WorldWideScience

Sample records for varying network conditions

  1. Globally exponential stability condition of a class of neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Liao, T.-L.; Yan, J.-J.; Cheng, C.-J.; Hwang, C.-C.

    2005-01-01

    In this Letter, the globally exponential stability for a class of neural networks including Hopfield neural networks and cellular neural networks with time-varying delays is investigated. Based on the Lyapunov stability method, a novel and less conservative exponential stability condition is derived. The condition is delay-dependent and easily applied only by checking the Hamiltonian matrix with no eigenvalues on the imaginary axis instead of directly solving an algebraic Riccati equation. Furthermore, the exponential stability degree is more easily assigned than those reported in the literature. Some examples are given to demonstrate validity and excellence of the presented stability condition herein

  2. Emergence of epidemics in rapidly varying networks

    International Nuclear Information System (INIS)

    Kohar, Vivek; Sinha, Sudeshna

    2013-01-01

    We describe a simple model mimicking disease spreading on a network with dynamically varying connections, and investigate the dynamical consequences of switching links in the network. Our central observation is that the disease cycles get more synchronized, indicating the onset of epidemics, as the underlying network changes more rapidly. This behavior is found for periodically switched links, as well as links that switch randomly in time. We find that the influence of changing links is more pronounced in networks where the nodes have lower degree, and the disease cycle has a longer infective stage. Further, when the switching of links is periodic we observe finer dynamical features, such as beating patterns in the emergent oscillations and resonant enhancement of synchronization, arising from the interplay between the time-scales of the connectivity changes and that of the epidemic outbreaks

  3. Learning conditional Gaussian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

  4. Panorama 2011: Refining: varying conditions by region

    International Nuclear Information System (INIS)

    Silva, C.

    2011-01-01

    The economic crisis has further weakened a sector that was already facing difficulties, if we look beyond the flush period (2005-2008) when, buoyed by strong demand, margins remained high and refiners could generate profits while maintaining a healthy level of activity. Falling demand and increased over-capacity in some regions - the immediate consequences of the deteriorating economic conditions over the past two years - have led to declining margins and to financial accounts being in the red. The adoption of increasingly stringent emissions standards and product specifications, burdensome regulatory requirements for refineries (for combating local pollution and reducing greenhouse gas emissions), stiffer competition from new fuels: all of these structural factors are weakening the sector, especially in industrialized nations with their more rigorous regulatory compliance. In this generally gloomy climate, numerous new projects are still being envisaged - although many have recently been postponed and tend to be concentrated in developing countries. (author)

  5. Network Coded Cooperation Over Time-Varying Channels

    DEFF Research Database (Denmark)

    Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João

    2014-01-01

    transmissions, e.g., in terms of the rate of packet transmission or the energy consumption. A comprehensive analysis of the MDP solution is carried out under different network conditions to extract optimal rules of packet transmission. Inspired by the extracted rules, we propose two near-optimal heuristics......In this paper, we investigate the optimal design of cooperative network-coded strategies for a three-node wireless network with time-varying, half-duplex erasure channels. To this end, we formulate the problem of minimizing the total cost of transmitting M packets from source to two receivers...... as a Markov Decision Process (MDP). The actions of the MDP model include the source and the type of transmission to be used in a given time slot given perfect knowledge of the system state. The cost of packet transmission is defined such that it can incorporate the difference between broadcast and unicast...

  6. Time-varying multiplex network: Intralayer and interlayer synchronization

    Science.gov (United States)

    Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar

    2017-12-01

    A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.

  7. Scaling properties in time-varying networks with memory

    Science.gov (United States)

    Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

    2015-12-01

    The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

  8. Entropy Rate of Time-Varying Wireless Networks

    DEFF Research Database (Denmark)

    Cika, Arta; Badiu, Mihai Alin; Coon, Justin P.

    2018-01-01

    In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with random node positions in a closed space and Rayleigh...... fading affecting the connections between nodes. The existence of an edge between two nodes at given locations is modeled by a Markov chain, enabling memory effects in network dynamics. We then derive a lower and an upper bound on the entropy rate of the spatiotemporal network. The entropy rate measures...

  9. Inferring time-varying network topologies from gene expression data.

    Science.gov (United States)

    Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

    2007-01-01

    Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

  10. Epidemic spreading in time-varying community networks.

    Science.gov (United States)

    Ren, Guangming; Wang, Xingyuan

    2014-06-01

    The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q epidemic spreading in complex networks with community structure.

  11. Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

    International Nuclear Information System (INIS)

    Wan Li; Zhou Qinghua

    2007-01-01

    The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established

  12. Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

    Science.gov (United States)

    Wan, Li; Zhou, Qinghua

    2007-11-01

    The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.

  13. Novel criteria for exponential synchronization of inner time-varying complex networks with coupling delay

    International Nuclear Information System (INIS)

    Zhang Qun-Jiao; Zhao Jun-Chan

    2012-01-01

    This paper mainly investigates the exponential synchronization of an inner time-varying complex network with coupling delay. Firstly, the synchronization of complex networks is decoupled into the stability of the corresponding dynamical systems. Based on the Lyapunov function theory, some sufficient conditions to guarantee its stability with any given convergence rate are derived, thus the synchronization of the networks is achieved. Finally, the results are illustrated by a simple time-varying network model with a coupling delay. All involved numerical simulations verify the correctness of the theoretical analysis. (general)

  14. Contact Dynamics of EHL Contacts under Time Varying Conditions

    NARCIS (Netherlands)

    Venner, Cornelis H.; Popovici, G.; Wijnant, Ysbrand H.; Dalmaz, G.; Lubrecht, A.A.; Priest, M

    2004-01-01

    By means of numerical simulations of two situations with time varying operating conditions it is shown that the dynamic behaviour of Elasto-Hydrodynamically Lubricated contacts in terms of vibrations can be characterized as: Changes in the mutual approach lead to film thickness changes in the inlet

  15. Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Syed Ali, M.; Balasubramaniam, P.

    2009-01-01

    In this paper, the Takagi-Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.

  16. Renormalization group theory for percolation in time-varying networks.

    Science.gov (United States)

    Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M

    2018-05-22

    Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.

  17. Stochastic analysis of epidemics on adaptive time varying networks

    Science.gov (United States)

    Kotnis, Bhushan; Kuri, Joy

    2013-06-01

    Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

  18. Vibration condition monitoring of planetary gearbox under varying external load

    Energy Technology Data Exchange (ETDEWEB)

    Bartelmus, W.; Zimroz, R. [Wroclaw University of Technology, Wroclaw (Poland)

    2009-01-15

    The paper shows that for condition monitoring of planetary gearboxes it is important to identify the external varying load condition. In the paper, systematic consideration has been taken of the influence of many factors on the vibration signals generated by a system in which a planetary gearbox is included. These considerations give the basis for vibration signal interpretation, development of the means of condition monitoring, and for the scenario of the degradation of the planetary gearbox. Real measured vibration signals obtained in the industrial environment are processed. The signals are recorded during normal operation of the diagnosed objects, namely planetary gearboxes, which are a part of the driving system used in a bucket wheel excavator, used in lignite mines. It has been found that the most important factor of the proper planetary gearbox condition is connected with perturbation of arm rotation, where an arm rotation gives rise to a specific vibration signal whose properties are depicted by a short-time Fourier transform (STFT) and Wigner-Ville distribution presented as a time-frequency map. The paper gives evidence that there are two dominant low-frequency causes that influence vibration signal modulation, i.e. the varying load, which comes from the nature of the bucket wheel digging process, and the arm/carrier rotation. These two causes determine the condition of the planetary gearboxes considered.

  19. Delay-dependent exponential stability of cellular neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2005-01-01

    The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results

  20. Model Complexities of Shallow Networks Representing Highly Varying Functions

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2016-01-01

    Roč. 171, 1 January (2016), s. 598-604 ISSN 0925-2312 R&D Projects: GA MŠk(CZ) LD13002 Grant - others:grant for Visiting Professors(IT) GNAMPA-INdAM Institutional support: RVO:67985807 Keywords : shallow networks * model complexity * highly varying functions * Chernoff bound * perceptrons * Gaussian kernel units Subject RIV: IN - Informatics, Computer Science Impact factor: 3.317, year: 2016

  1. Modeling information diffusion in time-varying community networks

    Science.gov (United States)

    Cui, Xuelian; Zhao, Narisa

    2017-12-01

    Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.

  2. Conditional CAPM: Time-varying Betas in the Brazilian Market

    Directory of Open Access Journals (Sweden)

    Frances Fischberg Blank

    2014-10-01

    Full Text Available The conditional CAPM is characterized by time-varying market beta. Based on state-space models approach, beta behavior can be modeled as a stochastic process dependent on conditioning variables related to business cycle and estimated using Kalman filter. This paper studies alternative models for portfolios sorted by size and book-to-market ratio in the Brazilian stock market and compares their adjustment to data. Asset pricing tests based on time-series and cross-sectional approaches are also implemented. A random walk process combined with conditioning variables is the preferred model, reducing pricing errors compared to unconditional CAPM, but the errors are still significant. Cross-sectional test show that book-to-market ratio becomes less relevant, but past returns still capture cross-section variation

  3. Epidemic spreading in time-varying community networks

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)

    2014-06-15

    The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.

  4. Epidemic spreading in time-varying community networks

    International Nuclear Information System (INIS)

    Ren, Guangming; Wang, Xingyuan

    2014-01-01

    The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q c . The epidemic will survive when q > q c and die when q  c . These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure

  5. Atmospheric particle formation in spatially and temporally varying conditions

    Energy Technology Data Exchange (ETDEWEB)

    Lauros, J.

    2011-07-01

    Atmospheric particles affect the radiation balance of the Earth and thus the climate. New particle formation from nucleation has been observed in diverse atmospheric conditions but the actual formation path is still unknown. The prevailing conditions can be exploited to evaluate proposed formation mechanisms. This study aims to improve our understanding of new particle formation from the view of atmospheric conditions. The role of atmospheric conditions on particle formation was studied by atmospheric measurements, theoretical model simulations and simulations based on observations. Two separate column models were further developed for aerosol and chemical simulations. Model simulations allowed us to expand the study from local conditions to varying conditions in the atmospheric boundary layer, while the long-term measurements described especially characteristic mean conditions associated with new particle formation. The observations show statistically significant difference in meteorological and back-ground aerosol conditions between observed event and non-event days. New particle formation above boreal forest is associated with strong convective activity, low humidity and low condensation sink. The probability of a particle formation event is predicted by an equation formulated for upper boundary layer conditions. The model simulations call into question if kinetic sulphuric acid induced nucleation is the primary particle formation mechanism in the presence of organic vapours. Simultaneously the simulations show that ignoring spatial and temporal variation in new particle formation studies may lead to faulty conclusions. On the other hand, the theoretical simulations indicate that short-scale variations in temperature and humidity unlikely have a significant effect on mean binary water sulphuric acid nucleation rate. The study emphasizes the significance of mixing and fluxes in particle formation studies, especially in the atmospheric boundary layer. The further

  6. One-dimensional radionuclide transport under time-varying conditions

    International Nuclear Information System (INIS)

    Gelbard, F.; Olague, N.E.; Longsine, D.E.

    1990-01-01

    This paper discusses new analytical and numerical solutions presented for one-dimensional radionuclide transport under time-varying fluid-flow conditions including radioactive decay. The analytical solution assumes that all radionuclides have identical retardation factors, and is limited to instantaneous releases. The numerical solution does not have these limitations, but is tested against the limiting case given for the analytical solution. Reasonable agreement between the two solutions was found. Examples are given for the transport of a three-member radionuclide chain transported over distances and flow rates comparable to those reported for Yucca Mountain, the proposed disposal site for high-level nuclear waste

  7. Modelling and Control of Ionic Electroactive Polymer Actuators under Varying Humidity Conditions

    Directory of Open Access Journals (Sweden)

    S. Sunjai Nakshatharan

    2018-02-01

    Full Text Available In this work, we address the problem of position control of ionic electroactive polymer soft actuators under varying relative humidity conditions. The impact of humidity on the actuation performance of ionic actuators is studied through frequency response and impedance spectroscopy analysis. Considering the uncertain performance of the actuator under varying humidity conditions, an adaptable model using the neural network method is developed. The model uses relative humidity magnitude as one of the model parameters, making it robust to different environmental conditions. Utilizing the model, a closed-loop controller based on the model predictive controller is developed for position control of the actuator. The developed model and controller are experimentally verified and found to be capable of predicting and controlling the actuators with excellent tracking accuracy under relative humidity conditions varying in the range of 10–90%.

  8. On global exponential stability of high-order neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Zhang Baoyong; Xu Shengyuan; Li Yongmin; Chu Yuming

    2007-01-01

    This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria

  9. On global exponential stability of high-order neural networks with time-varying delays

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Baoyong [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: baoyongzhang@yahoo.com.cn; Xu Shengyuan [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: syxu02@yahoo.com.cn; Li Yongmin [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China) and Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)]. E-mail: ymlwww@163.com; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)

    2007-06-18

    This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria.

  10. Global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Liang Jinling; Cao Jinde

    2003-01-01

    Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result

  11. Global exponential stability for reaction-diffusion recurrent neural networks with multiple time varying delays

    International Nuclear Information System (INIS)

    Lou, X.; Cui, B.

    2008-01-01

    In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)

  12. A thermal model for photovoltaic panels under varying atmospheric conditions

    International Nuclear Information System (INIS)

    Armstrong, S.; Hurley, W.G.

    2010-01-01

    The response of the photovoltaic (PV) panel temperature is dynamic with respect to the changes in the incoming solar radiation. During periods of rapidly changing conditions, a steady state model of the operating temperature cannot be justified because the response time of the PV panel temperature becomes significant due to its large thermal mass. Therefore, it is of interest to determine the thermal response time of the PV panel. Previous attempts to determine the thermal response time have used indoor measurements, controlling the wind flow over the surface of the panel with fans or conducting the experiments in darkness to avoid radiative heat loss effects. In real operating conditions, the effective PV panel temperature is subjected to randomly varying ambient temperature and fluctuating wind speeds and directions; parameters that are not replicated in controlled, indoor experiments. A new thermal model is proposed that incorporates atmospheric conditions; effects of PV panel material composition and mounting structure. Experimental results are presented which verify the thermal behaviour of a photovoltaic panel for low to strong winds.

  13. Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

    Science.gov (United States)

    Syed Ali, M.; Balasubramaniam, P.

    2008-07-01

    In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.

  14. Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Syed Ali, M.; Balasubramaniam, P.

    2008-01-01

    In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB

  15. Bioventing of gasoline-contaminated soil under varied laboratory conditions

    International Nuclear Information System (INIS)

    Hallman, M.; Shewfelt, K.; Lee, H.; Zytner, R.G.

    2002-01-01

    Bioventing is becoming a popular in situ soil remediation technology for the treatment of hydrocarbon-contaminated soil. Bioventing relies on enhancing the growth of indigenous microorganisms, which can mineralize the contaminant in the presence of sufficient nutrients. Although bioventing is currently being used as a remediation technology, there are some important questions that remain to be answered in order to optimize the process. These questions include the optimum soil moisture content, type and amount of nutrients necessary, and the best means of producing these conditions in the field. To address these questions, two distinct phases of experiments were conducted. The first experimental phase was designed to determine the optimum moisture content, C:N ratio and form of nitrogen supply for this soil. Using approximately 200g of contaminated soil in each of a series of sealed respirometers, microbial degradation of gasoline under bioventing conditions was quantified for C:N ratios of 5, 10 and 20:1, using varying mixtures of NH 4 + - and NO 3 - -N. The results of the studies indicated that the optimum soil moisture content was 15 wt%, with a C:N ratio of 10:1, using a 100% ammonium application. Using the results of the first phase, a second phase of laboratory research was initiated. Five mesoscale reactors have been developed to simulate the bioventing process that takes place in the field. These reactors are filled with approximately 4kg of gasoline-contaminated soil. The initial results are favourable. (author)

  16. Temporal-varying failures of nodes in networks

    Science.gov (United States)

    Knight, Georgie; Cristadoro, Giampaolo; Altmann, Eduardo G.

    2015-08-01

    We consider networks in which random walkers are removed because of the failure of specific nodes. We interpret the rate of loss as a measure of the importance of nodes, a notion we denote as failure centrality. We show that the degree of the node is not sufficient to determine this measure and that, in a first approximation, the shortest loops through the node have to be taken into account. We propose approximations of the failure centrality which are valid for temporal-varying failures, and we dwell on the possibility of externally changing the relative importance of nodes in a given network by exploiting the interference between the loops of a node and the cycles of the temporal pattern of failures. In the limit of long failure cycles we show analytically that the escape in a node is larger than the one estimated from a stochastic failure with the same failure probability. We test our general formalism in two real-world networks (air-transportation and e-mail users) and show how communities lead to deviations from predictions for failures in hubs.

  17. Innovation diffusion on time-varying activity driven networks

    Science.gov (United States)

    Rizzo, Alessandro; Porfiri, Maurizio

    2016-01-01

    Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

  18. Robust stability analysis of switched Hopfield neural networks with time-varying delay under uncertainty

    International Nuclear Information System (INIS)

    Huang He; Qu Yuzhong; Li Hanxiong

    2005-01-01

    With the development of intelligent control, switched systems have been widely studied. Here we try to introduce some ideas of the switched systems into the field of neural networks. In this Letter, a class of switched Hopfield neural networks with time-varying delay is investigated. The parametric uncertainty is considered and assumed to be norm bounded. Firstly, the mathematical model of the switched Hopfield neural networks is established in which a set of Hopfield neural networks are used as the individual subsystems and an arbitrary switching rule is assumed; Secondly, robust stability analysis for such switched Hopfield neural networks is addressed based on the Lyapunov-Krasovskii approach. Some criteria are given to guarantee the switched Hopfield neural networks to be globally exponentially stable for all admissible parametric uncertainties. These conditions are expressed in terms of some strict linear matrix inequalities (LMIs). Finally, a numerical example is provided to illustrate our results

  19. Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller.

    Science.gov (United States)

    Gong, Shuqing; Yang, Shaofu; Guo, Zhenyuan; Huang, Tingwen

    2018-06-01

    The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. Exponential stability of fuzzy cellular neural networks with constant and time-varying delays

    International Nuclear Information System (INIS)

    Liu Yanqing; Tang Wansheng

    2004-01-01

    In this Letter, the global stability of delayed fuzzy cellular neural networks (FCNN) with either constant delays or time varying delays is proposed. Firstly, we give the existence and uniqueness of the equilibrium point by using the theory of topological degree and the properties of nonsingular M-matrix and the sufficient conditions for ascertaining the global exponential stability by constructing a suitable Lyapunov functional. Secondly, the criteria for guaranteeing the global exponential stability of FCNN with time varying delays are given and the estimation of exponential convergence rate with regard to speed of vary of delays is presented by constructing a suitable Lyapunov functional

  1. Global exponential stability of fuzzy BAM neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Zhang Qianhong; Luo Wei

    2009-01-01

    In this paper, a class of fuzzy bidirectional associated memory (BAM) neural networks with time-varying delays are studied. Employing fixed point theorem, matrix theory and inequality analysis, some sufficient conditions are established for the existence, uniqueness and global exponential stability of equilibrium point. The sufficient conditions are easy to verify at pattern recognition and automatic control. Finally, an example is given to show feasibility and effectiveness of our results.

  2. Estimation of thermal sensation during varied air temperature conditions.

    Science.gov (United States)

    Katsuura, T; Tabuchi, R; Iwanaga, K; Harada, H; Kikuchi, Y

    1998-03-01

    Seven male students were exposed to four varied air temperature environments: hot (37 degrees C) to neutral (27 degrees C) (HN), neutral to hot (NH), cool (17 degrees C) to neutral (CN), and neutral to cool (NC). The air temperature was maintained at the first condition for 20 min, then was changed to the second condition after 15 min and was held there for 20 min. Each subject wore a T-shirt, briefs, trunks, and socks. Each sat on a chair and was continuously evaluated for thermal sensation, thermal comfort, and air velocity sensation. Some physiological and thermal parameters were also measured every 5 s during the experiment. The correlation between thermal sensation and skin temperature at 15 sites was found to be poor. The subjects felt much warmer during the rising phase of the air temperature (CN, NH) than during the descending phase (HN, NC) at a given mean skin temperature. However, thermal sensation at the same heat flux or at the same value of the difference between skin and air temperature (delta(Tsk - Ta)) was not so different among the four experimental conditions, and the correlation between thermal sensation and heat flux or delta(Tsk - Ta) was fairly good. The multiple regression equation of the thermal sensation (TS) on 15 sites of skin temperature (Tsk; degrees C) was calculated and the coefficient of determination (R*2) was found to be 0.656. Higher coefficients of determination were found in the equations of thermal sensation for the heat flux (H; kcal.m-2.h-1) at the right and left thighs of the subjects and on delta(Tsk - Ta) (degrees C) at 4 sites. They were as follows: TS = 2.04 - 0.016 Hright - 0.036 Hleft; R*2 = 0.717, TS = 1.649 + 0.013 delta(Tsk - Ta)UpperArm - 0.036 delta(Tsk - Ta)Chest - 0.223 delta(Tsk - Ta)Thigh-0.083 delta(Tsk - Ta)LowerLeg; R*2 = 0.752, respectively.

  3. Lyapunov Functions to Caputo Fractional Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Ravi Agarwal

    2018-05-01

    Full Text Available One of the main properties of solutions of nonlinear Caputo fractional neural networks is stability and often the direct Lyapunov method is used to study stability properties (usually these Lyapunov functions do not depend on the time variable. In connection with the Lyapunov fractional method we present a brief overview of the most popular fractional order derivatives of Lyapunov functions among Caputo fractional delay differential equations. These derivatives are applied to various types of neural networks with variable coefficients and time-varying delays. We show that quadratic Lyapunov functions and their Caputo fractional derivatives are not applicable in some cases when one studies stability properties. Some sufficient conditions for stability of equilibrium of nonlinear Caputo fractional neural networks with time dependent transmission delays, time varying self-regulating parameters of all units and time varying functions of the connection between two neurons in the network are obtained. The cases of time varying Lipschitz coefficients as well as nonLipschitz activation functions are studied. We illustrate our theory on particular nonlinear Caputo fractional neural networks.

  4. Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays.

    Science.gov (United States)

    Wan, Peng; Jian, Jigui

    2018-03-01

    This paper focuses on delay-dependent passivity analysis for a class of memristive impulsive inertial neural networks with time-varying delays. By choosing proper variable transformation, the memristive inertial neural networks can be rewritten as first-order differential equations. The memristive model presented here is regarded as a switching system rather than employing the theory of differential inclusion and set-value map. Based on matrix inequality and Lyapunov-Krasovskii functional method, several delay-dependent passivity conditions are obtained to ascertain the passivity of the addressed networks. In addition, the results obtained here contain those on the passivity for the addressed networks without impulse effects as special cases and can also be generalized to other neural networks with more complex pulse interference. Finally, one numerical example is presented to show the validity of the obtained results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Lan Liu

    2017-01-01

    Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when qnetwork malware and provide a theoretical basis to reduce and prevent network security incidents.

  6. Finite-time stability of neutral-type neural networks with random time-varying delays

    Science.gov (United States)

    Ali, M. Syed; Saravanan, S.; Zhu, Quanxin

    2017-11-01

    This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov-Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.

  7. Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay

    International Nuclear Information System (INIS)

    Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia

    2009-01-01

    This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.

  8. Thermal shock behaviour of different tungsten grades under varying conditions

    Energy Technology Data Exchange (ETDEWEB)

    Wirtz, Oliver Marius

    2012-07-19

    Thermonuclear fusion power plants are a promising option to ensure the energy supply for future generations, but in many fields of research enormous challenges have to be faced. A major step on the way to the prototype fusion reactor DEMO will be ITER which is build in Cadarache, southern France. One of the most critical issues is the field of in-vessel materials and components, in particular the plasma facing materials (PFM). PFMs that will be used in a device like ITER have to withstand severe environmental conditions in terms of steady state and transient thermal loads as well as high particle fluxes such as hydrogen, helium and neutrons. Candidate wall materials are beryllium, tungsten and carbon based materials like CFC (carbon fibre composite). Tungsten is the most promising material for an application in the divertor region with very severe loading conditions and it will most probably also be used as PFM for DEMO. Hence, this work focuses on the investigation of the thermal shock response of different tungsten grades in order to understand the damage mechanisms and to identify material parameters which influence this behaviour under ITER and DEMO relevant operation conditions. Therefore the microstructure and the mechanical and thermal properties of five industrially manufactured tungsten grades were characterised. All five tungsten grades were exposed to transient thermal events with very high power densities of up to 1.27 GWm{sup -2} at varying base temperatures between RT and 600 C in the electron beam device JUDITH 1. The pulse numbers were limited to a maximum of 1000 in order to avoid immoderate workload on the test facility and to have enough time to cover a wide range of loading conditions. The results of this damage mapping enable to define different damage and cracking thresholds for the investigated tungsten grades and to identify certain material parameters which influence the location of these thresholds and the distinction of the induced

  9. Thermal shock behaviour of different tungsten grades under varying conditions

    International Nuclear Information System (INIS)

    Wirtz, Oliver Marius

    2012-01-01

    Thermonuclear fusion power plants are a promising option to ensure the energy supply for future generations, but in many fields of research enormous challenges have to be faced. A major step on the way to the prototype fusion reactor DEMO will be ITER which is build in Cadarache, southern France. One of the most critical issues is the field of in-vessel materials and components, in particular the plasma facing materials (PFM). PFMs that will be used in a device like ITER have to withstand severe environmental conditions in terms of steady state and transient thermal loads as well as high particle fluxes such as hydrogen, helium and neutrons. Candidate wall materials are beryllium, tungsten and carbon based materials like CFC (carbon fibre composite). Tungsten is the most promising material for an application in the divertor region with very severe loading conditions and it will most probably also be used as PFM for DEMO. Hence, this work focuses on the investigation of the thermal shock response of different tungsten grades in order to understand the damage mechanisms and to identify material parameters which influence this behaviour under ITER and DEMO relevant operation conditions. Therefore the microstructure and the mechanical and thermal properties of five industrially manufactured tungsten grades were characterised. All five tungsten grades were exposed to transient thermal events with very high power densities of up to 1.27 GWm -2 at varying base temperatures between RT and 600 C in the electron beam device JUDITH 1. The pulse numbers were limited to a maximum of 1000 in order to avoid immoderate workload on the test facility and to have enough time to cover a wide range of loading conditions. The results of this damage mapping enable to define different damage and cracking thresholds for the investigated tungsten grades and to identify certain material parameters which influence the location of these thresholds and the distinction of the induced damages

  10. Robust convergence of Cohen-Grossberg neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Xiong Wenjun; Ma Deyi; Liang Jinling

    2009-01-01

    In this paper, robust convergence is studied for the Cohen-Grossberg neural networks (CGNNs) with time-varying delays. By applying the differential inequality and the Lyapunov method, some delay-independent conditions are derived ensuring the robust CGNNs to converge, globally, uniformly and exponentially, to a ball in the state space with a pre-specified convergence rate. Finally, the effectiveness of our results are verified by an illustrative example.

  11. Passivity of memristive BAM neural networks with leakage and additive time-varying delays

    Science.gov (United States)

    Wang, Weiping; Wang, Meiqi; Luo, Xiong; Li, Lixiang; Zhao, Wenbing; Liu, Linlin; Ping, Yuan

    2018-02-01

    This paper investigates the passivity of memristive bidirectional associate memory neural networks (MBAMNNs) with leakage and additive time-varying delays. Based on some useful inequalities and appropriate Lyapunov-Krasovskii functionals (LKFs), several delay-dependent conditions for passivity performance are obtained in linear matrix inequalities (LMIs). Moreover, the leakage delays as well as additive delays are considered separately. Finally, numerical simulations are provided to demonstrate the feasibility of the theoretical results.

  12. Analysis on Passivity for Uncertain Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    O. M. Kwon

    2014-01-01

    Full Text Available The problem of passivity analysis for neural networks with time-varying delays and parameter uncertainties is considered. By the consideration of newly constructed Lyapunov-Krasovskii functionals, improved sufficient conditions to guarantee the passivity of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs, which can be solved easily by various efficient convex optimization algorithms. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum allowable delay bounds.

  13. Boundedness and stability for recurrent neural networks with variable coefficients and time-varying delays

    International Nuclear Information System (INIS)

    Liang Jinling; Cao Jinde

    2003-01-01

    In this Letter, the problems of boundedness and stability for a general class of non-autonomous recurrent neural networks with variable coefficients and time-varying delays are analyzed via employing Young inequality technique and Lyapunov method. Some simple sufficient conditions are given for boundedness and stability of the solutions for the recurrent neural networks. These results generalize and improve the previous works, and they are easy to check and apply in practice. Two illustrative examples and their numerical simulations are also given to demonstrate the effectiveness of the proposed results

  14. New results on global exponential stability of recurrent neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Xu Shengyuan; Chu Yuming; Lu Junwei

    2006-01-01

    This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples

  15. New results on global exponential stability of recurrent neural networks with time-varying delays

    Energy Technology Data Exchange (ETDEWEB)

    Xu Shengyuan [Department of Automation, Nanjing University of Science and Technology, Nanjing 210094 (China)]. E-mail: syxu02@yahoo.com.cn; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou, Zhejiang 313000 (China); Lu Junwei [School of Electrical and Automation Engineering, Nanjing Normal University, 78 Bancang Street, Nanjing, 210042 (China)

    2006-04-03

    This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples.

  16. On the Conditional Entropy of Wireless Networks

    DEFF Research Database (Denmark)

    Coon, Justin P.; Badiu, Mihai Alin; Gündüz, Deniz

    2018-01-01

    The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two appr...... a homogeneous binomial point process in this work) and the network topology....

  17. Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints

    Directory of Open Access Journals (Sweden)

    Shu-Min Lu

    2017-01-01

    Full Text Available An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.

  18. New convergence behavior of solutions to Cohen-Grossberg neural networks with delays and time-varying coefficients

    International Nuclear Information System (INIS)

    Liu Bingwen

    2008-01-01

    In this Letter the convergence behavior of Cohen-Grossberg neural networks with delays and time-varying coefficients are considered. Some sufficient conditions are established to ensure that the solutions of the networks converge locally exponentially to zero point, which are new and complement of previously known results

  19. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Science.gov (United States)

    Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

    2013-09-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

  20. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    International Nuclear Information System (INIS)

    Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

    2013-01-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

  1. Delay-dependent exponential stability for neural networks with discrete and distributed time-varying delays

    International Nuclear Information System (INIS)

    Zhu Xunlin; Wang Youyi

    2009-01-01

    This Letter studies the exponential stability for a class of neural networks (NNs) with both discrete and distributed time-varying delays. Under weaker assumptions on the activation functions, by defining a more general type of Lyapunov functionals and developing a new convex combination technique, new less conservative and less complex stability criteria are established to guarantee the global exponential stability of the discussed NNs. The obtained conditions are dependent on both discrete and distributed delays, are expressed in terms of linear matrix inequalities (LMIs), and contain fewer decision variables. Numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.

  2. Design of Multijunction Photovoltaic Cells Optimized for Varied Atmospheric Conditions

    Directory of Open Access Journals (Sweden)

    C. Zhang

    2014-01-01

    Full Text Available Band gap engineering provides an opportunity to not only provide higher overall conversion efficiencies of the reference AM1.5 spectra but also customize PV device design for specific geographic locations and microenvironments based on atmospheric conditions characteristic to that particular location. Indium gallium nitride and other PV materials offer the opportunity for limited bandgap engineering to match spectra. The effects of atmospheric conditions such as aerosols, cloud cover, water vapor, and air mass have been shown to cause variations in spectral radiance that alters PV system performance due to both overrating and underrating. Designing PV devices optimized for spectral radiance of a particular region can result in improved PV system performance. This paper presents a new method for designing geographically optimized PV cells with using a numerical model for bandgap optimization. The geographic microclimate spectrally resolved solar flux for twelve representative atmospheric conditions for the incident radiation angle (zenith angle of 48.1° and fixed array angle of 40° is used to iteratively optimize the band gap for tandem, triple, and quad-layer of InGaN-based multijunction cells. The results of this method are illustrated for the case study of solar farms in the New York region and discussed.

  3. H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

    Science.gov (United States)

    Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

    2018-03-01

    This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Pinning synchronization of memristor-based neural networks with time-varying delays.

    Science.gov (United States)

    Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng

    2017-09-01

    In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Varied overstrain injuries of the vertebral column conditioned by evolution

    Energy Technology Data Exchange (ETDEWEB)

    Kohlbach, W

    1983-08-01

    During physiological growth of the juvenile vertebral column, various stages of stability occur which are characterized by the condition of the marginal rim of the vertebral bodies. If the vertebral juvenile column is overstrained, these variations in stability results in a variety of damage to vertebral bodies and vertebral disks. One of these lesions corresponds to Scheuermann's disease (osteochondrosis of vertebral epiphyses in juveniles). Damage of the vertebral column due to overstrain can occur only if the overstrain is applied in upright position. Since Man alone can damage his vertebral column in upright position (as a result of his evolutionary development), Scheuermann's thesis is confirmed that Scheuermann's disease is confined to Man. Spondylolysis/spondylolisthesis is also a damage caused by overstrain. Here, too, the damage can occur only if the load is exercised in upright position, with the exception of a slanted positioning of the intervertebral components.

  6. Varied overstrain injuries of the vertebral column conditioned by evolution

    International Nuclear Information System (INIS)

    Kohlbach, W.

    1983-01-01

    During physiological growth of the juvenile vertebral column, various stages of stability occur which are characterized by the condition of the marginal rim of the vertebral bodies. If the vertebral juvenile column is overstrained, these variations in stability results in a variety of damage to vertebral bodies and vertebral disks. One of these lesions corresponds to Scheuermann's disease (osteochondrosis of vertebral epiphyses in juveniles). Damage of the vertebral column due to overstrain can occur only if the overstrain is applied in upright position. Since Man alone can damage his vertebral column in upright position (as a result of his evolutionary development), Scheuermann's thesis is confirmed that Scheuermann's disease is confined to Man. Spondylolysis/spondylolisthesis is also a damage caused by overstrain. Here, too, the damage can occur only if the load is exercised in upright position, with the exception of a slanted positioning of the intervertebral components. (orig.) [de

  7. Varied overstrain injuries of the vertebral column conditioned by evolution

    Energy Technology Data Exchange (ETDEWEB)

    Kohlbach, W.

    1983-08-01

    During physiological growth of the juvenile vertebral column, various stages of stability occur which are characterized by the condition of the marginal rim of the vertebral bodies. If the vertebral juvenile column is overstrained, these variations in stability results in a variety of damage to vertebral bodies and vertebral disks. One of these lesions corresponds to Scheuermann's disease (osteochondrosis of vertebral epiphyses in juveniles). Damage of the vertebral column due to overstrain can occur only if the overstrain is applied in upright position. Since Man alone can damage his vertebral column in upright position (as a result of his evolutionary development), Scheuermann's thesis is confirmed that Scheuermann's disease is confined to Man. Spondylolysis/spondylolisthesis is also a damage caused by overstrain. Here, too, the damage can occur only if the load is exercised in upright position, with the exception of a slanted positioning of the intervertebral components.

  8. Concurrent conditional clustering of multiple networks: COCONETS.

    Directory of Open Access Journals (Sweden)

    Sabrina Kleessen

    Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

  9. Weed spectrum and selectivity of tembotrione under varying environmental conditions

    Directory of Open Access Journals (Sweden)

    Gatzweiler, Elmar

    2012-03-01

    Full Text Available Tembotrione is a novel HPPD maize herbicide effective against a wide range of broadleaf and grass weeds. Some characteristics of this compound are described in this paper linking weed and crop responses following tembotrione applications to environmental parameters or use conditions. The activity of HPPD herbicides is very much dependant on the availability of light. Increasing illumination intensities following application augmented the activity levels of several comparable HPPD compounds in a growth chamber experiment. Tembotrione was shown to be more efficacious at low and high illumination intensities compared to standard herbicides applied at the same rate. At the high intensity, tembotrione retained its high efficacy from two up to four weeks after application showing a rapid and strong herbicidal activity. The activity following post-emergent treatments of tembotrione against broadleaf weeds was influenced by soil characteristics such as soil texture and organic matter content in a glasshouse test. The level of weed suppression clearly declined stronger on heavier soils than on lighter soils at a rather low application rate of 12.5 g a.i./ha and lower. This is a clear indication of residual efficacy of tembotrione. The selectivity of tembotrione was tested on numerous maize varieties following post-emergent treatment with tembotrione alone or in mixture with the safener isoxadifen-ethyl under field conditions in Germany in comparison to a standard herbicide. The level of crop phytotoxicity tended to increase in the following order: Tembotrione plus safener, standard herbicide to tembotrione alone. Only the mixture of tembotrione with safener did not cause significant adverse effects on maize. Another field experiment in the USA examined crop phytotoxicity using one maize variety in a situation of infurrow soil insecticide treatment followed by a post-emergent application of tembotrione (plus/minus isoxadifen-ethyl and standard herbicides

  10. Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Huaiqin Wu

    2013-01-01

    Full Text Available This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays. Under the framework of Filippov solutions, by applying the inequality analysis techniques, the existence and asymptotically almost periodic behavior of solutions are discussed. Based on the differential inclusions theory and Lyapunov functional approach, the stability issues of almost periodic solution are investigated, and a sufficient condition for the existence, uniqueness, and global exponential stability of the almost periodic solution is established. Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks. Two examples are given to illustrate the validity of the theoretical results.

  11. Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay

    International Nuclear Information System (INIS)

    Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.

    2010-01-01

    In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.

  12. Novel global robust stability criteria for interval neural networks with multiple time-varying delays

    International Nuclear Information System (INIS)

    Xu Shengyuan; Lam, James; Ho, Daniel W.C.

    2005-01-01

    This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method

  13. A Kalman-filter based approach to identification of time-varying gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Jie Xiong

    Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

  14. Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis

    International Nuclear Information System (INIS)

    Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui

    2007-01-01

    This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition

  15. Statistical Traffic Anomaly Detection in Time-Varying Communication Networks

    Science.gov (United States)

    2015-02-01

    PLs can be generated using tad and (7). Otherwise, the network is periodic according to feature a, and a family of candidate PLs can be generated...using tad , t a p, and (8). In addition, in case that some prior knowledge of td and tp is available, the family of candidate PLs can include the PLs

  16. Statistical Traffic Anomaly Detection in Time Varying Communication Networks

    Science.gov (United States)

    2015-02-01

    PLs can be generated using tad and (7). Otherwise, the network is periodic according to feature a, and a family of candidate PLs can be generated...using tad , t a p, and (8). In addition, in case that some prior knowledge of td and tp is available, the family of candidate PLs can include the PLs

  17. On the Conditional Entropy of Wireless Networks

    DEFF Research Database (Denmark)

    Coon, Justin P.; Badiu, Mihai Alin; Gündüz, Deniz

    2018-01-01

    The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two...... approaches are considered: 1) conditioning on subgraphs, and 2) conditioning on node positions. The first approach is shown to yield a relatively tight bound on the network entropy. The second yields a loose bound, in general, but it provides insight into the dependence between node positions (modelled using...

  18. H∞ state estimation of generalised neural networks with interval time-varying delays

    Science.gov (United States)

    Saravanakumar, R.; Syed Ali, M.; Cao, Jinde; Huang, He

    2016-12-01

    This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov-Krasovskii functional are handled by the Jensen's inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.

  19. Basic regulatory principles of Escherichia coli's electron transport chain for varying oxygen conditions.

    Science.gov (United States)

    Henkel, Sebastian G; Ter Beek, Alexander; Steinsiek, Sonja; Stagge, Stefan; Bettenbrock, Katja; de Mattos, M Joost Teixeira; Sauter, Thomas; Sawodny, Oliver; Ederer, Michael

    2014-01-01

    For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the global transcriptional regulators FNR and ArcA are involved in oxygen response it is unclear how they interplay in the regulation of ETC enzymes under micro-aerobic chemostat conditions. Also, there are diverse results which and how quinones (oxidised/reduced, ubiquinone/other quinones) are controlling the ArcBA two-component system. In the following a mathematical model of the E. coli ETC linked to basic modules for substrate uptake, fermentation product excretion and biomass formation is introduced. The kinetic modelling focusses on regulatory principles of the ETC for varying oxygen conditions in glucose-limited continuous cultures. The model is based on the balance of electron donation (glucose) and acceptance (oxygen or other acceptors). Also, it is able to account for different chemostat conditions due to changed substrate concentrations and dilution rates. The parameter identification process is divided into an estimation and a validation step based on previously published and new experimental data. The model shows that experimentally observed, qualitatively different behaviour of the ubiquinone redox state and the ArcA activity profile in the micro-aerobic range for different experimental conditions can emerge from a single network structure. The network structure features a strong feed-forward effect from the FNR regulatory system to the ArcBA regulatory system via a common control of the dehydrogenases of the ETC. The model supports the hypothesis that ubiquinone but not ubiquinol plays a key role in determining the activity of ArcBA in a glucose-limited chemostat at micro-aerobic conditions.

  20. Stability analysis of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time varying delays

    International Nuclear Information System (INIS)

    Ali, M. Syed

    2014-01-01

    In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples

  1. Synchronization of nonidentical chaotic neural networks with leakage delay and mixed time-varying delays

    Directory of Open Access Journals (Sweden)

    Cao Jinde

    2011-01-01

    Full Text Available Abstract In this paper, an integral sliding mode control approach is presented to investigate synchronization of nonidentical chaotic neural networks with discrete and distributed time-varying delays as well as leakage delay. By considering a proper sliding surface and constructing Lyapunov-Krasovskii functional, as well as employing a combination of the free-weighting matrix method, Newton-Leibniz formulation and inequality technique, a sliding mode controller is designed to achieve the asymptotical synchronization of the addressed nonidentical neural networks. Moreover, a sliding mode control law is also synthesized to guarantee the reachability of the specified sliding surface. The provided conditions are expressed in terms of linear matrix inequalities, and are dependent on the discrete and distributed time delays as well as leakage delay. A simulation example is given to verify the theoretical results.

  2. Stability in Cohen Grossberg-type bidirectional associative memory neural networks with time-varying delays

    Science.gov (United States)

    Cao, Jinde; Song, Qiankun

    2006-07-01

    In this paper, the exponential stability problem is investigated for a class of Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results.

  3. Synchronization of uncertain time-varying network based on sliding mode control technique

    Science.gov (United States)

    Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe

    2017-09-01

    We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.

  4. Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Chunmei Wu

    2015-01-01

    Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.

  5. Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays.

    Science.gov (United States)

    Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed

    2018-02-01

    This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.

  6. Neural network to diagnose lining condition

    Science.gov (United States)

    Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

    2018-03-01

    The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

  7. Changing Conditions for Networked Learning?

    DEFF Research Database (Denmark)

    Ryberg, Thomas

    2011-01-01

    in describing the novel pedagogical potentials of these new technologies and practices (e.g. in debates around virtual learning environments versus personal learning environment). Likewise, I shall briefly discuss the notions of ‘digital natives’ or ‘the net generation’ from a critical perspective...... of social technologies. I argue that we are seeing the emergence of new architectures and scales of participation, collaboration and networking e.g. through interesting formations of learning networks at different levels of scale, for different purposes and often bridging boundaries such as formal...

  8. Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case

    Science.gov (United States)

    Raja, R.; Marshal Anthoni, S.

    2011-02-01

    This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method.

  9. Optimal routing of hazardous substances in time-varying, stochastic transportation networks

    International Nuclear Information System (INIS)

    Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.

    1998-07-01

    This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Several specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions

  10. New Passivity Criteria for Fuzzy Bam Neural Networks with Markovian Jumping Parameters and Time-Varying Delays

    Science.gov (United States)

    Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Thangaraj, P.

    2013-02-01

    This paper addresses the problem of passivity analysis issue for a class of fuzzy bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time varying delays. A set of sufficient conditions for the passiveness of the considered fuzzy BAM neural network model is derived in terms of linear matrix inequalities by using the delay fractioning technique together with the Lyapunov function approach. In addition, the uncertainties are inevitable in neural networks because of the existence of modeling errors and external disturbance. Further, this result is extended to study the robust passivity criteria for uncertain fuzzy BAM neural networks with time varying delays and uncertainties. These criteria are expressed in the form of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical software. Two numerical examples are provided to demonstrate the effectiveness of the obtained results.

  11. New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays.

    Science.gov (United States)

    Zhang, Guodong; Zeng, Zhigang; Hu, Junhao

    2018-01-01

    This paper is concerned with the global exponential dissipativity of memristive inertial neural networks with discrete and distributed time-varying delays. By constructing appropriate Lyapunov-Krasovskii functionals, some new sufficient conditions ensuring global exponential dissipativity of memristive inertial neural networks are derived. Moreover, the globally exponential attractive sets and positive invariant sets are also presented here. In addition, the new proposed results here complement and extend the earlier publications on conventional or memristive neural network dynamical systems. Finally, numerical simulations are given to illustrate the effectiveness of obtained results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

    OpenAIRE

    Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

    2014-01-01

    It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inf...

  13. Synchronization between Different Networks with Time-Varying Delay and Its Application in Bilayer Coupled Public Traffic Network

    Directory of Open Access Journals (Sweden)

    Wenju Du

    2016-01-01

    Full Text Available In order to study the dynamic characteristics of urban public traffic network, this paper establishes the conventional bus traffic network and the urban rail traffic network based on the space R modeling method. Then regarding these two networks as the subnetwork, the paper presents a new bilayer coupled public traffic network through the transfer relationship between subway and bus, and this model well reflects the connection between the passengers and bus operating vehicles. Based on the synchronization theory of coupling network with time-varying delay and taking “Lorenz system” as the network node, the paper studies the synchronization of bilayer coupled public traffic network. Finally, numerical results are given to show the impact of public traffic dispatching, delayed departure, the number of public bus stops between bus lines, and the number of transfer stations between two traffic modes on the bilayer coupled public traffic network balance through Matlab simulation.

  14. Estimation of Conditional Quantile using Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1999-01-01

    The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis...... for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating...... the capabilities of the elaborated neural network are also given....

  15. Exponential convergence for a class of delayed cellular neural networks with time-varying coefficients

    International Nuclear Information System (INIS)

    Liu Bingwen

    2008-01-01

    In this Letter, we consider a class of delayed cellular neural networks with time-varying coefficients. By applying Lyapunov functional method and differential inequality techniques, we establish new results to ensure that all solutions of the networks converge exponentially to zero point

  16. Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

    International Nuclear Information System (INIS)

    Jian-Rui, Chen; Li-Cheng, Jiao; Jian-She, Wu; Xiao-Hua, Wang

    2009-01-01

    A new general network model for two complex networks with time-varying delay coupling is presented. Then we investigate its synchronization phenomena. The two complex networks of the model differ in dynamic nodes, the number of nodes and the coupling connections. By using adaptive controllers, a synchronization criterion is derived. Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion. This study may widen the application range of synchronization, such as in chaotic secure communication. (general)

  17. Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses.

    Science.gov (United States)

    Zhang, Wei; Huang, Tingwen; He, Xing; Li, Chuandong

    2017-11-01

    In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks. Finally, two numerical examples are provided to illustrate the efficiency of the proposed methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

    International Nuclear Information System (INIS)

    Mei, Sun; Chang-Yan, Zeng; Li-Xin, Tian

    2009-01-01

    Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand–supply of energy resource in some regions of China

  19. Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

    Science.gov (United States)

    Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin

    2009-01-01

    Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.

  20. On the synchronization of neural networks containing time-varying delays and sector nonlinearity

    International Nuclear Information System (INIS)

    Yan, J.-J.; Lin, J.-S.; Hung, M.-L.; Liao, T.-L.

