WorldWideScience

Sample records for network activity rate

  1. Stock price change rate prediction by utilizing social network activities.

    Science.gov (United States)

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  2. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  3. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    Directory of Open Access Journals (Sweden)

    Maxwell R Bennett

    Full Text Available Measurements of blood oxygenation level dependent (BOLD signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular connections.

  4. Dependence of synchronized bursting activity on medium stirring and the perfusion rate in a cultured network of neurons

    Science.gov (United States)

    Heo, Ryoun; Kim, Hyun; Lee, Kyoung J.

    2016-05-01

    A cultured network of neurons coupled with a multi-electrode-array (MEA) recording system has been a useful platform for investigating various issues in neuroscience and engineering. The neural activity supported by the system can be sensitive to environmental fluctuations, for example, in the medium's nutrient composition, ph, and temperature, and to mechanical disturbances, yet this issue has not been the subject. Especially, a normal practice in maintaining neuronal cell cultures involves an intermittent sequence of medium exchanges, typically at a time interval of a few days, and one such sudden medium exchange is unavoidably accompanied by many unintended disturbances. Here, based on a quantitative time-series analysis of synchronized bursting events, we explicitly demonstrate that such a medium exchange can, indeed, bring a huge change in the existing neural activity. Subsequently, we develop a medium perfusion-stirring system and an ideal protocol that can be used in conjunction with a MEA recording system, providing long-term stability. Specifically, we systematically evaluate the effects of medium stirring and perfusion rates. Unexpectedly, even some vigorous mechanical agitations do not have any impacts on neural activity. On the other hand, too much replenishment ( e.g., 1.8 ml/day for a 1.8-ml dish) of neurobasal medium results in an excitotoxicity.

  5. Shapley ratings in brain networks

    Directory of Open Access Journals (Sweden)

    Rolf Kötter

    2007-11-01

    Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

  6. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

    Science.gov (United States)

    DeMarse, Thomas B; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J; Wheeler, Bruce C

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized

  7. Reflections on Active Networking

    Science.gov (United States)

    2005-01-01

    with a Software Switch for Active Networks ”. We had initially called the project “ SoftSwitch ”, but after some concerns David Farber raised that this...Reflections on Active Networking Jonathan M. Smith CIS Department, University of Pennsylvania jms@cis.upenn.edu Abstract Interactions among...telecommunications networks , computers, and other peripheral devices have been of interest since the earliest distributed computing systems. A key

  8. Foreign currency rate forecasting using neural networks

    Science.gov (United States)

    Pandya, Abhijit S.; Kondo, Tadashi; Talati, Amit; Jayadevappa, Suryaprasad

    2000-03-01

    Neural networks are increasingly being used as a forecasting tool in many forecasting problems. This paper discusses the application of neural networks in predicting daily foreign exchange rates between the USD, GBP as well as DEM. We approach the problem from a time-series analysis framework - where future exchange rates are forecasted solely using past exchange rates. This relies on the belief that the past prices and future prices are very close related, and interdependent. We present the result of training a neural network with historical USD-GBP data. The methodology used in explained, as well as the training process. We discuss the selection of inputs to the network, and present a comparison of using the actual exchange rates and the exchange rate differences as inputs. Price and rate differences are the preferred way of training neural network in financial applications. Results of both approaches are present together for comparison. We show that the network is able to learn the trends in the exchange rate movements correctly, and present the results of the prediction over several periods of time.

  9. Ninety-five orthotopic transplantations in 74 women of ovarian tissue after cytotoxic treatment in a fertility preservation network: tissue activity, pregnancy and delivery rates.

    Science.gov (United States)

    Van der Ven, H; Liebenthron, J; Beckmann, M; Toth, B; Korell, M; Krüssel, J; Frambach, T; Kupka, M; Hohl, M K; Winkler-Crepaz, K; Seitz, S; Dogan, A; Griesinger, G; Häberlin, F; Henes, M; Schwab, R; Sütterlin, M; von Wolff, M; Dittrich, R

    2016-09-01

    What is the success rate in terms of ovarian activity (menstrual cycles) as well as pregnancy and delivery rates 1 year after orthotopic ovarian transplantations conducted in a three-country network? In 49 women with a follow-up >1 year after transplantation, the ovaries were active in 67% of cases and the pregnancy and delivery rates were 33 and 25%, respectively. Cryopreservation of ovarian tissue in advance of cytotoxic therapies and later transplantation of the tissue is being performed increasingly often, and the total success rates in terms of pregnancy and delivery have been described in case series. However, published case series have not allowed either a more detailed analysis of patients with premature ovarian insufficiency (POI) or calculation of success rates based on the parameter 'tissue activity'. Retrospective analysis of 95 orthotopic transplantations in 74 patients who had been treated for cancer, performed in the FertiPROTEKT network from 2008 to June 2015. Of those 95 transplantations, a first subgroup (Subgroup 1) was defined for further analysis, including 49 women with a follow-up period >1 year after transplantation. Of those 49 women, a second subgroup (Subgroup 5) was further analysed, including 40 women who were transplanted for the first time and who were diagnosed with POI before transplantation. Transplantation was performed in 16 centres and data were transferred to the FertiPROTEKT registry. The transplantations were carried out after oncological treatment had been completed and after a remission period of at least 2 years. Tissue was transplanted orthotopically, either into or onto the residual ovaries or into a pelvic peritoneal pocket. The success rates were defined as tissue activity (menstrual cycles) after 1 year (primary outcome) and as pregnancies and deliveries achieved. The average age of all transplanted 74 women was 31 ± 5.9 years at the time of cryopreservation and 35 ± 5.2 at the time of transplantation. Twenty

  10. Stochastic cycle selection in active flow networks

    Science.gov (United States)

    Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn

    2016-11-01

    Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.

  11. Active Versus Passive Academic Networking

    DEFF Research Database (Denmark)

    Goel, Rajeev K.; Grimpe, Christoph

    2013-01-01

    This paper examines determinants of networking by academics. Using information from a unique large survey of German researchers, the key contribution focuses on the active versus passive networking distinction. Is active networking by researchers a substitute or a complement to passive networking......? Other contributions include examining the role of geographic factors in networking and whether research bottlenecks affect a researcher's propensity to network. Are the determinants of European conference participation by German researchers different from conferences in rest of the world? Results show...... that some types of passive academic networking are complementary to active networking, while others are substitute. Further, we find differences in factors promoting participation in European conferences versus conferences in rest of the world. Finally, publishing bottlenecks as a group generally do...

  12. The association between social networks and self-rated risk of HIV ...

    African Journals Online (AJOL)

    Elizabeth J. Lyimo

    2014-03-18

    Mar 18, 2014 ... Bonding networks were defined as social groupings of students participating in activities ... bridging social networks and self-rated HIV risk behavior. ...... book for Theory and Research for the Sociology of Education, 241–258.

  13. Pushing the network harder `Dynamic Ratings`

    Energy Technology Data Exchange (ETDEWEB)

    Liondas, V.; Howatt, C.; Norrie, P. [Prospect Electricity, Blacktown, NSW (Australia)

    1995-12-31

    The demand for electricity in the area serviced by Prospect Electricity, is increasing, necessitating an increase in power transfer through the distribution system. Satisfying this demand generally requires more electrical infrastructure, but this is becoming less feasible due to economic constraints and environmental considerations. This paper discusses an approach to the dynamic (or real time) rating of different network elements. Dynamic rating is taken to mean that rating which is determined essentially in real time using known temperature constraints for the relevant elements, together with the prevailing ambient or environmental conditions. The purpose of dynamic rating is to achieve greater system utilization, thus allowing significant economic benefits, particularly from deferment of capital expenditure and greater operational flexibility. A number of technologies are being developed to do this for overhead lines, underground cables and transformers. The dynamic rating of cables has proved to be the most intractable part of the dynamic rating project. Work done to date, however, using finite element techniques together with the proposals to further develop point and distributed temperature sensing using fibre optic methods gives some confidence to the future success of this development. (author). 2 tabs., 4 figs., 4 refs.

  14. Real-time relationship between PKA biochemical signal network dynamics and increased action potential firing rate in heart pacemaker cells: Kinetics of PKA activation in heart pacemaker cells.

    Science.gov (United States)

    Yaniv, Yael; Ganesan, Ambhighainath; Yang, Dongmei; Ziman, Bruce D; Lyashkov, Alexey E; Levchenko, Andre; Zhang, Jin; Lakatta, Edward G

    2015-09-01

    cAMP-PKA protein kinase is a key nodal signaling pathway that regulates a wide range of heart pacemaker cell functions. These functions are predicted to be involved in regulation of spontaneous action potential (AP) generation of these cells. Here we investigate if the kinetics and stoichiometry of increase in PKA activity match the increase in AP firing rate in response to β-adrenergic receptor (β-AR) stimulation or phosphodiesterase (PDE) inhibition, that alters the AP firing rate of heart sinoatrial pacemaker cells. In cultured adult rabbit pacemaker cells infected with an adenovirus expressing the FRET sensor AKAR3, the EC50 in response to graded increases in the intensity of β-AR stimulation (by Isoproterenol) the magnitude of the increases in PKA activity and the spontaneous AP firing rate were similar (0.4±0.1nM vs. 0.6±0.15nM, respectively). Moreover, the kinetics (t1/2) of the increases in PKA activity and spontaneous AP firing rate in response to β-AR stimulation or PDE inhibition were tightly linked. We characterized the system rate-limiting biochemical reactions by integrating these experimentally derived data into a mechanistic-computational model. Model simulations predicted that phospholamban phosphorylation is a potent target of the increase in PKA activity that links to increase in spontaneous AP firing rate. In summary, the kinetics and stoichiometry of increases in PKA activity in response to a physiological (β-AR stimulation) or pharmacological (PDE inhibitor) stimuli match those of changes in the AP firing rate. Thus Ca(2+)-cAMP/PKA-dependent phosphorylation limits the rate and magnitude of increase in spontaneous AP firing rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Neural Networks Modelling of Municipal Real Estate Market Rent Rates

    Directory of Open Access Journals (Sweden)

    Muczyński Andrzej

    2016-12-01

    Full Text Available This paper presents the results of research on the application of neural networks modelling of municipal real estate market rent rates. The test procedure was based on selected networks trained on the local real estate market data and transformation of the detected dependencies – through established models – to estimate the potential market rent rates of municipal premises. On this basis, the assessment of the adequacy of the actual market rent rates of municipal properties was made. Empirical research was conducted on the local real estate market of the city of Olsztyn in Poland. In order to describe the phenomenon of market rent rates formation an unidirectional three-layer network and a network of radial base was selected. Analyses showed a relatively low degree of convergence of the actual municipal rent rents with potential market rent rates. This degree was strongly varied depending on the type of business ran on the property and its’ social and economic impact. The applied research methodology and the obtained results can be used in order to rationalize municipal property management, including the activation of rental policy.

  16. Rate Aware Instantly Decodable Network Codes

    KAUST Repository

    Douik, Ahmed

    2016-02-26

    This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.

  17. Rate Aware Instantly Decodable Network Codes

    KAUST Repository

    Douik, Ahmed; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.

  18. How adaptation shapes spike rate oscillations in recurrent neuronal networks

    Directory of Open Access Journals (Sweden)

    Moritz eAugustin

    2013-02-01

    Full Text Available Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 Hz to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.

  19. Networking Technologies and the Rate of Technological Change

    Directory of Open Access Journals (Sweden)

    Charles Mitchell

    2005-12-01

    Full Text Available Network technology is changing rapidly and those adept at ICT analysis need resolve rate of change issues. Developments in networking now are in the direction of heuristic intelligence. Since about 1980, networking techniques have encouraged combining bits of information with imagination cognitively to improve ideas about reality. ICT enterprise projects utilize networking to sustain requisite imagination. Assumptions and misassuptions of project builders are rationally comprehended as networking sustains creative processes. The monopolization of valuable network techniques influences in the direction of esoteric networking. Data presents that substantial knowledge and networking is now occurring globally. As a netaphor, networking

  20. Time-variant coherence between heart rate variability and EEG activity in epileptic patients: an advanced coupling analysis between physiological networks

    International Nuclear Information System (INIS)

    Piper, D; Schiecke, K; Pester, B; Witte, H; Benninger, F; Feucht, M

    2014-01-01

    Time-variant coherence analysis between the heart rate variability (HRV) and the channel-related envelopes of adaptively selected EEG components was used as an indicator for the occurrence of (correlative) couplings between the central autonomic network (CAN) and the epileptic network before, during and after epileptic seizures. Two groups of patients were investigated, a group with left and a group with right hemispheric temporal lobe epilepsy. The individual EEG components were extracted by a signal-adaptive approach, the multivariate empirical mode decomposition, and the envelopes of each resulting intrinsic mode function (IMF) were computed by using Hilbert transform. Two IMFs, whose envelopes were strongly correlated with the HRV’s low-frequency oscillation (HRV-LF; ≈0.1 Hz) before and after the seizure were identified. The frequency ranges of these IMFs correspond to the EEG delta-band. The time-variant coherence was statistically quantified and tensor decomposition of the time-frequency coherence maps was applied to explore the topography-time-frequency characteristics of the coherence analysis. Results allow the hypothesis that couplings between the CAN, which controls the cardiovascular-cardiorespiratory system, and the ‘epileptic neural network’ exist. Additionally, our results confirm the hypothesis of a right hemispheric lateralization of sympathetic cardiac control of the HRV-LF. (paper)

  1. Networking activism: implications for Greece

    Directory of Open Access Journals (Sweden)

    Pantelis Vatikiotis

    2011-12-01

    Full Text Available The outbreak of December 2008 against police brutality through a wave of demonstrations and street protests in Athens, which was strongly advocated by protest activities and practices across the world, addresses several issues in relation to the transformative potentials of mediated collective action. The paper critically evaluates different accounts of December events, probing then into thevery networking of that movement. From this perspective, it points out another aspect of the local-global interplay in protest culture along new mediating practices (beyond the creation of transnational publics, that of the implications of transnational networking for local social activism and identification, addressing relevant questions in the Greek context.

  2. Theorizing Network-Centric Activity in Education

    Science.gov (United States)

    HaLevi, Andrew

    2011-01-01

    Networks and network-centric activity are increasingly prevalent in schools and school districts. In addition to ubiquitous social network tools like Facebook and Twitter, educational leaders deal with a wide variety of network organizational forms that include professional development, advocacy, informational networks and network-centric reforms.…

  3. Immunological network activation by low-dose rate irradiation. Analysis of cell populations and cell surface molecules in whole body irradiated mice

    International Nuclear Information System (INIS)

    Ina, Yasuhiro; Sakai, Kazuo

    2003-01-01

    The effects of low-dose rate whole body irradiation on biodefense and immunological systems were investigated using female C57BL/6 (B6) mice. These B6 mice were exposed continuously to γ-rays from a 137 Cs source in the long-term low-dose rate irradiation facility at CRIEPI for 0 - 12 weeks at a dose rate of 0.95 mGy/hr. In the bone marrow, thymus, spleen, lymph nodes, and peripheral blood of the irradiated mice, changes in cell populations and cell surface molecules were examined. The cell surface functional molecules (CD3, CD4, CD8, CD19, CD45R/B220, ICAM-1, Fas, NK-1.1, CXCR4, and CCR5), and activation molecules (THAM, CD28, CD40, CD44H, CD70, B7-1, B7-2, OX-40 antigen, CTLA-4, CD30 ligand, and CD40 ligand) were analyzed by flow cytometry. The percentage of CD4 + T cells and cell surface CD8 molecule expressions on the CD8 + T cells increased significantly to 120-130% after 3 weeks of the irradiation, compared to non-irradiated control mice. On the other hand, the percentage of CD45R/B220 + CD40 + B cells, which is one of the immunological markers of inflammation, infection, tumor, and autoimmune disease, decreased significantly to 80-90% between the 3rd to 5th week of irradiation. There was no significant difference in other cell population rates and cell surface molecule expression. Furthermore, abnormal T cells bearing mutated T cell receptors induced by high-dose rate irradiation were not observed throughout this study. These results suggest that low-dose rate irradiation activates the immunological status of the whole body. (author)

  4. Discrete rate and variable power adaptation for underlay cognitive networks

    KAUST Repository

    Abdallah, Mohamed M.; Salem, Ahmed H.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2010-01-01

    We consider the problem of maximizing the average spectral efficiency of a secondary link in underlay cognitive networks. In particular, we consider the network setting whereby the secondary transmitter employs discrete rate and variable power

  5. Video interpretability rating scale under network impairments

    Science.gov (United States)

    Kreitmair, Thomas; Coman, Cristian

    2014-01-01

    This paper presents the results of a study of the impact of network transmission channel parameters on the quality of streaming video data. A common practice for estimating the interpretability of video information is to use the Motion Imagery Quality Equation (MIQE). MIQE combines a few technical features of video images (such as: ground sampling distance, relative edge response, modulation transfer function, gain and signal-to-noise ratio) to estimate the interpretability level. One observation of this study is that the MIQE does not fully account for video-specific parameters such as spatial and temporal encoding, which are relevant to appreciating degradations caused by the streaming process. In streaming applications the main artifacts impacting the interpretability level are related to distortions in the image caused by lossy decompression of video data (due to loss of information and in some cases lossy re-encoding by the streaming server). One parameter in MIQE that is influenced by network transmission errors is the Relative Edge Response (RER). The automated calculation of RER includes the selection of the best edge in the frame, which in case of network errors may be incorrectly associated with a blocked region (e.g. low resolution areas caused by loss of information). A solution is discussed in this document to address this inconsistency by removing corrupted regions from the image analysis process. Furthermore, a recommendation is made on how to account for network impairments in the MIQE, such that a more realistic interpretability level is estimated in case of streaming applications.

  6. Intrinsically-generated fluctuating activity in excitatory-inhibitory networks

    Science.gov (United States)

    Mastrogiuseppe, Francesca; Ostojic, Srdjan

    2017-01-01

    Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations; for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons. PMID:28437436

  7. 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...

  8. Coordinated Voltage Control of Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Xie Jiang

    2016-01-01

    Full Text Available This paper presents a centralized coordinated voltage control method for active distribution network to solve off-limit problem of voltage after incorporation of distributed generation (DG. The proposed method consists of two parts, it coordinated primal-dual interior point method-based voltage regulation schemes of DG reactive powers and capacitors with centralized on-load tap changer (OLTC controlling method which utilizes system’s maximum and minimum voltages, to improve the qualified rate of voltage and reduce the operation numbers of OLTC. The proposed coordination has considered the cost of capacitors. The method is tested using a radial edited IEEE-33 nodes distribution network which is modelled using MATLAB.

  9. Information mining in weighted complex networks with nonlinear rating projection

    Science.gov (United States)

    Liao, Hao; Zeng, An; Zhou, Mingyang; Mao, Rui; Wang, Bing-Hong

    2017-10-01

    Weighted rating networks are commonly used by e-commerce providers nowadays. In order to generate an objective ranking of online items' quality according to users' ratings, many sophisticated algorithms have been proposed in the complex networks domain. In this paper, instead of proposing new algorithms we focus on a more fundamental problem: the nonlinear rating projection. The basic idea is that even though the rating values given by users are linearly separated, the real preference of users to items between the different given values is nonlinear. We thus design an approach to project the original ratings of users to more representative values. This approach can be regarded as a data pretreatment method. Simulation in both artificial and real networks shows that the performance of the ranking algorithms can be improved when the projected ratings are used.

  10. Presence of animal feeding operations and community socioeconomic factors impact salmonellosis incidence rates: An ecological analysis using data from the Foodborne Diseases Active Surveillance Network (FoodNet), 2004-2010.

    Science.gov (United States)

    Shaw, Kristi S; Cruz-Cano, Raul; Jiang, Chengsheng; Malayil, Leena; Blythe, David; Ryan, Patricia; Sapkota, Amy R

    2016-10-01

    Nontyphoidal Salmonella spp. are a leading cause of foodborne illness. Risk factors for salmonellosis include the consumption of contaminated chicken, eggs, pork and beef. Agricultural, environmental and socioeconomic factors also have been associated with rates of Salmonella infection. However, to our knowledge, these factors have not been modeled together at the community-level to improve our understanding of whether rates of salmonellosis are variable across communities defined by differing factors. To address this knowledge gap, we obtained data on culture-confirmed Salmonella Typhimurium, S. Enteritidis, S. Newport and S. Javiana cases (2004-2010; n=14,297) from the Foodborne Diseases Active Surveillance Network (FoodNet), and socioeconomic, environmental and agricultural data from the 2010 Census of Population and Housing, the 2011 American Community Survey, and the 2007 U.S. Census of Agriculture. We linked data by zip code and derived incidence rate ratios using negative binomial regressions. Multiple community-level factors were associated with salmonellosis rates; however, our findings varied by state. For example, in Georgia (Incidence Rate Ratio (IRR)=1.01; 95% Confidence Interval (CI)=1.005-1.015) Maryland (IRR=1.01; 95% CI=1.003-1.015) and Tennessee (IRR=1.01; 95% CI=1.002-1.012), zip codes characterized by greater rurality had higher rates of S. Newport infections. The presence of broiler chicken operations, dairy operations and cattle operations in a zip code also was associated with significantly higher rates of infection with at least one serotype in states that are leading producers of these animal products. For instance, in Georgia and Tennessee, rates of S. Enteritidis infection were 48% (IRR=1.48; 95% CI=1.12-1.95) and 46% (IRR=1.46; 95% CI=1.17-1.81) higher in zip codes with broiler chicken operations compared to those without these operations. In Maryland, New Mexico and Tennessee, higher poverty levels in zip codes were associated with

  11. Monitoring Malware Activity on the LAN Network

    Science.gov (United States)

    Skrzewski, Mirosław

    Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.

  12. Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

    Science.gov (United States)

    Ly, Cheng

    2015-12-01

    Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

  13. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; Ko, King-Tim

    2011-01-01

    the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolution algorithm to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general, presumes that we have product form between the nodes. Otherwise, we have the state space explosion. Even so, the detailed state space of each node may become very large because there is no product form between chains inside a node. A prerequisite for product form...

  14. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; King-Tim, Ko

    2011-01-01

    the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolutions to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate the detailed......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general presumes that we have product form between the nodes. Other ways we have the state space explosion. Even so the detailed state space of each node may easily become very large because there is no product form between chains inside a node. A prerequisite for product form...

  15. Opinion dynamics in activity-driven networks

    Science.gov (United States)

    Li, Dandan; Han, Dun; Ma, Jing; Sun, Mei; Tian, Lixin; Khouw, Timothy; Stanley, H. Eugene

    2017-10-01

    Social interaction between individuals constantly affects the development of their personal opinions. Previous models such as the Deffuant model and the Hegselmann-Krause (HK) model have assumed that individuals only update their opinions after interacting with neighbors whose opinions are similar to their own. However, people are capable of communicating widely with all of their neighbors to gather their ideas and opinions, even if they encounter a number of opposing attitudes. We propose a model in which agents listen to the opinions of all their neighbors. Continuous opinion dynamics are investigated in activity-driven networks with a tolerance threshold. We study how the initial opinion distribution, tolerance threshold, opinion-updating speed, and activity rate affect the evolution of opinion. We find that when the initial fraction of positive opinion is small, all opinions become negative by the end of the simulation. As the initial fraction of positive opinions rises above a certain value —about 0.45— the final fraction of positive opinions sharply increases and eventually equals 1. Increased tolerance threshold δ is found to lead to a more varied final opinion distribution. We also find that if the negative opinion has an initial advantage, the final fraction of negative opinion increases and reaches its peak as the updating speed λ approaches 0.5. Finally we show that the lower the activity rate of individuals, the greater the fluctuation range of their opinions.

  16. The interchangeability of learning rate and gain in backpropagation neural networks

    NARCIS (Netherlands)

    Thimm, G.; Moerland, P.; Fiesler, E.

    1996-01-01

    The backpropagation algorithm is widely used for training multilayer neural networks. In this publication the gain of its activation function(s) is investigated. In specific, it is proven that changing the gain of the activation function is equivalent to changing the learning rate and the weights.

  17. The Political Activity in the Network Environment

    Directory of Open Access Journals (Sweden)

    Марианна Юрьевна Павлютенкова

    2015-12-01

    Full Text Available The rapid development and deep penetration into all areas of modern society of information and communication technologies significantly increase the role of network interactions. Network structures represented primarily social networks, embedded in the public policy process and became one of the key political actors. Online communities take the form of public policy, where the formation of public opinion and political decision-making plays the main role. Networking environment opens up new opportunities for the opposition and protest movements, civic participation, and control of public policy in general. The article gives an insight on the political aspects of social networking, concludes on the trend formation and network's strengthening of the political activity in a wide distribution of e-networking and e-communications.

  18. Inference of financial networks using the normalised mutual information rate

    Science.gov (United States)

    2018-01-01

    In this paper, we study data from financial markets, using the normalised Mutual Information Rate. We show how to use it to infer the underlying network structure of interrelations in the foreign currency exchange rates and stock indices of 15 currency areas. We first present the mathematical method and discuss its computational aspects, and apply it to artificial data from chaotic dynamics and to correlated normal-variates data. We then apply the method to infer the structure of the financial system from the time-series of currency exchange rates and stock indices. In particular, we study and reveal the interrelations among the various foreign currency exchange rates and stock indices in two separate networks, of which we also study their structural properties. Our results show that both inferred networks are small-world networks, sharing similar properties and having differences in terms of assortativity. Importantly, our work shows that global economies tend to connect with other economies world-wide, rather than creating small groups of local economies. Finally, the consistent interrelations depicted among the 15 currency areas are further supported by a discussion from the viewpoint of economics. PMID:29420644

  19. Inference of financial networks using the normalised mutual information rate.

    Science.gov (United States)

    Goh, Yong Kheng; Hasim, Haslifah M; Antonopoulos, Chris G

    2018-01-01

    In this paper, we study data from financial markets, using the normalised Mutual Information Rate. We show how to use it to infer the underlying network structure of interrelations in the foreign currency exchange rates and stock indices of 15 currency areas. We first present the mathematical method and discuss its computational aspects, and apply it to artificial data from chaotic dynamics and to correlated normal-variates data. We then apply the method to infer the structure of the financial system from the time-series of currency exchange rates and stock indices. In particular, we study and reveal the interrelations among the various foreign currency exchange rates and stock indices in two separate networks, of which we also study their structural properties. Our results show that both inferred networks are small-world networks, sharing similar properties and having differences in terms of assortativity. Importantly, our work shows that global economies tend to connect with other economies world-wide, rather than creating small groups of local economies. Finally, the consistent interrelations depicted among the 15 currency areas are further supported by a discussion from the viewpoint of economics.

  20. Exchange rate variability, market activity and heterogeneity

    OpenAIRE

    Rime, Dagfinn; Sucarrat, Genaro

    2007-01-01

    We study the role played by geographic and bank-size heterogeneity in the relation between exchange rate variability and market activity. We find some support for the hypothesis that increases in short-term global interbank market activity, which can be interpreted as due to variation in information arrival, increase variability. However, our results do not suggest that local short-term activity increases variability. With respect to long-term market activity, which can be interpreted as a me...

  1. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  2. Entertainment Capture through Heart Rate Activity in Physical Interactive Playgrounds

    DEFF Research Database (Denmark)

    Yannakakis, Georgios; Hallam, John; Lund, Henrik Hautop

    2008-01-01

    children’s physiological signals, an estimator of the degree to which games provided by the playground engage the players. For this purpose children’s heart rate (HR) signals, and their expressed preferences of how much “fun” particular game variants are, are obtained from experiments using games...... that predict reported entertainment preferences given HR features. These models are expressed as artificial neural networks and are demonstrated and evaluated on two Playware games and two control tasks requiring physical activity. The best network is able to correctly match expressed preferences in 64...

  3. Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

    International Nuclear Information System (INIS)

    Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

    2009-01-01

    Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

  4. Radar meteor rates and solar activity

    International Nuclear Information System (INIS)

    Prikryl, P.

    1983-01-01

    The short-term variation of diurnal radar meteor rates with solar activity represented by solar microwave flux Fsub(10.7), and sunspots relative number Rsub(z), is investigated. Applying the superposed-epoch analysis to the observational material of radar meteor rates from Christchurch (1960-61 and 1963-65), a decrease in the recorded radar rates is found during days of enhanced solar activity. No effect of geomagnetic activity similar to the one reported for the Swedish and Canadian radar meteor data was found by the author in the Christchurch data. A possible explanation of the absence of the geomagnetic effect on radar meteor rates from New Zealand due to a lower echo ceiling height of the Christchurch radar is suggested. The variation of the atmospheric parameters as a possible cause of the observed variation in radar meteor rates is also discussed. (author)

  5. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  6. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Network feedback regulates motor output across a range of modulatory neuron activity.

    Science.gov (United States)

    Spencer, Robert M; Blitz, Dawn M

    2016-06-01

    Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab (Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5-35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation. Copyright © 2016 the American Physiological Society.

  8. Study Heart Rate by Tools from Complex Networks

    International Nuclear Information System (INIS)

    Makowiec, D.; Wdowczyk-Szulc, J.; Zarczynska-Buchowiecka, M.; Gruchala, M.; Rynkiewicz, A.

    2011-01-01

    Heart rate measured as beat-to-beat time intervals varies in time. It is believed that time intervals between subsequent normal heart contractions carry information about the regulatory system of the heart. How to quantify such signals is not clear and because of that heart rate variability is still apart from the clinic routine. In the following, we propose a method for representing a heart rate signal as a directed network. Then we study the signal properties by complex network tools. The signals to study were collected from patients recovering after the heart transplantation. The aim is to classify the progress of adapting of the new heart - graft. Moreover, it is expected that the method allows for visual classification. Our investigations are preliminary, however the obtained results are promising. (authors)

  9. Decorrelation of Neural-Network Activity by Inhibitory Feedback

    Science.gov (United States)

    Einevoll, Gaute T.; Diesmann, Markus

    2012-01-01

    Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between

  10. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  11. Estimating Ads’ Click through Rate with Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    Chen Qiao-Hong

    2016-01-01

    Full Text Available With the development of the Internet, online advertising spreads across every corner of the world, the ads' click through rate (CTR estimation is an important method to improve the online advertising revenue. Compared with the linear model, the nonlinear models can study much more complex relationships between a large number of nonlinear characteristics, so as to improve the accuracy of the estimation of the ads’ CTR. The recurrent neural network (RNN based on Long-Short Term Memory (LSTM is an improved model of the feedback neural network with ring structure. The model overcomes the problem of the gradient of the general RNN. Experiments show that the RNN based on LSTM exceeds the linear models, and it can effectively improve the estimation effect of the ads’ click through rate.

  12. Flexibility and Balancing in Active Distribution Networks

    DEFF Research Database (Denmark)

    Kordheili, Reza Ahmadi

    . Chapter 4 presents the details of the analysis, as well as the details of the MV network. To generalize the analysis, a standard MV network has been used for the studies. The MV network is also an active network, i.e. it involves MV wind turbines and decentralized combined heat and power (DCHP). DCHP...... units play an important role in Danish power system, and they contribute to electricity production as well. Modeling of wind turbines is done considering real data of a Vestas wind turbine. For wind speed, a modified wind speed model has been used for wind turbines, considering the available wind...... measurement. Also, a detailed model of DCHP units has been used in this thesis. Details of wind turbine model, as well as details of DCHP are presented in the thesis. The third objective of the research is to include the LV and MV networks in frequency response of the power system. Considering the increasing...

  13. Management of synchronized network activity by highly active neurons

    International Nuclear Information System (INIS)

    Shein, Mark; Raichman, Nadav; Ben-Jacob, Eshel; Volman, Vladislav; Hanein, Yael

    2008-01-01

    Increasing evidence supports the idea that spontaneous brain activity may have an important functional role. Cultured neuronal networks provide a suitable model system to search for the mechanisms by which neuronal spontaneous activity is maintained and regulated. This activity is marked by synchronized bursting events (SBEs)—short time windows (hundreds of milliseconds) of rapid neuronal firing separated by long quiescent periods (seconds). However, there exists a special subset of rapidly firing neurons whose activity also persists between SBEs. It has been proposed that these highly active (HA) neurons play an important role in the management (i.e. establishment, maintenance and regulation) of the synchronized network activity. Here, we studied the dynamical properties and the functional role of HA neurons in homogeneous and engineered networks, during early network development, upon recovery from chemical inhibition and in response to electrical stimulations. We found that their sequences of inter-spike intervals (ISI) exhibit long time correlations and a unimodal distribution. During the network's development and under intense inhibition, the observed activity follows a transition period during which mostly HA neurons are active. Studying networks with engineered geometry, we found that HA neurons are precursors (the first to fire) of the spontaneous SBEs and are more responsive to electrical stimulations

  14. Aberrant Network Activity in Schizophrenia.

    Science.gov (United States)

    Hunt, Mark J; Kopell, Nancy J; Traub, Roger D; Whittington, Miles A

    2017-06-01

    Brain dynamic changes associated with schizophrenia are largely equivocal, with interpretation complicated by many factors, such as the presence of therapeutic agents and the complex nature of the syndrome itself. Evidence for a brain-wide change in individual network oscillations, shared by all patients, is largely equivocal, but stronger for lower (delta) than for higher (gamma) bands. However, region-specific changes in rhythms across multiple, interdependent, nested frequencies may correlate better with pathology. Changes in synaptic excitation and inhibition in schizophrenia disrupt delta rhythm-mediated cortico-cortical communication, while enhancing thalamocortical communication in this frequency band. The contrasting relationships between delta and higher frequencies in thalamus and cortex generate frequency mismatches in inter-regional connectivity, leading to a disruption in temporal communication between higher-order brain regions associated with mental time travel. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Adaptive intelligent power systems: Active distribution networks

    International Nuclear Information System (INIS)

    McDonald, Jim

    2008-01-01

    Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

  16. [Establishment of regional active neonatal transport network].

    Science.gov (United States)

    Kong, Xiang-yong; Gao, Xin; Yin, Xiao-juan; Hong, Xiao-yang; Fang, Huan-sheng; Wang, Zi-zhen; Li, Ai-hua; Luo, Fen-ping; Feng, Zhi-chun

    2010-01-01

    To evaluate the clinical function and significance of establishing a regional active neonatal transport network (ANTN) in Beijing. The authors retrospectively studied intensive care and the role of ANTN system in management of critically ill neonates and compared the outcome of newborn infants transported to our NICU before and after we established standardized NICU and ANTN system (phase 1: July 2004 to June 2006 vs phase 2: July 2006 to May 2008). The number of neonatal transport significantly increased from 587 during phase 1 to 2797 during phase 2. Success rate of transport and the total cure rate in phase 2 were 97.85% and 91.99% respectively, which were significantly higher than those in phase 1 (94.36% and 88.69%, respectively, P capacity of our NICU was enlarged following the development of ANTN. There are 200 beds for level 3 infants in phase 2, but there were only 20 beds in phase 1. Significantly less patients in the phase 2 had hypothermia, acidosis and the blood glucose instability than those in phase 1 (P transported to our NICU were higher in phase 2 compared with that in phase 1, especially infants whose gestational age was below 32 weeks. The proportions of asphyxia and respiratory distress syndrome were lower in phase 2 than that in phase 1, but the total cure rates of these two diseases had no significant changes between the two phases. The most important finding was that the improvement of outcome of premature infants and those with asphyxia and aspiration syndrome was noted following the development of ANTN. Establishing regional ANTN for a tertiary hospital is very important to elevate the total level in management of critically ill newborn infants. It plays a very important role in reducing mortality and improving total outcomes of newborn infants. There are still some problems remained to solve after four years practice in order to optimize the ANTN to meet needs of the development of neonatology.

  17. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  18. Thermodynamically based constraints for rate coefficients of large biochemical networks.

    Science.gov (United States)

    Vlad, Marcel O; Ross, John

    2009-01-01

    Wegscheider cyclicity conditions are relationships among the rate coefficients of a complex reaction network, which ensure the compatibility of kinetic equations with the conditions for thermodynamic equilibrium. The detailed balance at equilibrium, that is the equilibration of forward and backward rates for each elementary reaction, leads to compatibility between the conditions of kinetic and thermodynamic equilibrium. Therefore, Wegscheider cyclicity conditions can be derived by eliminating the equilibrium concentrations from the conditions of detailed balance. We develop matrix algebra tools needed to carry out this elimination, reexamine an old derivation of the general form of Wegscheider cyclicity condition, and develop new derivations which lead to more compact and easier-to-use formulas. We derive scaling laws for the nonequilibrium rates of a complex reaction network, which include Wegscheider conditions as a particular case. The scaling laws for the rates are used for clarifying the kinetic and thermodynamic meaning of Wegscheider cyclicity conditions. Finally, we discuss different ways of using Wegscheider cyclicity conditions for kinetic computations in systems biology.

  19. Reconstructing Causal Biological Networks through Active Learning.

    Directory of Open Access Journals (Sweden)

    Hyunghoon Cho

    Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.

  20. Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks

    Directory of Open Access Journals (Sweden)

    Atsushi Usami

    2008-01-01

    Full Text Available Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

  1. Backtracking and Mixing Rate of Diffusion on Uncorrelated Temporal Networks

    Directory of Open Access Journals (Sweden)

    Martin Gueuning

    2017-10-01

    Full Text Available We consider the problem of diffusion on temporal networks, where the dynamics of each edge is modelled by an independent renewal process. Despite the apparent simplicity of the model, the trajectories of a random walker exhibit non-trivial properties. Here, we quantify the walker’s tendency to backtrack at each step (return where he/she comes from, as well as the resulting effect on the mixing rate of the process. As we show through empirical data, non-Poisson dynamics may significantly slow down diffusion due to backtracking, by a mechanism intrinsically different from the standard bus paradox and related temporal mechanisms. We conclude by discussing the implications of our work for the interpretation of results generated by null models of temporal networks.

  2. Active hippocampal networks undergo spontaneous synaptic modification.

    Directory of Open Access Journals (Sweden)

    Masako Tsukamoto-Yasui

    Full Text Available The brain is self-writable; as the brain voluntarily adapts itself to a changing environment, the neural circuitry rearranges its functional connectivity by referring to its own activity. How the internal activity modifies synaptic weights is largely unknown, however. Here we report that spontaneous activity causes complex reorganization of synaptic connectivity without any external (or artificial stimuli. Under physiologically relevant ionic conditions, CA3 pyramidal cells in hippocampal slices displayed spontaneous spikes with bistable slow oscillations of membrane potential, alternating between the so-called UP and DOWN states. The generation of slow oscillations did not require fast synaptic transmission, but their patterns were coordinated by local circuit activity. In the course of generating spontaneous activity, individual neurons acquired bidirectional long-lasting synaptic modification. The spontaneous synaptic plasticity depended on a rise in intracellular calcium concentrations of postsynaptic cells, but not on NMDA receptor activity. The direction and amount of the plasticity varied depending on slow oscillation patterns and synapse locations, and thus, they were diverse in a network. Once this global synaptic refinement occurred, the same neurons now displayed different patterns of spontaneous activity, which in turn exhibited different levels of synaptic plasticity. Thus, active networks continuously update their internal states through ongoing synaptic plasticity. With computational simulations, we suggest that with this slow oscillation-induced plasticity, a recurrent network converges on a more specific state, compared to that with spike timing-dependent plasticity alone.

  3. Flow rate of transport network controls uniform metabolite supply to tissue.

    Science.gov (United States)

    Meigel, Felix J; Alim, Karen

    2018-05-01

    Life and functioning of higher organisms depends on the continuous supply of metabolites to tissues and organs. What are the requirements on the transport network pervading a tissue to provide a uniform supply of nutrients, minerals or hormones? To theoretically answer this question, we present an analytical scaling argument and numerical simulations on how flow dynamics and network architecture control active spread and uniform supply of metabolites by studying the example of xylem vessels in plants. We identify the fluid inflow rate as the key factor for uniform supply. While at low inflow rates metabolites are already exhausted close to flow inlets, too high inflow flushes metabolites through the network and deprives tissue close to inlets of supply. In between these two regimes, there exists an optimal inflow rate that yields a uniform supply of metabolites. We determine this optimal inflow analytically in quantitative agreement with numerical results. Optimizing network architecture by reducing the supply variance over all network tubes, we identify patterns of tube dilation or contraction that compensate sub-optimal supply for the case of too low or too high inflow rate. © 2018 The Authors.

  4. Italian retail gasoline activities: inadequate distribution network

    International Nuclear Information System (INIS)

    Verde, Stefano

    2005-01-01

    It is common belief that competition in the Italian retail gasoline activities is hindered by oil companies' collusive behaviour. However, when developing a broader analysis of the sector, low efficiency and scarce competition could results as the consequences coming from an inadequate distribution network and from the recognition of international markets and focal point [it

  5. Modulation of neuronal network activity with ghrelin

    NARCIS (Netherlands)

    Stoyanova, Irina; Rutten, Wim; le Feber, Jakob

    2012-01-01

    Ghrelin is a neuropeptide regulating multiple physiological processes, including high brain functions such as learning and memory formation. However, the effect of ghrelin on network activity patterns and developments has not been studied yet. Therefore, we used dissociated cortical neurons plated

  6. Alumni Activities : International Alumni Network for TUAS

    OpenAIRE

    Saarinen, Riikka-Maria

    2013-01-01

    Turku University of Applied Sciences is currently planning on creating an International Alumni Network for the former exchange students who had their exchange period at TUAS. In this thesis, alumni functions are divided into three sections, i.e. the purpose of the alumni, the activities of the alumni and the management of the communication of the alumni. The research of the alumni functions was conducted by introduction of alumni activities in general and introducing three examples of Amer...

