamic loading
Institute of Scientific and Technical Information of China (English)
REN ChaoFeng; HOU ZhenDe; ZHAO Wei
2009-01-01
When hydroxyapatite bone substitutes are implanted in human bodies, bone tissues will grow into their porous structure, which will reinforce their strength and stiffness. The concept of mechanical com-patibility of bone substitutes implies that their mechanical properties are similar to the bone tissues around, as if they were part of the bone. The mechanical compatibility of bone substitutes includes both static and dynamic behavior, due to the mechanical properties of bone depending on the strain rate. In this study, split Hopkinson pressure bar technique (SHPB) was employed to determine the dy-namic mechanical properties of coralline hydroxyapatite, bones with and bones without organic com-ponents, and their dynamic stress-strain curves of the three materials were obtained. The mechanical effects of collagens in bone were assessed, by comparing the difference between the Young's moduli of the three materials. As the implanted bone substitute becomes a part of bone, it can be regarded as an inclusion composite. The effective modulus of the composite was also evaluated in order to estimate its mechanical compatibility on stiffness. The evaluated result shows that the suitable porosity of HA is0.8, which is in favor of both static and dynamic stiffness compatibility.
Wideband impedance measurements of DC motors under dynamic load conditions
Diouf, F.; Buesink, Frederik Johannes Karel; Leferink, Frank Bernardus Johannes; Duval, Fabrice; Bensetti, Mohamed
2013-01-01
One of the principal conducted EMI(electromagnetic interferences) sources of low voltage DC (direct current) motors is the commutation occurring during rotation. In this paper the small-signal impedance of low voltage DC motors under different functioning modes, including the dynamic one is studied
Application of the load flow and random flow models for the analysis of power transmission networks
International Nuclear Information System (INIS)
Zio, Enrico; Piccinelli, Roberta; Delfanti, Maurizio; Olivieri, Valeria; Pozzi, Mauro
2012-01-01
In this paper, the classical load flow model and the random flow model are considered for analyzing the performance of power transmission networks. The analysis concerns both the system performance and the importance of the different system elements; this latter is computed by power flow and random walk betweenness centrality measures. A network system from the literature is analyzed, representing a simple electrical power transmission network. The results obtained highlight the differences between the LF “global approach” to flow dispatch and the RF local approach of randomized node-to-node load transfer. Furthermore, computationally the LF model is less consuming than the RF model but problems of convergence may arise in the LF calculation.
Salience network dynamics underlying successful resistance of temptation
Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q
2017-01-01
Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582
Dynamic hydro-climatic networks in pristine and regulated rivers
Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.
2014-12-01
Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes
Dynamics of Number of Packets in Transit in Free Flow State of Data Network
International Nuclear Information System (INIS)
Shengkun Xie; Lawniczak, A.T.
2011-01-01
We study how the dynamics of Number of Packets in Transit (NPT) is affected by the coupling of a routing type with a volume of incoming packet traffic in a data network model of packet switching type. The NPT is a network performance indicator of an aggregate type that measures in '' real time '', how many packets are in the network on their routes to their destinations. We conduct our investigation using a time-discrete simulation model that is an abstraction of the Network Layer of the ISO OSI Seven Layer Reference Model. This model focuses on packets and their routing. We consider a static routing and two different types of dynamic routings coupled with different volumes of incoming packet traffic in the network free flow state. Our study shows that the order of the values of the NPT mean value time series depends on the coupling of a routing type with a volume of incoming packet traffic and changes when the volume of incoming packet traffic increases and is closed to the critical source load values, i.e. when it is closed to the phase transition points from the network free flow state to its congested states. (authors)
Dynamic behavior of reinforced concrete beam subjected to impact load
International Nuclear Information System (INIS)
Ito, Chihiro; Ohnuma, Hiroshi; Sato, Koichi; Takano, Hiroshi
1984-01-01