    2007-01-01

    We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme

  1. Novel criteria for global exponential periodicity and stability of recurrent neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Song Qiankun

    2008-01-01

    In this paper, the global exponential periodicity and stability of recurrent neural networks with time-varying delays are investigated by applying the idea of vector Lyapunov function, M-matrix theory and inequality technique. We assume neither the global Lipschitz conditions on these activation functions nor the differentiability on these time-varying delays, which were needed in other papers. Several novel criteria are found to ascertain the existence, uniqueness and global exponential stability of periodic solution for recurrent neural network with time-varying delays. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. Some previous results are improved and generalized, and an example is given to show the effectiveness of our method

  2. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    International Nuclear Information System (INIS)

    Dong Suyalatu; Deng Yan-Bin; Huang Yong-Chang

    2017-01-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network . (paper)

  3. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    Science.gov (United States)

    Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

    2017-10-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

  4. Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions.

    Science.gov (United States)

    Song, Li; Prince, Silvas; Valliyodan, Babu; Joshi, Trupti; Maldonado dos Santos, Joao V; Wang, Jiaojiao; Lin, Li; Wan, Jinrong; Wang, Yongqin; Xu, Dong; Nguyen, Henry T

    2016-01-15

    Soybean is a major crop that provides an important source of protein and oil to humans and animals, but its production can be dramatically decreased by the occurrence of drought stress. Soybeans can survive drought stress if there is a robust and deep root system at the early vegetative growth stage. However, little is known about the genome-wide molecular mechanisms contributing to soybean root system architecture. This study was performed to gain knowledge on transcriptome changes and related molecular mechanisms contributing to soybean root development under water limited conditions. The soybean Williams 82 genotype was subjected to very mild stress (VMS), mild stress (MS) and severe stress (SS) conditions, as well as recovery from the severe stress after re-watering (SR). In total, 6,609 genes in the roots showed differential expression patterns in response to different water-deficit stress levels. Genes involved in hormone (Auxin/Ethylene), carbohydrate, and cell wall-related metabolism (XTH/lipid/flavonoids/lignin) pathways were differentially regulated in the soybean root system. Several transcription factors (TFs) regulating root growth and responses under varying water-deficit conditions were identified and the expression patterns of six TFs were found to be common across the stress levels. Further analysis on the whole plant level led to the finding of tissue-specific or water-deficit levels specific regulation of transcription factors. Analysis of the over-represented motif of different gene groups revealed several new cis-elements associated with different levels of water deficit. The expression patterns of 18 genes were confirmed byquantitative reverse transcription polymerase chain reaction method and demonstrated the accuracy and effectiveness of RNA-Seq. The primary root specific transcriptome in soybean can enable a better understanding of the root response to water deficit conditions. The genes detected in root tissues that were associated with

  5. An analysis of periodic solutions of bi-directional associative memory networks with time-varying delays

    International Nuclear Information System (INIS)

    Cao Jinde; Jiang Qiuhao

    2004-01-01

    In this Letter, several sufficient conditions are derived for the existence and uniqueness of periodic oscillatory solution for bi-directional associative memory (BAM) networks with time-varying delays by employing a new Lyapunov functional and an elementary inequality, and all other solutions of the BAM networks converge exponentially to the unique periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of periodic neural circuits for delayed BAM. As an illustration, two numerical examples are worked out using the results obtained

  6. Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    O. M. Kwon

    2012-01-01

    Full Text Available The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

  7. Stability of Almost Periodic Solution for a General Class of Discontinuous Neural Networks with Mixed Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Yingwei Li

    2013-01-01

    Full Text Available The global exponential stability issues are considered for almost periodic solution of the neural networks with mixed time-varying delays and discontinuous neuron activations. Some sufficient conditions for the existence, uniqueness, and global exponential stability of almost periodic solution are achieved in terms of certain linear matrix inequalities (LMIs, by applying differential inclusions theory, matrix inequality analysis technique, and generalized Lyapunov functional approach. In addition, the existence and asymptotically almost periodic behavior of the solution of the neural networks are also investigated under the framework of the solution in the sense of Filippov. Two simulation examples are given to illustrate the validity of the theoretical results.

  8. Centralized and decentralized global outer-synchronization of asymmetric recurrent time-varying neural network by data-sampling.

    Science.gov (United States)

    Lu, Wenlian; Zheng, Ren; Chen, Tianping

    2016-03-01

    In this paper, we discuss outer-synchronization of the asymmetrically connected recurrent time-varying neural networks. By using both centralized and decentralized discretization data sampling principles, we derive several sufficient conditions based on three vector norms to guarantee that the difference of any two trajectories starting from different initial values of the neural network converges to zero. The lower bounds of the common time intervals between data samples in centralized and decentralized principles are proved to be positive, which guarantees exclusion of Zeno behavior. A numerical example is provided to illustrate the efficiency of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Exponential Stability for Impulsive BAM Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms

    Directory of Open Access Journals (Sweden)

    Qiankun Song

    2007-06-01

    Full Text Available Impulsive bidirectional associative memory neural network model with time-varying delays and reaction-diffusion terms is considered. Several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for the addressed neural network are derived by M-matrix theory, analytic methods, and inequality techniques. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The obtained results in this paper are less restrictive than previously known criteria. Two examples are given to show the effectiveness of the obtained results.

  10. Exponential Stability for Impulsive BAM Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms

    Directory of Open Access Journals (Sweden)

    Cao Jinde

    2007-01-01

    Full Text Available Impulsive bidirectional associative memory neural network model with time-varying delays and reaction-diffusion terms is considered. Several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for the addressed neural network are derived by M-matrix theory, analytic methods, and inequality techniques. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The obtained results in this paper are less restrictive than previously known criteria. Two examples are given to show the effectiveness of the obtained results.

  11. Robust stability of uncertain Markovian jumping Cohen-Grossberg neural networks with mixed time-varying delays

    International Nuclear Information System (INIS)

    Sheng Li; Yang Huizhong

    2009-01-01

    This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.

  12. Robust stability analysis of Takagi—Sugeno uncertain stochastic fuzzy recurrent neural networks with mixed time-varying delays

    International Nuclear Information System (INIS)

    Ali, M. Syed

    2011-01-01

    In this paper, the global stability of Takagi—Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature. (general)

  13. Impulsive effect on global exponential stability of BAM fuzzy cellular neural networks with time-varying delays

    Science.gov (United States)

    Li, Kelin

    2010-02-01

    In this article, a class of impulsive bidirectional associative memory (BAM) fuzzy cellular neural networks (FCNNs) with time-varying delays is formulated and investigated. By employing delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM FCNNs with time-varying delays are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM FCNNs. An example is given to show the effectiveness of the results obtained here.

  14. Exponential networked synchronization of master-slave chaotic systems with time-varying communication topologies

    International Nuclear Information System (INIS)

    Yang Dong-Sheng; Liu Zhen-Wei; Liu Zhao-Bing; Zhao Yan

    2012-01-01

    The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method. (general)

  15. Computing Conditional VaR using Time-varying CopulasComputing Conditional VaR using Time-varying Copulas

    Directory of Open Access Journals (Sweden)

    Beatriz Vaz de Melo Mendes

    2005-12-01

    Full Text Available It is now widespread the use of Value-at-Risk (VaR as a canonical measure at risk. Most accurate VaR measures make use of some volatility model such as GARCH-type models. However, the pattern of volatility dynamic of a portfolio follows from the (univariate behavior of the risk assets, as well as from the type and strength of the associations among them. Moreover, the dependence structure among the components may change conditionally t past observations. Some papers have attempted to model this characteristic by assuming a multivariate GARCH model, or by considering the conditional correlation coefficient, or by incorporating some possibility for switches in regimes. In this paper we address this problem using time-varying copulas. Our modeling strategy allows for the margins to follow some FIGARCH type model while the copula dependence structure changes over time.

  16. Flows in networks under fuzzy conditions

    CERN Document Server

    Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich

    2017-01-01

    This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...

  17. Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

    Science.gov (United States)

    Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

    2017-01-01

    The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

  18. Chimeras in a network of three oscillator populations with varying network topology

    DEFF Research Database (Denmark)

    Martens, Erik Andreas

    2010-01-01

    this system as a model system, we discuss for the first time the influence of network topology on the existence of so-called chimera states. In this context, the network with three populations represents an interesting case because the populations may either be connected as a triangle, or as a chain, thereby......-like. By showing that chimera states only exist for a bounded set of parameter values, we demonstrate that their existence depends strongly on the underlying network structures, and conclude that chimeras exist on networks with a chain-like character....

  19. Bearing Condition Recognition and Degradation Assessment under Varying Running Conditions Using NPE and SOM

    Directory of Open Access Journals (Sweden)

    Shaohui Zhang

    2014-01-01

    Full Text Available Manifold learning methods have been widely used in machine condition monitoring and fault diagnosis. However, the results reported in these studies focus on the machine faults under stable loading and rotational speeds, which cannot interpret the practical machine running. Rotating machine is always running under variable speeds and loading, which makes the vibration signal more complicated. To address such concern, the NPE (neighborhood preserving embedding is applied for bearing fault classification. Compared with other algorithms (PCA, LPP, LDA, and ISOP, the NPE performs well in feature extraction. Since the traditional time domain signal denoising is time consuming and memory consuming, we denoise the signal features directly in feature space. Furthermore, NPE and SOM (self-organizing map are combined to assess the bearing degradation performance. Simulation and experiment results validate the effectiveness of the proposed method.

  20. Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints

    International Nuclear Information System (INIS)

    Zhang Yunong; Li Zhan

    2009-01-01

    In this Letter, by following Zhang et al.'s method, a recurrent neural network (termed as Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying convex quadratic-programming problem subject to time-varying linear-equality constraints. Different from conventional gradient-based neural networks (GNN), such a ZNN model makes full use of the time-derivative information of time-varying coefficient. The resultant ZNN model is theoretically proved to have global exponential convergence to the time-varying theoretical optimal solution of the investigated time-varying convex quadratic program. Computer-simulation results further substantiate the effectiveness, efficiency and novelty of such ZNN model and method.

  1. Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

    Science.gov (United States)

    2010-12-10

    Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen

  2. Artificial neural network modeling of DDGS flowability with varying process and storage parameters

    Science.gov (United States)

    Neural Network (NN) modeling techniques were used to predict flowability behavior in distillers dried grains with solubles (DDGS) prepared with varying CDS (10, 15, and 20%, wb), drying temperature (100, 200, and 300°C), cooling temperature (-12, 0, and 35°C) and cooling time (0 and 1 month) levels....

  3. Robustness analysis of the Zhang neural network for online time-varying quadratic optimization

    International Nuclear Information System (INIS)

    Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen

    2010-01-01

    A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.

  4. Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

    Directory of Open Access Journals (Sweden)

    Naradasu Kumar Ravi

    2013-01-01

    Full Text Available Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.

  5. Leading-Edge Noise Prediction of General Airfoil Profiles with Spanwise-Varying Inflow Conditions

    NARCIS (Netherlands)

    Miotto, Renato Fuzaro; Wolf, William Roberto; De Santana, Leandro Dantas

    2018-01-01

    This paper presents a study of the leading-edge noise radiated by an airfoil undergoing a turbulent inflow. The noise prediction of generic airfoil profiles subjected to spanwise-varying inflow conditions is performed with the support of Amiet’s theory and the inverse strip technique. In the

  6. Leading-Edge Noise Prediction of General Airfoil Profiles with Spanwise-Varying Inflow Conditions

    NARCIS (Netherlands)

    Miotto, Renato Fuzaro; Wolf, William Roberto; De Santana, Leandro Dantas

    This paper presents a study of the leading-edge noise radiated by an airfoil undergoing a turbulent inflow. The noise prediction of generic airfoil profiles subjected to spanwise-varying inflow conditions is performed with the support of Amiet’s theory and the inverse strip technique. In the

  7. Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions

    Directory of Open Access Journals (Sweden)

    Lang Xue

    2017-06-01

    Full Text Available Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions.

  8. Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions.

    Science.gov (United States)

    Xue, Lang; Li, Naipeng; Lei, Yaguo; Li, Ningbo

    2017-06-20

    Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR) features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP) is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions.

  9. Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

    Science.gov (United States)

    Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

    2018-05-01

    Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

  10. Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

    Science.gov (United States)

    Li, Shuai; Li, Yangming

    2013-10-28

    The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

  11. Network conditioning under conflicting goals: Accident causation

    International Nuclear Information System (INIS)

    Jouse, W.C.

    1992-01-01

    Networks based on the Barto-Sutton architecture (BSA) of neural-like elements have an information-processing structure that is analogous to the cognitive structure of a human. Given a set of explicitly stated rules of conduct, such networks develop a set of skills that is capable of satisfying the rules. In this sense, the network acts as a translator of rules into skill-based behavior. The BSA acquires its skills through casual, correlation-based scheduling. Stated briefly, it first constructs an internal representation, or model, of the rules of conduct, and then uses the model to correct deficiencies in its skill. It learns in a manner that closely resembles classical conditioning, shifting the onset of signals associated with unconditioned stimuli forward in time to coincide with the onset of conditioning stimuli. The low-level positive reinforcement the network receives from enhancing its operational efficiency is immediate and direct. In the absence of countervailing influences, this continuous pressure is sufficient to discount the recollection of past failures and leads to accidents with a predictable regularity

  12. Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

    Directory of Open Access Journals (Sweden)

    Fikret Emre eKapucu

    2012-06-01

    Full Text Available In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC, exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI histograms. Moreover, the algorithm calculates interspike interval thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

  13. Saliency detection by conditional generative adversarial network

    Science.gov (United States)

    Cai, Xiaoxu; Yu, Hui

    2018-04-01

    Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

  14. Remaining useful life estimation for deteriorating systems with time-varying operational conditions and condition-specific failure zones

    Directory of Open Access Journals (Sweden)

    Li Qi

    2016-06-01

    Full Text Available Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life (RUL for the deteriorating systems. This paper presents a method based on probabilistic and stochastic approaches to estimate system RUL for periodically monitored degradation processes with dynamic time-varying operational conditions and condition-specific failure zones. The method assumes that the degradation rate is influenced by specific operational condition and moreover, the transition between different operational conditions plays the most important role in affecting the degradation process. These operational conditions are assumed to evolve as a discrete-time Markov chain (DTMC. The failure thresholds are also determined by specific operational conditions and described as different failure zones. The 2008 PHM Conference Challenge Data is utilized to illustrate our method, which contains mass sensory signals related to the degradation process of a commercial turbofan engine. The RUL estimation method using the sensor measurements of a single sensor was first developed, and then multiple vital sensors were selected through a particular optimization procedure in order to increase the prediction accuracy. The effectiveness and advantages of the proposed method are presented in a comparison with existing methods for the same dataset.

  15. Single server queueing networks with varying service times and renewal input

    Directory of Open Access Journals (Sweden)

    Pierre Le Gall

    2000-01-01

    Full Text Available Using recent results in tandem queues and queueing networks with renewal input, when successive service times of the same customer are varying (and when the busy periods are frequently not broken up in large networks, the local queueing delay of a single server queueing network is evaluated utilizing new concepts of virtual and actual delays (respectively. It appears that because of an important property, due to the underlying tandem queue effect, the usual queueing standards (related to long queues cannot protect against significant overloads in the buffers due to some possible “agglutination phenomenon” (related to short queues. Usual network management methods and traffic simulation methods should be revised, and should monitor the partial traffic streams loads (and not only the server load.

  16. Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

    Directory of Open Access Journals (Sweden)

    Lingyun Li

    2013-01-01

    Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.

  17. Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

    Science.gov (United States)

    Meng, Su; Chen, Jie; Sun, Jian

    2017-10-01

    This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

  18. Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

    Science.gov (United States)

    Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

    2017-05-01

    The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

  19. Gas metal arc welding of butt joint with varying gap width based on neural networks

    DEFF Research Database (Denmark)

    Christensen, Kim Hardam; Sørensen, Torben

    2005-01-01

    penetration, when the gap width is varying during the welding process. The process modeling to facilitate the mapping from joint geometry and reference weld quality to significant welding parameters, has been based on a multi-layer feed-forward network. The Levenberg-Marquardt algorithm for non-linear least......This paper describes the application of the neural network technology for gas metal arc welding (GMAW) control. A system has been developed for modeling and online adjustment of welding parameters, appropriate to guarantee a certain degree of quality in the field of butt joint welding with full...

  20. Closeness-Centrality-Based Synchronization Criteria for Complex Dynamical Networks With Interval Time-Varying Coupling Delays.

    Science.gov (United States)

    Park, Myeongjin; Lee, Seung-Hoon; Kwon, Oh-Min; Seuret, Alexandre

    2017-09-06

    This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

  1. Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

    Science.gov (United States)

    Wu, Wei; Cui, Bao-Tong

    2007-07-01

    In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.

  2. Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

    Science.gov (United States)

    Nie, Xiaobing; Zheng, Wei Xing

    2015-05-01

    This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control

    International Nuclear Information System (INIS)

    Cui Baotong; Lou Xuyang

    2009-01-01

    In this paper, a new method to synchronize two identical chaotic recurrent neural networks is proposed. Using the drive-response concept, a nonlinear feedback control law is derived to achieve the state synchronization of the two identical chaotic neural networks. Furthermore, based on the Lyapunov method, a delay independent sufficient synchronization condition in terms of linear matrix inequality (LMI) is obtained. A numerical example with graphical illustrations is given to illuminate the presented synchronization scheme

  4. Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure

    DEFF Research Database (Denmark)

    Amado, Christina; Teräsvirta, Timo

    multiplier type misspecification tests. Finite-sample properties of these procedures and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice......In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either ad- ditive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change...... in the conditional and unconditional variances where the transition between regimes over time is smooth. A modelling strategy for these new time-varying parameter GARCH models is developed. It relies on a sequence of Lagrange multiplier tests, and the adequacy of the estimated models is investigated by Lagrange...

  5. Improving Delay-Range-Dependent Stability Condition for Systems with Interval Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Wei Qian

    2013-01-01

    Full Text Available This paper discusses the delay-range-dependent stability for systems with interval time-varying delay. Through defining the new Lyapunov-Krasovskii functional and estimating the derivative of the LKF by introducing new vectors, using free matrices and reciprocally convex approach, the new delay-range-dependent stability conditions are obtained. Two well-known examples are given to illustrate the less conservatism of the proposed theoretical results.

  6. Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay

    International Nuclear Information System (INIS)

    Tu Fenghua; Liao Xiaofeng

    2005-01-01

    We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable

  7. A note on "Multicriteria adaptive paths in stochastic, time-varying networks"

    DEFF Research Database (Denmark)

    Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan

    In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...... that does not hold in general. Opasanon and Miller-Hooks also propose an algorithm for solving a parametric problem. We give a simplified algorithm which is linear in the input size....

  8. Some new results for recurrent neural networks with varying-time coefficients and delays

    International Nuclear Information System (INIS)

    Jiang Haijun; Teng Zhidong

    2005-01-01

    In this Letter, we consider the recurrent neural networks with varying-time coefficients and delays. By constructing new Lyapunov functional, introducing ingeniously many real parameters and applying the technique of Young inequality, we establish a series of criteria on the boundedness, global exponential stability and the existence of periodic solutions. In these criteria, we do not require that the response functions are differentiable, bounded and monotone nondecreasing. Some previous works are improved and extended

  9. On exponential stability of bidirectional associative memory neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Park, Ju H.; Lee, S.M.; Kwon, O.M.

    2009-01-01

    For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.

  10. Conditional efficient multiuser quantum cryptography network

    International Nuclear Information System (INIS)

    Xue Peng; Li Chuanfeng; Guo Guangcan

    2002-01-01

    We propose a conditional quantum key distribution scheme with three nonorthogonal states. Combined with the idea presented by Lo et al. (H.-K. Lo, H. F. Chau, and M. Ardehali, e-print arXiv: quant-ph/0011056), the efficiency of this scheme is increased to tend to 100%. Also, such a refined data analysis guarantees the security of our scheme against the most general eavesdropping strategy. Then, based on the scheme, we present a quantum cryptography network with the addition of a device called ''space optical switch.'' Moreover, we give out a realization of a quantum random number generator. Thus, a feasible experimental scheme of this efficient quantum cryptography network is completely given

  11. Fluctuating interaction network and time-varying stability of a natural fish community

    Science.gov (United States)

    Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

    2018-02-01

    Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

  12. Knowledge diffusion in complex networks by considering time-varying information channels

    Science.gov (United States)

    Zhu, He; Ma, Jing

    2018-03-01

    In this article, based on a model of epidemic spreading, we explore the knowledge diffusion process with an innovative mechanism for complex networks by considering time-varying information channels. To cover the knowledge diffusion process in homogeneous and heterogeneous networks, two types of networks (the BA network and the ER network) are investigated. The mean-field theory is used to theoretically draw the knowledge diffusion threshold. Numerical simulation demonstrates that the knowledge diffusion threshold is almost linearly correlated with the mean of the activity rate. In addition, under the influence of the activity rate and distinct from the classic Susceptible-Infected-Susceptible (SIS) model, the density of knowers almost linearly grows with the spreading rate. Finally, in consideration of the ubiquitous mechanism of innovation, we further study the evolution of knowledge in our proposed model. The results suggest that compared with the effect of the spreading rate, the average knowledge version of the population is affected more by the innovation parameter and the mean of the activity rate. Furthermore, in the BA network, the average knowledge version of individuals with higher degree is always newer than those with lower degree.

  13. The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow

    Directory of Open Access Journals (Sweden)

    Yin Tian

    2018-04-01

    Full Text Available Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG references, namely, AR (average of all recording channels and reference electrode standardization technique (REST, were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

  14. Multistability and instability analysis of recurrent neural networks with time-varying delays.

    Science.gov (United States)

    Zhang, Fanghai; Zeng, Zhigang

    2018-01-01

    This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Sex differences in in-group cooperation vary dynamically with competitive conditions and outcomes.

    Science.gov (United States)

    Bailey, Drew H; Winegard, Benjamin; Oxford, Jon; Geary, David C

    2012-03-18

    Men's but not women's investment in a public goods game varied dynamically with the presence or absence of a perceived out-group. Three hundred fifty-four (167 male) young adults participated in multiple iterations of a public goods game under intergroup and individual competition conditions. Participants received feedback about whether their investments in the group were sufficient to earn a bonus to be shared among all in-group members. Results for the first trial confirm previous research in which men's but not women's investments were higher when there was a competing out-group. We extended these findings by showing that men's investment in the in-group varied dynamically by condition depending on the outcome of the previous trial: In the group condition, men, but not women, decreased spending following a win (i.e., earning an in-group bonus). In the individual condition, men, but not women, increased spending following a win. We hypothesize that these patterns reflect a male bias to calibrate their level of in-group investment such that they sacrifice only what is necessary for their group to successfully compete against a rival group.

  16. Sex Differences in In-Group Cooperation Vary Dynamically with Competitive Conditions and Outcomes

    Directory of Open Access Journals (Sweden)

    Drew H. Bailey

    2012-01-01

    Full Text Available Men's but not women's investment in a public goods game varied dynamically with the presence or absence of a perceived out-group. Three hundred fifty-four (167 male young adults participated in multiple iterations of a public goods game under intergroup and individual competition conditions. Participants received feedback about whether their investments in the group were sufficient to earn a bonus to be shared among all in-group members. Results for the first trial confirm previous research in which men's but not women's investments were higher when there was a competing out-group. We extended these findings by showing that men's investment in the in-group varied dynamically by condition depending on the outcome of the previous trial: In the group condition, men, but not women, decreased spending following a win (i.e., earning an in-group bonus. In the individual condition, men, but not women, increased spending following a win. We hypothesize that these patterns reflect a male bias to calibrate their level of in-group investment such that they sacrifice only what is necessary for their group to successfully compete against a rival group.

  17. The effect of varying talker identity and listening conditions on gaze behavior during audiovisual speech perception.

    Science.gov (United States)

    Buchan, Julie N; Paré, Martin; Munhall, Kevin G

    2008-11-25

    During face-to-face conversation the face provides auditory and visual linguistic information, and also conveys information about the identity of the speaker. This study investigated behavioral strategies involved in gathering visual information while watching talking faces. The effects of varying talker identity and varying the intelligibility of speech (by adding acoustic noise) on gaze behavior were measured with an eyetracker. Varying the intelligibility of the speech by adding noise had a noticeable effect on the location and duration of fixations. When noise was present subjects adopted a vantage point that was more centralized on the face by reducing the frequency of the fixations on the eyes and mouth and lengthening the duration of their gaze fixations on the nose and mouth. Varying talker identity resulted in a more modest change in gaze behavior that was modulated by the intelligibility of the speech. Although subjects generally used similar strategies to extract visual information in both talker variability conditions, when noise was absent there were more fixations on the mouth when viewing a different talker every trial as opposed to the same talker every trial. These findings provide a useful baseline for studies examining gaze behavior during audiovisual speech perception and perception of dynamic faces.

  18. Understanding and simulating vibrations of plain bridge cables under varying meteorological conditions

    DEFF Research Database (Denmark)

    Matteoni, Giulia

    amplitude peak to peak amplitudes, occurred. This latter behaviour was likely to be associated to dry inclined galloping. Passive dynamic wind tunnel tests were finally undertaken in presence of rain, using the same cable model as adopted in the dry state. The tests served to improve the current......The dissertation investigates the phenomenon of wind induced vibration of bridge cables under varying meteorological conditions. A twin research approach is adopted, where wind tunnel investigation of full-scale bridge cable section models is paralleled with theoretical modelling. A literature......-scale monitoring, wind tunnel testing and theoretical modelling. An extensive wind tunnel test campaign was then undertaken in order to further understand the onset conditions and characteristics of instability in the different climatic conditions described in the literature. Tests were separated into two...

  19. Differences in displayed pump flow compared to measured flow under varying conditions during simulated cardiopulmonary bypass.

    LENUS (Irish Health Repository)

    Hargrove, M

    2008-07-01

    Errors in blood flow delivery due to shunting have been reported to reduce flow by, potentially, up to 40-83% during cardiopulmonary bypass. The standard roller-pump measures revolutions per minute and a calibration factor for different tubing sizes calculates and displays flow accordingly. We compared displayed roller-pump flow with ultrasonically measured flow to ascertain if measured flow correlated with the heart-lung pump flow reading. Comparison of flows was measured under varying conditions of pump run duration, temperature, viscosity, varying arterial\\/venous loops, occlusiveness, outlet pressure, use of silicone or polyvinyl chloride (PVC) in the roller race, different tubing diameters, and use of a venous vacuum-drainage device.

  20. State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

    International Nuclear Information System (INIS)

    Lakshmanan, S.; Park, Ju H.; Jung, H. Y.; Balasubramaniam, P.

    2012-01-01

    This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed time-varying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov—Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages

  1. An in vitro experimental study of flow past aortic valve under varied pulsatile conditions

    Science.gov (United States)

    Zhang, Ruihang; Zhang, Yan

    2017-11-01

    Flow past aortic valve represents a complex fluid-structure interaction phenomenon that involves pulsatile, vortical, and turbulent conditions. The flow characteristics immediately downstream of the valve, such as the variation of pulsatile flow velocity, formation of vortices, distribution of shear stresses, are of particular interest to further elucidate the role of hemodynamics in various aortic diseases. However, the fluid dynamics of a realistic aortic valve is not fully understood. Particularly, it is unclear how the flow fields downstream of the aortic valve would change under varied pulsatile inlet boundary conditions. In this study, an in vitro experiment has been conducted to investigate the flow fields downstream of a silicone aortic valve model within a cardiovascular flow simulator. Phased-locked Particle Image Velocimetry measurements were performed to map the velocity fields and Reynolds normal and shear stresses at different phases in a cardiac cycle. Temporal variations of pressure across the valve model were measured using high frequency transducers. Results have been compared for different pulsatile inlet conditions, including varied frequencies (heart rates), magnitudes (stroke volumes), and cardiac contractile functions (shapes of waveforms).

  2. New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

    Directory of Open Access Journals (Sweden)

    YaJun Li

    2015-01-01

    Full Text Available The passivity problem for a class of stochastic neural networks systems (SNNs with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix approach, and combining with integral inequality technic and stochastic analysis theory, the delay-dependent conditions have been proposed such that SNNs are asymptotically stable with guaranteed performance. The time-varying delay is divided into several subintervals and two adjustable parameters are introduced; more information about time delay is utilised and less conservative results have been obtained. Examples are provided to illustrate the less conservatism of the proposed method and simulations are given to show the impact of leakage delay on stability of SNNs.

  3. Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

    Science.gov (United States)

    Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

    2018-01-01

    Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

  4. Applicability of common stomatal conductance models in maize under varying soil moisture conditions.

    Science.gov (United States)

    Wang, Qiuling; He, Qijin; Zhou, Guangsheng

    2018-07-01

    In the context of climate warming, the varying soil moisture caused by precipitation pattern change will affect the applicability of stomatal conductance models, thereby affecting the simulation accuracy of carbon-nitrogen-water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a soil moisture consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying soil moisture conditions. The effects of soil moisture made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of soil relative water content (i.e., 55%-65%, 56%-67%, 37%-79% and 37%-95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying soil moisture conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Modelling of the diffusion of pollutants in the atmosphere under varying conditions in large cultivated regions

    International Nuclear Information System (INIS)

    Wueneke, C.D.; Schultz, H.

    1975-01-01

    The most important routines of a numerical code based on the particle-in-cell-method for calculating the transport and the turbulent dispersion of inert and radio-active pollutants in the atmosphere have been programmed and have been tested successfully on the CDC computer CYBER 73/76 of the Regional Computer Centre for Niedersachsen in Hanover. Compared to the Gaussian plume model such a numerical code based on the particle-in-cell-method offers several advantages for the computation of the diffusion under varying conditions in large cultivated regions. (orig.) [de

  6. Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

    Science.gov (United States)

    Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

    2018-03-01

    In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

  7. Synchronization of Reaction-Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays.

    Science.gov (United States)

    Sheng, Yin; Zhang, Hao; Zeng, Zhigang

    2017-10-01

    This paper is concerned with synchronization for a class of reaction-diffusion neural networks with Dirichlet boundary conditions and infinite discrete time-varying delays. By utilizing theories of partial differential equations, Green's formula, inequality techniques, and the concept of comparison, algebraic criteria are presented to guarantee master-slave synchronization of the underlying reaction-diffusion neural networks via a designed controller. Additionally, sufficient conditions on exponential synchronization of reaction-diffusion neural networks with finite time-varying delays are established. The proposed criteria herein enhance and generalize some published ones. Three numerical examples are presented to substantiate the validity and merits of the obtained theoretical results.

  8. A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2018-01-01

    In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

  9. A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

    KAUST Repository

    Rached, Nadhir B.

    2018-01-11

    In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

  10. Positive and negative variations in capacitive images for given defects under varying experimental conditions

    Science.gov (United States)

    Li, Chen; Yin, Xiaokang; Li, Zhen; Li, Wei; Chen, Guoming

    2018-04-01

    Capacitive imaging (CI) technique is a novel electromagnetic NDE technique. The Quasi-static electromagnetic field from the carefully designed electrode pair will vary when the electrical properties of the sample change, leading to the possibility of imaging. It is observed that for a given specimen, the targeted features appear as different variations in capacitive images under different experimental conditions. In some cases, even opposite variations occur, which brings confusion to indication interpretation. It is thus thought interesting to embark on investigations into the cause and effects of the negative variation phenomenon. In this work, the positive and negative variations were first explained from the measurement sensitivity distribution perspective. This was then followed by a detailed analysis using finite element models in COMSOL. A parametric experimental study on a glass fiber composite plate with artificial defects was then carried out to investigate how the experimental conditions affect the variation.

  11. Feedback topology and XOR-dynamics in Boolean networks with varying input structure

    Science.gov (United States)

    Ciandrini, L.; Maffi, C.; Motta, A.; Bassetti, B.; Cosentino Lagomarsino, M.

    2009-08-01

    We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter γ . We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying γ , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.

  12. Feedback topology and XOR-dynamics in Boolean networks with varying input structure.

    Science.gov (United States)

    Ciandrini, L; Maffi, C; Motta, A; Bassetti, B; Cosentino Lagomarsino, M

    2009-08-01

    We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.

  13. H∞ Control for a Networked Control Model of Systems with Two Additive Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Hanyong Shao

    2014-01-01

    Full Text Available This paper is concerned with H∞ control for a networked control model of systems with two additive time-varying delays. A new Lyapunov functional is constructed to make full use of the information of the delays, and for the derivative of the Lyapunov functional a novel technique is employed to compute a tighter upper bound, which is dependent on the two time-varying delays instead of the upper bounds of them. Then the convex polyhedron method is proposed to check the upper bound of the derivative of the Lyapunov functional. The resulting stability criteria have fewer matrix variables but less conservatism than some existing ones. The stability criteria are applied to designing a state feedback controller, which guarantees that the closed-loop system is asymptotically stable with a prescribed H∞ disturbance attenuation level. Finally examples are given to show the advantages of the stability criteria and the effectiveness of the proposed control method.

  14. A receding horizon scheme for discrete-time polytopic linear parameter varying systems in networked architectures

    International Nuclear Information System (INIS)

    Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

    2014-01-01

    This paper proposes a Model Predictive Control (MPC) strategy to address regulation problems for constrained polytopic Linear Parameter Varying (LPV) systems subject to input and state constraints in which both plant measurements and command signals in the loop are sent through communication channels subject to time-varying delays (Networked Control System (NCS)). The results here proposed represent a significant extension to the LPV framework of a recent Receding Horizon Control (RHC) scheme developed for the so-called robust case. By exploiting the parameter availability, the pre-computed sequences of one- step controllable sets inner approximations are less conservative than the robust counterpart. The resulting framework guarantees asymptotic stability and constraints fulfilment regardless of plant uncertainties and time-delay occurrences. Finally, experimental results on a laboratory two-tank test-bed show the effectiveness of the proposed approach

  15. Assessment of a surface-layer parameterization scheme in an atmospheric model for varying meteorological conditions

    Directory of Open Access Journals (Sweden)

    T. J. Anurose

    2014-06-01

    Full Text Available The performance of a surface-layer parameterization scheme in a high-resolution regional model (HRM is carried out by comparing the model-simulated sensible heat flux (H with the concurrent in situ measurements recorded at Thiruvananthapuram (8.5° N, 76.9° E, a coastal station in India. With a view to examining the role of atmospheric stability in conjunction with the roughness lengths in the determination of heat exchange coefficient (CH and H for varying meteorological conditions, the model simulations are repeated by assigning different values to the ratio of momentum and thermal roughness lengths (i.e. z0m/z0h in three distinct configurations of the surface-layer scheme designed for the present study. These three configurations resulted in differential behaviour for the varying meteorological conditions, which is attributed to the sensitivity of CH to the bulk Richardson number (RiB under extremely unstable, near-neutral and stable stratification of the atmosphere.

  16. Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Wenbing [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Wang, Zidong [Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH (United Kingdom); Liu, Yurong, E-mail: yrliu@yzu.edu.cn [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia); Ding, Derui [Shanghai Key Lab of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093 (China); Alsaadi, Fuad E. [Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia)

    2017-01-05

    The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator. - Highlights: • An event-triggered estimator is designed for complex networks with time-varying delays. • A novel event generator function is proposed to reduce the communication burden. • The comparison principle is utilized to derive the sufficient conditions. • The designed triggering condition is shown to be free of the Zeno behavior.

  17. Analysis of grain filling process to the varied meteorological conditions in winter wheat [Triticum aestivum] cultivars

    International Nuclear Information System (INIS)

    Inoue, K.; Nakazono, K.; Wakiyama, Y.

    2005-01-01

    This paper describes effects of varied meteorological conditions on the grain filling periods, stabilities of yield and quality of winter wheat cultivars with different maturity characteristics (cv. Ayahikari, Norin61, Bandowase, and Tsurupikari). In the field experiments, the meteorological treatments were made during the first heading time on 17 April 2001 and the middle heading time on 24 April 2000. Air temperature, global solar radiation and soil moisture were controlled using a rain shelter, cheesecloth and irrigation system. The growth speed and growth period of wheat grains varied among four winter wheat cultivars, depending on meteorological conditions. The growth speed increased within 1 8.4 deg C of mean air temperature over the 30 days after the anthesis. On the other hand, it was found that the growth speed of wheat grains and the maximum number of wheat grains (Ymax) decreased greatly with the 44.4% interception of global solar radiation. Logistic functions were fitted to the relationship between the relative thousand-kernel-weight (Y/Ymax) and the total integrated temperature (sigmaTa) after heading for all treatment conditions. The maximum weight of grains (Ymax) achieved at the harvest time varied somewhat clearly among four winter wheat cultivars and meteorological conditions. Multiple regression analysis showed that the grain yield (Ymax) of four wheat cultivars correlated positively with daily mean solar radiation. It was also found that the cultivar Ayahikari had a highly significant negative correlation between its grain weight and soil moisture. Namely, the grain weight of high soil moisture plot with pF=1.5 was lower by about 9% than that of a control plot with pF=3.5. On the other hand, the grain yield of cultivar Norin61 responded inversely to a wet environment, indicating that its grain weight was higher for high soil moisture and high wet-bulb temperature than for a dry environment. The grain yield of early varieties of Bandowase and

  18. A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Song, Qiankun; Wang, Zidong

    2007-01-01

    In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate Lyapunov-Krasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria

  19. A normalized PID controller in networked control systems with varying time delays.

    Science.gov (United States)

    Tran, Hoang-Dung; Guan, Zhi-Hong; Dang, Xuan-Kien; Cheng, Xin-Ming; Yuan, Fu-Shun

    2013-09-01

    It requires not only simplicity and flexibility but also high specified stability and robustness of system to design a PI/PID controller in such complicated networked control systems (NCSs) with delays. By gain and phase margins approach, this paper proposes a novel normalized PI/PID controller for NCSs based on analyzing the stability and robustness of system under the effect of network-induced delays. Specifically, We take into account the total measured network delays to formulate the gain and phase margins of the closed-loop system in the form of a set of equations. With pre-specified values of gain and phase margins, this set of equations is then solved for calculating the closed forms of control parameters which enable us to propose the normalized PI/PID controller simultaneously satisfying the following two requirements: (1) simplicity without re-solving the optimization problem for a new process, (2) high flexibility to cope with large scale of random delays and deal with many different processes in different conditions of network. Furthermore, in our method, the upper bound of random delay can be estimated to indicate the operating domain of proposed PI/PID controller. Finally, simulation results are shown to demonstrate the advantages of our proposed controller in many situations of network-induced delays. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Mapping and simulating systematics due to spatially varying observing conditions in DES science verification data

    International Nuclear Information System (INIS)

    Leistedt, B.; Peiris, H. V.; Elsner, F.; Benoit-Lévy, A.; Amara, A.

    2016-01-01

    Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES–SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES–SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. Finally, the framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high

  1. Dynamics of a class of cellular neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Huang Lihong; Huang Chuangxia; Liu Bingwen

    2005-01-01

    Employing Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis, the authors make a further investigation of a class of cellular neural networks with delays (DCNNs) in this Letter. A family of sufficient conditions are given for checking global exponential stability and the existence of periodic solutions of DCNNs. These results have important leading significance in the design and applications of globally stable DCNNs and periodic oscillatory DCNNs. Our results extend and improve some earlier publications

  2. Dimensionality-varied convolutional neural network for spectral-spatial classification of hyperspectral data

    Science.gov (United States)

    Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

    2017-11-01

    Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

  3. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon

    2013-10-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing algorithms, such as Monte Carlo maximum likelihood estimation (MCMLE) and stochastic approximation, often fail for this problem in the presence of model degeneracy. In this article, we introduce the varying truncation stochastic approximation Markov chain Monte Carlo (SAMCMC) algorithm to tackle this problem. The varying truncation mechanism enables the algorithm to choose an appropriate starting point and an appropriate gain factor sequence, and thus to produce a reasonable parameter estimate for the ERGM even in the presence of model degeneracy. The numerical results indicate that the varying truncation SAMCMC algorithm can significantly outperform the MCMLE and stochastic approximation algorithms: for degenerate ERGMs, MCMLE and stochastic approximation often fail to produce any reasonable parameter estimates, while SAMCMC can do; for nondegenerate ERGMs, SAMCMC can work as well as or better than MCMLE and stochastic approximation. The data and source codes used for this article are available online as supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  4. A delay-dependent approach to robust control for neutral uncertain neural networks with mixed interval time-varying delays

    International Nuclear Information System (INIS)

    Lu, Chien-Yu

    2011-01-01

    This paper considers the problem of delay-dependent global robust stabilization for discrete, distributed and neutral interval time-varying delayed neural networks described by nonlinear delay differential equations of the neutral type. The parameter uncertainties are norm bounded. The activation functions are assumed to be bounded and globally Lipschitz continuous. Using a Lyapunov functional approach and linear matrix inequality (LMI) techniques, the stability criteria for the uncertain neutral neural networks with interval time-varying delays are established in the form of LMIs, which can be readily verified using the standard numerical software. An important feature of the result reported is that all the stability conditions are dependent on the upper and lower bounds of the delays. Another feature of the results lies in that it involves fewer free weighting matrix strategy, and upper bounds of the inner product between two vectors are not introduced to reduce the conservatism of the criteria. Two illustrative examples are provided to demonstrate the effectiveness and the reduced conservatism of the proposed method

  5. Detection and classification of alarm threshold violations in condition monitoring systems working in highly varying operational conditions

    Science.gov (United States)

    Strączkiewicz, M.; Barszcz, T.; Jabłoński, A.

    2015-07-01

    All commonly used condition monitoring systems (CMS) enable defining alarm thresholds that enhance efficient surveillance and maintenance of dynamic state of machinery. The thresholds are imposed on the measured values such as vibration-based indicators, temperature, pressure, etc. For complex machinery such as wind turbine (WT) the total number of thresholds might be counted in hundreds multiplied by the number of operational states. All the parameters vary not only due to possible machinery malfunctions, but also due to changes in operating conditions and these changes are typically much stronger than the former ones. Very often, such a behavior may lead to hundreds of false alarms. Therefore, authors propose a novel approach based on parameterized description of the threshold violation. For this purpose the novelty and severity factors are introduced. The first parameter refers to the time of violation occurrence while the second one describes the impact of the indicator-increase to the entire machine. Such approach increases reliability of the CMS by providing the operator with the most useful information of the system events. The idea of the procedure is presented on a simulated data similar to those from a wind turbine.

  6. Detection and classification of alarm threshold violations in condition monitoring systems working in highly varying operational conditions

    International Nuclear Information System (INIS)

    Strączkiewicz, M; Barszcz, T; Jabłoński, A

    2015-01-01

    All commonly used condition monitoring systems (CMS) enable defining alarm thresholds that enhance efficient surveillance and maintenance of dynamic state of machinery. The thresholds are imposed on the measured values such as vibration-based indicators, temperature, pressure, etc. For complex machinery such as wind turbine (WT) the total number of thresholds might be counted in hundreds multiplied by the number of operational states. All the parameters vary not only due to possible machinery malfunctions, but also due to changes in operating conditions and these changes are typically much stronger than the former ones. Very often, such a behavior may lead to hundreds of false alarms. Therefore, authors propose a novel approach based on parameterized description of the threshold violation. For this purpose the novelty and severity factors are introduced. The first parameter refers to the time of violation occurrence while the second one describes the impact of the indicator-increase to the entire machine. Such approach increases reliability of the CMS by providing the operator with the most useful information of the system events. The idea of the procedure is presented on a simulated data similar to those from a wind turbine. (paper)

  7. Building GSM network in extreme conditions

    Science.gov (United States)

    Mikulec, M.; Voznak, M.; Fajkus, M.; Partila, P.; Tovarek, J.; Chmelikova, Z.

    2015-05-01

    The paper is focused on the building ad-hoc GSM network based on open source software and low-cost hardware. The created Base Transmission Station can be deployed and put into operation in a few minutes in a required area to ensure private communication between connected GSM mobile terminals. The convergence between BTS station and the other networks is possible through IP network. The paper tries to define connection parameters to provide sufficient quality of voice service between the GSM network and IP Multimedia Subsystem. The paper brings practical results of voice call quality measurement between users inside BTS station mobile network and users inside IP Multimedia Subsystem network. The calls are simulated by low-cost embedded solution for speech quality measurement in GSM network. This tool is under development of our laboratory and allows automatic speech quality measurement of any GSM or UMTS mobile network. The Perceptual Evaluation of Speech Quality method is used to get final comparable results. The communication between BTS station and connected networks has to be secured against the interception from the third party. The influence of the securing method for quality of service is presented in detail. Paper, apart from the quality of service measurement section, describes technical requirements for successful interconnection between BTS and IMS networks. The authentication, authorization and accounting methods in roaming between BTS and IMS system are presented too.

  8. Risky behavior and its effect on survival: snowshoe hare behavior under varying moonlight conditions

    Science.gov (United States)

    Gigliotti, Laura C.; Diefenbach, Duane R.

    2018-01-01

    Predation and predation risk can exert strong influences on the behavior of prey species. However, risk avoidance behaviors may vary among populations of the same species. We studied a population of snowshoe hares (Lepus americanus) near the southern edge of their range, in Pennsylvania. This population occupies different habitat types, experiences different environmental conditions, and are exposed to different predator species and densities than northern hare populations; therefore, they might exhibit differences in risk avoidance behaviors. We analyzed hare survival, movement rates, and habitat use under different levels of predation risk, as indexed by moonlight. Similar to previous work, we found snowshoe hare survival decreased with increased moon illumination during the winter, but we found differences in behavioral responses to increased predation risk. We found that snowshoe hares did not reduce movement rates during high‐risk nights, but instead found that hares selected areas with denser canopy cover, compared to low‐risk nights. We suggest that behavioral plasticity in response to predation risk allows populations of the same species to respond to localized conditions.

  9. PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

    Science.gov (United States)

    Csaszar, Elizabeth; Yu, Mei; Morris, Quaid; Zandstra, Peter W.

    2012-01-01

    The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity. PMID:23284283

  10. Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions

    Science.gov (United States)

    Liu, Dedi; Guo, Shenglian; Shao, Quanxi; Liu, Pan; Xiong, Lihua; Wang, Le; Hong, Xingjun; Xu, Yao; Wang, Zhaoli

    2018-01-01

    Human activities and climate change have altered the spatial and temporal distribution of water availability which is a principal prerequisite for allocation of different water resources. In order to quantify the impacts of climate change and human activities on water availability and optimal allocation of water resources, hydrological models and optimal water resource allocation models should be integrated. Given that increasing human water demand and varying water availability conditions necessitate adaptation measures, we propose a framework to assess the effects of these measures on optimal allocation of water resources. The proposed model and framework were applied to a case study of the middle and lower reaches of the Hanjiang River Basin in China. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) were employed to project future climate, and the Variable Infiltration Capacity (VIC) hydrological model was used to simulate the variability of flows under historical (1956-2011) and future (2012-2099) conditions. The water availability determined by simulating flow with the VIC hydrological model was used to establish the optimal water resources allocation model. The allocation results were derived under an extremely dry year (with an annual average water flow frequency of 95%), a very dry year (with an annual average water flow frequency of 90%), a dry year (with an annual average water flow frequency of 75%), and a normal year (with an annual average water flow frequency of 50%) during historical and future periods. The results show that the total available water resources in the study area and the inflow of the Danjiangkou Reservoir will increase in the future. However, the uneven distribution of water availability will cause water shortage problems, especially in the boundary areas. The effects of adaptation measures, including water saving, and dynamic control of flood limiting water levels (FLWLs) for reservoir operation, were

  11. Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks

    Science.gov (United States)

    St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.

    2018-02-01

    We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.