  7. Discrete rate and variable power adaptation for underlay cognitive networks

    KAUST Repository

    Abdallah, Mohamed M.

    2010-01-01

    We consider the problem of maximizing the average spectral efficiency of a secondary link in underlay cognitive networks. In particular, we consider the network setting whereby the secondary transmitter employs discrete rate and variable power adaptation under the constraints of maximum average transmit power and maximum average interference power allowed at the primary receiver due to the existence of an interference link between the secondary transmitter and the primary receiver. We first find the optimal discrete rates assuming a predetermined partitioning of the signal-to-noise ratio (SNR) of both the secondary and interference links. We then present an iterative algorithm for finding a suboptimal partitioning of the SNR of the interference link assuming a fixed partitioning of the SNR of secondary link selected for the case where no interference link exists. Our numerical results show that the average spectral efficiency attained by using the iterative algorithm is close to that achieved by the computationally extensive exhaustive search method for the case of Rayleigh fading channels. In addition, our simulations show that selecting the optimal partitioning of the SNR of the secondary link assuming no interference link exists still achieves the maximum average spectral efficiency for the case where the average interference constraint is considered. © 2010 IEEE.

  8. Designing container shipping network under changing demand and freight rates

    Directory of Open Access Journals (Sweden)

    C. Chen

    2010-03-01

    Full Text Available This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non-linear programming problem (MINP with an objective of maximizing the average unit ship-slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship-slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi-level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.

  9. A distributed lumped active all-pass network configuration.

    Science.gov (United States)

    Huelsman, L. P.; Raghunath, S.

    1972-01-01

    In this correspondence a new and interesting distributed lumped active network configuration that realizes an all-pass network function is described. A design chart for determining the values of the network elements is included.

  10. Prediction of ozone tropospheric degradation rate constant of organic compounds by using artificial neural networks

    International Nuclear Information System (INIS)

    Fatemi, M.H.

    2006-01-01

    Ozone tropospheric degradation of organic compound is very important in environmental chemistry. The lifetime of organic chemicals in the atmosphere can be calculated from the knowledge of the rate constant of their reaction with free radicals such as OH and NO 3 or O 3 . In the present work, the rate constant for the tropospheric degradation of 137 organic compounds by reaction with ozone, the least widely and successfully modeled degradation process, are predicted by quantitative structure activity relationships modeling based on a variety of theoretical descriptors, which screened and selected by genetic algorithm variable subset selection procedure. These descriptors which can be used as inputs for generated artificial neural networks are; HOMO-LUMO gap, number of double bonds, number of single bonds, maximum net charge on C atom, minimum (>0.1) bond order of C atom and Minimum e-e repulsion of H atom. After generation, optimization and training of artificial neural network, network was used for the prediction of log KO 3 for the validation set. The root mean square error for the neural network calculated log KO 3 for training, prediction and validation set are 0.357, 0.460 and 0.481, respectively, which are smaller than those obtained by multiple linear regressions model (1.217, 0.870 and 0.968, respectively). Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ozone tropospheric degradations rate constant of organic compounds

  11. Generalized activity equations for spiking neural network dynamics

    Directory of Open Access Journals (Sweden)

    Michael A Buice

    2013-11-01

    Full Text Available Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

  12. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle

    2005-01-01

    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  13. 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

  14. Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

    Science.gov (United States)

    Mutter, Kussay Nugamesh

    2018-01-01

    This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

  15. Forecasting Flare Activity Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Hernandez, T.

    2017-12-01

    Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

  16. Activating and inhibiting connections in biological network dynamics

    Directory of Open Access Journals (Sweden)

    Knight Rob

    2008-12-01

    Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

  17. A Distributed Flow Rate Control Algorithm for Networked Agent System with Multiple Coding Rates to Optimize Multimedia Data Transmission

    Directory of Open Access Journals (Sweden)

    Shuai Zeng

    2013-01-01

    Full Text Available With the development of wireless technologies, mobile communication applies more and more extensively in the various walks of life. The social network of both fixed and mobile users can be seen as networked agent system. At present, kinds of devices and access network technology are widely used. Different users in this networked agent system may need different coding rates multimedia data due to their heterogeneous demand. This paper proposes a distributed flow rate control algorithm to optimize multimedia data transmission of the networked agent system with the coexisting various coding rates. In this proposed algorithm, transmission path and upload bandwidth of different coding rate data between source node, fixed and mobile nodes are appropriately arranged and controlled. On the one hand, this algorithm can provide user nodes with differentiated coding rate data and corresponding flow rate. On the other hand, it makes the different coding rate data and user nodes networked, which realizes the sharing of upload bandwidth of user nodes which require different coding rate data. The study conducts mathematical modeling on the proposed algorithm and compares the system that adopts the proposed algorithm with the existing system based on the simulation experiment and mathematical analysis. The results show that the system that adopts the proposed algorithm achieves higher upload bandwidth utilization of user nodes and lower upload bandwidth consumption of source node.

  18. Partner network communities – a resource of universities’ activities

    Directory of Open Access Journals (Sweden)

    Romm Mark V.

    2016-01-01

    Full Text Available The network activity is not only part and parcel of the modern university, but it also demonstrates the level of its success. There appeared an urgent need for understanding the nature of universities’ network interactions and finding the most effective models of their network cooperation. The article analyzes partnership network communities with higher educational establishments (universities’ participation, which are being actively created nowadays. The conditions for successful network activities of a university in scientific, academic and professional network communities are presented.

  19. Accuracy in activation analysis: count rate effects

    International Nuclear Information System (INIS)

    Lindstrom, R.M.; Fleming, R.F.

    1980-01-01

    The accuracy inherent in activation analysis is ultimately limited by the uncertainty of counting statistics. When careful attention is paid to detail, several workers have shown that all systematic errors can be reduced to an insignificant fraction of the total uncertainty, even when the statistical limit is well below one percent. A matter of particular importance is the reduction of errors due to high counting rate. The loss of counts due to random coincidence (pulse pileup) in the amplifier and to digitization time in the ADC may be treated as a series combination of extending and non-extending dead times, respectively. The two effects are experimentally distinct. Live timer circuits in commercial multi-channel analyzers compensate properly for ADC dead time for long-lived sources, but not for pileup. Several satisfactory solutions are available, including pileup rejection and dead time correction circuits, loss-free ADCs, and computed corrections in a calibrated system. These methods are sufficiently reliable and well understood that a decaying source can be measured routinely with acceptably small errors at a dead time as high as 20 percent

  20. Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

    Directory of Open Access Journals (Sweden)

    Klipp Edda

    2006-12-01

    Full Text Available Abstract Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. Conclusion Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases.

  1. A reanalysis of "Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons".

    Science.gov (United States)

    Engelken, Rainer; Farkhooi, Farzad; Hansel, David; van Vreeswijk, Carl; Wolf, Fred

    2016-01-01

    Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF) neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

  2. Circumpolar Active Layer Monitoring (CALM) Program Network, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The CALM network includes 168 active sites in both hemispheres with 15 participating countries. This network represents the only coordinated and standardized program...

  3. Distinguishing the rates of gene activation from phenotypic variations.

    Science.gov (United States)

    Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

    2015-06-18

    Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which regime a considered gene regulatory network is in from their phenotypic variations. We studied a gene expression model with positive feedbacks when genetic switching rates vary over a wide range. With the goal of providing a method to distinguish the regime of the switching rates, we first focus on understanding the essential dynamics of gene expression system in different cases. In the regime of slow switching rates, we found that the effective dynamics can be reduced to independent evolutions on two separate layers corresponding to gene activation and inactivation states, and the transitions between two layers are rare events, after which the system goes mainly along deterministic ODE trajectories on a particular layer to reach new steady states. The energy landscape in this regime can be well approximated by using Gaussian mixture model. In the regime of intermediate switching rates, we analyzed the mean switching time to investigate the stability of the system in different parameter ranges. We also discussed the case of fast switching rates from the viewpoint of transition state theory. Based on the obtained results, we made a proposal to distinguish these three regimes in a simulation experiment. We identified the intermediate regime from the fact that the strength of cellular memory is lower than the other two cases, and the fast and slow regimes can be distinguished by their different perturbation-response behavior with respect to the switching rates perturbations. We proposed a

  4. Phase-dependent effects of stimuli locked to oscillatory activity in cultured cortical networks

    NARCIS (Netherlands)

    Stegenga, J.; le Feber, Jakob; Marani, Enrico; Rutten, Wim

    The archetypal activity pattern in cultures of dissociated neurons is spontaneous network-wide bursting. Bursts may interfere with controlled activation of synaptic plasticity, but can be suppressed by the application of stimuli at a sufficient rate. We sinusoidally modulated (4 Hz) the pulse rate

  5. Network governance of active employment policy

    DEFF Research Database (Denmark)

    Damgaard, Bodil; Torfing, Jacob

    2010-01-01

    The recent reform of the Danish governance system in the field of active employment policy has been subject to fierce criticism, as many commentators fear that it is the beginning of the end of the Danish Model of active stakeholder involvement. Drawing on both quantitative and qualitative data, ......, the tight metagovernance of the LECs does not seem to straightjacket the LECs as there is a considerable scope for local policy making which makes it worthwhile for the social partners to participate in the local networks.......The recent reform of the Danish governance system in the field of active employment policy has been subject to fierce criticism, as many commentators fear that it is the beginning of the end of the Danish Model of active stakeholder involvement. Drawing on both quantitative and qualitative data......, this study aims to analyse the impact of the governance reform by assessing the initial experiences with the Local Employment Councils (LECs). The analysis shows that the LECs are relatively well-functioning and contribute to an effective and democratic governance of local employment policy. Furthermore...

  6. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  7. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.

    Directory of Open Access Journals (Sweden)

    Saket Navlakha

    2015-07-01

    Full Text Available Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains.

  8. Active Traffic Capture for Network Forensics

    Science.gov (United States)

    Slaviero, Marco; Granova, Anna; Olivier, Martin

    Network traffic capture is an integral part of network forensics, but current traffic capture techniques are typically passive in nature. Under heavy loads, it is possible for a sniffer to miss packets, which affects the quality of forensic evidence.

  9. Application of neural networks to seismic active control

    International Nuclear Information System (INIS)

    Tang, Yu.

    1995-01-01

    An exploratory study on seismic active control using an artificial neural network (ANN) is presented in which a singledegree-of-freedom (SDF) structural system is controlled by a trained neural network. A feed-forward neural network and the backpropagation training method are used in the study. In backpropagation training, the learning rate is determined by ensuring the decrease of the error function at each training cycle. The training patterns for the neural net are generated randomly. Then, the trained ANN is used to compute the control force according to the control algorithm. The control strategy proposed herein is to apply the control force at every time step to destroy the build-up of the system response. The ground motions considered in the simulations are the N21E and N69W components of the Lake Hughes No. 12 record that occurred in the San Fernando Valley in California on February 9, 1971. Significant reduction of the structural response by one order of magnitude is observed. Also, it is shown that the proposed control strategy has the ability to reduce the peak that occurs during the first few cycles of the time history. These promising results assert the potential of applying ANNs to active structural control under seismic loads

  10. Energy-aware architecture for multi-rate ad hoc networks

    Directory of Open Access Journals (Sweden)

    Ahmed Yahya

    2010-06-01

    Full Text Available The backbone of ad hoc network design is energy performance and bandwidth resources limitations. Multi-rate adaptation architectures have been proposed to reduce the control overhead and to increase bandwidth utilization efficiency. In this paper, we propose a multi-rate protocol to provide the highest network performance under very low control overhead. The efficiency of the proposed auto multi-rate protocol is validated extensive simulations using QualNet network simulator. The simulation results demonstrate that our solution significantly improves the overall network performance.

  11. A new chaotic Hopfield network with piecewise linear activation function

    International Nuclear Information System (INIS)

    Peng-Sheng, Zheng; Wan-Sheng, Tang; Jian-Xiong, Zhang

    2010-01-01

    This paper presents a new chaotic Hopfield network with a piecewise linear activation function. The dynamic of the network is studied by virtue of the bifurcation diagram, Lyapunov exponents spectrum and power spectrum. Numerical simulations show that the network displays chaotic behaviours for some well selected parameters

  12. Fluid limits for bandwidth-sharing networks with rate constraints

    NARCIS (Netherlands)

    M. Frolkova (Masha); J. Reed (Josh); A.P. Zwart (Bert)

    2013-01-01

    htmlabstractBandwidth-sharing networks as introduced by Massouli\\'e~\\& Roberts (1998) model the dynamic interaction among an evolving population of elastic flows competing for several links. With policies based on optimization procedures, such models are of interest both from a~Queueing Theory and

  13. Using Active Networking to Detect and Troubleshoot Issues in Tactical Data Networks

    Science.gov (United States)

    2014-06-01

    networking (SDN) paradigm, which has gained popularity in recent years, has its roots in the idea of programmable networks [6]. By extending the...278–289, Aug. 2011. 67 [13] M. Hicks, P. Kakkar, J. T. Moore, C. A. Gunter, and S. Nettles , “Plan: A programming language for active networks,” ACM

  14. Network Layer Protocol Activation for Packet Data Access in UMTS WCDMA Laboratory Network

    OpenAIRE

    Lakkisto, Erkka

    2011-01-01

    The purpose of this Bachelor’s Thesis was to set up the UMTS WCDMA network in the laboratory environment of Helsinki Metropolia University of Applied Sciences and to study the network layer protocol activation for packet data access. The development of 3G technology has been very rapid and it can be considered as one of the main technologies in telecommunication. Implementing the laboratory network in Metropolia enables teaching and researching of the modern network technology. Labora...

  15. Active Computer Network Defense: An Assessment

    Science.gov (United States)

    2001-04-01

    sufficient base of knowledge in information technology can be assumed to be working on some form of computer network warfare, even if only defensive in...the Defense Information Infrastructure (DII) to attack. Transmission Control Protocol/ Internet Protocol (TCP/IP) networks are inherently resistant to...aims to create this part of information superiority, and computer network defense is one of its fundamental components. Most of these efforts center

  16. Tourist activated networks: Implications for dynamic packaging systems in tourism

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike; Fesenmaier, Daniel R.

    2008-01-01

    This paper discusses tourist activated networks as a concept to inform technological applications supporting dynamic bundling and en-route recommendations. Empirical data was collected from travellers who visited a regional destination in the US and then analyzed with respect to its network...... structure. The results indicate that the tourist activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist activated network and provide implications for technology design and tourism...

  17. A packet-based dual-rate PID control strategy for a slow-rate sensing Networked Control System.

    Science.gov (United States)

    Cuenca, A; Alcaina, J; Salt, J; Casanova, V; Pizá, R

    2018-05-01

    This paper introduces a packet-based dual-rate control strategy to face time-varying network-induced delays, packet dropouts and packet disorder in a Networked Control System. Slow-rate sensing enables to achieve energy saving and to avoid packet disorder. Fast-rate actuation makes reaching the desired control performance possible. The dual-rate PID controller is split into two parts: a slow-rate PI controller located at the remote side (with no permanent communication to the plant) and a fast-rate PD controller located at the local side. The remote side also includes a prediction stage in order to generate the packet of future, estimated slow-rate control actions. These actions are sent to the local side and converted to fast-rate ones to be used when a packet does not arrive at this side due to the network-induced delay or due to occurring dropouts. The proposed control solution is able to approximately reach the nominal (no-delay, no-dropout) performance despite the existence of time-varying delays and packet dropouts. Control system stability is ensured in terms of probabilistic Linear Matrix Inequalities (LMIs). Via real-time control for a Cartesian robot, results clearly reveal the superiority of the control solution compared to a previous proposal by authors. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune; Andrea Francini; Lisa Zhang

    2011-07-12

    This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet. The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks

  19. Competing dynamic phases of active polymer networks

    Science.gov (United States)

    Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

    Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

  20. Networking Activities at the Library of Congress.

    Science.gov (United States)

    Maruyama, Lenore S.; Avram, Henriette D.

    1979-01-01

    Examines the background studies and high-priority projects which will lay the groundwork for the library bibliographic component of a National Library and Information Service Network and reviews the progress and problems of the national network as evidenced by current cooperative projects. (CWM)

  1. Linking Environmental Orientation to Start-ups’ Networking Activities

    DEFF Research Database (Denmark)

    Dickel, Petra; Ritter, Thomas

    Besides for-profit start-ups, an increasing number of firms start their existence with the purpose to “do good” for society – mirrored in an increasing academic discussion of sustainable firms. Yet, there is little research on the networking activities of start-ups that do not have profit...... generation as their primary focus. Addressing this research gap, we develop hypotheses on the different networking activities of environmentally oriented start-ups arguing that their societal focus has a positive impact on the frequency of their networking and the size of their network. For empirically...... investigating such networking differences, we use data from 179 technology-based start-ups and show that start-ups with a strong external environmental orientation have significantly higher networking frequency and build larger networks. On the contrary, strong internal environmental orientation is linked...

  2. State estimation for networked control systems using fixed data rates

    Science.gov (United States)

    Liu, Qing-Quan; Jin, Fang

    2017-07-01

    This paper investigates state estimation for linear time-invariant systems where sensors and controllers are geographically separated and connected via a bandwidth-limited and errorless communication channel with the fixed data rate. All plant states are quantised, coded and converted together into a codeword in our quantisation and coding scheme. We present necessary and sufficient conditions on the fixed data rate for observability of such systems, and further develop the data-rate theorem. It is shown in our results that there exists a quantisation and coding scheme to ensure observability of the system if the fixed data rate is larger than the lower bound given, which is less conservative than the one in the literature. Furthermore, we also examine the role that the disturbances have on the state estimation problem in the case with data-rate limitations. Illustrative examples are given to demonstrate the effectiveness of the proposed method.

  3. Exponential stability of Cohen-Grossberg neural networks with a general class of activation functions

    International Nuclear Information System (INIS)

    Wan Anhua; Wang Miansen; Peng Jigen; Qiao Hong

    2006-01-01

    In this Letter, the dynamics of Cohen-Grossberg neural networks model are investigated. The activation functions are only assumed to be Lipschitz continuous, which provide a much wider application domain for neural networks than the previous results. By means of the extended nonlinear measure approach, new and relaxed sufficient conditions for the existence, uniqueness and global exponential stability of equilibrium of the neural networks are obtained. Moreover, an estimate for the exponential convergence rate of the neural networks is precisely characterized. Our results improve those existing ones

  4. The signal extraction of fetal heart rate based on wavelet transform and BP neural network

    Science.gov (United States)

    Yang, Xiao Hong; Zhang, Bang-Cheng; Fu, Hu Dai

    2005-04-01

    This paper briefly introduces the collection and recognition of bio-medical signals, designs the method to collect FM signals. A detailed discussion on the system hardware, structure and functions is also given. Under LabWindows/CVI,the hardware and the driver do compatible, the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively, expedites program reflect speed, improves the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network; Finally the results of collecting signals and BP networks are discussed. 8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.

  5. Finding quasi-optimal network topologies for information transmission in active networks.

    Science.gov (United States)

    Baptista, Murilo S; de Carvalho, Josué X; Hussein, Mahir S

    2008-01-01

    This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

  6. Finding quasi-optimal network topologies for information transmission in active networks.

    Directory of Open Access Journals (Sweden)

    Murilo S Baptista

    Full Text Available This work clarifies the relation between network circuit (topology and behaviour (information transmission and synchronization in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

  7. Network-dependent modulation of brain activity during sleep.

    Science.gov (United States)

    Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

    2014-09-01

    Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Rate adaptation in ad hoc networks based on pricing

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available that incorporates penalty (pricing) obtruded to users’ choices of transmission parameters to curb the self-interest behaviour. Therefore users determine their data rates and transmit power based on the perceived coupled interference at the intended receiver...

  9. High throughput route selection in multi-rate wireless mesh networks

    Institute of Scientific and Technical Information of China (English)

    WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

    2008-01-01

    Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

  10. Physician social networks and variation in rates of complications after radical prostatectomy.

    Science.gov (United States)

    Evan Pollack, Craig; Wang, Hao; Bekelman, Justin E; Weissman, Gary; Epstein, Andrew J; Liao, Kaijun; Dugoff, Eva H; Armstrong, Katrina

    2014-07-01

    Variation in care within and across geographic areas remains poorly understood. The goal of this article was to examine whether physician social networks-as defined by shared patients-are associated with rates of complications after radical prostatectomy. In five cities, we constructed networks of physicians on the basis of their shared patients in 2004-2005 Surveillance, Epidemiology and End Results-Medicare data. From these networks, we identified subgroups of urologists who most frequently shared patients with one another. Among men with localized prostate cancer who underwent radical prostatectomy, we used multilevel analysis with generalized linear mixed-effect models to examine whether physician network structure-along with specific characteristics of the network subgroups-was associated with rates of 30-day and late urinary complications, and long-term incontinence after accounting for patient-level sociodemographic, clinical factors, and urologist patient volume. Networks included 2677 men in five cities who underwent radical prostatectomy. The unadjusted rate of 30-day surgical complications varied across network subgroups from an 18.8 percentage-point difference in the rate of complications across network subgroups in city 1 to a 26.9 percentage-point difference in city 5. Large differences in unadjusted rates of late urinary complications and long-term incontinence across subgroups were similarly found. Network subgroup characteristics-average urologist centrality and patient racial composition-were significantly associated with rates of surgical complications. Analysis of physician networks using Surveillance, Epidemiology and End Results-Medicare data provides insight into observed variation in rates of complications for localized prostate cancer. If validated, such approaches may be used to target future quality improvement interventions. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier

  11. Open-source hardware and software and web application for gamma dose rate network operation

    International Nuclear Information System (INIS)

    Luff, R.; Zaehringer, M.; Harms, W.; Bleher, M.; Prommer, B.; Stoehlker, U.

    2014-01-01

    The German Federal Office for Radiation Protection operates a network of about 1800 gamma dose rate stations as a part of the national emergency preparedness plan. Each of the six network centres is capable of operating the network alone. Most of the used hardware and software have been developed in-house under open-source license. Short development cycles and close cooperation between developers and users ensure robustness, transparency and fast maintenance procedures, thus avoiding unnecessary complex solutions. This also reduces the overall costs of the network operation. An easy-to-expand web interface has been developed to make the complete system available to other interested network operators in order to increase cooperation between different countries. The interface is also regularly in use for education during scholarships of trainees supported, e.g. by the 'international Atomic Energy Agency' to operate a local area dose rate monitoring test network. (authors)

  12. Reduction Method for Active Distribution Networks

    DEFF Research Database (Denmark)

    Raboni, Pietro; Chen, Zhe

    2013-01-01

    On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution...... Networks also would be too large. In this paper an adaptive aggregation method for subsystems with power electronic interfaced generators and voltage dependant loads is proposed. With this tool may be relatively easier including distribution networks into security assessment. The method is validated...... by comparing the results obtained in PSCAD® with the detailed network model and with the reduced one. Moreover the control schemes of a wind turbine and a photovoltaic plant included in the detailed network model are described....

  13. Adaptive Relay Activation in the Network Coding Protocols

    DEFF Research Database (Denmark)

    Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Fitzek, Frank

    2015-01-01

    State-of-the-art Network coding based routing protocols exploit the link quality information to compute the transmission rate in the intermediate nodes. However, the link quality discovery protocols are usually inaccurate, and introduce overhead in wireless mesh networks. In this paper, we presen...

  14. Topic-oriented community detection of rating-based social networks

    Directory of Open Access Journals (Sweden)

    Ali Reihanian

    2016-07-01

    Full Text Available Nowadays, real world social networks contain a vast range of information including shared objects, comments, following information, etc. Finding meaningful communities in this kind of networks is an interesting research area and has attracted the attention of many researchers. The community structure of complex networks reveals both their organization and hidden relations among their constituents. Most of the researches in the field of community detection mainly focus on the topological structure of the network without performing any content analysis. In recent years, a number of researches have proposed approaches which consider both the contents that are interchanged in networks, and the topological structures of the networks in order to find more meaningful communities. In this research, the effect of topic analysis in finding more meaningful communities in social networking sites in which the users express their feelings toward different objects (like movies by means of rating is demonstrated by performing extensive experiments.

  15. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Directory of Open Access Journals (Sweden)

    Axel Hutt

    Full Text Available Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  16. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Science.gov (United States)

    Hutt, Axel; Mierau, Andreas; Lefebvre, Jérémie

    Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  17. Google matrix of the world network of economic activities

    Science.gov (United States)

    Kandiah, Vivek; Escaith, Hubert; Shepelyansky, Dima L.

    2015-07-01

    Using the new data from the OECD-WTO world network of economic activities we construct the Google matrix G of this directed network and perform its detailed analysis. The network contains 58 countries and 37 activity sectors for years 1995 and 2008. The construction of G, based on Markov chain transitions, treats all countries on equal democratic grounds while the contribution of activity sectors is proportional to their exchange monetary volume. The Google matrix analysis allows to obtain reliable ranking of countries and activity sectors and to determine the sensitivity of CheiRank-PageRank commercial balance of countries in respect to price variations and labor cost in various countries. We demonstrate that the developed approach takes into account multiplicity of network links with economy interactions between countries and activity sectors thus being more efficient compared to the usual export-import analysis. The spectrum and eigenstates of G are also analyzed being related to specific activity communities of countries.

  18. Fixed-Point Approximations of Bandwidth-Sharing Networks with Rate Constraints

    NARCIS (Netherlands)

    M. Frolkova (Masha); J. Reed (Josh); A.P. Zwart (Bert)

    2011-01-01

    htmlabstractBandwidth-sharing networks are important flow level models of communication networks. We focus on the fact that it takes a signicant number of users to saturate a link, necessitating the inclusion of individual rate constraints. In particular we extend work of Reed & Zwart on fluid

  19. Identifying Interbank Loans, Rates, and Claims Networks from Transactional Data

    NARCIS (Netherlands)

    Leon Rincon, C.E.; Cely, Jorge; Cadena, Carlos

    2015-01-01

    We identify interbank (i.e. non-collateralized) loans from the Colombian large-value payment system by implementing Furfine’s method. After identifying interbank loans from transactional data we obtain the interbank rates and claims without relying on financial institutions’ reported data.

  20. Simulating activation propagation in social networks using the graph theory

    Directory of Open Access Journals (Sweden)

    František Dařena

    2010-01-01

    Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

  1. Joint sensor placement and power rating selection in energy harvesting wireless sensor networks

    KAUST Repository

    Bushnaq, Osama M.; Al-Naffouri, Tareq Y.; Chepuri, Sundeep Prabhakar; Leus, Geert

    2017-01-01

    In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account the amount of energy harvested by the sensing nodes, communication link quality

  2. Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

    Science.gov (United States)

    2008-03-01

    warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

  3. On-line validation of feedwater flow rate in nuclear power plants using neural networks

    International Nuclear Information System (INIS)

    Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.

    1994-01-01

    On-line calibration of feedwater flow rate measurement in nuclear power plants provides a continuous realistic value of feedwater flow rate. It also reduces the manpower required for periodic calibration needed due to the fouling and defouling of the venturi meter surface condition. This paper presents a method for on-line validation of feedwater flow rate in nuclear power plants. The method is an improvement of the previously developed method which is based on the use of a set of process variables dynamically related to the feedwater flow rate. The online measurements of this set of variables are used as inputs to a neural network to obtain an estimate of the feedwater flow rate reading. The difference between the on-line feedwater flow rate reading, and the neural network estimate establishes whether there is a need to apply a correction factor to the feedwater flow rate measurement for calculation of the actual reactor power. The method was applied to the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant. The venturi meters used for flow measurements are susceptible to frequent fouling that degrades their measurement accuracy. The fouling effects can cause an inaccuracy of up to 3% relative error in feedwater flow rate reading. A neural network, whose inputs were the readings of a set of reference instruments, was designed to predict both feedwater flow rates simultaneously. A multi-layer feedforward neural network employing the backpropagation algorithm was used. A number of neural network training tests were performed to obtain an optimum filtering technique of the input/output data of the neural networks. The result of the selection of the filtering technique was confirmed by numerous Fast Fourier Transform (FFT) tests. Training and testing were done on data from TMI-1 nuclear power plant. The results show that the neural network can predict the correct flow rates with an absolute relative error of less than 2%

  4. Large deviations and queueing networks: Methods for rate function identification

    OpenAIRE

    Atar, Rami; Dupuis, Paul

    1999-01-01

    This paper considers the problem of rate function identification for multidimensional queueing models with feedback. A set of techniques are introduced which allow this identification when the model possesses certain structural properties. The main tools used are representation formulas for exponential integrals, weak convergence methods, and the regularity properties of associated Skorokhod Problems. Two examples are treated as special cases of the general theory: the classical Jackson netwo...

  5. Improving publication rates in a collaborative clinical trials research network

    Science.gov (United States)

    Archer, Stephanie Wilson; Carlo, Waldemar A.; Truog, William E.; Stevenson, David K.; Van Meurs, Krisa P.; Sánchez, Pablo J.; Das, Abhik; Devaskar, Uday; Nelin, Leif D.; Petrie Huitema, Carolyn M.; Crawford, Margaret M.; Higgins, Rosemary D.

    2016-01-01

    Unpublished results can bias biomedical literature, favoring positive over negative findings, primary over secondary analyses, and can lead to duplicate studies that unnecessarily endanger subjects and waste resources. The Neonatal Research Network’s (NRN) publication policies for approving, reviewing, and tracking abstracts and papers work to combat these problems. In 2003, the NRN restricted investigators with unfinished manuscripts from proposing new ones and in 2010, urged authors to complete long-outstanding manuscripts. Data from 1991 to 2015 were analyzed to determine effectiveness of these policy changes. The NRN has achieved an overall publication rate of 78% for abstracts. For 1990–2002, of 137 abstracts presented, 43 (31%) were published within 2 years; for 2003–2009, after the manuscript completion policy was instituted, of 140 abstracts presented, 68 (49%) were published within 2 years. Following the effort in 2010, the rate increased to 64%. The NRN surpassed reported rates by developing a comprehensive process, holding investigators accountable and tracking abstracts from presentation to publication. PMID:27423510

  6. An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks

    International Nuclear Information System (INIS)

    Cao Jinde

    2004-01-01

    In this Letter, the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are estimated by means of matrix measure and comparison principle. A new estimation is given for the domain of attraction of memory patterns and exponential convergence rate. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks

  7. Achievable Performance of Zero-Delay Variable-Rate Coding in Rate-Constrained Networked Control Systems with Channel Delay

    DEFF Research Database (Denmark)

    Barforooshan, Mohsen; Østergaard, Jan; Stavrou, Fotios

    2017-01-01

    This paper presents an upper bound on the minimum data rate required to achieve a prescribed closed-loop performance level in networked control systems (NCSs). The considered feedback loop includes a linear time-invariant (LTI) plant with single measurement output and single control input. Moreover......, in this NCS, a causal but otherwise unconstrained feedback system carries out zero-delay variable-rate coding, and control. Between the encoder and decoder, data is exchanged over a rate-limited noiseless digital channel with a known constant time delay. Here we propose a linear source-coding scheme...

  8. Dynamical Properties of Discrete-Time Background Neural Networks with Uniform Firing Rate

    Directory of Open Access Journals (Sweden)

    Min Wan

    2013-01-01

    Full Text Available The dynamics of a discrete-time background network with uniform firing rate and background input is investigated. The conditions for stability are firstly derived. An invariant set is then obtained so that the nondivergence of the network can be guaranteed. In the invariant set, it is proved that all trajectories of the network starting from any nonnegative value will converge to a fixed point under some conditions. In addition, bifurcation and chaos are discussed. It is shown that the network can engender bifurcation and chaos with the increase of background input. The computations of Lyapunov exponents confirm the chaotic behaviors.

  9. The Impact of the Physical Activity Policy Research Network.

    Science.gov (United States)

    Manteiga, Alicia M; Eyler, Amy A; Valko, Cheryl; Brownson, Ross C; Evenson, Kelly R; Schmid, Thomas

    2017-03-01

    Lack of physical activity is one of the greatest challenges of the 21st century. The Physical Activity Policy Research Network (PAPRN) is a thematic network established in 2004 to identify determinants, implementation, and outcomes of policies that are effective in increasing physical activity. The purpose of this study is to describe the products of PAPRN and make recommendations for future research and best practices. A mixed methods approach was used to obtain both quantitative and qualitative data on the network. First, in 2014, PAPRN's dissemination products from 2004 to 2014 were extracted and reviewed, including 57 publications and 56 presentations. Next, semi-structured qualitative interviews were conducted with 25 key network participants from 17 locations around the U.S. The transcripts were transcribed and coded. The results of the interviews indicated that the research network addressed several components of its mission, including the identification of physical activity policies, determinants of these policies, and the process of policy implementation. However, research focusing on physical activity policy outcomes was limited. Best practices included collaboration between researchers and practitioners and involvement of practitioners in research design, data collection, and dissemination of results. PAPRN is an example of a productive research network and has contributed to both the process and content of physical activity policy research over the past decade. Future research should emphasize physical activity policy outcomes. Additionally, increased partnerships with practitioners for collaborative, cross-sectoral physical activity policy research should be developed. Copyright © 2016 American Journal of Preventive Medicine. All rights reserved.

  10. The impact of ambient dose rate measuring network and precipitation radar system for detection of environmental radioactivity released by accident

    International Nuclear Information System (INIS)

    Bleher, M; Stoehlker, U.

    2003-01-01

    For the surveillance of environmental radioactivity, the German measuring network of BfS consists of more than 2000 stations where the ambient gamma dose rate is continuously measured. This network is a helpful tool to detect and localise enhanced environmental contamination from artificial radionuclides. The threshold for early warning is so low, that already an additional dose rate contribution of 0,07 μGy/h is detectable. However, this threshold is frequently exceeded due to precipitation events caused by washout of natural activity in air. Therefore, the precipitation radar system of the German Weather Service provides valuable information on the problem, whether the increase of the ambient dose rate is due to natural or man-made events. In case of an accidental release, the data of this radar system show small area precipitation events and potential local hot spots not detected by the measuring network. For the phase of cloud passage, the ambient dose rate measuring network provides a reliable database for the evaluation of the current situation and its further development. It is possible to compare measured data for dose rate with derived intervention levels for countermeasures like ''sheltering''. Thus, critical regions can be identified and it is possible to verify implemented countermeasures. During and after this phase of cloud passage the measured data of the monitoring network help to adapt the results of the national decision support systems PARK and RODOS. Therefore, it is necessary to derive the actual additional contribution to the ambient dose rate. Map representations of measured dose rate are rapidly available and helpful to optimise measurement strategies of mobile systems and collection strategies for samples of agricultural products. (orig.)

  11. Forecasting the mortality rates of Indonesian population by using neural network

    Science.gov (United States)

    Safitri, Lutfiani; Mardiyati, Sri; Rahim, Hendrisman

    2018-03-01

    A model that can represent a problem is required in conducting a forecasting. One of the models that has been acknowledged by the actuary community in forecasting mortality rate is the Lee-Certer model. Lee Carter model supported by Neural Network will be used to calculate mortality forecasting in Indonesia. The type of Neural Network used is feedforward neural network aligned with backpropagation algorithm in python programming language. And the final result of this study is mortality rate in forecasting Indonesia for the next few years

  12. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Mingfu Li

    2014-01-01

    Full Text Available Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  13. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    Science.gov (United States)

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  14. Heart Rate Estimated from Body Movements at Six Degrees of Freedom by Convolutional Neural Networks.

    Science.gov (United States)

    Lee, Hyunwoo; Whang, Mincheol

    2018-05-01

    Cardiac activity has been monitored continuously in daily life by virtue of advanced medical instruments with microelectromechanical system (MEMS) technology. Seismocardiography (SCG) has been considered to be free from the burden of measurement for cardiac activity, but it has been limited in its application in daily life. The most important issues regarding SCG are to overcome the limitations of motion artifacts due to the sensitivity of motion sensor. Although novel adaptive filters for noise cancellation have been developed, they depend on the researcher’s subjective decision. Convolutional neural networks (CNNs) can extract significant features from data automatically without a researcher’s subjective decision, so that signal processing has been recently replaced as CNNs. Thus, this study aimed to develop a novel method to enhance heart rate estimation from thoracic movement by CNNs. Thoracic movement was measured by six-axis accelerometer and gyroscope signals using a wearable sensor that can be worn by simply clipping on clothes. The dataset was collected from 30 participants (15 males, 15 females) using 12 measurement conditions according to two physical conditions (i.e., relaxed and aroused conditions), three body postures (i.e., sitting, standing, and supine), and six movement speeds (i.e., 3.2, 4.5, 5.8, 6.4, 8.5, and 10.3 km/h). The motion data (i.e., six-axis accelerometer and gyroscope) and heart rate (i.e., electrocardiogram (ECG)) were determined as the input data and labels in the dataset, respectively. The CNN model was developed based on VGG Net and optimized by testing according to network depth and data augmentation. The ensemble network of the VGG-16 without data augmentation and the VGG-19 with data augmentation was determined as optimal architecture for generalization. As a result, the proposed method showed higher accuracy than the previous SCG method using signal processing in most measurement conditions. The three main contributions

  15. Heart Rate Estimated from Body Movements at Six Degrees of Freedom by Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Hyunwoo Lee

    2018-05-01

    Full Text Available Cardiac activity has been monitored continuously in daily life by virtue of advanced medical instruments with microelectromechanical system (MEMS technology. Seismocardiography (SCG has been considered to be free from the burden of measurement for cardiac activity, but it has been limited in its application in daily life. The most important issues regarding SCG are to overcome the limitations of motion artifacts due to the sensitivity of motion sensor. Although novel adaptive filters for noise cancellation have been developed, they depend on the researcher’s subjective decision. Convolutional neural networks (CNNs can extract significant features from data automatically without a researcher’s subjective decision, so that signal processing has been recently replaced as CNNs. Thus, this study aimed to develop a novel method to enhance heart rate estimation from thoracic movement by CNNs. Thoracic movement was measured by six-axis accelerometer and gyroscope signals using a wearable sensor that can be worn by simply clipping on clothes. The dataset was collected from 30 participants (15 males, 15 females using 12 measurement conditions according to two physical conditions (i.e., relaxed and aroused conditions, three body postures (i.e., sitting, standing, and supine, and six movement speeds (i.e., 3.2, 4.5, 5.8, 6.4, 8.5, and 10.3 km/h. The motion data (i.e., six-axis accelerometer and gyroscope and heart rate (i.e., electrocardiogram (ECG were determined as the input data and labels in the dataset, respectively. The CNN model was developed based on VGG Net and optimized by testing according to network depth and data augmentation. The ensemble network of the VGG-16 without data augmentation and the VGG-19 with data augmentation was determined as optimal architecture for generalization. As a result, the proposed method showed higher accuracy than the previous SCG method using signal processing in most measurement conditions. The three main

  16. Facility Activity Inference Using Radiation Networks

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Nageswara S. [ORNL; Ramirez Aviles, Camila A. [ORNL

    2017-11-01

    We consider the problem of inferring the operational status of a reactor facility using measurements from a radiation sensor network deployed around the facility’s ventilation off-gas stack. The intensity of stack emissions decays with distance, and the sensor counts or measurements are inherently random with parameters determined by the intensity at the sensor’s location. We utilize the measurements to estimate the intensity at the stack, and use it in a one-sided Sequential Probability Ratio Test (SPRT) to infer on/off status of the reactor. We demonstrate the superior performance of this method over conventional majority fusers and individual sensors using (i) test measurements from a network of 21 NaI detectors, and (ii) effluence measurements collected at the stack of a reactor facility. We also analytically establish the superior detection performance of the network over individual sensors with fixed and adaptive thresholds by utilizing the Poisson distribution of the counts. We quantify the performance improvements of the network detection over individual sensors using the packing number of the intensity space.

  17. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  18. Fault diagnosis for temperature, flow rate and pressure sensors in VAV systems using wavelet neural network

    Energy Technology Data Exchange (ETDEWEB)

    Du, Zhimin; Jin, Xinqiao; Yang, Yunyu [School of Mechanical Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, Shanghai (China)

    2009-09-15

    Wavelet neural network, the integration of wavelet analysis and neural network, is presented to diagnose the faults of sensors including temperature, flow rate and pressure in variable air volume (VAV) systems to ensure well capacity of energy conservation. Wavelet analysis is used to process the original data collected from the building automation first. With three-level wavelet decomposition, the series of characteristic information representing various operation conditions of the system are obtained. In addition, neural network is developed to diagnose the source of the fault. To improve the diagnosis efficiency, three data groups based on several physical models or balances are classified and constructed. Using the data decomposed by three-level wavelet, the neural network can be well trained and series of convergent networks are obtained. Finally, the new measurements to diagnose are similarly processed by wavelet. And the well-trained convergent neural networks are used to identify the operation condition and isolate the source of the fault. (author)

  19. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  20. Synaptic model for spontaneous activity in developing networks

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Rinzel, J.