The purpose of this report is to find out the impact behavior of reinforced concrete beams by means of experiment. The reinforced concrete is widely used for such an important structure as the building facilities of the nuclear power plant, and so the impact behavior of the reinforced concrete structures must be examined to estimate the resistance of concrete containment against impact load and to develope the reasonable and reliable design procedure. The impact test on reinforced concrete beam which is one of the most basic elements in the structure was conducted. Main results are summarized as follows. 1) Bending failure occured on static test. On the other hand, shear failure occured in the case of high impact velocity on impact test. 2) Penetration depth and residual deflection are approximately proportional to V 2 (V: velocity at impact). 3) Flexural wave propagates about at the speed of 2000 m/s. 4) The resistance of reinforced concrete beam against the impact load is fairly good. (author)
Mechanical Model for Dynamic Behavior of Concrete Under Impact Loading
Sun, Yuanxiang
Concrete is a geo-material which is used substantively in the civil building and military safeguard. One coupled model of damage and plasticity to describe the complex behavior of concrete subjected to impact loading is proposed in this research work. The concrete is assumed as homogeneous continuum with pre-existing micro-cracks and micro-voids. Damage to concrete is caused due to micro-crack nucleation, growth and coalescence, and defined as the probability of fracture at a given crack density. It induces a decrease of strength and stiffness of concrete. Compaction of concrete is physically a collapse of the material voids. It produces the plastic strain in the concrete and, at the same time, an increase of the bulk modulus. In terms of crack growth model, micro-cracks are activated, and begin to propagate gradually. When crack density reaches a critical value, concrete takes place the smashing destroy. The model parameters for mortar are determined using plate impact experiment with uni-axial strain state. Comparison with the test results shows that the proposed model can give consistent prediction of the impact behavior of concrete. The proposed model may be used to design and analysis of concrete structures under impact and shock loading. This work is supported by State Key Laboratory of Explosion science and Technology, Beijing Institute of Technology (YBKT14-02).
Cell fate reprogramming by control of intracellular network dynamics
Zanudo, Jorge G. T.; Albert, Reka
Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.
Impact of constrained rewiring on network structure and node dynamics
Rattana, P.; Berthouze, L.; Kiss, I. Z.
2014-11-01
In this paper, we study an adaptive spatial network. We consider a susceptible-infected-susceptible (SIS) epidemic on the network, with a link or contact rewiring process constrained by spatial proximity. In particular, we assume that susceptible nodes break links with infected nodes independently of distance and reconnect at random to susceptible nodes available within a given radius. By systematically manipulating this radius we investigate the impact of rewiring on the structure of the network and characteristics of the epidemic. We adopt a step-by-step approach whereby we first study the impact of rewiring on the network structure in the absence of an epidemic, then with nodes assigned a disease status but without disease dynamics, and finally running network and epidemic dynamics simultaneously. In the case of no labeling and no epidemic dynamics, we provide both analytic and semianalytic formulas for the value of clustering achieved in the network. Our results also show that the rewiring radius and the network's initial structure have a pronounced effect on the endemic equilibrium, with increasingly large rewiring radiuses yielding smaller disease prevalence.
Directory of Open Access Journals (Sweden)
D. K. Sengupta
2013-01-01
Full Text Available Alternatives to conventional rigid fusion have been proposed for several conditions related to degenerative disc disease when nonoperative treatment has failed. Semirigid fixation, in the form of dynamic stabilization or PEEK rods, is expected to provide compression under loading as well as an intermediate level of stabilization. This study systematically examines both the load-sharing characteristics and kinematics of these two devices compared to the standard of internal rigid fixators. Load-sharing was studied by using digital pressure films inserted between an artificially machined disc and two loading fixtures. Rigid rods, PEEK rods, and the dynamic stabilization system were inserted posteriorly for stabilization. The kinematics were quantified on ten, human, cadaver lumbosacral spines (L3-S1 which were tested under a pure bending moment, in flexion-extension, lateral bending, and axial rotation. The magnitude of load transmission through the anterior column was significantly greater with the dynamic device compared to PEEK rods and rigid rods. The contact pressures were distributed more uniformly, throughout the disc with the dynamic stabilization devices, and had smaller maximum point-loading (pressures on any particular point within the disc. Kinematically, the motion was reduced by both semirigid devices similarly in all directions, with slight rigidity imparted by a lateral interbody device.