  12. Impact of Interference in Coexisting Wireless Networks with Applications to Arbitrarily Varying Bidirectional Broadcast Channels

    Directory of Open Access Journals (Sweden)

    Holger Boche

    2012-08-01

    Full Text Available The paradigm shift from an exclusive allocation of frequency bands, one for each system, to a shared use of frequencies comes along with the need of new concepts since interference will be an ubiquitous phenomenon. In this paper, we use the concept of arbitrarily varying channels to model the impact of unknown interference caused by coexisting wireless systems which operate on the same frequencies. Within this framework, capacity can be zero if pre-specified encoders and decoders are used. This necessitates the use of more sophisticated coordination schemes where the choice of encoders and decoders is additionally coordinated based on common randomness. As an application we study the arbitrarily varying bidirectional broadcast channel and derive the capacity regions for different coordination strategies. This problem is motivated by decode-and-forward bidirectional or two-way relaying, where a relay establishes a bidirectional communication between two other nodes while sharing the resources with other coexisting wireless networks.

  13. Estimating Conditional Distributions by Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1998-01-01

    Neural Networks for estimating conditionaldistributions and their associated quantiles are investigated in this paper. A basic network structure is developed on the basis of kernel estimation theory, and consistency property is considered from a mild set of assumptions. A number of applications...

  14. MPE inference in conditional linear gaussian networks

    DEFF Research Database (Denmark)

    Salmerón, Antonio; Rumí, Rafael; Langseth, Helge

    2015-01-01

    Given evidence on a set of variables in a Bayesian network, the most probable explanation (MPE) is the problem of finding a configuration of the remaining variables with maximum posterior probability. This problem has previously been addressed for discrete Bayesian networks and can be solved using...

  15. Projective synchronization of time-varying delayed neural network with adaptive scaling factors

    International Nuclear Information System (INIS)

    Ghosh, Dibakar; Banerjee, Santo

    2013-01-01

    Highlights: • Projective synchronization in coupled delayed neural chaotic systems with modulated delay time is introduced. • An adaptive rule for the scaling factors is introduced. • This scheme is highly applicable in secure communication. -- Abstract: In this work, the projective synchronization between two continuous time delayed neural systems with time varying delay is investigated. A sufficient condition for synchronization for the coupled systems with modulated delay is presented analytically with the help of the Krasovskii–Lyapunov approach. The effect of adaptive scaling factors on synchronization are also studied in details. Numerical simulations verify the effectiveness of the analytic results

  16. Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Xing Yin

    2011-01-01

    uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF and free-weighting matrix approach (FWM, some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria.

  17. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    OpenAIRE

    Wei Feng; Simon X. Yang; Haixia Wu

    2014-01-01

    The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported ...

  18. Phytoremdiation Species And Their Modification Under By Weed Varying Climatic Condition A Changing Scenario

    Directory of Open Access Journals (Sweden)

    Anita Singh

    2015-08-01

    Full Text Available Abstract The major reasons for environmental contamination are population explosion increase in industrial and other urban activities. One of the consequent effect of these activities is heavy metal pollution. It is one of the serious issue to be discussed by the scientists and academicians that how to solve this problem to protect the environment. As heavy metals are non-biodegradable so they require effective cleanup technology. Most of the traditional methods such as excavation solidification and burial are very costly or they simply involve the isolation of the metals from contaminated sites. Among different technologies phytoremediation is best approach for removing metal contamination from environment. It involves plants to remove detoxify or immobilize metals from environment. Weed plants are found to be play very important role in metal remediation. They get affected by climatic variation which is also a consequent effect of environmental pollution. The physiology of plants as well as physiochemical properties of soil gets affected by varying climatic condition. Therefore the present review gives the information on metal remediation processes and how these process particularly phytoremediation by weed plants get affected by climatic changes.

  19. Asymmetric Vibration of Polar Orthotropic Annular Circular Plates of Quadratically Varying Thickness with Same Boundary Conditions

    Directory of Open Access Journals (Sweden)

    N. Bhardwaj

    2008-01-01

    Full Text Available In the present paper, asymmetric vibration of polar orthotropic annular circular plates of quadratically varying thickness resting on Winkler elastic foundation is studied by using boundary characteristic orthonormal polynomials in Rayleigh-Ritz method. Convergence of the results is tested and comparison is made with results already available in the existing literature. Numerical results for the first ten frequencies for various values of parameters describing width of annular plate, thickness profile, material orthotropy and foundation constant for all three possible combinations of clamped, simply supported and free edge conditions are shown and discussed. It is found that (a higher elastic property in circumferential direction leads to higher stiffness against lateral vibration; (b Lateral vibration characteristics of F-Fplates is more sensitive towards parametric changes in material orthotropy and foundation stiffness than C-C and S-Splates; (c Effect of quadratical thickness variation on fundamental frequency is more significant in cases of C-C and S-S plates than that of F-Fplates. Thickness profile which is convex relative to plate center-line tends to result in higher stiffness of annular plates against lateral vibration than the one which is concave and (d Fundamental mode of vibration of C-C and S-Splates is axisymmetrical while that of F-Fplates is asymmetrical.

  20. The influence of spatially and temporally varying oceanographic conditions on meroplanktonic metapopulations

    Science.gov (United States)

    Botsford, L. W.; Moloney, C. L.; Hastings, A.; Largier, J. L.; Powell, T. M.; Higgins, K.; Quinn, J. F.

    We synthesize the results of several modelling studies that address the influence of variability in larval transport and survival on the dynamics of marine metapopulations distributed along a coast. Two important benthic invertebrates in the California Current System (CCS), the Dungeness crab and the red sea urchin, are used as examples of the way in which physical oceanographic conditions can influence stability, synchrony and persistence of meroplanktonic metapopulations. We first explore population dynamics of subpopulations and metapopulations. Even without environmental forcing, isolated local subpopulations with density-dependence can vary on time scales roughly twice the generation time at high adult survival, shifting to annual time scales at low survivals. The high frequency behavior is not seen in models of the Dungeness crab, because of their high adult survival rates. Metapopulations with density-dependent recruitment and deterministic larval dispersal fluctuate in an asynchronous fashion. Along the coast, abundance varies on spatial scales which increase with dispersal distance. Coastwide, synchronous, random environmental variability tends to synchronize these metapopulations. Climate change could cause a long-term increase or decrease in mean larval survival, which in this model leads to greater synchrony or extinction respectively. Spatially managed metapopulations of red sea urchins go extinct when distances between harvest refugia become greater than the scale of larval dispersal. All assessments of population dynamics indicate that metapopulation behavior in general dependes critically on the temporal and spatial nature of larval dispersal, which is largely determined by physical oceanographic conditions. We therfore explore physical influences on larval dispersal patterns. Observed trends in temperature and salinity applied to laboratory-determined responses indicate that natural variability in temperature and salinity can lead to variability in

  1. Effect of Varying Acid Hydrolysis Condition in Gracilaria Sp. Fermentation Using Sasad

    Science.gov (United States)

    Mansuit, H.; Samsuri, M. D. C.; Sipaut, C. S.; Yee, C. F.; Yasir, S. M.; Mansa, R.

    2015-04-01

    Macroalgae or seaweed is being considered as promising feedstock for bioalcohol production due to high polysaccharides content. Polysaccharides can be converted into fermentable sugar through acid hydrolysis pre-treatment. In this study, the potential of using carbohydrate-rich macroalgae, Gracilaria sp. as feedstock for bioalcohol production via various acid hydrolysis conditions prior to the fermentation process was investigated and evaluated. The seaweed used in this research was from the red algae group, using species of Gracilaria sp. which was collected from Sg. Petani Kedah, Malaysia. Pre-treatment of substrate was done using H2SO4 and HCl with molarity ranging from 0.2M to 0.8M. The pretreatment time were varied in the range of 15 to 30 minutes. Fermentation was conducted using Sasad, a local Sabahan fermentation agent as a starter culture. Alcohol extraction was done using a distillation unit. Reducing sugar analysis was done by Benedict test method. Alcohol content analysis was done using specific gravity test. After hydrolysis, it was found out that acid hydrolysis at 0.2M H2SO4 and pre-treated for 20 minutes at 121°C has shown the highest reducing sugar content which has yield (10.06 mg/g) of reducing sugar. It was followed by other samples hydrolysis using 0.4M HCl with 30 minutes pre-treatment and 0.2M H2SO4, 15 minutes pre-treatment with yield of 8.06 mg/g and 5.75 mg/g reducing sugar content respectively. In conclusion, acid hydrolysis of Gracilaria sp. can produce higher reducing sugar yield and thus it can further enhance the bioalcohol production yield. Hence, acid hydrolysis of Gracilaria sp. should be studied more as it is an important step in the bioalcohol production and upscaling process.

  2. Global Robust Stability of Switched Interval Neural Networks with Discrete and Distributed Time-Varying Delays of Neural Type

    Directory of Open Access Journals (Sweden)

    Huaiqin Wu

    2012-01-01

    Full Text Available By combing the theories of the switched systems and the interval neural networks, the mathematics model of the switched interval neural networks with discrete and distributed time-varying delays of neural type is presented. A set of the interval parameter uncertainty neural networks with discrete and distributed time-varying delays of neural type are used as the individual subsystem, and an arbitrary switching rule is assumed to coordinate the switching between these networks. By applying the augmented Lyapunov-Krasovskii functional approach and linear matrix inequality (LMI techniques, a delay-dependent criterion is achieved to ensure to such switched interval neural networks to be globally asymptotically robustly stable in terms of LMIs. The unknown gain matrix is determined by solving this delay-dependent LMIs. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.

  3. Multi-Fibre Optode Microsensors: affordable designs for monitoring oxygen in soils under varying environmental conditions

    Science.gov (United States)

    Rezanezhad, F.; Milojevic, T.; Parsons, C. T.; Smeaton, C. M.; Van Cappellen, P.

    2017-12-01

    , where the imaged data is transmitted remotely using a photo-logging system. The MuFO sensor is currently being tested at a Southern Ontario field site in a year-long experiment. Here we present the field and laboratory results of soil O2 monitoring by this newly developed MuFO microsensor system under varying environmental conditions.

  4. Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

    OpenAIRE

    Jalalifar, Seyed Ali; Hasani, Hosein; Aghajan, Hamid

    2018-01-01

    We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track.

  5. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    Science.gov (United States)

    Hwang, Chih-Lyang; Jan, Chau

    2016-02-01

    At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

  6. Synchronization of coupled stochastic complex-valued dynamical networks with time-varying delays via aperiodically intermittent adaptive control

    Science.gov (United States)

    Wang, Pengfei; Jin, Wei; Su, Huan

    2018-04-01

    This paper deals with the synchronization problem of a class of coupled stochastic complex-valued drive-response networks with time-varying delays via aperiodically intermittent adaptive control. Different from the previous works, the intermittent control is aperiodic and adaptive, and the restrictions on the control width and time delay are removed, which lead to a larger application scope for this control strategy. Then, based on the Lyapunov method and Kirchhoff's Matrix Tree Theorem as well as differential inequality techniques, several novel synchronization conditions are derived for the considered model. Specially, impulsive control is also considered, which can be seen as a special case of the aperiodically intermittent control when the control width tends to zero. And the corresponding synchronization criteria are given as well. As an application of the theoretical results, a class of stochastic complex-valued coupled oscillators with time-varying delays is studied, and the numerical simulations are also given to demonstrate the effectiveness of the control strategies.

  7. Attenuation of organic micropollutants in an urban lowland stream under varying seasonal and hydrological conditions

    Science.gov (United States)

    Jaeger, Anna; Posselt, Malte; Schaper, Jonas; Lewandowski, Jörg

    2017-04-01

    Transport and fate of polar organic micropollutants in urban streams are of increasing concern for urban water management. Appropriate river management techniques may support a river's ability to self-purify. The river Erpe, an urban lowland stream located in Berlin, Germany, receives treated wastewater which increases its discharge up to 4-fold. Numerous micropollutants (e.g. pharmaceuticals, personal care products, performance chemicals) which survive the treatment process are released into the river and threaten ecosystems and aquatic groundwater quality. In the present work the transport of 57 substances was investigated along a 4.7 km stretch of the river with the aim of understanding the influence of varying seasonal and hydrological conditions on micropollutant fate. We hypothesized that particularly transient storage is a main driver of micropollutant attenuation. A Lagrangian sampling scheme was applied to follow water parcels down the river using the diurnal fluctuations of conservative solute concentrations as an intrinsic tracer. Water samples were collected at two (April) and three (June) stations along a 4.7 km reach downstream of the wastewater inflow. In June the experiment was conducted twice, before and after the first stretch was cleared of macrophytes. Each experiment comprised of hourly sample collection for 48 hours, accompanied by discharge measurements and continuous data logging of water-level, -temperature and electric conductivity. The set of micropollutants, which included both parent compounds and transformation products, was analysed by a newly developed direct injection-UHPLC-MS/MS method. The behaviour of individual micropollutants was compound-specific. Carbamazepine and benzotriazole were persistent along the river stretch while substances such as valsartan and metoprolol were attenuated by up to 15% of their original concentration. Interestingly, some transformation products, such as valsartan acid increased in concentration

  8. Effect of Varying Hemodynamic and Vascular Conditions on Fractional Flow Reserve: An In Vitro Study.

    Science.gov (United States)

    Kolli, Kranthi K; Min, James K; Ha, Seongmin; Soohoo, Hilary; Xiong, Guanglei

    2016-06-30

    The aim of this study was to investigate the impact of varying hemodynamic conditions on fractional flow reserve (ratio of pressure distal [Pd] and proximal [Pa] to stenosis under hyperemia) in an in vitro setting. Failure to achieve maximal hyperemia and the choice of hyperemic agents may have differential effects on coronary hemodynamics and, consequently, on the determination of fractional flow reserve. An in vitro flow system was developed to experimentally model the physiological coronary circulation as flow-dependent stenosis resistance in series with variable downstream resistance. Five idealized models with 30% to 70% diameter stenosis severity were fabricated using VeroClear rigid material in an Objet260 Connex printer. Mean aortic pressure was maintained at 7 levels (60-140 mm Hg) from hypotension to hypertension using a needle valve that mimicked adjustable microcirculatory resistance. A range of physiological flow rates was applied by a steady flow pump and titrated by a flow sensor. The pressure drop and the pressure ratio (Pd/Pa) were assessed for the 7 levels of aortic pressure and differing flow rates. The in vitro experimental data were coupled with pressure-flow relationships from clinical data for populations with and without myocardial infarction, respectively, to evaluate fractional flow reserve. The curve for pressure ratio and flow rate demonstrated a quadratic relationship with a decreasing slope. The absolute decrease in fractional flow reserve in the group without myocardial infarction (with myocardial infarction) was on the order of 0.03 (0.02), 0.05 (0.02), 0.07 (0.05), 0.17 (0.13) and 0.20 (0.24), respectively, for 30%, 40%, 50%, 60%, and 70% diameter stenosis, for an increase in aortic pressure from 60 to 140 mm Hg. The fractional flow reserve value, an index of physiological stenosis significance, was observed to decrease with increasing aortic pressure for a given stenosis in this idealized in vitro experiment for vascular

  9. Performance of green LTE networks powered by the smart grid with time varying user density

    KAUST Repository

    Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

    2013-01-01

    In this study, we implement a green heuristic algorithm involving the base station sleeping strategy that aims to ensure energy saving for the radio access network of the 4GLTE (Fourth Generation Long Term Evolution) mobile networks. We propose

  10. Volatility spillover and time-varying conditional correlation between DDGS, corn, and soybean meal markets

    NARCIS (Netherlands)

    Etienne, Xiaoli L.; Trujillo-Barrera, Andrés; Hoffman, Linwood A.

    2017-01-01

    We find distiller's dried grains with solubles (DDGS) prices to be positively correlated with both corn and soybean meal prices in the long run. However, neither corn nor soybean meal prices respond to deviations from this long-run relationship. We also identify strong time-varying dynamic

  11. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Wei Feng

    2014-01-01

    Full Text Available The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results. Two numerical examples are illustrated to verify our results.

  12. Estimating time-varying conditional correlations between stock and foreign exchange markets

    Science.gov (United States)

    Tastan, Hüseyin

    2006-02-01

    This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

  13. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    Science.gov (United States)

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  14. Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations.

    Science.gov (United States)

    Xiao, Lin; Liao, Bolin; Li, Shuai; Chen, Ke

    2018-02-01

    In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurrent neural networks are proved to be convergent within finite-time. Besides, by solving differential equation, the upper bounds of the finite convergence time are determined analytically. Compared with existing recurrent neural networks, the proposed two nonlinear recurrent neural networks have a better convergence property (i.e., the upper bound is lower), and thus the accurate solutions of general time-varying LMEs can be obtained with less time. At last, various different situations have been considered by setting different coefficient matrices of general time-varying LMEs and a great variety of computer simulations (including the application to robot manipulators) have been conducted to validate the better finite-time convergence of the proposed two nonlinear recurrent neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Facilitating conditions for boundary-spanning behavior in governance networks

    OpenAIRE

    Meerkerk, Ingmar; Edelenbos, Jurian

    2017-01-01

    textabstractThis article examines the impact of two facilitating conditions for boundary-spanning behaviour in urban governance networks. While research on boundary spanning is growing, there is little attention for antecedents. Combining governance network literature on project management and organizational literature on facilitative and servant leadership, we examine two potential conditions: a facilitative project management style and executive support. We conducted survey research among p...

  16. Linear parameter varying control of wind turbines covering both partial load and full load conditions

    DEFF Research Database (Denmark)

    Østergaard, Kasper Zinck; Stoustrup, Jakob; Brath, Per

    2009-01-01

    operations tend to be ill-conditioned. The paper proposes a controller construction algorithm together with various remedies for improving the numerical conditioning the algorithm.The proposed algorithm is applied to the design of a LPV controller for wind turbines, and a comparison is made with a controller...... designed using classical techniques to conclude that an improvement in performance is obtained for the entire operating envelope....

  17. Numerical simulation of diurnally varying thermal environment in a street canyon under haze-fog conditions

    Science.gov (United States)

    Tan, Zijing; Dong, Jingliang; Xiao, Yimin; Tu, Jiyuan

    2015-10-01

    The impact of haze-fog on surface temperature, flow pattern, pollutant dispersion and pedestrian thermal comfort are investigated using computational fluid dynamics (CFD) approach based on a three-dimensional street canyon model under different haze-fog conditions. In this study, light extinction coefficient (Kex) is adopted to represent haze-fog pollution level. Numerical simulations are performed for different Kex values at four representative time events (1000 LST, 1300 LST, 1600 LST and 2000 LST). The numerical results suggest that the surface temperature is strongly affected by the haze-fog condition. Surface heating induced by the solar radiation is enhanced by haze-fog, as higher surface temperature is observed under thicker haze-fog condition. Moreover, the temperature difference between sunlit and shadow surfaces is reduced, while that for the two shadow surfaces is slightly increased. Therefore, the surface temperature among street canyon facets becomes more evenly distributed under heavy haze-fog conditions. In addition, flow patterns are considerably altered by different haze-fog conditions, especially for the afternoon (1600 LST) case, in which thermal-driven flow has opposite direction as that of the wind-driven flow direction. Consequently, pollutants such as vehicular emissions will accumulate at pedestrian level, and pedestrian thermal comfort may lower under thicker haze-fog condition.

  18. Adaptive observer-based control for an IPMC actuator under varying humidity conditions

    Science.gov (United States)

    Bernat, Jakub; Kolota, Jakub

    2018-05-01

    As ionic polymer metal composites (IPMC) are increasingly applied to mechatronic systems, many new IPMC modeling efforts have been reported in the literature. The demands of rapidly growing technology has generated interest in advancing the intrinsic actuation and sensing capabilities of IPMC. Classical IPMC applications need constant hydration to operate. On the other hand, for IPMCs operating in air, the water content of the polymer varies with the humidity level of the ambient environment, which leads to its strong humidity-dependent behavior. Furthermore, decreasing water content over time plays a crucial role in the effectiveness of IPMC. Therefore, the primary challenge of this work is to accurately model this phenomenon. The principal contribution of the paper is a new IPMC model, which considers the change of moisture content. A novel nonlinear adaptive observer is designed to determine the unknown electric potential and humidity level in the polymer membrane. This approach effectively determines the moisture content of the IPMC during long-term continuous operation in air. This subsequently allows us to develop an effective back-stepping control algorithm that considers varying moisture content. Data from experiments are presented to support the effectiveness of the observation process, which is shown in illustrative examples.

  19. Relationship between continuity of care and adverse outcomes varies by number of chronic conditions among older adults with diabetes

    Directory of Open Access Journals (Sweden)

    Eva H. DuGoff

    2016-06-01

    Full Text Available Follow us on Twitter Co-Editors-in-Chief Martin Fortin Jane Gunn Stewart W. Mercer Susan Smith Marjan van den Akker Society for Academic Primary Care Journal Help USER You are logged in as... avalster My Profile Log Out JOURNAL CONTENT Search Search Scope Search Browse By Issue By Author By Title By Sections By Identify Types OPEN JOURNAL SYSTEMS FONT SIZE Make font size smallerMake font size defaultMake font size larger INFORMATION For Readers For Authors For Librarians ARTICLE TOOLS Print this article Indexing metadata How to cite item Supplementary files Finding References Email this article Email the author Post a Comment NOTIFICATIONS View (378 new Manage IRCMO NEWS ‘Addressing the global challenge of... Publications on multimorbidity... The CARE Plus study Prevalence of multimorbidity in the... Multimorbidity in adults from a... CURRENT ISSUE Atom logo RSS2 logo RSS1 logo HOSTED BY Part of the PKP Publishing Services Network HOME ABOUT USER HOME SEARCH CURRENT ARCHIVES ANNOUNCEMENTS PUBLISHER AUTHOR GUIDELINES SUBMISSIONS WHY PUBLISH WITH US? Home > Vol 6, No 2 (2016 >\tDuGoff Relationship between continuity of care and adverse outcomes varies by number of chronic conditions among older adults with diabetes Eva H. DuGoff, Karen Bandeen-Roche, Gerard F. Anderson Abstract Background: Continuity of care is a basic tenant of primary care practice. However, the evidence on the importance of continuity of care for older adults with complex conditions is mixed. Objective: To assess the relationship between measurement of continuity of care, number of chronic conditions, and health outcomes. Design: We analyzed data from a cohort of 1,600 US older adults with diabetes and ≥1 other chronic condition in a private Medicare health plan from July 2010 to December 2011. Multivariate regression models were used to examine the association of baseline continuity (the first 6 months and the composite outcome of any emergency room use or inpatient

  20. Performance of asphaltic concrete incorporating styrene butadiene rubber subjected to varying aging condition

    Science.gov (United States)

    Salah, Faisal Mohammed; Jaya, Ramadhansyah Putra; Mohamed, Azman; Hassan, Norhidayah Abdul; Rosni, Nurul Najihah Mad; Mohamed, Abdullahi Ali; Agussabti

    2017-12-01

    The influence of styrene butadiene rubber (SBR) on asphaltic concrete properties at different aging conditions was presented in this study. These aging conditions were named as un-aged, short-term, and long-term aging. The conventional asphalt binder of penetration grade 60/70 was used in this work. Four different levels of SBR addition were employed (i.e., 0 %, 1 %, 3 %, and 5 % by binder weight). Asphalt concrete mixes were prepared at selected optimum asphalt content (5 %). The performance was evaluated based on Marshall Stability, resilient modulus, and dynamic creep tests. Results indicated the improving stability and permanent deformation characteristics that the mixes modified with SBR polymer have under aging conditions. The result also showed that the stability, resilient modulus, and dynamic creep tests have the highest rates compared to the short-term aging and un-aged samples. Thus, the use of 5 % SBR can produce more durable asphalt concrete mixtures with better serviceability.

  1. The Metal-Halide Lamp Under Varying Gravity Conditions Measured by Emission and Laser Absorption Spectroscopy

    Science.gov (United States)

    Flikweert, A. J.; Nimalasuriya, T.; Kroesen, G. M. W.; Haverlag, M.; Stoffels, W. W.

    2009-11-01

    Diffusive and convective processes in the metal-halide lamp cause an unwanted axial colour segregation. Convection is induced by gravity. To understand the flow phenomena in the arc discharge lamp it has been investigated under normal laboratory conditions, micro-gravity (ISS and parabolic flights) and hyper-gravity (parabolic flights 2 g, centrifuge 1 g-10 g). The measurement techniques are webcam imaging, and emission and laser absorption spectroscopy. This paper aims to give an overview of the effect of different artificial gravity conditions on the lamp and compares the results from the three measurement techniques.

  2. Pre-Swirl Stator and Propeller Design for Varying Operating Conditions

    DEFF Research Database (Denmark)

    Saettone, Simone; Regener, Pelle Bo; Andersen, Poul

    2016-01-01

    blades ahead of the propeller.This paper describes the hydrodynamic design of apre-swirl stator with radially variable pitch, paired with aconventional propeller. The aim is to achieve the highest possible effciency in various operating conditions, and to avoid effciency penalties in off-design operation.......To investigate the propeller and stator designs and configurations in different operating conditions, the computationally inexpensive vortex-lattice method is used a sa first step to optimize the geometry in an initial parameter study. Then the flow over hull, stator and propelleris simulated in a CFD...

  3. Experimental study on Kd of 137Cs at varying suspended load conditions

    International Nuclear Information System (INIS)

    Jaison, T.J.; Jain, Abhishek; Patra, A.K.; Ravi, P.M.; Tripathi, R.M.

    2018-01-01

    137 Cs is one of the radionuclide likely to be released through liquid effluents from a nuclear facility. It is soluble in water, but its mobility in aquatic environments is highly retarded by its strong interaction with suspended sediment. The 137 Cs + sorption by suspended load, especially in the subtropics and tropics are not fully understood. Besides, according to IAEA document in emergency situation 137 Cs and 131 I being marker radionuclides, are easier to identify and representative of all the other radionuclides present. Hence a laboratory study is carried out on sorption of 137 Cs with varying silt load, using the upstream lake water and sediments to estimate site specific distribution coefficient (K d )

  4. 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)

  5. Basic regulatory principles of Escherichia coli's electron transport chain for varying oxygen conditions

    NARCIS (Netherlands)

    Henkel, S.G.; Ter Beek, A.S.; Steinsiek, S.; Stagge, S.; Bettenbrock, K.; Teixeira De Mattos, M.J.; Sauter, T.; Sawodny, O.; Ederer, M.

    2014-01-01

    For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the global transcriptional regulators FNR and ArcA are involved in oxygen response it is unclear

  6. Adult Tea Green Leafhoppers, Empoasca onukii (Matsuda), Change Behaviors under Varying Light Conditions.

    Science.gov (United States)

    Shi, Longqing; Vasseur, Liette; Huang, Huoshui; Zeng, Zhaohua; Hu, Guiping; Liu, Xin; You, Minsheng

    2017-01-01

    Insect behaviors are often influenced by light conditions including photoperiod, light intensity, and wavelength. Understanding pest insect responses to changing light conditions may help with developing alternative strategies for pest control. Little is known about the behavioral responses of leafhoppers (Hemiptera: Cicadellidae) to light conditions. The behavior of the tea green leafhopper, Empoasca onukii Matsuda, was examined when exposed to different light photoperiods or wavelengths. Observations included the frequency of locomotion and cleaning activities, and the duration of time spent searching. The results suggested that under normal photoperiod both female and male adults were generally more active in darkness (i.e., at night) than in light. In continuous darkness (DD), the locomotion and cleaning events in Period 1 (7:00-19:00) were significantly increased, when compared to the leafhoppers under normal photoperiod (LD). Leafhoppers, especially females, changed their behavioral patterns to a two day cycle under DD. Under continuous illumination (continuous quartz lamp light, yellow light at night, and green light at night), the activities of locomotion, cleaning, and searching were significantly suppressed during the night (19:00-7:00) and locomotion activities of both females and males were significantly increased during the day (7:00-19:00), suggesting a shift in circadian rhythm. Our work suggests that changes in light conditions, including photoperiod and wavelength, can influence behavioral activities of leafhoppers, potentially affecting other life history traits such as reproduction and development, and may serve as a method for leafhopper behavioral control.

  7. Existence and global exponential stability of periodic solution of memristor-based BAM neural networks with time-varying delays.

    Science.gov (United States)

    Li, Hongfei; Jiang, Haijun; Hu, Cheng

    2016-03-01

    In this paper, we investigate a class of memristor-based BAM neural networks with time-varying delays. Under the framework of Filippov solutions, boundedness and ultimate boundedness of solutions of memristor-based BAM neural networks are guaranteed by Chain rule and inequalities technique. Moreover, a new method involving Yoshizawa-like theorem is favorably employed to acquire the existence of periodic solution. By applying the theory of set-valued maps and functional differential inclusions, an available Lyapunov functional and some new testable algebraic criteria are derived for ensuring the uniqueness and global exponential stability of periodic solution of memristor-based BAM neural networks. The obtained results expand and complement some previous work on memristor-based BAM neural networks. Finally, a numerical example is provided to show the applicability and effectiveness of our theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon; Liang, Faming

    2013-01-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing

  9. The in vitro fitness cost of antimicrobial resistance in Escherichia coli varies with the growth conditions

    DEFF Research Database (Denmark)

    Petersen, Andreas; Aarestrup, Frank Møller; Olsen, John Elmerdahl

    2009-01-01

    The objective of this study was to investigate the influence of stressful growth conditions on the fitness cost of antimicrobial resistance in Escherichia coli BJ4 caused by chromosomal mutations and plasmid acquisition. The fitness cost of chromosomal streptomycin resistance increased......H and at high-salt concentrations. Strains with an impaired rpoS demonstrated a reduced fitness only during growth in a high-salt concentration. In conclusion, it was demonstrated that bacterial fitness cost in association with antimicrobial resistance generally increases under stressful growth conditions....... However, the growth potential of bacteria with antimicrobial resistances did not increase in a straightforward manner in these in vitro experiments and is therefore probably even more difficult to predict in vivo....

  10. Characterization of Transient Plasma Ignition Flame Kernel Growth for Varying Inlet Conditions

    Science.gov (United States)

    2009-12-01

    from Intercity Manufacturing. Without their expertise in precision machining this thesis would not have been possible. Their countless hours spent...somewhere within the combustor due to the time required to produce the required conditions, and will be travelling at near Mach 5 speeds for most...atmospheric pressure. This sudden drop in pressure creates a rarefaction wave that travels forward in the combustor. The blowdown time for a 1 meter long

  11. Detection of respiratory viruses in shelter dogs maintained under varying environmental conditions

    Directory of Open Access Journals (Sweden)

    Francielle Liz Monteiro

    Full Text Available Abstract Three dog shelters in Rio Grande do Sul were investigated for associations between the occurrence of respiratory viruses and shelter environmental conditions. Nasal secretions randomly collected during the cold season were tested via PCR, and this data collection was followed by nucleotide sequencing of the amplicons. In shelter #1 (poor sanitary and nutritional conditions, high animal density and constant contact between dogs, 78% (58/74 of the nasal samples were positive, 35% (26/74 of which were in single infections and 44% (32/74 of which were in coinfections. Shelters #2 and #3 had satisfactory sanitary and nutritional conditions, outdoors exercise areas (#2 and animal clustering by groups (#3. In shelter #2, 9% (3/35 of the samples were positive for Canine parainfluenza virus (CPIV, and 6% (2/35 were positive for Canid herpesvirus 1 (CaHV-1. In shelter #3, 9% (7/77 of the samples were positive for Canine adenovirus type 2 (CAdV-2, and 1% (1/77 were positive for Canine distemper virus (CDV. The amplicon sequences (CPIV and CDV nucleoprotein gene; CAdV-2 E3 gene; CaHV-1 glycoprotein B gene showed 94-100% nucleotide identity with GenBank sequences. Our results demonstrate that CPIV, CAdV-2 and CDV are common in dog shelters and that their frequencies appear to be related with environmental and nutritional conditions. These results indicate the need for control/prevention measures, including vaccination and environmental management, to minimize these infections and improve dog health.

  12. Analysis of a Data Communication Network’s Performance under Varying Retransmission Disciplines

    Science.gov (United States)

    1990-09-01

    The routing table is updated using delay information transmitted via congestion/routing up- date packets ( CRUP ) or through delay measurement...previous delay, plus or minus a threshold value, a CRUP is generated and flooded over the network. Upon receipt of a CRUP the ROUTING function up- dates...DDN topology is very large, accounting for the time delay for the full network to be updated, whereas adjacent PSN’s receive CRUP packets virtually

  13. Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kurtz, Nolan Scot [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-09-01

    The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.

  14. Mobility of Iron-Cyanide Complexes in a Humic Topsoil under Varying Redox Conditions

    Directory of Open Access Journals (Sweden)

    Thilo Rennert

    2009-01-01

    Full Text Available The potentially toxic Fe-CN complexes ferricyanide, [FeIII(CN6]3−, and ferrocyanide, [FeII(CN6]4−, undergo a variety of redox processes in soil, which affect their mobility. We carried out microcosm experiments with suspensions of a humic topsoil (pH 5.3; Corg 107 g kg-1 to which we added ferricyanide (20 mg l-1. We varied the redox potential (EH from −280 to 580 mV by using O2, N2 and glucose. The decrease of EH led to decreasing concentrations of Fe-CN complexes and partial reductive dissolution of (hydrous Fe and Mn oxides. The dynamics of aqueous Fe-CN concentrations was characterized by decreasing concentrations when the pH rose and the EH dropped. We attribute these dependencies to adsorption on organic surfaces, for which such a pH/EH behavior has been shown previously. Adsorption was reversible, because when the pH and EH changed into the opposite direction, desorption occurred. This study demonstrates the possible impact of soil organic matter on the fate of Fe-CN complexes in soil.

  15. Transient response of a polymer electrolyte membrane fuel cell subjected to time-varying modulating conditions

    Energy Technology Data Exchange (ETDEWEB)

    Noorani, S.; Shamim, T. [Michigan-Dearborn Univ., Dearborn, MI (United States). Dept. of Mechanical Engineering

    2009-07-01

    In order for fuel cells to compete with internal combustion engines, they must have significant advantages in terms of overall efficiency, weight, packaging, safety and cost. A key requirement is its ability to operate under highly transient conditions during start-up, acceleration, and deceleration with stable performance. Therefore, a better understanding of fuel cell dynamic behaviour is needed along with better water management and distributions inside the cell. Therefore, this study investigated the effect of transient conditions on water distribution inside a polymer electrolyte membrane (PEM) cell. A macroscopic single-fuel cell based, one-dimensional, isothermal mathematical model was used to study the effect of modulating cell voltage on the water distribution of anode, cathode, catalyst layers, and membrane. Compared to other existing models, this model did not rely on the non-physical assumption of the uptake curve equilibrium between the pore vapour and ionomer water in the catalyst layers. Instead, the transition between the two phases was modeled as a finite-rate equilibration process. The modulating conditions were simulated by forcing the temporal variations in fuel cell voltage. The results revealed that cell voltage modulations cause a departure in the cell behaviour from its steady behaviour, and the finite-rate equilibration between the catalyst vapour and liquid water can be a factor in determining the cell response. The cell response is also affected by the modulating frequency and amplitude. The peak cell response was observed at low frequencies. Keywords: fuel cell, water transport, dynamic behaviour, numerical simulations. 9 refs., 1 tab., 5 figs.

  16. Demonstration of Aerosol Property Profiling by Multiwavelength Lidar Under Varying Relative Humidity Conditions

    Science.gov (United States)

    Veselovskii, I.; Whiteman, D. N.; Kolgotin, A.; Andrews, E.; Korenskii, M.

    2009-01-01

    During the months of July-August 2007 NASA conducted a research campaign called the Tropical Composition, Clouds and Climate Coupling (TC4) experiment. Vertical profiles of ozone were measured daily using an instrument known as an ozonesonde, which is attached to a weather balloon and launch to altitudes in excess of 30 km. These ozone profiles were measured over coastal Las Tablas, Panama (7.8N, 80W) and several times per week at Alajuela, Costa Rica (ION, 84W). Meteorological systems in the form of waves, detected most prominently in 100-300 in thick ozone layer in the tropical tropopause layer, occurred in 50% (Las Tablas) and 40% (Alajuela) of the soundings. These layers, associated with vertical displacements and classified as gravity waves ("GW," possibly Kelvin waves), occur with similar stricture and frequency over the Paramaribo (5.8N, 55W) and San Cristobal (0.925, 90W) sites of the Southern Hemisphere Additional Ozonesondes (SHADOZ) network. The gravity wave labeled layers in individual soundings correspond to cloud outflow as indicated by the tracers measured from the NASA DC-8 and other aircraft data, confirming convective initiation of equatorial waves. Layers representing quasi-horizontal displacements, referred to as Rossby waves, are robust features in soundings from 23 July to 5 August. The features associated with Rossby waves correspond to extra-tropical influence, possibly stratospheric, and sometimes to pollution transport. Comparison of Las Tablas and Alajuela ozone budgets with 1999-2007 Paramaribo and San Cristobal soundings shows that TC4 is typical of climatology for the equatorial Americas. Overall during TC4, convection and associated meteorological waves appear to dominate ozone transport in the tropical tropopause layer.

  17. Oral complementary medicine and alternative practitioner use varies across chronic conditions and attitudes to risk

    Directory of Open Access Journals (Sweden)

    Robert J Adams

    2010-11-01

    Full Text Available Robert J Adams1, Sarah L Appleton1, Antonia Cole2, Tiffany K Gill3, Anne W Taylor3, Catherine L Hill11The Health Observatory, 2Rheumatology Unit, 3Population Research and Outcomes Unit, SA Health, The University of Adelaide Discipline of Medicine, Queen Elizabeth Hospital, Woodville, AustraliaObjectives: To determine whether chronic conditions and patient factors, such as risk perception and decision-making preferences, are associated with complementary medicine and alternative practitioner use in a representative longitudinal population cohort.Participants and setting: Analysis of data from Stage 2 of the North West Adelaide Health Study of 3161 adults who attended a study clinic visit in 2004–2006. The main outcome measures were the medications brought by participants to the study clinic visit, chronic health conditions, attitudes to risk, levels of satisfaction with conventional medicine, and preferred decision-making style.Results: At least one oral complementary medicine was used by 27.9% of participants, and 7.3% were visiting alternative practitioners (naturopath, osteopath. Oral complementary medicine use was significantly associated with arthritis, osteoporosis, and mental health conditions, but not with other chronic conditions. Any pattern of complementary medicine use was generally significantly associated with female gender, age at least 45 years, patient-driven decision-making preferences (odds ratio [OR] 1.38, 95% confidence interval [CI]: 1.08–1.77, and frequent general practitioner visits (>five per year; OR 3.62, 95% CI: 2.13–6.17. Alternative practitioner visitors were younger, with higher levels of education (diploma/trade [OR 1.88, 95% CI: 1.28–2.76], bachelor’s degree [OR 1.77, 95% CI: 1.11–2.82], income > $80,000 (OR 2.28, 95% CI: 1.26–4.11, female gender (OR 3.15, 95% CI: 2.19–4.52, joint pain not diagnosed as arthritis (OR 1.68, 95% CI: 1.17–2.41, moderate to severe depressive symptoms (OR 2.15, 95% CI

  18. Nitrous Oxide Production and Fluxes from Coastal Sediments under Varying Environmental Conditions

    Science.gov (United States)

    Ziebis, W.; Wankel, S. D.; de Beer, D.; Dentinger, J.; Buchwald, C.; Charoenpong, C.

    2014-12-01

    Although coastal zones represent important contributors to the increasing levels of atmospheric nitrous oxide (N2O), it is still unclear which role benthic processes play and whether marine sediments represent sinks or sources for N2O, since interactions among closely associated microbial groups lead to a high degree of variability. In addition, coastal areas are extremely dynamic regions, often exposed to increased nutrient loading and conditions of depleted oxygen. We investigated benthic N2O fluxes and how environmental conditions affect N2O production in different sediments at 2 different geographical locations (German Wadden Sea, a California coastal lagoon). At each location, a total of 32 sediment cores were taken in areas that differed in sediment type, organic content and pore-water nutrient concentrations, as well as in bioturbation activity. Parallel cores were incubated under in-situ conditions, low oxygen and increased nitrate levels for 10 days. Zones of N2O production and consumption were identified in intact cores by N2O microprofiles at the beginning and end of the experiments. In a collaborative effort to determine the dominant sources of N2O, samples were taken throughout the course of the experiments for the determination of the isotopic composition of N2O (as well as nitrate, nitrite and ammonium). Our results indicate that both, nitrate addition and low oxygen conditions in the overlying water, caused an increase of subsurface N2O production in most sediments, with a high variability between different sediment types. N2O production in the sediments was accompanied by N2O consumption, reducing the fluxes to the water column. In general, organic rich sediments showed the strongest response to environmental changes with increased production and efflux of N2O into the overlying water. Bioturbation activity added to the complexity of N2O dynamics by an increase in nitrification-denitrification processes, as well as enhanced pore-water transport

  19. Oral complementary medicine and alternative practitioner use varies across chronic conditions and attitudes to risk.

    Science.gov (United States)

    Adams, Robert J; Appleton, Sarah L; Cole, Antonia; Gill, Tiffany K; Taylor, Anne W; Hill, Catherine L

    2010-11-08

    To determine whether chronic conditions and patient factors, such as risk perception and decision-making preferences, are associated with complementary medicine and alternative practitioner use in a representative longitudinal population cohort. Analysis of data from Stage 2 of the North West Adelaide Health Study of 3161 adults who attended a study clinic visit in 2004-2006. The main outcome measures were the medications brought by participants to the study clinic visit, chronic health conditions, attitudes to risk, levels of satisfaction with conventional medicine, and preferred decision-making style. At least one oral complementary medicine was used by 27.9% of participants, and 7.3% were visiting alternative practitioners (naturopath, osteopath). Oral complementary medicine use was significantly associated with arthritis, osteoporosis, and mental health conditions, but not with other chronic conditions. Any pattern of complementary medicine use was generally significantly associated with female gender, age at least 45 years, patient-driven decision-making preferences (odds ratio [OR] 1.38, 95% confidence interval [CI]: 1.08-1.77), and frequent general practitioner visits (>five per year; OR 3.62, 95% CI: 2.13-6.17). Alternative practitioner visitors were younger, with higher levels of education (diploma/trade [OR 1.88, 95% CI: 1.28-2.76], bachelor's degree [OR 1.77, 95% CI: 1.11-2.82], income >$80,000 (OR 2.28, 95% CI: 1.26-4.11), female gender (OR 3.15, 95% CI: 2.19-4.52), joint pain not diagnosed as arthritis (OR 1.68, 95% CI: 1.17-2.41), moderate to severe depressive symptoms (OR 2.15, 95% CI: 1.04-4.46), and risk-taking behavior (3.26, 1.80-5.92), or low-to-moderate risk aversion (OR 2.08, 95% CI: 1.26-4.11). Although there is widespread use of complementary medicines in the Australian community, there are differing patterns of use between those using oral complementary medicines and those using alternative practitioners.

  20. Aerodynamic performance of a vibrating piezoelectric fan under varied operational conditions

    International Nuclear Information System (INIS)

    Stafford, J; Jeffers, N

    2014-01-01

    This paper experimentally examines the bulk aerodynamic performance of a vibrating fan operating in the first mode of vibration. The influence of operating condition on the local velocity field has also been investigated to understand the flow distribution at the exit region and determine the stalling condition for vibrating fans. Fan motion has been generated and controlled using a piezoelectric ceramic attached to a stainless steel cantilever. The frequency and amplitude at resonance were 109.4 Hz and 12.5 mm, respectively. A test facility has been developed to measure the pressure-flow characteristics of the vibrating fan and simultaneously conduct local velocity field measurements using particle image velocimetry. The results demonstrate the impact of system characteristics on the local velocity field. High momentum regions generated due to the oscillating motion exist with a component direction that is tangent to the blade at maximum displacement. These high velocity zones are significantly affected by increasing impedance while flow reversal is a dominant feature at maximum pressure rise. The findings outlined provide useful information for design of thermal management solutions that may incorporate this air cooling approach.

  1. Buckling of Nonprismatic Column on Varying Elastic Foundation with Arbitrary Boundary Conditions

    Directory of Open Access Journals (Sweden)

    Ahmad A. Ghadban

    2017-01-01

    Full Text Available Buckling of nonprismatic single columns with arbitrary boundary conditions resting on a nonuniform elastic foundation may be considered as the most generalized treatment of the subject. The buckling differential equation for such columns is extremely difficult to solve analytically. Thus, the authors propose a numerical approach by discretizing the column into a finite number of segments. Each segment has constants E (modulus of elasticity, I (moment of inertia, and β (subgrade stiffness. Next, an exact analytical solution is derived for each prismatic segment resting on uniform elastic foundation. These segments are then assembled in a matrix from which the critical buckling load is obtained. The derived formulation accounts for different end boundary conditions. Validation is performed by benchmarking the present results against analytical solutions found in the literature, showing excellent agreement. After validation, more examples are solved to illustrate the power and flexibility of the proposed method. Overall, the proposed method provides reasonable results, and the examples solved demonstrate the versatility of the developed approach and some of its many possible applications.

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

    Science.gov (United States)

    Vestergaard, Christian L; Génois, Mathieu

    2015-10-01

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

  3. Schema bias in source monitoring varies with encoding conditions: support for a probability-matching account.

    Science.gov (United States)

    Kuhlmann, Beatrice G; Vaterrodt, Bianca; Bayen, Ute J

    2012-09-01

    Two experiments examined reliance on schematic knowledge in source monitoring. Based on a probability-matching account of source guessing, a schema bias will only emerge if participants do not have a representation of the source-item contingency in the study list, or if the perceived contingency is consistent with schematic expectations. Thus, the account predicts that encoding conditions that affect contingency detection also affect schema bias. In Experiment 1, the schema bias commonly found when schematic information about the sources is not provided before encoding was diminished by an intentional source-memory instruction. In Experiment 2, the depth of processing of schema-consistent and schema-inconsistent source-item pairings was manipulated. Participants consequently overestimated the occurrence of the pairing type they processed in a deep manner, and their source guessing reflected this biased contingency perception. Results support the probability-matching account of source guessing. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  4. Rimsulfuron in Soil: Effects on Microbiological Properties under Varying Soil Conditions

    Directory of Open Access Journals (Sweden)

    Ljiljana Radivojević

    2011-01-01

    Full Text Available The effects of rimsulfuron a sulfonylurea herbicide on the growth and activity of soil microorganisms under laboratory conditions was investigated in two soils. The application rates were: 0.2, 2.0 and 20.0 mg a.i kg-1 soil. The lowest concentration tested was the label rate (0.2 mg a.i kg-1, and the other two were ten and hundred timeshigher. No adverse effects on microbiological processes were observed for the label rate. Decrease in microbial biomass carbon, dehydrogenase activity, fungi and bacteria in comparison with untreated control, were found at higher rates. The magnitude of these effects were generally slight and transitory.

  5. Conditions for Productive Learning in Network Learning Environments

    DEFF Research Database (Denmark)

    Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.

    2004-01-01

    are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments.   The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...

  6. Performance of green LTE networks powered by the smart grid with time varying user density

    KAUST Repository

    Ghazzai, Hakim

    2013-09-01

    In this study, we implement a green heuristic algorithm involving the base station sleeping strategy that aims to ensure energy saving for the radio access network of the 4GLTE (Fourth Generation Long Term Evolution) mobile networks. We propose an energy procurement model that takes into consideration the existence of multiple energy providers in the smart grid power system (e.g. fossil fuel and renewable energy sources, etc.) in addition to deployed photovoltaic panels in base station sites. Moreover, the analysis is based on the dynamic time variation of daily traffic and aims to maintain the network quality of service. Our simulation results show an important contribution in the reduction of CO2 emissions that can be reached by optimal power allocation over the active base stations. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.