    2005-01-01

    Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic...... dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between...

  1. Decentralized control of transmission rates in energy-critical wireless networks

    KAUST Repository

    Xia, Li

    2013-06-01

    In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

  2. Decentralized control of transmission rates in energy-critical wireless networks

    KAUST Repository

    Xia, Li; Shihada, Basem

    2013-01-01

    In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

  3. Evaluating Maximum Wind Energy Exploitation in Active Distribution Networks

    DEFF Research Database (Denmark)

    Siano, Pierluigi; Chen, Peiyuan; Chen, Zhe

    2010-01-01

    The increased spreading of distributed and renewable generation requires moving towards active management of distribution networks. In this paper, in order to evaluate maximum wind energy exploitation in active distribution networks, a method based on a multi-period optimal power flow (OPF......) analysis is proposed. Active network management schemes such as coordinated voltage control, energy curtailment and power factor control are integrated in the method in order to investigate their impacts on the maximization of wind energy exploitation. Some case studies, using real data from a Danish...... distribution system, confirmed the effectiveness of the proposed method in evaluating the optimal applications of active management schemes to increase wind energy harvesting without costly network reinforcement for the connection of wind generation....

  4. The effect of zealots on the rate of consensus achievement in complex networks

    Science.gov (United States)

    Kashisaz, Hadi; Hosseini, S. Samira; Darooneh, Amir H.

    2014-05-01

    In this study, we investigate the role of zealots on the result of voting process on both scale-free and Watts-Strogatz networks. We observe that inflexible individuals are very effective in consensus achievement and also in the rate of ordering process in complex networks. Zealots make the magnetization of the system to vary exponentially with time. We obtain that on SF networks, increasing the zealots' population, Z, exponentially increases the rate of consensus achievement. The time needed for the system to reach a desired magnetization, shows a power-law dependence on Z. As well, we obtain that the decay time of the order parameter shows a power-law dependence on Z. We also investigate the role of zealots' degree on the rate of ordering process and finally, we analyze the effect of network's randomness on the efficiency of zealots. Moving from a regular to a random network, the re-wiring probability P increases. We show that with increasing P, the efficiency of zealots for reducing the consensus achievement time increases. The rate of consensus is compared with the rate of ordering for different re-wiring probabilities of WS networks.

  5. How to Identify Success Among Networks That Promote Active Living.

    Science.gov (United States)

    Litt, Jill; Varda, Danielle; Reed, Hannah; Retrum, Jessica; Tabak, Rachel; Gustat, Jeanette; O'Hara Tompkins, Nancy

    2015-11-01

    We evaluated organization- and network-level factors that influence organizations' perceived success. This is important for managing interorganizational networks, which can mobilize communities to address complex health issues such as physical activity, and for achieving change. In 2011, we used structured interview and network survey data from 22 states in the United States to estimate multilevel random-intercept models to understand organization- and network-level factors that explain perceived network success. A total of 53 of 59 "whole networks" met the criteria for inclusion in the analysis (89.8%). Coordinators identified 559 organizations, with 3 to 12 organizations from each network taking the online survey (response rate = 69.7%; range = 33%-100%). Occupying a leadership position (P Organizations' perceptions of success can influence decisions about continuing involvement and investment in networks designed to promote environment and policy change for active living. Understanding these factors can help leaders manage complex networks that involve diverse memberships, varied interests, and competing community-level priorities.

  6. Consumer Activities and Reactions to Social Network Marketing

    Directory of Open Access Journals (Sweden)

    Bistra Vassileva

    2017-06-01

    Full Text Available The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM referral behaviour, and purchase intentions. Consumers are investigated based on their attitudes toward social network marketing and basic socio-demographic covariates using data from a sample size of 700 Bulgarian respondents (age group 21–54 years, Internet users, urban inhabitants. Factor and cluster analyses are applied. It is found that consumers are willing to receive information about brands and companies through social networks. They like to talk in social networks about these brands and companies and to share information as well (factor 2, brand engagement. Internet users are willing to share information received through social network advertising (factor 1, wom referral behaviour but they would not buy a certain brand as a result of brand communication activities in social networks (factor 3, purchase intention. Several practical implications regarding marketing activities through social networks are drawn.

  7. Activity, exposure rate and spectrum prediction with Java programming

    International Nuclear Information System (INIS)

    Sahin, D.; Uenlue, K.

    2009-01-01

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  8. Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinfeng Wu

    2009-10-01

    Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  9. Cross-layer active predictive congestion control protocol for wireless sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng

    2009-01-01

    In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  10. Critical Transitions in Social Network Activity

    DEFF Research Database (Denmark)

    Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

    2014-01-01

    A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks....

  11. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  12. Active system area networks for data intensive computations. Final report

    Energy Technology Data Exchange (ETDEWEB)

    None

    2002-04-01

    The goal of the Active System Area Networks (ASAN) project is to develop hardware and software technologies for the implementation of active system area networks (ASANs). The use of the term ''active'' refers to the ability of the network interfaces to perform application-specific as well as system level computations in addition to their traditional role of data transfer. This project adopts the view that the network infrastructure should be an active computational entity capable of supporting certain classes of computations that would otherwise be performed on the host CPUs. The result is a unique network-wide programming model where computations are dynamically placed within the host CPUs or the NIs depending upon the quality of service demands and network/CPU resource availability. The projects seeks to demonstrate that such an approach is a better match for data intensive network-based applications and that the advent of low-cost powerful embedded processors and configurable hardware makes such an approach economically viable and desirable.

  13. Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

    Science.gov (United States)

    Ly, Cheng; Marsat, Gary

    2018-02-01

    Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.

  14. Max-Min Optimality of Service Rate Control in Closed Queueing Networks

    KAUST Repository

    Xia, Li; Shihada, Basem

    2013-01-01

    of service rates in closed Jackson networks and all the previous works only involve the first conclusion. Moreover, our result is also valid for both the state-dependent and load-dependent service rates, under both the time-average and customer

  15. Systematic network assessment of the carcinogenic activities of cadmium

    International Nuclear Information System (INIS)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao; Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun; Jia, Xudong; Ba, Qian; Wang, Hui

    2016-01-01

    Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  16. Systematic network assessment of the carcinogenic activities of cadmium

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Jia, Xudong [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Ba, Qian, E-mail: qba@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2016-11-01

    Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  17. Resource management for multimedia services in high data rate wireless networks

    CERN Document Server

    Zhang, Ruonan; Pan, Jianping

    2017-01-01

    This brief offers a valuable resource on principles of quality-of-service (QoS) provisioning and the related link-layer resource management techniques for high data-rate wireless networks. The primary emphasis is on protocol modeling and analysis. It introduces media access control (MAC) protocols, standards of wireless local area networks (WLANs), wireless personal area networks (WPANs), and wireless body area networks (WBANs), discussing their key technologies, applications, and deployment scenarios. The main analytical approaches and models for performance analysis of the fundamental resource scheduling mechanisms, including the contention-based, reservation-based, and hybrid MAC, are presented. To help readers understand and evaluate system performance, the brief contains a range of simulation results. In addition, a thorough bibliography provides an additional tool. This brief is an essential resource for engineers, researchers, students, and users of wireless networks.

  18. Input data preprocessing method for exchange rate forecasting via neural network

    Directory of Open Access Journals (Sweden)

    Antić Dragan S.

    2014-01-01

    Full Text Available The aim of this paper is to present a method for neural network input parameters selection and preprocessing. The purpose of this network is to forecast foreign exchange rates using artificial intelligence. Two data sets are formed for two different economic systems. Each system is represented by six categories with 70 economic parameters which are used in the analysis. Reduction of these parameters within each category was performed by using the principal component analysis method. Component interdependencies are established and relations between them are formed. Newly formed relations were used to create input vectors of a neural network. The multilayer feed forward neural network is formed and trained using batch training. Finally, simulation results are presented and it is concluded that input data preparation method is an effective way for preprocessing neural network data. [Projekat Ministarstva nauke Republike Srbije, br.TR 35005, br. III 43007 i br. III 44006

  19. Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems

    Directory of Open Access Journals (Sweden)

    Dionisis Margaris

    2018-04-01

    Full Text Available One of the major problems that social networks face is the continuous production of successful, user-targeted information in the form of recommendations, which are produced exploiting technology from the field of recommender systems. Recommender systems are based on information about users’ past behavior to formulate recommendations about their future actions. However, as time goes by, social network users may change preferences and likings: they may like different types of clothes, listen to different singers or even different genres of music and so on. This phenomenon has been termed as concept drift. In this paper: (1 we establish that when a social network user abstains from rating submission for a long time, it is a strong indication that concept drift has occurred and (2 we present a technique that exploits the abstention interval concept, to drop from the database ratings that do not reflect the current social network user’s interests, thus improving prediction quality.

  20. Exchange rate prediction with multilayer perceptron neural network using gold price as external factor

    Directory of Open Access Journals (Sweden)

    Mohammad Fathian

    2012-04-01

    Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.

  1. Connectivity, excitability and activity patterns in neuronal networks

    International Nuclear Information System (INIS)

    Le Feber, Joost; Stoyanova, Irina I; Chiappalone, Michela

    2014-01-01

    Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

  2. Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

    Directory of Open Access Journals (Sweden)

    W. L. C. Rutten

    2006-01-01

    Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

  3. User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

    OpenAIRE

    Davoust, Alan; Esfandiari, Babak

    2016-01-01

    An important problem with online communities in general, and online rating systems in particular, is uncooperative behavior: lack of user participation, dishonest contributions. This may be due to an incentive structure akin to a Prisoners' Dilemma (PD). We show that introducing an explicit social network to PD games fosters cooperative behavior, and use this insight to design a new aggregation technique for online rating systems. Using a dataset of ratings from Yelp, we show that our aggrega...

  4. A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

    OpenAIRE

    Christian de Peretti; Carole Siani; Mario Cerrato

    2010-01-01

    This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

  5. Handoff Rate and Coverage Analysis in Multi-tier Heterogeneous Networks

    OpenAIRE

    Sadr, Sanam; Adve, Raviraj S.

    2015-01-01

    This paper analyzes the impact of user mobility in multi-tier heterogeneous networks. We begin by obtaining the handoff rate for a mobile user in an irregular cellular network with the access point locations modeled as a homogeneous Poisson point process. The received signal-to-interference-ratio (SIR) distribution along with a chosen SIR threshold is then used to obtain the probability of coverage. To capture potential connection failures due to mobility, we assume that a fraction of handoff...

  6. Linking structure and activity in nonlinear spiking networks.

    Directory of Open Access Journals (Sweden)

    Gabriel Koch Ocker

    2017-06-01

    Full Text Available Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

  7. Linking structure and activity in nonlinear spiking networks.

    Science.gov (United States)

    Ocker, Gabriel Koch; Josić, Krešimir; Shea-Brown, Eric; Buice, Michael A

    2017-06-01

    Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

  8. Goal-congruent default network activity facilitates cognitive control.

    Science.gov (United States)

    Spreng, R Nathan; DuPre, Elizabeth; Selarka, Dhawal; Garcia, Juliana; Gojkovic, Stefan; Mildner, Judith; Luh, Wen-Ming; Turner, Gary R

    2014-10-15

    Substantial neuroimaging evidence suggests that spontaneous engagement of the default network impairs performance on tasks requiring executive control. We investigated whether this impairment depends on the congruence between executive control demands and internal mentation. We hypothesized that activation of the default network might enhance performance on an executive control task if control processes engage long-term memory representations that are supported by the default network. Using fMRI, we scanned 36 healthy young adult humans on a novel two-back task requiring working memory for famous and anonymous faces. In this task, participants (1) matched anonymous faces interleaved with anonymous face, (2) matched anonymous faces interleaved with a famous face, or (3) matched a famous faces interleaved with an anonymous face. As predicted, we observed a facilitation effect when matching famous faces, compared with anonymous faces. We also observed greater activation of the default network during these famous face-matching trials. The results suggest that activation of the default network can contribute to task performance during an externally directed executive control task. Our findings provide evidence that successful activation of the default network in a contextually relevant manner facilitates goal-directed cognition. Copyright © 2014 the authors 0270-6474/14/3414108-07$15.00/0.

  9. Vertically oriented graphene bridging active-layer/current-collector interface for ultrahigh rate supercapacitors.

    Science.gov (United States)

    Bo, Zheng; Zhu, Weiguang; Ma, Wei; Wen, Zhenhai; Shuai, Xiaorui; Chen, Junhong; Yan, Jianhua; Wang, Zhihua; Cen, Kefa; Feng, Xinliang

    2013-10-25

    Dense networks of graphene nanosheets standing vertically on a current collector can work as numerous electrically conductive bridges to facilitate charge transport and mitigate the constriction/spreading resistance at the interface between the active material and the current collector. The vertically oriented graphene-bridged supercapacitors present excellent rate and power capabilities. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

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

    2017-09-01

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

  11. Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

    Science.gov (United States)

    Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.

    2018-03-01

    The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression.

  12. The efficacy of centralized flow rate control in 802.11-based wireless mesh networks

    KAUST Repository

    Jamshaid, K.

    2013-06-13

    Commodity WiFi-based wireless mesh networks (WMNs) can be used to provide last mile Internet access. These networks exhibit extreme unfairness with backlogged traffic sources. Current solutions propose distributed source-rate control algorithms requiring link-layer or transport-layer changes on all mesh nodes. This is often infeasible in large practical deployments. In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We wish to evaluate the feasibility of establishing similar centralized control via gateways in WMNs. In this paper, we focus on the efficacy of this control rather than the specifics of the controller design mechanism. We answer the question: Given sources that react predictably to congestion notification, can we enforce a desired rate allocation through a single centralized controller? The answer is not obvious because flows experience varying contention levels, and transmissions are scheduled by a node using imperfect local knowledge. We find that common router-assisted flow control schemes used in wired networks fail in WMNs because they assume that (1) links are independent, and (2) router queue buildups are sufficient for detecting congestion. We show that non-work-conserving, rate-based centralized scheduling can effectively enforce rate allocation. It can achieve results comparable to source rate limiting, without requiring any modifications to mesh routers or client devices. 2013 Jamshaid et al.; licensee Springer.

  13. Tansig activation function (of MLP network) for cardiac abnormality detection

    Science.gov (United States)

    Adnan, Ja'afar; Daud, Nik Ghazali Nik; Ishak, Mohd Taufiq; Rizman, Zairi Ismael; Rahman, Muhammad Izzuddin Abd

    2018-02-01

    Heart abnormality often occurs regardless of gender, age and races. This problem sometimes does not show any symptoms and it can cause a sudden death to the patient. In general, heart abnormality is the irregular electrical activity of the heart. This paper attempts to develop a program that can detect heart abnormality activity through implementation of Multilayer Perceptron (MLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP network by using several training algorithms with Tansig activation function.

  14. Ethanol affects network activity in cultured rat hippocampus: mediation by potassium channels.

    Directory of Open Access Journals (Sweden)

    Eduard Korkotian

    Full Text Available The effects of ethanol on neuronal network activity were studied in dissociated cultures of rat hippocampus. Exposure to low (0.25-0.5% ethanol concentrations caused an increase in synchronized network spikes, and a decrease in the duration of individual spikes. Ethanol also caused an increase in rate of miniature spontaneous excitatory postsynaptic currents. Higher concentrations of ethanol eliminated network spikes. These effects were reversible upon wash. The effects of the high, but not the low ethanol were blocked by the GABA antagonist bicuculline. The enhancing action of low ethanol was blocked by apamin, an SK potassium channel antagonist, and mimicked by 1-EBIO, an SK channel opener. It is proposed that in cultured hippocampal networks low concentration of ethanol is associated with SK channel activity, rather than the GABAergic receptor.

  15. Study of active crossover network | Tyona | Nigerian Journal of Physics

    African Journals Online (AJOL)

    An active crossover network system has been realized using an active component LF356 with a JFET input. The net work has two drives, the low frequency drive (Bass) and the high frequency drive (Treble). It employs high level crossover technique. The circuit performance was adequately verified and the frequency ...

  16. A prediction method for the wax deposition rate based on a radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Ying Xie

    2017-06-01

    Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

  17. Active Engine Mounting Control Algorithm Using Neural Network

    Directory of Open Access Journals (Sweden)

    Fadly Jashi Darsivan

    2009-01-01

    Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.

  18. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  19. A complex-valued firing-rate model that approximates the dynamics of spiking networks.

    Directory of Open Access Journals (Sweden)

    Evan S Schaffer

    2013-10-01

    Full Text Available Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons.

  20. A complex-valued firing-rate model that approximates the dynamics of spiking networks.

    Science.gov (United States)

    Schaffer, Evan S; Ostojic, Srdjan; Abbott, L F

    2013-10-01

    Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons.

  1. AMETH laboratories network activities; Activites du reseau de Laboratoires AMETH

    Energy Technology Data Exchange (ETDEWEB)

    Marimbordes, T.; Ould El Moctar, A.; Peerhossaini, H. [Nantes Univ., Ecole Polytechnique, UMR CNRS 6607, Lab. de Thermocinetique, 44 (France)] [and others

    2000-07-01

    The AMETH laboratories are a network for the improvement of thermal exchanges for one or two phases. This meeting of the 15 november 2000, dealt with the activities of this network of laboratories in the following topics: thermal-hydrodynamic instabilities and control of the limit layer; transfers with change in the liquid-vapor phase; transfers with change in the solid-liquid phase. Ten papers were presented. (A.L.B.)

  2. Green corona, geomagnetic activity and radar meteor rates

    International Nuclear Information System (INIS)

    Prikryl, P.

    1979-01-01

    The short-term dependence of radar meteor rates on geomagnetic activity and/or central meridian passage (CMP) of bright or faint green corona regions is studied. A superimposed-epoch analysis was applied to radar meteor observations from the Ottawa patrol radar (Springhill, Ont.) and Ksub(p)-indices of geomagnetic activity for the period 1963 to 1967. During the minimum of solar activity (1963 to 1965) the CMP of bright coronal regions was followed by the maximum in the daily rates of persistent meteor echoes (>=4s), and the minimum in the daily sums of Ksub(p)-indices whereas the minimum or the maximum, respectively, occurs after the CMP of faint coronal regions. The time delay between the CMP of coronal structures and the corresponding maxima or minima is found to be 3 to 4 days. However, for the period immediately after the minimum of solar activity (1966 to 1967) the above correlation with the green corona is void both for the geomagnetic activity and radar meteor rates. An inverse correlation was found between the radar meteor rates and the geomagnetic activity irrespective of the solar activity. The observed effect can be ascribed to the solar-wind-induced ''geomagnetic'' heating of the upper atmosphere and to the subsequent change in the density gradient in the meteor zone. (author)

  3. Statistical inference, the bootstrap, and neural-network modeling with application to foreign exchange rates.

    Science.gov (United States)

    White, H; Racine, J

    2001-01-01

    We propose tests for individual and joint irrelevance of network inputs. Such tests can be used to determine whether an input or group of inputs "belong" in a particular model, thus permitting valid statistical inference based on estimated feedforward neural-network models. The approaches employ well-known statistical resampling techniques. We conduct a small Monte Carlo experiment showing that our tests have reasonable level and power behavior, and we apply our methods to examine whether there are predictable regularities in foreign exchange rates. We find that exchange rates do appear to contain information that is exploitable for enhanced point prediction, but the nature of the predictive relations evolves through time.

  4. Impact of visual repetition rate on intrinsic properties of low frequency fluctuations in the visual network.

    Directory of Open Access Journals (Sweden)

    Yi-Chia Li

    Full Text Available BACKGROUND: Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz fluctuations (LFFs during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1 interactions between visual stimuli and resting-state; (2 impact of repetition rate of visual stimuli. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses, fALFF (fractional Amplitude of Low Frequency Fluctuation, and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated. CONCLUSIONS/SIGNIFICANCE: To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration and disordered behaviors (early blind, but also exogenous sensory stimuli (visual stimuli with various repetition rates. It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains.

  5. Dynamic neural networking as a basis for plasticity in the control of heart rate.

    Science.gov (United States)

    Kember, G; Armour, J A; Zamir, M

    2013-01-21

    A model is proposed in which the relationship between individual neurons within a neural network is dynamically changing to the effect of providing a measure of "plasticity" in the control of heart rate. The neural network on which the model is based consists of three populations of neurons residing in the central nervous system, the intrathoracic extracardiac nervous system, and the intrinsic cardiac nervous system. This hierarchy of neural centers is used to challenge the classical view that the control of heart rate, a key clinical index, resides entirely in central neuronal command (spinal cord, medulla oblongata, and higher centers). Our results indicate that dynamic networking allows for the possibility of an interplay among the three populations of neurons to the effect of altering the order of control of heart rate among them. This interplay among the three levels of control allows for different neural pathways for the control of heart rate to emerge under different blood flow demands or disease conditions and, as such, it has significant clinical implications because current understanding and treatment of heart rate anomalies are based largely on a single level of control and on neurons acting in unison as a single entity rather than individually within a (plastically) interconnected network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Recognizing Multi-user Activities using Body Sensor Networks

    DEFF Research Database (Denmark)

    Gu, Tao; Wang, Liang; Chen, Hanhua

    2011-01-01

    The advances of wireless networking and sensor technology open up an interesting opportunity to infer human activities in a smart home environment. Existing work in this paradigm focuses mainly on recognizing activities of a single user. In this work, we address the fundamental problem...... activity classes of data—for building activity models and design a scalable, noise-resistant, Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single- and multi-user activities. We develop a multi-modal, wireless body sensor network for collecting real-world traces in a smart...... home environment, and conduct comprehensive empirical studies to evaluate our system. Results show that epMAR outperforms existing schemes in terms of accuracy, scalability and robustness....

  7. Application of neural networks to validation of feedwater flow rate in a nuclear power plant

    International Nuclear Information System (INIS)

    Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.

    1993-01-01

    Feedwater flow rate measurement in nuclear power plants requires periodic calibration. This is due to the fact that the venturi surface condition of the feedwater flow rate sensor changes because of a chemical reaction between the surface coating material and the feedwater. Fouling of the venturi surface, due to this chemical reaction and the deposits of foreign materials, has been observed shortly after a clean venturi is put in operation. A fouled venturi causes an incorrect measurement of feedwater flow rate, which in turn results in an inaccurate calculation of the generated power. This paper presents two methods for verifying incipient and continuing fouling of the venturi of the feedwater flow rate sensors. Both methods are based on the use of a set of dissimilar process variables dynamically related to the feedwater flow rate variable. The first method uses a neural network to generate estimates of the feedwater flow rate readings. Agreement, within a given tolerance, of the feedwater flow rate instrument reading, and the corresponding neural network output establishes that the feedwater flow rate instrument is operating properly. The second method is similar to the first method except that the neural network predicts the core power which is calculated from measurements on the primary loop, rather than the feedwater flow rates. This core power is referred to the primary core power in this paper. A comparison of the power calculated from the feedwater flow measurements in the secondary loop, with the calculated and neural network predicted primary core power provides information from which it can be determined whether fouling is beginning to occur. The two methods were tested using data from the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant

  8. Noise in attractor networks in the brain produced by graded firing rate representations.

    Directory of Open Access Journals (Sweden)

    Tristan J Webb

    Full Text Available Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry.

  9. Social Network resources and self-rated health in a deprived Danish neighborhood

    DEFF Research Database (Denmark)

    Tanggaard Andersen, Pernille; Holst Algren, Maria; Fromsejer Heiberg, Regina

    2017-01-01

    Research has demonstrated that living in a deprived neighborhood contributes to the occurrence and development of poor health. Furthermore evidence shows that social networks are fundamental resources in preventing poor mental health. Neighborhood relationships and networks are vital for sustaining...... and improving quality of life. However, to determine potentials for public health action, the health impact of various types of network resources need to be explored and the association between socioeconomic position and self-rated health needs to be analysed to determine whether it is partially explained...... by social network resources. This is the main aim of this article. Cross-sectional data from one deprived neighborhood located in Denmark were collected in 2008 and 2013 using a postal health survey. The target group was defined as adults older than 16 years. In 2008, 408 residents participated...

  10. Managing CSCL Activity through networking models

    Directory of Open Access Journals (Sweden)

    Luis Casillas

    2014-04-01

    Full Text Available This study aims at managing activity carried out in Computer-Supported Collaborative Learning (CSCL environments. We apply an approach that gathers and manages the knowledge underlying huge data structures, resulting from collaborative interaction among participants and stored as activity logs. Our method comprises a variety of important issues and aspects, such as: deep understanding of collaboration among participants in workgroups, definition of an ontology for providing meaning to isolated data manifestations, discovering of knowledge structures built in huge amounts of data stored in log files, and development of high-semantic indicators to describe diverse primitive collaborative acts, and binding these indicators to formal descriptions defined in the collaboration ontology; besides our method includes gathering collaboration indicators from web forums using natural language processing (NLP techniques.

  11. Distinguishing the rates of gene activation from phenotypic variations

    OpenAIRE

    Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

    2015-01-01

    Background Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which r...

  12. Heart rate and activity profile for young female soccer players

    OpenAIRE

    Barbero Álvarez, José Carlos; Gómez López, Maite; Barbero Álvarez, Verónica; Granda Vera, Juan; Castagna, Carlo

    2008-01-01

    The physical and physiological demands of high-level male soccer have been studied extensively, while few studies have investigated the demands placed on females during match-play, however, there is no information available about the heart rate and activity profile of young female soccer players during match play. Therefore, the aim of this study was to examine cardiovascular (heart-rates HR) and physical demands of young female soccer players during a match. Players were observed during a fr...

  13. Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

    Directory of Open Access Journals (Sweden)

    Chih-Hong Kao

    2011-01-01

    Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

  14. BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

    Science.gov (United States)

    Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

    2015-06-12

    During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

  15. ON ONE OF THE APPROACHES TO ENHANCING THE MOTIVATION OF STUDENTS TO EDUCATIONAL AND EXTRACURRICULAR ACTIVITIES THROUGH THE RATING SYSTEM

    OpenAIRE

    Soghoyan S. S.; Dyachenko R. A.; Belchenko I. V.

    2016-01-01

    The problems of increasing the motivation of students of organizations of secondary vocational education and higher education to educational and training activities is due to the use of score-rating approach to recording achievements. The article examines factors that have a negative impact on training and outside training activities, such as TV entertainment, online games, social networks. We consider the activities that have a positive impact on the educational and training activities outsi...

  16. Too-connected versus too-big-to-fail: banks’ network centrality and overnight interest rates.

    OpenAIRE

    Gabrieli, S.

    2012-01-01

    What influences banks’ borrowing costs in the unsecured money market? The objective of this paper is to test whether measures of centrality, quantifying network effects due to interactions among banks in the market, can help explain heterogeneous patterns in the interest rates paid to borrow unsecured funds once bank size and other bank and market factors that affect the overnight segment are controlled for. Preliminary evidence shows that large banks borrow on average at better rates compare...

  17. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

  18. On attracting sets in artificial networks: cross activation

    Directory of Open Access Journals (Sweden)

    Sadyrbaev Felix

    2018-01-01

    Full Text Available Mathematical models of artificial networks can be formulated in terms of dynamical systems describing the behaviour of a network over time. The interrelation between nodes (elements of a network is encoded in the regulatory matrix. We consider a system of ordinary differential equations that describes in particular also genomic regulatory networks (GRN and contains a sigmoidal function. The results are presented on attractors of such systems for a particular case of cross activation. The regulatory matrix is then of particular form consisting of unit entries everywhere except the main diagonal. We show that such a system can have not more than three critical points. At least n–1 eigenvalues corresponding to any of the critical points are negative. An example for a particular choice of sigmoidal function is considered.

  19. Choosing optimum noise figure and data rate in wireless sensor network radio transceivers

    NARCIS (Netherlands)

    Dutta, R.; van der Zee, Ronan A.R.; Bentum, Marinus Jan; Kokkeler, Andre B.J.

    2011-01-01

    To reduce the energy consumption in wireless sensor network transceivers, we propose an approach which combines two tradeoffs. The first tradeoff is between the receiver sensitivity and transmitter output power. The second one is the duty cycle and data rate of the transceiver. The combined approach

  20. 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

  1. The association between social networks and self-rated risk of HIV ...

    African Journals Online (AJOL)

    This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15–24 years in 5 secondary schools in Moshi, Tanzania.

  2. Packetized Predictive Control for Rate-Limited Networks via Sparse Representation

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan

    2012-01-01

    controller and the plant input. To achieve robustness with respect to dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. In our formulation, we design sparse packets for rate-limited networks, by adopting an an ℓ0 optimization...

  3. Resource allocation via sum-rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina; Alouini, Mohamed-Slim; Dawy, Zaher

    2012-01-01

    In this paper, we consider maximizing the sum rate in the uplink of a multi-cell orthogonal frequency-division multiple access network. The problem has a non-convex combinatorial structure and is known to be NP-hard. Because of the inherent

  4. Structural and functional social network attributes moderate the association of self-rated health with mental health in midlife and older adults.

    Science.gov (United States)

    Windsor, Tim D; Rioseco, Pilar; Fiori, Katherine L; Curtis, Rachel G; Booth, Heather

    2016-01-01

    Social relationships are multifaceted, and different social network components can operate via different processes to influence well-being. This study examined associations of social network structure and relationship quality (positive and negative social exchanges) with mental health in midlife and older adults. The focus was on both direct associations of network structure and relationship quality with mental health, and whether these social network attributes moderated the association of self-rated health (SRH) with mental health. Analyses were based on survey data provided by 2001 (Mean age = 65, SD = 8.07) midlife and older adults. We used Latent Class Analysis (LCA) to classify participants into network types based on network structure (partner status, network size, contact frequency, and activity engagement), and used continuous measures of positive and negative social exchanges to operationalize relationship quality. Regression analysis was used to test moderation. LCA revealed network types generally consistent with those reported in previous studies. Participants in more diverse networks reported better mental health than those categorized into a restricted network type after adjustment for age, sex, education, and employment status. Analysis of moderation indicated that those with poorer SRH were less likely to report poorer mental health if they were classified into more diverse networks. A similar moderation effect was also evident for positive exchanges. The findings suggest that both quantity and quality of social relationships can play a role in buffering against the negative implications of physical health decline for mental health.

  5. Depression and unemployment incidence rate evolution in Portugal, 1995-2013: General Practitioner Sentinel Network data.

    Science.gov (United States)

    Rodrigues, Ana Paula; Sousa-Uva, Mafalda; Fonseca, Rita; Marques, Sara; Pina, Nuno; Matias-Dias, Carlos

    2017-11-17

    Quantify, for both genders, the correlation between the depression incidence rate and the unemployment rate in Portugal between 1995 and 2013. An ecological study was developed to correlate the evolution of the depression incidence rates estimated by the General Practitioner Sentinel Network and the annual unemployment rates provided by the National Statistical Institute in official publications. There was a positive correlation between the depression incidence rate and the unemployment rate in Portugal, which was significant only for males (R2 = 0.83, p = 0.04). For this gender, an increase of 37 new cases of depression per 100,000 inhabitants was estimated for each 1% increase in the unemployment rate between 1995 and 2013. Although the study design does not allow the establishment of a causal association between unemployment and depression, the results suggest that the evolution of unemployment in Portugal may have had a significant impact on the level of mental health of the Portuguese, especially among men.

  6. Impact of dynamic rate coding aspects of mobile phone networks on forensic voice comparison.

    Science.gov (United States)

    Alzqhoul, Esam A S; Nair, Balamurali B T; Guillemin, Bernard J

    2015-09-01

    Previous studies have shown that landline and mobile phone networks are different in their ways of handling the speech signal, and therefore in their impact on it. But the same is also true of the different networks within the mobile phone arena. There are two major mobile phone technologies currently in use today, namely the global system for mobile communications (GSM) and code division multiple access (CDMA) and these are fundamentally different in their design. For example, the quality of the coded speech in the GSM network is a function of channel quality, whereas in the CDMA network it is determined by channel capacity (i.e., the number of users sharing a cell site). This paper examines the impact on the speech signal of a key feature of these networks, namely dynamic rate coding, and its subsequent impact on the task of likelihood-ratio-based forensic voice comparison (FVC). Surprisingly, both FVC accuracy and precision are found to be better for both GSM- and CDMA-coded speech than for uncoded. Intuitively one expects FVC accuracy to increase with increasing coded speech quality. This trend is shown to occur for the CDMA network, but, surprisingly, not for the GSM network. Further, in respect to comparisons between these two networks, FVC accuracy for CDMA-coded speech is shown to be slightly better than for GSM-coded speech, particularly when the coded-speech quality is high, but in terms of FVC precision the two networks are shown to be very similar. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Fine-Grained Rate Shaping for Video Streaming over Wireless Networks

    Directory of Open Access Journals (Sweden)

    Chen Tsuhan

    2004-01-01

    Full Text Available Video streaming over wireless networks faces challenges of time-varying packet loss rate and fluctuating bandwidth. In this paper, we focus on streaming precoded video that is both source and channel coded. Dynamic rate shaping has been proposed to “shape” the precompressed video to adapt to the fluctuating bandwidth. In our earlier work, rate shaping was extended to shape the channel coded precompressed video, and to take into account the time-varying packet loss rate as well as the fluctuating bandwidth of the wireless networks. However, prior work on rate shaping can only adjust the rate oarsely. In this paper, we propose “fine-grained rate shaping (FGRS” to allow for bandwidth adaptation over a wide range of bandwidth and packet loss rate in fine granularities. The video is precoded with fine granularity scalability (FGS followed by channel coding. Utilizing the fine granularity property of FGS and channel coding, FGRS selectively drops part of the precoded video and still yields decodable bit-stream at the decoder. Moreover, FGRS optimizes video streaming rather than achieves heuristic objectives as conventional methods. A two-stage rate-distortion (RD optimization algorithm is proposed for FGRS. Promising results of FGRS are shown.

  8. Cooperative wireless network control based health and activity monitoring system.

    Science.gov (United States)

    Prakash, R; Ganesh, A Balaji; Girish, Siva V

    2016-10-01

    A real-time cooperative communication based wireless network is presented for monitoring health and activity of an end-user in their environment. The cooperative communication offers better energy consumption and also an opportunity to aware the current location of a user non-intrusively. The link between mobile sensor node and relay node is dynamically established by using Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) based on adaptive relay selection scheme. The study proposes a Linear Acceleration based Transmission Power Decision Control (LA-TPDC) algorithm to further enhance the energy efficiency of cooperative communication. Further, the occurrences of false alarms are carefully prevented by introducing three stages of sequential warning system. The real-time experiments are carried-out by using the nodes, namely mobile sensor node, relay nodes and a destination node which are indigenously developed by using a CC430 microcontroller integrated with an in-built transceiver at 868 MHz. The wireless node performance characteristics, such as energy consumption, Signal-Noise ratio (SNR), Bit Error Rate (BER), Packet Delivery Ratio (PDR) and transmission offset are evaluated for all the participated nodes. The experimental results observed that the proposed linear acceleration based transmission power decision control algorithm almost doubles the battery life time than energy efficient conventional cooperative communication.

  9. 76 FR 79169 - Power Network New Mexico, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes...

    Science.gov (United States)

    2011-12-21

    ... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ER12-605-000] Power Network New Mexico, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for... Power Network New Mexico, LLC's application for market-based rate authority, with an accompanying rate...

  10. Information transmission and signal permutation in active flow networks

    Science.gov (United States)

    Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn

    2018-03-01

    Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

  11. Facility optimization to improve activation rate distributions during IVNAA

    International Nuclear Information System (INIS)

    Ebrahimi Khankook, Atiyeh; Rafat Motavalli, Laleh; Miri Hakimabad, Hashem

    2013-01-01

    Currently, determination of body composition is the most useful method for distinguishing between certain diseases. The prompt-gamma in vivo neutron activation analysis (IVNAA) facility for non-destructive elemental analysis of the human body is the gold standard method for this type of analysis. In order to obtain accurate measurements using the IVNAA system, the activation probability in the body must be uniform. This can be difficult to achieve, as body shape and body composition affect the rate of activation. The aim of this study was to determine the optimum pre-moderator, in terms of material for attaining uniform activation probability with a CV value of about 10% and changing the collimator role to increase activation rate within the body. Such uniformity was obtained with a high thickness of paraffin pre-moderator, however, because of increasing secondary photon flux received by the detectors it was not an appropriate choice. Our final calculations indicated that using two paraffin slabs with a thickness of 3 cm as a pre-moderator, in the presence of 2 cm Bi on the collimator, achieves a satisfactory distribution of activation rate in the body. (author)

  12. Assessment of high to low frequency variations of isoprene emission rates using a neural network approach

    Science.gov (United States)

    Boissard, C.; Chervier, F.; Dutot, A. L.

    2007-08-01

    Using a statistical approach based on artificial neural networks, an emission algorithm (ISO_LF) accounting for high (instantaneous) to low (seasonal) frequency variations was developed for isoprene. ISO_LF was optimised using an isoprene emission data base (ISO-DB) specifically designed for this work. ISO-DB consists of 1321 emission rates collected in the literature, together with 34 environmental variables, measured or assessed using NCDC (National Climatic Data Center) or NCEP (National Centers for Environmental Predictions) meteorological databases. ISO-DB covers a large variety of emitters (25 species) and environmental conditions (10° S to 60° N). When only instantaneous environmental regressors (air temperature and photosynthetic active radiation, PAR) were used, a maximum of 60% of the overall isoprene variability was assessed and the highest emissions were underestimated. Considering a total of 9 high (instantaneous) to low (up to 3 weeks) frequency regressors, ISO_LF accounts for up to 91% of the isoprene emission variability, whatever the emission range, species or climate. Diurnal and seasonal variations are correctly reproduced for textit{Ulex europaeus} with a maximum factor of discrepancy of 4. ISO-LF was found to be mainly sensitive to air temperature cumulated over 3 weeks T21 and to instantaneous light L0 and air temperature T0 variations. T21, T0 and L0 only accounts for 76% of the overall variability. The use of ISO-LF for non stored monoterpene emissions was shown to give poor results.

  13. Collaborative Event-Driven Coverage and Rate Allocation for Event Miss-Ratio Assurances in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ozgur Sanli H

    2010-01-01

    Full Text Available Wireless sensor networks are often required to provide event miss-ratio assurance for a given event type. To meet such assurances along with minimum energy consumption, this paper shows how a node's activation and rate assignment is dependent on its distance to event sources, and proposes a practical coverage and rate allocation (CORA protocol to exploit this dependency in realistic environments. Both uniform event distribution and nonuniform event distribution are considered and the notion of ideal correlation distance around a clusterhead is introduced for on-duty node selection. In correlation distance guided CORA, rate assignment assists coverage scheduling by determining which nodes should be activated for minimizing data redundancy in transmission. Coverage scheduling assists rate assignment by controlling the amount of overlap among sensing regions of neighboring nodes, thereby providing sufficient data correlation for rate assignment. Extensive simulation results show that CORA meets the required event miss-ratios in realistic environments. CORA's joint coverage scheduling and rate allocation reduce the total energy expenditure by 85%, average battery energy consumption by 25%, and the overhead of source coding up to 90% as compared to existing rate allocation techniques.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-04-15

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

  16. Max-Min Optimality of Service Rate Control in Closed Queueing Networks

    KAUST Repository

    Xia, Li

    2013-04-01

    In this technical note, we discuss the optimality properties of service rate control in closed Jackson networks. We prove that when the cost function is linear to a particular service rate, the system performance is monotonic w.r.t. (with respect to) that service rate and the optimal value of that service rate can be either maximum or minimum (we call it Max-Min optimality); When the second-order derivative of the cost function w.r.t. a particular service rate is always positive (negative), which makes the cost function strictly convex (concave), the optimal value of such service rate for the performance maximization (minimization) problem can be either maximum or minimum. To the best of our knowledge, this is the most general result for the optimality of service rates in closed Jackson networks and all the previous works only involve the first conclusion. Moreover, our result is also valid for both the state-dependent and load-dependent service rates, under both the time-average and customer-average performance criteria.

  17. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Directory of Open Access Journals (Sweden)

    Melanie Weber

    2017-11-01

    Full Text Available Neurodegenerative diseases and traumatic brain injuries (TBI are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS, which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i to extend Hopfield's model for associative memory to account for the effects of FAS, (ii to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive

  18. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Science.gov (United States)

    Weber, Melanie; Maia, Pedro D.; Kutz, J. Nathan

    2017-01-01

    Neurodegenerative diseases and traumatic brain injuries (TBI) are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS), which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i) to extend Hopfield's model for associative memory to account for the effects of FAS, (ii) to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii) to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive deficits. PMID

  19. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  20. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  1. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  2. Effect of water activity on rates of serpentinization of olivine.