A simplified model of dynamic interior cooling load evaluation for office buildings
International Nuclear Information System (INIS)
Ding, Yan; Zhang, Qiang; Wang, Zhaoxia; Liu, Min; He, Qing
2016-01-01
Highlights: • The core interior disturbance was determined by principle component analysis. • Influences of occupants on cooling load should be described using time series. • A simplified model was built to evaluate dynamic interior building cooling load. - Abstract: Predicted cooling load is a valuable tool for assessing the operation of air-conditioning systems. Compared with exterior cooling load, interior cooling load is more unpredictable. According to principle components analysis, occupancy was proved to be a typical factor influencing interior cooling loads in buildings. By exploring the regularity of interior disturbances in an office building, a simplified evaluation model for interior cooling load was established in this paper. The stochastic occupancy rate was represented by a Markov transition model. Equipment power, lighting power and fresh air were all related to occupancy rate based on time sequence. The superposition of different types of interior cooling loads was also considered in the evaluation model. The error between the evaluation results and measurement results was found to be lower than 10%. In reference to the cooling loads calculated by the traditional design method and area-based method in case study office rooms, the evaluated cooling loads were suitable for operation regulation.
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...
Dynamic Optical Networks for Future Internet Environments
Matera, Francesco
2014-05-01
This article reports an overview on the evolution of the optical network scenario taking into account the exponential growth of connected devices, big data, and cloud computing that is driving a concrete transformation impacting the information and communication technology world. This hyper-connected scenario is deeply affecting relationships between individuals, enterprises, citizens, and public administrations, fostering innovative use cases in practically any environment and market, and introducing new opportunities and new challenges. The successful realization of this hyper-connected scenario depends on different elements of the ecosystem. In particular, it builds on connectivity and functionalities allowed by converged next-generation networks and their capacity to support and integrate with the Internet of Things, machine-to-machine, and cloud computing. This article aims at providing some hints of this scenario to contribute to analyze impacts on optical system and network issues and requirements. In particular, the role of the software-defined network is investigated by taking into account all scenarios regarding data centers, cloud computing, and machine-to-machine and trying to illustrate all the advantages that could be introduced by advanced optical communications.
Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke
2017-05-01
Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
DEFF Research Database (Denmark)
Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani
2014-01-01
This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...
International Nuclear Information System (INIS)
Ahmadigorji, Masoud; Amjady, Nima
2014-01-01
Highlights: • A new dynamic distribution network expansion planning model is presented. • A Binary Enhanced Particle Swarm Optimization (BEPSO) algorithm is proposed. • A Modified Differential Evolution (MDE) algorithm is proposed. • A new bi-level optimization approach composed of BEPSO and MDE is presented. • The effectiveness of the proposed optimization approach is extensively illustrated. - Abstract: Reconstruction in the power system and appearing of new technologies for generation capacity of electrical energy has led to significant innovation in Distribution Network Expansion Planning (DNEP). Distributed Generation (DG) includes the application of small/medium generation units located in power distribution networks and/or near the load centers. Appropriate utilization of DG can affect the various technical and operational indices of the distribution network such as the feeder loading, energy losses and voltage profile. In addition, application of DG in proper size is an essential tool to achieve the DG maximum potential benefits. In this paper, a time-based (dynamic) model for DNEP is proposed to determine the optimal size, location and installation year of DG in distribution system. Also, in this model, the Optimal Power Flow (OPF) is exerted to determine the optimal generation of DGs for every potential solution in order to minimize the investment and operation costs following the load growth in a specified planning period. Besides, the reinforcement requirements of existing distribution feeders are considered, simultaneously. The proposed optimization problem is solved by the combination of evolutionary methods of a new Binary Enhanced Particle Swarm Optimization (BEPSO) and Modified Differential Evolution (MDE) to find the optimal expansion strategy and solve OPF, respectively. The proposed planning approach is applied to two typical primary distribution networks and compared with several other methods. These comparisons illustrate the
Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen
2018-09-01
We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.