  7. Mittag-Leffler synchronization of fractional neural networks with time-varying delays and reaction-diffusion terms using impulsive and linear controllers.

    Science.gov (United States)

    Stamova, Ivanka; Stamov, Gani

    2017-12-01

    In this paper, we propose a fractional-order neural network system with time-varying delays and reaction-diffusion terms. We first develop a new Mittag-Leffler synchronization strategy for the controlled nodes via impulsive controllers. Using the fractional Lyapunov method sufficient conditions are given. We also study the global Mittag-Leffler synchronization of two identical fractional impulsive reaction-diffusion neural networks using linear controllers, which was an open problem even for integer-order models. Since the Mittag-Leffler stability notion is a generalization of the exponential stability concept for fractional-order systems, our results extend and improve the exponential impulsive control theory of neural network system with time-varying delays and reaction-diffusion terms to the fractional-order case. The fractional-order derivatives allow us to model the long-term memory in the neural networks, and thus the present research provides with a conceptually straightforward mathematical representation of rather complex processes. Illustrative examples are presented to show the validity of the obtained results. We show that by means of appropriate impulsive controllers we can realize the stability goal and to control the qualitative behavior of the states. An image encryption scheme is extended using fractional derivatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. IR radiation characteristics of rocket exhaust plumes under varying motor operating conditions

    Directory of Open Access Journals (Sweden)

    Qinglin NIU

    2017-06-01

    Full Text Available The infrared (IR irradiance signature from rocket motor exhaust plumes is closely related to motor type, propellant composition, burn time, rocket geometry, chamber parameters and flight conditions. In this paper, an infrared signature analysis tool (IRSAT was developed to understand the spectral characteristics of exhaust plumes in detail. Through a finite volume technique, flow field properties were obtained through the solution of axisymmetric Navier-Stokes equations with the Reynolds-averaged approach. A refined 13-species, 30-reaction chemistry scheme was used for combustion effects and a k-ε-Rt turbulence model for entrainment effects. Using flowfield properties as input data, the spectrum was integrated with a line of sight (LOS method based on a single line group (SLG model with Curtis-Godson approximation. The model correctly predicted spectral distribution in the wavelengths of 1.50–5.50 μm and had good agreement for its location with imaging spectrometer data. The IRSAT was then applied to discuss the effects of three operating conditions on IR signatures: (a afterburning; (b chamber pressure from ignition to cutoff; and (c minor changes in the ratio of hydroxyl-terminated polybutadiene (HTPB binder to ammonium perchlorate (AP oxidizer in propellant. Results show that afterburning effects can increase the size and shape of radiance images with enhancement of radiation intensity up to 40%. Also, the total IR irradiance in different bands can be characterized by a non-dimensional chamber pressure trace in which the maximum discrepancy is less than 13% during ignition and engine cutoff. An increase of chamber pressure can lead to more distinct diamonds, whose distance intervals are extended, and the position of the first diamond moving backwards. In addition, an increase in HTPB/AP causes a significant jump in spectral intensity. The incremental rates of radiance intensity integrated in each band are linear with the increase of HTPB

  9. Hydroxyisohexyl 3-cyclohexene carboxaldehyde (lyral) in patch test preparations under varied storage conditions.

    Science.gov (United States)

    Hamann, Dathan; Hamann, Carsten R; Zimerson, Erik; Bruze, Magnus

    2013-01-01

    The common practice of preparing patch tests in advance has recently been called into question by researchers. It has been established that fragrance compounds are volatile and their testing efficacy may be affected by storage conditions and preparation. Allergens in fragrance mix I rapidly decrease in concentration after preapplication to test chambers. This study aimed to investigate the volatility of hydroxyisohexyl 3-cyclohexene carboxaldehyde (HICC) in petrolatum when stored in test chambers and to explore the correlation between vapor pressure and allergen loss in petrolatum during preparation and storage. Standardized HICC in petrolatum was prepared and stored in IQ Chambers and Finn Chambers with covers at 5°C, 25°C, and 35°C, and concentration was analyzed at intervals for up to 9 days using gel permeation chromatography. Changes in HICC concentrations were not statistically significant at 8 hours at 5°C, 25°C, and 35°C. After 9 days, HICC concentrations were found to fall approximately 30% when stored at 35°C, 10% at 25°C, and less than 5% at 5°C. There was no significant difference between IQ and Finn chambers. Hydroxyisohexyl 3-cyclohexene carboxaldehyde concentrations are more stable in petrolatum than many other studied fragrance allergens, but HICC is still at risk for decreasing concentration when exposed to ambient air or heat for prolonged periods.

  10. Vibration Analysis of a Tire in Ground Contact under Varied Conditions

    Directory of Open Access Journals (Sweden)

    Karakus Murat

    2017-03-01

    Full Text Available The effect of three different factors, which are inflation pressure, vertical load and coefficient of friction on the natural frequencies of a tire (175/70 R13 has been studied. A three dimensional tire model is constructed, using four different material properties and parts in the tire. Mechanical properties of the composite parts are evaluated. After investigating the free vibration, contact analysis is carried out. A concrete block and the tire are modelled together, using three different coefficients of friction. Experiments are run under certain conditions to check the accuracy of the numerical model. The natural frequencies are measured to describe free vibration and vibration of the tire contacted by ground, using a damping monitoring method. It is seen, that experimental and numerical results are in good agreement. On the other hand, investigating the impact of three different factors together is quite difficult on the natural frequencies. When some of these factors are assumed to be constant and the variables are taken one by one, it is easier to assess the effects.

  11. Toxicity of pentachlorophenol to aquatic organisms under naturally varying and controlled environmental conditions

    Energy Technology Data Exchange (ETDEWEB)

    Hedtke, S.F.; West, C.W.; Allen, K.N.; Norberg-King, T.J.; Mount, D.I.

    1986-06-01

    The toxicity of pentachlorophenol (PCP) was determined in the laboratory for 11 aquatic species. Tests were conducted seasonally in ambient Mississippi River water and under controlled conditions in Lake Superior water. Fifty-one acute toxicity tests were conducted, with LC50 values ranging from 85 micrograms/L for the white sucker Catastomus commersoni during the summer to greater than 7770 micrograms/L for the isopod Asellus racovitzai during the winter. The effect of PCP on growth and/or reproduction was determined for seven species. The most sensitive chronically exposed organisms were the cladoceran Ceriodaphnia reticulata and the snail Physa gyrina. The greatest variation in toxicity was due to species sensitivity. Within a given, season there was as much as a 40-fold difference in LC50 values between species. For any one species, the maximum variation in LC50 between seasons was approximately 14-fold. There were also substantial differences in acute-chronic relationships, with acute/chronic ratios ranging from greater than 37 for C. reticulata to 1 for Simocephalus vetulus. It is suggested that the composition of the aquatic community should be the most important consideration in estimating the potential environmental effects of PCP.

  12. Comparison of the kinetics of different Markov models for ligand binding under varying conditions

    International Nuclear Information System (INIS)

    Martini, Johannes W. R.; Habeck, Michael

    2015-01-01

    We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest

  13. Comparison of the kinetics of different Markov models for ligand binding under varying conditions

    Energy Technology Data Exchange (ETDEWEB)

    Martini, Johannes W. R., E-mail: jmartin2@gwdg.de [Max Planck Institute for Developmental Biology, Tübingen (Germany); Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Habeck, Michael, E-mail: mhabeck@gwdg.de [Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Max Planck Institute for Biophysical Chemistry, Göttingen (Germany)

    2015-03-07

    We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest.

  14. Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Yonggang Chen

    2008-01-01

    Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.

  15. Delay-Dependent Stability Criterion for Bidirectional Associative Memory Neural Networks with Interval Time-Varying Delays

    Science.gov (United States)

    Park, Ju H.; Kwon, O. M.

    In the letter, the global asymptotic stability of bidirectional associative memory (BAM) neural networks with delays is investigated. The delay is assumed to be time-varying and belongs to a given interval. A novel stability criterion for the stability is presented based on the Lyapunov method. The criterion is represented in terms of linear matrix inequality (LMI), which can be solved easily by various optimization algorithms. Two numerical examples are illustrated to show the effectiveness of our new result.

  16. Primary School Teachers and Outdoor Education: Varying Levels of Teacher Leadership in Informal Networks of Peers

    Science.gov (United States)

    Hovardas, Tasos

    2016-01-01

    The study concentrated on an area in Greece with a multiplicity of sites for outdoor education. Informal networks of teachers were detected through a snowball technique and data were collected by means of a questionnaire and semi-structured interviews. A typology was first enriched to account for teacher interaction. This typology was then…

  17. Modeling Quantum Dot Nanoparticle Fate and Transport in Saturated Porous Media under Varying Flow Conditions

    Science.gov (United States)

    Becker, M. D.; Wang, Y.; Englehart, J.; Pennell, K. D.; Abriola, L. M.

    2010-12-01

    As manufactured nanomaterials become more prevalent in commercial and industrial applications, the development of mathematical models capable of predicting nanomaterial transport and retention in subsurface systems is crucial to assessing their fate and distribution in the environment. A systematic modeling approach based on a modification of clean-bed filtration theory was undertaken to elucidate mechanisms governing the transport and deposition behavior of quantum dots in saturated quartz sand as a function of grain size and flow velocity. The traditional deposition governing equation, which assumes irreversible attachment by a first-order rate (katt), was modified to include a maximum or limiting retention capacity (Smax) and first-order detachment of particles from the solid phase (kdet). Quantum dot mobility experiments were performed in columns packed with three size fractions of Ottawa sand (d50 = 125, 165, and 335 μm) at two different pore-water velocities (0.8 m/d and 7.6 m/d). The CdSe quantum dots in a CdZnS shell and polyacrylic acid coating were negatively charged (zeta potential measured ca. -35 mV) with a hydrodynamic diameter of approximately 30 nm. Fitted values of katt, Smax, and kdet were obtained for each transport and deposition experiment through the implementation of a nonlinear least-squares routine developed to fit the model to experimental breakthrough and retention data via multivariate optimization. Fitted attachment rates and retention capacities increased exponentially with decreasing grain size at both flow rates, while no discernable trend was apparent for the fitted detachment rates. Maximum retention capacity values were plotted against a normalized mass flux expression, which accounts for flow conditions and grain size. A power function fit to the data yielded a dependence that was consistent with a previous study undertaken with fullerene nanoparticles.

  18. Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication.

    Science.gov (United States)

    Lakshmanan, Shanmugam; Prakash, Mani; Lim, Chee Peng; Rakkiyappan, Rajan; Balasubramaniam, Pagavathigounder; Nahavandi, Saeid

    2018-01-01

    In this paper, synchronization of an inertial neural network with time-varying delays is investigated. Based on the variable transformation method, we transform the second-order differential equations into the first-order differential equations. Then, using suitable Lyapunov-Krasovskii functionals and Jensen's inequality, the synchronization criteria are established in terms of linear matrix inequalities. Moreover, a feedback controller is designed to attain synchronization between the master and slave models, and to ensure that the error model is globally asymptotically stable. Numerical examples and simulations are presented to indicate the effectiveness of the proposed method. Besides that, an image encryption algorithm is proposed based on the piecewise linear chaotic map and the chaotic inertial neural network. The chaotic signals obtained from the inertial neural network are utilized for the encryption process. Statistical analyses are provided to evaluate the effectiveness of the proposed encryption algorithm. The results ascertain that the proposed encryption algorithm is efficient and reliable for secure communication applications.

  19. Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Fengxia Xu

    2014-01-01

    Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.

  20. Exponential Antisynchronization Control of Stochastic Memristive Neural Networks with Mixed Time-Varying Delays Based on Novel Delay-Dependent or Delay-Independent Adaptive Controller

    Directory of Open Access Journals (Sweden)

    Minghui Yu

    2017-01-01

    Full Text Available The global exponential antisynchronization in mean square of memristive neural networks with stochastic perturbation and mixed time-varying delays is studied in this paper. Then, two kinds of novel delay-dependent and delay-independent adaptive controllers are designed. With the ability of adapting to environment changes, the proposed controllers can modify their behaviors to achieve the best performance. In particular, on the basis of the differential inclusions theory, inequality theory, and stochastic analysis techniques, several sufficient conditions are obtained to guarantee the exponential antisynchronization between the drive system and response system. Furthermore, two numerical simulation examples are provided to the validity of the derived criteria.

  1. Routing of radioactive shipments in networks with time-varying costs and curfews

    Energy Technology Data Exchange (ETDEWEB)

    Bowler, L.A.; Mahmassani, H.S. [Univ. of Texas, Austin, TX (United States). Dept. of Civil Engineering

    1998-09-01

    This research examines routing of radioactive shipments in highway networks with time-dependent travel times and population densities. A time-dependent least-cost path (TDLCP) algorithm that uses a label-correcting approach is adapted to include curfews and waiting at nodes. A method is developed to estimate time-dependent population densities, which are required to estimate risk associated with the use of a particular highway link at a particular time. The TDLCP algorithm is implemented for example networks and used to examine policy questions related to radioactive shipments. It is observed that when only Interstate highway facilities are used to transport these materials, a shipment must go through many cities and has difficulty avoiding all of them during their rush hour periods. Decreases in risk, increased departure time flexibility, and modest increases in travel times are observed when primary and/or secondary roads are included in the network. Based on the results of the example implementation, the suitability of the TDLCP algorithm for strategic nuclear material and general radioactive material shipments is demonstrated.

  2. Routing of radioactive shipments in networks with time-varying costs and curfews

    International Nuclear Information System (INIS)

    Bowler, L.A.; Mahmassani, H.S.

    1998-09-01

    This research examines routing of radioactive shipments in highway networks with time-dependent travel times and population densities. A time-dependent least-cost path (TDLCP) algorithm that uses a label-correcting approach is adapted to include curfews and waiting at nodes. A method is developed to estimate time-dependent population densities, which are required to estimate risk associated with the use of a particular highway link at a particular time. The TDLCP algorithm is implemented for example networks and used to examine policy questions related to radioactive shipments. It is observed that when only Interstate highway facilities are used to transport these materials, a shipment must go through many cities and has difficulty avoiding all of them during their rush hour periods. Decreases in risk, increased departure time flexibility, and modest increases in travel times are observed when primary and/or secondary roads are included in the network. Based on the results of the example implementation, the suitability of the TDLCP algorithm for strategic nuclear material and general radioactive material shipments is demonstrated

  3. Conditions for Viral Influence Spreading through Multiplex Correlated Social Networks

    Science.gov (United States)

    Hu, Yanqing; Havlin, Shlomo; Makse, Hernán A.

    2014-04-01

    A fundamental problem in network science is to predict how certain individuals are able to initiate new networks to spring up "new ideas." Frequently, these changes in trends are triggered by a few innovators who rapidly impose their ideas through "viral" influence spreading, producing cascades of followers and fragmenting an old network to create a new one. Typical examples include the rise of scientific ideas or abrupt changes in social media, like the rise of Facebook to the detriment of Myspace. How this process arises in practice has not been conclusively demonstrated. Here, we show that a condition for sustaining a viral spreading process is the existence of a multiplex-correlated graph with hidden "influence links." Analytical solutions predict percolation-phase transitions, either abrupt or continuous, where networks are disintegrated through viral cascades of followers, as in empirical data. Our modeling predicts the strict conditions to sustain a large viral spreading via a scaling form of the local correlation function between multilayers, which we also confirm empirically. Ultimately, the theory predicts the conditions for viral cascading in a large class of multiplex networks ranging from social to financial systems and markets.

  4. Time-varying causal network of the Korean financial system based on firm-specific risk premiums

    Science.gov (United States)

    Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin

    2016-09-01

    The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.

  5. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  6. Personnel shift assignment: Existence conditions and network models

    NARCIS (Netherlands)

    van den Berg, Jeroen P.; van den Berg, J.P.; Panton, David M.

    1994-01-01

    The personnel scheduling problem is known to be a five-stage process in which the final stage involves the assignment of shifts to the days worked in the schedule. This paper discusses the existence conditions for both continuous and forward rotating shift assignments and heuristic network

  7. Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays

    International Nuclear Information System (INIS)

    Balasubramaniam, P.; Lakshmanan, S.; Manivannan, A.

    2012-01-01

    Highlights: ► Robust stability analysis for Markovian jumping interval neural networks is considered. ► Both linear fractional and interval uncertainties are considered. ► A new LKF is constructed with triple integral terms. ► MATLAB LMI control toolbox is used to validate theoretical results. ► Numerical examples are given to illustrate the effectiveness of the proposed method. - Abstract: This paper investigates robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional (LKF), some inequality techniques and stochastic stability theory, new delay-dependent stability criteria have been obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.

  8. Varying the agglomeration position of particles in a micro-channel using Acoustic Radiation Force beyond the resonance condition.

    Science.gov (United States)

    Dron, Olivier; Aider, Jean-Luc

    2013-09-01

    It is well-known that particles can be focused at mid-height of a micro-channel using Acoustic Radiation Force (ARF) tuned at the resonance frequency (h=λ/2). The resonance condition is a strong limitation to the use of acoustophoresis (particles manipulation using acoustic force) in many applications. In this study we show that it is possible to focus the particles anywhere along the height of a micro-channel just by varying the acoustic frequency, in contradiction with the resonance condition. This result has been thoroughly checked experimentally. The different physical properties as well as wall materials have been changed. The wall materials is finally the only critical parameters. One of the specificity of the micro-channel is the thickness of the carrier and reflector layer. A preliminary analysis of the experimental results suggests that the acoustic focusing beyond the classic resonance condition can be explained in the framework of the multilayered resonator proposed by Hill [1]. Nevertheless, further numerical studies are needed in order to confirm and fully understand how the acoustic pressure node can be moved over the entire height of the micro channel by varying the acoustic frequency. Despite some uncertainties about the origin of the phenomenon, it is robust and can be used for improved acoustic sorting or manipulation of particles or biological cells in confined set-ups. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Event-Based $H_\\infty $ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.

    Science.gov (United States)

    Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E

    2017-10-01

    In this paper, the event-based finite-horizon H ∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v) -dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H ∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.

  10. Urban tree species show the same hydraulic response to vapor pressure deficit across varying tree size and environmental conditions.

    Directory of Open Access Journals (Sweden)

    Lixin Chen

    Full Text Available The functional convergence of tree transpiration has rarely been tested for tree species growing under urban conditions even though it is of significance to elucidate the relationship between functional convergence and species differences of urban trees for establishing sustainable urban forests in the context of forest water relations.We measured sap flux of four urban tree species including Cedrus deodara, Zelkova schneideriana, Euonymus bungeanus and Metasequoia glyptostroboides in an urban park by using thermal dissipation probes (TDP. The concurrent microclimate conditions and soil moisture content were also measured. Our objectives were to examine 1 the influence of tree species and size on transpiration, and 2 the hydraulic control of urban trees under different environmental conditions over the transpiration in response to VPD as represented by canopy conductance. The results showed that the functional convergence between tree diameter at breast height (DBH and tree canopy transpiration amount (E(c was not reliable to predict stand transpiration and there were species differences within same DBH class. Species differed in transpiration patterns to seasonal weather progression and soil water stress as a result of varied sensitivity to water availability. Species differences were also found in their potential maximum transpiration rate and reaction to light. However, a same theoretical hydraulic relationship between G(c at VPD = 1 kPa (G(cref and the G(c sensitivity to VPD (-dG(c/dlnVPD across studied species as well as under contrasting soil water and R(s conditions in the urban area.We concluded that urban trees show the same hydraulic regulation over response to VPD across varying tree size and environmental conditions and thus tree transpiration could be predicted with appropriate assessment of G(cref.

  11. Urban tree species show the same hydraulic response to vapor pressure deficit across varying tree size and environmental conditions.

    Science.gov (United States)

    Chen, Lixin; Zhang, Zhiqiang; Ewers, Brent E

    2012-01-01

    The functional convergence of tree transpiration has rarely been tested for tree species growing under urban conditions even though it is of significance to elucidate the relationship between functional convergence and species differences of urban trees for establishing sustainable urban forests in the context of forest water relations. We measured sap flux of four urban tree species including Cedrus deodara, Zelkova schneideriana, Euonymus bungeanus and Metasequoia glyptostroboides in an urban park by using thermal dissipation probes (TDP). The concurrent microclimate conditions and soil moisture content were also measured. Our objectives were to examine 1) the influence of tree species and size on transpiration, and 2) the hydraulic control of urban trees under different environmental conditions over the transpiration in response to VPD as represented by canopy conductance. The results showed that the functional convergence between tree diameter at breast height (DBH) and tree canopy transpiration amount (E(c)) was not reliable to predict stand transpiration and there were species differences within same DBH class. Species differed in transpiration patterns to seasonal weather progression and soil water stress as a result of varied sensitivity to water availability. Species differences were also found in their potential maximum transpiration rate and reaction to light. However, a same theoretical hydraulic relationship between G(c) at VPD = 1 kPa (G(cref)) and the G(c) sensitivity to VPD (-dG(c)/dlnVPD) across studied species as well as under contrasting soil water and R(s) conditions in the urban area. We concluded that urban trees show the same hydraulic regulation over response to VPD across varying tree size and environmental conditions and thus tree transpiration could be predicted with appropriate assessment of G(cref).

  12. Comparison of creep behavior under varying load/temperature conditions between Hastelloy XR alloys with different boron content levels

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Nakajima, Hajime; Shindo, Masami; Tanabe, Tatsuhiko; Nakasone, Yuji.

    1996-01-01

    In the design of the high-temperature components, it is often required to predict the creep rupture life under the conditions in which the stress and/or temperature may vary by using the data obtained with the constant load and temperature creep rupture tests. Some conventional creep damage rules have been proposed to meet the above-mentioned requirement. Currently only limited data are available on the behavior of Hastelloy XR, which is a developed alloy as the structural material for high-temperature components of the High-Temperature Engineering Test Reactor (HTTR), under varying stress and/or temperature creep conditions. Hence a series of constant load and temperature creep rupture tests as well as varying load and temperature creep rupture tests was carried out on two kinds of Hastelloy XR alloys whose boron content levels are different, i.e., below 10 and 60 mass ppm. The life fraction rule completely fails in the prediction of the creep rupture life of Hastelloy XR with 60 mass ppm boron under varying load and temperature conditions though the rule shows good applicability for Hastelloy XR with below 10 mass ppm boron. The change of boron content level of the material during the tests is the most probable source of impairing the applicability of the life fraction rule to Hastelloy XR whose boron content level is 60 mass ppm. The modified life fraction rule has been proposed based on the dependence of the creep rupture strength on the boron content level of the alloy. The modified rule successfully predicts the creep rupture life under the two stage creep test conditions from 1000 to 900degC. The trend observed in the two stage creep tests from 900 to 1000degC can be qualitatively explained by the mechanism that the oxide film which is formed during the prior exposure to 900degC plays the role of the protective barrier against the boron dissipation into the environment. (J.P.N.)

  13. Empirical Bayes conditional independence graphs for regulatory network recovery

    Science.gov (United States)

    Mahdi, Rami; Madduri, Abishek S.; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R.; Crystal, Ronald G.; Mezey, Jason G.

    2012-01-01

    Motivation: Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. Methods: We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Results: Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Availability and implementation: Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. Contact: ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22685074

  14. Multiple types of synchronization analysis for discontinuous Cohen-Grossberg neural networks with time-varying delays.

    Science.gov (United States)

    Li, Jiarong; Jiang, Haijun; Hu, Cheng; Yu, Zhiyong

    2018-03-01

    This paper is devoted to the exponential synchronization, finite time synchronization, and fixed-time synchronization of Cohen-Grossberg neural networks (CGNNs) with discontinuous activations and time-varying delays. Discontinuous feedback controller and Novel adaptive feedback controller are designed to realize global exponential synchronization, finite time synchronization and fixed-time synchronization by adjusting the values of the parameters ω in the controller. Furthermore, the settling time of the fixed-time synchronization derived in this paper is less conservative and more accurate. Finally, some numerical examples are provided to show the effectiveness and flexibility of the results derived in this paper. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks

    Directory of Open Access Journals (Sweden)

    Charalambous Charalambos D

    2006-01-01

    Full Text Available A new time-varying (TV long-term fading (LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system, thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models, the statistics of the proposed model are shown to be TV, but converge in steady state to their static counterparts. Moreover, optimal power control algorithms (PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies (PPCS are used. In addition, an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models, and the distributed stochastic PCA provides better power stability and consumption than the distributed deterministic PCA.

  16. Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

    Science.gov (United States)

    Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

    2015-11-01

    The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of the fixed point theorem, nonsmooth analysis theory and other analytical tools, some sufficient conditions are established to guarantee that such n-dimensional memristive Cohen-Grossberg neural networks can have 5(n) equilibrium points, among which 3(n) equilibrium points are locally exponentially stable. It is shown that greater storage capacity can be achieved by neural networks with the non-monotonic activation functions introduced herein than the ones with Mexican-hat-type activation function. In addition, unlike most existing multistability results of neural networks with monotonic activation functions, those obtained 3(n) locally stable equilibrium points are located both in saturated regions and unsaturated regions. The theoretical findings are verified by an illustrative example with computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. An optimal power-dispatching system using neural networks for the electrochemical process of zinc depending on varying prices of electricity.

    Science.gov (United States)

    Yang, Chunhua; Deconinck, G; Gui, Weihua; Li, Yonggang

    2002-01-01

    Depending on varying prices of electricity, an optimal power-dispatching system (OPDS) is developed to minimize the cost of power consumption in the electrochemical process of zinc (EPZ). Due to the complexity of the EPZ, the main factors influencing the power consumption are determined by qualitative analysis, and a series of conditional experiments is conducted to acquire sufficient data, then two backpropagation neural networks are used to describe these relationships quantitatively. An equivalent Hopfield neural network is constructed to solve the optimization problem where a penalty function is introduced into the network energy function so as to meet the equality constraints, and inequality constraints are removed by alteration of the Sigmoid function. This OPDS was put into service in a smeltery in 1998. The cost of power consumption has decreased significantly, the total electrical energy consumption is reduced, and it is also beneficial to balancing the load of the power grid. The actual results show the effectiveness of the OPDS. This paper introduces a successful industrial application and mainly presents how to utilize neural networks to solve particular problems for the real world.

  18. Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

    Science.gov (United States)

    Chen, Po-Wei; Chen, Bor-Sen

    2011-08-01

    Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. Large scale network management. Condition indicators for network stations, high voltage power conductions and cables

    International Nuclear Information System (INIS)

    Eggen, Arnt Ove; Rolfseng, Lars; Langdal, Bjoern Inge

    2006-02-01

    In the Strategic Institute Programme (SIP) 'Electricity Business enters e-business (eBee)' SINTEF Energy research has developed competency that can help the energy business employ ICT systems and computer technology in an improved way. Large scale network management is now a reality, and it is characterized by large entities with increasing demands on efficiency and quality. These are goals that can only be reached by using ICT systems and computer technology in a more clever way than what is the case today. At the same time it is important that knowledge held by experienced co-workers is consulted when formal rules for evaluations and decisions in ICT systems are developed. In this project an analytical concept for evaluation of networks based information in different ICT systems has been developed. The method estimating the indicators to describe different conditions in a network is general, and indicators can be made to fit different levels of decision and network levels, for example network station, transformer circuit, distribution network and regional network. Moreover, the indicators can contain information about technical aspects, economy and HSE. An indicator consists of an indicator name, an indicator value, and an indicator colour based on a traffic-light analogy to indicate a condition or a quality for the indicator. Values on one or more indicators give an impression of important conditions in the network, and make up the basis for knowing where more detailed evaluations have to be conducted before a final decision on for example maintenance or renewal is made. A prototype has been developed for testing the new method. The prototype has been developed in Excel, and especially designed for analysing transformer circuits in a distribution network. However, the method is a general one, and well suited for implementation in a commercial computer system (ml)

  20. Mobility and cloud: operating in intermittent, austere network conditions

    OpenAIRE

    Wee, Toon Joo; Ling, Yu Xian Eldine

    2014-01-01

    Approved for public release; distribution is unlimited Cloud computing is emerging as the mainstream platform for a range of on-demand applications, services, and infrastructure. Before the benefits of cloud computing are realized, several technology challenges must be addressed. Operating in intermittent and austere network conditions is one of such challenges, which navy ships face when communicating with land-based cloud computing environments. Given limited bandwidth and intermittent c...

  1. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

  2. Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions

    Directory of Open Access Journals (Sweden)

    Jyotika Bahuguna

    2017-08-01

    Full Text Available The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural

  3. Gain control network conditions in early sensory coding.

    Directory of Open Access Journals (Sweden)

    Eduardo Serrano

    Full Text Available Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

  4. Synthesis of different-sized silver nanoparticles by simply varying reaction conditions with leaf extracts of Bauhinia variegata L.

    Science.gov (United States)

    Kumar, V; Yadav, S K

    2012-03-01

    Green synthesis of nanoparticles is one of the crucial requirements in today's climate change scenario all over the world. In view of this, leaf extract (LE) of Bauhinia variegata L. possessing strong antidiabetic and antibacterial properties has been used to synthesise silver nanoparticles (SNP) in a controlled manner. Various-sized SNP (20-120 nm) were synthesised by varying incubation temperature, silver nitrate and LE concentrations. The rate of SNP synthesis and their size increased with increase in AgNO(3) concentration up to 4 mM. With increase in LE concentration, size and aggregation of SNP was increased. The size and aggregation of SNP were also increased at temperatures above and below 40°C. This has suggested that size and dispersion of SNP can be controlled by varying reaction components and conditions. Polarity-based fractionation of B. variegata LE has suggested that only water-soluble fraction is responsible for SNP synthesis. Fourier transform infrared spectroscopy analysis revealed the attachment of polyphenolic and carbohydrate moieties to SNP. The synthesised SNPs were found stable in double distilled water, BSA and phosphate buffer (pH 7.4). On the contrary, incubation of SNP with NaCl induced aggregation. This suggests the safe use of SNP for various in vivo applications.

  5. Premature saturation in backpropagation networks: Mechanism and necessary conditions

    International Nuclear Information System (INIS)

    Vitela, J.E.; Reifman, J.

    1997-01-01

    The mechanism that gives rise to the phenomenon of premature saturation of the output units of feedforward multilayer neural networks during training with the standard backpropagation algorithm is described. The entire process of premature saturation is characterized by three distinct stages and it is concluded that the momentum term plays the leading role in the occurrence of the phenomenon. The necessary conditions for the occurrence of premature saturation are presented and a new method is proposed, based on these conditions, that eliminates the occurrence of the phenomenon. Validity of the conditions and the proposed method are illustrated through simulation results. Three case studies are presented. The first two came from a training session for classification of three component failures in a nuclear power plant. The last case, comes from a training session for classification of welded fuel elements

  6. Varying hydric conditions during incubation influence egg water exchange and hatchling phenotype in the red-eared slider turtle.

    Science.gov (United States)

    Delmas, Virginie; Bonnet, Xavier; Girondot, Marc; Prévot-Julliard, Anne-Caroline

    2008-01-01

    Environmental conditions within the nest, notably temperature and moisture of substrate, exert a powerful influence during embryogenesis in oviparous reptiles. The influence of fluctuating nest temperatures has been experimentally examined in different reptile species; however, similar experiments using moisture as the key variable are lacking. In this article, we examine the effect of various substrate moisture regimes during incubation on different traits (egg mass, incubation length, and hatchling mass) in a chelonian species with flexible-shelled eggs, the red-eared slider turtle (Trachemys scripta elegans). Our results show that the rate of water uptake by the eggs was higher in wet than in dry substrate and varied across development. More important, during the first third of development, the egg mass changes were relatively independent of the soil moisture level; they became very sensitive to moisture levels during the other two-thirds. Moreover, hydric conditions exerted a strong influence on the eggs' long-term sensitivity to the moisture of the substrate. Even short-term episodes of high or low levels of moisture modified permanently their water sensitivity, notably through modification of eggshell shape and volume, and in turn entailed significant effects on hatchling mass (and hence offspring quality). Such complex influences of fluctuating moisture levels at various incubation stages on hatchling phenotype better reflect the natural situation, compared to experiments based on stable, albeit different, moisture levels.

  7. Experiments and numerical modeling of fast flowing liquid metal thin films under spatially varying magnetic field conditions

    Science.gov (United States)

    Narula, Manmeet Singh

    Innovative concepts using fast flowing thin films of liquid metals (like lithium) have been proposed for the protection of the divertor surface in magnetic fusion devices. However, concerns exist about the possibility of establishing the required flow of liquid metal thin films because of the presence of strong magnetic fields which can cause flow disrupting MHD effects. A plan is underway to design liquid lithium based divertor protection concepts for NSTX, a small spherical torus experiment at Princeton. Of these, a promising concept is the use of modularized fast flowing liquid lithium film zones, as the divertor (called the NSTX liquid surface module concept or NSTX LSM). The dynamic response of the liquid metal film flow in a spatially varying magnetic field configuration is still unknown and it is suspected that some unpredicted effects might be lurking. The primary goal of the research work being reported in this dissertation is to provide qualitative and quantitative information on the liquid metal film flow dynamics under spatially varying magnetic field conditions, typical of the divertor region of a magnetic fusion device. The liquid metal film flow dynamics have been studied through a synergic experimental and numerical modeling effort. The Magneto Thermofluid Omnibus Research (MTOR) facility at UCLA has been used to design several experiments to study the MHD interaction of liquid gallium films under a scaled NSTX outboard divertor magnetic field environment. A 3D multi-material, free surface MHD modeling capability is under development in collaboration with HyPerComp Inc., an SBIR vendor. This numerical code called HIMAG provides a unique capability to model the equations of incompressible MHD with a free surface. Some parts of this modeling capability have been developed in this research work, in the form of subroutines for HIMAG. Extensive code debugging and benchmarking exercise has also been carried out. Finally, HIMAG has been used to study the

  8. Synchronization of Markovian jumping stochastic complex networks with distributed time delays and probabilistic interval discrete time-varying delays

    International Nuclear Information System (INIS)

    Li Hongjie; Yue Dong

    2010-01-01

    The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.

  9. Impact of Varying Wave Conditions on the Mobility of Arsenic in a Nearshore Aquifer on the Great Lakes

    Science.gov (United States)

    Rakhimbekova, S.; O'Carroll, D. M.; Robinson, C. E.

    2017-12-01

    Groundwater-coastal water interactions play an important role in controlling the behavior of inorganic chemicals in nearshore aquifers and the subsequent flux of these chemicals to receiving coastal waters. Previous studies have shown that dynamic groundwater flows and water exchange across the sediment-water interface can set up strong geochemical gradients and an important reaction zone in a nearshore aquifer that affect the fate of reactive chemicals. There is limited understanding of the impact of transient coastal forcing such as wave conditions on groundwater dynamics and geochemistry in a nearshore aquifer. The goal of this study was to assess the impact of intensified wave conditions on the behavior of arsenic in a nearshore aquifer and to determine the hydrological and geochemical factors controlling its fate and ultimate delivery to receiving coastal waters. Field investigations were conducted over the period of intensified wave conditions on a freshwater beach on Lake Erie, Canada. High spatial resolution aqueous and sediment sampling was conducted to characterize the subsurface distribution of inorganic species in the nearshore aquifer. Numerical groundwater flow and transport simulations were conducted to evaluate wave-induced perturbations in the flow dynamics including characterizing changes in the groundwater flow recirculations in the nearshore aquifer. The combination of field data and numerical simulations reveal that varying wave conditions alter groundwater flows and set up geochemical transition zones within the aquifer resulting in the release and sequestration of arsenic. Interactions between oxic surface water, mildly reducing shallow groundwater, and reducing sulfur- and iron-rich deep groundwater promote dynamic iron, sulfur and manganese cycling which control the mobility of arsenic in the aquifer. The findings of this study have potential implications for the fate and transport of other reactive chemicals (e.g. phosphorus, mercury) in

  10. Evaluation of the Survivability of Microorganisms Deposited on Filtering Respiratory Protective Devices under Varying Conditions of Humidity

    Directory of Open Access Journals (Sweden)

    Katarzyna Majchrzycka

    2016-01-01

    Full Text Available Bioaerosols are common biological factors in work environments, which require routine use of filtering respiratory protective devices (FRPDs. Currently, no studies link humidity changes in the filter materials of such devices, during use, with microorganism survivability. Our aim was to determine the microclimate inside FRPDs, by simulating breathing, and to evaluate microorganism survivability under varying humidity conditions. Breathing was simulated using commercial filtering facepiece respirators in a model system. Polypropylene melt-blown nonwoven fabrics with moisture contents of 40%, 80%, and 200%, were used for assessment of microorganisms survivability. A modified AATCC 100-2004 method was used to measure the survivability of ATCC and NCAIM microorganisms: Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Candida albicans and Aspergillus niger. During simulation relative humidity under the facepiece increased after 7 min of usage to 84%–92% and temperature increased to 29–30 °C. S. aureus survived the best on filter materials with 40%–200% moisture content. A decrease in survivability was observed for E. coli and C. albicans when mass humidity decreased. We found that B. subtilis and A. niger proliferated for 48–72 h of incubation and then died regardless of the moisture content. In conclusion, our tests showed that the survivability of microorganisms on filter materials depends on the amount of accumulated moisture and microorganism type.

  11. Evaluation of the Survivability of Microorganisms Deposited on Filtering Respiratory Protective Devices under Varying Conditions of Humidity.

    Science.gov (United States)

    Majchrzycka, Katarzyna; Okrasa, Małgorzata; Skóra, Justyna; Gutarowska, Beata

    2016-01-04

    Bioaerosols are common biological factors in work environments, which require routine use of filtering respiratory protective devices (FRPDs). Currently, no studies link humidity changes in the filter materials of such devices, during use, with microorganism survivability. Our aim was to determine the microclimate inside FRPDs, by simulating breathing, and to evaluate microorganism survivability under varying humidity conditions. Breathing was simulated using commercial filtering facepiece respirators in a model system. Polypropylene melt-blown nonwoven fabrics with moisture contents of 40%, 80%, and 200%, were used for assessment of microorganisms survivability. A modified AATCC 100-2004 method was used to measure the survivability of ATCC and NCAIM microorganisms: Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Candida albicans and Aspergillus niger. During simulation relative humidity under the facepiece increased after 7 min of usage to 84%-92% and temperature increased to 29-30 °C. S. aureus survived the best on filter materials with 40%-200% moisture content. A decrease in survivability was observed for E. coli and C. albicans when mass humidity decreased. We found that B. subtilis and A. niger proliferated for 48-72 h of incubation and then died regardless of the moisture content. In conclusion, our tests showed that the survivability of microorganisms on filter materials depends on the amount of accumulated moisture and microorganism type.

  12. Experimental FSO network availability estimation using interactive fog condition monitoring

    Science.gov (United States)

    Turán, Ján.; Ovseník, Łuboš

    2016-12-01

    Free Space Optics (FSO) is a license free Line of Sight (LOS) telecommunication technology which offers full duplex connectivity. FSO uses infrared beams of light to provide optical broadband connection and it can be installed literally in a few hours. Data rates go through from several hundreds of Mb/s to several Gb/s and range is from several 100 m up to several km. FSO link advantages: Easy connection establishment, License free communication, No excavation are needed, Highly secure and safe, Allows through window connectivity and single customer service and Compliments fiber by accelerating the first and last mile. FSO link disadvantages: Transmission media is air, Weather and climate dependence, Attenuation due to rain, snow and fog, Scattering of laser beam, Absorption of laser beam, Building motion and Air pollution. In this paper FSO availability evaluation is based on long term measured data from Fog sensor developed and installed at TUKE experimental FSO network in TUKE campus, Košice, Slovakia. Our FSO experimental network has three links with different physical distances between each FSO heads. Weather conditions have a tremendous impact on FSO operation in terms of FSO availability. FSO link availability is the percentage of time over a year that the FSO link will be operational. It is necessary to evaluate the climate and weather at the actual geographical location where FSO link is going to be mounted. It is important to determine the impact of a light scattering, absorption, turbulence and receiving optical power at the particular FSO link. Visibility has one of the most critical influences on the quality of an FSO optical transmission channel. FSO link availability is usually estimated using visibility information collected from nearby airport weather stations. Raw data from fog sensor (Fog Density, Relative Humidity, Temperature measured at each ms) are collected and processed by FSO Simulator software package developed at our Department. Based

  13. Heavy metals in precipitation waters under conditions of varied anthropopressure in typical of European low mountain regions

    Directory of Open Access Journals (Sweden)

    Rabajczyk A.

    2013-04-01

    Full Text Available The environment is a dynamic system, subject to change resulting from a variety of physicochemical factors, such as temperature, pressure, pH, redox potential and human activity. The quantity and variety of these determinants cause the inflow of substances into individual environmental elements to vary in both time and space, as well as in terms of substance types and quantities. The energy and matter flow in the environment determines its integrity, which means that the processes occurring in one element of the environment affect the others. A certain measure of the energy and matter flow is the migration of chemical substances in various forms from one place to another. In a particular geographical space, under natural conditions, a specific level of balance between individual processes appears; in areas subject to anthropopressure, the correlations are different. In small areas, varying deposition volumes and chemism of precipitation waters which reach the substratum directly can both be observed. The study area is similar in terms of geological origins as well as morphological, structural and physico-chemical properties, and is typical of European low mountain regions. A qualitative and quantitative study of wet atmospheric precipitation was conducted between February 2009 and May 2011 in the Bobrza river catchment in the Holy Cross (Świętokrzyskie Mountains (Poland, at three sampling sites of varying land development and distance from sources of various acidic-alkaline emissions. Field and laboratory work was conducted over 29 months, from February 2009 to May 2011. Atmospheric precipitation measurements were carried out in a continuous manner by means of a Hellman rain gauge (200cm2. The collecting surface was placed at ground level (0m AGL. The application of a collecting funnel and an adequately prepared polyethylene collecting can in the rain gauge enabled the measurement of precipitation volume and water sampling for chemical

  14. Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

    Science.gov (United States)

    Duda, Piotr; Jaworski, Maciej; Rutkowski, Leszek

    2018-03-01

    One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated memory is constant and the models incorporate changes of investigated streams. A vast majority of available methods have been developed for data stream classification and only a few of them attempted to solve regression problems, using various heuristic approaches. In this paper, we develop mathematically justified regression models working in a time-varying environment. More specifically, we study incremental versions of generalized regression neural networks, called IGRNNs, and we prove their tracking properties - weak (in probability) and strong (with probability one) convergence assuming various concept drift scenarios. First, we present the IGRNNs, based on the Parzen kernels, for modeling stationary systems under nonstationary noise. Next, we extend our approach to modeling time-varying systems under nonstationary noise. We present several types of concept drifts to be handled by our approach in such a way that weak and strong convergence holds under certain conditions. Finally, in the series of simulations, we compare our method with commonly used heuristic approaches, based on forgetting mechanism or sliding windows, to deal with concept drift. Finally, we apply our concept in a real life scenario solving the problem of currency exchange rates prediction.

  15. Evaluation of poly(2-ethyl-2-oxazoline) containing copolymer networks of varied composition as sustained metoprolol tartrate delivery systems.

    Science.gov (United States)

    Kostova, Bistra; Ivanova, Sijka; Balashev, Konstantin; Rachev, Dimitar; Christova, Darinka

    2014-08-01

    Segmented copolymer networks (SCN) based on poly(2-ethyl-2-oxazoline) and containing 2-hydroxyethyl methacrylate, 2-hydroxypropyl acrylate, and/or methyl methacrylate segments have been evaluated as potential sustained release systems of the water soluble cardioselective β-blocker metoprolol tartrate. The structure and properties of the drug carriers were investigated by differential scanning calorimetry, attenuated total reflectance Fourier transform infrared spectroscopy, scanning electron microscopy, and atomic force microscopy. Swelling kinetics of SCNs in various media was followed, and the conditions for effective MT loading were specified. MT-loaded SCNs with drug content up to 80 wt.% were produced. The release kinetics of metoprolol tartrate from the systems was studied and it was shown that the conetworks of different structure and composition are able to sustain the metoprolol tartrate release without additional excipients.

  16. Adaptive neural network motion control for aircraft under uncertainty conditions

    Science.gov (United States)

    Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

    2018-02-01

    We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

  17. International Children's Palliative Care Network: A Global Action Network for Children With Life-Limiting Conditions.

    Science.gov (United States)

    Marston, Joan; Boucher, Sue; Downing, Julia

    2018-02-01

    The International Children's Palliative Care Network (ICPCN) is a global network of individuals and organizations working together to reach the estimated 21 million children with life-limiting conditions and life-threatening illnesses. The drive to establish the ICPCN was born from the recognition of the gaps in service provision for children's palliative care and the need to collaborate, network, and share resources. Established in 2005 during a meeting in Seoul, South Korea, the ICPCN has developed over the years into an established network with a global membership. The history of the organization is described, including some of the key events since its inception. Working in collaboration with others, ICPCN has five key focus areas: Communication; Advocacy; Research; Education; and Strategic development, and is the only international charity working globally for the rights of children with palliative care needs. Activities in these areas are discussed, along with the inter-connection between the five areas. Without the ICPCN, palliative care for children would not have developed as far as it has over the years and the organization is committed to ongoing work in this area until all children requiring palliative care have access to quality services, wherever they live around the world. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  18. Rare Earth Element Behavior During Incongruent Weathering and Varying Discharge Conditions in Silicate Dominated River Systems: The Australian Victorian Alps

    Science.gov (United States)

    Hagedorn, K. B.; Cartwright, I.

    2008-12-01

    The distribution of rare earth elements (REE) and trace elements was measured by ICP-MS on fresh, slightly weathered and weathered granite and surface water samples from a network of 11 pristine rivers draining the Australian Victorian Alps during (i) high and (ii) low discharge conditions. River water REE concentrations are largely derived from atmospheric precipitation (rain, snow), as indicated by similar Chondrite normalized REE patterns (higher LREE over HREE; negative Ce anomalies, positive Eu anomalies) and similar total REE concentrations during both dry and wet seasons. Calculations based on the covariance between REE and Cl concentrations and oxygen and hydrogen isotopes indicate precipitation input coupled with subsequent evaporation may account for 30% o 100% of dissolved REE in stream waters. The dissolved contribution to the granitic substratum to stream water comes mainly from the transformation of plagioclase to smectite, kaolinite and gibbsite and minor apatite dissolution. However, since most REE of the regional granite are present in accessory minerals (titanite, zircon, etc.) they do not significantly contribute to the river REE pool. REE concentrations drop sharply downstream as a result of dilution and chemical attenuation. A trend of downstream enrichment of the heavier REE is due to selective partitioning of the lighter REE (as both free REE or REECO3 complexes) to hydrous oxides of suspended Al which, in turn, is controlled by a downstream increase of pH to values > 6.1 (for free REE) and > 7.3 (for REECO3 complexes). Although most circumneutral waters were supersaturated with REE phosphate compounds, precipitation of LnPO4 is not believed to have been a dominant process because the predicted phosphate fractionation pattern is inconsistent with the observed trends. Negative saturation indices of hydrous ferric oxides also militate against surface complexation onto goethite. Instead, REE attenuation most likely resulted from adsorption onto

  19. Varied Human Tolerance to the Combined Conditions of Low Contrast and Diminished Luminance: A Quasi-Meta Analysis

    Science.gov (United States)

    2017-08-30

    conditions (e.g., dry eyes , mild cataractous conditions, Stevens-Johnson Syndrome ) using CS alone as the performance index. More commonly, it has been...subjects tested under conditions of spherical blur, astigmatic blur, low luminance, and one eye vs. two eyes ...conditions). The vast majority of past mesopic visual performance studies were predominantly isolated to evaluations of various eye disease

  20. Exponential stability for stochastic delayed recurrent neural networks with mixed time-varying delays and impulses: the continuous-time case

    International Nuclear Information System (INIS)

    Karthik Raja, U; Leelamani, A; Raja, R; Samidurai, R

    2013-01-01

    In this paper, the exponential stability for a class of stochastic neural networks with time-varying delays and impulsive effects is considered. By constructing suitable Lyapunov functionals and by using the linear matrix inequality optimization approach, we obtain sufficient delay-dependent criteria to ensure the exponential stability of stochastic neural networks with time-varying delays and impulses. Two numerical examples with simulation results are provided to illustrate the effectiveness of the obtained results over those already existing in the literature. (paper)

  1. Thermo-Mechanical Properties of Semi-Degradable Poly(β-amino ester)-co-Methyl Methacrylate Networks under Simulated Physiological Conditions

    Science.gov (United States)

    Safranski, David L.; Crabtree, Jacob C.; Huq, Yameen R.; Gall, Ken

    2011-01-01

    Poly(β-amino ester) networks are being explored for biomedical applications, but they may lack the mechanical properties necessary for long term implantation. The objective of this study is to evaluate the effect of adding methyl methacrylate on networks' mechanical properties under simulated physiological conditions. The networks were synthesized in two parts: (1) a biodegradable crosslinker was formed from a diacrylate and amine, (2) and then varying concentrations of methyl methacrylate were added prior to photopolymerizing the network. Degradation rate, mechanical properties, and glass transition temperature were studied as a function of methyl methacrylate composition. The crosslinking density played a limited role on mechanical properties for these networks, but increasing methyl methacrylate concentration improved the toughness by several orders of magnitude. Under simulated physiological conditions, networks showed increasing toughness or sustained toughness as degradation occurred. This work establishes a method of creating degradable networks with tailorable toughness while undergoing partial degradation. PMID:21966028

  2. Conditions for extinction events in chemical reaction networks with discrete state spaces.

    Science.gov (United States)

    Johnston, Matthew D; Anderson, David F; Craciun, Gheorghe; Brijder, Robert

    2018-05-01

    We study chemical reaction networks with discrete state spaces and present sufficient conditions on the structure of the network that guarantee the system exhibits an extinction event. The conditions we derive involve creating a modified chemical reaction network called a domination-expanded reaction network and then checking properties of this network. Unlike previous results, our analysis allows algorithmic implementation via systems of equalities and inequalities and suggests sequences of reactions which may lead to extinction events. We apply the results to several networks including an EnvZ-OmpR signaling pathway in Escherichia coli.