    Science.gov (United States)

    Lamadrid, Hector M; Rimstidt, J Donald; Schwarzenbach, Esther M; Klein, Frieder; Ulrich, Sarah; Dolocan, Andrei; Bodnar, Robert J

    2017-07-14

    The hydrothermal alteration of mantle rocks (referred to as serpentinization) occurs in submarine environments extending from mid-ocean ridges to subduction zones. Serpentinization affects the physical and chemical properties of oceanic lithosphere, represents one of the major mechanisms driving mass exchange between the mantle and the Earth's surface, and is central to current origin of life hypotheses as well as the search for microbial life on the icy moons of Jupiter and Saturn. In spite of increasing interest in the serpentinization process by researchers in diverse fields, the rates of serpentinization and the controlling factors are poorly understood. Here we use a novel in situ experimental method involving olivine micro-reactors and show that the rate of serpentinization is strongly controlled by the salinity (water activity) of the reacting fluid and demonstrate that the rate of serpentinization of olivine slows down as salinity increases and H 2 O activity decreases.

  3. Effect of water activity on rates of serpentinization of olivine

    Science.gov (United States)

    Lamadrid, Hector M.; Rimstidt, J. Donald; Schwarzenbach, Esther M.; Klein, Frieder; Ulrich, Sarah; Dolocan, Andrei; Bodnar, Robert J.

    2017-07-01

    The hydrothermal alteration of mantle rocks (referred to as serpentinization) occurs in submarine environments extending from mid-ocean ridges to subduction zones. Serpentinization affects the physical and chemical properties of oceanic lithosphere, represents one of the major mechanisms driving mass exchange between the mantle and the Earth's surface, and is central to current origin of life hypotheses as well as the search for microbial life on the icy moons of Jupiter and Saturn. In spite of increasing interest in the serpentinization process by researchers in diverse fields, the rates of serpentinization and the controlling factors are poorly understood. Here we use a novel in situ experimental method involving olivine micro-reactors and show that the rate of serpentinization is strongly controlled by the salinity (water activity) of the reacting fluid and demonstrate that the rate of serpentinization of olivine slows down as salinity increases and H2O activity decreases.

  4. Constraining slip rates and spacings for active normal faults

    Science.gov (United States)

    Cowie, Patience A.; Roberts, Gerald P.

    2001-12-01

    Numerous observations of extensional provinces indicate that neighbouring faults commonly slip at different rates and, moreover, may be active over different time intervals. These published observations include variations in slip rate measured along-strike of a fault array or fault zone, as well as significant across-strike differences in the timing and rates of movement on faults that have a similar orientation with respect to the regional stress field. Here we review published examples from the western USA, the North Sea, and central Greece, and present new data from the Italian Apennines that support the idea that such variations are systematic and thus to some extent predictable. The basis for the prediction is that: (1) the way in which a fault grows is fundamentally controlled by the ratio of maximum displacement to length, and (2) the regional strain rate must remain approximately constant through time. We show how data on fault lengths and displacements can be used to model the observed patterns of long-term slip rate where measured values are sparse. Specifically, we estimate the magnitude of spatial variation in slip rate along-strike and relate it to the across-strike spacing between active faults.

  5. Spontaneous brain network activity: Analysis of its temporal complexity

    Directory of Open Access Journals (Sweden)

    Mangor Pedersen

    2017-06-01

    Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

  6. Neural networks based identification and compensation of rate-dependent hysteresis in piezoelectric actuators

    International Nuclear Information System (INIS)

    Zhang, Xinliang; Tan, Yonghong; Su, Miyong; Xie, Yangqiu

    2010-01-01

    This paper presents a method of the identification for the rate-dependent hysteresis in the piezoelectric actuator (PEA) by use of neural networks. In this method, a special hysteretic operator is constructed from the Prandtl-Ishlinskii (PI) model to extract the changing tendency of the static hysteresis. Then, an expanded input space is constructed by introducing the proposed hysteretic operator to transform the multi-valued mapping of the hysteresis into a one-to-one mapping. Thus, a feedforward neural network is applied to the approximation of the rate-independent hysteresis on the constructed expanded input space. Moreover, in order to describe the rate-dependent performance of the hysteresis, a special hybrid model, which is constructed by a linear auto-regressive exogenous input (ARX) sub-model preceded with the previously obtained neural network based rate-independent hysteresis sub-model, is proposed. For the compensation of the effect of the hysteresis in PEA, the PID feedback controller with a feedforward hysteresis compensator is developed for the tracking control of the PEA. Thus, a corresponding inverse model based on the proposed modeling method is developed for the feedforward hysteresis compensator. Finally, both simulations and experimental results on piezoelectric actuator are presented to verify the effectiveness of the proposed approach for the rate-dependent hysteresis.

  7. Automatic optimisation of gamma dose rate sensor networks: The DETECT Optimisation Tool

    DEFF Research Database (Denmark)

    Helle, K.B.; Müller, T.O.; Astrup, Poul

    2014-01-01

    of the EU FP 7 project DETECT. It evaluates the gamma dose rates that a proposed set of sensors might measure in an emergency and uses this information to optimise the sensor locations. The gamma dose rates are taken from a comprehensive library of simulations of atmospheric radioactive plumes from 64......Fast delivery of comprehensive information on the radiological situation is essential for decision-making in nuclear emergencies. Most national radiological agencies in Europe employ gamma dose rate sensor networks to monitor radioactive pollution of the atmosphere. Sensor locations were often...... source locations. These simulations cover the whole European Union, so the DOT allows evaluation and optimisation of sensor networks for all EU countries, as well as evaluation of fencing sensors around possible sources. Users can choose from seven cost functions to evaluate the capability of a given...

  8. A Reaction-Diffusion-Based Coding Rate Control Mechanism for Camera Sensor Networks

    Directory of Open Access Journals (Sweden)

    Naoki Wakamiya

    2010-08-01

    Full Text Available A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

  9. A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

    Science.gov (United States)

    Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

    2010-01-01

    A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

  10. Topological quantum computing with a very noisy network and local error rates approaching one percent.

    Science.gov (United States)

    Nickerson, Naomi H; Li, Ying; Benjamin, Simon C

    2013-01-01

    A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.

  11. Kainate-induced network activity in the anterior cingulate cortex.

    Science.gov (United States)

    Shinozaki, R; Hojo, Y; Mukai, H; Hashizume, M; Murakoshi, T

    2016-06-14

    Anterior cingulate cortex (ACC) plays a pivotal role in higher order processing of cognition, attention and emotion. The network oscillation is considered an essential means for integration of these CNS functions. The oscillation power and coherence among related areas are often dis-regulated in several psychiatric and pathological conditions with a hemispheric asymmetric manner. Here we describe the network-based activity of field potentials recorded from the superficial layer of the mouse ACC in vitro using submerged type recordings. A short activation by kainic acid administration to the preparation induced populational activities ranging over several frequency bands including theta (3-8Hz), alpha (8-12Hz), beta (13-30Hz), low gamma (30-50Hz) and high gamma (50-80Hz). These responses were repeatable and totally abolished by tetrodotoxin, and greatly diminished by inhibitors of ionotropic and metabotropic glutamate receptors, GABAA receptor or gap-junctions. These observations suggest that the kainate-induced network activity can be a useful model of the network oscillation in the ACC circuit. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  12. Provable network activity for protecting users against false accusation

    NARCIS (Netherlands)

    Papadopoulos, Panagiotis; Athanasopoulos, Ilias; Kosta, Eleni; Siganos, George; Keromytis, Angelos D.; Markatos, Evangelos P.

    2016-01-01

    With the proliferation of the World Wide Web, data traces that correspond to users’ network activity can be collected by several Internet actors, including (i) web sites, (ii) smartphone apps, and even (iii) Internet Service Providers. Given that the collection and storage of these data are beyond

  13. Nash Equilibrium of an Energy Saving Strategy with Dual Rate Transmission in Wireless Regional Area Network

    Directory of Open Access Journals (Sweden)

    Zhanqiang Huo

    2017-01-01

    Full Text Available Wireless regional area network (WRAN adopts centralized network architecture and is currently one of the most typical cognitive radio networks. In order to reduce the energy consumption of the communication networks with the constraint of spectrum resource utilization, a working sleep mechanism is introduced into the base station (BS, and a novel energy saving strategy with dual rate transmission is proposed. Combining the multiple-vacation queue and priority queue, using the quasi-birth-death process and the matrix-geometric solution method, we assess the average latency and the forced termination probability of secondary user packets, as well as the energy saving ratio and the channel utilization of system. Based on the revenue-expenditure structure, a profit function is built, and then the Nash equilibrium behavior and the socially optimal behavior are investigated. With the help of the particle swarm optimization, an intelligent optimization algorithm to search the socially optimal arrival rate of secondary user packets is presented. In order to unify the arrival rates of secondary user packets with Nash equilibrium and social optimization, a reasonable pricing policy is formulated. In addition, system experiments are carried out to verify the effectiveness of the energy saving strategy and the rationality of the pricing policy.

  14. Photonic network R and D activities in Japan

    Science.gov (United States)

    Kitayama, Ken-ichi; Miki, Tetsuya; Morioka, Toshio; Tsushima, Hideaki; Koga, Masafumi; Mori, Kazuyuki; Araki, Soichiro; Sato, Ken-ichi; Onaka, Hiroshi; Namiki, Shu; Aovama, Tomonori

    2005-11-01

    R and D activities on photonic networks in Japan are presented. First, milestones in current, ongoing R and D programs supported by Japanese government agencies are introduced, including long-distance and WDM fiber transmission, wavelength routing, optical burst switching, and control plane technology for IP backbone networks. Their goal was set to evolve a legacy telecommunications network to IP over WDM networks by introducing technologies for WDM and wavelength routing. We then discuss the perspectives of so-called PHASE II R and D programs for photonic networks over the next five years until 2010, by focusing on the report which has been recently issued by the Photonic Internet Forum (PIF), a consortium that has major carriers, telecom vendors, and Japanese academics as members. The PHASE II R and D programs should serve to establish a photonic platform to provide abundant bandwidth on demand, at any time on a real-time basis through the customer's initiative, to promote bandwidth-rich applications, such as grid computing, real-time digital-cinema streaming, medical and educational applications, and network storage in e-commerce.

  15. RelEx: Visualization for Actively Changing Overlay Network Specifications.

    Science.gov (United States)

    Sedlmair, M; Frank, A; Munzner, T; Butz, A

    2012-12-01

    We present a network visualization design study focused on supporting automotive engineers who need to specify and optimize traffic patterns for in-car communication networks. The task and data abstractions that we derived support actively making changes to an overlay network, where logical communication specifications must be mapped to an underlying physical network. These abstractions are very different from the dominant use case in visual network analysis, namely identifying clusters and central nodes, that stems from the domain of social network analysis. Our visualization tool RelEx was created and iteratively refined through a full user-centered design process that included a full problem characterization phase before tool design began, paper prototyping, iterative refinement in close collaboration with expert users for formative evaluation, deployment in the field with real analysts using their own data, usability testing with non-expert users, and summative evaluation at the end of the deployment. In the summative post-deployment study, which entailed domain experts using the tool over several weeks in their daily practice, we documented many examples where the use of RelEx simplified or sped up their work compared to previous practices.

  16. Power consumption analysis of constant bit rate data transmission over 3G mobile wireless networks

    DEFF Research Database (Denmark)

    Wang, Le; Ukhanova, Ann; Belyaev, Evgeny

    2011-01-01

    This paper presents the analysis of the power consumption of data transmission with constant bit rate over 3G mobile wireless networks. Our work includes the description of the transition state machine in 3G networks, followed by the detailed energy consumption analysis and measurement results...... of the radio link power consumption. Based on these description and analysis, we propose power consumption model. The power model was evaluated on the smartphone Nokia N900, which follows a 3GPP Release 5 and 6 supporting HSDPA/HSPA data bearers. Further we propose method of parameters selection for 3GPP...... transition state machine that allows to decrease power consumption on the mobile device....

  17. Activity flow over resting-state networks shapes cognitive task activations.

    Science.gov (United States)

    Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

    2016-12-01

    Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

  18. Click-Evoked Auditory Efferent Activity: Rate and Level Effects.

    Science.gov (United States)

    Boothalingam, Sriram; Kurke, Julianne; Dhar, Sumitrajit

    2018-05-07

    There currently are no standardized protocols to evaluate auditory efferent function in humans. Typical tests use broadband noise to activate the efferents, but only test the contralateral efferent pathway, risk activating the middle ear muscle reflex (MEMR), and are laborious for clinical use. In an attempt to develop a clinical test of bilateral auditory efferent function, we have designed a method that uses clicks to evoke efferent activity, obtain click-evoked otoacoustic emissions (CEOAEs), and monitor MEMR. This allows for near-simultaneous estimation of cochlear and efferent function. In the present study, we manipulated click level (60, 70, and 80 dB peak-equivalent sound pressure level [peSPL]) and rate (40, 50, and 62.5 Hz) to identify an optimal rate-level combination that evokes measurable efferent modulation of CEOAEs. Our findings (n = 58) demonstrate that almost all click levels and rates used caused significant inhibition of CEOAEs, with a significant interaction between level and rate effects. Predictably, bilateral activation produced greater inhibition compared to stimulating the efferents only in the ipsilateral or contralateral ear. In examining the click rate-level effects during bilateral activation in greater detail, we observed a 1-dB inhibition of CEOAE level for each 10-dB increase in click level, with rate held constant at 62.5 Hz. Similarly, a 10-Hz increase in rate produced a 0.74-dB reduction in CEOAE level, with click level held constant at 80 dB peSPL. The effect size (Cohen's d) was small for either monaural condition and medium for bilateral, faster-rate, and higher-level conditions. We were also able to reliably extract CEOAEs from efferent eliciting clicks. We conclude that clicks can indeed be profitably employed to simultaneously evaluate cochlear health using CEOAEs as well as their efferent modulation. Furthermore, using bilateral clicks allows the evaluation of both the crossed and uncrossed elements of the auditory

  19. Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis

    Science.gov (United States)

    Fokas, Alexander S.; Cole, Daniel J.; Ahnert, Sebastian E.; Chin, Alex W.

    2016-01-01

    Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function. PMID:27623708

  20. Restructuring the crystalline cellulose hydrogen bond network enhances its depolymerization rate

    Science.gov (United States)

    Shishir P.S. Chundawat; Giovanni Bellesia; Nirmal Uppugundla; Leonardo da Costa Sousa; Dahai Gao; Albert M. Cheh; Umesh P. Agarwal; Christopher M. Bianchetti; George N. Phillips; Paul Langan; Venkatesh Balan; S. Gnanakaran; Bruce E. Dale

    2011-01-01

    Conversion of lignocellulose to biofuels is partly inefficient due to the deleterious impact of cellulose crystallinity on enzymatic saccharification. We demonstrate how the synergistic activity of cellulases was enhanced by altering the hydrogen bond network within crystalline cellulose fibrils. We provide a molecular-scale explanation of these phenomena through...

  1. Strain energy storage and dissipation rate in active cell mechanics

    Science.gov (United States)

    Agosti, A.; Ambrosi, D.; Turzi, S.

    2018-05-01

    When living cells are observed at rest on a flat substrate, they can typically exhibit a rounded (symmetric) or an elongated (polarized) shape. Although the cells are apparently at rest, the active stress generated by the molecular motors continuously stretches and drifts the actin network, the cytoskeleton of the cell. In this paper we theoretically compare the energy stored and dissipated in this active system in two geometric configurations of interest: symmetric and polarized. We find that the stored energy is larger for a radially symmetric cell at low activation regime, while the polar configuration has larger strain energy when the active stress is beyond a critical threshold. Conversely, the dissipation of energy in a symmetric cell is always larger than that of a nonsymmetric one. By a combination of symmetry arguments and competition between surface and bulk stress, we argue that radial symmetry is an energetically expensive metastable state that provides access to an infinite number of lower-energy states, the polarized configurations.

  2. Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

    OpenAIRE

    Kaiser, Marcus; Hilgetag, Claus C.

    2010-01-01

    An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

  3. Ads' click-through rates predicting based on gated recurrent unit neural networks

    Science.gov (United States)

    Chen, Qiaohong; Guo, Zixuan; Dong, Wen; Jin, Lingzi

    2018-05-01

    In order to improve the effect of online advertising and to increase the revenue of advertising, the gated recurrent unit neural networks(GRU) model is used as the ads' click through rates(CTR) predicting. Combined with the characteristics of gated unit structure and the unique of time sequence in data, using BPTT algorithm to train the model. Furthermore, by optimizing the step length algorithm of the gated unit recurrent neural networks, making the model reach optimal point better and faster in less iterative rounds. The experiment results show that the model based on the gated recurrent unit neural networks and its optimization of step length algorithm has the better effect on the ads' CTR predicting, which helps advertisers, media and audience achieve a win-win and mutually beneficial situation in Three-Side Game.

  4. Low Duty-Cycling MAC Protocol for Low Data-Rate Medical Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Chongqing Zhang

    2017-05-01

    Full Text Available Wireless body area networks (WBANs are severely energy constrained, and how to improve the energy efficiency so as to prolong the network lifetime as long as possible is one of the most important goals of WBAN research. Low data-rate WBANs are promising to cut down the energy consumption and extend the network lifetime. Considering the characteristics and demands of low data-rate WBANs, a low duty-cycling medium access control (MAC protocol is specially designed for this kind of WBAN in this paper. Longer superframes are exploited to cut down the energy consumed on the transmissions and receptions of redundant beacon frames. Insertion time slots are embedded into the inactive part of a superframe to deliver the frames and satisfy the quality of service (QoS requirements. The number of the data subsections in an insertion time slot can be adaptively adjusted so as to accommodate low data-rate WBANs with different traffic. Simulation results show that the proposed MAC protocol performs well under the condition of low data-rate monitoring traffic.

  5. The European ALARA network. Development, functioning and main activities

    International Nuclear Information System (INIS)

    Schmitt-Hannig, A.

    2009-01-01

    The new ICRP recommendations (ICRP 103), and in particular the detailed treatment of optimisation in the ICRP Publication 101, define optimisation of protection as a source-related process aimed at keeping the likelihood of incurred exposures, the number of people exposed and the magnitude of their individual doses as low as reasonably achievable, also below constraints, taking into account economic and societal factors. Practical implementation and further development of the ALARA principle has been achieved for many years now by the successful cooperation of experts from different European organisations; first as pioneers by establishing the European ALARA Network and then by enthusiastically supporting the activities of the network itself. This contribution presents the evolution, operation and key activities of the European ALARA Network (EAN) in the last years; the successful cooperation of experts from different professional backgrounds, advocating the ALARA principle in a range of radiation protection areas, and contributing to its further development by trading experience and networking. The interaction between the EAN and international organisations, which support the ALARA principle by including relevant activities in their work programmes, is described. (orig.)

  6. TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

    Science.gov (United States)

    Song, W.-Z.; Huang, R.; Shirazi, B.; Husent, R.L.

    2009-01-01

    Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and frame into slots. Parent determines children's frame assigmnent based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. Firstly, given any node, at any time slot, there is at most one active sender in its neighborhood (includ ing itself). Secondly, the packet scheduling with TreelMAC is bufferless, which therefore minimizes the probability of network congestion. Thirdly, the data throughput to gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24 node test bed demonstrate that TreeMAC protocol significantly improves network throughput and energy efficiency, by comparing to the TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC[8]. ?? 2009 IEEE.

  7. Time-Efficient High-Rate Data Flooding in One-Dimensional Acoustic Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jae Kyun Kwon

    2015-10-01

    Full Text Available Because underwater communication environments have poor characteristics, such as severe attenuation, large propagation delays and narrow bandwidths, data is normally transmitted at low rates through acoustic waves. On the other hand, as high traffic has recently been required in diverse areas, high rate transmission has become necessary. In this paper, transmission/reception timing schemes that maximize the time axis use efficiency to improve the resource efficiency for high rate transmission are proposed. The excellence of the proposed scheme is identified by examining the power distributions by node, rate bounds, power levels depending on the rates and number of nodes, and network split gains through mathematical analysis and numerical results. In addition, the simulation results show that the proposed scheme outperforms the existing packet train method.

  8. Meditation leads to reduced default mode network activity beyond an active task.

    Science.gov (United States)

    Garrison, Kathleen A; Zeffiro, Thomas A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

    2015-09-01

    Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.

  9. Recruitment rates in workplace physical activity interventions: characteristics for success.

    Science.gov (United States)

    Ryde, Gemma C; Gilson, Nicholas D; Burton, Nicola W; Brown, Wendy J

    2013-01-01

    To conduct a systematic review to assess recruitment rates in workplace physical activity (PA) intervention studies and describe characteristics of studies with high recruitment rates. Data Source. Electronic and manual searches were conducted. Workplace PA intervention studies that reported the number of employees invited to participate and the number who responded were included. Studies with recruitment rates of ≥70% were categorized as high with the remaining studies (recruitment rate. Seventy-six percent of studies failed to report recruitment rates (n = 30 included for review). Studies with high recruitment rates (n = 8) tended to have longer study duration (mean 1.6 years) and target smaller cohorts of employees (mean n = 199) than comparison studies (3.9 months; n = 1241). For recruitment strategies and intervention components of high studies, involvement of employees was driven by the organization, with PA interventions provided as part of the working day in paid time. These findings suggest a potential to improve recruitment through targeting small cohorts of employees, incorporating PA as a long-term strategy, facilitating organizationally driven employee involvement, and providing PA interventions during paid time.

  10. Evaluating failure rate of fault-tolerant multistage interconnection networks using Weibull life distribution

    International Nuclear Information System (INIS)

    Bistouni, Fathollah; Jahanshahi, Mohsen

    2015-01-01

    Fault-tolerant multistage interconnection networks (MINs) play a vital role in the performance of multiprocessor systems where reliability evaluation becomes one of the main concerns in analyzing these networks properly. In many cases, the primary objective in system reliability analysis is to compute a failure distribution of the entire system according to that of its components. However, since the problem is known to be NP-hard, in none of the previous efforts, the precise evaluation of the system failure rate has been performed. Therefore, our goal is to investigate this parameter for different fault-tolerant MINs using Weibull life distribution that is one of the most commonly used distributions in reliability. In this paper, four important groups of fault-tolerant MINs will be examined to find the best fault-tolerance techniques in terms of failure rate; (1) Extra-stage MINs, (2) Parallel MINs, (3) Rearrangeable non-blocking MINs, and (4) Replicated MINs. This paper comprehensively analyzes all perspectives of the reliability (terminal, broadcast, and network reliability). Moreover, in this study, all reliability equations are calculated for different network sizes. - Highlights: • The failure rate of different MINs is analyzed by using Weibull life distribution. • This article tries to find the best fault-tolerance technique in the field of MINs. • Complex series-parallel RBDs are used to determine the reliability of the MINs. • All aspects of the reliability (i.e. terminal, broadcast, and network) are analyzed. • All reliability equations will be calculated for different size N×N.

  11. Optimal multicasting in a multi-line-rate ethernet-over-WDM network

    Science.gov (United States)

    Harve, Shruthi; Batayneh, Marwan; Mukherjee, Biswanath

    2009-11-01

    Ethernet is the dominant transport technology for Local Area Networks. Efforts are now under way to use carrier-grade Ethernet in backbone networks of different service providers. With the advent of applications such as IPTV and Videoon- Demand, there is need for techniques to route multicast traffic over the Ethernet backbone networks. Here, we address the problem of Routing and Wavelength Assignment (RWA) of a set of multicast requests in a Multi-Line-Rate Ethernet backbone network with the objective of minimizing the cost of setting up the network, in terms of the Service Provider's Capital Expenditure (CAPEX). We present an Auxiliary Graph based heuristic algorithm that routes each multicast request on a light-tree structure, and assigns minimum cost wavelengths along the route. We compare the properties of the algorithm to the optimal solution given by a mathematical model formulated as an Integer Linear Program (ILP), and show that they compare very well. We also find that the algorithm is most cost-effective when the incoming requests are processed in descending order of their bandwidth requirements.

  12. The development trends of credit rating agencies activity in Russia

    Directory of Open Access Journals (Sweden)

    L. E. Galyaeva

    2016-01-01

    Full Text Available The process and the prospects of development of the rating industry in the country are examined in the article. The author analyzes the influence of sovereign Russian credit rating decrease by the world’s leading rating agencies at the beginning of 2015 on financial sector of the country. Politically motivated international credit rating agencies ratings hinder the development of the Russian financial system. That’s why particular attention is paid to the rejection of dependence on the international credit rating agencies ratings and the appearance of a new strong and powerful national credit agency on the Russian market. The problems concerned with speculative estimates of the Russian investment potential. The author points some possible ways to recover from the crisis by involving inner agencies instead of international ones. Special attention is devoted to the existent legislative modifications. Never the less, speaking about the prospects and the future of the leading agencies, it is significant that their work will be relevant in long term due to the increasing uncertainty of the external environment. Moreover the necessity of investing funds in different objects intensifies which leads to the investors and depositors needs of investing. The presented information may be interesting for further profound exploration of the issues, identify the range of problems to be solved by international ratings of the issuers and their securities. In addition, the information proposed in the article can be also served as a basis for further comparison of the activity of international and national agencies in terms of the services offered.

  13. Adaptive sampling rate control for networked systems based on statistical characteristics of packet disordering.

    Science.gov (United States)

    Li, Jin-Na; Er, Meng-Joo; Tan, Yen-Kheng; Yu, Hai-Bin; Zeng, Peng

    2015-09-01

    This paper investigates an adaptive sampling rate control scheme for networked control systems (NCSs) subject to packet disordering. The main objectives of the proposed scheme are (a) to avoid heavy packet disordering existing in communication networks and (b) to stabilize NCSs with packet disordering, transmission delay and packet loss. First, a novel sampling rate control algorithm based on statistical characteristics of disordering entropy is proposed; secondly, an augmented closed-loop NCS that consists of a plant, a sampler and a state-feedback controller is transformed into an uncertain and stochastic system, which facilitates the controller design. Then, a sufficient condition for stochastic stability in terms of Linear Matrix Inequalities (LMIs) is given. Moreover, an adaptive tracking controller is designed such that the sampling period tracks a desired sampling period, which represents a significant contribution. Finally, experimental results are given to illustrate the effectiveness and advantages of the proposed scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  15. 3D Filament Network Segmentation with Multiple Active Contours

    Science.gov (United States)

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2014-03-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

  16. Impairment of GABA transporter GAT-1 terminates cortical recurrent network activity via enhanced phasic inhibition

    Directory of Open Access Journals (Sweden)

    Daniel Simon Razik

    2013-09-01

    Full Text Available In the central nervous system, GABA transporters (GATs very efficiently clear synaptically released GABA from the extracellular space, and thus exert a tight control on GABAergic inhibition. In neocortex, GABAergic inhibition is heavily recruited during recurrent phases of spontaneous action potential activity which alternate with neuronally quiet periods. Therefore, such activity should be quite sensitive to minute alterations of GAT function. Here, we explored the effects of a gradual impairment of GAT-1 and GAT-2/3 on spontaneous recurrent network activity – termed network bursts and silent periods – in organotypic slice cultures of rat neocortex. The GAT-1 specific antagonist NO-711 depressed activity already at nanomolar concentrations (IC50 for depression of spontaneous multiunit firing rate of 42 nM, reaching a level of 80% at 500-1000 nM. By contrast, the GAT-2/3 preferring antagonist SNAP-5114 had weaker and less consistent effects. Several lines of evidence pointed towards an enhancement of phasic GABAergic inhibition as the dominant activity-depressing mechanism: network bursts were drastically shortened, phasic GABAergic currents decayed slower, and neuronal excitability during ongoing activity was diminished. In silent periods, NO-711 had little effect on neuronal excitability or membrane resistance, quite in contrast to the effects of muscimol, a GABA mimetic which activates GABAA receptors tonically. Our results suggest that an enhancement of phasic GABAergic inhibition efficiently curtails cortical recurrent activity and may mediate antiepileptic effects of therapeutically relevant concentrations of GAT-1 antagonists.

  17. Multipath Activity Based Routing Protocol for Mobile ‎Cognitive Radio Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Shereen Omar

    2017-01-01

    Full Text Available Cognitive radio networks improve spectrum utilization by ‎sharing licensed spectrum with cognitive radio devices. In ‎cognitive radio ad hoc networks the routing protocol is one ‎of the most challenging tasks due to the changes in ‎frequency spectrum and the interrupted connectivity ‎caused by the primary user activity. In this paper, a multi‎path activity based routing protocol for cognitive radio ‎network (MACNRP is proposed. The protocol utilizes ‎channel availability and creates multiple node-disjoint ‎routes between the source and destination nodes. The ‎proposed protocol is compared with D2CARP and FTCRP ‎protocols. The performance evaluation is conducted ‎through mathematical analysis and using OPNET ‎simulation. The performance of the proposed protocol ‎achieves an increase in network throughput; besides it ‎decreases the probability of route failure due to node ‎mobility and primary user activity. We have found that the ‎MACNRP scheme results in 50% to 75% reduction in ‎blocking probability and 33% to 78% improvement in ‎network throughput, with a reasonable additional routing ‎overhead and average packet delay. Due to the successful ‎reduction of collision between primary users and ‎cognitive users, the MACNRP scheme results in decreasing ‎the path failure rate by 50% to 87%.‎

  18. Bounds on Rates of Variable-Basis and Neural-Network Approximation

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2001-01-01

    Roč. 47, č. 6 (2001), s. 2659-2665 ISSN 0018-9448 R&D Projects: GA ČR GA201/00/1482 Institutional research plan: AV0Z1030915 Keywords : approximation by variable-basis functions * bounds on rates of approximation * complexity of neural networks * high-dimensional optimal decision problems Subject RIV: BA - General Mathematics Impact factor: 2.077, year: 2001

  19. Exponential convergence rate estimation for uncertain delayed neural networks of neutral type

    International Nuclear Information System (INIS)

    Lien, C.-H.; Yu, K.-W.; Lin, Y.-F.; Chung, Y.-J.; Chung, L.-Y.

    2009-01-01

    The global exponential stability for a class of uncertain delayed neural networks (DNNs) of neutral type is investigated in this paper. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of DNNs via LMI and Razumikhin-like approaches. For a given delay, the maximal allowable exponential convergence rate will be estimated. Some numerical examples are given to illustrate the effectiveness of our results. The simulation results reveal significant improvement over the recent results.

  20. On a multistable competitive network model in the case of an inhomogeneous growth rate spectrum: With an application to priming

    International Nuclear Information System (INIS)

    Frank, T.D.

    2009-01-01

    A stability analysis of a network model proposed by Haken is carried out for the case of an inhomogeneous spectrum of growth rates. The degree of multistability as a function of the coupling strength between network units is determined. An application to priming shows that the network can reconstruct the fundamental phenomenon that primed items have shorter recall latencies than non-primed items when assuming that learning affects the inhomogeneity of the growth rate spectrum.

  1. Passive and Active Monitoring on a High Performance Research Network

    International Nuclear Information System (INIS)

    Matthews, Warren

    2001-01-01

    The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10 12 ). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge has arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data

  2. Passive and Active Monitoring on a High Performance Research Network.

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Warren

    2001-05-01

    The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10{sup 12}). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge has arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not!) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data.

  3. The Brain on Art: Intense Aesthetic Experience Activates the Default Mode Network

    Directory of Open Access Journals (Sweden)

    Edward A Vessel

    2012-04-01

    Full Text Available Aesthetic responses to visual art comprise multiple types of experiences, from sensation and perception to emotion and self-reflection. Moreover, aesthetic experience is highly individual, with observers varying significantly in their responses to the same artwork. Combining fMRI and behavioral analysis of individual differences in aesthetic response, we identify two distinct patterns of neural activity exhibited by different subnetworks. Activity increased linearly with observers’ ratings (4-level scale in sensory (occipito-temporal regions. Activity in the striatum also varied linearly with ratings, with below-baseline activations for low-rated artworks. In contrast, a network of frontal regions showed a step-like increase only for the most moving artworks (4 ratings and non-differential activity for all others. This included several regions belonging to the default mode network previously associated with self-referential mentation. Our results suggest that aesthetic experience involves the integration of sensory and emotional reactions in a manner linked with their personal relevance.

  4. Harvesting full-duplex rate gains in cellular networks with half-duplex user terminals

    KAUST Repository

    AlAmmouri, Ahmad

    2016-07-26

    Full-Duplex (FD) transceivers may be expensive in terms of complexity, power consumption, and price to be implemented in all user terminals. Therefore, techniques to exploit in-band full-duplex communication with FD base stations (BSs) and half-duplex (HD) users\\' equipment (UEs) are required. In this context, 3-node topology (3NT) has been recently proposed for FD BSs to reuse the uplink (UL) and downlink (DL) channels with HD terminals within the same cell. In this paper, we present a tractable mathematical framework, based on stochastic geometry, for 3NT in cellular networks. To this end, we propose a design paradigm via pulse-shaping and partial overlap between UL and DL channels to maximize the harvested rate gains in 3NT. The results show that 3NT achieves a close performance to networks with FD BSs and FD UEs, denoted by 2-node topology (2NT) networks. A maximum of 5% rate loss is reported when 3NT is compared to 2NT with efficient self-interference cancellation (SIC). If the SIC in 2NT is not efficient, 3NT highly outperforms 2NT. Consequently, we conclude that, irrespective to the UE duplexing scheme, it is sufficient to have FD BSs to harvest FD rate gains.

  5. The study of RMB exchange rate complex networks based on fluctuation mode

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou; Liu, Xiao-Feng

    2015-10-01

    In the paper, we research on the characteristics of RMB exchange rate time series fluctuation with methods of symbolization and coarse gaining. First, based on fluctuation features of RMB exchange rate, we define the first type of fluctuation mode as one specific foreign currency against RMB in four days' fluctuating situations, and the second type as four different foreign currencies against RMB in one day's fluctuating situation. With the transforming method, we construct the unique-currency and multi-currency complex networks. Further, through analyzing the topological features including out-degree, betweenness centrality and clustering coefficient of fluctuation-mode complex networks, we find that the out-degree distribution of both types of fluctuation mode basically follows power-law distributions with exponents between 1 and 2. The further analysis reveals that the out-degree and the clustering coefficient generally obey the approximated negative correlation. With this result, we confirm previous observations showing that the RMB exchange rate exhibits a characteristic of long-range memory. Finally, we analyze the most probable transmission route of fluctuation modes, and provide probability prediction matrix. The transmission route for RMB exchange rate fluctuation modes exhibits the characteristics of partially closed loop, repeat and reversibility, which lays a solid foundation for predicting RMB exchange rate fluctuation patterns with large volume of data.

  6. Microgrids in Active Network Management-Part I

    DEFF Research Database (Denmark)

    Palizban, Omid; Kauhaniemia, Kimmo; Guerrero, Josep M.

    2014-01-01

    The microgrid concept has been closely investigated and implemented by numerous experts worldwide. The first part of this paper describes the principles of microgrid design, considering the operational concepts and requirements arising from participation in active network management. Over the las......, energy storage systems, and market participation in both island and grid-connection operation. Finally, control techniques and the principles of energy-storage systems are summarized in a comprehensive flowchart.......The microgrid concept has been closely investigated and implemented by numerous experts worldwide. The first part of this paper describes the principles of microgrid design, considering the operational concepts and requirements arising from participation in active network management. Over the last...

  7. The effect of the neural activity on topological properties of growing neural networks.

    Science.gov (United States)

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  8. Design of a heart rate controller for treadmill exercise using a recurrent fuzzy neural network.

    Science.gov (United States)

    Lu, Chun-Hao; Wang, Wei-Cheng; Tai, Cheng-Chi; Chen, Tien-Chi

    2016-05-01

    In this study, we developed a computer controlled treadmill system using a recurrent fuzzy neural network heart rate controller (RFNNHRC). Treadmill speeds and inclines were controlled by corresponding control servo motors. The RFNNHRC was used to generate the control signals to automatically control treadmill speed and incline to minimize the user heart rate deviations from a preset profile. The RFNNHRC combines a fuzzy reasoning capability to accommodate uncertain information and an artificial recurrent neural network learning process that corrects for treadmill system nonlinearities and uncertainties. Treadmill speeds and inclines are controlled by the RFNNHRC to achieve minimal heart rate deviation from a pre-set profile using adjustable parameters and an on-line learning algorithm that provides robust performance against parameter variations. The on-line learning algorithm of RFNNHRC was developed and implemented using a dsPIC 30F4011 DSP. Application of the proposed control scheme to heart rate responses of runners resulted in smaller fluctuations than those produced by using proportional integra control, and treadmill speeds and inclines were smoother. The present experiments demonstrate improved heart rate tracking performance with the proposed control scheme. The RFNNHRC scheme with adjustable parameters and an on-line learning algorithm was applied to a computer controlled treadmill system with heart rate control during treadmill exercise. Novel RFNNHRC structure and controller stability analyses were introduced. The RFNNHRC were tuned using a Lyapunov function to ensure system stability. The superior heart rate control with the proposed RFNNHRC scheme was demonstrated with various pre-set heart rates. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Activity of cardiorespiratory networks revealed by transsynaptic virus expressing GFP.

    Science.gov (United States)

    Irnaten, M; Neff, R A; Wang, J; Loewy, A D; Mettenleiter, T C; Mendelowitz, D

    2001-01-01

    A fluorescent transneuronal marker capable of labeling individual neurons in a central network while maintaining their normal physiology would permit functional studies of neurons within entire networks responsible for complex behaviors such as cardiorespiratory reflexes. The Bartha strain of pseudorabies virus (PRV), an attenuated swine alpha herpesvirus, can be used as a transsynaptic marker of neural circuits. Bartha PRV invades neuronal networks in the CNS through peripherally projecting axons, replicates in these parent neurons, and then travels transsynaptically to continue labeling the second- and higher-order neurons in a time-dependent manner. A Bartha PRV mutant that expresses green fluorescent protein (GFP) was used to visualize and record from neurons that determine the vagal motor outflow to the heart. Here we show that Bartha PRV-GFP-labeled neurons retain their normal electrophysiological properties and that the labeled baroreflex pathways that control heart rate are unaltered by the virus. This novel transynaptic virus permits in vitro studies of identified neurons within functionally defined neuronal systems including networks that mediate cardiovascular and respiratory function and interactions. We also demonstrate superior laryngeal motorneurons fire spontaneously and synapse on cardiac vagal neurons in the nucleus ambiguus. This cardiorespiratory pathway provides a neural basis of respiratory sinus arrhythmias.

  10. Multi-agent system based active distribution networks

    OpenAIRE

    Nguyen, H.P.

    2010-01-01

    This thesis gives a particular vision of the future power delivery system with its main requirements. An investigation of suitable concepts and technologies which creates a road map forward the smart grid has been carried out. They should meet the requirements on sustainability, efficiency, flexibility and intelligence. The so called Active Distribution Network (ADN) is introduced as an important element of the future power delivery system. With an open architecture, the ADN is designed to in...

  11. Modeling and Visualization of Human Activities for Multicamera Networks

    Directory of Open Access Journals (Sweden)

    Aswin C. Sankaranarayanan

    2009-01-01

    Full Text Available Multicamera networks are becoming complex involving larger sensing areas in order to capture activities and behavior that evolve over long spatial and temporal windows. This necessitates novel methods to process the information sensed by the network and visualize it for an end user. In this paper, we describe a system for modeling and on-demand visualization of activities of groups of humans. Using the prior knowledge of the 3D structure of the scene as well as camera calibration, the system localizes humans as they navigate the scene. Activities of interest are detected by matching models of these activities learnt a priori against the multiview observations. The trajectories and the activity index for each individual summarize the dynamic content of the scene. These are used to render the scene with virtual 3D human models that mimic the observed activities of real humans. In particular, the rendering framework is designed to handle large displays with a cluster of GPUs as well as reduce the cognitive dissonance by rendering realistic weather effects and illumination. We envision use of this system for immersive visualization as well as summarization of videos that capture group behavior.

  12. Quantifying sources of bias in National Healthcare Safety Network laboratory-identified Clostridium difficile infection rates.

    Science.gov (United States)

    Haley, Valerie B; DiRienzo, A Gregory; Lutterloh, Emily C; Stricof, Rachel L

    2014-01-01

    To assess the effect of multiple sources of bias on state- and hospital-specific National Healthcare Safety Network (NHSN) laboratory-identified Clostridium difficile infection (CDI) rates. Sensitivity analysis. A total of 124 New York hospitals in 2010. New York NHSN CDI events from audited hospitals were matched to New York hospital discharge billing records to obtain additional information on patient age, length of stay, and previous hospital discharges. "Corrected" hospital-onset (HO) CDI rates were calculated after (1) correcting inaccurate case reporting found during audits, (2) incorporating knowledge of laboratory results from outside hospitals, (3) excluding days when patients were not at risk from the denominator of the rates, and (4) adjusting for patient age. Data sets were simulated with each of these sources of bias reintroduced individually and combined. The simulated rates were compared with the corrected rates. Performance (ie, better, worse, or average compared with the state average) was categorized, and misclassification compared with the corrected data set was measured. Counting days patients were not at risk in the denominator reduced the state HO rate by 45% and resulted in 8% misclassification. Age adjustment and reporting errors also shifted rates (7% and 6% misclassification, respectively). Changing the NHSN protocol to require reporting of age-stratified patient-days and adjusting for patient-days at risk would improve comparability of rates across hospitals. Further research is needed to validate the risk-adjustment model before these data should be used as hospital performance measures.

  13. Rate-based congestion control in networks with smart links, revision. B.S. Thesis - May 1988

    Science.gov (United States)

    Heybey, Andrew Tyrrell

    1990-01-01

    The author uses a network simulator to explore rate-based congestion control in networks with smart links that can feed back information to tell senders to adjust their transmission rates. This method differs in a very important way from congestion control in which a congested network component just drops packets - the most commonly used method. It is clearly advantageous for the links in the network to communicate with the end users about the network capacity, rather than the users unilaterally picking a transmission rate. The components in the middle of the network, not the end users, have information about the capacity and traffic in the network. The author experiments with three different algorithms for calculating the control rate to feed back to the users. All of the algorithms exhibit problems in the form of large queues when simulated with a configuration modeling the dynamics of a packet-voice system. However, the problems are not with the algorithms themselves, but with the fact that feedback takes time. If the network steady-state utilization is low enough that it can absorb transients in the traffic through it, then the large queues disappear. If the users are modified to start sending slowly, to allow the network to adapt to a new flow without causing congestion, a greater portion of the network's bandwidth can be used.

  14. Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using Response Surface Methodology and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Mohamad, R.

    2013-01-01

    Full Text Available Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM and artificial neural network (ANN were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391,a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%. Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05. In addition the use of RSM and ANN alongside each other provided a proper growth prediction model.

  15. Predicting forest insect flight activity: A Bayesian network approach.

    Directory of Open Access Journals (Sweden)

    Stephen M Pawson

    Full Text Available Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

  16. Evolution on neutral networks accelerates the ticking rate of the molecular clock.

    Science.gov (United States)

    Manrubia, Susanna; Cuesta, José A

    2015-01-06

    Large sets of genotypes give rise to the same phenotype, because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as the genotype mutates into another one on the same set. By linking every pair of genotypes that are mutually accessible through mutation, genotypes organize themselves into neutral networks (NNs). These networks are known to be heterogeneous and assortative, and these properties affect the evolutionary dynamics of the population. By studying the dynamics of populations on NNs with arbitrary topology, we analyse the effect of assortativity, of NN (phenotype) fitness and of network size. We find that the probability that the population leaves the network is smaller the longer the time spent on it. This progressive 'phenotypic entrapment' entails a systematic increase in the overdispersion of the process with time and an acceleration in the fixation rate of neutral mutations. We also quantify the variation of these effects with the size of the phenotype and with its fitness relative to that of neighbouring alternatives. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  17. Visualization of heart rate variability of long-term heart transplant patient by transition networks: a case report

    Directory of Open Access Journals (Sweden)

    Joanna eWdowczyk

    2016-03-01

    Full Text Available We present a heart transplant patient at his 17th year of uncomplicated follow-up. Within a frame of routine check out several tests were performed. With such a long and uneventful follow-up some degree of graft reinnervation could be anticipated. However, the patient's electrocardiogram and exercise parameters seemed largely inconclusive in this regard. The exercise heart rate dynamics were suggestive of only mild, if any parasympathetic reinnervation of the graft with persisting sympathetic activation. On the other hand, traditional heart rate variability (HRV indices were inadequately high, due to erratic rhythm resulting from interference of the persisting recipient sinus node or nonconducted atrial parasystole. New tools, originated from network representation of time series, by visualization short-term dynamical patterns, provided a method to discern HRV increase due to reinnervation from other reasons.

  18. Promotion of active ageing combining sensor and social network data.

    Science.gov (United States)

    Bilbao, Aritz; Almeida, Aitor; López-de-Ipiña, Diego

    2016-12-01

    The increase of life expectancy in modern society has caused an increase in elderly population. Elderly people want to live independently in their home environment for as long as possible. However, as we age, our physical skills tend to worsen and our social circle tends to become smaller, something that often leads to a considerable decrease of both our physical and social activities. In this paper, we present an AAL framework developed within the SONOPA project, whose objective is to promote active ageing by combining a social network with information inferred using in-home sensors. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Technical and economic impacts of active management on distribution network

    International Nuclear Information System (INIS)

    Zhang, Jietan; Cheng, Haozhong; Wang, Chun

    2009-01-01

    With the deregulation of energy market and the appeal for environment protection, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called ''fit and forget'' policy and the capacity of DG is limited rigidly by distribution network operator (DNO) to avoid the negative effects of high level penetration. Therefore active management (AM) is put forward as an effective method to network reinforcement for the connection and operation of DG. In this paper, the concept and principle of AM are introduced, and several indices are proposed to evaluate both technical and economic impacts of AM on distribution network with DG. To simplify the simulation fuzzy C-means clustering (FCM) algorithm is introduced. The test results on a sample system represent that AM will lead to decrease of power generation of DG, but it can reduce energy losses and improve voltage profile effectively. Furthermore, AM will take great economic incentives to DG developer as well as DNO with reasonable policy. (author)

  20. Will available bit rate (ABR) services give us the capability to offer virtual LANs over wide-area ATM networks?

    Science.gov (United States)

    Ferrandiz, Ana; Scallan, Gavin

    1995-10-01

    The available bit rate (ABR) service allows connections to exceed their negotiated data rates during the life of the connections when excess capacity is available in the network. These connections are subject to flow control from the network in the event of network congestion. The ability to dynamically adjust the data rate of the connection can provide improved utilization of the network and be a valuable service to end users. ABR type service is therefore appropriate for the transmission of bursty LAN traffic over a wide area network in a manner that is more efficient and cost effective than allocating bandwdith at the peak cell rate. This paper describes the ABR service and discusses if it is realistic to operate a LAN like service over a wide area using ABR.

  1. Taurine activates GABAergic networks in the neocortex of immature mice

    Directory of Open Access Journals (Sweden)

    Bogdan Aurel Sava

    2014-02-01

    Full Text Available Although it has been suggested that taurine is the main endogenous neurotransmitter acting on glycine receptors, the implications of glycine receptor-mediated taurine actions on immature neocortical networks have not been addressed yet. To investigate the influence of taurine on the excitability of neuronal networks in the immature neocortex, we performed whole-cell patch-clamp recordings from visually identified pyramidal neurons and interneurons in coronal slices from C57Bl/6 and GAD67-GFP transgenic mice (postnatal days 2-4. In 46 % of the pyramidal neurons bath-application of taurine at concentrations ≥ 300 mM significantly enhanced the frequency of postsynaptic currents (PSCs by 744.3 ± 93.8 % (n = 120 cells. This taurine-induced increase of PSC frequency was abolished by 0.2 mM tetrodotoxine, 1 mM strychnine or 3 mM gabazine, but was unaffected by the glutamatergic antagonists 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX and (± R(--3-(2-carboxypiperazine-4-yl-propyl-1-phosphonic acid (CPP, suggesting that taurine specifically activates GABAergic network activity projecting to pyramidal neurons. Cell-attached recordings revealed that taurine enhanced the frequency of action potentials in pyramidal neurons, indicating an excitatory action of the GABAergic PSCs. In order to identify the presynaptic targets of taurine we demonstrate that bath application of taurine induced in GAD67-GFP labeled interneurons an inward current that is mainly mediated by glycine receptors and can generate action potentials in these cells. We conclude from these results that taurine can enhance network excitability in the immature neocortex by selectively activating GABAergic interneurons via interactions with glycine receptors.

  2. PersonA: Persuasive social network for physical Activity.

    Science.gov (United States)

    Ayubi, Soleh U; Parmanto, Bambang

    2012-01-01

    Advances in physical activity (PA) monitoring devices provide ample opportunities for innovations in the way the information produced by these devices is used to encourage people to have more active lifestyles. One such innovation is expanding the current use of the information from self-management to social support. We developed a Persuasive social network for physical Activity (PersonA) that combines automatic input of physical activity data, a smartphone, and a social networking system (SNS). This paper describes the motivation for and overarching design of the PersonA and its functional and non-functional features. PersonA is designed to intelligently and automatically receive raw PA data from the sensors in the smartphone, calculate the data into meaningful PA information, store the information on a secure server, and show the information to the users as persuasive and real-time feedbacks or publish the information to the SNS to generate social support. The implementation of self-monitoring, social support, and persuasive concepts using currently available technologies has the potential for promoting healthy lifestyle, greater community participation, and higher quality of life. We also expect that PersonA will enable health professionals to collect in situ data related to physical activity. The platform is currently being used and tested to improve PA level of three groups of users in Pittsburgh, PA, USA.

  3. Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring.

    Science.gov (United States)

    Lin, Zhiming; Chen, Jun; Li, Xiaoshi; Zhou, Zhihao; Meng, Keyu; Wei, Wei; Yang, Jin; Wang, Zhong Lin

    2017-09-26

    Heart-rate monitoring plays a critical role in personal healthcare management. A low-cost, noninvasive, and user-friendly heart-rate monitoring system is highly desirable. Here, a self-powered wireless body sensor network (BSN) system is developed for heart-rate monitoring via integration of a downy-structure-based triboelectric nanogenerator (D-TENG), a power management circuit, a heart-rate sensor, a signal processing unit, and Bluetooth module for wireless data transmission. By converting the inertia energy of human walking into electric power, a maximum power of 2.28 mW with total conversion efficiency of 57.9% was delivered at low operation frequency, which is capable of immediately and sustainably driving the highly integrated BSN system. The acquired heart-rate signal by the sensor would be processed in the signal process circuit, sent to an external device via the Bluetooth module, and displayed on a personal cell phone in a real-time manner. Moreover, by combining a TENG-based generator and a TENG-based sensor, an all-TENG-based wireless BSN system was developed, realizing continuous and self-powered heart-rate monitoring. This work presents a potential method for personal heart-rate monitoring, featured as being self-powered, cost-effective, noninvasive, and user-friendly.

  4. Effect and Analysis of Sustainable Cell Rate using MPEG video Traffic in ATM Networks

    Directory of Open Access Journals (Sweden)

    Sakshi Kaushal

    2006-04-01

    Full Text Available The broadband networks inhibit the capability to carry multiple types of traffic – voice, video and data, but these services need to be controlled according to the traffic contract negotiated at the time of the connection to maintain desired Quality of service. Such control techniques use traffic descriptors to evaluate its performance and effectiveness. In case of Variable Bit Rate (VBR services, Peak Cell Rate (PCR and its Cell Delay Variation Tolerance (CDVTPCR are mandatory descriptors. In addition to these, ATM Forum proposed Sustainable Cell Rate (SCR and its Cell delay variation tolerance (CDVTSCR. In this paper, we evaluated the impact of specific SCR and CDVTSCR values on the Usage Parameter Control (UPC performance in case of measured MPEG traffic for improving the efficiency

  5. Precision Obtained Using an Artificial Neural Network for Predicting the Material Removal Rate in Ultrasonic Machining

    Directory of Open Access Journals (Sweden)

    Gaoyan Zhong

    2017-12-01

    Full Text Available The present study proposes a back propagation artificial neural network (BPANN to provide improved precision for predicting the material removal rate (MRR in ultrasonic machining. The BPANN benefits from the advantage of artificial neural networks (ANNs in dealing with complex input-output relationships without explicit mathematical functions. In our previous study, a conventional linear regression model and improved nonlinear regression model were established for modelling the MRR in ultrasonic machining to reflect the influence of machining parameters on process response. In the present work, we quantitatively compare the prediction precision obtained by the previously proposed regression models and the presently proposed BPANN model. The results of detailed analyses indicate that the BPANN model provided the highest prediction precision of the three models considered. The present work makes a positive contribution to expanding the applications of ANNs and can be considered as a guide for modelling complex problems of general machining.

  6. Power consumption analysis of constant bit rate video transmission over 3G networks

    DEFF Research Database (Denmark)

    Ukhanova, Ann; Belyaev, Evgeny; Wang, Le

    2012-01-01

    This paper presents an analysis of the power consumption of video data transmission with constant bit rate over 3G mobile wireless networks. The work includes the description of the radio resource control transition state machine in 3G networks, followed by a detailed power consumption analysis...... and measurements of the radio link power consumption. Based on this description and analysis, we propose our power consumption model. The power model was evaluated on a smartphone Nokia N900, which follows 3GPP Release 5 and 6 supporting HSDPA/HSUPA data bearers. We also propose a method for parameter selection...... for the 3GPP transition state machine that allows to decrease power consumption on a mobile device taking signaling traffic, buffer size and latency restrictions into account. Furthermore, we discuss the gain in power consumption vs. PSNR for transmitted video and show the possibility of performing power...

  7. State estimation for Markov-type genetic regulatory networks with delays and uncertain mode transition rates

    International Nuclear Information System (INIS)

    Liang Jinling; Lam, James; Wang Zidong

    2009-01-01

    This Letter is concerned with the robust state estimation problem for uncertain time-delay Markovian jumping genetic regulatory networks (GRNs) with SUM logic, where the uncertainties enter into both the network parameters and the mode transition rate. The nonlinear functions describing the feedback regulation are assumed to satisfy the sector-like conditions. The main purpose of the problem addressed is to design a linear estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, the desired state estimator, that can ensure the estimation error dynamics to be globally robustly asymptotically stable in the mean square, exists. The obtained LMI conditions are dependent on both the lower and the upper bounds of the delays. An illustrative example is presented to demonstrate the feasibility of the proposed estimation schemes.

  8. Deep Recurrent Neural Networks for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Abdulmajid Murad

    2017-11-01

    Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

  9. 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.

  10. Deep Recurrent Neural Networks for Human Activity Recognition.

    Science.gov (United States)

    Murad, Abdulmajid; Pyun, Jae-Young

    2017-11-06

    Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

  11. Tunable deformation modes shape contractility in active biopolymer networks

    Science.gov (United States)

    Stam, Samantha; Banerjee, Shiladitya; Weirich, Kim; Freedman, Simon; Dinner, Aaron; Gardel, Margaret

    Biological polymer-based materials remodel under active, molecular motor-driven forces to perform diverse physiological roles, such as force transmission and spatial self-organization. Critical to understanding these biomaterials is elucidating the role of microscopic polymer deformations, such as stretching, bending, buckling, and relative sliding, on material remodeling. Here, we report that the shape of motor-driven deformations can be used to identify microscopic deformation modes and determine how they propagate to longer length scales. In cross-linked actin networks with sufficiently low densities of the motor protein myosin II, microscopic network deformations are predominantly uniaxial, or dominated by sliding. However, longer-wavelength modes are mostly biaxial, or dominated by bending and buckling, indicating that deformations with uniaxial shapes do not propagate across length scales significantly larger than that of individual polymers. As the density of myosin II is increased, biaxial modes dominate on all length scales we examine due to buildup of sufficient stress to produce smaller-wavelength buckling. In contrast, when we construct networks from unipolar, rigid actin bundles, we observe uniaxial, sliding-based contractions on 1 to 100 μm length scales. Our results demonstrate the biopolymer mechanics can be used to tune deformation modes which, in turn, control shape changes in active materials.

  12. Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

    Science.gov (United States)

    Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

    2017-06-01

    A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

  13. Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

    Science.gov (United States)

    Cassanelli, J.

    2017-12-01

    Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars

  14. A triboelectric motion sensor in wearable body sensor network for human activity recognition.

    Science.gov (United States)

    Hui Huang; Xian Li; Ye Sun

    2016-08-01

    The goal of this study is to design a novel triboelectric motion sensor in wearable body sensor network for human activity recognition. Physical activity recognition is widely used in well-being management, medical diagnosis and rehabilitation. Other than traditional accelerometers, we design a novel wearable sensor system based on triboelectrification. The triboelectric motion sensor can be easily attached to human body and collect motion signals caused by physical activities. The experiments are conducted to collect five common activity data: sitting and standing, walking, climbing upstairs, downstairs, and running. The k-Nearest Neighbor (kNN) clustering algorithm is adopted to recognize these activities and validate the feasibility of this new approach. The results show that our system can perform physical activity recognition with a successful rate over 80% for walking, sitting and standing. The triboelectric structure can also be used as an energy harvester for motion harvesting due to its high output voltage in random low-frequency motion.

  15. Eleven years of net network research activity - inr contributions

    International Nuclear Information System (INIS)

    Deaconu, V.; Ionita, I.; Meleg, T.; Deaconu, M.; Truta, C.; Oncioiu, G.

    2013-01-01

    The European Network on Neutron Techniques Standardization for Structural Integrity (NeT) was established in 2002, grouping institutions from industry, research and academic media. Coordinated by the European Commission.s Joint Research Centre, the main mission of this network is to develop experimental and numerical techniques and standards for the reliable characterisation of residual stresses in structural welds. Each problem is tackled by creating a dedicated Task Group which manages measurement and modelling round robin studies and undertakes a thorough analysis and interpretation of the results. Over forty institutions are active NeT partners, their specific involvement and contributions being summarised in this paper. The Institute for Nuclear Research Pitesti (INR) is one of NeT founders and its contribution is related to numerical modelling, specimen analysis, material characterisation, data analysis or SANS support. This is also emphasised throughout this paper, together with the specific NeT research topics presentation. (authors)

  16. Default-mode-like network activation in awake rodents.

    Directory of Open Access Journals (Sweden)

    Jaymin Upadhyay

    Full Text Available During wakefulness and in absence of performing tasks or sensory processing, the default-mode network (DMN, an intrinsic central nervous system (CNS network, is in an active state. Non-human primate and human CNS imaging studies have identified the DMN in these two species. Clinical imaging studies have shown that the pattern of activity within the DMN is often modulated in various disease states (e.g., Alzheimer's, schizophrenia or chronic pain. However, whether the DMN exists in awake rodents has not been characterized. The current data provides evidence that awake rodents also possess 'DMN-like' functional connectivity, but only subsequent to habituation to what is initially a novel magnetic resonance imaging (MRI environment as well as physical restraint. Specifically, the habituation process spanned across four separate scanning sessions (Day 2, 4, 6 and 8. At Day 8, significant (p<0.05 functional connectivity was observed amongst structures such as the anterior cingulate (seed region, retrosplenial, parietal, and hippocampal cortices. Prior to habituation (Day 2, functional connectivity was only detected (p<0.05 amongst CNS structures known to mediate anxiety (i.e., anterior cingulate (seed region, posterior hypothalamic area, amygdala and parabracial nucleus. In relating functional connectivity between cingulate-default-mode and cingulate-anxiety structures across Days 2-8, a significant inverse relationship (r = -0.65, p = 0.0004 was observed between these two functional interactions such that increased cingulate-DMN connectivity corresponded to decreased cingulate anxiety network connectivity. This investigation demonstrates that the cingulate is an important component of both the rodent DMN-like and anxiety networks.

  17. Performance Analysis for Bit Error Rate of DS- CDMA Sensor Network Systems with Source Coding

    Directory of Open Access Journals (Sweden)

    Haider M. AlSabbagh

    2012-03-01

    Full Text Available The minimum energy (ME coding combined with DS-CDMA wireless sensor network is analyzed in order to reduce energy consumed and multiple access interference (MAI with related to number of user(receiver. Also, the minimum energy coding which exploits redundant bits for saving power with utilizing RF link and On-Off-Keying modulation. The relations are presented and discussed for several levels of errors expected in the employed channel via amount of bit error rates and amount of the SNR for number of users (receivers.

  18. A network-based rating system and its resistance to bribery

    OpenAIRE

    Turrini, P; Grandi, U

    2016-01-01

    We study a rating system in which a set of individ- uals (e.g., the customers of a restaurant) evaluate a given service (e.g, the restaurant), with their ag- gregated opinion determining the probability of all individuals to use the service and thus its generated revenue. We explicitly model the influence relation by a social network, with individuals being influ- enced by the evaluation of their trusted peers. On top of that we allow a malicious service provider (e.g., the restaurant owne...

  19. Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

    Science.gov (United States)

    Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

    2018-02-01

    Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

  20. Wireless sensor networks for active vibration control in automobile structures

    International Nuclear Information System (INIS)

    Mieyeville, Fabien; Navarro, David; Du, Wan; Ichchou, Mohamed; Scorletti, Gérard

    2012-01-01

    Wireless sensor networks (WSNs) are nowadays widely used in monitoring and tracking applications. This paper presents the feasibility of using WSNs in active vibration control strategies. The method employed here involves active-structural acoustic control using piezoelectric sensors distributed on a car structure. This system aims at being merged with a WSN whose head node collects data and processes control laws so as to command piezoelectric actuators wisely placed on the structure. We will study the feasibility of implementing WSNs in active vibration control and introduce a complete design methodology to optimize hardware/software and control law synergy in mechatronic systems. A design space exploration will be conducted so as to identify the best WSN platform and the resulting impact on control. (paper)

  1. A Comparative Study of Neural Networks and ANFIS for Forecasting Attendance Rate of Soccer Games

    Directory of Open Access Journals (Sweden)

    Mehmet Şahin

    2017-11-01

    Full Text Available The main purpose of this study was to develop and apply a neural network (NN approach and an adaptive neuro-fuzzy inference system (ANFIS model for forecasting the attendance rates at soccer games. The models were designed based on the characteristics of the problem. Past real data was used. Training data was used for training the models, and the testing data was used for evaluating the performance of the forecasting models. The obtained forecasting results were compared to the actual data and to each other. To evaluate the performance of the models, two statistical indicators, Mean Absolute Deviation (MAD and mean absolute percent error (MAPE, were used. Based on the results, the proposed neural network approach and the ANFIS model were shown to be effective in forecasting attendance at soccer games. The neural network approach performed better than the ANFIS model. The main contribution of this study is to introduce two effective techniques for estimating attendance at sports games. This is the first attempt to use an ANFIS model for that purpose.

  2. Academic Activities Transaction Extraction Based on Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Xiangqian Wang

    2017-01-01

    Full Text Available Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.

  3. The pairwise phase consistency in cortical network and its relationship with neuronal activation

    Directory of Open Access Journals (Sweden)

    Wang Daming

    2017-01-01

    Full Text Available Gamma-band neuronal oscillation and synchronization with the range of 30-90 Hz are ubiquitous phenomenon across numerous brain areas and various species, and correlated with plenty of cognitive functions. The phase of the oscillation, as one aspect of CTC (Communication through Coherence hypothesis, underlies various functions for feature coding, memory processing and behaviour performing. The PPC (Pairwise Phase Consistency, an improved coherence measure, statistically quantifies the strength of phase synchronization. In order to evaluate the PPC and its relationships with input stimulus, neuronal activation and firing rate, a simplified spiking neuronal network is constructed to simulate orientation columns in primary visual cortex. If the input orientation stimulus is preferred for a certain orientation column, neurons within this corresponding column will obtain higher firing rate and stronger neuronal activation, which consequently engender higher PPC values, with higher PPC corresponding to higher firing rate. In addition, we investigate the PPC in time resolved analysis with a sliding window.

  4. Study of the dose rate measured by the radiological surveillance network of the Basque country

    International Nuclear Information System (INIS)

    Alegria, N.; Legarda, F.; Herranz, M.

    2006-01-01

    Full text of publication follows: The radiological Surveillance Network of the Basque Country, which is constituted by three stations located in Bilbao, Vitoria and San Sebastian, measures and records the dose date every 10 minutes. Some environmental parameters affect the behaviour of the dose rate. One of most important meteorological parameters is rain. So, it has been necessary to study separately the behaviour of dose rate in the absence of rain, defining that time as Dry Time, and the behaviour when it rains, designating that time as Wet Time. Previous studies have confirmed that dose rate values are fitted to normal distributions, and in those cases, Critical Limits can be calculated using Curie formulation. Every January, data recorded in previous year, two Critical Limits are obtained, one of them for dry time and other one for wet time, and both together define the Alarm Level for each radiological station. That Alarm Level is the reference value for dose rate. If some dose rate value is higher than the corresponding Alarm Level, the recorded values have to be studied in order to identify the origin or the cause of that value. In most cases, in which the dose rate is higher than the corresponding Alarm Level due to precipitation, occurs that when rain stops the dose rate value does not fall immediately to dry rime values, and then the Alarm Level which is now that for dry time is exceeded by the dose rate. So, those values can be considered a special group called Transition Area. The second part of the study tries to explain the cause and the behaviour of the values in the transition Area by means of the study of the behaviour of radon daughters in the atmosphere and their deposition onto the ground during rain intervals. To check the results several situations have been simulated using the Monte Carlo code MCNP-4C. (authors)

  5. Modeling long-term human activeness using recurrent neural networks for biometric data.

    Science.gov (United States)

    Kim, Zae Myung; Oh, Hyungrai; Kim, Han-Gyu; Lim, Chae-Gyun; Oh, Kyo-Joong; Choi, Ho-Jin

    2017-05-18

    With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user's "activeness", and investigates the feasibility in modeling and predicting the long-term activeness of the user. The dataset used in this study consisted of several months of biometric time-series data gathered by seven users independently. Four recurrent neural network (RNN) architectures-as well as a deep neural network and a simple regression model-were proposed to investigate the performance on predicting the activeness of the user under various length-related hyper-parameter settings. In addition, the learned model was tested to predict the time period when the user's activeness falls below a certain threshold. A preliminary experimental result shows that each type of activeness data exhibited a short-term autocorrelation; and among the three types of data, the consumed calories and the number of footsteps were positively correlated, while the heart rate data showed almost no correlation with neither of them. It is probably due to this characteristic of the dataset that although the RNN models produced the best results on modeling the user's activeness, the difference was marginal; and other baseline models, especially the linear regression model, performed quite admirably as well. Further experimental results show that it is feasible to predict a user's future activeness with precision, for example, a trained RNN model could predict-with the precision of 84%-when the user would be less active within the next hour given the latest 15 min of his activeness data. This paper defines and investigates the notion of a user's "activeness", and shows that forecasting the long-term activeness of the user is indeed possible. Such information can be utilized by a health-related application to proactively

  6. Moving Target Detection and Active Tracking with a Multicamera Network

    Directory of Open Access Journals (Sweden)

    Long Zhao

    2014-01-01

    Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.

  7. Impact of Demand Side Management in Active Distribution Networks

    DEFF Research Database (Denmark)

    Ponnaganti, Pavani; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    Demand Side Management (DSM) is an efficient flexible program which helps distribution network operators to meet the future critical peak demand. It is executed in cases of not only technical issues like voltage sag or swell, transformer burdening, cable congestions, but also to increase the degree...... of visibility in the electricity markets. The aim of this paper is to find the optimal flexible demands that can be shifted to another time in order to operate the active distribution system within secure operating limits. A simple mechanism is proposed for finding the flexibility of the loads where electric...

  8. Joint sensor placement and power rating selection in energy harvesting wireless sensor networks

    KAUST Repository

    Bushnaq, Osama M.

    2017-11-02

    In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account the amount of energy harvested by the sensing nodes, communication link quality, and the observation accuracy at the sensor level. In particular, the aim is to reconstruct the estimation parameter with minimum error at a fusion center under a system budget constraint. To achieve this goal, a subset of sensing locations is selected from a large pool of candidate sensing locations. Furthermore, the type of sensor to be placed at those locations is selected from a given set of sensor types (e.g., sensors with different power ratings). We further investigate whether it is better to install a large number of cheap sensors, a few expensive sensors or a combination of different sensor types at the optimal locations.

  9. Informatics technology mimics ecology: dense, mutualistic collaboration networks are associated with higher publication rates.

    Directory of Open Access Journals (Sweden)

    Marco D Sorani

    Full Text Available Information technology (IT adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense

  10. Informatics technology mimics ecology: dense, mutualistic collaboration networks are associated with higher publication rates.

    Science.gov (United States)

    Sorani, Marco D

    2012-01-01

    Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense, mutualistic

  11. Active self-testing noise measurement sensors for large-scale environmental sensor networks.

    Science.gov (United States)

    Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

    2013-12-13

    Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10.

  12. Friendship Network Characteristics Are Associated with Physical Activity and Sedentary Behavior in Early Adolescence.

    Science.gov (United States)

    Marks, Jennifer; de la Haye, Kayla; Barnett, Lisa M; Allender, Steven

    2015-01-01

    There is limited understanding of the association between peer social networks and physical activity (PA), sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents. Participants were 310 students, aged 11-13 years, from fifteen randomly selected Victorian primary schools (43% response rate). PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior. Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys. Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time.

  13. Failure rate modeling using fault tree analysis and Bayesian network: DEMO pulsed operation turbine study case

    Energy Technology Data Exchange (ETDEWEB)

    Dongiovanni, Danilo Nicola, E-mail: danilo.dongiovanni@enea.it [ENEA, Nuclear Fusion and Safety Technologies Department, via Enrico Fermi 45, Frascati 00040 (Italy); Iesmantas, Tomas [LEI, Breslaujos str. 3 Kaunas (Lithuania)

    2016-11-01

    Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability

  14. Failure rate modeling using fault tree analysis and Bayesian network: DEMO pulsed operation turbine study case

    International Nuclear Information System (INIS)

    Dongiovanni, Danilo Nicola; Iesmantas, Tomas

    2016-01-01

    Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability

  15. Extraction of elementary rate constants from global network analysis of E. coli central metabolism

    Directory of Open Access Journals (Sweden)

    Broderick Gordon

    2008-05-01

    Full Text Available Abstract Background As computational performance steadily increases, so does interest in extending one-particle-per-molecule models to larger physiological problems. Such models however require elementary rate constants to calculate time-dependent rate coefficients under physiological conditions. Unfortunately, even when in vivo kinetic data is available, it is often in the form of aggregated rate laws (ARL that do not specify the required elementary rate constants corresponding to mass-action rate laws (MRL. There is therefore a need to develop a method which is capable of automatically transforming ARL kinetic information into more detailed MRL rate constants. Results By incorporating proteomic data related to enzyme abundance into an MRL modelling framework, here we present an efficient method operating at a global network level for extracting elementary rate constants from experiment-based aggregated rate law (ARL models. The method combines two techniques that can be used to overcome the difficult properties in parameterization. The first, a hybrid MRL/ARL modelling technique, is used to divide the parameter estimation problem into sub-problems, so that the parameters of the mass action rate laws for each enzyme are estimated in separate steps. This reduces the number of parameters that have to be optimized simultaneously. The second, a hybrid algebraic-numerical simulation and optimization approach, is used to render some rate constants identifiable, as well as to greatly narrow the bounds of the other rate constants that remain unidentifiable. This is done by incorporating equality constraints derived from the King-Altman and Cleland method into the simulated annealing algorithm. We apply these two techniques to estimate the rate constants of a model of E. coli glycolytic pathways. The simulation and statistical results show that our innovative method performs well in dealing with the issues of high computation cost, stiffness, local

  16. Extraction of elementary rate constants from global network analysis of E. coli central metabolism

    Science.gov (United States)

    Zhao, Jiao; Ridgway, Douglas; Broderick, Gordon; Kovalenko, Andriy; Ellison, Michael

    2008-01-01

    Background As computational performance steadily increases, so does interest in extending one-particle-per-molecule models to larger physiological problems. Such models however require elementary rate constants to calculate time-dependent rate coefficients under physiological conditions. Unfortunately, even when in vivo kinetic data is available, it is often in the form of aggregated rate laws (ARL) that do not specify the required elementary rate constants corresponding to mass-action rate laws (MRL). There is therefore a need to develop a method which is capable of automatically transforming ARL kinetic information into more detailed MRL rate constants. Results By incorporating proteomic data related to enzyme abundance into an MRL modelling framework, here we present an efficient method operating at a global network level for extracting elementary rate constants from experiment-based aggregated rate law (ARL) models. The method combines two techniques that can be used to overcome the difficult properties in parameterization. The first, a hybrid MRL/ARL modelling technique, is used to divide the parameter estimation problem into sub-problems, so that the parameters of the mass action rate laws for each enzyme are estimated in separate steps. This reduces the number of parameters that have to be optimized simultaneously. The second, a hybrid algebraic-numerical simulation and optimization approach, is used to render some rate constants identifiable, as well as to greatly narrow the bounds of the other rate constants that remain unidentifiable. This is done by incorporating equality constraints derived from the King-Altman and Cleland method into the simulated annealing algorithm. We apply these two techniques to estimate the rate constants of a model of E. coli glycolytic pathways. The simulation and statistical results show that our innovative method performs well in dealing with the issues of high computation cost, stiffness, local minima and uncertainty

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

    Science.gov (United States)

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

    2017-02-01

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

  18. Neural Network for Determining Risk Rate of Post-Heart Stroke Patients

    Directory of Open Access Journals (Sweden)

    Oldřich Trenz

    2014-01-01

    Full Text Available The ischemic heart disease presents an important health problem that affects a great part of the population and is the cause of one third of all deaths in the Czech Republic. The availability of data describing the patients’ prognosis enables their further analysis, with the aim of lowering the patients’ risk, by proposing optimum treatment. The main reason for creating the neural network model is not only to automate the process of establishing the risk rate of patients suffering from ischemic heart disease, but also to adapt it for practical use in clinical conditions. Our aim is to identify especially the specific group of risk-rate patients whose well-timed preventive care can improve the quality and prolong the length of their lives.The aim of the paper is to propose a patient-parameter structure, using which we could create a suitable model based on a self-taught neural network. The emphasis is placed on identifying key descriptive parameters (in the form of a reduction of the available descriptive parameters that are crucial for identifying the required patients, and simultaneously to achieve a portability of the model among individual clinical workplaces (availability of parameters.

  19. Death and rebirth of neural activity in sparse inhibitory networks

    Science.gov (United States)

    Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

    2017-05-01

    Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

  20. Studying the active deformation of distributed plate boundaries by integration of GNSS networks

    Science.gov (United States)

    D'Agostino, Nicola; Avallone, Antonio; Cecere, Gianpaolo; D'Anastasio, Elisabetta

    2013-04-01

    In the last decade GNSS networks installed for different purposes have proliferated in Italy and now provide a large amount of data available to geophysical studies. In addition to the existing regional and nation-wide scientific GNSS networks developed by ASI (http://geodaf.mt.asi.it), INGV (http://ring.gm.ingv.it) and OGS (http://crs.inogs.it/frednet), a large number (> 400) of continuously-operating GPS stations have been installed in the framework of regional and national networks, both publicly-operated and commercial, developed to provide real-time positioning capability to surveyors. Although the quality of the data and metadata associated to these stations is generally lower with respect to the "scientific" CGPS stations, the increased density and redundancy in crustal motion information, resulting in more than 500 stations with more than 2.5 years of observations, significantly increase the knowledge of the active deformation of the Italian territory and provides a unique image of the crustal deformation field. The obtained GPS velocity field is analysed and various features ranging from the definition of strain distribution and microplate kinematics within the plate boundary, to the evaluation of tectonic strain accumulation on active faults are presented in this work. Undeforming, aseismic regions (Sardinia, Southern Apulia) provide test sites to evaluate the lower bound on the accuracy achievable to measure tectonic deformation. Integration of GNSS networks significantly improves the resolution of the strain rate field in Central Italy showing that active deformation is concentrated in a narrow belt along the crest of the Apennines, consistently with the distribution of the largest historical and recent earthquakes. Products derived from dense GPS velocity and strain rate fields include map of earthquake potential developed under the assumption that the rate of seismic moment accumulation measured from geodesy distributes into earthquake sizes that

  1. Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention

    Directory of Open Access Journals (Sweden)

    Mara eKottlow

    2015-05-01

    Full Text Available Working memory (WM processes depend on our momentary mental state and therefore exhibit considerable fluctuations. Here, we investigate the interplay of task-preparatory and task-related brain activity as represented by pre-stimulus BOLD-fluctuations and spectral EEG from the retention periods of a visual WM task. Visual WM is used to maintain sensory information in the brain enabling the performance of cognitive operations and is associated with mental health.We tested 22 subjects simultaneously with EEG and fMRI while performing a visuo-verbal Sternberg task with two different loads, allowing for the temporal separation of preparation, encoding, retention and retrieval periods.Four temporally coherent networks - the default mode network (DMN, the dorsal attention, the right and the left WM network - were extracted from the continuous BOLD data by means of a group ICA. Subsequently, the modulatory effect of these networks’ pre-stimulus activation upon retention-related EEG activity in the theta, alpha and beta frequencies was analyzed. The obtained results are informative in the context of state-dependent information processing.We were able to replicate two well-known load-dependent effects: the frontal-midline theta increase during the task and the decrease of pre-stimulus DMN activity. As our main finding, these two measures seem to depend on each other as the significant negative correlations at frontal-midline channels suggested. Thus, suppressed pre-stimulus DMN levels facilitated later task related frontal midline theta increases. In general, based on previous findings that neuronal coupling in different frequency bands may underlie distinct functions in WM retention, our results suggest that processes reflected by spectral oscillations during retention seem not only to be online synchronized with activity in different attention-related networks but are also modulated by activity in these networks during preparation intervals.

  2. Inventive Activity of Researchers: Cross-Country Rating Assessments

    Directory of Open Access Journals (Sweden)

    Tatyana Ivanovna Volkova

    2017-03-01

    Full Text Available In recent years, the study of the research capacity of the country and regions has become more active not only from the point of view of their leading components (personnel, financial, information, organizational, material-and-technical ones but also from the perspective of the assessment of productivity and effectiveness of researchers’ work. In the cross-country analysis, the certain highly aggregative parameters, which values, as a rule, are not in favour of Russia, are used. At the same time, at profound studying of this topic, these estimates cannot represent correctly the real trends of inventive activity in the scientific and technological sphere of the country and its regions. Moreover, the measurement of the researchers’ creative potential realization is carried out mainly through the assessment systems of their printing activity. Little attention is paid to the problem of the rating assessments of the researchers’ inventive and patent activity and its products from a cross-country perspective (especially to the detailed ones as well as to its institutional determinants. Therefore, the authors have chosen this subject-matter of the research. Its empirical basis is the statistical materials of both the national database and those which are recognized by the world scientific community. This research has both theoretical and methodological orientations. The purpose is the development of methodological and methodical tools of the research and assessment of researchers’ inventive activity including methodological support of cross-country comparative assessments. The authors have based the hypothesis on their previous research: in the conditions of the decreasing level of financial security, continuous reduction of a number of researchers, institutional restrictions and contradictions, the inventive activity of national researchers is still exist, and in a number of its leading parameters is implemented at the level of the advanced

  3. Implementation of a wireless sensor network for heart rate monitoring in a senior center.

    Science.gov (United States)

    Huang, Jyh-How; Su, Tzu-Yao; Raknim, Paweeya; Lan, Kun-Chan

    2015-06-01

    Wearable sensor systems are widely used to monitor vital sign in hospitals and in recent years have also been used at home. In this article we present a system that includes a ring probe, sensor, radio, and receiver, designed for use as a long-term heart rate monitoring system in a senior center. The primary contribution of this article is successfully implementing a cheap, large-scale wireless heart rate monitoring system that is stable and comfortable to use 24 h a day. We developed new finger ring sensors for comfortable continuous wearing experience and used dynamic power adjustment on the ring so the sensor can detect pulses at different strength levels. Our system has been deployed in a senior center since May 2012, and 63 seniors have used this system in this period. During the 54-h system observation period, 10 alarms were set off. Eight of them were due to abnormal heart rate, and two of them were due to loose probes. The monitoring system runs stably with the senior center's existing WiFi network, and achieves 99.48% system availability. The managers and caregivers use our system as a reliable warning system for clinical deterioration. The results of the year-long deployment show that the wireless group heart rate monitoring system developed in this work is viable for use within a designated area.

  4. Integrated Strategic Planning of Global Production Networks and Financial Hedging under Uncertain Demands and Exchange Rates

    Directory of Open Access Journals (Sweden)

    Achim Koberstein

    2013-11-01

    Full Text Available In this paper, we present a multi-stage stochastic programming model that integrates financial hedging decisions into the planning of strategic production networks under uncertain exchange rates and product demands. This model considers the expenses of production plants and the revenues of markets in different currency areas. Financial portfolio planning decisions for two types of financial instruments, forward contracts and options, are represented explicitly by multi-period decision variables and a multi-stage scenario tree. Using an illustrative example, we analyze the impact of exchange-rate and demand volatility, the level of investment expenses and interest rate spreads on capacity location and dimensioning decisions. In particular, we show that, in the illustrative example, the exchange-rate uncertainty cannot be completely eliminated by financial hedging in the presence of demand uncertainty. In this situation, we find that the integrated model can result in better strategic planning decisions for a risk-averse decision maker compared to traditional modeling approaches.

  5. Optimal Bidding Strategy for Renewable Microgrid with Active Network Management

    Directory of Open Access Journals (Sweden)

    Seung Wan Kim

    2016-01-01

    Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.

  6. Situation awareness of active distribution network: roadmap, technologies, and bottlenecks

    DEFF Research Database (Denmark)

    Lin, Jin; Wan, Can; Song, Yonghua

    2016-01-01

    With the rapid development of local generation and demand response, the active distribution network (ADN), which aggregates and manages miscellaneous distributed resources, has moved from theory to practice. Secure and optimal operations now require an advanced situation awareness (SA) system so...... in the project of developing an SA system as the basic component of a practical active distribution management system (ADMS) deployed in Beijing, China, is presented. This paper reviews the ADN’s development roadmap by illustrating the changes that are made in elements, topology, structure, and control scheme....... Taking into consideration these hardware changes, a systematic framework is proposed for the main components and the functional hierarchy of an SA system for the ADN. The SA system’s implementation bottlenecks are also presented, including, but not limited to issues in big data platform, distribution...