  3. Atmospheric conditions measured by a wireless sensor network on the local scale

    Science.gov (United States)

    Lengfeld, K.; Ament, F.

    2010-09-01

    Atmospheric conditions close to the surface, like temperature, wind speed and humidity, vary on small scales because of surface heterogeneities. Therefore, the traditional measuring approach of using a single, highly accurate station is of limited representativeness for a larger domain, because it is not able to determine these small scale variabilities. However, both the variability and the domain averages are important information for the development and validation of atmospheric models and soil-vegetation-atmosphere-transfer (SVAT) schemes. Due to progress in microelectronics it is possible to construct networks of comparably cheap meteorological stations with moderate accuracy. Such a network provides data in high spatial and temporal resolution. The EPFL Lausanne developed such a network called SensorScope, consisting of low cost autonomous stations. Each station observes air and surface temperature, humidity, wind direction and speed, incoming solar radiation, precipitation, soil moisture and soil temperature and sends the data via radio communication to a base station. This base station forwards the collected data via GSM/GPRS to a central server. The first measuring campaign took place within the FLUXPAT project in August 2009. We deployed 15 stations as a twin transect near Jülich, Germany. To test the quality of the low cost sensors we compared two of them to more accurate reference systems. It turned out, that although the network sensors are not highly accurate, the measurements are consistent. Consequently an analysis of the pattern of atmospheric conditions is feasible. The transect is 2.3 km long and covers different types of vegetation and a small river. Therefore, we analyse the influence of different land surfaces and the distance to the river on meteorological conditions. For example, we found a difference in air temperature of 0.8°C between the station closest to and the station farthest from the river. The decreasing relative humidity with

  4. Generation of synthetic surface electromyography signals under fatigue conditions for varying force inputs using feedback control algorithm.

    Science.gov (United States)

    Venugopal, G; Deepak, P; Ghosh, Diptasree M; Ramakrishnan, S

    2017-11-01

    Surface electromyography is a non-invasive technique used for recording the electrical activity of neuromuscular systems. These signals are random, complex and multi-component. There are several techniques to extract information about the force exerted by muscles during any activity. This work attempts to generate surface electromyography signals for various magnitudes of force under isometric non-fatigue and fatigue conditions using a feedback model. The model is based on existing current distribution, volume conductor relations, the feedback control algorithm for rate coding and generation of firing pattern. The result shows that synthetic surface electromyography signals are highly complex in both non-fatigue and fatigue conditions. Furthermore, surface electromyography signals have higher amplitude and lower frequency under fatigue condition. This model can be used to study the influence of various signal parameters under fatigue and non-fatigue conditions.

  5. A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions

    Directory of Open Access Journals (Sweden)

    Zhinong Jiang

    2018-01-01

    Full Text Available Under frequently time-varying operating conditions, equipment with dual rotors like gas turbines is influenced by two rotors with different rotating speeds. Alarm methods of fixed threshold are unable to consider the influences of time-varying operating conditions. Hence, those methods are not suitable for monitoring dual-rotor equipment. An early warning method for dual-rotor equipment under time-varying operating conditions is proposed in this paper. The influences of time-varying rotating speeds of dual rotors on alarm thresholds have been considered. Firstly, the operating conditions are divided into several limited intervals according to rotating speeds of dual rotors. Secondly, the train data within each interval is processed by SVDD and the allowable ranges (i.e., the alarm threshold of the vibration are determined. The alarm threshold of each interval of operating conditions is obtained. The alarm threshold can be expressed as a sphere, whose controlling parameters are the coordinate of the center and the radius. Then, the cluster center of the test data, whose alarm state is to be judged, can be extracted through K-means. Finally, the alarm state can be obtained by comparing the cluster center with the corresponding sphere. Experiments are conducted to validate the proposed method.

  6. Mesoscopic structure conditions the emergence of cooperation on social networks.

    Directory of Open Access Journals (Sweden)

    Sergi Lozano

    Full Text Available BACKGROUND: We study the evolutionary Prisoner's Dilemma on two social networks substrates obtained from actual relational data. METHODOLOGY/PRINCIPAL FINDINGS: We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement with the observations in both real substrates. CONCLUSION: Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.

  7. Mesoscopic structure conditions the emergence of cooperation on social networks

    Energy Technology Data Exchange (ETDEWEB)

    Lozano, S.; Arenas, A.; Sanchez, A.

    2008-12-01

    We study the evolutionary Prisoner's Dilemma on two social networks substrates obtained from actual relational data. We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement with the observations in both real substrates. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.

  8. Trade networks evolution under the conditions of stock market globalization

    Directory of Open Access Journals (Sweden)

    Kopylova Olga Volodymyrivna

    2016-12-01

    Full Text Available The modern perception of the stock market in terms of information technologies rapid development and under the institutionalists influence has been significantly modified and becomes multifaceted. It was detected that the main function of the market is activated, information asymmetry is minimized and more advanced financial architecture space is formed through trade networks. Formation of the modern trade networks has started on the basis of the old infrastructure, that had the highest tendency to self-organization and adaptation. The proposed architecture of trade networks of the stock market has a very clear vector of subordination – from top to bottom and has a number of positive points.

  9. Biodiesel production process optimization and characterization to assess the suitability of the product for varied environmental conditions

    Energy Technology Data Exchange (ETDEWEB)

    Eevera, T.; Rajendran, K.; Saradha, S. [Department of Biotechnology, Periyar Maniammai University, Periyar Nagar, Vallam, Thanjavur, Tamilnadu 613 403 (India)

    2009-03-15

    In this study, both edible (coconut oil, palm oil, groundnut oil, and rice bran oil) and non-edible oils (pongamia, neem and cotton seed oil) were used to optimize the biodiesel production process variables like catalyst concentration, amount of methanol required for reaction, reaction time and reaction temperature. The fuel properties like specific gravity, moisture content, refractive index, acid value, iodine number, saponification value and peroxide value were estimated. Based on the cetane number and iodine value, the methyl esters obtained from palm and coconut oils were not suitable to use as biodiesel in cold weather conditions, but for hot climate condition biodiesel obtained from the remaining oil sources is suitable. (author)

  10. TRANSFORMATION OF PB(II FROM CERRUSITE TO CHLOROPYROMORPHITE IN THE PRESENCE OF HYDROXYAPATITE UNDER VARYING CONDITIONS OF PH

    Science.gov (United States)

    The soluble Pb concentration and formation of chloropyromorphite [Pb5(PO4)3Cl] were monitored during the reaction of cerrusite (PbCO3), a highly bioavailable soil Pb species, and hydroxyapatite [Ca5(PO4)3OH] at various P/Pb molar ratios under constant and dynamic pH conditions. ...

  11. Analytical solution for multi-species contaminant transport in finite media with time-varying boundary conditions

    Science.gov (United States)

    Most analytical solutions available for the equations governing the advective-dispersive transport of multiple solutes undergoing sequential first-order decay reactions have been developed for infinite or semi-infinite spatial domains and steady-state boundary conditions. In this work we present an ...

  12. Foam Core Particleboards with Intumescent FRT Veneer: Cone Calorimeter Testing With Varying Adhesives, Surface Layer Thicknesses, and Processing Conditions

    Science.gov (United States)

    Mark A. Dietenberger; Johannes Welling; Ali Shalbafan

    2014-01-01

    Intumescent FRT Veneers adhered to the surface of foam core particleboard to provide adequate fire protection were evaluated by means of cone calorimeter tests (ASTM E1354). The foam core particleboards were prepared with variations in surface layer treatment, adhesives, surface layer thicknesses, and processing conditions. Ignitability, heat release rate profile, peak...

  13. Exponential synchronization of delayed neutral-type neural networks with Lévy noise under non-Lipschitz condition

    Science.gov (United States)

    Ma, Shuo; Kang, Yanmei

    2018-04-01

    In this paper, the exponential synchronization of stochastic neutral-type neural networks with time-varying delay and Lévy noise under non-Lipschitz condition is investigated for the first time. Using the general Itô's formula and the nonnegative semi-martingale convergence theorem, we derive general sufficient conditions of two kinds of exponential synchronization for the drive system and the response system with adaptive control. Numerical examples are presented to verify the effectiveness of the proposed criteria.

  14. Spinning in different directions: western rock lobster larval condition varies with eddy polarity, but does their diet?

    OpenAIRE

    O'Rorke, R.; Jeffs, A. G.; Wang, M.; Waite, A. M.; Beckley, L. E.; Lavery, S. D.

    2015-01-01

    Larvae of the western rock lobster (Panulirus cygnus) that occur in the south-east Indian Ocean offshore of Western Australia have been found to be in poorer nutritional condition in anticyclonic compared with cyclonic mesoscale eddies. The reason for this is unknown, but culture-based experiments have shown that diet composition and water temperature are key determinants of phyllosoma health and survival. Whether differences in prey composition are the cause of poor phyllosoma co...

  15. Intelligent condition monitoring of railway catenary systems : A Bayesian Network approach

    NARCIS (Netherlands)

    Wang, H.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Liu, Zhigang; Chen, Junwen; Spiryagin, Maksym; Gordon, Timothy; Cole, Colin; McSweeney, Tim

    2017-01-01

    This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head

  16. Effects of varying environmental conditions on emissivity spectra of bulk lunar soils: Application to Diviner thermal infrared observations of the Moon

    Science.gov (United States)

    Donaldson Hanna, K. L.; Greenhagen, B. T.; Patterson, W. R.; Pieters, C. M.; Mustard, J. F.; Bowles, N. E.; Paige, D. A.; Glotch, T. D.; Thompson, C.

    2017-02-01

    Currently, few thermal infrared measurements exist of fine particulate (samples (e.g. minerals, mineral mixtures, rocks, meteorites, and lunar soils) measured under simulated lunar conditions. Such measurements are fundamental for interpreting thermal infrared (TIR) observations by the Diviner Lunar Radiometer Experiment (Diviner) onboard NASA's Lunar Reconnaissance Orbiter as well as future TIR observations of the Moon and other airless bodies. In this work, we present thermal infrared emissivity measurements of a suite of well-characterized Apollo lunar soils and a fine particulate (sample as we systematically vary parameters that control the near-surface environment in our vacuum chamber (atmospheric pressure, incident solar-like radiation, and sample cup temperature). The atmospheric pressure is varied between ambient (1000 mbar) and vacuum (radiation is varied between 52 and 146 mW/cm2, and the sample cup temperature is varied between 325 and 405 K. Spectral changes are characterized as each parameter is varied, which highlight the sensitivity of thermal infrared emissivity spectra to the atmospheric pressure and the incident solar-like radiation. Finally spectral measurements of Apollo 15 and 16 bulk lunar soils are compared with Diviner thermal infrared observations of the Apollo 15 and 16 sampling sites. This comparison allows us to constrain the temperature and pressure conditions that best simulate the near-surface environment of the Moon for future laboratory measurements and to better interpret lunar surface compositions as observed by Diviner.

  17. Depression and Chronic Health Conditions Among Latinos: The Role of Social Networks.

    Science.gov (United States)

    Soto, Sandra; Arredondo, Elva M; Villodas, Miguel T; Elder, John P; Quintanar, Elena; Madanat, Hala

    2016-12-01

    The purpose of this study was to examine the "buffering hypothesis" of social network characteristics in the association between chronic conditions and depression among Latinos. Cross-sectional self-report data from the San Diego Prevention Research Center's community survey of Latinos were used (n = 393). Separate multiple logistic regression models tested the role of chronic conditions and social network characteristics in the likelihood of moderate-to-severe depressive symptoms. Having a greater proportion of the network comprised of friends increased the likelihood of depression among those with high cholesterol. Having a greater proportion of women in the social network was directly related to the increased likelihood of depression, regardless of the presence of chronic health conditions. Findings suggest that network characteristics may play a role in the link between chronic conditions and depression among Latinos. Future research should explore strategies targeting the social networks of Latinos to improve health outcomes.

  18. Evolution of deformation structures under varying loading conditions followed in situ by high angular resolution 3DXRD

    DEFF Research Database (Denmark)

    Pantleon, Wolfgang; Wejdemann, Christian; Jakobsen, B.

    2009-01-01

    copper to different loading conditions are presented: during uninterrupted tensile deformation, formation of subgrains can be observed concurrently with broadening of the Bragg reflection shortly after onset of plastic deformation. With continued tensile deformation, the subgrain structure develops...... intermittently. When the traction is terminated, stress relaxation occurs and number, size and orientation of subgrains are found to be constant. The subgrain structure freezes and only a minor clean-up of the dislocation structure is observed. When changing the tensile direction after pre-deformation in tension...

  19. Influence of different land surfaces on atmospheric conditions measured by a wireless sensor network

    Science.gov (United States)

    Lengfeld, Katharina; Ament, Felix

    2010-05-01

    Atmospheric conditions close to the surface, like temperature, wind speed and humidity, vary on small scales because of surface heterogeneities. Therefore, the traditional measuring approach of using a single, highly accurate station is of limited representativeness for a larger domain, because it is not able to determine these small scale variabilities. However, both the variability and the domain averages are important information for the development and validation of atmospheric models and soil-vegetation-atmosphere-transfer (SVAT) schemes. Due to progress in microelectronics it is possible to construct networks of comparably cheap meteorological stations with moderate accuracy. Such a network provides data in high spatial and temporal resolution. The EPFL Lausanne developed such a network called SensorScope, consisting of low cost autonomous stations. Each station observes air and surface temperature, humidity, wind direction and speed, incoming solar radiation, precipitations, soil moisture and soil temperature and sends the data via radio communication to a base station. This base station forwards the collected data via GSM/GPRS to a central server. Within the FLUXPAT project in August 2009 we deployed 15 stations as a twin transect near Jülich, Germany. One aim of this first experiment was to test the quality of the low cost sensors by comparing them to more accurate reference measurements. It turned out, that although the network is not highly accurate, the measurements are consistent. Consequently an analysis of the pattern of atmospheric conditions is feasible. For example, we detect a variability of ± 0.5K in the mean temperature at a distance of only 2.3 km. The transect covers different types of vegetation and a small river. Therefore, we analyzed the influence of different land surfaces and the distance to the river on meteorological conditions. On the one hand, some results meet our expectations, e.g. the relative humidity decreases with increasing

  20. The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

    OpenAIRE

    Ambrogioni, Luca; Güçlü, Umut; van Gerven, Marcel A. J.; Maris, Eric

    2017-01-01

    This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex conditional densities as linear combinations of a family of kernel functions centered at a subset of training points. The weights are determined by the outer layer of a deep neural network, trained by minimizing the negative log likelihood. This generalizes the popular quantized softmax approach, which can be seen ...

  1. Wireless sensor network for monitoring soil moisture and weather conditions

    Science.gov (United States)

    A wireless sensor network (WSN) was developed and deployed in three fields to monitor soil water status and collect weather data for irrigation scheduling. The WSN consists of soil-water sensors, weather sensors, wireless data loggers, and a wireless modem. Soil-water sensors were installed at three...

  2. Parallel importance sampling in conditional linear Gaussian networks

    DEFF Research Database (Denmark)

    Salmerón, Antonio; Ramos-López, Darío; Borchani, Hanen

    2015-01-01

    In this paper we analyse the problem of probabilistic inference in CLG networks when evidence comes in streams. In such situations, fast and scalable algorithms, able to provide accurate responses in a short time are required. We consider the instantiation of variational inference and importance ...

  3. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    Energy Technology Data Exchange (ETDEWEB)

    Vellinger, Céline, E-mail: celine.vellinger@gmail.com [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Sohm, Bénédicte, E-mail: benedicte.sohm@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Parant, Marc, E-mail: marc.parant@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Immel, Françoise, E-mail: Francoise.Immel@u-bourgogne.fr [Biogéosciences, CNRS UMR 6282, Université de Bourgogne – Dijon (France); Usseglio-Polatera, Philippe, E-mail: philippe.usseglio-polatera@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France)

    2016-08-15

    This study aims at investigating the potential use of comparative proteomics as a multi-marker approach of metal contamination, taking into account the potential confounding effect of water temperature. The major objective was to identify combinations of proteins specifically responding to a given metal, even if included in a metal mixture. The diagnostic approach was performed via the comparative analysis of protein expression on spot mapping provided by adult males of Gammarus pulex (Amphipoda, Crustacea) respectively exposed to arsenate (As), cadmium (Cd) or a binary mixture of these metals (AsCd) at three realistic temperatures (5, 10 and 15 °C). Proteomic expression analysis was performed by Differential in-Gel Electrophoresis (2D-DiGE), and completed by an adapted inferential statistical approach. Combinations of under/over-expressed protein spots discriminated the metal identity. However, none of these spots discriminated both the individual metal effect (As or Cd) and its effect in metal mixture (AsCd) whatever the tested temperature. Some limits of the two-dimensional analysis of protein spot maps in G. pulex have been highlighted: (i) the presence of contaminating peptides and/or abundant “déja-vu” proteins which can mask the responses of other proteins of interest or (ii) the presence of post-translational modifications. An optimization of the experimental design (especially during the sample preparation) has been described for future investigations. This study has also highlighted (i) the importance of precisely identifying the protein spots of interest to avoid erroneous interpretations in terms of action mechanisms of chemicals and (ii) the importance of working under controlled laboratory conditions with a temperature close to 10 °C. In such conditions, we have demonstrated a higher impact of As than Cd on the energetic metabolism of Gammarus. This As impact is reduced in AsCd mixture confirming the antagonistic interaction of this binary

  4. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    International Nuclear Information System (INIS)

    Vellinger, Céline; Sohm, Bénédicte; Parant, Marc; Immel, Françoise; Usseglio-Polatera, Philippe

    2016-01-01

    This study aims at investigating the potential use of comparative proteomics as a multi-marker approach of metal contamination, taking into account the potential confounding effect of water temperature. The major objective was to identify combinations of proteins specifically responding to a given metal, even if included in a metal mixture. The diagnostic approach was performed via the comparative analysis of protein expression on spot mapping provided by adult males of Gammarus pulex (Amphipoda, Crustacea) respectively exposed to arsenate (As), cadmium (Cd) or a binary mixture of these metals (AsCd) at three realistic temperatures (5, 10 and 15 °C). Proteomic expression analysis was performed by Differential in-Gel Electrophoresis (2D-DiGE), and completed by an adapted inferential statistical approach. Combinations of under/over-expressed protein spots discriminated the metal identity. However, none of these spots discriminated both the individual metal effect (As or Cd) and its effect in metal mixture (AsCd) whatever the tested temperature. Some limits of the two-dimensional analysis of protein spot maps in G. pulex have been highlighted: (i) the presence of contaminating peptides and/or abundant “déja-vu” proteins which can mask the responses of other proteins of interest or (ii) the presence of post-translational modifications. An optimization of the experimental design (especially during the sample preparation) has been described for future investigations. This study has also highlighted (i) the importance of precisely identifying the protein spots of interest to avoid erroneous interpretations in terms of action mechanisms of chemicals and (ii) the importance of working under controlled laboratory conditions with a temperature close to 10 °C. In such conditions, we have demonstrated a higher impact of As than Cd on the energetic metabolism of Gammarus. This As impact is reduced in AsCd mixture confirming the antagonistic interaction of this binary

  5. An empirical assessment of driver motivation and emotional states in perceived safety margins under varied driving conditions.

    Science.gov (United States)

    Zhang, Yu; Kaber, David B

    2013-01-01

    Motivation models in driving behaviour postulate that driver motives and emotional states dictate risk tolerance under various traffic conditions. The present study used time and driver performance-based payment systems to manipulate motivation and risk-taking behaviour. Ten participants drove to a predefined location in a simulated driving environment. Traffic patterns (density and velocity) were manipulated to cause driver behaviour adjustments due to the need to conform with the social norms of the roadway. The driving environment complexity was investigated as a mediating factor in risk tolerance. Results revealed the performance-based payment system to closely relate to risk-taking behaviour as compared with the time-based payment system. Drivers conformed with social norms associated with specific traffic patterns. Higher roadway complexity led to a more conservative safety margins and speeds. This research contributes to the further development of motivational models of driver behaviour. This study provides empirical justification for two motivation factors in driver risk-taking decisions, including compliance with social norm and emotions triggered by incentives. Environment complexity was identified as a mediating factor in motivational behaviour model. This study also recommended safety margin measures sensitive to changes in driver risk tolerance.

  6. Analysis of critical operating conditions for LV distribution networks with microgrids

    Science.gov (United States)

    Zehir, M. A.; Batman, A.; Sonmez, M. A.; Font, A.; Tsiamitros, D.; Stimoniaris, D.; Kollatou, T.; Bagriyanik, M.; Ozdemir, A.; Dialynas, E.

    2016-11-01

    Increase in the penetration of Distributed Generation (DG) in distribution networks, raises the risk of voltage limit violations while contributing to line losses. Especially in low voltage (LV) distribution networks (secondary distribution networks), impacts of active power flows on the bus voltages and on the network losses are more dominant. As network operators must meet regulatory limitations, they have to take into account the most critical operating conditions in their systems. In this study, it is aimed to present the impact of the worst operation cases of LV distribution networks comprising microgrids. Simulation studies are performed on a field data-based virtual test-bed. The simulations are repeated for several cases consisting different microgrid points of connection with different network loading and microgrid supply/demand conditions.

  7. Synchronization of a Class of Memristive Stochastic Bidirectional Associative Memory Neural Networks with Mixed Time-Varying Delays via Sampled-Data Control

    Directory of Open Access Journals (Sweden)

    Manman Yuan

    2018-01-01

    Full Text Available The paper addresses the issue of synchronization of memristive bidirectional associative memory neural networks (MBAMNNs with mixed time-varying delays and stochastic perturbation via a sampled-data controller. First, we propose a new model of MBAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying distributed delays and discrete delays. Second, we design a new method of sampled-data control for the stochastic MBAMNNs. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the methods are carefully designed to confirm the synchronization processes are suitable for the feather of the memristor. Third, sufficient criteria guaranteeing the synchronization of the systems are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

  8. Modulating the phenology and yield of camelina sativa L. by varying sowing dates under water deficit stress conditions

    Directory of Open Access Journals (Sweden)

    Ejaz Ahmad Waraich

    2017-05-01

    Full Text Available Camelina (Camelina sativa L. an oilseed crop has emerged as a potential source for biofuels and bio-products. Camelina is an economic crop due to its less requirements of agronomic inputs as compared to other oilseed crops. However, it is direly required to evaluate the adaptability of camelina and characterize its production potential. Therefore, a pot experiment was carried out in rain out shelter at the Department of Agronomy, University of Agriculture, Faisalabad, Pakistan to optimize appropriate sowing date with respect to growth and yield potential of different genotypes of camelina under drought stress. Completely randomized design with factorial arrangements was adopted. Three sowing dates with the difference of 10 days (November 13 th, 23rd and December 03rd, two water regimes (100% FC and 60% FC and two camlena genotypes (611 and 618 were used in this experiment. Results indicated that camelina growth and yield related traits were significantly influenced by difference in sowing dates and water regimes. Maximum leaf area index (LAI, crop growth rate (CGR, leaf area duration (LAD, net assimilation rate (NAR and yield related traits were recorded with early sowing (13th November which was followed by sowing on 23rd November and least values of these variables were recorded in late sowing (December 03rd. Plants grown under water deficit conditions (60% FC showed the decreased values of LAI, CGR, LAD, NAR and yield related attributes as compared to normally irrigated plants (100% FC. However, the response of genotypes of camelina 611 and 618 remained statistically similar to each other.

  9. Measuring networks for environmental radioactivity monitoring in the European Community, - a pattern of diversity as varying as the peoples?

    International Nuclear Information System (INIS)

    Maushart, R.

    1991-01-01

    A new study entitled 'Monitoring of Environmental Radioactivity in the European Community', (RAES, 90), shows a survey of the methods currently applied in every country. The study compiles available quality assurance programs and makes suggestions for CEC initiatives. The study refers to the current practice of monitoring in European countries as 'enormous diversity of methods' in member countries. Further suggestions for standardization of the data measuring networks are put forward by a manufacturer of monitoring equipment. (orig./DG) [de

  10. Evaluation of Poly(2-Ethyl-2-Oxazoline) Containing Copolymer Networks of Varied Composition as Sustained Metoprolol Tartrate Delivery Systems

    OpenAIRE

    Kostova, Bistra; Ivanova, Sijka; Balashev, Konstantin; Rachev, Dimitar; Christova, Darinka

    2014-01-01

    Segmented copolymer networks (SCN) based on poly(2-ethyl-2-oxazoline) and containing 2-hydroxyethyl methacrylate, 2-hydroxypropyl acrylate, and/or methyl methacrylate segments have been evaluated as potential sustained release systems of the water soluble cardioselective β-blocker metoprolol tartrate. The structure and properties of the drug carriers were investigated by differential scanning calorimetry, attenuated total reflectance Fourier transform infrared spectroscopy, scanning electron ...

  11. A new criterion on the global exponential stability for cellular neural networks with multiple time-varying delays

    International Nuclear Information System (INIS)

    Jiang Haijun; Teng Zhidong

    2005-01-01

    In this Letter, based on the Lyapunov stability theorem as well as some facts about the positive definiteness and inequality of matrices, a new sufficient condition to ensure the global exponential stability of equilibrium point for autonomous delayed CNNs is obtained. This condition is less restrictive than given in the earlier references

  12. Processes influencing migration of bioavailable organic compounds from polymers - investigated during biotic and abiotic testing under static and non-static conditions with varying S/V-ratios

    DEFF Research Database (Denmark)

    Corfitzen, Charlotte B.; Arvin, Erik; Albrechtsen, Hans-Jørgen

    . The bioavailable migration from the polymer surface was influence by diffusion over the solid-liquid boundary layer under sterile conditions, which resulted in an inversely proportionally relationship between bioavailable migration expressed per unit surface area of material and the surface to volume ratio (S/V-ratio...... the effect of the boundary layer, since bioavailable migration was continuously consumed by the bacteria. Thus the driving force for the diffusion process was maintained at a maximum, thereby enhancing the bioavailable migration from the material surfaces. Thus neither non-static conditions nor varying S/V-ratios...

  13. Creep rupture properties under varying load/temperature conditions on a nickel-base heat-resistant alloy strengthened by boron addition

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Tanabe, Tatsuhiko; Nakajima, Hajime

    1994-01-01

    A series of constant load and temperature creep rupture tests and varying load and temperature creep rupture tests was carried out on Hastelloy XR whose boron content level is 60 mass ppm at 900 and 1000 C in order to examine the behavior of the alloy under varying load and temperature conditions. The life fraction rule completely fails in the prediction of the creep rupture life under varying load and temperature conditions though the rule shows good applicability for Hastelloy XR whose boron content level is below 10 mass ppm. The modified life fraction rule has been proposed based on the dependence of the creep rupture strength on the boron content level of the alloy. The modified rule successfully predicts the creep rupture life under the test conditions from 1000 to 900 C. The trend observed in the tests from 900 to 1000 C can be qualitatively explained by the mechanism that the oxide film which is formed during the prior exposure to 900 C plays the role of the protective barrier against the boron dissipation into the environment. (orig.)

  14. Creep rupture properties under varying load/temperature conditions on a nickel-base heat-resistant alloy strengthened by boron addition

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Nakajima, Hajime; Tanabe, Tatsuhiko.

    1993-09-01

    A series of constant load and temperature creep rupture tests and varying load and temperature creep rupture tests was carried out on Hastelloy XR whose boron content level is 60 mass ppm at 900 and 1000degC in order to examine the behavior of the alloy under varying load and temperature conditions. The life fraction rule completely fails in the prediction of the creep rupture life under varying load and temperature conditions though the rule shows good applicability for Hastelloy XR whose boron content level is below 10 mass ppm. The modified life fraction rule has been proposed based on the dependence of the creep rupture strength on the born content level of the alloy. The modified rule successfully predicts the creep rupture life under the test conditions from 1000degC to 900degC. The trend observed in the tests from 900degC to 1000degC can be qualitatively explained by the mechanism that the oxide film which is formed during the prior exposure to 900degC plays the role of the protective barrier against the boron dissipation into the environment. (author)

  15. Identification of Pavement Distress Types and Pavement Condition Evaluation Based on Network Level Inspection for Jazan City Road Network

    Directory of Open Access Journals (Sweden)

    M Mubaraki

    2014-06-01

    Full Text Available The first step in establishing a pavement management system (PMS is road network identification. An important feature of a PMS is the ability to determine the current condition of a road network and predict its future condition. Pavement condition evaluation may involve structure, roughness, surface distress, and safety evaluation. In this study, a pavement distress condition rating procedure was used to achieve the objectives of this study. The main objectives of this study were to identify the common types of distress that exist on the Jazan road network (JRN, either on main roads or secondary roads, and to evaluate the pavement condition based on network level inspection. The study was conducted by collecting pavement distress types from 227 sample units on main roads and 500 sample units from secondary roads. Data were examined through analysis of common types of distress identified in both main and secondary roads. Through these data, pavement condition index (PCI for each sample unit was then calculated. Through these calculations, average PCIs for the main and secondary roads were determined. Results indicated that the most common pavement distress types on main roads were patching and utility cut patching, longitudinal and transverse cracking, polished aggregate, weathering and raveling, and alligator cracking. The most common pavement distress types on secondary roads were weathering and raveling, patching and utility cut patching, longitudinal and transverse cracking, potholes, and alligator cracking. The results also indicated that 65% of Jazan's main road network has an average pavement condition rating of very good while only 30% of Jazan's secondary roads network has an average pavement condition.

  16. Integrated Optimization of Service-Oriented Train Plan and Schedule on Intercity Rail Network with Varying Demand

    Directory of Open Access Journals (Sweden)

    Wenliang Zhou

    2015-01-01

    Full Text Available For a better service level of a train operating plan, we propose an integrated optimization method of train planning and train scheduling, which generally are optimized, respectively. Based on the cost analysis of both passengers travelling and enterprises operation, and the constraint analysis of trains operation, we construct a multiobjective function and build an integrated optimization model with the aim of reducing both passenger travel costs and enterprise operating costs. Then, a solving algorithm is established based on the simulated annealing algorithm. Finally, using as an example the Changzhutan intercity rail network, as an example we analyze the optimized results and the influence of the model parameters on the results.

  17. PAVECHECK : integrating deflection and GPR for network condition surveys.

    Science.gov (United States)

    2009-01-01

    The PAVECHECK data integration and analysis system was developed to merge Falling Weight : Deflectometer (FWD) and Ground Penetrating Radar (GPR) data together with digital video images of : surface conditions. In this study Global Positioning System...

  18. Comparative transcriptome and gene co-expression network analysis reveal genes and signaling pathways adaptively responsive to varied adverse stresses in the insect fungal pathogen, Beauveria bassiana.

    Science.gov (United States)

    He, Zhangjiang; Zhao, Xin; Lu, Zhuoyue; Wang, Huifang; Liu, Pengfei; Zeng, Fanqin; Zhang, Yongjun

    2018-01-01

    Sensing, responding, and adapting to the surrounding environment are crucial for all living organisms to survive, proliferate, and differentiate in their biological niches. Beauveria bassiana is an economically important insect-pathogenic fungus which is widely used as a biocontrol agent to control a variety of insect pests. The fungal pathogen unavoidably encounters a variety of adverse environmental stresses and defense response from the host insects during application of the fungal agents. However, few are known about the transcription response of the fungus to respond or adapt varied adverse stresses. Here, we comparatively analyzed the transcriptome of B. bassiana in globe genome under the varied stationary-phase stresses including osmotic agent (0.8 M NaCl), high temperature (32 °C), cell wall-perturbing agent (Congo red), and oxidative agents (H 2 O 2 or menadione). Total of 12,412 reads were obtained, and mapped to the 6767 genes of the B. bassiana. All of these stresses caused transcription responses involved in basal metabolism, cell wall construction, stress response or cell rescue/detoxification, signaling transduction and gene transcription regulation, and likely other cellular processes. An array of genes displayed similar transcription patterns in response to at least two of the five stresses, suggesting a shared transcription response to varied adverse stresses. Gene co-expression network analysis revealed that mTOR signaling pathway, but not HOG1 MAP kinase pathway, played a central role in regulation the varied adverse stress responses, which was verified by RNAi-mediated knockdown of TOR1. Our findings provided an insight of transcription response and gene co-expression network of B. bassiana in adaptation to varied environments. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Between giant oscillations and uniform distribution of droplets: The role of varying lumen of channels in microfluidic networks.

    Science.gov (United States)

    Cybulski, Olgierd; Jakiela, Slawomir; Garstecki, Piotr

    2015-12-01

    The simplest microfluidic network (a loop) comprises two parallel channels with a common inlet and a common outlet. Recent studies that assumed a constant cross section of the channels along their length have shown that the sequence of droplets entering the left (L) or right (R) arm of the loop can present either a uniform distribution of choices (e.g., RLRLRL...) or long sequences of repeated choices (RRR...LLL), with all the intermediate permutations being dynamically equivalent and virtually equally probable to be observed. We use experiments and computer simulations to show that even small variation of the cross section along channels completely shifts the dynamics either into the strong preference for highly grouped patterns (RRR...LLL) that generate system-size oscillations in flow or just the opposite-to patterns that distribute the droplets homogeneously between the arms of the loop. We also show the importance of noise in the process of self-organization of the spatiotemporal patterns of droplets. Our results provide guidelines for rational design of systems that reproducibly produce either grouped or homogeneous sequences of droplets flowing in microfluidic networks.

  20. Resilience of Networked Infrastructure with Evolving Component Conditions: Pavement Network Application

    DEFF Research Database (Denmark)

    Levenberg, Eyal; Miller-Hooks, Elise; Asadabadi, Ali

    2017-01-01

    This paper deals with quantifying the resilience of a network of pavements. Calculations were carried out by modeling network performance under a set of possible damage-meteorological scenarios with known probability of occurrence. Resilience evaluation was performed a priori while accounting...

  1. Fixed-time synchronization of memristor-based BAM neural networks with time-varying discrete delay.

    Science.gov (United States)

    Chen, Chuan; Li, Lixiang; Peng, Haipeng; Yang, Yixian

    2017-12-01

    This paper is devoted to studying the fixed-time synchronization of memristor-based BAM neural networks (MBAMNNs) with discrete delay. Fixed-time synchronization means that synchronization can be achieved in a fixed time for any initial values of the considered systems. In the light of the double-layer structure of MBAMNNs, we design two similar feedback controllers. Based on Lyapunov stability theories, several criteria are established to guarantee that the drive and response MBAMNNs can realize synchronization in a fixed time. In particular, by changing the parameters of controllers, this fixed time can be adjusted to some desired value in advance, irrespective of the initial values of MBAMNNs. Numerical simulations are included to validate the derived results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Multiple Transcoding Impact on Speech Quality in Ideal Network Conditions

    Directory of Open Access Journals (Sweden)

    Martin Mikulec

    2015-01-01

    Full Text Available This paper deals with the impact of transcoding on the speech quality. We have focused mainly on the transcoding between codecs without the negative influence of the network parameters such as packet loss and delay. It has ensured objective and repeatable results from our measurement. The measurement was performed on the Transcoding Measuring System developed especially for this purpose. The system is based on the open source projects and is useful as a design tool for VoIP system administrators. The paper compares the most used codecs from the transcoding perspective. The multiple transcoding between G711, GSM and G729 codecs were performed and the speech quality of these calls was evaluated. The speech quality was measured by Perceptual Evaluation of Speech Quality method, which provides results in Mean Opinion Score used to describe the speech quality on a scale from 1 to 5. The obtained results indicate periodical speech quality degradation on every transcoding between two codecs.

  3. Power losses in electrical networks depending on weather conditions

    International Nuclear Information System (INIS)

    Zhelezko, Yu. S.; Kostyushko, V. A.; Krylov, S. V.; Nikiforov, E. P.; Savchenko, O. V.; Timashova, L. V.; Solomonik, E. A.

    2005-01-01

    Specific power losses to corona and to leakage currents over overhead insulators are presented for 110 - 750-kV transmission lines with different phase design and pole types for different weather conditions. Consumption of electric energy for ice melting on conductors of various cross sections is evaluated. Meteorological data of 1372 weather stations in Russia are processed for a period of 10 years. The territory of the country is divided into 7 regions with approximately homogeneous weather conditions. Specific power losses to corona and leakage currents over overhead insulators are presented for every region

  4. Conditions of Antonin seam exploitation in the open pit Druzba near Sokolov with regard to the protection of thermal and mineral water resources in Karlovy Vary

    International Nuclear Information System (INIS)

    Grmela, A.; Sterba, J.

    1997-01-01

    From new structural-tectonic findings concerning the extent and character of the Nove Sedlo fault in the area of the Druzba open pit in the Sokolov Basin, it is evident that it is a form of listric fault of shallow range, ending in an intermediate slip. This finding has a decisive relevance for deciding as to the current placement of the pit in the protection zone of Karlovy Vary's thermal springs. For the purposes of the exploitation of the Antonin seam, it is necessary to create a network of multipurpose bore holes at the bottom of the pit and in front of the working face for the regulation of pressure in the basal aquifer and to ensure unity of monitoring and its complex evaluation on the basis of numerical modelling of the hydrodynamic state of the basal aquifer and the geotechnical processes of the seam's impermeable bedrock. 4 refs

  5. Feasibility of Optical Packet Switched WDM Networks without Packet Synchronisation Under Bursty Traffic Conditions

    DEFF Research Database (Denmark)

    Fjelde, Tina; Hansen, Peter Bukhave; Kloch, Allan

    1999-01-01

    We show that complex packet synchronisation may be avoided in optical packetswitched networks. Detailed traffic analysis demonstrates that packet lossratios of 1e-10 are feasible under bursty traffic conditions for a highcapacity network consisting of asynchronously operated add-drop switch...

  6. Network communities as a new form of social organization in conditions of postmodern

    Directory of Open Access Journals (Sweden)

    N. V. Burmaha

    2016-03-01

    Full Text Available This article deals with the approach to interpretation of essence of the network community concept in which we propose to consider it as a new form of social organization that is substantiated by the specificity of how our society is functioning in conditions of Postmodern. There were explored two main approaches to network communities studying: the first approach considers social networks in a classic, traditional interpretation of modernity as a special kind of social structure, and the second one represents social networks as a specific virtual formation, a social structure of virtual Internet reality. There were revealed some common features of a social organization and a network community: presence of permanent communication between members of the group, united by certain common interests and goals, as well as presence of the certain hierarchy among all members of the community, and the rules of conduct, implementation of communication. Distinctive features: network community is more informal, offers its members considerable leeway in the implementation of their own goals and satisfying the needs, full virtualization of communication absence of direct interaction during communication, under conditions where the main resource for the interchange in network communities is information. It was shown that in the process of emergence, development and distribution of network communities, the fundamental role is played by modern communications - namely, unification them in a stable set of interconnected networks and, in particular network communities.

  7. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  8. Use of neural networks to identify transient operating conditions in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Guo, Z.

    1989-01-01

    A technique using neural networks as a means of diagnosing specific abnormal conditions or problems in nuclear power plants is investigated and found to be feasible. The technique is based on the fact that each physical state of the plant can be represented by a unique pattern of instrument readings, which can be related to the condition of the plant. Neural networks are used to relate this pattern to the fault or problem. 3 refs., 2 figs., 4 tabs

  9. FLOWNET: A Computer Program for Calculating Secondary Flow Conditions in a Network of Turbomachinery

    Science.gov (United States)

    Rose, J. R.

    1978-01-01

    The program requires the network parameters, the flow component parameters, the reservoir conditions, and the gas properties as input. It will then calculate all unknown pressures and the mass flow rate in each flow component in the network. The program can treat networks containing up to fifty flow components and twenty-five unknown network pressures. The types of flow components that can be treated are face seals, narrow slots, and pipes. The program is written in both structured FORTRAN (SFTRAN) and FORTRAN 4. The program must be run in an interactive (conversational) mode.

  10. Carbon allocation to major metabolites in illuminated leaves is not just proportional to photosynthesis when gaseous conditions (CO2 and O2 ) vary.

    Science.gov (United States)

    Abadie, Cyril; Bathellier, Camille; Tcherkez, Guillaume

    2018-04-01

    In gas-exchange experiments, manipulating CO 2 and O 2 is commonly used to change the balance between carboxylation and oxygenation. Downstream metabolism (utilization of photosynthetic and photorespiratory products) may also be affected by gaseous conditions but this is not well documented. Here, we took advantage of sunflower as a model species, which accumulates chlorogenate in addition to sugars and amino acids (glutamate, alanine, glycine and serine). We performed isotopic labelling with 13 CO 2 under different CO 2 /O 2 conditions, and determined 13 C contents to compute 13 C-allocation patterns and build-up rates. The 13 C content in major metabolites was not found to be a constant proportion of net fixed carbon but, rather, changed dramatically with CO 2 and O 2 . Alanine typically accumulated at low O 2 (hypoxic response) while photorespiratory intermediates accumulated under ambient conditions and at high photorespiration, glycerate accumulation exceeding serine and glycine build-up. Chlorogenate synthesis was relatively more important under normal conditions and at high CO 2 and its synthesis was driven by phosphoenolpyruvate de novo synthesis. These findings demonstrate that carbon allocation to metabolites other than photosynthetic end products is affected by gaseous conditions and therefore the photosynthetic yield of net nitrogen assimilation varies, being minimal at high CO 2 and maximal at high O 2 . © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

  11. Hydraulic and Condition Assessment of Existing Sewerage Network: A Case Study of an Educational Institute

    Science.gov (United States)

    Sourabh, Nishant; Timbadiya, P. V.

    2018-04-01

    The hydraulic simulation of the existing sewerage network provides various information about critical points to assess the deteriorating condition and help in rehabilitation of existing network and future expansion. In the present study, hydraulic and condition assessment of existing network of educational Institute (i.e. Sardar Vallabhbhai National Institute of Technology-Surat, Gujarat, India), having an area of 100 ha and ground levels in range of 5.0-9.0 m above mean sea level, has been carried out using sewage flow simulation for existing and future scenarios analysis using SewerGEMS v8i. The paper describes the features of 4.79 km long sewerage network of institute followed by network model simulation for aforesaid scenarios and recommendations on improvement of the existing network for future use. The total sewer loads for present and future scenarios are 1.67 million litres per day (MLD) and 3.62 MLD, considering the peak factor of 3 on the basis of population. The hydraulic simulation of the existing scenario indicated depth by diameter (d/D) ratio in the range of 0.02-0.48 and velocity range of 0.08-0.53 m/s for existing network for present scenario. For the future scenario, the existing network is needed to be modified and it was found that total of 11 conduits (length: 464.8 m) should be replaced to the next higher diameter available, i.e., 350 mm for utilization of existing network for future scenario. The present study provides the methodology for condition assessment of existing network and its utilization as per guidelines provided by Central Public Health and Environmental Engineering Organization, 2013. The methodology presented in this paper can be used by municipal/public health engineer for the assessment of existing sewerage network for its serviceability and improvement in future.

  12. Optimization of hydrostatic pressure at varied sonication conditions--power density, intensity, very low frequency--for isothermal ultrasonic sludge treatment.

    Science.gov (United States)

    Delmas, Henri; Le, Ngoc Tuan; Barthe, Laurie; Julcour-Lebigue, Carine

    2015-07-01

    This work aims at investigating for the first time the key sonication (US) parameters: power density (DUS), intensity (IUS), and frequency (FS) - down to audible range, under varied hydrostatic pressure (Ph) and low temperature isothermal conditions (to avoid any thermal effect). The selected application was activated sludge disintegration, a major industrial US process. For a rational approach all comparisons were made at same specific energy input (ES, US energy per solid weight) which is also the relevant economic criterion. The decoupling of power density and intensity was obtained by either changing the sludge volume or most often by changing probe diameter, all other characteristics being unchanged. Comprehensive results were obtained by varying the hydrostatic pressure at given power density and intensity. In all cases marked maxima of sludge disintegration appeared at optimum pressures, which values increased at increasing power intensity and density. Such optimum was expected due to opposite effects of increasing hydrostatic pressure: higher cavitation threshold then smaller and fewer bubbles, but higher temperature and pressure at the end of collapse. In addition the first attempt to lower US frequency down to audible range was very successful: at any operation condition (DUS, IUS, Ph, sludge concentration and type) higher sludge disintegration was obtained at 12 kHz than at 20 kHz. The same values of optimum pressure were observed at 12 and 20 kHz. At same energy consumption the best conditions - obtained at 12 kHz, maximum power density 720 W/L and 3.25 bar - provided about 100% improvement with respect to usual conditions (1 bar, 20 kHz). Important energy savings and equipment size reduction may then be expected. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Corrosion study of API 5L x-series pipeline steels in 3.5% NaCl solution under varying conditions

    International Nuclear Information System (INIS)

    Shahid, M.; Qureshi, M.I.; Farooq, M.U.; Khan, M.I.