  7. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    Directory of Open Access Journals (Sweden)

    Mehrshad Salmasi

    2012-07-01

    Full Text Available Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in noise attenuation are compared. We use Elman network as a recurrent neural network. For simulations, noise signals from a SPIB database are used. In order to compare the networks appropriately, equal number of layers and neurons are considered for the networks. Moreover, training and test samples are similar. Simulation results show that feedforward and recurrent neural networks present good performance in noise cancellation. As it is seen, the ability of recurrent neural network in noise attenuation is better than feedforward network.

  8. Photonic Network R&D Activities in Japan-Current Activities and Future Perspectives

    Science.gov (United States)

    Kitayama, Ken-Ichi; Miki, Tetsuya; Morioka, Toshio; Tsushima, Hideaki; Koga, Masafumi; Mori, Kazuyuki; Araki, Soichiro; Sato, Ken-Ichi; Onaka, Hiroshi; Namiki, Shu; Aoyama, Tomonori

    2005-10-01

    R&D activities on photonic networks in Japan are presented. First, milestones in current ongoing R&D programs supported by Japanese government agencies are introduced, including long-distance and wavelength division multiplexing (WDM) fiber transmission, wavelength routing, optical burst switching (OBS), and control-plane technology for IP backbone networks. Their goal was set to evolve a legacy telecommunications network to IP-over-WDM networks by introducing technologies for WDM and wavelength routing. We then discuss the perspectives of so-called PHASE II R&D programs for photonic networks over the next 5 years until 2010, by focusing on the report that has been recently issued by the Photonic Internet Forum (PIF), a consortium that has major carriers, telecom vendors, and Japanese academics as members. The PHASE II R&D programs should serve to establish a photonic platform to provide abundant bandwidth on demand, at any time on a real-time basis, through the customer's initiative to promote bandwidth-rich applications, such as grid computing, real-time digital-cinema streaming, medical and educational applications, and network storage in e-commerce.

  9. Estimation of Leak Flow Rate during Post-LOCA Using Cascaded Fuzzy Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Yeong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Na, Man Gyun [Chosun University, Gwangju (Korea, Republic of)

    2016-10-15

    In this study, important parameters such as the break position, size, and leak flow rate of loss of coolant accidents (LOCAs), provide operators with essential information for recovering the cooling capability of the nuclear reactor core, for preventing the reactor core from melting down, and for managing severe accidents effectively. Leak flow rate should consist of break size, differential pressure, temperature, and so on (where differential pressure means difference between internal and external reactor vessel pressure). The leak flow rate is strongly dependent on the break size and the differential pressure, but the break size is not measured and the integrity of pressure sensors is not assured in severe circumstances. In this paper, a cascaded fuzzy neural network (CFNN) model is appropriately proposed to estimate the leak flow rate out of break, which has a direct impact on the important times (time approaching the core exit temperature that exceeds 1200 .deg. F, core uncover time, reactor vessel failure time, etc.). The CFNN is a data-based model, it requires data to develop and verify itself. Because few actual severe accident data exist, it is essential to obtain the data required in the proposed model using numerical simulations. In this study, a CFNN model was developed to predict the leak flow rate before proceeding to severe LOCAs. The simulations showed that the developed CFNN model accurately predicted the leak flow rate with less error than 0.5%. The CFNN model is much better than FNN model under the same conditions, such as the same fuzzy rules. At the result of comparison, the RMS errors of the CFNN model were reduced by approximately 82 ~ 97% of those of the FNN model.

  10. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

    OpenAIRE

    Li, Jibin; Lau, Joseph T. F.; Mo, Phoenix K. H.; Su, Xuefen; Wu, Anise M. S.; Tang, Jie; Qin, Zuguo

    2016-01-01

    Background Online social networking use has been integrated into adolescents? daily life and the intensity of online social networking use may have important consequences on adolescents? well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. Methods A total of 910 students who were social networking...

  11. A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons” [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Rainer Engelken

    2016-08-01

    Full Text Available Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

  12. Fault Activity Aware Service Delivery in Wireless Sensor Networks for Smart Cities

    Directory of Open Access Journals (Sweden)

    Xiaomei Zhang

    2017-01-01

    Full Text Available Wireless sensor networks (WSNs are increasingly used in smart cities which involve multiple city services having quality of service (QoS requirements. When misbehaving devices exist, the performance of current delivery protocols degrades significantly. Nonetheless, the majority of existing schemes either ignore the faulty behaviors’ variability and time-variance in city environments or focus on homogeneous traffic for traditional data services (simple text messages rather than city services (health care units, traffic monitors, and video surveillance. We consider the problem of fault-aware multiservice delivery, in which the network performs secure routing and rate control in terms of fault activity dynamic metric. To this end, we first design a distributed framework to estimate the fault activity information based on the effects of nondeterministic faulty behaviors and to incorporate these estimates into the service delivery. Then we present a fault activity geographic opportunistic routing (FAGOR algorithm addressing a wide range of misbehaviors. We develop a leaky-hop model and design a fault activity rate-control algorithm for heterogeneous traffic to allocate resources, while guaranteeing utility fairness among multiple city services. Finally, we demonstrate the significant performance of our scheme in routing performance, effective utility, and utility fairness in the presence of misbehaving sensors through extensive simulations.

  13. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks

    OpenAIRE

    Wang, Yongqiang; Nunez, Felipe; Doyle III, Francis J.

    2012-01-01

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is incr...

  14. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    Science.gov (United States)

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc.

  15. Cost-related model for transit rates in electric power distribution networks

    International Nuclear Information System (INIS)

    Collstrand, F.

    1994-02-01

    The planned deregulation of the swedish electrical power market will require a new structure of the electrical energy rates. In this report different models of transit rates are studied. The report includes studies of literature and a proposal to a rate structure and is made specifically for Malmoe Energi AB. The differences between various methods of calculating the transfer cost are illustrated. Further, the build-up of the tariff structure and its base elements are discussed. The costs are divided on different categories of costumers and shows the cost for each customer. The new regulations should apply simultaneously to all networks, independent of the voltage level. The transit cost should be based on a number of basic elements: capital cost, operation and maintenance, losses, measuring and administration. Capital cost and operation and maintenance should be charged as power fees, the loss cost as an energy fee and the measuring and administration cost as a fixed fee. The customer bill should be split into two parts, one for the transit cost and one for the energy usage. 15 refs., 37 tabs., 6 figs

  16. Predicting Click-Through Rates of New Advertisements Based on the Bayesian Network

    Directory of Open Access Journals (Sweden)

    Zhipeng Fang

    2014-01-01

    Full Text Available Most classical search engines choose and rank advertisements (ads based on their click-through rates (CTRs. To predict an ad’s CTR, historical click information is frequently concerned. To accurately predict the CTR of the new ads is challenging and critical for real world applications, since we do not have plentiful historical data about these ads. Adopting Bayesian network (BN as the effective framework for representing and inferring dependencies and uncertainties among variables, in this paper, we establish a BN-based model to predict the CTRs of new ads. First, we built a Bayesian network of the keywords that are used to describe the ads in a certain domain, called keyword BN and abbreviated as KBN. Second, we proposed an algorithm for approximate inferences of the KBN to find similar keywords with those that describe the new ads. Finally based on the similar keywords, we obtain the similar ads and then calculate the CTR of the new ad by using the CTRs of the ads that are similar with the new ad. Experimental results show the efficiency and accuracy of our method.

  17. An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

    Science.gov (United States)

    Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

    2015-06-26

    Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

  18. Resource allocation via sum-rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    In this paper, we consider maximizing the sum rate in the uplink of a multi-cell orthogonal frequency-division multiple access network. The problem has a non-convex combinatorial structure and is known to be NP-hard. Because of the inherent complexity of implementing the optimal solution, firstly, we derive an upper bound (UB) and a lower bound (LB) to the optimal average network throughput. Moreover, we investigate the performance of a near-optimal single cell resource allocation scheme in the presence of inter-cell interference, which leads to another easily computable LB. We then develop a centralized sub-optimal scheme that is composed of a geometric programming-based power control phase in conjunction with an iterative subcarrier allocation phase. Although the scheme is computationally complex, it provides an effective benchmark for low complexity schemes even without the power control phase. Finally, we propose less complex centralized and distributed schemes that are well suited for practical scenarios. The computational complexity of all schemes is analyzed, and the performance is compared through simulations. Simulation results demonstrate that the proposed low complexity schemes can achieve comparable performance with that of the centralized sub-optimal scheme in various scenarios. Moreover, comparisons with the UB and LB provide insight on the performance gap between the proposed schemes and the optimal solution. Copyright © 2011 John Wiley & Sons, Ltd.

  19. Silver/carbon nanotube hybrids: A novel conductive network for high-rate lithium ion batteries

    International Nuclear Information System (INIS)

    Zhou, Fangdong; Qiu, Kehui; Peng, Gongchang; Xia, Li

    2015-01-01

    LiNi 1/3 Co 1/3 Mn 1/3 O 2 /Ag composite cathodes are synthesized by a thermal decomposition method and multi-walled carbon nanotubes are uniformly introduced into the composites through ball mixing. A composite electrically conductive network consisting of CNTs and Ag is obtained to improve the conductivity of LiNi 1/3 Co 1/3 Mn 1/3 O 2 material. By comparing with the pure LiNi 1/3 Co 1/3 Mn 1/3 O 2 and cathode modified by CNTs or Ag, the as-obtained LiNi 1/3 Co 1/3 Mn 1/3 O 2 –CNT/Ag electrode exhibits the best rate capability (120.6 mAh/g at 5C) and cycle performance (134.2 mAh/g at 1C with a capacity retention of 94.4% over 100 cycles). With the construction of 3D spatial conductive network, the novel hybrid CNT/Ag demonstrates itself a promising strategy to improve Li storage performance for lithium ion batteries

  20. An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sandeep Pirbhulal

    2015-06-01

    Full Text Available Body Sensor Network (BSN is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG, Photoplethysmography (PPG, Electrocardiogram (ECG, etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA, Data Encryption Standard (DES and Rivest Shamir Adleman (RSA. Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

  1. An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

    Science.gov (United States)

    Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

    2015-01-01

    Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption. PMID:26131666

  2. Radiation dose rate map interpolation in nuclear plants using neural networks and virtual reality techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mol, Antonio Carlos A., E-mail: mol@ien.gov.br [Comissao Nacional de Energia Nuclear, Instituto de Engenharia Nuclear Rua Helio de Almeida, 75, Ilha do Fundao, P.O. Box 68550, 21941-906 Rio de Janeiro, RJ (Brazil); Instituto Nacional de Ciencia e Tecnologia de Reatores Nucleares Inovadores/CNPq (Brazil); Pereira, Claudio Marcio N.A., E-mail: cmnap@ien.gov.br [Comissao Nacional de Energia Nuclear, Instituto de Engenharia Nuclear Rua Helio de Almeida, 75, Ilha do Fundao, P.O. Box 68550, 21941-906 Rio de Janeiro, RJ (Brazil); Instituto Nacional de Ciencia e Tecnologia de Reatores Nucleares Inovadores/CNPq (Brazil); Freitas, Victor Goncalves G. [Universidade Federal do Rio de Janeiro, Programa de Engenharia Nuclear, Rio de Janeiro, RJ (Brazil); Jorge, Carlos Alexandre F., E-mail: calexandre@ien.gov.br [Comissao Nacional de Energia Nuclear, Instituto de Engenharia Nuclear Rua Helio de Almeida, 75, Ilha do Fundao, P.O. Box 68550, 21941-906 Rio de Janeiro, RJ (Brazil)

    2011-02-15

    This paper reports the most recent development results of a simulation tool for assessment of radiation dose exposition by nuclear plant's personnel, using artificial intelligence and virtual reality technologies. The main purpose of this tool is to support training of nuclear plants' personnel, to optimize working tasks for minimisation of received dose. A finer grid of measurement points was considered within the nuclear plant's room, for different power operating conditions. Further, an intelligent system was developed, based on neural networks, to interpolate dose rate values among measured points. The intelligent dose prediction system is thus able to improve the simulation of dose received by personnel. This work describes the improvements implemented in this simulation tool.

  3. Radiation dose rate map interpolation in nuclear plants using neural networks and virtual reality techniques

    International Nuclear Information System (INIS)

    Mol, Antonio Carlos A.; Pereira, Claudio Marcio N.A.; Freitas, Victor Goncalves G.; Jorge, Carlos Alexandre F.

    2011-01-01

    This paper reports the most recent development results of a simulation tool for assessment of radiation dose exposition by nuclear plant's personnel, using artificial intelligence and virtual reality technologies. The main purpose of this tool is to support training of nuclear plants' personnel, to optimize working tasks for minimisation of received dose. A finer grid of measurement points was considered within the nuclear plant's room, for different power operating conditions. Further, an intelligent system was developed, based on neural networks, to interpolate dose rate values among measured points. The intelligent dose prediction system is thus able to improve the simulation of dose received by personnel. This work describes the improvements implemented in this simulation tool.

  4. Cooperative Spatial Reuse with Transmit Beamforming in Multi-rate Wireless Networks

    DEFF Research Database (Denmark)

    Lu, Chenguang; Fitzek, Frank; Eggers, Patrick Claus F.

    2009-01-01

    We present a cooperative spatial reuse (CSR) scheme as a cooperative extension of the current TDMA-based MAC to enable spatial reuse in multi-rate wireless networks. We model spatial reuse as a cooperation problem on utilizing the time slots obtained from the TDMA-based MAC. In CSR, there are two...... operation modes. One is TDMA mode while the other is spatial reuse mode in which links transmit simultaneously. Links contribute their own time slots to form a cooperative group to do spatial reuse. Each link joins the group only if it can benefit in capacity or energy efficiency. Otherwise, the link...... will leave spatial reuse mode and switch back to TDMA. In this work, we focus on the transmit beamforming techniques to enable CSR by interference cancellation on MISO (Multiple Input Single Output) links. We compare the CSR scheme using zero-forcing (ZF) transmit beamforming, namely ZF-CSR, to the TDMA...

  5. Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

    Science.gov (United States)

    Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

    2017-09-01

    The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Truth in Reporting: How Data Capture Methods Obfuscate Actual Surgical Site Infection Rates within a Health Care Network System.

    Science.gov (United States)

    Bordeianou, Liliana; Cauley, Christy E; Antonelli, Donna; Bird, Sarah; Rattner, David; Hutter, Matthew; Mahmood, Sadiqa; Schnipper, Deborah; Rubin, Marc; Bleday, Ronald; Kenney, Pardon; Berger, David

    2017-01-01

    Two systems measure surgical site infection rates following colorectal surgeries: the American College of Surgeons National Surgical Quality Improvement Program and the Centers for Disease Control and Prevention National Healthcare Safety Network. The Centers for Medicare & Medicaid Services pay-for-performance initiatives use National Healthcare Safety Network data for hospital comparisons. This study aimed to compare database concordance. This is a multi-institution cohort study of systemwide Colorectal Surgery Collaborative. The National Surgical Quality Improvement Program requires rigorous, standardized data capture techniques; National Healthcare Safety Network allows 5 data capture techniques. Standardized surgical site infection rates were compared between databases. The Cohen κ-coefficient was calculated. This study was conducted at Boston-area hospitals. National Healthcare Safety Network or National Surgical Quality Improvement Program patients undergoing colorectal surgery were included. Standardized surgical site infection rates were the primary outcomes of interest. Thirty-day surgical site infection rates of 3547 (National Surgical Quality Improvement Program) vs 5179 (National Healthcare Safety Network) colorectal procedures (2012-2014). Discrepancies appeared: National Surgical Quality Improvement Program database of hospital 1 (N = 1480 patients) routinely found surgical site infection rates of approximately 10%, routinely deemed rate "exemplary" or "as expected" (100%). National Healthcare Safety Network data from the same hospital and time period (N = 1881) revealed a similar overall surgical site infection rate (10%), but standardized rates were deemed "worse than national average" 80% of the time. Overall, hospitals using less rigorous capture methods had improved surgical site infection rates for National Healthcare Safety Network compared with standardized National Surgical Quality Improvement Program reports. The correlation coefficient

  7. An Approach to Active Queue Management in Computer Network

    OpenAIRE

    Asimkiran Dandapat

    2016-01-01

    Active queue management is a key technique for reducing the packet drop rate in the internet. This packet dropping mechanism is used in a router to minimize congestion when the packets are dropped before queue gets full. In this paper a new framework of Active queue management namely MYRED is proposed. The goal of this new scheme is to improve the performance of AQM by keeping router queue length optimized. In RED packets are marked or dropped with a statistical probability before packet buff...

  8. Natural lecithin promotes neural network complexity and activity

    Science.gov (United States)

    Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

    2016-01-01

    Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called “essential” fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications. PMID:27228907

  9. Natural lecithin promotes neural network complexity and activity.

    Science.gov (United States)

    Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

    2016-05-27

    Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called "essential" fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.

  10. Nonreciprocal signal routing in an active quantum network

    Science.gov (United States)

    Metelmann, A.; Türeci, H. E.

    2018-04-01

    As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. Here, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

  11. How heterogeneous susceptibility and recovery rates affect the spread of epidemics on networks

    Directory of Open Access Journals (Sweden)

    Wei Gou

    2017-08-01

    Full Text Available In this paper, an extended heterogeneous SIR model is proposed, which generalizes the heterogeneous mean-field theory. Different from the traditional heterogeneous mean-field model only taking into account the heterogeneity of degree, our model considers not only the heterogeneity of degree but also the heterogeneity of susceptibility and recovery rates. Then, we analytically study the basic reproductive number and the final epidemic size. Combining with numerical simulations, it is found that the basic reproductive number depends on the mean of distributions of susceptibility and disease course when both of them are independent. If the mean of these two distributions is identical, increasing the variance of susceptibility may block the spread of epidemics, while the corresponding increase in the variance of disease course has little effect on the final epidemic size. It is also shown that positive correlations between individual susceptibility, course of disease and the square of degree make the population more vulnerable to epidemic and avail to the epidemic prevalence, whereas the negative correlations make the population less vulnerable and impede the epidemic prevalence. Keywords: Networks, Heterogeneity, Susceptibility, Recovery rates, Correlation, The basic reproductive number, The final epidemic size

  12. Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile

    Directory of Open Access Journals (Sweden)

    Naftali Goldshleger

    2012-01-01

    Full Text Available We explored the effect of raindrop energy on both water infiltration into soil and the soil's NIR-SWIR spectral reflectance (1200–2400 nm. Seven soils with different physical and morphological properties from Israel and the US were subjected to an artificial rainstorm. The spectral properties of the crust formed on the soil surface were analyzed using an artificial neural network (ANN. Results were compared to a study with the same population in which partial least-squares (PLS regression was applied. It was concluded that both models (PLS regression and ANN are generic as they are based on properties that correlate with the physical crust, such as clay content, water content and organic matter. Nonetheless, better results for the connection between infiltration rate and spectral properties were achieved with the non-linear ANN technique in terms of statistical values (RMSE of 17.3% for PLS regression and 10% for ANN. Furthermore, although both models were run at the selected wavelengths and their accuracy was assessed with an independent external group of samples, no pre-processing procedure was applied to the reflectance data when using ANN. As the relationship between infiltration rate and soil reflectance is not linear, ANN methods have the advantage for examining this relationship when many soils are being analyzed.

  13. Distortion-Rate Bounds for Distributed Estimation Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Nihar Jindal

    2008-03-01

    Full Text Available We deal with centralized and distributed rate-constrained estimation of random signal vectors performed using a network of wireless sensors (encoders communicating with a fusion center (decoder. For this context, we determine lower and upper bounds on the corresponding distortion-rate (D-R function. The nonachievable lower bound is obtained by considering centralized estimation with a single-sensor which has all observation data available, and by determining the associated D-R function in closed-form. Interestingly, this D-R function can be achieved using an estimate first compress afterwards (EC approach, where the sensor (i forms the minimum mean-square error (MMSE estimate for the signal of interest; and (ii optimally (in the MSE sense compresses and transmits it to the FC that reconstructs it. We further derive a novel alternating scheme to numerically determine an achievable upper bound of the D-R function for general distributed estimation using multiple sensors. The proposed algorithm tackles an analytically intractable minimization problem, while it accounts for sensor data correlations. The obtained upper bound is tighter than the one determined by having each sensor performing MSE optimal encoding independently of the others. Numerical examples indicate that the algorithm performs well and yields D-R upper bounds which are relatively tight with respect to analytical alternatives obtained without taking into account the cross-correlations among sensor data.

  14. Physical and Radiological Characterisation of Measuring Sites Within The Croatian Gamma Dose Rate Early Warning Network

    International Nuclear Information System (INIS)

    Cindro, M.; Stepisnik, M.; Pinezic, D.; Sinka, D.; Skanata, D.

    2016-01-01

    The work described in this paper was done within the EU funded project 'Upgrading the systems for the on- and off-line monitoring of radioactivity in the environment in Croatia in regular and emergency situations'. The existing system of early warning in case of nuclear accident in Croatia (SPUNN), managed by the State Office for Radiological and Nuclear Safety, includes 33 stations for measuring ambient gamma dose rate (GDR). The aim of the project was to determine appropriate correction factors that will allow the results from this network to be used not only for timely warning in case of nuclear accident but also in routine environmental monitoring to determine the background radiation. Additionally, in the case of fresh deposition due to radioactive contamination, the corrected values are better suited to be used as an input for support systems for decision making in the case of emergency (such as RODOS), as well as for international data exchange (EURDEP) or automatic interpolation and mapping of radiological data (INTAMAP). The response of the individual probes to natural or accidental radiation mostly depends on the geometry or topography, surrounding buildings, vegetation (trees) and the type of soil beneath the detector. In the case of measuring the dose rate, objects such as buildings act as a shield against gamma radiation and limit the field of vision of the detector. If we want to have representative values that can be compared with other measuring sites, it is clear that we need to define standard conditions that each location has to meet. This is true not only for the probes within the same network, but can also be applied more broadly, at the international level, since data exchange mechanisms for GDR data already exist across Europe. The response of each probe is not determined only by the physical features, it is also important to understand the radiological characteristics of the site. Radiological characterization was performed through

  15. Error rate degradation due to switch crosstalk in large modular switched optical networks

    DEFF Research Database (Denmark)

    Saxtoft, Christian; Chidgey, P.

    1993-01-01

    A theoretical model of an optical network incorporating wavelength selective elements, amplifiers, couplers and switches is presented. The model is used to evaluate a large modular switch optical network that provides the capability of adapting easily to changes in network traffic requirements. T....... The network dimensions are shown to be limited by the optical crosstalk in the switch matrices and by the polarization dependent loss in the optical components...

  16. Both novelty and expertise increase action observation network activity

    Directory of Open Access Journals (Sweden)

    Sook-Lei eLiew

    2013-09-01

    Full Text Available Our experiences with others affect how we perceive their actions. In particular, activity in bilateral premotor and parietal cortices during action observation, collectively known as the action observation network (AON, is modulated by one’s expertise with the observed actions or individuals. However, conflicting reports suggest that AON activity is greatest both for familiar and unfamiliar actions. The current study examines the effects of different types and amounts of experience (e.g., visual, interpersonal, personal on AON activation. fMRI was used to scan 16 healthy participants without prior experience with individuals with amputations (novices, 11 experienced occupational therapists (OTs who had varying amounts of experience with individuals with amputations, and one individual born with below-elbow residual limbs (participant CJ, as they viewed video clips of goal-matched actions performed by an individual with residual limbs and by an individual with hands. Participants were given increased visual exposure to actions performed by both effectors midway through the scanning procedure. Novices demonstrated a large AON response to the initial viewing of an individual with residual limbs compared to one with hands, but this signal was attenuated after they received visual exposure to both effectors. In contrast, OTs, who had moderate familiarity with residual limbs, demonstrated a lower AON response upon initial viewing—similar to novices after they received visual exposure. At the other extreme, CJ, who has extreme familiarity with residual limbs both visually and motorically, shows a largely increased left-lateralized AON response, exceeding that of novices and experienced OTs, when viewing the residual limb compared to hand actions. These results suggest that a nuanced model of AON engagement is needed to explain how cases of both extreme experience (CJ and extreme novelty (novices can result in the greatest AON activity.

  17. Recent Progress in Some Active Topics on Complex Networks

    International Nuclear Information System (INIS)

    Gu, J; Zhu, Y; Wang, Q A; Guo, L; Jiang, J; Chi, L; Li, W; Cai, X

    2015-01-01

    Complex networks have been extensively studied across many fields, especially in interdisciplinary areas. It has since long been recognized that topological structures and dynamics are important aspects for capturing the essence of complex networks. The recent years have also witnessed the emergence of several new elements which play important roles in network study. By combining the results of different research orientations in our group, we provide here a review of the recent advances in regards to spectral graph theory, opinion dynamics, interdependent networks, graph energy theory and temporal networks. We hope this will be helpful for the newcomers of those fields to discover new intriguing topics. (paper)

  18. Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study.

    Directory of Open Access Journals (Sweden)

    Makii Muthalib

    Full Text Available Neuroimaging studies have shown neuromuscular electrical stimulation (NMES-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC, premotor cortex (PMC, supplementary motor area (SMA, and secondary somatosensory area (S2, as well as regions of the prefrontal cortex (PFC known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI, and with reference to voluntary (VOL wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb and deoxygenated (HHb hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2. However, the level and area of contralateral sensorimotor network (including PFC activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

  19. Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study.

    Science.gov (United States)

    Muthalib, Makii; Re, Rebecca; Zucchelli, Lucia; Perrey, Stephane; Contini, Davide; Caffini, Matteo; Spinelli, Lorenzo; Kerr, Graham; Quaresima, Valentina; Ferrari, Marco; Torricelli, Alessandro

    2015-01-01

    Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

  20. Spatio-temporal specialization of GABAergic septo-hippocampal neurons for rhythmic network activity.

    Science.gov (United States)

    Unal, Gunes; Crump, Michael G; Viney, Tim J; Éltes, Tímea; Katona, Linda; Klausberger, Thomas; Somogyi, Peter

    2018-03-03

    Medial septal GABAergic neurons of the basal forebrain innervate the hippocampus and related cortical areas, contributing to the coordination of network activity, such as theta oscillations and sharp wave-ripple events, via a preferential innervation of GABAergic interneurons. Individual medial septal neurons display diverse activity patterns, which may be related to their termination in different cortical areas and/or to the different types of innervated interneurons. To test these hypotheses, we extracellularly recorded and juxtacellularly labeled single medial septal neurons in anesthetized rats in vivo during hippocampal theta and ripple oscillations, traced their axons to distant cortical target areas, and analyzed their postsynaptic interneurons. Medial septal GABAergic neurons exhibiting different hippocampal theta phase preferences and/or sharp wave-ripple related activity terminated in restricted hippocampal regions, and selectively targeted a limited number of interneuron types, as established on the basis of molecular markers. We demonstrate the preferential innervation of bistratified cells in CA1 and of basket cells in CA3 by individual axons. One group of septal neurons was suppressed during sharp wave-ripples, maintained their firing rate across theta and non-theta network states and mainly fired along the descending phase of CA1 theta oscillations. In contrast, neurons that were active during sharp wave-ripples increased their firing significantly during "theta" compared to "non-theta" states, with most firing during the ascending phase of theta oscillations. These results demonstrate that specialized septal GABAergic neurons contribute to the coordination of network activity through parallel, target area- and cell type-selective projections to the hippocampus.

  1. Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks.

    Science.gov (United States)

    Navia, Marlon; Campelo, Jose C; Bonastre, Alberto; Ors, Rafael; Capella, Juan V; Serrano, Juan J

    2015-09-18

    Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

  2. Low-complexity full-rate transmission scheme with full diversity for two-path relay networks

    KAUST Repository

    Fareed, Muhammad Mehboob; Yang, Hongchuan; Alouini, Mohamed-Slim

    2015-01-01

    Existing full-rate transmission schemes for two-path relay networks typically cannot achieve full diversity while demanding high decoding complexity. In this paper, we present a novel low-complexity full-rate transmission scheme for two-path relay networks to harvest maximum achievable diversity. The proposed scheme adopts block transmission with small block size of four symbols, which greatly reduces the decoding complexity at the receiver. Through the performance analysis of the resulting two-path relay network in terms of the symbol error rate (SER) and diversity order, we show the proposed scheme can achieve full diversity order of four and mimic a 2 \\times 2 multiple-input multiple-output system. Simulations results are provided to validate the mathematical formulation. © 1967-2012 IEEE.

  3. Low-complexity full-rate transmission scheme with full diversity for two-path relay networks

    KAUST Repository

    Fareed, Muhammad Mehboob

    2015-04-01

    Existing full-rate transmission schemes for two-path relay networks typically cannot achieve full diversity while demanding high decoding complexity. In this paper, we present a novel low-complexity full-rate transmission scheme for two-path relay networks to harvest maximum achievable diversity. The proposed scheme adopts block transmission with small block size of four symbols, which greatly reduces the decoding complexity at the receiver. Through the performance analysis of the resulting two-path relay network in terms of the symbol error rate (SER) and diversity order, we show the proposed scheme can achieve full diversity order of four and mimic a 2 \\\\times 2 multiple-input multiple-output system. Simulations results are provided to validate the mathematical formulation. © 1967-2012 IEEE.

  4. Reciprocal Reinforcement Between Wearable Activity Trackers and Social Network Services in Influencing Physical Activity Behaviors.

    Science.gov (United States)

    Chang, Rebecca Cherng-Shiow; Lu, Hsi-Peng; Yang, Peishan; Luarn, Pin

    2016-07-05

    Wearable activity trackers (WATs) are emerging consumer electronic devices designed to support physical activities (PAs), which are based on successful behavior change techniques focusing on goal-setting and frequent behavioral feedbacks. Despite their utility, data from both recent academic and market research have indicated high attrition rates of WAT users. Concurrently, evidence shows that social support (SS), delivered/obtained via social network services or sites (SNS), could increase adherence and engagement of PA intervention programs. To date, relatively few studies have looked at how WATs and SS may interact and affect PAs. The purpose of this study was to explore how these two Internet and mobile technologies, WATs and SNS, could work together to foster sustainable PA behavior changes and habits among middle-aged adults (40-60 years old) in Taiwan. We used purposive sampling of Executive MBA Students from National Taiwan University of Science and Technology to participate in our qualitative research. In-depth interviews and focus groups were conducted with a total of 15 participants, including 9 WAT users and 6 nonusers. Analysis of the collected materials was done inductively using the thematic approach with no preset categories. Two authors from different professional backgrounds independently annotated and coded the transcripts, and then discussed and debated until consensus was reached on the final themes. The thematic analysis revealed six themes: (1) WATs provided more awareness than motivation in PA with goal-setting and progress monitoring, (2) SS, delivered/obtained via SNS, increased users' adherence and engagement with WATs and vice versa, (3) a broad spectrum of configurations would be needed to deliver WATs with appropriately integrated SS functions, (4) WAT design, style, and appearance mattered even more than those of smartphones, as they are body-worn devices, (5) the user interfaces of WATs left a great deal to be desired, and (6

  5. Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations

    OpenAIRE

    Harradon, Michael; Druce, Jeff; Ruttenberg, Brian

    2018-01-01

    Deep neural networks are complex and opaque. As they enter application in a variety of important and safety critical domains, users seek methods to explain their output predictions. We develop an approach to explaining deep neural networks by constructing causal models on salient concepts contained in a CNN. We develop methods to extract salient concepts throughout a target network by using autoencoders trained to extract human-understandable representations of network activations. We then bu...

  6. Three-dimensional neural cultures produce networks that mimic native brain activity.

    Science.gov (United States)

    Bourke, Justin L; Quigley, Anita F; Duchi, Serena; O'Connell, Cathal D; Crook, Jeremy M; Wallace, Gordon G; Cook, Mark J; Kapsa, Robert M I

    2018-02-01

    Development of brain function is critically dependent on neuronal networks organized through three dimensions. Culture of central nervous system neurons has traditionally been limited to two dimensions, restricting growth patterns and network formation to a single plane. Here, with the use of multichannel extracellular microelectrode arrays, we demonstrate that neurons cultured in a true three-dimensional environment recapitulate native neuronal network formation and produce functional outcomes more akin to in vivo neuronal network activity. Copyright © 2017 John Wiley & Sons, Ltd.

  7. Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2015-08-01

    Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

  8. State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

    Science.gov (United States)

    Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

    2011-11-16

    The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

  9. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  10. Activity-Driven Influence Maximization in Social Networks

    DEFF Research Database (Denmark)

    Kumar, Rohit; Saleem, Muhammad Aamir; Calders, Toon

    2017-01-01

    -driven approach based on the identification of influence propagation patterns. In the first work, we identify so-called information-channels to model potential pathways for information spread, while the second work exploits how users in a location-based social network check in to locations in order to identify...... influential locations. To make our algorithms scalable, approximate versions based on sketching techniques from the data streams domain have been developed. Experiments show that in this way it is possible to efficiently find good seed sets for influence propagation in social networks.......Interaction networks consist of a static graph with a timestamped list of edges over which interaction took place. Examples of interaction networks are social networks whose users interact with each other through messages or location-based social networks where people interact by checking...

  11. Consumer Activities and Reactions to Social Network Marketing

    OpenAIRE

    Bistra Vassileva

    2017-01-01

    The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM) referral behaviour, and purchase intentions. Consumers are investigated ...

  12. Networking in Sport Management: Ideas and Activities to Enhance Student Engagement and Career Development

    Directory of Open Access Journals (Sweden)

    Alan S. Kornspan

    2013-01-01

    Full Text Available The primary purpose of this paper is to present information regarding the development of networking skills to enhance the career development of sport management students. Specifically, literature is reviewed which supports the importance of networking in the attainment of employment and career advancement in the sport industry. This is followed by an overview of emerging networking activities that allow opportunities for sport management students to expand their network. Sport industry career fairs and career conferences that students can attend are discussed. Additionally, sport industry professional associations that students can become involved with are presented. This is then followed with information related to the development of sport management clubs and various events that can be promoted to enhance the networking process. Specifically, activities provided by university faculty to enhance the educational experience of sport management students are detailed. Finally, a sample schedule of semester activities focused on student engagement and networking activities is provided.

  13. Contagion processes on the static and activity driven coupling networks

    OpenAIRE

    Lei, Yanjun; Jiang, Xin; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

    2015-01-01

    The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and a...

  14. Tourist activated networks: Implications for dynamic bundling and en-route recommendations

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike

    2011-01-01

    This article discusses tourist-activated networks as a concept to inform technological applications supporting dynamic bundling and en route recommendations. Empirical data were collected from travelers who visited a regional destination in the US and then analyzed with respect to its network...... structure. The results indicate that the tourist-activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist-activated network and provide implications for technology design and tourism...

  15. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    OpenAIRE

    Mehrshad Salmasi; Homayoun Mahdavi-Nasab

    2012-01-01

    Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in n...

  16. Avoidant Responses to Interpersonal Provocation Are Associated with Increased Amygdala and Decreased Mentalizing Network Activity

    Science.gov (United States)

    Krämer, Ulrike M.

    2017-01-01

    When intentionally pushed or insulted, one can either flee from the provoker or retaliate. The implementation of such fight-or-flight decisions is a central aspect in the genesis and evolution of aggression episodes, yet it is usually investigated only indirectly or in nonsocial situations. In the present fMRI study, we aimed to distinguish brain regions associated with aggressive and avoidant responses to interpersonal provocation in humans. Participants (thirty-six healthy young women) could either avoid or face a highly (HP) and a lowly (LP) provoking opponent in a competitive reaction time task: the fight-or-escape (FOE) paradigm. Subjects avoided the HP more often, but retaliated when facing her. Moreover, they chose to fight the HP more quickly, and showed increased heart rate (HR) right before confronting her. Orbitofrontal cortex (OFC) and sensorimotor cortex were more active when participants decided to fight, whereas the mentalizing network was engaged when deciding to avoid. Importantly, avoiding the HP relative to the LP was associated with both higher activation in the right basolateral amygdala and lower relative activity in several mentalizing regions [e.g., medial and inferior frontal gyrus (IFG), temporal-parietal junction (TPJ)]. These results suggest that avoidant responses to provocation might result from heightened threat anticipation and are associated with reduced perspective taking. Furthermore, our study helps to reconcile conflicting findings on the role of the mentalizing network, the amygdala, and the OFC in aggression. PMID:28660251

  17. Plasticity of Neuron-Glial Transmission: Equipping Glia for Long-Term Integration of Network Activity

    Directory of Open Access Journals (Sweden)

    Wayne Croft

    2015-01-01

    Full Text Available The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.

  18. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks.

    Science.gov (United States)

    Wang, Yongqiang; Núñez, Felipe; Doyle, Francis J

    2012-07-25

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is increased even under a fixed transmission power. Given that energy consumption in synchronization is determined by the product of synchronization time and transformation power, the new strategy reduces energy consumption in clock synchronization. QualNet experiments confirm the theoretical results.

  19. Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

    Directory of Open Access Journals (Sweden)

    Helmut Schmidt

    2014-11-01

    Full Text Available Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz and low-alpha (6-9 Hz bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic

  20. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    NARCIS (Netherlands)

    Hjorth, J.J.J.; Dawitz, J.; Kroon, T.; da Silva Dias Pires, J.H.; Dassen, V.J.; Berkhout, J.A.; Emperador Melero, J.; Nadadhur, A.G.; Alevra, M.; Toonen, R.F.G.; Heine, V.M.; Mansvelder, H.D.; Meredith, R.M.

    2016-01-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell

  1. A Hierarchical Approach to Real-time Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Tao, Xianping

    2012-01-01

    Real-time activity recognition in body sensor networks is an important and challenging task. In this paper, we propose a real-time, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this model, we rst use a fast and lightweight al...

  2. Real-time Human Activity Recognition using a Body Sensor Network

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Chen, Hanhua

    2010-01-01

    Real-time activity recognition using body sensor networks is an important and challenging task and it has many potential applications. In this paper, we propose a realtime, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this mo...

  3. Distributed state estimation for multi-agent based active distribution networks

    NARCIS (Netherlands)

    Nguyen, H.P.; Kling, W.L.

    2010-01-01

    Along with the large-scale implementation of distributed generators, the current distribution networks have changed gradually from passive to active operation. State estimation plays a vital role to facilitate this transition. In this paper, a suitable state estimation method for the active network

  4. Finding Influential Spreaders from Human Activity beyond Network Location.

    Science.gov (United States)

    Min, Byungjoon; Liljeros, Fredrik; Makse, Hernán A

    2015-01-01

    Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

  5. Finding Influential Spreaders from Human Activity beyond Network Location.

    Directory of Open Access Journals (Sweden)

    Byungjoon Min

    Full Text Available Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

  6. Combined Rate and Power Allocation with Link Scheduling in Wireless Data Packet Relay Networks with Fading Channels

    OpenAIRE

    Subhrakanti Dey; Minyi Huang

    2007-01-01

    We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal ...

  7. Semi-Automatic Rating Method for Neutrophil Alkaline Phosphatase Activity.

    Science.gov (United States)

    Sugano, Kanae; Hashi, Kotomi; Goto, Misaki; Nishi, Kiyotaka; Maeda, Rie; Kono, Keigo; Yamamoto, Mai; Okada, Kazunori; Kaga, Sanae; Miwa, Keiko; Mikami, Taisei; Masauzi, Nobuo

    2017-01-01

    The neutrophil alkaline phosphatase (NAP) score is a valuable test for the diagnosis of myeloproliferative neoplasms, but it has still manually rated. Therefore, we developed a semi-automatic rating method using Photoshop ® and Image-J, called NAP-PS-IJ. Neutrophil alkaline phosphatase staining was conducted with Tomonaga's method to films of peripheral blood taken from three healthy volunteers. At least 30 neutrophils with NAP scores from 0 to 5+ were observed and taken their images. From which the outer part of neutrophil was removed away with Image-J. These were binarized with two different procedures (P1 and P2) using Photoshop ® . NAP-positive area (NAP-PA) and granule (NAP-PGC) were measured and counted with Image-J. The NAP-PA in images binarized with P1 significantly (P < 0.05) differed between images with NAP scores from 0 to 3+ (group 1) and those from 4+ to 5+ (group 2). The original images in group 1 were binarized with P2. NAP-PGC of them significantly (P < 0.05) differed among all four NAP score groups. The mean NAP-PGC with NAP-PS-IJ indicated a good correlation (r = 0.92, P < 0.001) to results by human examiners. The sensitivity and specificity of NAP-PS-IJ were 60% and 92%, which might be considered as a prototypic method for the full-automatic rating NAP score. © 2016 Wiley Periodicals, Inc.

  8. Resonance of about-weekly human heart rate rhythm with solar activity change.

    Science.gov (United States)

    Cornelissen, G; Halberg, F; Wendt, H W; Bingham, C; Sothern, R B; Haus, E; Kleitman, E; Kleitman, N; Revilla, M A; Revilla, M; Breus, T K; Pimenov, K; Grigoriev, A E; Mitish, M D; Yatsyk, G V; Syutkina, E V

    1996-12-01

    In several human adults, certain solar activity rhythms may influence an about 7-day rhythm in heart rate. When no about-weekly feature was found in the rate of change in sunspot area, a measure of solar activity, the double amplitude of a circadian heart rate rhythm, approximated by the fit of a 7-day cosine curve, was lower, as was heart rate corresponds to about-weekly features in solar activity and/or relates to a sunspot cycle.