    2003-01-01

    Pipelines provide convenient and efficient means for mass transportation of variety of fluids, such as oil and gas, over varying distances. In the last two decades or so, pipeline designers focused mainly on the usage of larger sizes and higher operating pressures for achieving higher transportation efficiency. This has been accomplished through the provision of steels with progressive increase in yield strength coupled with good weldability and sufficient toughness to restrict crack propagation. In addition to higher strength and toughness, developing pipeline technologies have required improved resistance to corrosion, which has been tried with specific alloy additions and special control over non-metallic inclusions. Corrosion investigations were carried out on various grades of pipeline steels (API 5L X-46, X-52, X-56, X-60 and X- 70) under varying environmental conditions. This paper describes the results pertaining to corrosion behavior of the steels in 3.5% NaCl solutions in stagnant, turbulent and deaerated conditions. It was found that all grades corrode in this solution and their corrosion potentials and corrosion currents are in close vicinity of each other. Turbulent solutions, however, have shown an increase in corrosion rates whereas deaeration has revealed a relative decrease in aggressivity of the electrolyte. (author)

  14. Solute transport in streams of varying morphology inferred from a high resolution network of potentiometric wireless chloride sensors

    Science.gov (United States)

    Klaus, Julian; Smettem, Keith; Pfister, Laurent; Harris, Nick

    2017-04-01

    There is ongoing interest in understanding and quantifying the travel times and dispersion of solutes moving through stream environments, including the hyporheic zone and/or in-channel dead zones where retention affects biogeochemical cycling processes that are critical to stream ecosystem functioning. Modelling these transport and retention processes requires acquisition of tracer data from injection experiments where the concentrations are recorded downstream. Such experiments are often time consuming and costly, which may be the reason many modelling studies of chemical transport have tended to rely on relatively few well documented field case studies. This leads to the need of fast and cheap distributed sensor arrays that respond instantly and record chemical transport at points of interest on timescales of seconds at various locations in the stream environment. To tackle this challenge we present data from several tracer experiments carried out in the Attert river catchment in Luxembourg employing low-cost (in the order of a euro per sensor) potentiometric chloride sensors in a distributed array. We injected NaCl under various baseflow conditions in streams of different morphologies and observed solute transport at various distances and locations. This data is used to benchmark the sensors to data obtained from more expensive electrical conductivity meters. Furthermore, the data allowed spatial resolution of hydrodynamic mixing processes and identification of chemical 'dead zones' in the study reaches.

  15. Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data

    Science.gov (United States)

    Kennedy, Jeffrey R.; Ferre, Ty P.A.

    2015-01-01

    The relative gravimeter is the primary terrestrial instrument for measuring spatially and temporally varying gravitational fields. The background noise of the instrument—that is, non-linear drift and random tares—typically requires some form of least-squares network adjustment to integrate data collected during a campaign that may take several days to weeks. Here, we present an approach to remove the change in the observed relative-gravity differences caused by hydrologic or other transient processes during a single campaign, so that the adjusted gravity values can be referenced to a single epoch. The conceptual approach is an example of coupled hydrogeophysical inversion, by which a hydrologic model is used to inform and constrain the geophysical forward model. The hydrologic model simulates the spatial variation of the rate of change of gravity as either a linear function of distance from an infiltration source, or using a 3-D numerical groundwater model. The linear function can be included in and solved for as part of the network adjustment. Alternatively, the groundwater model is used to predict the change of gravity at each station through time, from which the accumulated gravity change is calculated and removed from the data prior to the network adjustment. Data from a field experiment conducted at an artificial-recharge facility are used to verify our approach. Maximum gravity change due to hydrology (observed using a superconducting gravimeter) during the relative-gravity field campaigns was up to 2.6 μGal d−1, each campaign was between 4 and 6 d and one month elapsed between campaigns. The maximum absolute difference in the estimated gravity change between two campaigns, two months apart, using the standard network adjustment method and the new approach, was 5.5 μGal. The maximum gravity change between the same two campaigns was 148 μGal, and spatial variation in gravity change revealed zones of preferential infiltration and areas of relatively

  16. Tribological and Wear Performance of Carbide Tools with TiB2 PVD Coating under Varying Machining Conditions of TiAl6V4 Aerospace Alloy

    Directory of Open Access Journals (Sweden)

    Jose Mario Paiva

    2017-11-01

    Full Text Available Tribological phenomena and tool wear mechanisms during machining of hard-to-cut TiAl6V4 aerospace alloy have been investigated in detail. Since cutting tool wear is directly affected by tribological phenomena occurring between the surfaces of the workpiece and the cutting tool, the performance of the cutting tool is strongly associated with the conditions of the machining process. The present work shows the effect of different machining conditions on the tribological and wear performance of TiB2-coated cutting tools compared to uncoated carbide tools. FEM modeling of the temperature profile on the friction surface was performed for wet machining conditions under varying cutting parameters. Comprehensive characterization of the TiB2 coated vs. uncoated cutting tool wear performance was made using optical 3D imaging, SEM/EDX and XPS methods respectively. The results obtained were linked to the FEM modeling. The studies carried out show that during machining of the TiAl6V4 alloy, the efficiency of the TiB2 coating application for carbide cutting tools strongly depends on cutting conditions. The TiB2 coating is very efficient under roughing at low speeds (with strong buildup edge formation. In contrast, it shows similar wear performance to the uncoated tool under finishing operations at higher cutting speeds when cratering wear predominates.

  17. Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal versus Visible Spectrum Video-Based Systems

    Directory of Open Access Journals (Sweden)

    Ting Fu

    2017-01-01

    Full Text Available Vision-based monitoring systems using visible spectrum (regular video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Although new camera technologies, including thermal video sensors, may improve the performance of digital video-based sensors, their performance under various conditions has rarely been evaluated at multimodal facilities. The purpose of this research is to integrate existing computer vision methods for automated data collection and evaluate the detection, classification, and speed measurement performance of thermal video sensors under varying lighting and temperature conditions. Thermal and regular video data was collected simultaneously under different conditions across multiple sites. Although the regular video sensor narrowly outperformed the thermal sensor during daytime, the performance of the thermal sensor is significantly better for low visibility and shadow conditions, particularly for pedestrians and cyclists. Retraining the algorithm on thermal data yielded an improvement in the global accuracy of 48%. Thermal speed measurements were consistently more accurate than for the regular video at daytime and nighttime. Thermal video is insensitive to lighting interference and pavement temperature, solves issues associated with visible light cameras for traffic data collection, and offers other benefits such as privacy, insensitivity to glare, storage space, and lower processing requirements.

  18. Wireless Sensor Network Quality of Service Improvement on Flooding Attack Condition

    Science.gov (United States)

    Hartono, R.; Widyawan; Wibowo, S. B.; Purnomo, A.; Hartatik

    2018-03-01

    There are two methods of building communication using wireless media. The first method is building a base infrastructure as an intermediary between users. Problems that arise on this type of network infrastructure is limited space to build any network physical infrastructure and also the cost factor. The second method is to build an ad hoc network between users who will communicate. On ad hoc network, each user must be willing to send data from source to destination for the occurrence of a communication. One of network protocol in Ad Hoc, Ad hoc on demand Distance Vector (AODV), has the smallest overhead value, easier to adapt to dynamic network and has small control message. One AODV protocol’s drawback is route finding process’ security for sending the data. In this research, AODV protocol is optimized by determining Expanding Ring Search (ERS) best value. Random topology is used with variation in the number of nodes: 25, 50, 75, 100, 125 and 150 with node’s speed of 10m/s in the area of 1000m x 1000m on flooding network condition. Parameters measured are Throughput, Packet Delivery Ratio, Average Delay and Normalized Routing Load. From the test results of AODV protocol optimization with best value of Expanding Ring Search (ERS), throughput increased by 5.67%, packet delivery ratio increased by 5.73%, and as for Normalized Routing Load decreased by 4.66%. ERS optimal value for each node’s condition depending on the number of nodes on the network.

  19. The effect of bedload transport rates on bedform and planform morphological development in a laboratory meandering stream under varying flow conditions

    Science.gov (United States)

    Sullivan, C.; Good, R. G. R.; Binns, A. D.

    2017-12-01

    Sediment transport processes in streams provides valuable insight into the temporal evolution of planform and bedform geometry. The majority of previous experimental research in the literature has focused on bedload transport and corresponding bedform development in rectangular, confined channels, which does not consider planform adjustment processes in streams. In contrast, research conducted with laboratory streams having movable banks can investigate planform development in addition to bedform development, which is more representative of natural streams. The goal of this research is to explore the relationship between bedload transport rates and the morphological adjustments in meandering streams. To accomplish this, a series of experimental runs were conducted in a 5.6 m by 1.9 m river basin flume at the University of Guelph to analyze the bedload impacts on bed formations and planform adjustments in response to varying flow conditions. In total, three experimental runs were conducted: two runs using steady state conditions and one run using unsteady flow conditions in the form of a symmetrical hydrograph implementing quasi steady state flow. The runs were performed in a series of time-steps in order to monitor the evolution of the stream morphology and the bedload transport rates. Structure from motion (SfM) was utilized to capture the channel morphology after each time-step, and Agisoft PhotoScan software was used to produce digital elevation models to analyze the morphological evolution of the channel with time. Bedload transport rates were quantified using a sediment catch at the end of the flume. Although total flow volumes were similar for each run, the morphological evolution and bedload transport rates in each run varied. The observed bedload transport rates from the flume are compared with existing bedload transport formulas to assess their accuracy with respect to sediment transport in unconfined meandering channels. The measured sediment transport

  20. On the formation of sulphuric acid – amine clusters in varying atmospheric conditions and its influence on atmospheric new particle formation

    Directory of Open Access Journals (Sweden)

    I. K. Ortega

    2012-10-01

    Full Text Available Sulphuric acid is a key component in atmospheric new particle formation. However, sulphuric acid alone does not form stable enough clusters to initiate particle formation in atmospheric conditions. Strong bases, such as amines, have been suggested to stabilize sulphuric acid clusters and thus participate in particle formation. We modelled the formation rate of clusters with two sulphuric acid and two amine molecules (JA2B2 at varying atmospherically relevant conditions with respect to concentrations of sulphuric acid ([H2SO4], dimethylamine ([DMA] and trimethylamine ([TMA], temperature and relative humidity (RH. We also tested how the model results change if we assume that the clusters with two sulphuric acid and two amine molecules would act as seeds for heterogeneous nucleation of organic vapours (other than amines with higher atmospheric concentrations than sulphuric acid. The modelled formation rates JA2B2 were functions of sulphuric acid concentration with close to quadratic dependence, which is in good agreement with atmospheric observations of the connection between the particle formation rate and sulphuric acid concentration. The coefficients KA2B2 connecting the cluster formation rate and sulphuric acid concentrations as JA2B2=KA2B2[H2SO4]2 turned out to depend also on amine concentrations, temperature and relative humidity. We compared the modelled coefficients KA2B2 with the corresponding coefficients calculated from the atmospheric observations (Kobs from environments with varying temperatures and levels of anthropogenic influence. By taking into account the modelled behaviour of JA2B2 as a function of [H2SO4], temperature and RH, the atmospheric particle formation rate was reproduced more closely than with the traditional semi-empirical formulae based on sulphuric acid concentration only. The formation rates of clusters with two sulphuric acid and two amine molecules with different amine compositions (DMA or TMA or one of both had

  1. WMAXC: a weighted maximum clique method for identifying condition-specific sub-network.

    Directory of Open Access Journals (Sweden)

    Bayarbaatar Amgalan

    Full Text Available Sub-networks can expose complex patterns in an entire bio-molecular network by extracting interactions that depend on temporal or condition-specific contexts. When genes interact with each other during cellular processes, they may form differential co-expression patterns with other genes across different cell states. The identification of condition-specific sub-networks is of great importance in investigating how a living cell adapts to environmental changes. In this work, we propose the weighted MAXimum clique (WMAXC method to identify a condition-specific sub-network. WMAXC first proposes scoring functions that jointly measure condition-specific changes to both individual genes and gene-gene co-expressions. It then employs a weaker formula of a general maximum clique problem and relates the maximum scored clique of a weighted graph to the optimization of a quadratic objective function under sparsity constraints. We combine a continuous genetic algorithm and a projection procedure to obtain a single optimal sub-network that maximizes the objective function (scoring function over the standard simplex (sparsity constraints. We applied the WMAXC method to both simulated data and real data sets of ovarian and prostate cancer. Compared with previous methods, WMAXC selected a large fraction of cancer-related genes, which were enriched in cancer-related pathways. The results demonstrated that our method efficiently captured a subset of genes relevant under the investigated condition.

  2. Using modular neural networks to monitor accident conditions in nuclear power plants

    International Nuclear Information System (INIS)

    Guo, Z.

    1992-01-01

    Nuclear power plants are very complex systems. The diagnoses of transients or accident conditions is very difficult because a large amount of information, which is often noisy, or intermittent, or even incomplete, need to be processed in real time. To demonstrate their potential application to nuclear power plants, neural networks axe used to monitor the accident scenarios simulated by the training simulator of TVA's Watts Bar Nuclear Power Plant. A self-organization network is used to compress original data to reduce the total number of training patterns. Different accident scenarios are closely related to different key parameters which distinguish one accident scenario from another. Therefore, the accident scenarios can be monitored by a set of small size neural networks, called modular networks, each one of which monitors only one assigned accident scenario, to obtain fast training and recall. Sensitivity analysis is applied to select proper input variables for modular networks

  3. Reconstruction of Oryza sativa indica Genome Scale Metabolic Model and Its Responses to Varying RuBisCO Activity, Light Intensity, and Enzymatic Cost Conditions

    Directory of Open Access Journals (Sweden)

    Ankita Chatterjee

    2017-11-01

    Full Text Available To combat decrease in rice productivity under different stresses, an understanding of rice metabolism is needed. Though there are different genome scale metabolic models (GSMs of Oryza sativa japonica, no GSM with gene-protein-reaction association exist for Oryza sativa indica. Here, we report a GSM, OSI1136 of O.s. indica, which includes 3602 genes and 1136 metabolic reactions and transporters distributed across the cytosol, mitochondrion, peroxisome, and chloroplast compartments. Flux balance analysis of the model showed that for varying RuBisCO activity (Vc/Vo (i the activity of the chloroplastic malate valve increases to transport reducing equivalents out of the chloroplast under increased photorespiratory conditions and (ii glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase can act as source of cytosolic ATP under decreased photorespiration. Under increasing light conditions we observed metabolic flexibility, involving photorespiration, chloroplastic triose phosphate and the dicarboxylate transporters of the chloroplast and mitochondrion for redox and ATP exchanges across the intracellular compartments. Simulations under different enzymatic cost conditions revealed (i participation of peroxisomal glutathione-ascorbate cycle in photorespiratory H2O2 metabolism (ii different modes of the chloroplastic triose phosphate transporters and malate valve, and (iii two possible modes of chloroplastic Glu–Gln transporter which were related with the activity of chloroplastic and cytosolic isoforms of glutamine synthetase. Altogether, our results provide new insights into plant metabolism.

  4. Differences in nutrient uptake capacity of the benthic filamentous algae Cladophora sp., Klebsormidium sp. and Pseudanabaena sp. under varying N/P conditions.

    Science.gov (United States)

    Liu, Junzhuo; Vyverman, Wim

    2015-03-01

    The N/P ratio of wastewater can vary greatly and directly affect algal growth and nutrient removal process. Three benthic filamentous algae species Cladophora sp., Klebsormidium sp. and Pseudanabaena sp. were isolated from a periphyton bioreactor and cultured under laboratory conditions on varying N/P ratios to determine their ability to remove nitrate and phosphorus. The N/P ratio significantly influenced the algal growth and phosphorus uptake process. Appropriate N/P ratios for nitrogen and phosphorus removal were 5-15, 7-10 and 7-20 for Cladophora sp., Klebsormidium sp. and Pseudanabaena sp., respectively. Within these respective ranges, Cladophora sp. had the highest biomass production, while Pseudanabaena sp. had the highest nitrogen and phosphorus contents. This study indicated that Cladophora sp. had a high capacity of removing phosphorus from wastewaters of low N/P ratio, and Pseudanabaena sp. was highly suitable for removing nitrogen from wastewaters with high N/P ratio. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition

    Science.gov (United States)

    Paul, R R; Mukherjee, A; Dutta, P K; Banerjee, S; Pal, M; Chatterjee, J; Chaudhuri, K; Mukkerjee, K

    2005-01-01

    Aim: To describe a novel neural network based oral precancer (oral submucous fibrosis; OSF) stage detection method. Method: The wavelet coefficients of transmission electron microscopy images of collagen fibres from normal oral submucosa and OSF tissues were used to choose the feature vector which, in turn, was used to train the artificial neural network. Results: The trained network was able to classify normal and oral precancer stages (less advanced and advanced) after obtaining the image as an input. Conclusions: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions. PMID:16126873

  6. Young adults with mental health conditions and social networking websites: seeking tools to build community.

    Science.gov (United States)

    Gowen, Kris; Deschaine, Matthew; Gruttadara, Darcy; Markey, Dana

    2012-01-01

    This study examined ways that young adults with mental illnesses (1) currently use social networking; and (2) how they would like to use a social networking site tailored for them. The authors examined differences between those with mental health conditions and those without. An online survey was administered by the National Alliance on Mental Illness (NAMI) to 274 participants; of those, 207 reported being between 18 and 24 years old. The survey included questions about current social networking use, the key resources respondents believed young adults living with mental illness need, and the essential components that should be included in a social networking site specifically tailored to young adults living with mental illness. Pearson Chi-square analyses examined the differences between those who reported having a mental illness and those who did not. Results indicate that almost all (94%) participants with mental illnesses currently use social networking sites. Individuals living with a mental illness are more likely than those not living with a mental illness to report engaging in various social networking activities that promote connectivity and making online friends. Individuals living with mental illnesses are also more likely to report wanting resources on independent living skills and overcoming social isolation available on a social networking site. Young adults living with mental illnesses are currently using social networking sites and express high interest in a social networking site specifically tailored to their population with specific tools designed to decrease social isolation and help them live more independently. These results indicate that practitioners should themselves be aware of the different social networking sites frequented by their young adult clients, ask clients about their use of social networking, and encourage safe and responsible online behaviors.

  7. Seed banks as a source of vegetation regeneration to support the recovery of degraded rivers: A comparison of river reaches of varying condition.

    Science.gov (United States)

    O'Donnell, Jessica; Fryirs, Kirstie A; Leishman, Michelle R

    2016-01-15

    Anthropogenic disturbance has contributed to widespread geomorphic adjustment and the degradation of many rivers. This research compares for river reaches of varying condition, the potential for seed banks to support geomorphic river recovery through vegetation regeneration. Seven river reaches in the lower Hunter catchment of south-eastern Australia were assessed as being in poor, moderate, or good condition, based on geomorphic and ecological indicators. Seed bank composition within the channel and floodplain (determined in a seedling emergence study) was compared to standing vegetation. Seed bank potential for supporting geomorphic recovery was assessed by measuring native species richness, and the abundance of different plant growth forms, with consideration of the roles played by different growth forms in geomorphic adjustment. The exotic seed bank was considered a limiting factor for achieving ecological restoration goals, and similarly analysed. Seed bank native species richness was comparable between the reaches, and regardless of condition, early successional and pioneer herbs, sedges, grasses and rushes dominated the seed bank. The capacity for these growth forms to colonise and stabilise non-cohesive sediments and initiate biogeomorphic succession, indicates high potential for the seed banks of even highly degraded reaches to contribute to geomorphic river recovery. However, exotic propagules increasingly dominated the seed banks of moderate and poor condition reaches and reflected increasing encroachment by terrestrial exotic vegetation associated with riparian degradation. As the degree of riparian degradation increases, the resources required to control the regeneration of exotic species will similarly increase, if seed bank-based regeneration is to contribute to both geomorphic and ecological restoration goals. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. A method comparison of total and HMW adiponectin: HMW/total adiponectin ratio varies versus total adiponectin, independent of clinical condition.

    Science.gov (United States)

    van Andel, Merel; Drent, Madeleine L; van Herwaarden, Antonius E; Ackermans, Mariëtte T; Heijboer, Annemieke C

    2017-02-01

    Total and high-molecular-weight (HMW) adiponectin have been associated with endocrine and cardiovascular pathology. As no gold standard is available, the discussion about biological relevance of isoforms is complicated. In our study we perform a method comparison between two commercially available assays measuring HMW and total adiponectin, in various patient groups, thus contributing further to this discussion. We determined levels of HMW and total adiponectin using assays by Lumipulse® and Millipore® respectively, in 126 patients with different clinical characteristics (n=29 healthy volunteers, n=22 dialysis patients, n=25 elderly with body mass index (BMI) LUMIPULSE ∗0.5-0.9=total adiponectin MILLIPORE , albeit with significant deviation from linearity (p<0.001). Pearson's correlation was R=0.987 (p=0.000). No significant differences between patient groups were observed (p=0.190). The HMW/total adiponectin ratio varies with total adiponectin concentration independent of clinical conditions studied. Our results imply that total and HMW adiponectin have similar utility when assessing adiponectin levels in blood, as the ratio is independent of clinical condition. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Effects of Varying RedoxConditions on Natural Attenuation of Inorganic Contaminants from the D-Area Coal Pile Runoff Basin (U)

    Energy Technology Data Exchange (ETDEWEB)

    Kaplan, D

    2004-05-30

    The objective of this study was to provide geochemical parameters to characterize the D-Area Coal Pile Runoff Basin (DCPRB) sediment as a potential source term. It is anticipated that the measured values will be used in risk calculations and will provide additional technical support for imposing Monitored Natural Attenuation at D-Area. This study provides a detailed evaluation of the DCPRB sediment and is part of another study that quantified the Monitored Natural Attenuation of inorganic contaminants more broadly at the D-Area Expanded Operable Unit, which includes the DCPRB (Powell et al. 2004). Distribution coefficients (K{sub d} values; a solid to liquid contaminant concentration ratio) and the Potentially Leachable Fraction (the percent of the total contaminant concentration in the sediment that can likely contribute to a contaminant plume) were measured in a DCPRB sediment as a function of redox conditions. Redox conditions at the DCPRB are expected to vary greatly as the system undergoes varying drying and flooding conditions. Conservative values; K{sub d} values that err on the side of being too low and Potentially Leachable Fraction values that err on the side of being too high, are presented. The K{sub d} values are high compared to conservative literature values, and underscores the importance of measuring site-specific values to provide estimates of sediments natural attenuation/sorption capacities. The Potentially Leachable Fraction indicates that as little as 27% of the As, but all of the Cu and Tl will be part of the source term. In the case of the As, the remaining 83% will likely never leach out of the sediment, thereby providing a form of natural attenuation. Importantly, Be, Cr, Cu, Ni, and V concentrations in the sediment were less-than twice background levels, indicating this sediment was not a potential source for these contaminants. K{sub d} values generally increased significantly (As, Cd, Co, Cr, Cu, Ni, Se, and Tl) when the sediment was

  10. Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

    Science.gov (United States)

    Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

    2014-12-01

    Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

    Directory of Open Access Journals (Sweden)

    Fei Xiao

    Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

  12. Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

    Science.gov (United States)

    Du, Yuanwei; Guo, Yubin

    2015-01-01

    The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

  13. ON THE MANAGEMENT OF URBAN ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

    Directory of Open Access Journals (Sweden)

    M. А. Fursanov

    2018-01-01

    Full Text Available The issues of prospective operation of the city electric networks in the conditions of the MART GRID, which will be quite different as compared to the traditional understanding and approaches, are under consideration. This requires the selection and application of appropriate analytical criteria and approaches to assessment, analysis and control of the networks. With this regard the following criteria are recommended: in a particular case – the optimal (minimal technological electric power consumption (losses, while in general – economically reasonable (minimal cost value of electric power transmission. It should be also borne in mind that contemporary urban networks are actively saturated with distributed sources of small generation that have radically changed the structure of electrical networks; therefore, account for such sources is an absolutely necessary objective of management regimes of urban electric networks, both traditional and in associated with the SMART GRID. A case of the analysis and control of urban electric 10 kV networks with distributed small sources of generation has been developed and presented according to the theoretical criterion of minimum relative active power losses in the circuit as a control case. The conducted research makes it possible to determine the magnitude of the tolerance network mode from the point of the theoretical minimum. 

  14. A new delay-independent condition for global robust stability of neural networks with time delays.

    Science.gov (United States)

    Samli, Ruya

    2015-06-01

    This paper studies the problem of robust stability of dynamical neural networks with discrete time delays under the assumptions that the network parameters of the neural system are uncertain and norm-bounded, and the activation functions are slope-bounded. By employing the results of Lyapunov stability theory and matrix theory, new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for delayed neural networks are presented. The results reported in this paper can be easily tested by checking some special properties of symmetric matrices associated with the parameter uncertainties of neural networks. We also present a numerical example to show the effectiveness of the proposed theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. A Sufficient Condition on Convex Relaxation of AC Optimal Power Flow in Distribution Networks

    DEFF Research Database (Denmark)

    Huang, Shaojun; Wu, Qiuwei; Wang, Jianhui

    2016-01-01

    This paper proposes a sufficient condition for the convex relaxation of AC Optimal Power Flow (OPF) in radial distribution networks as a second order cone program (SOCP) to be exact. The condition requires that the allowed reverse power flow is only reactive or active, or none. Under the proposed...... solution of the SOCP can be converted to an optimal solution of the original AC OPF. The efficacy of the convex relaxation to solve the AC OPF is demonstrated by case studies of an optimal multi-period planning problem of electric vehicles (EVs) in distribution networks....... sufficient condition, the feasible sub-injection region (power injections of nodes excluding the root node) of the AC OPF is convex. The exactness of the convex relaxation under the proposed condition is proved through constructing a group of monotonic series with limits, which ensures that the optimal...

  16. Modelling the Cost Performance of a Given Logistics Network Operating Under Regular and Irregular Conditions

    NARCIS (Netherlands)

    Janic, M.

    2009-01-01

    This paper develops an analytical model for the assessment of the cost performance of a given logistics network operating under regular and irregular (disruptive) conditions. In addition, the paper aims to carry out a sensitivity analysis of this cost with respect to changes of the most influencing

  17. Exploiting deep neural networks and head movements for binaural localisation of multiple speakers in reverberant conditions

    DEFF Research Database (Denmark)

    Ma, Ning; Brown, Guy J.; May, Tobias

    2015-01-01

    This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for binaural localisation of multiple speakers in reverberant conditions. DNNs are used to map binaural features, consisting of the complete crosscorrelation function (CCF) and interaural...

  18. Engine combustion network (Ecn) : characterization and comparison of boundary conditions for different combustion vessels

    NARCIS (Netherlands)

    Meijer, M.; Somers, L.M.T.; Johnson, J.; Naber, J.; Lee, S.Y.; Malbec, L.M.; Bruneaux, G.; Pickett, L.M.; Bardi, M.; Payri, R.; Bazyn, T.

    2012-01-01

    The Engine Combustion Network (ECN) is a worldwide group of institutions using combustion vessels and/or performing computational fluid dynamics (CFD) simulation, whose aim is to advance the state of spray and combustion knowledge at engine-relevant conditions. A key activity is the use of spray

  19. Fibril growth kinetics link buffer conditions and topology of 3D collagen I networks.

    Science.gov (United States)

    Kalbitzer, Liv; Pompe, Tilo

    2018-02-01

    Three-dimensional fibrillar networks reconstituted from collagen I are widely used as biomimetic scaffolds for in vitro and in vivo cell studies. Various physicochemical parameters of buffer conditions for in vitro fibril formation are well known, including pH-value, ion concentrations and temperature. However, there is a lack of a detailed understanding of reconstituting well-defined 3D network topologies, which is required to mimic specific properties of the native extracellular matrix. We screened a wide range of relevant physicochemical buffer conditions and characterized the topology of the reconstituted 3D networks in terms of mean pore size and fibril diameter. A congruent analysis of fibril formation kinetics by turbidimetry revealed the adjustment of the lateral growth phase of fibrils by buffer conditions to be key in the determination of pore size and fibril diameter of the networks. Although the kinetics of nucleation and linear growth phase were affected by buffer conditions as well, network topology was independent of those two growth phases. Overall, the results of our study provide necessary insights into how to engineer 3D collagen matrices with an independent control over topology parameters, in order to mimic in vivo tissues in in vitro experiments and tissue engineering applications. The study reports a comprehensive analysis of physicochemical conditions of buffer solutions to reconstitute defined 3D collagen I matrices. By a combined analysis of network topology, i.e., pore size and fibril diameter, and the kinetics of fibril formation we can reveal the dependence of 3D network topology on buffer conditions, such as pH-value, phosphate concentration and sodium chloride content. With those results we are now able to provide engineering strategies to independently tune the topology parameters of widely used 3D collagen scaffolds based on the buffer conditions. By that, we enable the straightforward mimicking of extracellular matrices of in vivo

  20. Consistent initial conditions for the Saint-Venant equations in river network modeling

    Directory of Open Access Journals (Sweden)

    C.-W. Yu

    2017-09-01

    Full Text Available Initial conditions for flows and depths (cross-sectional areas throughout a river network are required for any time-marching (unsteady solution of the one-dimensional (1-D hydrodynamic Saint-Venant equations. For a river network modeled with several Strahler orders of tributaries, comprehensive and consistent synoptic data are typically lacking and synthetic starting conditions are needed. Because of underlying nonlinearity, poorly defined or inconsistent initial conditions can lead to convergence problems and long spin-up times in an unsteady solver. Two new approaches are defined and demonstrated herein for computing flows and cross-sectional areas (or depths. These methods can produce an initial condition data set that is consistent with modeled landscape runoff and river geometry boundary conditions at the initial time. These new methods are (1 the pseudo time-marching method (PTM that iterates toward a steady-state initial condition using an unsteady Saint-Venant solver and (2 the steady-solution method (SSM that makes use of graph theory for initial flow rates and solution of a steady-state 1-D momentum equation for the channel cross-sectional areas. The PTM is shown to be adequate for short river reaches but is significantly slower and has occasional non-convergent behavior for large river networks. The SSM approach is shown to provide a rapid solution of consistent initial conditions for both small and large networks, albeit with the requirement that additional code must be written rather than applying an existing unsteady Saint-Venant solver.

  1. Assessing and monitoring the effects of filter material amendments on the biophysicochemical properties during composting of solid winery waste under open field and varying climatic conditions.

    Science.gov (United States)

    Mtimkulu, Y; Meyer, A H; Mulidzi, A R; Shange, P L; Nchu, F

    2017-01-01

    Waste management in winery and distillery industries faces numerous disposal challenges as large volumes of both liquid and solid waste by-products are generated yearly during cellar practices. Composting has been suggested as a feasible option to beneficiate solid organic waste. This incentivized the quest for efficient composting protocols to be put in place. The objective of this study was to experiment with different composting strategies for spent winery solid waste. Compost materials consisting of chopped pruning grape stalks, skins, seed and spent wine filter material consisting of a mixture of organic and inorganic expend ingredients were mixed in compost heaps. The filter material component varied (in percentage) among five treatments: T1 (40%) lined, T2 (20%) lined, T3 (0%) lined, T4 (40%) ground material, lined and T5 (40%) unlined. Composting was allowed to proceed under open field conditions over 12months, from autumn to summer. Indicators such as temperature, moisture, enzyme activities, microbial counts, pH, and C/N ratio, were recorded. Generally, season (df=3, 16, Pwinery solid waste. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. The improving of the heat networks operating process under the conditions of the energy efficiency providing

    Directory of Open Access Journals (Sweden)

    Blinova Tatiana

    2016-01-01

    Full Text Available Among the priorities it is important to highlight the modernization and improvement of energy efficiency of housing and communal services, as well as the transition to the principle of using the most efficient technologies used in reproduction (construction, creation of objects of municipal infrastructure and housing modernization. The main hypothesis of this study lies in the fact that in modern conditions the realization of the most important priorities of the state policy in the sphere of housing and communal services, is possible in the conditions of use of the most effective control technologies for the reproduction of thermal networks. It is possible to raise the level of information security Heat Distribution Company, and other market participants by improving business processes through the development of organizational and economic mechanism in the conditions of complex monitoring of heat network operation processes

  3. Variability of the morphometric features of Calliphora vicina (Diptera, Calliphoridae under the varying and constant micro-climatic condi-tions

    Directory of Open Access Journals (Sweden)

    L. I. Faly

    2013-03-01

    Full Text Available Variability of the main morphometric features of imago flies Calliphora vicina R.-D. (Diptera, Calliphoridae of two samples was studied. First sample consists of individuals caught in the wild (park ecosystems of Dnipropetrovsk, the second one – specimens cultured in the laboratory under the constant temperature and humidity. Possible using of C. vicina R.-D. as a bioindicator of anthropogenic factors is analysed. Environmental factors may act as the stimulators of adaptive changes in physiological functions, as the constraints that cause impossibility of the existence of certain species in particular conditions, and as modifiers that determine the morpho- anatomical and physiological changes in organisms. The most significant differences between studied samples were found for the width (“laboratory” individuals are characterized by larger head size and for the length of limbs segments. The fluctuating range of the head width in specimens collected in the wild is much wider, due to the heterogeneity of the micro-climatic conditions of the larvae development and trophic resources. Maximal negative asymmetry of the head width is observed in individuals C. vicina R.-D. of the “natural” sample as compared with “laboratory” individuals. Among imagoes caught in the wild the individuals with a relatively wide head are dominated, as evidenced by the large positive value of kurtosis. At the same time, the distribution of values in “laboratory” individuals is almost normal. In adults bred in the laboratory the shortening of segments of the leg pair I is observed in comparison with the individuals of “natural” sample. Similar results were recorded for other insect groups cultivated in a laboratory. For most other linear measurements of the C. vicina R.-D. body the differences between samples are not registered. Ephemeral existence of the substrate of blow flies leads to higher prevailing evolutionary adaptation of species to varying

  4. Conservadorismo condicional: estudo a partir de variáveis econômicas Conditional conservatism: a study based on economic variables

    Directory of Open Access Journals (Sweden)

    Rafael de Lacerda Moreira

    2010-12-01

    Full Text Available A Contabilidade, na perspectiva da abordagem da informação, volta-se à utilidade da informação. O Conservadorismo Condicional está ligado à tendência de a Contabilidade exigir um maior grau de verificação das boas notícias para reconhecê-las no resultado em relação ao grau de verificação das más notícias. Em face das preocupações referentes à qualidade da informação contábil, o objetivo deste artigo consiste em analisar o reflexo do Conservadorismo Condicional no resultado contábil a partir de variáveis econômicas. O estudo utiliza o Modelo Reverso de Lucros Associados a Retornos (BASU, 1997 e o modelo proposto por Kahn e Watts (2009, que analisam a relação entre as variáveis lucro contábil e retorno econômico, utilizando os valores dos retornos positivos e negativos como proxy de boas e más notícias, e outras variáveis largamente aceitas na avaliação do conservadorismo. Para tanto, foram estimados os modelos estatísticos para uma amostra de 96 empresas para o período de 2005 a 2007 partindo de informações anuais disponíveis no Economática® e dados reportados em notas explicativas. Com o objetivo de selecionar um evento econômico que pode impactar no reconhecimento assimétrico do resultado econômico, decidiu-se comparar os resultados entre empresas listadas nos níveis de governança da Bovespa com as demais empresas. Os resultados obtidos confirmam a hipótese de utilização de conservadorismo condicional na mensuração do resultado das companhias da amostra. A diferenciação positiva quanto ao grau de conservadorismo para as empresas que aderiram aos níveis de governança não são conclusivas, visto que os modelos apresentaram resultados dispersos. As variáveis econômicas criam vantagens quando as más notícias não podem ser tão claramente visíveis nas Demonstrações Contábeis, podendo diminuir os resultados futuros esperados.Accounting from an information perspective looks at the

  5. CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM

    Directory of Open Access Journals (Sweden)

    Valentin Potapov

    2016-12-01

    Full Text Available Purpose: This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life. Methods: allows the engine diagnostics with deep recognition to the structural assembly in the presence of single structural damage components of the engine running and the multifaceted damage. Results: of the optimization of neural network structure to solve the problems of evaluating technical state of the bypass turbofan engine, when used with genetic algorithms.

  6. Artificial Neural Network Application in the Diagnosis of Disease Conditions with Liver Ultrasound Images

    Directory of Open Access Journals (Sweden)

    Karthik Kalyan

    2014-01-01

    Full Text Available The preliminary study presented within this paper shows a comparative study of various texture features extracted from liver ultrasonic images by employing Multilayer Perceptron (MLP, a type of artificial neural network, to study the presence of disease conditions. An ultrasound (US image shows echo-texture patterns, which defines the organ characteristics. Ultrasound images of liver disease conditions such as “fatty liver,” “cirrhosis,” and “hepatomegaly” produce distinctive echo patterns. However, various ultrasound imaging artifacts and speckle noise make these echo-texture patterns difficult to identify and often hard to distinguish visually. Here, based on the extracted features from the ultrasonic images, we employed an artificial neural network for the diagnosis of disease conditions in liver and finding of the best classifier that distinguishes between abnormal and normal conditions of the liver. Comparison of the overall performance of all the feature classifiers concluded that “mixed feature set” is the best feature set. It showed an excellent rate of accuracy for the training data set. The gray level run length matrix (GLRLM feature shows better results when the network was tested against unknown data.

  7. Artificial Neural Network Application in the Diagnosis of Disease Conditions with Liver Ultrasound Images

    Science.gov (United States)

    Lele, Ramachandra Dattatraya; Joshi, Mukund; Chowdhary, Abhay

    2014-01-01

    The preliminary study presented within this paper shows a comparative study of various texture features extracted from liver ultrasonic images by employing Multilayer Perceptron (MLP), a type of artificial neural network, to study the presence of disease conditions. An ultrasound (US) image shows echo-texture patterns, which defines the organ characteristics. Ultrasound images of liver disease conditions such as “fatty liver,” “cirrhosis,” and “hepatomegaly” produce distinctive echo patterns. However, various ultrasound imaging artifacts and speckle noise make these echo-texture patterns difficult to identify and often hard to distinguish visually. Here, based on the extracted features from the ultrasonic images, we employed an artificial neural network for the diagnosis of disease conditions in liver and finding of the best classifier that distinguishes between abnormal and normal conditions of the liver. Comparison of the overall performance of all the feature classifiers concluded that “mixed feature set” is the best feature set. It showed an excellent rate of accuracy for the training data set. The gray level run length matrix (GLRLM) feature shows better results when the network was tested against unknown data. PMID:25332717

  8. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

    Science.gov (United States)

    Liu, Dan; Liu, Xuejun; Wu, Yiguang

    2018-04-24

    This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  9. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model

    Directory of Open Access Journals (Sweden)

    Dan Liu

    2018-04-01

    Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  10. Fate of As(V)-treated nano zero-valent iron: determination of arsenic desorption potential under varying environmental conditions by phosphate extraction.

    Science.gov (United States)

    Dong, Haoran; Guan, Xiaohong; Lo, Irene M C

    2012-09-01

    Nano zero-valent iron (NZVI) offers a promising approach for arsenic remediation, but the spent NZVI with elevated arsenic content could arouse safety concerns. This study investigated the fate of As(V)-treated NZVI (As-NZVI), by examining the desorption potential of As under varying conditions. The desorption kinetics of As from As-NZVI as induced by phosphate was well described by a biphasic rate model. The effects of As(V)/NZVI mass ratio, pH, and aging time on arsenic desorption from As-NZVI by phosphate were investigated. Less arsenic desorption was observed at lower pH or higher As(V)/NZVI mass ratio, where stronger complexes (bidentate) formed between As(V) and NZVI corrosion products as indicated by FTIR analysis. Compared with the fresh As-NZVI, the amount of phosphate-extractable As significantly decreased in As-NZVI aged for 30 or 60 days. The results of the sequential extraction experiments demonstrated that a larger fraction of As was sorbed in the crystalline phases after aging, making it less susceptible to phosphate displacement. However, at pH 9, a slightly higher proportion of phosphate-extractable As was observed in the 60-day sample than in the 30-day sample. XPS results revealed the transformation of As(V) to more easily desorbed As(III) during aging and a higher As(III)/As(V) ratio in the 60-day sample at pH 9, which might have resulted in the higher desorption. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. Successful transportation of human corneal endothelial tissues without cool preservation in varying Indian tropical climatic conditions and in vitro cell expansion using a novel polymer.

    Science.gov (United States)

    Rao, Srinivas K; Sudhakar, John; Parikumar, Periyasamy; Natarajan, Sundaram; Insaan, Aditya; Yoshioka, Hiroshi; Mori, Yuichi; Tsukahara, Shigeo; Baskar, Subramani; Manjunath, Sadananda Rao; Senthilkumar, Rajappa; Thamaraikannan, Paramasivam; Srinivasan, Thangavelu; Preethy, Senthilkumar; Abraham, Samuel J K

    2014-02-01

    Though the transplantation of human corneal endothelial tissue (CET) separated from cadaver cornea is in practice, its transportation has not been reported. We report the successful transportation of CET in varying Indian climatic conditions without cool preservation and the in vitro expansion of Human Corneal Endothelial Precursor Cells (HCEPCs) using a novel Thermo-reversible gelation polymer (TGP). CET from cadaver corneas (n = 67), unsuitable for transplantation, were used. In phase I, CET was transported in Basal Culture Medium (Group I) and TGP (Group II) and in Phase II, in TGP cocktail alone, from three hospitals 250-2500 km away, to a central laboratory. The transportation time ranged from 6 h to 72 h and the outdoor temperature between 20°C and 41°C. On arrival, CET were processed, cells were expanded upto 30 days in basal culture medium (Group A) and TGP scaffold (Group B). Cell viability and morphology were documented and Reverse transcription polymerase chain reaction (RT-PCR) characterization undertaken. In Phase I, TGP yielded more viable cells (0.11 × 10(6) cells) than Group I (0.04 × 10(6) cells). In Phase II, the average cell count was 5.44 × 10(4) cells. During expansion, viability of HCEPCs spheres in TGP was maintained for a longer duration. The cells from both the groups tested positive for B-3 tubulin and negative for cytokeratins K3 and K12, thereby proving them to be HCEPCs. TGP preserves the CET during transportation without cool preservation and supports in vitro expansion, with a higher yield of HCEPCs, similar to that reported in clinical studies.

  12. Successful transportation of human corneal endothelial tissues without cool preservation in varying Indian tropical climatic conditions and in vitro cell expansion using a novel polymer

    Directory of Open Access Journals (Sweden)

    Srinivas K Rao

    2014-01-01

    Full Text Available Background: Though the transplantation of human corneal endothelial tissue (CET separated from cadaver cornea is in practice, its transportation has not been reported. We report the successful transportation of CET in varying Indian climatic conditions without cool preservation and the in vitro expansion of Human Corneal Endothelial Precursor Cells (HCEPCs using a novel Thermo-reversible gelation polymer (TGP. Materials and Methods: CET from cadaver corneas (n = 67, unsuitable for transplantation, were used. In phase I, CET was transported in Basal Culture Medium (Group I and TGP (Group II and in Phase II, in TGP cocktail alone, from three hospitals 250-2500 km away, to a central laboratory. The transportation time ranged from 6 h to 72 h and the outdoor temperature between 20°C and 41°C. On arrival, CET were processed, cells were expanded upto 30 days in basal culture medium (Group A and TGP scaffold (Group B. Cell viability and morphology were documented and Reverse transcription polymerase chain reaction (RT-PCR characterization undertaken. Results: In Phase I, TGP yielded more viable cells (0.11 × 10 6 cells than Group I (0.04 × 10 6 cells. In Phase II, the average cell count was 5.44 × 10 4 cells. During expansion, viability of HCEPCs spheres in TGP was maintained for a longer duration. The cells from both the groups tested positive for B-3 tubulin and negative for cytokeratins K3 and K12, thereby proving them to be HCEPCs. Conclusion: TGP preserves the CET during transportation without cool preservation and supports in vitro expansion, with a higher yield of HCEPCs, similar to that reported in clinical studies.

  13. Condition Monitoring for DC-link Capacitors Based on Artificial Neural Network Algorithm

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Gadalla, Brwene Salah Abdelkarim

    2015-01-01

    hardware will reduce the cost, and therefore could be more promising for industry applications. A condition monitoring method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implementation of the ANN to the DC-link capacitor condition monitoring in a back......In power electronic systems, capacitor is one of the reliability critical components . Recently, the condition monitoring of capacitors to estimate their health status have been attracted by the academic research. Industry applications require more reliable power electronics products...... with preventive maintenance. However, the existing capacitor condition monitoring methods suffer from either increased hardware cost or low estimation accuracy, being the challenges to be adopted in industry applications. New development in condition monitoring technology with software solutions without extra...

  14. Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

    2012-12-31

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

  15. Acoustic emission condition monitoring of a nuclear power plant check valve using artificial neural networks

    International Nuclear Information System (INIS)

    Lee, Joon Hyun; Lee, Min Rae; Kim, Jung Teak

    2005-01-01

    In this study, an advanced condition monitoring technique based on acoustic emission (AE) detection and artificial neural networks was applied to a check valve, one of the components being used extensively in a safety system of a nuclear power plant (Npp). AE testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disk movement for valve degradation such as wear and leakage due to foreign object interference in a check valve. It is clearly demonstrated that the evaluation of different types of failure modes such as disk wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters. It is also shown that the leak size can be determined with an artificial neural network

  16. 75 FR 2433 - Special Conditions: Boeing Model 747-8/-8F Airplanes, Systems and Data Networks Security...

    Science.gov (United States)

    2010-01-15

    ... Conditions No. 25-401-SC] Special Conditions: Boeing Model 747-8/-8F Airplanes, Systems and Data Networks Security--Protection of Airplane Systems and Data Networks From Unauthorized External Access AGENCY... that effective electronic system security protection strategies are implemented to protect the airplane...

  17. Vibrational spectra of four-coordinated random networks with periodic boundary conditions

    International Nuclear Information System (INIS)

    Guttman, L.

    1976-01-01

    Examples of perfectly four-coordinated networks satisfying periodic boundary conditions are constructed by a pseudo-random process, starting from a crystalline region. The unphysical features (high density, large deviations from the tetrahedral bond-angle) are removed by systematic modification of the bonding scheme. The vibrational spectra are calculated, using a valence-force potential, and the neutron scattering is computed by a phonon-expansion approximation

  18. Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks

    OpenAIRE

    Yun, Kyongsik; Lu, Thomas; Chow, Edward

    2018-01-01

    Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts....

  19. COMPONENT SUPPLY MODEL FOR REPAIR ACTIVITIES NETWORK UNDER CONDITIONS OF PROBABILISTIC INDEFINITENESS.

    Directory of Open Access Journals (Sweden)

    Victor Yurievich Stroganov

    2017-02-01

    Full Text Available This article contains the systematization of the major production functions of repair activities network and the list of planning and control functions, which are described in the form of business processes (BP. Simulation model for analysis of the delivery effectiveness of components under conditions of probabilistic uncertainty was proposed. It has been shown that a significant portion of the total number of business processes is represented by the management and planning of the parts and components movement. Questions of construction of experimental design techniques on the simulation model in the conditions of non-stationarity were considered.

  20. Prioritization Assessment for Capability Gaps in Weapon System of Systems Based on the Conditional Evidential Network

    Directory of Open Access Journals (Sweden)

    Dong Pei

    2018-02-01

    Full Text Available The prioritization of capability gaps for weapon system of systems is the basis for design and capability planning in the system of systems development process. In order to address input information uncertainties, the prioritization of capability gaps is computed in two steps using the conditional evidential network method. First, we evaluated the belief distribution of degree of required satisfaction for capabilities, and then calculated the reverse conditional belief function between capability hierarchies. We also provided verification for the feasibility and effectiveness of the proposed method through a prioritization of capability gaps calculation using an example of a spatial-navigation-and-positioning system of systems.

  1. Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

    Science.gov (United States)

    Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

    2009-01-01

    We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

  2. Comparative estimation of inevitable endogenous ileal flow of amino acids in Pekin ducks under varying dietary or physiological conditions and their significance to nutritional requirements for amino acids.

    Science.gov (United States)

    Akinde, D O

    2017-10-01

    In 2 experiments in Pekin ducks the inevitable endogenous ileal flow (IEIF) of AA was estimated at changing intake and source of crude fiber (CF) or soybean oil (SO) level. Also the roles of dry matter intake (DMI) and BW or age as well as the proportion of IEIF in the dietary requirement for AA were studied. In experiment 1 three basal CP (20, 60, or 100 g/kg) diets were formulated containing a low CF (LCF, 30 g/kg) or high (HCF, 80 g/kg) level; achieved with cellulose supplementation. All diets were similar in every other respect including having SO content of 40 g/kg. Four floor pens of eight 85-day-old ducks were randomly allocated to each diet. Similar diets were mixed in experiment 2 but corn cob meal replaced cellulose as the fiber source. A high SO (HSO) series was also formed by increasing the SO level from 40 g/kg in the basal series to 100 g/kg. Thus the LCF series was concurrently classified as low SO (LSO) series to control SO effect. Each of the eventual 9 diets were fed to 5 floor pens of ten 65-day-old ducks. Ileal AA flow was measured after a 5 day feeding period in both experiments. Linear regression was calculated between ileal flow and dietary intake of individual AA. The IEIF interpreted as the y-intercept of each linear function responded neither to elevated ingestion of each CF type nor to SO level. Age and DMI had no effect on IEIF computed in relation to BW, but wide discrepancies resulted when related to DMI. Overall IEIF of AA varied between 14.3 to 129.8 mg/kg BW d-1. These flows were established in model computations to account for 10 to 64% of the recommended intake of limiting AA. In conclusion the ileal inevitable flow is constant within the dietary/age conditions investigated. However it is modulated by feed intake and accounts for a significant portion of total amino acid requirement. © 2017 Poultry Science Association Inc.

  3. Accumulation of N and P in the Legume Lespedeza davurica in Controlled Mixtures with the Grass Bothriochloa ischaemum under Varying Water and Fertilization Conditions.

    Science.gov (United States)

    Xu, Bingcheng; Xu, Weizhou; Wang, Zhi; Chen, Zhifei; Palta, Jairo A; Chen, Yinglong

    2018-01-01

    Water and fertilizers affect the nitrogen (N) and phosphorus (P) acquisition and allocation among organs in dominant species in natural vegetation on the semiarid Loess Plateau. This study aimed to clarify the N and P accumulation and N:P ratio at organ and plant level of a local legume species mixed with a grass species under varying water and fertilizer supplies, and thus to fully understand the requirements and balance of nutrient elements in response to growth conditions change of native species. The N and P concentration in the organ (leaf, stem, and root) and plant level of Lespedeza davurica (C 3 legume), were examined when intercropped with Bothriochloa ischaemum (C 4 grass). The two species were grown outdoors in pots under 80, 60, and 40% of soil water field capacity (FC), -NP, +N, +P, and +NP supply and the grass:legume mixture ratios of 2:10, 4:8, 6:6, 8:4, 10:2, and 12:0. The three set of treatments were under a randomized complete block design. Intercropping with B. ischaemum did not affect N concentrations in leaf, stem and root of L. davurica , but reduced P concentration in each organ under P fertilization. Only leaf N concentration in L. davurica showed decreasing trend as soil water content decreased under all fertilization and mixture proportion treatments. Stems had the lowest, while roots had the highest N and P concentration. As the mixture proportion of L. davurica decreased under P fertilization, P concentration in leaf and root also decreased. The N concentration in L. davurica at the whole plant level was 11.1-17.2%. P fertilization improved P concentration, while decreased N:P ratio in L. davurica . The N:P ratios were less than 14.0 under +P and +NP treatments. Our results implied that exogenous N and P fertilizer application may change the N:P stoichiometry and influence the balance between nutrients and organs of native dominant species in natural grassland, and P element should be paid more attention when considering rehabilitating

  4. Accumulation of N and P in the Legume Lespedeza davurica in Controlled Mixtures with the Grass Bothriochloa ischaemum under Varying Water and Fertilization Conditions

    Directory of Open Access Journals (Sweden)

    Bingcheng Xu

    2018-02-01

    Full Text Available Water and fertilizers affect the nitrogen (N and phosphorus (P acquisition and allocation among organs in dominant species in natural vegetation on the semiarid Loess Plateau. This study aimed to clarify the N and P accumulation and N:P ratio at organ and plant level of a local legume species mixed with a grass species under varying water and fertilizer supplies, and thus to fully understand the requirements and balance of nutrient elements in response to growth conditions change of native species. The N and P concentration in the organ (leaf, stem, and root and plant level of Lespedeza davurica (C3 legume, were examined when intercropped with Bothriochloa ischaemum (C4 grass. The two species were grown outdoors in pots under 80, 60, and 40% of soil water field capacity (FC, -NP, +N, +P, and +NP supply and the grass:legume mixture ratios of 2:10, 4:8, 6:6, 8:4, 10:2, and 12:0. The three set of treatments were under a randomized complete block design. Intercropping with B. ischaemum did not affect N concentrations in leaf, stem and root of L. davurica, but reduced P concentration in each organ under P fertilization. Only leaf N concentration in L. davurica showed decreasing trend as soil water content decreased under all fertilization and mixture proportion treatments. Stems had the lowest, while roots had the highest N and P concentration. As the mixture proportion of L. davurica decreased under P fertilization, P concentration in leaf and root also decreased. The N concentration in L. davurica at the whole plant level was 11.1–17.2%. P fertilization improved P concentration, while decreased N:P ratio in L. davurica. The N:P ratios were less than 14.0 under +P and +NP treatments. Our results implied that exogenous N and P fertilizer application may change the N:P stoichiometry and influence the balance between nutrients and organs of native dominant species in natural grassland, and P element should be paid more attention when considering

  5. Regional scenario building as a tool to support vulnerability assessment of food & water security and livelihood conditions under varying natural resources managements

    Science.gov (United States)

    Reinhardt, Julia; Liersch, Stefan; Dickens, Chris; Kabaseke, Clovis; Mulugeta Lemenih, Kassaye; Sghaier, Mongi; Hattermann, Fred

    2013-04-01

    Participatory regional scenario building was carried out with stakeholders and local researchers in four meso-scale case studies (CS) in Africa. In all CS the improvement of food and / or water security and livelihood conditions was identified as the focal issue. A major concern was to analyze the impacts of different plausible future developments on these issues. The process of scenario development is of special importance as it helps to identify main drivers, critical uncertainties and patterns of change. Opportunities and constraints of actors and actions become clearer and reveal adaptation capacities. Effective strategies must be furthermore reasonable and accepted by local stakeholders to be implemented. Hence, developing scenarios and generating strategies need the integration of local knowledge. The testing of strategies shows how they play out in different scenarios and how robust they are. Reasons and patterns of social and natural vulnerability can so be shown. The scenario building exercise applied in this study is inspired by the approach from Peter Schwartz. It aims at determining critical uncertainties and to identify the most important driving forces for a specific focal issue which are likely to shape future developments of a region. The most important and uncertain drivers were analyzed and systematized with ranking exercises during meetings with local researchers and stakeholders. Cause-effect relationships were drawn in the form of concept maps either during the meetings or by researchers based on available information. Past observations and the scenario building outcomes were used to conduct a trend analysis. Cross-comparisons were made to find similarities and differences between CS in terms of main driving forces, patterns of change, opportunities and constraints. Driving forces and trends which aroused consistently over scenarios and CS were identified. First results indicate that livelihood conditions of people rely often directly on the

  6. Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness.

    Science.gov (United States)

    Kim, Minkyung; Mashour, George A; Moraes, Stefanie-Blain; Vanini, Giancarlo; Tarnal, Vijay; Janke, Ellen; Hudetz, Anthony G; Lee, Uncheol

    2016-01-01

    Sleep, anesthesia, and coma share a number of neural features but the recovery profiles are radically different. To understand the mechanisms of reversibility of unconsciousness at the network level, we studied the conditions for gradual and abrupt transitions in conscious and anesthetized states. We hypothesized that the conditions for explosive synchronization (ES) in human brain networks would be present in the anesthetized brain just over the threshold of unconsciousness. To test this hypothesis, functional brain networks were constructed from multi-channel electroencephalogram (EEG) recordings in seven healthy subjects across conscious, unconscious, and recovery states. We analyzed four variables that are involved in facilitating ES in generic, non-biological networks: (1) correlation between node degree and frequency, (2) disassortativity (i.e., the tendency of highly-connected nodes to link with less-connected nodes, or vice versa), (3) frequency difference of coupled nodes, and (4) an inequality relationship between local and global network properties, which is referred to as the suppressive rule. We observed that the four network conditions for ES were satisfied in the unconscious state. Conditions for ES in the human brain suggest a potential mechanism for rapid recovery from the lightly-anesthetized state. This study demonstrates for the first time that the network conditions for ES, formerly shown in generic networks only, are present in empirically-derived functional brain networks. Further investigations with deep anesthesia, sleep, and coma could provide insight into the underlying causes of variability in recovery profiles of these unconscious states.

  7. Thermo-economic optimization of secondary distribution network of low temperature district heating network under local conditions of South Korea

    DEFF Research Database (Denmark)

    Park, Byung Sik; Imran, Muhammad; Hoon, Im-Yong

    2017-01-01

    . The corresponding heat loss from secondary network, pumping power and area of domestic hot water heat exchanger unit for each supply temperature and temperature difference for required heating load of the apartment complex are calculated. Results indicate that when supply temperature is decreased from 65 °C to 45...... apartment. The Apartment complex has 15 floors, 4 apartments on each floor and each apartment has heating surface area of 85 m2. The supply temperature of the hot water is reduced from 65 °C to 45 °C and the temperature difference between supply and return line is varied from 18 °C to 27 °C...... °C, area of heat exchanger is increased by 68.2%, pumping power is also increased by 9.8% and heat loss is reduced by 15.6%. These results correspond to a temperature difference of 20 °C, the standard temperature difference in South Korea residential heating system. Economic assessment...

  8. Functional brain networks involved in decision-making under certain and uncertain conditions

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J. [Boston University School of Medicine, Department of Anatomy and Neurobiology, Boston, MA (United States); Mian, Asim Z. [Boston University School of Medicine, Department of Radiology, Boston, MA (United States); Budson, Andrew E. [VA Boston Healthcare System, Boston, MA (United States)

    2018-01-15

    The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)

  9. Functional brain networks involved in decision-making under certain and uncertain conditions

    International Nuclear Information System (INIS)

    Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J.; Mian, Asim Z.; Budson, Andrew E.

    2018-01-01

    The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)

  10. Domain wall network as QCD vacuum and the chromomagnetic trap formation under extreme conditions

    International Nuclear Information System (INIS)

    Nedelko, Sergei N.; Voronin, Vladimir E.

    2015-01-01

    The ensemble of Euclidean gluon field configurations represented by the domain wall network is considered. A single domain wall is given by the sine-Gordon kink for the angle between chromomagnetic and chromoelectric components of the gauge field. The domain wall separates the regions with Abelian self-dual and anti-self-dual fields. The network of the domain wall defects is introduced as a combination of multiplicative and additive superpositions of kinks. The character of the spectrum and eigenmodes of color-charged fluctuations in the presence of the domain wall network is discussed. Conditions for the formation of a stable thick domain wall junction (the chromomagnetic trap) during heavy-ion collisions are discussed, and the spectrum of color-charged quasi-particles inside the trap is evaluated. An important observation is the existence of the critical size L c of a single trap stable against gluon tachyonic modes. The size L c is related to the value of gluon condensate left angle g 2 F 2 right angle. The growth of large lumps of merged chromomagnetic traps and the concept of the confinement-deconfinement transition in terms of the ensemble of domain wall networks are outlined. (orig.)

  11. CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

    Science.gov (United States)

    McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

    2014-06-01

    Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

  12. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  13. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  14. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  15. Adaptive Chemical Networks under Non-Equilibrium Conditions: The Evaporating Droplet.

    Science.gov (United States)

    Armao, Joseph J; Lehn, Jean-Marie

    2016-10-17

    Non-volatile solutes in an evaporating drop experience an out-of-equilibrium state due to non-linear concentration effects and complex flow patterns. Here, we demonstrate a small molecule chemical reaction network that undergoes a rapid adaptation response to the out-of-equilibrium conditions inside the droplet leading to control over the molecular constitution and spatial arrangement of the deposition pattern. Adaptation results in a pronounced coffee stain effect and coupling to chemical concentration gradients within the drop is demonstrated. Amplification and suppression of network species are readily identifiable with confocal fluorescence microscopy. We anticipate that these observations will contribute to the design and exploration of out-of-equilibrium chemical systems, as well as be useful towards the development of point-of-care medical diagnostics and controlled deposition of small molecules through inkjet printing. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Conditions for addressing environmental determinants of health behavior in intersectoral policy networks: A fuzzy set Qualitative Comparative Analysis.

    Science.gov (United States)

    Peters, D T J M; Verweij, S; Grêaux, K; Stronks, K; Harting, J

    2017-12-01

    Improving health requires changes in the social, physical, economic and political determinants of health behavior. For the realization of policies that address these environmental determinants, intersectoral policy networks are considered necessary for the pooling of resources to implement different policy instruments. However, such network diversity may increase network complexity and therefore hamper network performance. Network complexity may be reduced by network management and the provision of financial resources. This study examined whether network diversity - amidst the other conditions - is indeed needed to address environmental determinants of health behavior. We included 25 intersectoral policy networks in Dutch municipalities aimed at reducing overweight, smoking, and alcohol/drugs abuse. For our fuzzy set Qualitative Comparative Analysis we used data from three web-based surveys among (a) project leaders regarding network diversity and size (n = 38); (b) project leaders and project partners regarding management (n = 278); and (c) implementation professionals regarding types of environmental determinants addressed (n = 137). Data on budgets were retrieved from project application forms. Contrary to their intentions, most policy networks typically addressed personal determinants. If the environment was addressed too, it was mostly the social environment. To address environmental determinants of health behavior, network diversity (>50% of the actors are non-public health) was necessary in networks that were either small (policy networks in improving health behaviors by addressing a variety of environmental determinants. Copyright © 2017. Published by Elsevier Ltd.

  17. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose.

    Science.gov (United States)

    Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping

    2018-07-01

    Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state

  18. Optimization of Water Allocation between Different Crops in Water Stress Conditions in Qazvin Irrigation Network

    Directory of Open Access Journals (Sweden)

    Mehdi Mohammad khani

    2017-06-01

    Full Text Available Introduction: Evaluations show the necessity of using optimization models in order to determine optimal allocation of water in different water conditions. Its use can be proposed according to developed model abilities in this study in order to optimize water productivity and provide sustainable management and development of water resources over irrigation and drainage networks. Basic needs of the earth growing population and limitation of water and soil resources remindnecessity of optimal use of resources. World’s more than 280 million hectare lands are covered by irrigation networks (Khalkhali et al., 2006. The efficiency of most projects is between 30-50 percent and studies show that performance of most irrigation and drainage networks is not desirable and they have not achieved their aims. Hirich et al. (2014 Used deficit irrigation to improve crop water productivity of sweet corn, chickpea, faba bean and quinoa. For all crops, the highest water productivity and yield were obtained when deficit irrigation was applied during the vegetative growth stage. During the second season 2011 two cultivars of quinoa, faba bean and sweet corn have been cultivated applying 6 deficit irrigation treatments (rainfed, 0, 25, 50, 75 and 100% of full irrigation only during the vegetative growth stage, while in the rest of a crop cycle full irrigation was provided except for rainfed treatment. For quinoa and faba bean, treatment receiving 50% of the full irrigation during the vegetative growth stage recorded the highest yield and water productivity, while for sweet corn applying 75% of full irrigation was the optimal treatment in terms of yield and water productivity. Moghaddasi et al. (2010 worked examines and compares this approach with that based on the optimization method to manage agricultural water demand during drought to minimize damage. The results show that the optimization method resulted in 42% more income for the agricultural sector using the

  19. Development of an In-Situ Decommissioning Sensor Network Test Bed for Structural Condition Monitoring - 12156

    Energy Technology Data Exchange (ETDEWEB)

    Zeigler, Kristine E.; Ferguson, Blythe A. [Savannah River National Laboratory, Aiken, South Carolina 29808 (United States)

    2012-07-01

    The Savannah River National Laboratory (SRNL) has established an In Situ Decommissioning (ISD) Sensor Network Test Bed, a unique, small scale, configurable environment, for the assessment of prospective sensors on actual ISD system material, at minimal cost. The Department of Energy (DOE) is presently implementing permanent entombment of contaminated, large nuclear structures via ISD. The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. Validation of ISD system performance models and verification of actual system conditions can be achieved through the development a system of sensors to monitor the materials and condition of the structure. The ISD Sensor Network Test Bed has been designed and deployed to addresses the DOE-Environmental Management Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building at the Savannah River Site. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of groutable thermistors for temperature and moisture monitoring, strain gauges for crack growth monitoring, tilt-meters for settlement monitoring, and a communication system for data collection. Baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment. The Sensor Network Test Bed at SRNL uses COTS sensors on concrete blocks from the outer wall of the P Reactor Building to measure conditions expected to occur in ISD structures. Knowledge and lessons learned gained from installation, testing, and monitoring of the equipment will be applied to sensor installation in a meso-scale test bed at FIU and in future ISD structures. The initial data collected from the sensors

  20. A Mobile Localization Strategy for Wireless Sensor Network in NLOS Conditions

    Institute of Scientific and Technical Information of China (English)

    Long Cheng; Yan Wang; Xingming Sun; Nan Hu; Jian Zhang

    2016-01-01

    The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years.The localization accuracy will drastically grade in non-line of sight (NLOS) conditions.In this paper,we propose a mobile localization strategy based on Kalman filter.The key technologies for the proposed method are the NLOS identification and mitigation.The proposed method does not need the prior knowledge of the NLOS error and it is independent of the physical measurement ways.Simulation results show that the proposed method owns the higher localization accuracy when compared with other methods.

  1. Impact of Users Identities and Access Conditions on Downlink Performance in Closed Small-Cell Networks

    KAUST Repository

    Radaydeh, Redha

    2015-05-26

    This paper investigates the effect of various operation parameters on the downlink user performance in overlaid small-cell networks. The case study considers closed-access small cells (e.g., femtocells), wherein only active authorized user equipments (UEs) can be served, and each of which is allocated single downlink channel at a time. On the other hand, the macrocell base station can unconditionally serve macrocell UEs that exist inside its coverage space. The available channels can be shared simultaneously in the macrocell network and the femtocell network. Moreover, a channel can be reused only at the macrocell base station. The analysis provides quantitative approaches to model UEs identities, their likelihoods of being active, and their likelihoods of producing interference, considering UEs classifications, locations, and access capabilities. Moreover, it develops models for various interference sources observed from effective interference femtocells, considering femtocells capacities and operation conditions. The associated formulations to describe a desired UE performance and the impact of the number of available channels as well as the adopted channel assignment approach are thoroughly investigated. The results are generally presented for any channel models of interference sources as well as the desired source of the served UE. Moreover, specific channel models are then adopted, for which generalized closedform analytical results for the desired UE outage probability performance are obtained. Numerical and simulation results are presented to further clarify the main outcomes of the developed analysis.

  2. Development Of A Sensor Network Test Bed For ISD Materials And Structural Condition Monitoring

    International Nuclear Information System (INIS)

    Zeigler, K.; Ferguson, B.; Karapatakis, D.; Herbst, C.; Stripling, C.

    2011-01-01

    The P Reactor at the Savannah River Site is one of the first reactor facilities in the US DOE complex that has been placed in its end state through in situ decommissioning (ISD). The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. To evaluate the feasibility and utility of remote sensors to provide verification of ISD system conditions and performance characteristics, an ISD Sensor Network Test Bed has been designed and deployed at the Savannah River National Laboratory. The test bed addresses the DOE-EM Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of: (1) Groutable thermistors for temperature and moisture monitoring; (2) Strain gauges for crack growth monitoring; (3) Tiltmeters for settlement monitoring; and (4) A communication system for data collection. Preliminary baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment.

  3. Translation-aware semantic segmentation via conditional least-square generative adversarial networks

    Science.gov (United States)

    Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

    2017-10-01

    Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

  4. DEVELOPMENT OF A SENSOR NETWORK TEST BED FOR ISD MATERIALS AND STRUCUTRAL CONDITION MONITORING

    Energy Technology Data Exchange (ETDEWEB)

    Zeigler, K.; Ferguson, B.; Karapatakis, D.; Herbst, C.; Stripling, C.

    2011-07-06

    The P Reactor at the Savannah River Site is one of the first reactor facilities in the US DOE complex that has been placed in its end state through in situ decommissioning (ISD). The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. To evaluate the feasibility and utility of remote sensors to provide verification of ISD system conditions and performance characteristics, an ISD Sensor Network Test Bed has been designed and deployed at the Savannah River National Laboratory. The test bed addresses the DOE-EM Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of: (1) Groutable thermistors for temperature and moisture monitoring; (2) Strain gauges for crack growth monitoring; (3) Tiltmeters for settlement monitoring; and (4) A communication system for data collection. Preliminary baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment.

  5. Third-Order Spectral Techniques for the Diagnosis of Motor Bearing Condition Using Artificial Neural Networks

    Science.gov (United States)

    Yang, D.-M.; Stronach, A. F.; MacConnell, P.; Penman, J.

    2002-03-01

    This paper addresses the development of a novel condition monitoring procedure for rolling element bearings which involves a combination of signal processing, signal analysis and artificial intelligence methods. Seven approaches based on power spectrum, bispectral and bicoherence vibration analyses are investigated as signal pre-processing techniques for application in the diagnosis of a number of induction motor rolling element bearing conditions. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the power spectrum, the bispectrum, the bicoherence, the bispectrum diagonal slice, the bicoherence diagonal slice, the summed bispectrum and the summed bicoherence. Selected features are extracted from the vibration signatures so obtained and these are used as inputs to an artificial neural network trained to identify the bearing conditions. Quadratic phase coupling (QPC), examined using the magnitude of bispectrum and bicoherence and biphase, is shown to be absent from the bearing system and it is therefore concluded that the structure of the bearing vibration signatures results from inter-modulation effects. In order to test the proposed procedure, experimental data from a bearing test rig are used to develop an example diagnostic system. Results show that the bearing conditions examined can be diagnosed with a high success rate, particularly when using the summed bispectrum signatures.

  6. Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Gadalla, Brwene Salah Abdelkarim

    2015-01-01

    challenges. A capacitance estimation method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implemented ANN estimated the capacitance of the DC-link capacitor in a back-toback converter. Analysis of the error of the capacitance estimation is also given......In power electronic converters, reliability of DC-link capacitors is one of the critical issues. The estimation of their health status as an application of condition monitoring have been an attractive subject for industrial field and hence for the academic research filed as well. More reliable...... solutions are required to be adopted by the industry applications in which usage of extra hardware, increased cost, and low estimation accuracy are the main challenges. Therefore, development of new condition monitoring methods based on software solutions could be the new era that covers the aforementioned...

  7. PATs Operating in Water Networks under Unsteady Flow Conditions: Control Valve Manoeuvre and Overspeed Effect

    Directory of Open Access Journals (Sweden)

    Modesto Pérez-Sánchez

    2018-04-01

    Full Text Available The knowledge of transient conditions in water pressurized networks equipped with pump as turbines (PATs is of the utmost importance and necessary for the design and correct implementation of these new renewable solutions. This research characterizes the water hammer phenomenon in the design of PAT systems, emphasizing the transient events that can occur during a normal operation. This is based on project concerns towards a stable and efficient operation associated with the normal dynamic behaviour of flow control valve closure or by the induced overspeed effect. Basic concepts of mathematical modelling, characterization of control valve behaviour, damping effects in the wave propagation and runaway conditions of PATs are currently related to an inadequate design. The precise evaluation of basic operating rules depends upon the system and component type, as well as the required safety level during each operation.

  8. Structural Conditions for Collaboration and Learning in Innovation Networks: Using an Innovation System Performance Lens to Analyse Agricultural Knowledge Systems

    NARCIS (Netherlands)

    Hermans, F.; Klerkx, L.W.A.; Roep, D.

    2015-01-01

    Purpose: We investigate how the structural conditions of eight different European agricultural innovation systems can facilitate or hinder collaboration and social learning in multidisciplinary innovation networks. Methodology: We have adapted the Innovation System Failure Matrix to investigate the

  9. Near misses and unsafe conditions reported in a Pediatric Emergency Research Network

    Science.gov (United States)

    Ruddy, Richard M; Chamberlain, James M; Mahajan, Prashant V; Funai, Tomohiko; O'Connell, Karen J; Blumberg, Stephen; Lichenstein, Richard; Gramse, Heather L; Shaw, Kathy N

    2015-01-01

    Objective Patient safety may be enhanced by using reports from front-line staff of near misses and unsafe conditions to identify latent safety events. We describe paediatric emergency department (ED) near-miss events and unsafe conditions from hospital reporting systems in a 1-year observational study from hospitals participating in the Pediatric Emergency Care Applied Research Network (PECARN). Design This is a secondary analysis of 1 year of incident reports (IRs) from 18 EDs in 2007–2008. Using a prior taxonomy and established method, this analysis is of all reports classified as near-miss (events not reaching the patient) or unsafe condition. Classification included type, severity, contributing factors and personnel involved. In-depth review of 20% of IRs was performed. Results 487 reports (16.8% of eligible IRs) are included. Most common were medication-related, followed by laboratory-related, radiology-related and process-related IRs. Human factors issues were related to 87% and equipment issues to 11%. Human factor issues related to non-compliance with procedures accounted for 66.4%, including 5.95% with no or incorrect ID. Handoff issues were important in 11.5%. Conclusions Medication and process-related issues are important causes of near miss and unsafe conditions in the network. Human factors issues were highly reported and non-compliance with established procedures was very common, and calculation issues, communications (ie, handoffs) and clinical judgment were also important. This work should enable us to help improve systems within the environment of the ED to enhance patient safety in the future. PMID:26338681

  10. Stabilization of burn conditions in a thermonuclear reactor using artificial neural networks

    Science.gov (United States)

    Vitela, Javier E.; Martinell, Julio J.

    1998-02-01

    In this work we develop an artificial neural network (ANN) for the feedback stabilization of a thermonuclear reactor at nearly ignited burn conditions. A volume-averaged zero-dimensional nonlinear model is used to represent the time evolution of the electron density, the relative density of alpha particles and the temperature of the plasma, where a particular scaling law for the energy confinement time previously used by other authors, was adopted. The control actions include the concurrent modulation of the D-T refuelling rate, the injection of a neutral He-4 beam and an auxiliary heating power modulation, which are constrained to take values within a maximum and minimum levels. For this purpose a feedforward multilayer artificial neural network with sigmoidal activation function is trained using a back-propagation through-time technique. Numerical examples are used to illustrate the behaviour of the resulting ANN-dynamical system configuration. It is concluded that the resulting ANN can successfully stabilize the nonlinear model of the thermonuclear reactor at nearly ignited conditions for temperature and density departures significantly far from their nominal operating values. The NN-dynamical system configuration is shown to be robust with respect to the thermalization time of the alpha particles for perturbations within the region used to train the NN.

  11. Stabilization of burn conditions in a thermonuclear reactor using artificial neural networks

    International Nuclear Information System (INIS)

    Vitela, J.E.; Martinell, J.J.

    1998-01-01

    In this work we develop an artificial neural network (ANN) for the feedback stabilization of a thermonuclear reactor at nearly ignited burn conditions. A volume-averaged zero-dimensional nonlinear model is used to represent the time evolution of the electron density, the relative density of alpha particles and the temperature of the plasma, where a particular scaling law for the energy confinement time previously used by other authors, was adopted. The control actions include the concurrent modulation of the D-T refuelling rate, the injection of a neutral He-4 beam and an auxiliary heating power modulation, which are constrained to take values within a maximum and minimum levels. For this purpose a feedforward multilayer artificial neural network with sigmoidal activation function is trained using a back-propagation through-time technique. Numerical examples are used to illustrate the behaviour of the resulting ANN-dynamical system configuration. It is concluded that the resulting ANN can successfully stabilize the nonlinear model of the thermonuclear reactor at nearly ignited conditions for temperature and density departures significantly far from their nominal operating values. The NN-dynamical system configuration is shown to be robust with respect to the thermalization time of the alpha particles for perturbations within the region used to train the NN. (author)

  12. Visibility Enhancement of Scene Images Degraded by Foggy Weather Conditions with Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Farhan Hussain

    2016-01-01

    Full Text Available Nowadays many camera-based advanced driver assistance systems (ADAS have been introduced to assist the drivers and ensure their safety under various driving conditions. One of the problems faced by drivers is the faded scene visibility and lower contrast while driving in foggy conditions. In this paper, we present a novel approach to provide a solution to this problem by employing deep neural networks. We assume that the fog in an image can be mathematically modeled by an unknown complex function and we utilize the deep neural network to approximate the corresponding mathematical model for the fog. The advantages of our technique are as follows: (i its real-time operation and (ii being based on minimal input, that is, a single image, and exhibiting robustness/generalization for various unseen image data. Experiments carried out on various synthetic images indicate that our proposed technique has the abilities to approximate the corresponding fog function reasonably and remove it for better visibility and safety.

  13. Performance Analysis of Network-RTK Techniques for Drone Navigation considering Ionospheric Conditions

    Directory of Open Access Journals (Sweden)

    Tae-Suk Bae

    2018-01-01

    Full Text Available Recently, an accurate positioning has become the kernel of autonomous navigation with the rapid growth of drones including mapping purpose. The Network-based Real-time Kinematic (NRTK system was predominantly used for precision positioning in many fields such as surveying and agriculture, mostly in static mode or low-speed operation. The NRTK positioning, in general, shows much better performance with the fixed integer ambiguities. However, the success rate of the ambiguity resolution is highly dependent on the ionospheric condition and the surrounding environment of Global Navigation Satellite System (GNSS positioning, which particularly corresponds to the low-cost GNSS receivers. We analyzed the effects of the ionospheric conditions on the GNSS NRTK, as well as the possibility of applying the mobile NRTK to drone navigation for mapping. Two NRTK systems in operation were analyzed during a period of high ionospheric conditions, and the accuracy and the performance were compared for several operational cases. The test results show that a submeter accuracy is available even with float ambiguity under a favorable condition (i.e., visibility of the satellites as well as stable ionosphere. We still need to consider how to deal with ionospheric disturbances which may prevent NRTK positioning.

  14. Tracer Studies to Characterize the Effects of Roadside Noise Barriers on Near-Road Pollutant Dispersion under Varying Atmospheric Stability Conditions

    Science.gov (United States)

    A roadway toxics dispersion study was conducted by the Field Research Division (FRD) of NOAA at the Idaho National Laboratory (INL) near Idaho Falls, ID to document the effects on concentrations of roadway emissions behind a roadside sound barrier in various conditions of atmosph...

  15. CIRCUIT-DESIGN SOLUTIONS AND INFORMATION SUPPORT OF CITY ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

    Directory of Open Access Journals (Sweden)

    M. I. Fursanov

    2017-01-01

    Full Text Available The structure, circuit-design solutions and information support of the city electric networks in the conditions of the SMART GRID have been analyzed. It is demonstrated that the new conditions of functioning of electric power engineering, increasing demands for its technological state and reliability in most countries determined the transition to a restructuring of electrical networks to be based on the SMART GRID (intelligent power networks innovative new structure. The definitions of the SMART GRID, its various attributes and characteristics in most developed countries including Belarus are presented. It is revealed that the existing and future circuit and constructive solutions that can automate the process of managing modes of urban electric networks under the SMART GRID conditions are manifold. At present, the most common in distribution networks are the sources of distributed generation (combustion turbines, wind turbines, photovoltaic installations, mini-hydro, etc.. The patterns and problems of information traceability of a traditional urban networks of the unified energy system of Belarus have been analyzed, and it is demonstrated that in the conditions of the SMART GRID most of the problems of the control mode that are characteristic for traditional distribution networks 6–10 kV and 0.38 kV, lose their relevance. Therefore, the present article presents and features the main directions of development of automatic control modes of the SMART GRID.

  16. Social networks, work and network-based resources for the management of long-term conditions: a framework and study protocol for developing self-care support

    Directory of Open Access Journals (Sweden)

    Kapadia Dharmi

    2011-05-01

    Full Text Available Abstract Background Increasing the effective targeting and promotion of self-care support for long-term conditions requires more of a focus on patient contexts and networks. The aim of this paper is to describe how within a programme of research and implementation, social networks are viewed as being centrally involved in the mobilisation and deployment of resources in the management of a chronic condition. This forms the basis of a novel approach to understanding, designing, and implementing new forms of self-management support. Methods Drawing on evidence syntheses about social networks and capital and the role of information in self-management, we build on four conceptual approaches to inform the design of our research on the implementation of self-care support for people with long-term conditions. Our approach takes into consideration the form and content of social networks, notions of chronic illness work, normalisation process theory (NPT, and the whole systems informing self-management engagement (WISE approach to self-care support. Discussion The translation and implementation of a self-care agenda in contemporary health and social context needs to acknowledge and incorporate the resources and networks operating in patients' domestic and social environments and everyday lives. The latter compliments the focus on healthcare settings for developing and delivering self-care support by viewing communities and networks, as well as people suffering from long-term conditions, as a key means of support for managing long-term conditions. By focusing on patient work and social-network provision, our aim is to open up a second frontier in implementation research, to translate knowledge into better chronic illness management, and to shift the emphasis towards support that takes place outside formal health services.

  17. Automatically varying the composition of a mixed refrigerant solution for single mixed refrigerant LNG (liquefied natural gas) process at changing working conditions

    International Nuclear Information System (INIS)

    Xu, Xiongwen; Liu, Jinping; Cao, Le; Pang, Weiqiang

    2014-01-01

    The SMR (single mixed refrigerant) process is widely used in the small- and medium-scale liquefaction of NG (natural gas). Operating the MR (mixed-refrigerant) process outside of the design specifications is difficult but essential to save energy. Nevertheless, it is difficult to realize because the process needs to alter the working refrigerant composition. To address this challenge, this study investigated the performance diagnosis mechanism for SMR process. A control strategy was then proposed to control the changes in working refrigerant composition under different working conditions. This strategy separates the working refrigerant flow in the SMR process into three flows through two phase separators before it flows into the cold box. The first liquid flow is rich in the high-temperature component (isopentane). The second liquid flow is rich in the middle-temperature components (ethylene and propane), and the gas flow is rich in the low-temperature components (nitrogen and methane). By adjusting the flow rates, it is easy to decouple the control variables and automate the system. Finally, this approach was validated by process simulation and shown to be highly adaptive and exergy efficient in response to changing working conditions. - Highlights: • The performance diagnosis mechanism of SMR LNG process is studied. • A measure to automatically change the operation composition as per the working conditions is proposed for SMR process. • SMR process simulation is performed to verify the validity of the control solution. • The control solution notably improves the energy efficiency of SMR process at changing working condition

  18. Co-production of lipids, eicosapentaenoic acid, fucoxanthin, and chrysolaminarin by Phaeodactylum tricornutum cultured in a flat-plate photobioreactor under varying nitrogen conditions

    Science.gov (United States)

    Gao, Baoyan; Chen, Ailing; Zhang, Wenyuan; Li, Aifen; Zhang, Chengwu

    2017-10-01

    The marine diatom Phaeodactylum tricornutum is a polymorphological, ecologically significant, and well-studied model of unicellular microalga. This diatom can accumulate diverse important metabolites. Herein, we cultured P. tricornutum in an internally installed tie-piece flat-plate photobioreactor under 14.5 m mol L-1 (high nitrogen, HN) and 2.9 m mol L-1 (low nitrogen, LN) of KNO3 and assessed its time-resolved changes in biochemical compositions. The results showed that HN was inductive to accumulate high biomass (4.1 g L-1). However, the LN condition could accelerate lipid accumulation in P. tricornutum. The maximum total lipid (TL) content under LN was up to 42.5% of biomass on day 12. Finally, neutral lipids (NLs) were 63.8% and 75.7% of TLs under HN and LN, respectively. The content of EPA ranged from 2.3% to 1.5% of dry weight during the growth period under the two culture conditions. Peak volumetric lipid productivity of 128.4 mg L-1d-1 was achieved in the HN group (on day 9). The highest volumetric productivity values of EPA, chrysolaminarin, and fucoxanthin were obtained in the exponential phase (on day 6) under HN, which were 9.6, 93.6, and 4.7 mg L-1d-1, respectively. In conclusion, extractable amounts of lipids, EPA, fucoxanthin, and chrysolaminarin could be obtained from P. tricornutum by regulating the culture conditions.

  19. [Changes of vascular reactivity and reactive oxygen species in conditions of varying duration of permanent stay in the alienation zone in mice].

    Science.gov (United States)

    Tkachenko, M M; Kotsiuruba, A V; Baziliuk, O V; Horot', I V; Sahach, V F

    2010-01-01

    Peculiarities of changes in the vascular reactivity and in the content of reactive forms of oxygen and stable metabolites of nitric oxide (NO) were studied in the aorta preparations of C57BL/6 and BALB/c mice of the two age groups (6 and 18 mo.), which were born and permanently kept in the Chernobyl alienation zone. The results obtained showed a disturbance of acetylcholine-induced endothelium-dependent reactions of relaxation of smooth muscles of the thoracic aorta. A lower level of NO synthesis and lower level of oxidative arginase metabolism of arginine corresponded to a higher degree of damage of endothelium-dependent reactions of relaxation of the thoracic aorta smooth muscles. A decrease of NO synthesis in conditions of permanent effects of low doses of radiation was conditioned by an increase of generation of reactive forms of oxygen, namely, superoxide and hydroxyl radicals, which might be formed in mitochondria. In conditions of permanent effects of low doses of radiation a lesser level of protein nitrosothilation, same as lesser one of generation of OH-radical, corresponded to a higher level of damage of endothelium-dependent reactions.

  20. Ear Detection under Uncontrolled Conditions with Multiple Scale Faster Region-Based Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2017-04-01

    Full Text Available Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion, and imaging conditions provide a great challenge to the traditional ear detection methods under uncontrolled conditions. This paper proposes an efficient technique involving Multiple Scale Faster Region-based Convolutional Neural Networks (Faster R-CNN to detect ears from 2D profile images in natural images automatically. Firstly, three regions of different scales are detected to infer the information about the ear location context within the image. Then an ear region filtering approach is proposed to extract the correct ear region and eliminate the false positives automatically. In an experiment with a test set of 200 web images (with variable photographic conditions, 98% of ears were accurately detected. Experiments were likewise conducted on the Collection J2 of University of Notre Dame Biometrics Database (UND-J2 and University of Beira Interior Ear dataset (UBEAR, which contain large occlusion, scale, and pose variations. Detection rates of 100% and 98.22%, respectively, demonstrate the effectiveness of the proposed approach.

  1. Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

    Science.gov (United States)

    Masino, Johannes; Foitzik, Michael-Jan; Frey, Michael; Gauterin, Frank

    2017-06-01

    Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied comprehensively. This paper presents a method to automatically classify different types of pavement and the wear condition to identify noisy road surfaces. The methods are based on spectra of time series data of the tire cavity sound, acquired under normal vehicle operation. The classifier, an artificial neural network, correctly predicts three pavement types, whereas there are few bidirectional mis-classifications for two pavements, which have similar physical characteristics. The performance measures of the classifier to predict a new or worn out condition are over 94.6%. One could create a digital map with the output of the presented method. On the basis of these digital maps, road segments with a strong impact on tire road noise could be automatically identified. Furthermore, the method can estimate the road macro-texture, which has an impact on the tire road friction especially on wet conditions. Overall, this digital map would have a great benefit for civil engineering departments, road infrastructure operators, and for advanced driver assistance systems.

  2. Using a Novel Wireless-Networked Decentralized Control Scheme under Unpredictable Environmental Conditions.

    Science.gov (United States)

    Chang, Chung-Liang; Huang, Yi-Ming; Hong, Guo-Fong

    2015-11-12

    The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked decentralized fuzzy control scheme to regulate the environmental parameters of various culture zones within a greenhouse. The proposed scheme can create different environmental conditions for cultivating different crops in various zones and achieve diversification or standardization of crop production. A star-type wireless sensor network is utilized to communicate with each sensing node, actuator node, and control node in various zones within the greenhouse. The fuzzy rule-based inference system is used to regulate the environmental parameters for temperature and humidity based on real-time data of plant growth response provided by a growth stage selector. The growth stage selector defines the control ranges of temperature and humidity of the various culture zones according to the leaf area of the plant, the number of leaves, and the cumulative amount of light. The experimental results show that the proposed scheme is stable and robust and provides basis for future greenhouse applications.

  3. Using a Novel Wireless-Networked Decentralized Control Scheme under Unpredictable Environmental Conditions

    Directory of Open Access Journals (Sweden)

    Chung-Liang Chang

    2015-11-01

    Full Text Available The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked decentralized fuzzy control scheme to regulate the environmental parameters of various culture zones within a greenhouse. The proposed scheme can create different environmental conditions for cultivating different crops in various zones and achieve diversification or standardization of crop production. A star-type wireless sensor network is utilized to communicate with each sensing node, actuator node, and control node in various zones within the greenhouse. The fuzzy rule-based inference system is used to regulate the environmental parameters for temperature and humidity based on real-time data of plant growth response provided by a growth stage selector. The growth stage selector defines the control ranges of temperature and humidity of the various culture zones according to the leaf area of the plant, the number of leaves, and the cumulative amount of light. The experimental results show that the proposed scheme is stable and robust and provides basis for future greenhouse applications.

  4. Complete synchronization condition in a network of piezoelectric micro-beam

    International Nuclear Information System (INIS)

    Taffoti Yolong, V.Y.; Woafo, P.

    2007-10-01

    This work deals with the dynamics of a network of piezoelectric micro-beams. The complete synchronization condition for this class of chaotic nonlinear electromechanical systems devices with nearest-neighbor diffusive coupling is studied. The nonlinearities on the device studied here are both on the electrical component and on the mechanical one. The investigation is made for the case of a large number of discrete piezoelectric disks coupled. The problem of chaos synchronization is described and converted into the analysis of stability of the system via its differential equations. We show that the complete synchronization of N identical coupled nonlinear chaotic systems having the shift invariant coupling schemes can be calculated from the synchronization of two of them coupled in both directions. According to analytical, semi-analytical predictions and numerical calculations, the transition boundaries for chaos synchronization state in the coupled system are determined as a function of the increasing number of oscillators. (author)

  5. Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

    Directory of Open Access Journals (Sweden)

    Iker Urrutia

    2013-01-01

    Full Text Available Low Voltage (LV electricity distribution grid operations can be improved through a combination of new smart metering systems’ capabilities based on real time Power Line Communications (PLC and LV grid topology mapping. This paper presents two novel contributions. The first one is a new methodology developed for smart metering PLC network monitoring and analysis. It can be used to obtain relevant information from the grid, thus adding value to existing smart metering deployments and facilitating utility operational activities. A second contribution describes grid conditioning used to obtain LV feeder and phase identification of all connected smart electric meters. Real time availability of such information may help utilities with grid planning, fault location and a more accurate point of supply management.

  6. Condition monitoring of an electro-magnetic brake using an artificial neural network

    Science.gov (United States)

    Gofran, T.; Neugebauer, P.; Schramm, D.

    2017-10-01

    This paper presents a data-driven approach to Condition Monitoring of Electromagnetic brakes without use of additional sensors. For safe and efficient operation of electric motor a regular evaluation and replacement of the friction surface of the brake is required. One such evaluation method consists of direct or indirect sensing of the air-gap between pressure plate and magnet. A larger gap is generally indicative of worn surface(s). Traditionally this has been accomplished by the use of additional sensors - making existing systems complex, cost- sensitive and difficult to maintain. In this work a feed-forward Artificial Neural Network (ANN) is learned with the electrical data of the brake by supervised learning method to estimate the air-gap. The ANN model is optimized on the training set and validated using the test set. The experimental results of estimated air-gap with accuracy of over 95% demonstrate the validity of the proposed approach.

  7. Neural network ensemble based supplier evaluation model in line with nuclear safety conditions

    International Nuclear Information System (INIS)

    Wang Yonggang; Chang Baosheng

    2006-01-01

    Nuclear safety is the most critical target for nuclear power plant operation. Besides the rigid operation procedures established, evaluation of suppliers working with plants can be another important aspects. Selection and evaluation of suppliers can be classified with qualitative analysis and quantitative management. The indicators involved are coupled with each other in a very complicated manner, therefore the relevant data show the strong characteristic of non-linearity. The article is based on the research and analysis of the real conditions of the Daya Bay nuclear power plant operation management. Through study and analysis of the information home and abroad, and with reference to the neural network ensemble technology, the supplier evaluation system and model are established as illustrated within the paper, thus to heighten objectivity of the supplier selection. (authors)

  8. A new luminescence dating chronology for the Rhafas cave site (NE Morocco): Insights into Palaeolithic human cultural change under varying palaeoenvironmental conditions in the Maghreb

    Science.gov (United States)

    Dörschner, Nina; Fitzsimmons, Kathryn E.; Ditchfield, Peter; McLaren, Sue J.; Steele, Teresa E.; Zielhofer, Christoph; McPherron, Shannon P.; Bouzouggar, Abdeljalil; Hublin, Jean-Jacques

    2016-04-01

    Archaeological sites in northern Africa provide a rich record that is of increasing importance for current debates relating to the origins of modern human behaviour and to Out of Africa human dispersal events. Particular interest is placed on the cultural transition between the North African Middle Stone Age (MSA) and Late Stone Age (LSA), and the need for accurately defined chronologies, however the timing and nature of Palaeolithic human behaviour and dispersal across north-western Africa (the Maghreb) and potential correlation with environmental conditions remain poorly understood. The inland cave site of Rhafas (Morocco) preserves a long stratified sequence providing valuable chronological information about cultural changes in the Maghreb spanning the North African MSA through to the Neolithic. In this study, we apply optically stimulated luminescence (OSL) dating on sand-sized quartz grains to the cave deposits of Rhafas as well as to a section on the terrace in front of the cave entrance. Single grain OSL dating reliably constrains the timing of technocomplexes beyond the limits of radiocarbon by directly dating sediment associated with archaeological traces. We combine OSL dating with multi-proxy geological investigations (XRF, grain size analyses, stable isotopes, thin sections) to investigate site formation processes and reconstruct palaeoenvironmental conditions during human occupation phases at Rhafas. Our results indicate that the occupation of the site started at least in MIS 6 during a phase of relatively arid environmental conditions. Climatic amelioration after c.140 ka is associated with a change in sediment geochemistry at the site, most likely linked to a change in sediment source due to shifting wind directions. Tanged pieces - typical for the classical Aterian technocomplex - start to occur in the archaeological sequence in MIS 5, consistent with previously published chronological data from the Maghreb. From 55 ka, climatic conditions were

  9. A Comparative Study of Environmental Conditions, Bee Management and the Epidemiological Situation in Apiaries Varying in the Level of Colony Losses

    Directory of Open Access Journals (Sweden)

    Pohorecka Krystyna

    2014-12-01

    Full Text Available Explaining the reasons for the increased mortality of the honey bee (Apis mellifera L. in recent years, in Europe and North America, has become a global research priority in apicultural science. Our project was aimed at determining the relationship between environmental conditions, beekeeping techniques, the epidemiological situation of pathogens, and the mortality rate of bee colonies. Dead bee samples were collected by beekeepers from 2421 colonies. The samples were examined for the presence of V. destructor, Nosema spp. (Nosema apis and Nosema ceranae, chronic bee paralysis virus (CBPV, acute bee paralysis virus (ABPV, deformed wing virus (DWV, and Israeli acute paralysis virus (IAPV.

  10. Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands

    Science.gov (United States)

    Shope, James B.; Storlazzi, Curt D.; Hoeke, Ron K.