  9. The self-pleasantness judgment modulates the encoding performance and the Default Mode Network activity

    Directory of Open Access Journals (Sweden)

    Perrone-Bertolotti eMarcela

    2016-03-01

    Full Text Available In this functional magnetic resonance imaging (fMRI study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal thoughts and increase default mode network (DMN activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention but decreased recognition for unpleasantly-judged items (which depend on externally-oriented attention. To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding recruits two key medial posterior DMN regions, the posterior cingulate cortex and precuneus. A region of interest analysis including classic DMN areas, revealed significantly greater involvement of the medial Prefrontal Cortex in pleasant compared to unpleasant judgments, suggesting this region’s involvement in self-referential (i.e., internal processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful and pleasantness was observed for the posterior cingulate cortex, precuneus and inferior frontal gyrus. Overall, our

  10. Beneficial effect of physical activity on linear growth rate of ...

    African Journals Online (AJOL)

    It is not known if nutritional and/or other interventions could improve linear growth in adolescents. The purpose of this study was to assess the role of physical activity in promoting linear growth velocity of black adolescents in a low-income shanty town in South Africa. Two schools in a disadvantaged shanty town participated ...

  11. Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

    Science.gov (United States)

    Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

    2013-08-14

    High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary

  12. Selected aspects of modelling of foreign exchange rates with neural networks

    Directory of Open Access Journals (Sweden)

    Václav Mastný

    2005-01-01

    Full Text Available This paper deals with forecasting of the high-frequency foreign exchange market with neural networks. The objective is to investigate some aspects of modelling with neural networks (impact of topology, size of training set and time horizon of the forecast on the performance of the network. The data used for the purpose of this paper contain 15-minute time series of US dollar against other major currencies, Japanese Yen, British Pound and Euro. The results show, that performance of the network in terms of correct directorial change is negatively influenced by increasing number of hidden neurons and decreasing size of training set. The performance of the network is influenced by sampling frequency.

  13. ASSESSMENT OF RELEASE RATES FOR RADIONUCLIDES IN ACTIVATED CONCRETE.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.M.

    2003-08-23

    The Maine Yankee (MY) nuclear power plant is undergoing the process of decontamination and decommissioning (D&D). Part of the process requires analyses that demonstrate that any radioactivity that remains after D&D will not cause exposure to radioactive contaminants to exceed acceptable limits. This requires knowledge of the distribution of radionuclides in the remaining material and their potential release mechanisms from the material to the contacting groundwater. In this study the concern involves radionuclide contamination in activated concrete in the ICI Sump below the containment building. Figures 1-3 are schematic representations of the ICI Sump. Figure 2 and 3 contain the relevant dimensions needed for the analysis. The key features of Figures 2 and 3 are the 3/8-inch carbon steel liner that isolates the activated concrete from the pit and the concrete wall, which is between 7 feet and 7 feet 2 inches thick. During operations, a small neutron flux from the reactor activated the carbon steel liner and the concrete outside the liner. Current MY plans call for filling the ICI sump with compacted sand.

  14. Atrophy in distinct corticolimbic networks in frontotemporal dementia relates to social impairments measured using the Social Impairment Rating Scale

    Science.gov (United States)

    Bickart, Kevin C; Brickhouse, Michael; Negreira, Alyson; Sapolsky, Daisy

    2015-01-01

    Patients with frontotemporal dementia (FTD) often exhibit prominent, early and progressive impairments in social behaviour. We developed the Social Impairment Rating Scale (SIRS), rated by a clinician after a structured interview, which grades the types and severity of social behavioural symptoms in seven domains. In 20 FTD patients, we used the SIRS to study the anatomic basis of social impairments. In support of hypotheses generated from a prior study of healthy adults, we found that the relative magnitude of brain atrophy in three partially dissociable corticolimbic networks anchored in the amygdala predicted the severity of distinct social impairments measured using the SIRS. Patients with the greatest atrophy in a mesolimbic, reward-related (affiliation) network exhibited the most severe socioemotional detachment, whereas patients with the greatest atrophy in an interoceptive, pain-related (aversion) network exhibited the most severe lack of social apprehension. Patients with the greatest atrophy in a perceptual network exhibited the most severe lack of awareness or understanding of others’ social and emotional behaviour. Our findings underscore observations that FTD is associated with heterogeneous social symptoms that can be understood in a refined manner by measuring impairments in component processes subserved by dissociable neural networks. Furthermore, these findings support the validity of the SIRS as an instrument to measure the social symptoms of patients with FTD. Ultimately, we hope it will be useful as a longitudinal outcome measure in natural history studies and in clinical trials of putative interventions to improve social functioning. PMID:24133285

  15. Evaluation of Techniques to Detect Significant Network Performance Problems using End-to-End Active Network Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Cottrell, R.Les; Logg, Connie; Chhaparia, Mahesh; /SLAC; Grigoriev, Maxim; /Fermilab; Haro, Felipe; /Chile U., Catolica; Nazir, Fawad; /NUST, Rawalpindi; Sandford, Mark

    2006-01-25

    End-to-End fault and performance problems detection in wide area production networks is becoming increasingly hard as the complexity of the paths, the diversity of the performance, and dependency on the network increase. Several monitoring infrastructures are built to monitor different network metrics and collect monitoring information from thousands of hosts around the globe. Typically there are hundreds to thousands of time-series plots of network metrics which need to be looked at to identify network performance problems or anomalous variations in the traffic. Furthermore, most commercial products rely on a comparison with user configured static thresholds and often require access to SNMP-MIB information, to which a typical end-user does not usually have access. In our paper we propose new techniques to detect network performance problems proactively in close to realtime and we do not rely on static thresholds and SNMP-MIB information. We describe and compare the use of several different algorithms that we have implemented to detect persistent network problems using anomalous variations analysis in real end-to-end Internet performance measurements. We also provide methods and/or guidance for how to set the user settable parameters. The measurements are based on active probes running on 40 production network paths with bottlenecks varying from 0.5Mbits/s to 1000Mbit/s. For well behaved data (no missed measurements and no very large outliers) with small seasonal changes most algorithms identify similar events. We compare the algorithms' robustness with respect to false positives and missed events especially when there are large seasonal effects in the data. Our proposed techniques cover a wide variety of network paths and traffic patterns. We also discuss the applicability of the algorithms in terms of their intuitiveness, their speed of execution as implemented, and areas of applicability. Our encouraging results compare and evaluate the accuracy of our

  16. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  17. Active local distribution network management for embedded generation

    Energy Technology Data Exchange (ETDEWEB)

    White, S.

    2005-07-01

    With the newer electric power transmission networks, there is a requirement for power to flow in two different directions and this calls for more intelligent forms of management. To satisfy these demands, GENEVAC has produced a controller that aims to increase the energy that power plants can feed to the distribution networks. The software and hardware have undergone trials at two 33/11 kV substations in England. The hardware was designed to monitor voltage, current and phase angle at various points in the network. The software estimates the value of the voltages at every node in the network. The results showed good correlation between estimated and measured voltages: other findings are reported. Recommendations for further work are made including development of a full commercial system. The study was conducted by Econnect Ltd under contract to the DTI.

  18. Analyses of students' activity in the Internet social networks

    Directory of Open Access Journals (Sweden)

    Ermakov V.A.

    2016-09-01

    Full Text Available the article focuses on the empirical study of students' behavior in social networks; the study was conducted by statistical data analysis methods obtained by interviewing students.

  19. Wireless Powered Relaying Networks Under Imperfect Channel State Information: System Performance and Optimal Policy for Instantaneous Rate

    Directory of Open Access Journals (Sweden)

    D. T. Do

    2017-09-01

    Full Text Available In this investigation, we consider wireless powered relaying systems, where energy is scavenged by a relay via radio frequency (RF signals. We explore hybrid time switching-based and power splitting-based relaying protocol (HTPSR and compare performance of Amplify-and-Forward (AF with Decode-and-Forward (DF scheme under imperfect channel state information (CSI. Most importantly, the instantaneous rate, achievable bit error rate (BER are determined in the closed-form expressions under the impact of imperfect CSI. Through numerical analysis, we evaluate system insights via different parameters such as power splitting (PS and time switching (TS ratio of the considered HTPSR which affect outage performance and BER. It is noted that DF relaying networks outperform AF relaying networks. Besides that, the numerical results are given to prove the optimization problems of PS and TS ratio to obtain optimal instantaneous rate.

  20. A Rate-Adaptive MAC Protocol Based on TCP throughput for Ad Hoc Networks in Fading Channels

    Directory of Open Access Journals (Sweden)

    Shoko Uchida

    2008-10-01

    Full Text Available Wireless technology is becoming a leading option for future Internet access. Transmission Control Protocol (TCP is one of the protocols designed on the basis of the transmission characteristics in wired networks. It is known that the TCP performance deteriorates drastically under a wireless communication environment. On the other hand, many wireless networking standards such as IEEE 802.11a, 802.11b, and 802.11g have multirate capability. Therefore, adaptive rate control methods have been proposed for ad hoc networks. However, almost methods require the modification of the request to send (RTS and clear to send (CTS packets. Therefore, the conventional methods are not compatible with the standardized system. In this paper, we propose adaptive rate control mechanisms for ad hoc networks. Our mechanisms are based on the RTS/CTS mechanisms. However, no modifications to the RTS and CTS packets are required in the proposed method. Therefore, our proposed method can attempt to satisfy the conventional IEEE 802.11 standards. Moreover, an adequate transmission rate is selected based on an estimated TCP throughput performance. From simulation results, it is observed that the proposed method can improve the throughput performance without any modification of packet structures.

  1. Physical Activity in Individuals with Severe Mental Illness: Client versus Case Manager Ratings

    Science.gov (United States)

    Bezyak, Jill L.; Chan, Fong; Lee, Eun-Jeong; Catalano, Denise; Chiu, Chung-Yi

    2012-01-01

    The "Physical Activity Scale for Individuals With Physical Disabilities" was examined as a physical activity measure for people with severe mental illness. Case manager ratings were more closely related to body mass index than clients' ratings, challenging the accuracy of self-report physical activity measures for individuals with severe mental…

  2. How does network structure affect partnerships for promoting physical activity? Evidence from Brazil and Colombia.

    Science.gov (United States)

    Parra, Diana C; Dauti, Marsela; Harris, Jenine K; Reyes, Lissette; Malta, Deborah C; Brownson, Ross C; Quintero, Mario A; Pratt, Michael

    2011-11-01

    The objective of this study was to describe the network structure and factors associated with collaboration in two networks that promote physical activity (PA) in Brazil and Colombia. Organizations that focus on studying and promoting PA in Brazil (35) and Colombia (53) were identified using a modified one-step reputational snowball sampling process. Participants completed an on-line survey between December 2008 and March 2009 for the Brazil network, and between April and June 2009 for the Colombia network. Network stochastic modeling was used to investigate the likelihood of reported inter-organizational collaboration. While structural features of networks were significant predictors of collaboration within each network, the coefficients and other network characteristics differed. Brazil's PA network was decentralized with a larger number of shared partnerships. Colombia's PA network was centralized and collaboration was influenced by perceived importance of peer organizations. On average, organizations in the PA network of Colombia reported facing more barriers (1.5 vs. 2.5 barriers) for collaboration. Future studies should focus on how these different network structures affect the implementation and uptake of evidence-based PA interventions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Nadia Adnan Shiltagh

    2015-11-01

    Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC. The Modify Spike Neural Network controller (MSNC can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC algorithm shows that the (MSNTLP with EWBPRC is more efficient than (FTLP with EWBPRC algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC and EWBPRC with fixed traffic load parameter (µ shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2 in a computer having the following properties: windows 7 (64-bit, core i7, RAM 8GB, hard 1TB.

  4. Experimental Demonstration of Mixed Formats and Bit Rates Signal Allocation for Spectrum-flexible Optical Networking

    DEFF Research Database (Denmark)

    Borkowski, Robert; Karinou, Fotini; Angelou, Marianna

    2012-01-01

    We report on an extensive experimental study for adaptive allocation of 16-QAM and QPSK signals inside spectrum flexible heterogeneous superchannel. Physical-layer performance parameters are extracted for use in resource allocation mechanisms of future flexible networks....

  5. Failure Rate Prediction of Active Component Using PM Basis Database

    International Nuclear Information System (INIS)

    Kim, J. S.; Kim, H. W.; Park, J. S.; Jung, S. G.

    2011-01-01

    The safety security and efficient management of NPPs (Nuclear Power Plants) have been increased after the accident of TEPCO's Fukushima nuclear power stations. The needs for the safety and efficiency are becoming more important because about 90 percent of the NPPs all over the world are more than 20 operation years old. The preventive maintenance criteria need to be flexible, considering long-term development of the equipment performance and preventive maintenance. The PMBD (Preventive Maintenance Basis Database) program was widely used for optimization of the preventive maintenance criteria. PMBD program contains all kinds of failure mechanisms for each equipment that may occur in the power plant based on RCM(Reliability-Centered Maintenance) and numerically calculate the variation of reliability and failure rate based on PM interval changes. In this study, propriety evaluation of preventive maintenance task, cycle, technical basis for cost effective preventive maintenance strategy and an appropriate evaluation were suggested by the case application of PMBD for major components in the NPPs

  6. Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

    Science.gov (United States)

    Mendenhall, Jeffrey; Meiler, Jens

    2016-02-01

    Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

  7. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  8. Simulating ensembles of nonlinear continuous time dynamical systems via active ultra wideband wireless network

    Energy Technology Data Exchange (ETDEWEB)

    Dmitriev, Alexander S.; Yemelyanov, Ruslan Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation); Gerasimov, Mark Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Itskov, Vadim V. [Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation)

    2016-06-08

    The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

  9. Active patterning and asymmetric transport in a model actomyosin network

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

    2013-12-21

    Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

  10. Intrinsic network activity in tinnitus investigated using functional MRI

    Science.gov (United States)

    Leaver, Amber M.; Turesky, Ted K.; Seydell-Greenwald, Anna; Morgan, Susan; Kim, Hung J.; Rauschecker, Josef P.

    2016-01-01

    Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non-auditory brain structures, making network-level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, we used two resting-state functional connectivity (RSFC) approaches to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus-related reductions in RSFC between specific brain regions and resting-state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory-sensory regions like inferior colliculus and medial Heschl’s gyrus, as well as classically non-auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal and orbitofrontal cortex. Notably, patients’ reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory-sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory-sensory and fronto-striatal circuits in tinnitus pathophysiology. PMID:27091485

  11. The association between network social capital and self-rated health: pouring old wine in new bottles?

    Science.gov (United States)

    Verhaeghe, Pieter-Paul; Pattyn, Elise; Bracke, Piet; Verhaeghe, Mieke; Van De Putte, Bart

    2012-03-01

    This study examines whether there is an association between network social capital and self-rated health after controlling for social support. Moreover, we distinguish between network social capital that emerges from strong ties and weak ties. We used a cross-sectional representative sample of 815 adults from the Belgian population. Social capital is measured with the position generator and perceived social support with the MOS Social Support-scale. Results suggest that network social capital is associated with self-rated health after adjustment for social support. Because different social classes have access to different sets of resources, resources of friends and family from the intermediate and higher service classes are beneficial for self-rated health, whereas resources of friends and family from the working class appear to be rather detrimental for self-rated health. From a health-promoting perspective, these findings indicate that policy makers should deal with the root causes of socioeconomic disadvantages in society. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. The association between social networks and self-rated risk of HIV infection among secondary school students in Moshi Municipality, Tanzania

    DEFF Research Database (Denmark)

    Lyimo, Elizabeth; Todd, Jim; Richey, Lisa Ann

    2013-01-01

    This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15–24 years in 5 secondary schools...... participation in bonding and bridging social networks and self-rated HIV risk behavior. More participants participated in bonding networks (72%) than in bridging networks (29%). Participation in bridging networks was greater among females (25%) than males (12%, p 

  13. Hierarchical brain networks active in approach and avoidance goal pursuit.

    Science.gov (United States)

    Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

    2013-01-01

    Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  14. Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

    International Nuclear Information System (INIS)

    Zhang Guiqing; Yang Qiuying; Chen Tianlun

    2008-01-01

    Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities

  15. Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

    Science.gov (United States)

    Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

    2016-02-01

    Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.

  16. Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

    International Nuclear Information System (INIS)

    Wei Duqu; Luo Xiaoshu; Zou Yanli

    2008-01-01

    We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

  17. Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

    Science.gov (United States)

    Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

    2016-05-01

    Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

    Science.gov (United States)

    Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

    2015-01-01

    Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108

  19. Combined effect of chemical and electrical synapses in Hindmarsh-Rose neural networks on synchronization and the rate of information.

    Science.gov (United States)

    Baptista, M S; Moukam Kakmeni, F M; Grebogi, C

    2010-09-01

    In this work we studied the combined action of chemical and electrical synapses in small networks of Hindmarsh-Rose (HR) neurons on the synchronous behavior and on the rate of information produced (per time unit) by the networks. We show that if the chemical synapse is excitatory, the larger the chemical synapse strength used the smaller the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find desynchronous behavior. Otherwise, if the chemical synapse is inhibitory, the larger the chemical synapse strength used the larger the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find synchronous behaviors. Finally, we show how to calculate semianalytically an upper bound for the rate of information produced per time unit (Kolmogorov-Sinai entropy) in larger networks. As an application, we show that this upper bound is linearly proportional to the number of neurons in a network whose neurons are highly connected.

  20. Fast neutron spectra determination by threshold activation detectors using neural networks

    International Nuclear Information System (INIS)

    Kardan, M.R.; Koohi-Fayegh, R.; Setayeshi, S.; Ghiassi-Nejad, M.

    2004-01-01

    Neural network method was used for fast neutron spectra unfolding in spectrometry by threshold activation detectors. The input layer of the neural networks consisted of 11 neurons for the specific activities of neutron-induced nuclear reaction products, while the output layers were fast neutron spectra which had been subdivided into 6, 8, 10, 12, 15 and 20 energy bins. Neural network training was performed by 437 fast neutron spectra and corresponding threshold activation detector readings. The trained neural network have been applied for unfolding 50 spectra, which were not in training sets and the results were compared with real spectra and unfolded spectra by SANDII. The best results belong to 10 energy bin spectra. The neural network was also trained by detector readings with 5% uncertainty and the response of the trained neural network to detector readings with 5%, 10%, 15%, 20%, 25% and 50% uncertainty was compared with real spectra. Neural network algorithm, in comparison with other unfolding methods, is very fast and needless to detector response matrix and any prior information about spectra and also the outputs have low sensitivity to uncertainty in the activity measurements. The results show that the neural network algorithm is useful when a fast response is required with reasonable accuracy

  1. Distributed routing algorithms to manage power flow in agent-based active distribution network

    NARCIS (Netherlands)

    Nguyen, H.P.; Kling, W.L.; Georgiadis, G.; Papatriantafilou, M.; Anh-Tuan, L.; Bertling, L.

    2010-01-01

    The current transition from passive to active electric distribution networks comes with problems and challenges on bi-directional power flow in the network and the uncertainty in the forecast of power generation from grid-connected renewable and distributed energy sources. The power flow management

  2. Method and Apparatus for Predicting Unsteady Pressure and Flow Rate Distribution in a Fluid Network

    Science.gov (United States)

    Majumdar, Alok K. (Inventor)

    2009-01-01

    A method and apparatus for analyzing steady state and transient flow in a complex fluid network, modeling phase changes, compressibility, mixture thermodynamics, external body forces such as gravity and centrifugal force and conjugate heat transfer. In some embodiments, a graphical user interface provides for the interactive development of a fluid network simulation having nodes and branches. In some embodiments, mass, energy, and specific conservation equations are solved at the nodes, and momentum conservation equations are solved in the branches. In some embodiments, contained herein are data objects for computing thermodynamic and thermophysical properties for fluids. In some embodiments, the systems of equations describing the fluid network are solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution methods.

  3. Dynamical networks: Finding, measuring, and tracking neural population activity using network science

    Directory of Open Access Journals (Sweden)

    Mark D. Humphries

    2017-12-01

    Full Text Available Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

  4. Noise influence on spike activation in a Hindmarsh–Rose small-world neural network

    International Nuclear Information System (INIS)

    Zhe, Sun; Micheletto, Ruggero

    2016-01-01

    We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh−Rose (H−R) neural networks. (paper)

  5. Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

    Science.gov (United States)

    Zhe, Sun; Micheletto, Ruggero

    2016-07-01

    We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

  6. Perceived influence and college students' diet and physical activity behaviors: an examination of ego-centric social networks.

    Science.gov (United States)

    Harmon, Brook E; Forthofer, Melinda; Bantum, Erin O; Nigg, Claudio R

    2016-06-06

    Obesity is partially a social phenomenon, with college students particularly vulnerable to changes in social networks and obesity-related behaviors. Currently, little is known about the structure of social networks among college students and their potential influence on diet and physical activity behaviors. The purpose of the study was to examine social influences impacting college students' diet and physical activity behaviors, including sources of influence, comparisons between sources' and students' behaviors, and associations with meeting diet and physical activity recommendations. Data was collected from 40 students attending college in Hawaii. Participants completed diet and physical activity questionnaires and a name generator. Participants rated nominees' influence on their diet and physical activity behaviors as well as compared nominees' behaviors to their own. Descriptive statistics were used to look at perceptions of influence across network groups. Logistic regression models were used to examine associations between network variables and odds of meeting recommendations. A total of 325 nominations were made and included: family (n = 116), college friends (n = 104), high school friends (n = 87), and significant others (n = 18). Nearly half of participants were not from Hawaii. Significant others of non-Hawaii students were perceived to be the most influential (M(SD) = 9(1.07)) and high school friends the least influential (M(SD) = 1.31(.42)) network. Overall, perceived influence was highest for diet compared to physical activity, but varied based on comparisons with nominees' behaviors. Significant others were most often perceived has having similar (44 %) or worse (39 %) eating behaviors than participants, and those with similar eating behaviors were perceived as most influential (M(SD) = 9.25(1.04)). Few associations were seen between network variables and odds of meeting recommendations. Among the groups nominated, high

  7. Perceived influence and college students’ diet and physical activity behaviors: an examination of ego-centric social networks

    Directory of Open Access Journals (Sweden)

    Brook E. Harmon

    2016-06-01

    Full Text Available Abstract Background Obesity is partially a social phenomenon, with college students particularly vulnerable to changes in social networks and obesity-related behaviors. Currently, little is known about the structure of social networks among college students and their potential influence on diet and physical activity behaviors. The purpose of the study was to examine social influences impacting college students’ diet and physical activity behaviors, including sources of influence, comparisons between sources’ and students’ behaviors, and associations with meeting diet and physical activity recommendations. Methods Data was collected from 40 students attending college in Hawaii. Participants completed diet and physical activity questionnaires and a name generator. Participants rated nominees’ influence on their diet and physical activity behaviors as well as compared nominees' behaviors to their own. Descriptive statistics were used to look at perceptions of influence across network groups. Logistic regression models were used to examine associations between network variables and odds of meeting recommendations. Results A total of 325 nominations were made and included: family (n = 116, college friends (n = 104, high school friends (n = 87, and significant others (n = 18. Nearly half of participants were not from Hawaii. Significant others of non-Hawaii students were perceived to be the most influential (M(SD = 9(1.07 and high school friends the least influential (M(SD = 1.31(.42 network. Overall, perceived influence was highest for diet compared to physical activity, but varied based on comparisons with nominees’ behaviors. Significant others were most often perceived has having similar (44 % or worse (39 % eating behaviors than participants, and those with similar eating behaviors were perceived as most influential (M(SD = 9.25(1.04. Few associations were seen between network variables and odds of meeting

  8. Fast demand response in support of the active distribution network

    NARCIS (Netherlands)

    MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

    2013-01-01

    Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

  9. Voltage Estimation in Active Distribution Grids Using Neural Networks

    DEFF Research Database (Denmark)

    Pertl, Michael; Heussen, Kai; Gehrke, Oliver

    2016-01-01

    the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks...

  10. Active Control of Sound based on Diagonal Recurrent Neural Network

    NARCIS (Netherlands)

    Jayawardhana, Bayu; Xie, Lihua; Yuan, Shuqing

    2002-01-01

    Recurrent neural network has been known for its dynamic mapping and better suited for nonlinear dynamical system. Nonlinear controller may be needed in cases where the actuators exhibit the nonlinear characteristics, or in cases when the structure to be controlled exhibits nonlinear behavior. The

  11. Labor Mobility, Social Network Effects, and Innovative Activity

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Kongsted, H.C.; Rønde, Thomas

    . This relationship is stronger if workers join from innovative firms. We also find evidence for positive feedback from workers who leave for an innovative firm, presumably because the worker who left stays in contact with their former colleagues. This implies that the positive feedback (“social network effects...

  12. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    2017-01-01

    In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

  13. Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

    Directory of Open Access Journals (Sweden)

    Taras A Gritsun

    Full Text Available A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP synapses (so, no long-term potentiation, LTP, or depression, LTD, was included. However, elevated pre-phases (burst leaders and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

  14. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis.

    Science.gov (United States)

    Brignardello-Petersen, Romina; Bonner, Ashley; Alexander, Paul E; Siemieniuk, Reed A; Furukawa, Toshi A; Rochwerg, Bram; Hazlewood, Glen S; Alhazzani, Waleed; Mustafa, Reem A; Murad, M Hassan; Puhan, Milo A; Schünemann, Holger J; Guyatt, Gordon H

    2018-01-01

    This article describes conceptual advances of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group guidance to evaluate the certainty of evidence (confidence in evidence, quality of evidence) from network meta-analysis (NMA). Application of the original GRADE guidance, published in 2014, in a number of NMAs has resulted in advances that strengthen its conceptual basis and make the process more efficient. This guidance will be useful for systematic review authors who aim to assess the certainty of all pairwise comparisons from an NMA and who are familiar with the basic concepts of NMA and the traditional GRADE approach for pairwise meta-analysis. Two principles of the original GRADE NMA guidance are that we need to rate the certainty of the evidence for each pairwise comparison within a network separately and that in doing so we need to consider both the direct and indirect evidence. We present, discuss, and illustrate four conceptual advances: (1) consideration of imprecision is not necessary when rating the direct and indirect estimates to inform the rating of NMA estimates, (2) there is no need to rate the indirect evidence when the certainty of the direct evidence is high and the contribution of the direct evidence to the network estimate is at least as great as that of the indirect evidence, (3) we should not trust a statistical test of global incoherence of the network to assess incoherence at the pairwise comparison level, and (4) in the presence of incoherence between direct and indirect evidence, the certainty of the evidence of each estimate can help decide which estimate to believe. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. A microfluidic device for simultaneous measurement of viscosity and flow rate of blood in a complex fluidic network

    OpenAIRE

    Jun Kang, Yang; Yeom, Eunseop; Lee, Sang-Joon

    2013-01-01

    Blood viscosity has been considered as one of important biophysical parameters for effectively monitoring variations in physiological and pathological conditions of circulatory disorders. Standard previous methods make it difficult to evaluate variations of blood viscosity under cardiopulmonary bypass procedures or hemodialysis. In this study, we proposed a unique microfluidic device for simultaneously measuring viscosity and flow rate of whole blood circulating in a complex fluidic network i...

  16. Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

    Science.gov (United States)

    Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

    2016-01-01

    Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

  17. Engineering Online and In-Person Social Networks for Physical Activity: A Randomized Trial.

    Science.gov (United States)

    Rovniak, Liza S; Kong, Lan; Hovell, Melbourne F; Ding, Ding; Sallis, James F; Ray, Chester A; Kraschnewski, Jennifer L; Matthews, Stephen A; Kiser, Elizabeth; Chinchilli, Vernon M; George, Daniel R; Sciamanna, Christopher N

    2016-12-01

    Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. The purpose of this study was to conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively measured outcomes. Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3 % male, 83.4 % overweight/obese) were randomized to one of three groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking as well as prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Participants increased their MVPA by 21.0 min/week, 95 % CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. The trial was registered with the ClinicalTrials.gov (NCT01142804).

  18. Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

    Directory of Open Access Journals (Sweden)

    Shlomo eBerkovsky

    2015-10-01

    Full Text Available Online social networks were originally conceived as means of sharing information and activities with friends, and their success has been one of the primary contributors of the tremendous growth of the Web. Social network activity feeds were devised as a means to aggregate recent actions of friends into a convenient list. But the volume of actions and content generated by social network users is overwhelming, such that keeping users up-to-date with friend activities is an ongoing challenge for social network providers. Personalization has been proposed as a solution to combat social network information overload and help users to identify the nuggets of relevant information in the incoming flood of network activities. In this paper, we propose and thoroughly evaluate a personalized model for predicting the relevance of the activity feed items, which informs the ranking of the feeds and facilitates personalization. Results of a live study show that the proposed feed personalization approach successfully identifies and promotes relevant feed items and boosts the uptake of the feeds. In addition, it increases the contribution of user-generated content to the social network and spurs interaction between users.

  19. Topological probability and connection strength induced activity in complex neural networks

    International Nuclear Information System (INIS)

    Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

    2010-01-01

    Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

  20. The relationship between body temperature, heart rate, breathing rate, and rate of oxygen consumption, in the tegu lizard (Tupinambis merianae) at various levels of activity.

    Science.gov (United States)

    Piercy, Joanna; Rogers, Kip; Reichert, Michelle; Andrade, Denis V; Abe, Augusto S; Tattersall, Glenn J; Milsom, William K

    2015-12-01

    The present study determined whether EEG and/or EMG recordings could be used to reliably define activity states in the Brazilian black and white tegu lizard (Tupinambis merianae) and then examined the interactive effects of temperature and activity states on strategies for matching O2 supply and demand. In a first series of experiments, the rate of oxygen consumption (VO2), breathing frequency (fR), heart rate (fH), and EEG and EMG (neck muscle) activity were measured in different sleep/wake states (sleeping, awake but quiet, alert, or moving). In general, metabolic and cardio-respiratory changes were better indictors of the transition from sleep to wake than were changes in the EEG and EMG. In a second series of experiments, the interactive effects of temperature (17, 27 and 37 °C) and activity states on fR, tidal volume (VT), the fraction of oxygen extracted from the lung per breath (FIO2-FEO2), fH, and the cardiac O2 pulse were quantified to determine the relative roles of each of these variables in accommodating changes in VO2. The increases in oxygen supply to meet temperature- and activity-induced increases in oxygen demand were produced almost exclusively by increases in fH and fR. Regression analysis showed that the effects of temperature and activity state on the relationships between fH, fR and VO2 was to extend a common relationship along a single curve, rather than separate relationships for each metabolic state. For these lizards, the predictive powers of fR and fH were maximized when the effects of changes in temperature, digestive state and activity were pooled. However, the best r(2) values obtained were 0.63 and 0.74 using fR and fH as predictors of metabolic rate, respectively.

  1. Optimum noise figure and data rate for energy efficient wireless sensor network transceivers

    NARCIS (Netherlands)

    Dutta, R.; van der Zee, Ronan A.R.; Bentum, Marinus Jan; Kokkeler, Andre B.J.

    2011-01-01

    Most applications of wireless sensor networks desire an ultra-low power radio to extend the battery life of a sensor node. With power reducation of processors and semiconductor memories due to advanced CMOS scaling, radio transceiver in the bottleneck to extend battery lifetime of sensor nodes.

  2. Sum rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina; Alouini, Mohamed-Slim; Dawy, Zaher

    2012-01-01

    of each cell, while ignoring the significant effect of inter-cell interference. This paper investigates the problem of resource allocation (i.e., subcarriers and powers) in the uplink of a multi-cell OFDMA network. The problem has a non

  3. A relative rate utility based distributed power allocation algorithm for Cognitive Radio Networks

    DEFF Research Database (Denmark)

    Mahmood, Nurul Huda; Øien, G.E.; Lundheim, L.

    2012-01-01

    In an underlay Cognitive Radio Network, multiple secondary users coexist geographically and spectrally with multiple primary users under a constraint on the maximum received interference power at the primary receivers. Given such a setting, one may ask "how to achieve maximum utility benefit...

  4. The Interplay of Networking Activities and Internal Knowledge Actions for Subsidiary Influence within MNCs

    DEFF Research Database (Denmark)

    Tavani, Zhaleh Najafi; Giroud, Axèle; Andersson, Ulf

    2012-01-01

    Building on resource dependency theory; this research investigates the joint impacts of subsidiary knowledge based actions (Reverse Knowledge Transfer (RKT) and knowledge development) and networking activities (internal and external embeddedness) on its strategic influence in the multinational co...

  5. Assembling the puzzle for promoting physical activity in Brazil: a social network analysis.

    Science.gov (United States)

    Brownson, Ross C; Parra, Diana C; Dauti, Marsela; Harris, Jenine K; Hallal, Pedro C; Hoehner, Christine; Malta, Deborah Carvalho; Reis, Rodrigo S; Ramos, Luiz Roberto; Ribeiro, Isabela C; Soares, Jesus; Pratt, Michael

    2010-07-01

    Physical inactivity is a significant public health problem in Brazil that may be addressed by partnerships and networks. In conjunction with Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America), the aim of this study was to conduct a social network analysis of physical activity in Brazil. An online survey was completed by 28 of 35 organizations contacted from December 2008 through March 2009. Network analytic methods examined measures of collaboration, importance, leadership, and attributes of the respondent and organization. Leadership nominations for organizations studied ranged from 0 to 23. Positive predictors of collaboration included: south region, GUIA membership, years working in physical activity, and research, education, and promotion/practice areas of physical activity. The most frequently reported barrier to collaboration was bureaucracy. Social network analysis identified factors that are likely to improve collaboration among organizations in Brazil.

  6. ePAL roadmap for active ageing: a collaborative networks approach to extending professional life

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.; del Cura, A.; Playfoot, J.

    2010-01-01

    Active ageing, through a balanced combination of leisure and social interaction with continued work involvement, is central to meeting older citizens expectations, and maintaining their mental and physical health. Application of the collaborative networks paradigm, and the new generation of

  7. A dynamic compensation method for natural ambient dose rate based on 6 years data from the Dutch radioactivity monitoring network

    International Nuclear Information System (INIS)

    Smetsers, R.C.G.M.; Blaauboer, R.O.

    1997-01-01

    The significant variations in time exhibited by background radiation hinders a sensitive recognition of human-induced factors. A comprehensive study in the Netherlands has examined the influence of the various natural processes on the natural background using six years data from the Dutch nuclear emergency network. Results presented concentrate on temporal variations in ambient dose-equivalent rate, H*(10), and have led to simple expressions to model the ambient dose rate using a limited set of readily available parameters, i.e. air pressure, deposition rate and equilibrium equivalent decay product concentration of 222 Rn, EEDC. Best values and uncertainty ranges of the applied parameters are reported. Remaining variations, e.g. due to variations in the cosmic radiation intensity and the radon soil profile, are shown to be small in the Netherlands, with one exception when the cosmogenic dose rate at sea level was decreased for a period of months due to a global deflection of the earth's magnetic field in the summer of 1991. The resulting compensation method for the natural ambient dose rate enables sensitive detection of anomalies, supporting the surveillance of nuclear installations and the management of nuclear emergency networks. (Author)

  8. Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

    Science.gov (United States)

    Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

    2017-08-01

    Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM

  9. Active node determination for correlated data gathering in wireless sensor networks

    OpenAIRE

    Karasabun, Efe

    2009-01-01

    Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009. Thesis (Master's) -- Bilkent University, 2009. Includes bibliographical references leaves 53-55. In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. However, the sensor nodes that are selected as active should form a co...

  10. Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

    OpenAIRE

    Francisco Javier Ordóñez; Daniel Roggen

    2016-01-01

    Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we pro...

  11. The association between physical activity, cardiorespiratory fitness and self-rated health

    DEFF Research Database (Denmark)

    Eriksen, Louise; Curtis, Tine; Grønbæk, Morten

    2013-01-01

    OBJECTIVE: To investigate the joint association between self-reported physical activity as well as cardiorespiratory fitness and self-rated health among healthy women and men. METHOD: Data from 10,416 participants in The Danish Health Examination Survey 2007-2008 which took part in 13 Danish...... municipalities were analyzed. Leisure time physical activity level and self-rated health were based on self-reported questionnaire data. Optimal self-rated health was defined as "very good" or "good" self-rated health. Cardiorespiratory fitness (mL O2·min(-1)·kg(-1)) was estimated from maximal power output...... in a maximal cycle exercise test. RESULTS: A strong dose-response relation between cardiorespiratory fitness and self-rated health as well as between physical activity level and self-rated health among both women and men was found. Within categories of physical activity, odds ratios for optimal self...

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

    Science.gov (United States)

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

    2014-12-01

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

  13. 77 FR 20890 - Proposed Information Collection (Interest Rate Reduction Refinancing Loan Worksheet) Activity...

    Science.gov (United States)

    2012-04-06

    ... (Interest Rate Reduction Refinancing Loan Worksheet) Activity: Comment Request AGENCY: Veterans Benefits... to determine whether lenders computed the loan amount on interest rate reduction refinancing loans.... Title: Interest Rate Reduction Refinancing Loan Worksheet, VA Form 26-8923. OMB Control Number: 2900...

  14. Investigating solvability and complexity of linear active networks by means of matroids

    DEFF Research Database (Denmark)

    Petersen, Bjørn

    1979-01-01

    The solvability and complexity problems of finear active network are approached from a purely combinatorial point of view, using the concepts of matroid theory. Since the method is purely combinatorial, we take into account the network topology alone. Under this assumption necessary and sufficient...... conditions are given for the unique solvablity of linear active networks. The complexity and the number of dc-eigenfrequencies are also given. The method enables.you to decide if degeneracies are due to the topology alone, or if they are caused by special relations among network parameter values....... If the network parameter values are taken into account, the complexity and number of dc-eigenfrequencies given by the method, are only upper and lower bounds, respectively. The above conditions are fairly easily checked, and the complexity and number of dc-elgenfrequencies are found, using polynomially bounded...

  15. Ripples Make Waves: Binding Structured Activity and Plasticity in Hippocampal Networks

    Directory of Open Access Journals (Sweden)

    Josef H. L. P. Sadowski

    2011-01-01

    Full Text Available Establishing novel episodic memories and stable spatial representations depends on an exquisitely choreographed, multistage process involving the online encoding and offline consolidation of sensory information, a process that is largely dependent on the hippocampus. Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. In recent years, the occurrence of hippocampal sharp wave ripple (SWR oscillations has emerged as a potentially vital network phenomenon mediating the steps between encoding and consolidation, both at a cellular and network level by promoting the rapid replay and reactivation of recent activity patterns. Such events facilitate memory formation by optimising the conditions for synaptic plasticity to occur between contingent neural elements. In this paper, we explore the ways in which SWRs and other network events can bridge the gap between spatiomnemonic processing at cellular/synaptic and network levels in the hippocampus.

  16. Friendship networks and physical activity and sedentary behavior among youth: a systematized review.

    Science.gov (United States)

    Sawka, Keri Jo; McCormack, Gavin R; Nettel-Aguirre, Alberto; Hawe, Penelope; Doyle-Baker, Patricia K

    2013-12-01

    Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today's youth. Friend's health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual's level of physical activity changes to reflect his/her friends' higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend's sedentary behavior and individual sedentary behavior. Friends' physical activity level appears to have a significant influence on individual's physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents.

  17. AmeriFlux Network Data Activities: updates, progress and plans

    Science.gov (United States)

    Yang, B.; Boden, T.; Krassovski, M.; Song, X.

    2013-12-01

    The Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory serves as the long-term data repository for the AmeriFlux network. Datasets currently available include hourly or half-hourly meteorological and flux observations, biological measurement records, and synthesis data products. In this presentation, we provide an update of this network database including a comprehensive review and evaluation of the biological data from about 70 sites, development of a new product for flux uncertainty estimates, and re-formatting of Level-2 standard files. In 2013, we also provided data support to two synthesis studies --- 2012 drought synthesis and FACE synthesis. Issues related to data quality and solutions in compiling datasets for these synthesis studies will be discussed. We will also present our work plans in developing and producing other high-level products, such as derivation of phenology from the available measurements at flux sites.

  18. Social Learning Networks: From Data Analytics to Active Sensing

    Science.gov (United States)

    2017-10-13

    infeasible for a teaching staff to manage itself. This motivated our more specific investigations into identifying factors associated with these...retweeted sources, 232,000 etc Publication Identifier Type: Issue: 8 Date Published: 8/2/16 2:25PM Peer Reviewed: Publication Status: 1...Power of Networks Publication Identifier Type: ISBN Peer Reviewed: Y Publication Status: 1-Published CONFERENCE PAPERS: Date Received: 02-Nov-2016 Date

  19. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  20. Information content of neural networks with self-control and variable activity

    International Nuclear Information System (INIS)

    Bolle, D.; Amari, S.I.; Dominguez Carreta, D.R.C.; Massolo, G.

    2001-01-01

    A self-control mechanism for the dynamics of neural networks with variable activity is discussed using a recursive scheme for the time evolution of the local field. It is based upon the introduction of a self-adapting time-dependent threshold as a function of both the neural and pattern activity in the network. This mechanism leads to an improvement of the information content of the network as well as an increase of the storage capacity and the basins of attraction. Different architectures are considered and the results are compared with numerical simulations

  1. The association between physical activity, cardiorespiratory fitness and self-rated health.

    Science.gov (United States)

    Eriksen, Louise; Curtis, Tine; Grønbæk, Morten; Helge, Jørn W; Tolstrup, Janne S

    2013-12-01

    To investigate the joint association between self-reported physical activity as well as cardiorespiratory fitness and self-rated health among healthy women and men. Data from 10,416 participants in The Danish Health Examination Survey 2007-2008 which took part in 13 Danish municipalities were analyzed. Leisure time physical activity level and self-rated health were based on self-reported questionnaire data. Optimal self-rated health was defined as "very good" or "good" self-rated health. Cardiorespiratory fitness (mL O2·min(-1)·kg(-1)) was estimated from maximal power output in a maximal cycle exercise test. A strong dose-response relation between cardiorespiratory fitness and self-rated health as well as between physical activity level and self-rated health among both women and men was found. Within categories of physical activity, odds ratios for optimal self-rated health increased with increasing categories of cardiorespiratory fitness, and vice versa. Hence, participants who were moderately/vigorously physically active and had a high cardiorespiratory fitness had the highest odds ratio for optimal self-rated health compared with sedentary participants with low cardiorespiratory fitness (odds ratio=12.2, 95% confidence interval: 9.3-16.1). Although reluctant to conclude on causality, this study suggests that an active lifestyle as well as good cardiorespiratory fitness probably increase self-rated health. © 2013.

  2. Activation of specific neuronal networks leads to different seizure onset types.

    Science.gov (United States)

    Shiri, Zahra; Manseau, Frédéric; Lévesque, Maxime; Williams, Sylvain; Avoli, Massimo

    2016-03-01

    Ictal events occurring in temporal lobe epilepsy patients and in experimental models mimicking this neurological disorder can be classified, based on their onset pattern, into low-voltage, fast versus hypersynchronous onset seizures. It has been suggested that the low-voltage, fast onset pattern is mainly contributed by interneuronal (γ-aminobutyric acidergic) signaling, whereas the hypersynchronous onset involves the activation of principal (glutamatergic) cells. Here, we tested this hypothesis using the optogenetic control of parvalbumin-positive or somatostatin-positive interneurons and of calmodulin-dependent, protein kinase-positive, principal cells in the mouse entorhinal cortex in the in vitro 4-aminopyridine model of epileptiform synchronization. We found that during 4-aminopyridine application, both spontaneous seizure-like events and those induced by optogenetic activation of interneurons displayed low-voltage, fast onset patterns that were associated with a higher occurrence of ripples than of fast ripples. In contrast, seizures induced by the optogenetic activation of principal cells had a hypersynchronous onset pattern with fast ripple rates that were higher than those of ripples. Our results firmly establish that under a similar experimental condition (ie, bath application of 4-aminopyridine), the initiation of low-voltage, fast and of hypersynchronous onset seizures in the entorhinal cortex depends on the preponderant involvement of interneuronal and principal cell networks, respectively. © 2016 American Neurological Association.

  3. Engagement, compliance and retention with a gamified online social networking physical activity intervention.

    Science.gov (United States)

    Ryan, Jillian; Edney, Sarah; Maher, Carol

    2017-12-01

    Health behaviour interventions delivered via online social networks are an increasingly popular approach to addressing lifestyle-related health problems. However, research to date consistently reports poor user engagement and retention. The current study examined user engagement, compliance and retention with Active Team-a gamified physical activity intervention delivered by via an online Facebook application. Associations between engagement and participant (n = 51) demographic and team characteristics (sex, age, education and team size) were examined, as well as temporal trends in engagement during the 50-day intervention. Analyses revealed significant associations between both engagement (p = <0.001) and gamification (p = 0.04) with education, with participants in the middle education category appearing to have the highest rates of engagement and use of gamification features. Gender was also related to engagement, with males demonstrating the highest use of the intervention's gamification features (p = 0.004). Although compliance was consistently high for the duration, engagement declined steadily throughout the intervention. Engagement peaked on Wednesdays, coinciding with the delivery of a customised email reminder. Findings reveal individual differences in engagement with Active Team, highlighting a need to tailor interventions to the target audience. Gamification features may enhance engagement amongst males, who are traditionally recognised as a difficult demographic group to engage. Finally, the use of customised, periodic push reminders delivered by email may enhance user engagement by drawing them back to the intervention and helping to sustain intervention behaviours.

  4. On the Development and Application of High Data Rate Architecture (HiDRA) in Future Space Networks

    Science.gov (United States)

    Hylton, Alan; Raible, Daniel; Clark, Gilbert

    2017-01-01

    Historically, space missions have been severely constrained by their ability to downlink the data they have collected. These constraints are a result of relatively low link rates on the spacecraft as well as limitations on the time during which data can be sent. As part of a coherent strategy to address existing limitations and get more data to the ground more quickly, the Space Communications and Navigation (SCaN) program has been developing an architecture for a future solar system Internet. The High Data Rate Architecture (HiDRA) project is designed to fit into such a future SCaN network. HiDRA's goal is to describe a general packet-based networking capability which can be used to provide assets with efficient networking capabilities while simultaneously reducing the capital costs and operational costs of developing and flying future space systems.Along these lines, this paper begins by reviewing various characteristics of modern satellite design as well as relevant characteristics of emerging technologies (such as free-space optical links capable of working at 100+ Gbps). Next, the paper describes HiDRA's design, and how the system is able to both integrate and support the operation of not only today's high-rate systems, but also the high-rate systems likely to be found in the future. This section also explores both existing and future networking technologies, such as Delay Tolerant Networking (DTN) protocol (RFC4838 citeRFC:1, RFC5050citeRFC:2), and explains how HiDRA supports them. Additionally, this section explores how HiDRA is used for scheduling data movement through both proactive and reactive link management. After this, the paper moves on to explore a reference implementation of HiDRA. This implementation is currently being realized based on a Field Programmable Gate Array (FPGA) memory and interface controller that is itself controlled by a local computer running DTN software. Next, this paper explores HiDRA's natural evolution, which includes an

  5. ANALISIS TRANSFER RATE PENAMBAHAN NODE PADA INFRASTRUKTUR MOBILE ADHOC NETWORK (MANET UNTUK FILE SERVER

    Directory of Open Access Journals (Sweden)

    Rudi Kurniawan

    2017-05-01

    Full Text Available Teknologi Wireless Network sudah lama ditemukan dan seiring waktu juga mengalami perkembangan, Namun sifat teknologi ini menggantungkan diri pada infrastruktur jaringan yang ada. Hal ini bias menjadi kelemahan tersendiri saat kondisi infrastruktur jaringan sedang mengalami gangguan, karena setiap komunikasi yang melewati infrastruktur jaringan tersebut tidak akan sampai pada tujuan. Teknologi jaringan Mobile Ad-hoc Network (MANET diciptakan sebagai antisipasi jika infrastruktur jaringan sedang mengalami gangguan. Dengan jaringan MANET sistem komunikasi yang dilakukan tidak membutuhkan infrastruktur jaringan karena tiap node pada jaringan tersebut bersifat mobile. Untuk menguji kemampuan MANET, pada penelitian ini akan menerapkan File Transfer Protocol (FTP sebagai media untuk melakukan komunikasi data file transfer yang diimplementasi pada jaringan MANET. Dari pengujian yang telah dilakukan diperoleh hasil bahwa File Transfer dapat berfungsi dengan baik saat diterapkan pada jaringan MANET.

  6. Assessment of High and Low Rate Protocol-based Attacks on Ethernet Networks

    OpenAIRE

    Mina Malekzadeh; M.A. Beiruti; M.H. Shahrokh Abadi

    2015-01-01

    The Internet and Web have significantly transformed the world’s communication system. The capability of the Internet to instantly access information at anytime from anywhere has brought benefit for a wide variety of areas including business, government, education, institutions, medical, and entertainment services. However, the Internet has also opened up the possibilities for hackers to exploit flaws and limitations in the target networks to attack and break in without gaining physical access...

  7. Sum rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    Resource allocation in orthogonal frequency division multiple access (OFDMA) networks plays an imperative role to guarantee the system performance. However, most of the known resource allocation schemes are focused on maximizing the local throughput of each cell, while ignoring the significant effect of inter-cell interference. This paper investigates the problem of resource allocation (i.e., subcarriers and powers) in the uplink of a multi-cell OFDMA network. The problem has a non-convex combinatorial structure and is known to be NP hard. Firstly, we investigate the upper and lower bounds to the average network throughput due to the inherent complexity of implementing the optimal solution. Later, a centralized sub-optimal resource allocation scheme is developed. We further develop less complex centralized and distributed schemes that are well-suited for practical scenarios. The computational complexity of all schemes has been analyzed and the performance is compared through numerical simulations. Simulation results demonstrate that the distributed scheme achieves comparable performance to the centralized resource allocation scheme in various scenarios. © 2011 IEEE.

  8. Father Absence, Social Networks, and Maternal Ratings of Child Health: Evidence from the 2013 Social Networks and Health Information Survey in Mexico.

    Science.gov (United States)

    Edelblute, Heather B; Altman, Claire E

    2018-04-01

    Objectives To bridge the literature on the effect of father absence, international migration, and social networks on child health, we assess the association between father absence and maternal ratings of child poor health (MCPH). Next we test whether social networks of immediate and extended kin mediate the relationship between fathers' absence and MCPH. Methods Nested logistic regression models predicting MCPH are estimated using the 2013 Social Networks and Health Information Survey, collected in a migrant-sending community in Guanajuato, Mexico. These unique data distinguish among father absence due to migration versus other reasons and between immediate and extended kin ties. Results Descriptive results indicate that 25% of children with migrant fathers are assessed as having poor health, more often than children with present (15.5%) or otherwise absent fathers (17.5%). In the multivariate models, fathers' absence is not predictive of MCPH. However, the presence of extended kin ties for the mother was associated with approximately a 50% reduction in the odds of MCPH. Additionally, mother's poor self-assessed health was associated with increased odds of MCPH while the presence of a co-resident adult lowered the odds of MCPH. In sensitivity analysis among children with migrant fathers, the receipt of paternal remittances lowered the odds of MCPH. Conclusions for Practice Social networks have a direct and positive association with MCPH rather than mediating the father absence-MCPH relationship. The presence of extended kin ties in the local community is salient for more favorable child health and should be considered in public health interventions aimed at improving child health.

  9. Noise in attractor networks in the brain produced by graded firing rate representations

    OpenAIRE

    Webb, Tristan J.; Rolls, Edmund T; Deco, Gustavo; Feng, Jianfeng

    2011-01-01

    Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate\\ud probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as\\ud decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given\\ud mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribut...

  10. A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks.

    Science.gov (United States)

    Ponce, Hiram; Martínez-Villaseñor, María de Lourdes; Miralles-Pechuán, Luis

    2016-07-05

    Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data. In this paper, we presented the artificial hydrocarbon networks (AHN) technique to the human activity recognition community. Our artificial hydrocarbon networks novel approach is suitable for physical activity recognition, noise tolerance of corrupted data sensors and robust in terms of different issues on data sensors. We proved that the AHN classifier is very competitive for physical activity recognition and is very robust in comparison with other well-known machine learning methods.

  11. Bi-directional astrocytic regulation of neuronal activity within a network

    Directory of Open Access Journals (Sweden)

    Susan Yu Gordleeva

    2012-11-01

    Full Text Available The concept of a tripartite synapse holds that astrocytes can affect both the pre- and postsynaptic compartments through the Ca2+-dependent release of gliotransmitters. Because astrocytic Ca2+ transients usually last for a few seconds, we assumed that astrocytic regulation of synaptic transmission may also occur on the scale of seconds. Here, we considered the basic physiological functions of tripartite synapses and investigated astrocytic regulation at the level of neural network activity. The firing dynamics of individual neurons in a spontaneous firing network was described by the Hodgkin-Huxley model. The neurons received excitatory synaptic input driven by the Poisson spike train with variable frequency. The mean field concentration of the released neurotransmitter was used to describe the presynaptic dynamics. The amplitudes of the excitatory postsynaptic currents (PSCs obeyed the gamma distribution law. In our model, astrocytes depressed the presynaptic release and enhanced the postsynaptic currents. As a result, low frequency synaptic input was suppressed while high frequency input was amplified. The analysis of the neuron spiking frequency as an indicator of network activity revealed that tripartite synaptic transmission dramatically changed the local network operation compared to bipartite synapses. Specifically, the astrocytes supported homeostatic regulation of the network activity by increasing or decreasing firing of the neurons. Thus, the astrocyte activation may modulate a transition of neural network into bistable regime of activity with two stable firing levels and spontaneous transitions between them.

  12. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  13. The Koukopoulos Mixed Depression Rating Scale (KMDRS): An International Mood Network (IMN) validation study of a new mixed mood rating scale.

    Science.gov (United States)

    Sani, Gabriele; Vöhringer, Paul A; Barroilhet, Sergio A; Koukopoulos, Alexia E; Ghaemi, S Nassir

    2018-05-01

    It has been proposed that the broad major depressive disorder (MDD) construct is heterogenous. Koukopoulos has provided diagnostic criteria for an important subtype within that construct, "mixed depression" (MxD), which encompasses clinical pictures characterized by marked psychomotor or inner excitation and rage/anger, along with severe depression. This study provides psychometric validation for the first rating scale specifically designed to assess MxD symptoms cross-sectionally, the Koukopoulos Mixed Depression Rating Scale (KMDRS). 350 patients from the international mood network (IMN) completed three rating scales: the KMDRS, Montgomery-Asberg Depression Rating Scale (MADRS) and Young Mania Rating Scale (YMRS). KMDRS' psychometric properties assessed included Cronbach's alpha, inter-rater reliability, factor analysis, predictive validity, and Receiver Operator Curve analysis. Internal consistency (Cronbach's alpha = 0.76; 95% CI 0.57, 0.94) and interrater reliability (kappa = 0.73) were adequate. Confirmatory factor analysis identified 2 components: anger and psychomotor excitation (80% of total variance). Good predictive validity was seen (C-statistic = 0.82 95% CI 0.68, 0.93). Severity cut-off scores identified were as follows: none (0-4), possible (5-9), mild (10-15), moderate (16-20) and severe (> 21) MxD. Non DSM-based diagnosis of MxD may pose some difficulties in the initial use and interpretation of the scoring of the scale. Moreover, the cross-sectional nature of the evaluation does not verify the long-term stability of the scale. KMDRS was a reliable and valid instrument to assess MxD symptoms. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Labor Mobility, Social Network Effects, and Innovative Activity

    DEFF Research Database (Denmark)

    Kongsted, Hans Christian; Rønde, Thomas; Kaiser, Ulrich

    . This relationship is stronger if workers join from innovative firms. We also find evidence for positive feedback from workers who leave for an innovative firm, presumably because the worker who left stays in contact with their former colleagues. This implies that the positive feedback (“social network effects......”) that has been found by other studies not only exists but even outweighs the disruption and loss of knowledge occurring to the previous employer from the worker leaving. Summing up the effects of joining and leaving workers, we find ample evidence for mobility to be associated with an increase in total...

  15. Analyzing Reaction Rates with the Distortion/Interaction-Activation Strain Model

    NARCIS (Netherlands)

    Bickelhaupt, F. Matthias; Houk, Kendall N.

    2017-01-01

    The activation strain or distortion/interaction model is a tool to analyze activation barriers that determine reaction rates. For bimolecular reactions, the activation energies are the sum of the energies to distort the reactants into geometries they have in transition states plus the interaction

  16. HEART RATE AND PHYSICAL ACTIVITY PATTERNS IN PERSONS WITH PROFOUND INTELLECTUAL AND MULTIPLE DISABILITIES

    NARCIS (Netherlands)

    Waninge, Aly; van der Putten, Annette A. J.; Stewart, Roy E.; Steenbergen, Bert; van Wijck, Ruud; van der Schans, Cees P.

    2013-01-01

    Because physical fitness and health are related to physical activity, it is important to gain an insight into the physical activity levels of persons with profound intellectual and multiple disabilities (PIMD). The purpose of this study was to examine heart rate patterns to measure the activity

  17. Synaptic network activity induces neuronal differentiation of adult hippocampal precursor cells through BDNF signaling

    Directory of Open Access Journals (Sweden)

    Harish Babu

    2009-09-01

    Full Text Available Adult hippocampal neurogenesis is regulated by activity. But how do neural precursor cells in the hippocampus respond to surrounding network activity and translate increased neural activity into a developmental program? Here we show that long-term potential (LTP-like synaptic activity within a cellular network of mature hippocampal neurons promotes neuronal differentiation of newly generated cells. In co-cultures of precursor cells with primary hippocampal neurons, LTP-like synaptic plasticity induced by addition of glycine in Mg2+-free media for 5 min, produced synchronous network activity and subsequently increased synaptic strength between neurons. Furthermore, this synchronous network activity led to a significant increase in neuronal differentiation from the co-cultured neural precursor cells. When applied directly to precursor cells, glycine and Mg2+-free solution did not induce neuronal differentiation. Synaptic plasticity-induced neuronal differentiation of precursor cells was observed in the presence of GABAergic neurotransmission blockers but was dependent on NMDA-mediated Ca2+ influx. Most importantly, neuronal differentiation required the release of brain-derived neurotrophic factor (BDNF from the underlying substrate hippocampal neurons as well as TrkB receptor phosphorylation in precursor cells. This suggests that activity-dependent stem cell differentiation within the hippocampal network is mediated via synaptically evoked BDNF signaling.

  18. Throughput Maximization for Cognitive Radio Networks Using Active Cooperation and Superposition Coding

    KAUST Repository

    Hamza, Doha R.

    2015-02-13

    We propose a three-message superposition coding scheme in a cognitive radio relay network exploiting active cooperation between primary and secondary users. The primary user is motivated to cooperate by substantial benefits it can reap from this access scenario. Specifically, the time resource is split into three transmission phases: The first two phases are dedicated to primary communication, while the third phase is for the secondary’s transmission. We formulate two throughput maximization problems for the secondary network subject to primary user rate constraints and per-node power constraints with respect to the time durations of primary transmission and the transmit power of the primary and the secondary users. The first throughput maximization problem assumes a partial power constraint such that the secondary power dedicated to primary cooperation, i.e. for the first two communication phases, is fixed apriori. In the second throughput maximization problem, a total power constraint is assumed over the three phases of communication. The two problems are difficult to solve analytically when the relaying channel gains are strictly greater than each other and strictly greater than the direct link channel gain. However, mathematically tractable lowerbound and upperbound solutions can be attained for the two problems. For both problems, by only using the lowerbound solution, we demonstrate significant throughput gains for both the primary and the secondary users through this active cooperation scheme. We find that most of the throughput gains come from minimizing the second phase transmission time since the secondary nodes assist the primary communication during this phase. Finally, we demonstrate the superiority of our proposed scheme compared to a number of reference schemes that include best relay selection, dual-hop routing, and an interference channel model.

  19. Throughput Maximization for Cognitive Radio Networks Using Active Cooperation and Superposition Coding

    KAUST Repository

    Hamza, Doha R.; Park, Kihong; Alouini, Mohamed-Slim; Aissa, Sonia

    2015-01-01

    We propose a three-message superposition coding scheme in a cognitive radio relay network exploiting active cooperation between primary and secondary users. The primary user is motivated to cooperate by substantial benefits it can reap from this access scenario. Specifically, the time resource is split into three transmission phases: The first two phases are dedicated to primary communication, while the third phase is for the secondary’s transmission. We formulate two throughput maximization problems for the secondary network subject to primary user rate constraints and per-node power constraints with respect to the time durations of primary transmission and the transmit power of the primary and the secondary users. The first throughput maximization problem assumes a partial power constraint such that the secondary power dedicated to primary cooperation, i.e. for the first two communication phases, is fixed apriori. In the second throughput maximization problem, a total power constraint is assumed over the three phases of communication. The two problems are difficult to solve analytically when the relaying channel gains are strictly greater than each other and strictly greater than the direct link channel gain. However, mathematically tractable lowerbound and upperbound solutions can be attained for the two problems. For both problems, by only using the lowerbound solution, we demonstrate significant throughput gains for both the primary and the secondary users through this active cooperation scheme. We find that most of the throughput gains come from minimizing the second phase transmission time since the secondary nodes assist the primary communication during this phase. Finally, we demonstrate the superiority of our proposed scheme compared to a number of reference schemes that include best relay selection, dual-hop routing, and an interference channel model.

  20. Ratings of Sovereign Risk and the Macroeconomics Fundamentals of the countries: a Study Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Osvaldo Cândido da Silva Filho

    2009-05-01

    Full Text Available To minimize the consequences of asymmetric information, the sovereign risk ratings are instruments that constitute a key piece in the determination of credit market conditions, essential to the growth of developing countries like Brazil. In the present work we studied based on macroeconomics foundations, a classification to sovereign risk ratings realized by the ratings agencies finding the classification using Artificial Neural Networks. We observed homogeneity degree between the attributions of agencies and macroeconomics foundations in the countries of sample which four of foundations seem to be more directly connected with these attributions. After, in a comparative static exercise, we use the model to make simulations of scenarios of the credit external conditions for the Brazilian economy, changing the macroeconomics foundations which we noted that agencies expected for more per capita income increasing and decrease of public debt. (Full article in Portuguese only

  1. Combined Rate and Power Allocation with Link Scheduling in Wireless Data Packet Relay Networks with Fading Channels

    Directory of Open Access Journals (Sweden)

    Subhrakanti Dey

    2007-08-01

    Full Text Available We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal power, rate, and transmission time allocation at the wireless links. We further consider an optimal power allocation problem for multiple transmitting sources in the same framework. Performances of the resource allocation algorithms including the effect of buffer load control are illustrated via extensive simulation studies.

  2. The ATLAS Women's Network: one year of activities

    CERN Multimedia

    Paula Eerola

    The idea for an ATLAS Women's Network was born during the ATLAS overview week in October 2005, when a few of us discussed our experiences and were pondering about what we could do. We felt that it was important to increase the visibility of women working in ATLAS in order to make a better and more effective use of the ATLAS human resources, that is, make sure that women are duly included at all levels. Furthermore, it is our belief that making ATLAS a better working environment for female collaborators and other female co-workers will benefit both us and the collaboration as a whole. On the individual level, all of us thought that we could benefit from peer support and experience sharing, and an ATLAS Women's Network could facilitate this by developing contacts between the ATLAS Women in ATLAS Institutes worldwide. Finally, we thought that it was important to increase the number of women studying physics and working in the field of physics research by identifying gender barriers in the career paths of women i...

  3. Nuclear power plant maintenance optimisation SENUF network activity

    International Nuclear Information System (INIS)

    Ahlstrand, R.; Bieth, M.; Pla, P.; Rieg, C.; Trampus, P.

    2004-01-01

    During providing scientific and technical support to TACIS and PHARE nuclear safety programs a large amount of knowledge related to Russian design reactor systems has accumulated and led to creation of a new Network concerning Nuclear Safety in Central and Eastern Europe called ''Safety of Eastern European type Nuclear Facilities'' (SENUF). SENUF contributes to bring together all stakeholders of TACIS and PHARE: beneficiaries, end users, Eastern und Western nuclear industries, and thus, to favour fruitful technical exchanges and feedback of experience. At present the main focus of SENUF is the nuclear power plant maintenance as substantial element of plant operational safety as well as life management. A Working Group has been established on plant maintenance. One of its major tasks in 2004 is to prepare a status report on advanced strategies to optimise maintenance. Optimisation projects have an interface with the plant's overall life management program. Today, almost all plants involved in SENUF network have an explicit policy to extend their service life, thus, component ageing management, modernization and refurbishment actions became much more important. A database is also under development, which intends to help sharing the available knowledge and specific equipment and tools. (orig.)

  4. Nuclear power plant maintenance optimisation SENUF network activity

    Energy Technology Data Exchange (ETDEWEB)

    Ahlstrand, R.; Bieth, M.; Pla, P.; Rieg, C.; Trampus, P. [Inst. for Energy, EC DG Joint Research Centre, Petten (Netherlands)

    2004-07-01

    During providing scientific and technical support to TACIS and PHARE nuclear safety programs a large amount of knowledge related to Russian design reactor systems has accumulated and led to creation of a new Network concerning Nuclear Safety in Central and Eastern Europe called ''Safety of Eastern European type Nuclear Facilities'' (SENUF). SENUF contributes to bring together all stakeholders of TACIS and PHARE: beneficiaries, end users, Eastern und Western nuclear industries, and thus, to favour fruitful technical exchanges and feedback of experience. At present the main focus of SENUF is the nuclear power plant maintenance as substantial element of plant operational safety as well as life management. A Working Group has been established on plant maintenance. One of its major tasks in 2004 is to prepare a status report on advanced strategies to optimise maintenance. Optimisation projects have an interface with the plant's overall life management program. Today, almost all plants involved in SENUF network have an explicit policy to extend their service life, thus, component ageing management, modernization and refurbishment actions became much more important. A database is also under development, which intends to help sharing the available knowledge and specific equipment and tools. (orig.)

  5. Synaptic and intrinsic activation of GABAergic neurons in the cardiorespiratory brainstem network.

    Directory of Open Access Journals (Sweden)

    Julie G Frank

    Full Text Available GABAergic pathways in the brainstem play an essential role in respiratory rhythmogenesis and interactions between the respiratory and cardiovascular neuronal control networks. However, little is known about the identity and function of these GABAergic inhibitory neurons and what determines their activity. In this study we have identified a population of GABAergic neurons in the ventrolateral medulla that receive increased excitatory post-synaptic potentials during inspiration, but also have spontaneous firing in the absence of synaptic input. Using transgenic mice that express GFP under the control of the Gad1 (GAD67 gene promoter, we determined that this population of GABAergic neurons is in close apposition to cardioinhibitory parasympathetic cardiac neurons in the nucleus ambiguus (NA. These neurons fire in synchronization with inspiratory activity. Although they receive excitatory glutamatergic synaptic inputs during inspiration, this excitatory neurotransmission was not altered by blocking nicotinic receptors, and many of these GABAergic neurons continue to fire after synaptic blockade. The spontaneous firing in these GABAergic neurons was not altered by the voltage-gated calcium channel blocker cadmium chloride that blocks both neurotransmission to these neurons and voltage-gated Ca(2+ currents, but spontaneous firing was diminished by riluzole, demonstrating a role of persistent sodium channels in the spontaneous firing in these cardiorespiratory GABAergic neurons that possess a pacemaker phenotype. The spontaneously firing GABAergic neurons identified in this study that increase their activity during inspiration would support respiratory rhythm generation if they acted primarily to inhibit post-inspiratory neurons and thereby release inspiration neurons to increase their activity. This population of inspiratory-modulated GABAergic neurons could also play a role in inhibiting neurons that are most active during expiration and provide a

  6. Synaptic and intrinsic activation of GABAergic neurons in the cardiorespiratory brainstem network.

    Science.gov (United States)

    Frank, Julie G; Mendelowitz, David

    2012-01-01

    GABAergic pathways in the brainstem play an essential role in respiratory rhythmogenesis and interactions between the respiratory and cardiovascular neuronal control networks. However, little is known about the identity and function of these GABAergic inhibitory neurons and what determines their activity. In this study we have identified a population of GABAergic neurons in the ventrolateral medulla that receive increased excitatory post-synaptic potentials during inspiration, but also have spontaneous firing in the absence of synaptic input. Using transgenic mice that express GFP under the control of the Gad1 (GAD67) gene promoter, we determined that this population of GABAergic neurons is in close apposition to cardioinhibitory parasympathetic cardiac neurons in the nucleus ambiguus (NA). These neurons fire in synchronization with inspiratory activity. Although they receive excitatory glutamatergic synaptic inputs during inspiration, this excitatory neurotransmission was not altered by blocking nicotinic receptors, and many of these GABAergic neurons continue to fire after synaptic blockade. The spontaneous firing in these GABAergic neurons was not altered by the voltage-gated calcium channel blocker cadmium chloride that blocks both neurotransmission to these neurons and voltage-gated Ca(2+) currents, but spontaneous firing was diminished by riluzole, demonstrating a role of persistent sodium channels in the spontaneous firing in these cardiorespiratory GABAergic neurons that possess a pacemaker phenotype. The spontaneously firing GABAergic neurons identified in this study that increase their activity during inspiration would support respiratory rhythm generation if they acted primarily to inhibit post-inspiratory neurons and thereby release inspiration neurons to increase their activity. This population of inspiratory-modulated GABAergic neurons could also play a role in inhibiting neurons that are most active during expiration and provide a framework for

  7. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network.

    Science.gov (United States)

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-10-13

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods.

  8. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network

    Science.gov (United States)

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-01-01

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods. PMID:27754386

  9. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network

    Directory of Open Access Journals (Sweden)

    Peng Jiang

    2016-10-01

    Full Text Available Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB and a Lowest False Positive criterion (LFP, for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods.

  10. Social network activation: the role of health discussion partners in recovery from mental illness.

    Science.gov (United States)

    Perry, Brea L; Pescosolido, Bernice A

    2015-01-01

    In response to health problems, individuals may strategically activate their social network ties to help manage crisis and uncertainty. While it is well-established that social relationships provide a crucial safety net, little is known about who is chosen to help during an episode of illness. Guided by the Network Episode Model, two aspects of consulting others in the face of mental illness are considered. First, we ask who activates ties, and what kinds of ties and networks they attempt to leverage for discussing health matters. Second, we ask about the utility of activating health-focused network ties. Specifically, we examine the consequences of network activation at time of entry into treatment for individuals' quality of life, social satisfaction, ability to perform social roles, and mental health functioning nearly one year later. Using interview data from the longitudinal Indianapolis Network Mental Health Study (INMHS, N = 171), we focus on a sample of new patients with serious mental illness and a group with less severe disorders who are experiencing their first contact with the mental health treatment system. Three findings stand out. First, our results reveal the nature of agency in illness response. Whether under a rational choice or habitus logic, individuals appear to evaluate support needs, identifying the best possible matches among a larger group of potential health discussants. These include members of the core network and those with prior mental health experiences. Second, selective activation processes have implications for recovery. Those who secure adequate network resources report better outcomes than those who injudiciously activate network ties. Individuals who activate weaker relationships and those who are unsupportive of medical care experience poorer functioning, limited success in fulfilling social roles, and lower social satisfaction and quality of life later on. Third, the evidence suggests that social networks matter above and

  11. Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

    Science.gov (United States)

    Bajaj, Sahil; Adhikari, Bhim Mani; Dhamala, Mukesh

    2013-01-01

    The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not 'entirely' at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural

  12. A microfluidic device for simultaneous measurement of viscosity and flow rate of blood in a complex fluidic network.

    Science.gov (United States)

    Jun Kang, Yang; Yeom, Eunseop; Lee, Sang-Joon

    2013-01-01

    Blood viscosity has been considered as one of important biophysical parameters for effectively monitoring variations in physiological and pathological conditions of circulatory disorders. Standard previous methods make it difficult to evaluate variations of blood viscosity under cardiopulmonary bypass procedures or hemodialysis. In this study, we proposed a unique microfluidic device for simultaneously measuring viscosity and flow rate of whole blood circulating in a complex fluidic network including a rat, a reservoir, a pinch valve, and a peristaltic pump. To demonstrate the proposed method, a twin-shaped microfluidic device, which is composed of two half-circular chambers, two side channels with multiple indicating channels, and one bridge channel, was carefully designed. Based on the microfluidic device, three sequential flow controls were applied to identify viscosity and flow rate of blood, with label-free and sensorless detection. The half-circular chamber was employed to achieve mechanical membrane compliance for flow stabilization in the microfluidic device. To quantify the effect of flow stabilization on flow fluctuations, a formula of pulsation index (PI) was analytically derived using a discrete fluidic circuit model. Using the PI formula, the time constant contributed by the half-circular chamber is estimated to be 8 s. Furthermore, flow fluctuations resulting from the peristaltic pumps are completely removed, especially under periodic flow conditions within short periods (T viscosity with respect to varying flow rate conditions [(a) known blood flow rate via a syringe pump, (b) unknown blood flow rate via a peristaltic pump]. As a result, the flow rate and viscosity of blood can be simultaneously measured with satisfactory accuracy. In addition, the proposed method was successfully applied to identify the viscosity of rat blood, which circulates in a complex fluidic network. These observations confirm that the proposed method can be used for

  13. A GA-based PID active queue management control design for TCP/IP networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-02-15

    In this paper, a genetic algorithm-based (GA-based) proportional-integral-derivative (PID) controller as an active queue manager for Internet routers is proposed to reduce packet loss and improve network utilization in TCP/IP networks. Based on the window-based nonlinear dynamics, the TCP network was modeled as a time-delayed system with a saturated input due to the limitations of packet-dropping probability and the effects of propagation delays in TCP networks. An improved genetic algorithm is employed to derive optimal or near optimal PID control gains such that a performance index of integrated-absolute error (IAE) in terms of the error between the router queue length and the desired queue length is minimized. The performance of the proposed control scheme was evaluated in various network scenarios via a series of numerical simulations. The simulation results confirm that the proposed scheme outperforms other AQM schemes.

  14. A GA-based PID active queue management control design for TCP/IP networks

    International Nuclear Information System (INIS)

    Kuo, H-H; Chen, C-K; Liao, T-L; Yan, J-J

    2008-01-01

    In this paper, a genetic algorithm-based (GA-based) proportional-integral-derivative (PID) controller as an active queue manager for Internet routers is proposed to reduce packet loss and improve network utilization in TCP/IP networks. Based on the window-based nonlinear dynamics, the TCP network was modeled as a time-delayed system with a saturated input due to the limitations of packet-dropping probability and the effects of propagation delays in TCP networks. An improved genetic algorithm is employed to derive optimal or near optimal PID control gains such that a performance index of integrated-absolute error (IAE) in terms of the error between the router queue length and the desired queue length is minimized. The performance of the proposed control scheme was evaluated in various network scenarios via a series of numerical simulations. The simulation results confirm that the proposed scheme outperforms other AQM schemes

  15. Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity

    Directory of Open Access Journals (Sweden)

    Tanutama Lukas

    2014-03-01

    Full Text Available Companies increasingly rely on Internet for effective and efficient business communication. As Information Technology infrastructure backbone for business activities, corporate network connects the company to Internet and enables its activities globally. It carries data packets generated by the activities of the users performing their business tasks. Traditionally, infrastructure operations mainly maintain data carrying capacity and network devices performance. It would be advantageous if a company knows what activities are running in its network. The research provides a simple method of mapping the business activity reflected by the network data. To map corporate users’ activities, a slightly modified Attribute Oriented Induction (AOI approach to mine the network data was applied. The frequency of each protocol invoked were counted to show what the user intended to do. The collected data was samples taken within a certain sampling period. Samples were taken due to the enormous data packets generated. Protocols of interest are only Internet related while intranet protocols are ignored. It can be concluded that the method could provide the management a general overview of the usage of its infrastructure and lead to efficient, effective and secure ICT infrastructure.

  16. Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity

    Science.gov (United States)

    Tanutama, Lukas

    2014-03-01

    Companies increasingly rely on Internet for effective and efficient business communication. As Information Technology infrastructure backbone for business activities, corporate network connects the company to Internet and enables its activities globally. It carries data packets generated by the activities of the users performing their business tasks. Traditionally, infrastructure operations mainly maintain data carrying capacity and network devices performance. It would be advantageous if a company knows what activities are running in its network. The research provides a simple method of mapping the business activity reflected by the network data. To map corporate users' activities, a slightly modified Attribute Oriented Induction (AOI) approach to mine the network data was applied. The frequency of each protocol invoked were counted to show what the user intended to do. The collected data was samples taken within a certain sampling period. Samples were taken due to the enormous data packets generated. Protocols of interest are only Internet related while intranet protocols are ignored. It can be concluded that the method could provide the management a general overview of the usage of its infrastructure and lead to efficient, effective and secure ICT infrastructure.

  17. The efficacy of centralized flow rate control in 802.11-based wireless mesh networks

    KAUST Repository

    Jamshaid, K.; Ward, P.; Karsten, M.; Shihada, Basem

    2013-01-01

    predictably to congestion notification, can we enforce a desired rate allocation through a single centralized controller? The answer is not obvious because flows experience varying contention levels, and transmissions are scheduled by a node using imperfect

  18. Global synchronization of complex dynamical networks through digital communication with limited data rate.

    Science.gov (United States)

    Wang, Yan-Wu; Bian, Tao; Xiao, Jiang-Wen; Wen, Changyun

    2015-10-01

    This paper studies the global synchronization of complex dynamical network (CDN) under digital communication with limited bandwidth. To realize the digital communication, the so-called uniform-quantizer-sets are introduced to quantize the states of nodes, which are then encoded and decoded by newly designed encoders and decoders. To meet the requirement of the bandwidth constraint, a scaling function is utilized to guarantee the quantizers having bounded inputs and thus achieving bounded real-time quantization levels. Moreover, a new type of vector norm is introduced to simplify the expression of the bandwidth limit. Through mathematical induction, a sufficient condition is derived to ensure global synchronization of the CDNs. The lower bound on the sum of the real-time quantization levels is analyzed for different cases. Optimization method is employed to relax the requirements on the network topology and to determine the minimum of such lower bound for each case, respectively. Simulation examples are also presented to illustrate the established results.

  19. Real-time relationship between PKA biochemical signal network dynamics and increased action potential firing rate in heart pacemaker cells

    Science.gov (United States)

    Yaniv, Yael; Ganesan, Ambhighainath; Yang, Dongmei; Ziman, Bruce D.; Lyashkov, Alexey E.; Levchenko, Andre; Zhang, Jin; Lakatta, Edward G.

    2015-01-01

    cAMP-PKA protein kinase is a key nodal signaling pathway that regulates a wide range of heart pacemaker cell functions. These functions are predicted to be involved in regulation of spontaneous action potential (AP) generation of these cells. Here we investigate if the kinetics and stoichiometry of increase in PKA activity match the increase in AP firing rate in response to β-adrenergic receptor (β-AR) stimulation or phosphodiesterase (PDE) inhibition, that alter the AP firing rate of heart sinoatrial pacemaker cells. In cultured adult rabbit pacemaker cells infected with an adenovirous expressing the FRET sensor AKAR3, the EC50 in response to graded increases in the intensity of β-AR stimulation (by Isoproterenol) the magnitude of the increases in PKA activity and the spontaneous AP firing rate were similar (0.4±0.1nM vs. 0.6±0.15nM, respectively). Moreover, the kinetics (t1/2) of the increases in PKA activity and spontaneous AP firing rate in response to β-AR stimulation or PDE inhibition were tightly linked. We characterized the system rate-limiting biochemical reactions by integrating these experimentally derived data into mechanistic-computational model. Model simulations predicted that phospholamban phosphorylation is a potent target of the increase in PKA activity that links to increase in spontaneous AP firing rate. In summary, the kinetics and stoichiometry of increases in PKA activity in response to a physiological (β-AR stimulation) or pharmacological (PDE inhibitor) stimuli match those of changes in the AP firing rate. Thus Ca2+-cAMP/PKA-dependent phosphorylation limits the rate and magnitude of increase in spontaneous AP firing rate. PMID:26241846

  20. Determining Methane Leak Locations and Rates with a Wireless Network Composed of Low-Cost, Printed Sensors

    Science.gov (United States)

    Smith, C. J.; Kim, B.; Zhang, Y.; Ng, T. N.; Beck, V.; Ganguli, A.; Saha, B.; Daniel, G.; Lee, J.; Whiting, G.; Meyyappan, M.; Schwartz, D. E.

    2015-12-01

    We will present our progress on the development of a wireless sensor network that will determine the source and rate of detected methane leaks. The targeted leak detection threshold is 2 g/min with a rate estimation error of 20% and localization error of 1 m within an outdoor area of 100 m2. The network itself is composed of low-cost, high-performance sensor nodes based on printed nanomaterials with expected sensitivity below 1 ppmv methane. High sensitivity to methane is achieved by modifying high surface-area-to-volume-ratio single-walled carbon nanotubes (SWNTs) with materials that adsorb methane molecules. Because the modified SWNTs are not perfectly selective to methane, the sensor nodes contain arrays of variously-modified SWNTs to build diversity of response towards gases with adsorption affinity. Methane selectivity is achieved through advanced pattern-matching algorithms of the array's ensemble response. The system is low power and designed to operate for a year on a single small battery. The SWNT sensing elements consume only microwatts. The largest power consumer is the wireless communication, which provides robust, real-time measurement data. Methane leak localization and rate estimation will be performed by machine-learning algorithms built with the aid of computational fluid dynamics simulations of gas plume formation. This sensor system can be broadly applied at gas wells, distribution systems, refineries, and other downstream facilities. It also can be utilized for industrial and residential safety applications, and adapted to other gases and gas combinations.