    2017-10-01

    Atoll islands are dynamic features that respond to seasonal alterations in wave conditions and sea level. It is unclear how shoreline wave run-up and erosion patterns along these low elevation islands will respond to projected sea-level rise (SLR) and changes in wave climate over the next century, hindering communities' preparation for the future. To elucidate how these processes may respond to climate change, extreme boreal winter and summer wave conditions under future sea-level rise (SLR) and wave climate scenarios were simulated at two atolls, Wake and Midway, using a shallow-water hydrodynamic model. Nearshore wave conditions were used to compute the potential longshore sediment flux along island shorelines via the CERC empirical formula and wave-driven erosion was calculated as the divergence of the longshore drift; run-up and the locations where the run-up exceed the berm elevation were also determined. SLR is projected to predominantly drive future island morphological change and flooding. Seaward shorelines (i.e., ocean fronted shorelines directly facing incident wave energy) were projected to experience greater erosion and flooding with SLR and in hypothetical scenarios where changes to deep water wave directions were altered, as informed by previous climate change forced Pacific wave modeling efforts. These changes caused nearshore waves to become more shore-normal, increasing wave attack along previously protected shorelines. With SLR, leeward shorelines (i.e., an ocean facing shoreline but sheltered from incident wave energy) became more accretive on windward islands and marginally more erosive along leeward islands. These shorelines became more accretionary and subject to more flooding with nearshore waves becoming more shore-normal. Lagoon shorelines demonstrated the greatest SLR-driven increase in erosion and run-up. They exhibited the greatest relative change with increasing wave heights where both erosion and run-up magnitudes increased. Wider

  11. Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands

    Science.gov (United States)

    Shope, James B.; Storlazzi, Curt; Hoeke, Ron

    2017-01-01

    Atoll islands are dynamic features that respond to seasonal alterations in wave conditions and sea level. It is unclear how shoreline wave run-up and erosion patterns along these low elevation islands will respond to projected sea-level rise (SLR) and changes in wave climate over the next century, hindering communities' preparation for the future. To elucidate how these processes may respond to climate change, extreme boreal winter and summer wave conditions under future sea-level rise (SLR) and wave climate scenarios were simulated at two atolls, Wake and Midway, using a shallow-water hydrodynamic model. Nearshore wave conditions were used to compute the potential longshore sediment flux along island shorelines via the CERC empirical formula and wave-driven erosion was calculated as the divergence of the longshore drift; run-up and the locations where the run-up exceed the berm elevation were also determined. SLR is projected to predominantly drive future island morphological change and flooding. Seaward shorelines (i.e., ocean fronted shorelines directly facing incident wave energy) were projected to experience greater erosion and flooding with SLR and in hypothetical scenarios where changes to deep water wave directions were altered, as informed by previous climate change forced Pacific wave modeling efforts. These changes caused nearshore waves to become more shore-normal, increasing wave attack along previously protected shorelines. With SLR, leeward shorelines (i.e., an ocean facing shoreline but sheltered from incident wave energy) became more accretive on windward islands and marginally more erosive along leeward islands. These shorelines became more accretionary and subject to more flooding with nearshore waves becoming more shore-normal. Lagoon shorelines demonstrated the greatest SLR-driven increase in erosion and run-up. They exhibited the greatest relative change with increasing wave heights where both erosion and run-up magnitudes increased. Wider

  12. Global exponential stability and periodicity of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions

    International Nuclear Information System (INIS)

    Lu Junguo

    2008-01-01

    In this paper, the global exponential stability and periodicity for a class of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are addressed by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential converge to 0 of the difference between any two solutions of the original reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Furthermore, we prove periodicity of the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions. Sufficient conditions ensuring the global exponential stability and the existence of periodic oscillatory solutions for the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are given. These conditions are easy to check and have important leading significance in the design and application of reaction-diffusion recurrent neural networks with delays. Finally, two numerical examples are given to show the effectiveness of the obtained results

  13. Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Hossein Bashashati

    2017-07-01

    Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

  14. Estimating pesticide sampling rates by the polar organic chemical integrative sampler (POCIS) in the presence of natural organic matter and varying hydrodynamic conditions

    International Nuclear Information System (INIS)

    Charlestra, Lucner; Amirbahman, Aria; Courtemanch, David L.; Alvarez, David A.; Patterson, Howard

    2012-01-01

    The polar organic chemical integrative sampler (POCIS) was calibrated to monitor pesticides in water under controlled laboratory conditions. The effect of natural organic matter (NOM) on the sampling rates (R s ) was evaluated in microcosms containing −1 of total organic carbon (TOC). The effect of hydrodynamics was studied by comparing R s values measured in stirred (SBE) and quiescent (QBE) batch experiments and a flow-through system (FTS). The level of NOM in the water used in these experiments had no effect on the magnitude of the pesticide sampling rates (p > 0.05). However, flow velocity and turbulence significantly increased the sampling rates of the pesticides in the FTS and SBE compared to the QBE (p < 0.001). The calibration data generated can be used to derive pesticide concentrations in water from POCIS deployed in stagnant and turbulent environmental systems without correction for NOM. - Highlights: ► We assessed the effect of TOC and stirring on pesticide sampling rates by POCIS. ► Total organic carbon (TOC) had no effect on the sampling rates. ► Water flow and stirring significantly increased the magnitude of the sampling rates. ► The sampling rates generated are directly applicable to field conditions. - This study provides POCIS sampling rates data that can be used to estimate freely dissolved concentrations of toxic pesticides in natural waters.

  15. Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition.

    Science.gov (United States)

    Zhang, Xinxin; Niu, Peifeng; Ma, Yunpeng; Wei, Yanqiao; Li, Guoqiang

    2017-10-01

    This paper is concerned with the stability analysis issue of fractional-order impulsive neural networks. Under the one-side Lipschitz condition or the linear growth condition of activation function, the existence of solution is analyzed respectively. In addition, the existence, uniqueness and global Mittag-Leffler stability of equilibrium point of the fractional-order impulsive neural networks with one-side Lipschitz condition are investigated by the means of contraction mapping principle and Lyapunov direct method. Finally, an example with numerical simulation is given to illustrate the validity and feasibility of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Osteogenic stimulatory conditions enhance growth and maturation of endothelial cell microvascular networks in culture with mesenchymal stem cells

    Directory of Open Access Journals (Sweden)

    Torbjorn O Pedersen

    2012-12-01

    Full Text Available To optimize culture conditions for in vitro prevascularization of tissue-engineered bone constructs, the development of organotypic blood vessels under osteogenic stimulatory conditions (OM was investigated. Coculture of endothelial cells and mesenchymal stem cells was used to assess proangiogenic effects of mesenchymal stem cells on endothelial cells. Four different culture conditions were evaluated for their effect on development of microvascular endothelial cell networks. Mineralization, deposition of extracellular matrix, and perivascular gene expression were studied in OM. After 3 days, endothelial cells established elongated capillary-like networks, and upregulated expression of vascular markers was seen. After 15 days, all parameters evaluated were significantly increased for cultures in OM. Mature networks developed in OM presented lumens enveloped by basement membrane-like collagen IV, with obvious mineralization and upregulated perivascular gene expression from mesenchymal stem cells. Our results suggest osteogenic stimulatory conditions to be appropriate for in vitro development of vascularized bone implants for tissue engineering.

  17. Estimating pesticide sampling rates by the polar organic chemical integrative sampler (POCIS) in the presence of natural organic matter and varying hydrodynamic conditions

    Science.gov (United States)

    Charlestra, Lucner; Amirbahman, Aria; Courtemanch, David L.; Alvarez, David A.; Patterson, Howard

    2012-01-01

    The polar organic chemical integrative sampler (POCIS) was calibrated to monitor pesticides in water under controlled laboratory conditions. The effect of natural organic matter (NOM) on the sampling rates (Rs) was evaluated in microcosms containing -1 of total organic carbon (TOC). The effect of hydrodynamics was studied by comparing Rs values measured in stirred (SBE) and quiescent (QBE) batch experiments and a flow-through system (FTS). The level of NOM in the water used in these experiments had no effect on the magnitude of the pesticide sampling rates (p > 0.05). However, flow velocity and turbulence significantly increased the sampling rates of the pesticides in the FTS and SBE compared to the QBE (p < 0.001). The calibration data generated can be used to derive pesticide concentrations in water from POCIS deployed in stagnant and turbulent environmental systems without correction for NOM.

  18. A Mathematical Model of Hourly Solar Radiation in Varying Weather Conditions for a Dynamic Simulation of the Solar Organic Rankine Cycle

    Directory of Open Access Journals (Sweden)

    Taehong Sung

    2015-07-01

    Full Text Available A mathematical model of hourly solar radiation with weather variability is proposed based on the simple sky model. The model uses a superposition of trigonometric functions with short and long periods. We investigate the effects of the model variables on the clearness (kD and the probability of persistence (POPD indices and also evaluate the proposed model for all of the kD-POPD weather classes. A simple solar organic Rankine cycle (SORC system with thermal storage is simulated using the actual weather conditions, and then, the results are compared with the simulation results using the proposed model and the simple sky model. The simulation results show that the proposed model provides more accurate system operation characteristics than the simple sky model.

  19. Straw incorporation increases crop yield and soil organic carbon sequestration but varies under different natural conditions and farming practices in China: a system analysis

    Directory of Open Access Journals (Sweden)

    X. Han

    2018-04-01

    Full Text Available Loss of soil organic carbon (SOC from agricultural soils is a key indicator of soil degradation associated with reductions in net primary productivity in crop production systems worldwide. Technically simple and locally appropriate solutions are required for farmers to increase SOC and to improve cropland management. In the last 30 years, straw incorporation (SI has gradually been implemented across China in the context of agricultural intensification and rural livelihood improvement. A meta-analysis of data published before the end of 2016 was undertaken to investigate the effects of SI on crop production and SOC sequestration. The results of 68 experimental studies throughout China in different edaphic conditions, climate regions and farming regimes were analyzed. Compared with straw removal (SR, SI significantly sequestered SOC (0–20 cm depth at the rate of 0.35 (95 % CI, 0.31–0.40 Mg C ha−1 yr−1, increased crop grain yield by 13.4 % (9.3–18.4 % and had a conversion efficiency of the incorporated straw C of 16 % ± 2 % across China. The combined SI at the rate of 3 Mg C ha−1 yr−1 with mineral fertilizer of 200–400 kg N ha−1 yr−1 was demonstrated to be the best farming practice, where crop yield increased by 32.7 % (17.9–56.4 % and SOC sequestrated by the rate of 0.85 (0.54–1.15 Mg C ha−1 yr−1. SI achieved a higher SOC sequestration rate and crop yield increment when applied to clay soils under high cropping intensities, and in areas such as northeast China where the soil is being degraded. The SOC responses were highest in the initial starting phase of SI, then subsequently declined and finally became negligible after 28–62 years. However, crop yield responses were initially low and then increased, reaching their highest level at 11–15 years after SI. Overall, our study confirmed that SI created a positive feedback loop of SOC enhancement together with

  20. Straw incorporation increases crop yield and soil organic carbon sequestration but varies under different natural conditions and farming practices in China: a system analysis

    Science.gov (United States)

    Han, Xiao; Xu, Cong; Dungait, Jennifer A. J.; Bol, Roland; Wang, Xiaojie; Wu, Wenliang; Meng, Fanqiao

    2018-04-01

    Loss of soil organic carbon (SOC) from agricultural soils is a key indicator of soil degradation associated with reductions in net primary productivity in crop production systems worldwide. Technically simple and locally appropriate solutions are required for farmers to increase SOC and to improve cropland management. In the last 30 years, straw incorporation (SI) has gradually been implemented across China in the context of agricultural intensification and rural livelihood improvement. A meta-analysis of data published before the end of 2016 was undertaken to investigate the effects of SI on crop production and SOC sequestration. The results of 68 experimental studies throughout China in different edaphic conditions, climate regions and farming regimes were analyzed. Compared with straw removal (SR), SI significantly sequestered SOC (0-20 cm depth) at the rate of 0.35 (95 % CI, 0.31-0.40) Mg C ha-1 yr-1, increased crop grain yield by 13.4 % (9.3-18.4 %) and had a conversion efficiency of the incorporated straw C of 16 % ± 2 % across China. The combined SI at the rate of 3 Mg C ha-1 yr-1 with mineral fertilizer of 200-400 kg N ha-1 yr-1 was demonstrated to be the best farming practice, where crop yield increased by 32.7 % (17.9-56.4 %) and SOC sequestrated by the rate of 0.85 (0.54-1.15) Mg C ha-1 yr-1. SI achieved a higher SOC sequestration rate and crop yield increment when applied to clay soils under high cropping intensities, and in areas such as northeast China where the soil is being degraded. The SOC responses were highest in the initial starting phase of SI, then subsequently declined and finally became negligible after 28-62 years. However, crop yield responses were initially low and then increased, reaching their highest level at 11-15 years after SI. Overall, our study confirmed that SI created a positive feedback loop of SOC enhancement together with increased crop production, and this is of great practical importance to straw management as agriculture

  1. An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

    Science.gov (United States)

    Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

    2017-02-01

    Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

  2. Effect of Initial Hydraulic Conditions on Capillary Rise in a Porous Medium: Pore-Network Modeling

    KAUST Repository

    Joekar-Niasar, V.

    2012-01-01

    The dynamics of capillary rise in a porous medium have been mostly studied in initially dry systems. As initial saturation and initial hydraulic conditions in many natural and industrial porous media can be variable, it is important to investigate the influence of initial conditions on the dynamics of the process. In this study, using dynamic pore-network modeling, we simulated capillary rise in a porous medium for different initial saturations (and consequently initial capillary pressures). Furthermore, the effect of hydraulic connectivity of the wetting phase in corners on the height and velocity of the wetting front was studied. Our simulation results show that there is a trade-off between capillary forces and trapping due to snap-off, which leads to a nonlinear dependence of wetting front velocity on initial saturation at the pore scale. This analysis may provide a possible answer to the experimental observations in the literature showing a non-monotonic dependency between initial saturation and the macroscopic front velocity. © Soil Science Society of America.

  3. Cellular Neural Network Method for Critical Slab with Albedo Boundary Condition

    International Nuclear Information System (INIS)

    Pirouzmanda, A.; Hadada, K.; Suh, K. Y.

    2010-01-01

    The neutron transport problems have been studied theoretically and numerically for years. A number of researchers have studied the criticality problems of one-speed neutrons in homogeneous slabs and spheres using various methods. The Chebyshev polynomial approximation method (T N method) has lately been developed and improved for the neutron transport equation in slab geometry. The one-speed time-dependent neutron transport equation using the Cellular Neural Network (CNN) for the vacuum boundary condition has previously been solved. In this paper, we demonstrate the capacity of CNN in calculating the critical slab thickness for different boundary conditions and its variation with moments N. The architecture of the CNN has already been dealt with thoroughly. Essentially, the CNN is used to model a first-order system of the partial differential equations (PDEs). The original equations in the T N approximation are also a set of PDEs. The CNN approach lends itself to analog VLSI implementation. In this study, the CNN model is implemented using the HSpice software package

  4. Necessary conditions to implement innovation in remote networked schools: The stakeholders’ perceptions

    Directory of Open Access Journals (Sweden)

    Sandrine Turcotte

    2008-12-01

    Full Text Available Remote Networked Schools (RNS is an initiative by the Quebec Ministry of Education, Leisure and Sports (MELS to investigate solutions that the use of information and communication technologies (ICT can offer for the preservation of small rural schools in Quebec, Canada. The implementation of RNS mobilized then – as it still does now – the local capacity for innovation of all the stakeholders involved in this networking effort to improve learning. Building on Donald P. Ely’s work (1990; 1999, this paper presents the results of an investigation of the RNS educational stakeholders’ perceptions of the importance of the conditions that facilitate the implementation of educational technology innovations for the success of RNS in their locations. Les conditions nécessaires à l’implantation de l’innovation de l'École éloignée en réseau: la perception des intervenants Résumé: L’École éloignée en réseau est une initiative du Ministère de l’Éducation, du Loisir et du Sport du Québec (MELS, qui a comme objectif d’explorer ce que l’usage des technologies de l’information et de la communication (TIC peut offrir pour la sauvegarde des petites écoles rurales au Québec, Canada. L'implantation de l’École éloignée en réseau a mobilisé (et continue aujourd’hui la capacité locale, pour l’innovation, de tous les intervenants impliqués dans cet effort de mise en réseau pour améliorer l’apprentissage. Partant des recherches de Donald P. Ely (1990; 1999, ce texte présente les résultats d’une étude sur la perception des intervenants impliqués dans l’École éloignée en réseau, quant à l’importance des conditions facilitant l’implantation d’innovations technologiques afin que cela soit un succès dans leur communauté.

  5. Numerical and analytical investigation of the chimera state excitation conditions in the Kuramoto-Sakaguchi oscillator network

    Science.gov (United States)

    Frolov, Nikita S.; Goremyko, Mikhail V.; Makarov, Vladimir V.; Maksimenko, Vladimir A.; Hramov, Alexander E.

    2017-03-01

    In this paper we study the conditions of chimera states excitation in ensemble of non-locally coupled Kuramoto-Sakaguchi (KS) oscillators. In the framework of current research we analyze the dynamics of the homogeneous network containing identical oscillators. We show the chimera state formation process is sensitive to the parameters of coupling kernel and to the KS network initial state. To perform the analysis we have used the Ott-Antonsen (OA) ansatz to consider the behavior of infinitely large KS network.

  6. Identification of alterations in the Jacobian of biochemical reaction networks from steady state covariance data at two conditions.

    Science.gov (United States)

    Kügler, Philipp; Yang, Wei

    2014-06-01

    Model building of biochemical reaction networks typically involves experiments in which changes in the behavior due to natural or experimental perturbations are observed. Computational models of reaction networks are also used in a systems biology approach to study how transitions from a healthy to a diseased state result from changes in genetic or environmental conditions. In this paper we consider the nonlinear inverse problem of inferring information about the Jacobian of a Langevin type network model from covariance data of steady state concentrations associated to two different experimental conditions. Under idealized assumptions on the Langevin fluctuation matrices we prove that relative alterations in the network Jacobian can be uniquely identified when comparing the two data sets. Based on this result and the premise that alteration is locally confined to separable parts due to network modularity we suggest a computational approach using hybrid stochastic-deterministic optimization for the detection of perturbations in the network Jacobian using the sparsity promoting effect of [Formula: see text]-penalization. Our approach is illustrated by means of published metabolomic and signaling reaction networks.

  7. Distribution network monitoring : Interaction between EU legal conditions and state estimation accuracy

    NARCIS (Netherlands)

    Blaauwbroek, Niels; Kuiken, Dirk; H. Nguyen, Phuong; Vedder, Hans; Roggenkamp, Martha; Slootweg, Han

    2018-01-01

    The expected increase in uncertainty regarding energy consumption and production from intermittent distributed energy resources calls for advanced network control capabilities and (household) customer flexibility in the distribution network. Depending on the control applications deployed, grid

  8. Distribution network monitoring: Interaction between EU legal conditions and state estimation accuracy

    NARCIS (Netherlands)

    Blaauwbroek, Niels; Kuiken, Dirk; Nguyen, Phuong; Vedder, Hans; Roggenkamp, Martha; Slootweg, Han

    2018-01-01

    The expected increase in uncertainty regarding energy consumption and production from intermittent distributed energy resources calls for advanced network control capabilities and (household) customer flexibility in the distribution network. Depending on the control applications deployed, grid

  9. First results on T91 claddings with and without modified FeCrAlY coatings exposed in PbBi under varying conditions

    International Nuclear Information System (INIS)

    Weisenburger, A.; Heinzel, A.; Miller, G.; Rousanov, A.

    2008-01-01

    It is well known that at temperatures above 500 deg C low activation austenitic steels suffer from severe corrosion in lead or lead-bismuth. Low activation martensitic steels instead form under similar conditions concerning temperature and oxygen content thick oxide scales that periodically may span off. Both groups of materials are therefore restricted to areas having lower temperature load. For parts that are intended to be used in high-temperature regions, like claddings, surface protection has to be applied. From gas turbines the role of elements forming thin stable oxide scales is well understood. The concept chosen here for thermally high loaded parts, the claddings, is the deposition of a FeCrAlY coating of about 30 vt,m thickness that is afterwards re-melted applying a pulsed electron beam (GESA). The beam energy is adjusted in a way to melt the entire coating together with a few thin region of the bulk to create a perfect intermixing at the boundary. This results in a new surface area of the cladding with an aluminium content of the order of 5 wt.% that will be sufficiently high to grow thin stable oxide scales. This concept is proven for austenitic cladding materials like 1.4970 as well as for martensitic ones like T91. In long-term corrosion tests the compatibility to Pb or PbBi, the resistance against corrosion and severe oxidation, was clearly demonstrated. No negative response of such a modified coating on the mechanical properties and the stability under irradiation has been observed as of yet. This paper will focus on the surface modification process, the corrosion results thus far obtained and on the evaluation of some mechanical properties. For example, the swelling of the fuel by irradiation will lead during operation to an increase of the internal pressure. This is simulated in experiments where an internal pressure of defined value was applied on T91 cladding tubes. The influence of flow velocity between to 3 m/s on the oxidation behaviour of T

  10. Retrofit of heat exchanger networks with pressure recovery of process streams at sub-ambient conditions

    International Nuclear Information System (INIS)

    Onishi, Viviani C.; Ravagnani, Mauro A.S.S.; Caballero, José A.

    2015-01-01

    Highlights: • New mathematical model for heat exchanger networks retrofit with pressure recovery. • Optimal heat and work integration applied to the retrofit of sub-ambient processes. • Streams pressure manipulation is used to enhance heat integration of the system. • Compressors and turbines can act on a coupling shaft and/or as stand-alone equipment. • Use of smaller amount of cold utilities, reducing significantly the operational costs. - Abstract: This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes

  11. A life cycle cost economics model for automation projects with uniformly varying operating costs. [applied to Deep Space Network and Air Force Systems Command

    Science.gov (United States)

    Remer, D. S.

    1977-01-01

    The described mathematical model calculates life-cycle costs for projects with operating costs increasing or decreasing linearly with time. The cost factors involved in the life-cycle cost are considered, and the errors resulting from the assumption of constant rather than uniformly varying operating costs are examined. Parameters in the study range from 2 to 30 years, for project life; 0 to 15% per year, for interest rate; and 5 to 90% of the initial operating cost, for the operating cost gradient. A numerical example is presented.

  12. Novel forms of colloidal self-organization in temporally and spatially varying external fields: from low-density network-forming fluids to spincoated crystals

    Science.gov (United States)

    Yethiraj, Anand

    2010-03-01

    External fields affect self-organization in Brownian colloidal suspensions in many different ways [1]. High-frequency time varying a.c. electric fields can induce effectively quasi-static dipolar inter-particle interactions. While dipolar interactions can provide access to multiple open equilibrium crystal structures [2] whose origin is now reasonably well understood, they can also give rise to competing interactions on short and long length scales that produce unexpected low-density ordered phases [3]. Farther from equilibrium, competing external fields are active in colloid spincoating. Drying colloidal suspensions on a spinning substrate produces a ``perfect polycrystal'' - tiny polycrystalline domains that exhibit long-range inter-domain orientational order [4] with resultant spectacular optical effects that are decoupled from single-crystallinity. High-speed movies of drying crystals yield insights into mechanisms of structure formation. Phenomena arising from multiple spatially- and temporally-varying external fields can give rise to further control of order and disorder, with potential application as patterned (photonic and magnetic) materials. [4pt] [1] A. Yethiraj, Soft Matter 3, 1099 (2007). [2] A. Yethiraj, A. van Blaaderen, Nature 421, 513 (2003). [3] A.K. Agarwal, A. Yethiraj, Phys. Rev. Lett ,102, 198301 (2009). [4] C. Arcos, K. Kumar, W. Gonz'alez-Viñas, R. Sirera, K. Poduska, A. Yethiraj, Phys. Rev. E ,77, 050402(R) (2008).

  13. Condition monitoring and thermo economic optimization of operation for a hybrid plant using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Assadi, Mohsen; Fast, Magnus (Lund University, Dept. of Energy Sciences, Lund (Sweden))

    2008-05-15

    The project aim is to model the hybrid plant at Vaesthamnsverket in Helsingborg using artificial neural networks (ANN) and integrating the ANN models, for online condition monitoring and thermo economic optimization, on site. The definition of a hybrid plant is that it uses more than one fuel, in this case a natural gas fuelled gas turbine with heat recovery steam generator (HRSG) and a biomass fuelled steam boiler with steam turbine. The thermo economic optimization takes into account current electricity prices, taxes, fuel prices etc. and calculates the current production cost along with the 'predicted' production cost. The tool also has a built in feature of predicting when a compressor wash is economically beneficial. The user interface is developed together with co-workers at Vaesthamnsverket to ensure its usefulness. The user interface includes functions for warnings and alarms when possible deviations in operation occur and also includes a feature for plotting parameter trends (both measured and predicted values) in selected time intervals. The target group is the plant owners and the original equipment manufacturers (OEM). The power plant owners want to acquire a product for condition monitoring and thermo economic optimization of e.g. maintenance. The OEMs main interest lies in investigating the possibilities of delivering ANN models, for condition monitoring, along with their new gas turbines. The project has been carried out at Lund University, Department of Energy Sciences, with support from Vaesthamnsverket AB and Siemens Industrial Turbomachinery AB. Vaesthamnsverket has contributed with operational data from the plant as well as support in plant related questions. They have also been involved in the implementation of the ANN models in their computer system and the development of the user interface. Siemens have contributed with expert knowledge about their SGT800 gas turbine. The implementation of the ANN models, and the accompanying user

  14. Forest condition and chemical characteristics of atmospheric depositions: research and monitoring network in Lombardy

    Directory of Open Access Journals (Sweden)

    Flaminio DI GIROLAMO

    2002-09-01

    Full Text Available Since 1987, the Regional Forestry Board of Lombardy and the Water Research Institute of the National Research Council have been carrying out surveys of forest conditions and the response of the ecosystem to environmental factors. The study approach is based on a large number of permanent plots for extensive monitoring (Level 1. At this level, crown condition is assessed annually, and soil condition and the nutritional status of forests surveyed. Some of the permanent plots were selected for intensive monitoring (Level 2, focussing mainly on the impact of atmospheric pollution on forest ecosystems. Level 2 monitoring also includes increment analyses, ground vegetation assessment, atmospheric deposition, soil solution analyses and climatic observations. This paper summarises the main results of a pluriannual research, which provides a general picture of the state of forest health in the region and focuses on more detailed investigations, described as case studies. Modified wet and dry samplers which use a water surface to collect dry deposition were used in a pluriannual field campaign at five sites in alpine and prealpine areas, to measure the total atmospheric depositions and to evaluate the nitrogen and sulphate exceedances of critical loads. Throughfall and bulk precipitation chemistry were studied for five years (June 1994-May 1999 at two high elevation forest sites (Val Gerola and Val Masino which were known to differ in terms of tree health, as assessed by live crown condition. Results indicated a higher contribution from the dry deposition of N-NO3 -, N-NH4 + and H+ and considerable canopy leaching of Ca2+, K+ and weak organic acids at Val Gerola, where the symptoms of damage were more evident. In the area of Val Masino (SO, included since 1997 in the national CONECOFOR network, investigations focused on the effectiveness of the biological compartment in modifying fluxes of atmospheric elements, and on the role of nitrogen both as an

  15. Response to ``Comment on `Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks''' [Chaos 17, 038101 (2007)

    Science.gov (United States)

    Yu, Wenwu; Cao, Jinde

    2007-09-01

    Parameter identification of dynamical systems from time series has received increasing interest due to its wide applications in secure communication, pattern recognition, neural networks, and so on. Given the driving system, parameters can be estimated from the time series by using an adaptive control algorithm. Recently, it has been reported that for some stable systems, in which parameters are difficult to be identified [Li et al., Phys Lett. A 333, 269-270 (2004); Remark 5 in Yu and Cao, Physica A 375, 467-482 (2007); and Li et al., Chaos 17, 038101 (2007)], and in this paper, a brief discussion about whether parameters can be identified from time series is investigated. From some detailed analyses, the problem of why parameters of stable systems can be hardly estimated is discussed. Some interesting examples are drawn to verify the proposed analysis.

  16. Health vulnerabilities in adolescence: socioeconomic conditions, social networks, drugs and violence.

    Science.gov (United States)

    dos Reis, Dener Carlos; de Almeida, Thiara Amanda Corrêa; Miranda, Mariane Mendes; Alves, Rodrigo Henrique; Madeira, Anézia Moreira Faria

    2013-01-01

    to analyze the health vulnerabilities in adolescence associated with socioeconomic conditions, social networks, drugs and violence from the perspective of students. cross-sectional study with 678 students between 14-15 years old in Contagem, Brazil. A self-administered questionnaire divided into modules by subject was used. Quantitative, descriptive and stratified analyses were performed by sex. high percentage of adolescents (40.4%) were beneficiaries of Government financial support called "Bolsa Família" and 14.6% had a job, 57.1% and 23.6% had tried alcohol and tobacco, respectively. We identified 15% of aggression and 26.7% of bullying. The majority informed they never/rarely talk to parents about the daily difficulties (64.5%) and 22% reported insomnia and/or feelings of loneliness. the results indicated that there is a need to intensify educational activities that seek to develop cognitive, affective and social skills aimed at improving the way adolescents face the vulnerabilities, in these activities, nursing has a fundamental role.

  17. Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition

    Directory of Open Access Journals (Sweden)

    Ladislaus Lwambuka

    2014-01-01

    Full Text Available This paper presents a practical approach for prioritization of bridge maintenance within a given bridge network. The maintenance prioritization is formulated as a multiobjective optimization problem where the simultaneous satisfaction of several conflicting objectives includes minimization of maintenance costs, maximization of bridge deck condition, and minimization of traffic disruption and associated user costs. The prevalence of user cost during maintenance period is twofold; the first case refers to the period of dry season where normally the traffic flow is diverted to alternative routes usually resurfaced to regain traffic access. The second prevalence refers to the absence of alternative routes which is often the case in the least developed countries; in this case the user cost referred to results from the waiting time while the traffic flow is put on hold awaiting accomplishment of the maintenance activity. This paper deals with the second scenario of traffic closure in the absence of alternative diversion routes which in essence results in extreme user cost. The paper shows that the multiobjective optimization approach remains valid for extreme cases of user costs in the absence of detour roads as often is the scenario in countries with extreme poor road infrastructure.

  18. Joint route planning under varying market conditions

    NARCIS (Netherlands)

    Cruijssen, Frans; Bräysy, Olli; Dullaert, Wout; Fleuren, Hein; Salomon, Marc

    2007-01-01

    Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics. Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their

  19. Social network analysis via multi-state reliability and conditional influence models

    International Nuclear Information System (INIS)

    Schneider, Kellie; Rainwater, Chase; Pohl, Ed; Hernandez, Ivan; Ramirez-Marquez, Jose Emmanuel

    2013-01-01

    This paper incorporates multi-state reliability measures into the assessment of a social network in which influence is treated as a multi-state commodity that flows through the network. The reliability of the network is defined as the probability that at least a certain level of influence reaches an intended target. We consider an individual's influence level as a function of the influence levels received from preceding actors in the network. We define several communication functions which describe the level of influence a particular actor will pass along to other actors within the network. Illustrative examples are presented, and the network reliability under the various communication influence levels is computed using exhaustive enumeration for a small example and Monte Carlo simulation for larger, more realistic sized examples.

  20. New conditions on synchronization of networks of linearly coupled dynamical systems with non-Lipschitz right-hand sides.

    Science.gov (United States)

    Liu, Bo; Lu, Wenlian; Chen, Tianping

    2012-01-01

    In this paper, we study synchronization of networks of linearly coupled dynamical systems. The node dynamics of the network can be very general, which may not satisfy the QUAD condition. We derive sufficient conditions for synchronization, which can be regarded as extensions of previous results. These results can be employed to networks of coupled systems, of which, in particular, the node dynamics have non-Lipschitz or even discontinuous right-hand sides. We also give several corollaries where the synchronization of some specific non-QUAD systems can be deduced. As an application, we propose a scheme to realize synchronization of coupled switching systems via coupling the signals which drive the switchings. Examples with numerical simulations are also provided to illustrate the theoretical results. Copyright © 2011 Elsevier Ltd. All rights reserved.

  1. Method of optimum channel switching in equipment of infocommunication network in conditions of cyber attacks to their telecommunication infrastructure.

    Science.gov (United States)

    Kochedykov, S. S.; Noev, A. N.; Dushkin, A. V.; Gubin, I. A.

    2018-05-01

    On the basis of the mathematical graph theory, the method of optimum switching of infocommunication networks in the conditions of cyber attacks is developed. The idea of representation of a set of possible ways on the graph in the form of the multilevel tree ordered by rules of algebra of a logic theory is the cornerstone of a method. As a criterion of optimization, the maximum of network transmission capacity to which assessment Ford- Falkerson's theorem is applied is used. The method is realized in the form of a numerical algorithm, which can be used not only for design, but also for operational management of infocommunication networks in conditions of violation of the functioning of their switching centers.

  2. Tracer diffusion in a polymer gel: simulations of static and dynamic 3D networks using spherical boundary conditions

    International Nuclear Information System (INIS)

    Kamerlin, Natasha; Elvingson, Christer

    2016-01-01

    We have investigated an alternative to the standard periodic boundary conditions for simulating the diffusion of tracer particles in a polymer gel by performing Brownian dynamics simulations using spherical boundary conditions. The gel network is constructed by randomly distributing tetravalent cross-linking nodes and connecting nearest pairs. The final gel structure is characterised by the radial distribution functions, chain lengths and end-to-end distances, and the pore size distribution. We have looked at the diffusion of tracer particles with a wide range of sizes, diffusing in both static and dynamic networks of two different volume fractions. It is quantitatively shown that the dynamical effect of the network becomes more important in facilitating the diffusional transport for larger particle sizes, and that one obtains a finite diffusion also for particle sizes well above the maximum in the pore size distribution. (paper)

  3. Robust routing for hazardous materials transportation with conditional value-at-risk on time-dependent networks.

    Science.gov (United States)

    2012-11-01

    New methods are proposed for mitigating risk in hazardous materials (hazmat) transportation, based on Conditional : Value-at-Risk (CVaR) measure, on time-dependent vehicular networks. While the CVaR risk measure has been : popularly used in financial...

  4. Idiotypic networks incorporating T-B cell co-operation. The conditions for percolation

    NARCIS (Netherlands)

    Boer, R.J. de; Hogeweg, P.

    1989-01-01

    Previous work was concerned with symmetric immune networks of idiotypic interactions amongst B cell clones. The behaviour of these networks was contrary to expectations. This was caused by an extensive percolation of idiotypic signals. Idiotypic activation was thus expected to affect almost all

  5. An fMRI study of joint action – varying levels of cooperation correlates with activity in sensorimotor control, but not mentalization, networks

    Directory of Open Access Journals (Sweden)

    Thierry eChaminade

    2012-06-01

    Full Text Available As social agents, humans continuously interact with with the people around them. Here, motor cooperation was investigated by designing a situation in which pairs of participants, one being scanned with fMRI, controlled jointly a visually presented object with joystick movements. The object oscillated dynamically along two dimensions, shades of pink and width of gratings, corresponding to the two cardinal directions of joystick movements. While the overall control of each participant on the object was kept constant, the amount of cooperation along the two dimensions varied along four levels, from no (each participant controlled exclusively one dimension to full (each participant controlled half of each dimension cooperation. Increasing cooperation correlated with BOLD signal in the left parietal operculum and anterior cingulate cortex, while decreasing cooperation correlated with activity in the right inferior frontal and superior temporal gyri, in the intraparietal sulci and inferior temporal gyrii bilaterally, and in the dorsomedial prefrontal cortex. As joint control improved with the level of cooperation, we assessed the brain responses correlating with joint performance, and found that activity in most of the areas associated with levels of cooperation also correlated with the joint performance. The only brain area found exclusively in the negative correlation with cooperation was within the posterior region of the rostral medial frontal cortex, involved in the monitoring of action outcome. We therefore propose that this region responds to the predictability of visual feedback given the motor commands, which is maximal when participants do not cooperate as they fully control one dimension. Our results therefore indicate that, in the current experimental paradigm, the level of cooperation affects sensorimotor processing, but not mentalizing. Altogether, humans do not need to have access to others’ intentional states to cooperate on a joint

  6. De-identification of clinical notes via recurrent neural network and conditional random field.

    Science.gov (United States)

    Liu, Zengjian; Tang, Buzhou; Wang, Xiaolong; Chen, Qingcai

    2017-11-01

    De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-scale and RDOC Individualized Domains (N-GRID) clinical natural language processing (NLP) challenge contains a de-identification track in de-identifying electronic medical records (EMRs) (i.e., track 1). The challenge organizers provide 1000 annotated mental health records for this track, 600 out of which are used as a training set and 400 as a test set. We develop a hybrid system for the de-identification task on the training set. Firstly, four individual subsystems, that is, a subsystem based on bidirectional LSTM (long-short term memory, a variant of recurrent neural network), a subsystem-based on bidirectional LSTM with features, a subsystem based on conditional random field (CRF) and a rule-based subsystem, are used to identify PHI instances. Then, an ensemble learning-based classifiers is deployed to combine all PHI instances predicted by above three machine learning-based subsystems. Finally, the results of the ensemble learning-based classifier and the rule-based subsystem are merged together. Experiments conducted on the official test set show that our system achieves the highest micro F1-scores of 93.07%, 91.43% and 95.23% under the "token", "strict" and "binary token" criteria respectively, ranking first in the 2016 CEGS N-GRID NLP challenge. In addition, on the dataset of 2014 i2b2 NLP challenge, our system achieves the highest micro F1-scores of 96.98%, 95.11% and 98.28% under the "token", "strict" and "binary token" criteria respectively, outperforming other state-of-the-art systems. All these experiments prove the effectiveness of our proposed method. Copyright © 2017. Published by Elsevier Inc.

  7. A neural networks application for the study of the influence of transport conditions on the working performance

    Science.gov (United States)

    Anghel, D.-C.; Ene, A.; Ştirbu, C.; Sicoe, G.

    2017-10-01

    This paper presents a study about the factors that influence the working performances of workers in the automotive industry. These factors regard mainly the transportations conditions, taking into account the fact that a large number of workers live in places that are far away of the enterprise. The quantitative data obtained from this study will be generalized by using a neural network, software simulated. The neural network is able to estimate the performance of workers even for the combinations of input factors that had been not recorded by the study. The experimental data obtained from the study will be divided in two classes. The first class that contains approximately 80% of data will be used by the Java software for the training of the neural network. The weights resulted from the training process will be saved in a text file. The other class that contains the rest of the 20% of experimental data will be used to validate the neural network. The training and the validation of the networks are performed in a Java software (TrainAndValidate java class). We designed another java class, Test.java that will be used with new input data, for new situations. The experimental data collected from the study. The software that simulated the neural network. The software that estimates the working performance, when new situations are met. This application is useful for human resources department of an enterprise. The output results are not quantitative. They are qualitative (from low performance to high performance, divided in five classes).

  8. Global exponential stability and periodicity of reaction-diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions

    International Nuclear Information System (INIS)

    Lu Junguo; Lu Linji

    2009-01-01

    In this paper, global exponential stability and periodicity of a class of reaction-diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions are studied by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential convergence to 0 of the difference between any two solutions of the original neural networks, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Secondly, we prove periodicity. Sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the equilibrium and periodic solution are given. These conditions are easy to verify and our results play an important role in the design and application of globally exponentially stable neural circuits and periodic oscillatory neural circuits.

  9. Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters

    Science.gov (United States)

    Lee, Kyung-Jun; Suh, Doug-Young; Park, Gwang-Hoon; Huh, Jae-Doo

    This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.

  10. Impact of Users Identities and Access Conditions on Downlink Performance in Closed Small-Cell Networks

    KAUST Repository

    Radaydeh, Redha; Gaaloul, Fakhreddine; Alouini, Mohamed-Slim

    2015-01-01

    This paper investigates the effect of various operation parameters on the downlink user performance in overlaid small-cell networks. The case study considers closed-access small cells (e.g., femtocells), wherein only active authorized user

  11. Analysis and characterization of security regions in power systems. Part I. Load flow feasibility conditions in power networks

    Energy Technology Data Exchange (ETDEWEB)

    Jarjis, J; Galiana, F D

    1980-03-01

    A set theoretic analysis of loadflow feasibility of a general power network with arbitrary PQ, PV and slack buses is presented. Load-flow feasibility is that property of a power network defining the theoretical limitations on the bus injections under which a steady state equilibrium exists. The set theoretic analysis is based on the study of the conical loadflow feasibility region. This region is characterised by a set of supporting hyperplanes each of which defines an explicit necessary condition for loadflow feasibility on the bus injections. A quantitative measure of loadflow feasibility for an arbitrary given operating injection vector is defined through a computable scalar stability margin. This stability margin permits the loadflow feasibility of different injections and network structures to be quantitatively compared and analysed.

  12. Connectivity and conditional models of access and abundance of species in stream networks.

    Science.gov (United States)

    Chelgren, Nathan D; Dunham, Jason B

    2015-07-01

    Barriers to passage of aquatic organisms at stream road crossings are a major cause of habitat fragmentation in stream networks. Accordingly, large investments have been made to restore passage at these crossings, but often without estimation of population-level benefits. Here, we describe a broad-scale approach to quantifying the effectiveness of passage restoration in terms interpretable at population levels, namely numbers of fish and length of stream gained through restoration, by sampling abundance in a study design that accounts for variable biogeographic species pools, variable stream and barrier configurations, and variable probabilities of capture and detectability for multiple species. We modified an existing zero-inflated negative-binomial model to estimate the probability of site access, abundance conditional on access, and capture probability of individual fish. Therein, we modeled probability of access as a function of gradient, stream road-crossing type, and downstream access by fish simultaneously with a predictive model for abundance at sites accessible to fish. Results indicated that replacement of barriers with new crossing designs intended to allow for greater movement was associated with dramatically higher probability of access for all fishes, including migratory Pacific salmon, trout, sculpin, and lamprey. Conversely, existing non-replaced crossings negatively impacted fish distributions. Assuming no downstream constraints on access, we estimated the potential length of stream restored by the program ranged between 7.33 (lamprey) and 15.28 km (small coastal cutthroat and rainbow trout). These contributions represented a fraction of the total length available upstream (187 km) of replaced crossings. When limited ranges of species were considered, the estimated contributions of culvert replacement were reduced (1.65-km range, for longnose dace to 12.31 km for small coastal cutthroat and rainbow trout). Numbers of fish contributed ranged from

  13. An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

    Science.gov (United States)

    Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

    2018-01-01

    This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

  14. Network Challenges for Cyber Physical Systems with Tiny Wireless Devices: A Case Study on Reliable Pipeline Condition Monitoring

    Directory of Open Access Journals (Sweden)

    Salman Ali

    2015-03-01

    Full Text Available The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs. CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

  15. Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring.

    Science.gov (United States)

    Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Khan, Muhammad Farhan; Naeem, Muhammad; Anpalagan, Alagan

    2015-03-25

    The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

  16. Schizophrenia alters intra-network functional connectivity in the caudate for detecting speech under informational speech masking conditions.

    Science.gov (United States)

    Zheng, Yingjun; Wu, Chao; Li, Juanhua; Li, Ruikeng; Peng, Hongjun; She, Shenglin; Ning, Yuping; Li, Liang

    2018-04-04

    Speech recognition under noisy "cocktail-party" environments involves multiple perceptual/cognitive processes, including target detection, selective attention, irrelevant signal inhibition, sensory/working memory, and speech production. Compared to health listeners, people with schizophrenia are more vulnerable to masking stimuli and perform worse in speech recognition under speech-on-speech masking conditions. Although the schizophrenia-related speech-recognition impairment under "cocktail-party" conditions is associated with deficits of various perceptual/cognitive processes, it is crucial to know whether the brain substrates critically underlying speech detection against informational speech masking are impaired in people with schizophrenia. Using functional magnetic resonance imaging (fMRI), this study investigated differences between people with schizophrenia (n = 19, mean age = 33 ± 10 years) and their matched healthy controls (n = 15, mean age = 30 ± 9 years) in intra-network functional connectivity (FC) specifically associated with target-speech detection under speech-on-speech-masking conditions. The target-speech detection performance under the speech-on-speech-masking condition in participants with schizophrenia was significantly worse than that in matched healthy participants (healthy controls). Moreover, in healthy controls, but not participants with schizophrenia, the strength of intra-network FC within the bilateral caudate was positively correlated with the speech-detection performance under the speech-masking conditions. Compared to controls, patients showed altered spatial activity pattern and decreased intra-network FC in the caudate. In people with schizophrenia, the declined speech-detection performance under speech-on-speech masking conditions is associated with reduced intra-caudate functional connectivity, which normally contributes to detecting target speech against speech masking via its functions of suppressing masking-speech signals.

  17. Network Condition Based Adaptive Control and its Application to Power Balancing in Electrical Grids

    DEFF Research Database (Denmark)

    Pedersen, Rasmus; Findrik, Mislav; Sloth, Christoffer

    2017-01-01

    To maintain a reliable and stable power grid there must be balance between consumption and production. To achieve power balance in a system with high penetration of distributed renewable resources and flexible assets, these individual system can be coordinated through a control unit to become part...... of the power balancing effort. Such control strategies require communication networks for exchange of control loop information. In this work, we show how a congested communication network can have a dramatic impact on the control performance of such a power balancing controller. To alleviate potential...

  18. Robust stabilization of burn conditions in subignited fusion reactors using artificial neural networks

    International Nuclear Information System (INIS)

    Vitela, E. Javier; Martinell, J. Julio

    2000-01-01

    In this work it is shown that robust burn control in long pulse operations of thermonuclear reactors can be successfully achieved with artificial neural networks. The results reported here correspond to a volume averaged zero-dimensional nonlinear model of a subignited fusion device using the design parameters of the tokamak EDA-ITER group. A Radial Basis Neural Network (RBNN) was trained to provide feedback stabilization at a fixed operating point independently of any particular scaling law that the reactor confinement time may follow. A numerically simulated transient is used to illustrate the stabilization capabilities of the resulting RBNN when the reactor follows an ELMy scaling law corrupted with Gaussian noise. (author)

  19. Artificial neural networks and the effects of loading conditions on fatigue life of carbon and low-alloy steels

    International Nuclear Information System (INIS)

    Pleune, T.T.

    1996-11-01

    The ASME Boiler and Pressure Vessel Code contains rules for the construction of nuclear power plant components. Figure 1-90 of Appendix I to Section III of the Code specifies fatigue design curves for structural materials. However, the effects of light water reactor (LWR) coolant environments are not explicitly addressed by the Code design curves. Recent test data indicate significant decreases in the fatigue lives of carbon and low-alloy steels in LWR environments when five conditions are satisfied simultaneously. When applied strain range, temperature, dissolved oxygen in the water, and sulfur content of the steel are above a minimum threshold level, and the loading strain rate is below a threshold value, environmentally assisted fatigue occurs. For this study, a data base of 1036 fatigue tests was used to train an artificial neural network (ANN). Once the optimal ANN was designed, ANN were trained and used to predict fatigue life for specified sets of loading and environmental conditions. By finding patterns and trends in the data, the ANN can find the fatigue lifetime for any set of conditions. Artificial neural networks show great potential for predicting environmentally assisted corrosion. Their main benefits are that the fit of the data is based purely on data and not on preconceptions and that the network can interpolate effects by learning trends and patterns when data are not available

  20. Radio/antenna mounting system for wireless networking under row-crop agriculture conditions

    Science.gov (United States)

    Interest in and deployment of wireless monitoring systems is increasing in many diverse environments, including row-crop agricultural fields. While many studies have been undertaken to evaluate various aspects of wireless monitoring and networking, such as electronic hardware components, data-colle...